BAKER CHIROPRACTIC OFFICE - DR. JOHN RAYMOND BAKER, D.C.- A DOCTOR IN TEXAS

JOB OPENING IN LONGVIEW TEXAS

2007-09-25T04:45:00.000-07:00

BAKER CHIROPRACTIC, PA , one of the friendliest Doctor's offices in Longview, has a position available right now for the right applicant. For details, please click
http://positionavailable.blogspot.com
If you are interested in getting into health care in a ground level position, contact Baker Chiropractic about this job opening.

repeal of treatment planning rule

2007-06-14T22:42:00.001-07:00

<MedicalBenefits@tdi.state.tx.us> 6/13/2007 7:15 PM >>>The Texas Department of Insurance, Division of Workers' Compensation has announced that repeals of two workers' compensation rules will be submitted to the Texas Register. The rules are the Prospective Review of Medical Care Not Requiring Preauthorization (PRM) rule and the Treatment Planning rule.The PRM rule is no longer needed due to the adoption of treatment guidelines for the workers' compensation system. To view the news release concerning PRM, please click on the following link: http://www.tdi.state.tx.us/wc/news/2007/news200776.html .The treatment planning rule was adopted last December as one of several disability management rules but the effective date was postponed due to concerns expressed by system participants. The repeal of the treatment planning rule will not affect the other disability management rules including those adopting treatment and return-to-work guidelines for Texas. To view the news release concerning treatment planning, please click on the following link:
http://www.tdi.state.tx.us/wc/news/2007/news200779.html ."June 12, 2007
TDI Will Change Disability Management Requirements
FOR IMMEDIATE RELEASEJune 12, 2007News Release
FOR MORE INFORMATIONJohn Greeley @ (512) 804-4202
Austin, TX – The Texas Department of Insurance (TDI) announced that a workers’ compensation rule to require treatment planning for injured employees (28 Texas Administrative Code §137.300) will be repealed. This rule was adopted along with other disability management rules in December, 2006. The effective date for treatment planning was postponed until September 1, 2007, however, as the agency attempted to address ongoing concerns from system participants.
A repeal of the treatment planning rule will be submitted to the Texas Register. Since the rule has not become effective, system participants will not be required to meet the rule’s requirements.
“System participants support the concept of treatment planning, but many also agree that implementation will require significant business and administrative process changes,” Commissioner of Workers’ Compensation Albert Betts said. “We were concerned that participants would not be able to initiate treatment planning without some lapses in care for injured employees.”
Dr. Howard Smith, Medical Advisor for TDI’s Division of Workers’ Compensation, said TDI plans to work with health care providers and insurance carriers on a treatment planning pilot program.
“This treatment planning pilot will allow us to identify opportunities for improved communication and efficient delivery of appropriate medical care,” Smith said.
Since publication of the adopted disability management rules, system participants expressed the need for additional time to establish processes to appropriately address required treatment planning. Participants also argued for additional time to communicate and develop treatment planning parameters that are mutually acceptable to health care providers and insurance carriers.
Disability management rules requiring the use of workers’ compensation treatment guidelines and return-to-work guidelines became effective May 1, 2007 and will remain in effect."

BAKER CHIROPRACTIC,PA - NOW ON TEXAS TRUE CHOICE

2007-06-13T11:25:00.000-07:00

Baker Chiropractic,PA is now on the list of providers for Texas True Choice Insurance, which is the health insurance covering city workers in Longview Texas.

So, if you are on Texas True Choice and need Chiropractic, please call 903-753-5400 to make an appointment to come in for an examination.

Thanks for visiting our site.

SOMBRA , BIOFREEZE, TENS UNITS

2007-05-16T04:32:00.000-07:00

Baker Chiropractic, PA not only is the place for excellent care in Longview Texas, but we also carry a line of products to ease your muscle spasm and pain.

We carry Sombra, a pepper based liniment which offers warm relief to pain.

We also carry soothing, cool biofreeze, the green gel that soothes those tense muscles.

We also carry Transcutaneous Electrical Muscle Stimulators for those patients treated at Baker Chiropractic who may need an alternative pain management method.

And last but certainly not least, we carry the fine therapeutic line of pillows from Mellow Out Spa , Inc.

Please come in at 1420 McCann St., Longview Texas, in the Brookwood Shopping Village, or call us at 903-753-5400.

http://bakerchiro.sprinterweb.net

2007-03-18T19:37:00.000-07:00

http://bakerchiro.sprinterweb.net

Biological Basis For Teenage Mood Swings Found

2007-03-12T11:24:00.000-07:00

From http://www.medicalnewstoday.com/healthnews.php?newsid=65035

A new US study has revealed that teenage mood swings may be explained by biological changes in the adolescent brain.

The research is published in the journal Nature Neuroscience.

Mood swings and anxiety, often caused by stress, are well known characteristics of puberty.

A physiologist at the State University of New York, Sheryl Smith, and her research colleagues experimented on female adolescent mice and showed that their brains respond to stress in a different way to adults and pre-pubescent individuals.

Anxiety is regulated by the brains's principal inhibitory neurotransmitter, GABA (gamma-amino-butyric-acid) which counteracts the effect of glutamate, an excitatory neurotransmitter in the brain's limbic system.

Stress causes the release of a steroid known as THP (allopregnanolone) which in adult and pre-pubescent individuals increases the "calming" effect of GABA in the limbic system. However, Smith and her team found that THP had the opposite effect in adolescent mice.

It would appear that THP has two roles, one in the limbic system where it helps to calm things down, and another in the hippocampus where in adolescents it hots things up. The hippocampus is important for emotion regulation.

This paradoxical role of THP, said Smith and her team, is the reason for the adolescent brain behaving differently.

The underlying mechanism appears to be different levels of expression of a type of receptor known as the "alpha4betadelta" GABAA receptor in the hippocampal brain region known as CA1.

In adults and pre-adolescents, the receptors are in low numbers so the overall effect of THP is a calming one.

However, in adolescents, the expression of these receptors is high, so for these individuals the anxiety raising effect of THP in the hippocampus outweighs the calming effect it has in the limbic system.

Smith and her team were able to reverse the puberty effect in the mice by genetically altering the number of receptors.

The net effect is that whatever the teenage person's reaction to stress is likely to be, whether to cry or be angry, it will be "amplified". While to adults it may seem like an overreaction, to the teenager it is the only thing they can do, said the researchers.

This study is thought to be the first to suggest an underlying physiological, as opposed to a behavioural-psychological explanation for teenage mood swing

TREATED BAD BY INSURANCE CARRIER ?

2007-03-10T06:33:00.000-08:00

I see injured workers every day. As a treating doctor, daily I am confronted with insurance carriers who deny, dispute, foot drag, and some, act in a way that may constitute "bad faith".

Patients get upset. But, how will things get changed? Patients who are unrepresented by attorneys, patients who cannot afford to hire attorneys specializing in Work Comp, but who are advised by ombudsman, often lose Benefits Review Conferences (BRC) and Contested Claims Hearings (CCH), and, after reading the decisions, I believe these folks ought NOT to have lost, because there is a preponderence of medical opinion in their favor.

Perhaps you alone cannot change the system, but I contend that if ENOUGH weight is brought to bear on the Department of Insurance about perceived wrongdoing by insurance carriers, and enough media people (television stations, radio, newspapers, bloggers) bring the issue to the public attention, there is certainly a stronger possibility that some positive changes will occur.

If no one complains, or not enough complain, the system will get worse and worse and worse.

Perhaps the easiest way to contact the Texas Department of Insurance, Work Comp division, is via e-mail WorkersComp@tdi.state.tx.us .

To write a snail mail letter of complaint :
Texas Department of Insurance
Division of Workers' Compensation
7551 Metro Center Drive
Suite 100
Austin, TX 78744-1609
You may also contact the Field Office nearest you

In probably the only time in history, Dr. John Raymond Baker,DC and the Texas Medical Association are in agreement

2007-03-09T15:00:00.000-08:00

There is the old saying about the enemy of my enemy is my friend. I just discovered that I and the TMA are in agreement about something. Both of us agree that Gardasil, also known as the "cervical cancer vaccine" (though that is a misnomer and it is not a vaccine against cervical cancer) should NOT be mandated by the state of Texas.

"Earlier this month, Gov. Rick Perry issued an executive order that made Texas the first state to mandate the vaccine for young girls. Perry said his goal was to protect future generations from cervical cancer, which afflicts 10,000 U.S. women a year.
Perry has been rebuked by social conservatives, who say his promotion of the vaccine condones pre-marital sex, and legislators who say he exceeded his constitutional powers by issuing the executive order.
The Texas Medical Association, too, has said that the vaccine shouldn't be mandated, citing, in part, the high cost of the three-shot regimen, which starts at $360."
-http://www.chron.com/disp/story.mpl/headline/metro/4588270.html

We must note that, as cited above, the cost of the three shot regimen STARTS at $360.00.
Now imagine if, as Gov. Perry would have it, every female child in a certain age range, would be mandated to take the shot. Can you say "millions of dollars for Merck". It just so happens, that the same day Gov Perry signed the executive order mandating the Merck medicine be given to girls...his "campaign" received a "contribution" of $5000.00.

Perry says it was just a "coincidence".

Yeah, and light hitting the head of my bed just "coincides" with the sun rising.

Get ready for Spring and Summer

2007-03-09T05:01:00.000-08:00

Well, the hours in the day are getting longer, the weather is getting warmer, and it won't be long before you will be getting active in the outdoors. If that knee or back or neck is holding you back, isn't it about time you had it seen about and got the kind of treatment to get you back to shape?

Call 903-753-5400 today and make an appointment with Dr. John Raymond Baker,DC .

Check out another news portal

2007-03-08T04:26:00.000-08:00

http://johnraymondbaker.php1h.com/mambo/

CLOSING DATES FOR CHRISTMAS

2006-12-20T08:46:00.000-08:00

BAKER CHIROPRACTIC, 1420 MCCANN ROAD, LONGVIEW TEXAS, WILL BE CLOSING AT ONE (1) PM ON FRIDAY, 22ND OF DECEMBER, AND WILL REOPEN ON WEDNESDAY, THE 27TH OD DECEMBER, 2006.

WE APPRECIATE EACH AND EVERY ONE OF OUR PATIENTS AND WISH EVERYONE, MERRY CHRISTMAS AND HAPPY HOLIDAYS, AND WISH YOU THE VERY HAPPIEST, HEALTHIEST, AND MOST JOYOUS SEASON.

DR. JOHN RAYMOND BAKER,DC AND STAFF OF BAKER CHIROPRACTIC, PA
903-753-5400

TAMMY GRADUATES WITH TWO ASSOCIATE DEGREES

2006-12-17T14:28:00.000-08:00

http://www.healingtexas.com/tammygraduates.rm

2006-12-17T14:20:00.000-08:00

HAPPY THANKSGIVING

2006-11-23T13:17:00.000-08:00

OUR OFFICE IS CLOSED IN HONOR OF THE HOLIDAYS THIS THURSDAY AND FRIDAY, THE 23RD AND 24TH OF NOVEMBER, BUT WE SHALL RETURN ON MONDAY.

MEDICAL ERRORS...MORE

2006-10-20T18:23:00.000-07:00

=============================================================

editor's note- Recently, as indicated here and elsewhere, in Texas, a CRAZY thing happened, well, more like, a horrible abuse of the legal system happened. The Texas Medical Association, which has no mandate to oversee any profession (The Texas Medical Board, http://www.tmb.state.tx.us/ oversees practice of medicine in Texas) , filed a lawsuit against the Texas Board of Chiropractic Examiners, claiming , among other things, that Chiropractic Doctors should not be allowed legally to diagnose their own patients. The Texas Meddlesome Assn...er..uh "Texas Medical ASSn" says they did so, in order to "protect citizens of Texas".

This is ridiculous to the point of absurdity.

If the Texas Meddlesome ASSn, or "Texas Medical Association" as they prefer to be called,
cares so much about protecting the public, perhaps they should clean up their OWN profession.
Please read the following article.

http://metasearch.com/

The Quality of Health Care

Medical Error and Patient Injury: Costly and Often Preventable

Research Report

Andrew H. Smith, AARP Public Policy Institute

September 1998

Table of Contents:

Public Perception of Patient Safety and Medical Error

Incidence of Medical Error and Injury

Drugs and Medical Injury

Costs Resulting from Medical Injury

Why Do Medical Errors Happen, and How Should the Problem Be Addressed?

Addressing the Problem from a Systems Approach

Current Efforts to Address Medical Error From a Systems Perspective

Conclusion

Footnotes

Patient injuries that result from preventable medical errors are widespread
and costly.¹
One recent study found that more than one in six hospitalized patients suffered
medical injuries that prolonged their hospital stays.²
It has been estimated that total annual costs associated with injuries resulting
from medical error may be as high as $200 billion, the equivalent of nearly one
out of every five dollars spent on health care in America.³
Estimates of the frequency of medical errors and injuries and the costs
associated with them vary considerably, but even the most conservative estimates
indicate that the problem is widespread, very costly, and requires serious
attention.⁴

Preventable medical error and injury are of particular concern for older
people because there is evidence that they are injured at a substantially higher
rate than patients in other age groups. As

Figure 1 indicates, patients age 65 and older experience medical injury two
to four times as often as patients in age groups under the age of 45, according
to a landmark study published in 1991, the most recent age-specific data
available.⁵
Advancing age was the only demographic characteristic -- not gender, race,
ethnicity, or income -- associated with a significantly increased incidence of
medical injury and of injury due to "negligence."⁶
The evidence suggests that costs associated with preventable medical error and
injury, both in terms of human suffering and dollars spent by the Medicare
program to treat injured beneficiaries, are very significant.

Public Perception of Patient Safety and
Medical Error

There is a substantial amount of public concern about patient safety.⁷
In a 1997 national survey, respondents rated the current health care system as
only "moderately safe" -- safer than nuclear power and food handling, but less
safe than airplane travel and the workplace.⁸
(See

Table 1.) Forty-two percent of those surveyed said that they had been
involved, either personally or through a friend or relative, in a situation
where a medical mistake was made. Fifty-two percent of respondents stated that
they were satisfied with the measures currently in place to prevent medical
mistakes, but a large minority, 42 percent, said they were not satisfied.⁹
Not surprisingly, most of those who reported that they were not satisfied with
current measures were those who had been involved in some way with a medical
mistake.¹⁰

Table 1. Perceived Safety of Various Environments
Environment	Mean Scores
Airline travel	5.2
Workplace	5.2
Health care	4.9
Food handling	4.4
Nuclear power	4.2
Scores: 7=Safe, 1=Unsafe. Source: National Patient Safety Foundation at the AMA, "Public Opinion of Patient Safety Issues." Survey conducted by Louis Harris & Associates, September 1997.

Incidence of Medical Error and Injury

As noted above, recent estimates of the incidence of medical errors resulting

in injuries¹¹
reach as high as 17.7 percent of hospitalizations.¹²
One important study of medical injury is the 1990 Harvard Medical Practice Study
(Harvard Study), a population-based study of injuries resulting from medical
care during hospitalizations in New York. This study found that nearly 4 percent
of patients suffered an injury that caused their hospital stays to be prolonged,
or resulted in measurable disability.¹³
The Harvard Study, which used reviews of medical records to detect medical
injuries, found that almost 14 percent of those identified as having suffered
medical injury died as a result of their injuries. If the rate of deaths
resulting from medical error identified by the Harvard Study in New York were
consistent with rates in the other 49 states, that would mean that 180,000
Americans die annually as a result of medical injuries.¹⁴
That figure would be comparable to the number of deaths that would occur if
three jumbo-jets crashed every two days,¹⁵
and is approximately four times the number of traffic fatalities that occur
annually in America.¹⁶

Consistent with other studies that have found that most medical injuries are
due to errors, the Harvard Study determined that 69 percent of the medical
injuries identified were due to error, and were, therefore, preventable.¹⁷

Studies conducted more recently indicate that medical injury may be
substantially more common than suggested in the Harvard Study. Using a method
more likely to capture incidents of medical error than the earlier study,
Andrews and her colleagues found that 17.7 percent of patients whose care was
observed experienced at least one serious adverse event per hospitalization.¹⁸
The frequency of medical injuries was linked to severity of illness and length
of hospital stay, with the likelihood of experiencing a medical injury
increasing by 6 percent per day of hospitalization. One or more causes¹⁹
of medical injuries were determined in just over one half of cases in the study.
In 37.8 percent of cases, the adverse events were found to have been caused by
an individual; 15.6 percent had interactive causes; and 9.8 percent were due to
administrative decisions. Although 17.7 percent of patients experienced medical
injuries that prolonged their hospital stays, the study found that only 1.2
percent filed claims for compensation for their injuries.

Drugs and Medical Injury

Drugs have been found to be among the most common causes of medical injury.
In the Harvard study, 19.4 percent of the injuries detected were related to the
use of drugs, while the Andrews study determined that 9.3 percent of injuries
were medication-related.²⁰

A large percentage of adverse drug events (ADEs) have serious consequences,
and many of them are preventable. Bates and his colleagues found that of all
ADEs identified in their study, 1 percent were fatal, 12 percent
life-threatening, 30 percent serious, and 57 percent significant. Of ADEs that
were determined to have been preventable, 20 percent were life- threatening, and
43 percent were serious. (See

Figure 2.) Overall, 28 percent of the ADEs were judged preventable, but of
life-threatening and serious ADEs, 42 percent were determined to have been
preventable.²¹
Bates found rates of 6.5 ADEs and 5.5 potential ADEs per 100 non-obstetrical
admissions to tertiary-care hospitals. Classen and colleagues found that adverse
drug events complicated 2.43 percent of hospital admissions, adding
significantly to length of hospital stays and to costs.²²

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of Page

Costs Resulting from Medical Injury

The costs associated with injuries resulting from medical error are quite
substantial. As noted above, one recent estimate placed the total costs
associated with medical injury at as much as $200 billion annually.²³

Most studies that attempt to estimate costs associated with medical error
have focused on injuries resulting from the use or misuse of medications. In
their 1995 study, Johnson and Bootman estimated that costs associated with
drug-related illness and death that resulted primarily from patient
non-compliance, and inappropriate prescribing, and/or monitoring by health care
professionals equal $76.6 billion annually.²⁴
The costs calculated for drug-related illness and death were limited to those
that arose from medication use or misuse in an outpatient setting, with the
largest component of costs resulting from drug-related hospitalizations.²⁵

The ADEs identified in the Classen study, half of which were identified as
preventable, added 1.91 days to the mean length of hospital stays and resulted
in increased costs per stay of $2,262.²⁶

In a follow up to their earlier study, Bates and colleagues determined that
an additional 2.2 days of hospitalization were required for patients
experiencing an ADE, at an average added cost of $3,244. For ADEs identified as
preventable, patients stayed in the hospital an average of 4.6 extra days, at an
average additional cost of $5,857.²⁷

Why Do Medical Errors Happen, and How Should the
Problem Be Addressed?

1. Negligent and/or incompetent providers

As a recent survey reveals, many people believe that medical errors and
injuries occur because there are just too many "bad doctors" and other health
care professionals performing in a negligent manner.²⁸
Medical injury is viewed as primarily the result of allowing incompetent and/or
careless providers to continue in the practice of medicine, and of hospital
under-staffing and other cost-cutting practices.²⁹
It has frequently been observed that relatively few providers are sanctioned by
the medical profession and/or state entities charged with enforcing standards of
medical practice despite evidence of widespread negligence.³⁰

Those who believe that medical negligence and an ineffective oversight system
are largely responsible for medical error and injury have responded in a number
of ways. For example, they promoted the development and use of a practitioner
databank. As a result, the National Practitioner Data Bank (NPDB) was created.
The NPDB collects and releases information (to authorized entities) relating to
medical malpractice payments, adverse licensure actions, certain types of
professional review actions, and reports of Medicare and Medicaid sanctions
taken against physicians, dentists, and some other health care practitioners.³¹
They have also defended the laws that govern medical malpractice actions against
a strong effort from the medical community to enact legal reforms that would
curtail malpractice litigation.³²

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2. Inevitable human error and systems failures

A contrasting view holds that the problem of medical error and injury results
primarily from systems failures. Proponents of this view acknowledge that there
are incompetent and impaired providers who commit errors that result in patient
injury, and that few physicians face disciplinary actions. However, they
observe, there is little evidence that negligence is the major cause of medical
error, or that rooting out negligent and incompetent providers would solve the
problem.

Those who subscribe to a "systems approach" to medical error, drawing on
psychological and human factors research, argue that human beings, no matter how
careful and conscientious they are, will make mistakes.³³
They also note that because the practice of medicine is complex, there are a
great many opportunities for mistakes to occur, and that the high level of
complexity makes it unrealistic to depend on promoting individual perfection as
the method to avoid mistakes that result in patient injury. For example, in one
study of an intensive care unit, it was determined that patients received an
average of 178 "activities" each day.³⁴
The average number of errors per patient per day was 1.7, or slightly less than
1 percent. Thus, the unit was functioning correctly 99 percent of the time.³⁵
Leape notes, however, that even an accuracy rate of 99.9 percent may not prove
adequate, noting that a 99.9 percent accuracy rate would translate to:

Two unsafe landings at O'Hare airport each day;

16,000 pieces of lost mail per hour; and

32,000 bank checks deducted from the wrong account every hour.³⁶

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of Page

Addressing the Problem from a Systems
Approach

One medical specialty, anesthesiology, has already made significant
improvements in its safety record. Mortality resulting from errors in anesthesia
has been reduced by 95 percent over the past 15 years.³⁷

Recognizing system factors, rather than carelessness or incompetence as the
most important causes of medical error, anesthesiologists designed fail-safe
systems and developed and implemented training programs to avoid errors.³⁸

The success story in anesthesiology illustrates the possibilities and
problems for other areas of medical practice. Errors and the resulting injuries
in anesthesiology, unlike those in many areas of medical practice, tend to be
dramatic and severe.³⁹
Information about incidents and the circumstances surrounding them were,
therefore, available to those attempting to understand the problems, and the
reasons the errors occurred were often transparent. These factors were conducive
to understanding the problems and developing approaches to correct them.

A number of scholars believe that the most important reason that medicine has
failed to develop more effective ways to prevent error is that, except in the
case of the practice of anesthesiology, there has been little opportunity to
study the reasons that errors occur. Information about medical error is
inadequate for researchers because most errors go unreported. Unlike errors in
anesthesiology, which, as noted above, cannot easily be hidden, errors occurring
in other areas of medical practice tend to be less frequently obvious and
dramatic in effect. In what some call medicine's culture of blame, there
is good reason not to volunteer information that an error has occurred when it
might otherwise remain undiscovered. In the medical culture, error cannot be
accepted; physicians are taught in medical school and during residency to learn
and practice error-free medicine, i.e., to be perfect. Error is treated
as a moral failing,⁴⁰
and it is not surprising that mistakes are driven "underground."

Advocates of the systems approach argue that, for medicine to enjoy the
success observed in anesthesiology, it is essential to overcome the barriers to
full reporting of medical errors. For researchers to devise ways to prevent
and/or to absorb⁴¹
errors and prevent injuries, they must learn precisely how and why errors and
their resulting injuries take place. They must have access to detailed and
comprehensive information on errors, and full information can be obtained only
if there is full disclosure of errors.

Current Efforts to Address Medical Error
From a Systems Perspective

A number of initiatives have been developed to study and address the problem
of medical error using a systems approach. Examples include:

The National Coordinating Council for Medication Error Reporting and
Prevention (NCC MERP), an organization of pharmacy and health care
professional groups, the U.S. Food and Drug Administration, the U.S.
Pharmacopoeia, and consumer organizations, among others, has developed
numerous recommendations to prevent medication errors. These recommendations,
addressed to pharmaceutical manufacturers, packagers and repackagers,
hospitals and hospital pharmacies, outpatient pharmacies, physicians and other
health care personnel, should lead to the safer use of drugs in all settings.
Among NCC MERP's recommendations: (1) print warnings only on caps and
ferrules of injectables; (2) make intravenous drug names visible on both sides
of the container; and (3) print drug names in type that is at least as large
as company names and logos.⁴²

The organization is also encouraging the use of its "Medication Error Index
for Categorizing Errors," a new indexing system that will help researchers to
track medication errors in a consistent, systematic manner.⁴³
Widespread use of the index should result in the efficient collection and
compilation of data on medication error, and thereby allow the development of
recommendations that could lessen the chance for patient injury.
The National Patient Safety Foundation at the AMA (NPSF) and the National
Patient Safety Partnership (NPSP) constitute two major initiatives to (1)
study medical error and (2) develop systems-based responses to reduce the
incidence of medical error and absorb errors when they do occur so that the
errors do not reach the patient.

The NPSF was founded by the American Medical Association in 1997, but is
now an independent foundation supported by a broad range of organizations,
including health care professional organizations, consumer organizations,
insurance companies, managed care organizations, and academicians. The NPSP
was founded by the U.S. Veterans Administration, and like the NPSF, has a
broad range of participating organizations. The NPSF and NPSP have recently
linked their efforts to promote research into the causes and cures for medical
error and injury. Among the projects they are working on together are:

(1) an effort to design a voluntary, confidential, non-punitive system
that would promote the reporting of essential data that would allow
researchers to learn the nature of systems failures that lead to injury; and

(2) a survey of health care providers and the medical culture as it
relates to patient safety.

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of Page

Conclusion

The systems approach has been successfully employed in non-health care
settings that are, like health care, high risk enterprises. Both the airline
industry's Aviation Safety Reporting System (ASRS) and the National Aeronautics
and Space Administration's (NASA) "Close-Call" reporting system were developed
through use of the systems approach.⁴⁴

As noted above, the success achieved in anesthesiology through the use of a
systems approach to improve patient safety strongly suggests that applying that
approach would be appropriate in other areas of medical practice. Before systems
changes to prevent medical error and patient injury can be devised and
implemented, the weaknesses in the complex systems of medical care that allow,
or even promote, medical errors must be identified and understood. A great deal
of research must be performed before the goal of substantially reducing rates of
preventable injury can be realized.

The systems approach promises significant reductions of preventable medical
error and injury in the future. It cannot, however, eliminate current and future
needs for patient compensation when a preventable injury does occur, despite
systems improvements. Neither can it adequately address errors/injuries that
arise from provider incompetence and/or impairment. Those are matters that must
continue to be addressed through legal and administrative mechanisms.

The work of the NPSF, NPSP, and NCC MERP, among other organizations, to
coordinate and support research and disseminate its results, should lead to
safer medical practice, fewer patient injuries, and reduced health care costs.
Success in preventing or absorbing medical error should prove beneficial to
Medicare beneficiaries, who most frequently suffer medical injuries, and could
save the Medicare program billions of dollars currently devoted to treating
preventable medical injuries.

Footnotes

¹ "Medical error" may be defined as "an unintended act (either of
omission or commission) or one that does not achieve its intended outcomes."
Leape, Lucien. "Error in Medicine." Journal of the American Medical
Association 272(23):1851-57 (Dec. 21, 1994).

² Andrews, Lori B., Carol
Stocking, Thomas Krizek, et al. "An Alternative Strategy for Studying Adverse
Events in Medical Care." Lancet 349:309-13 (Feb. 1, 1997).

³ Perrone, J. "Designing a Safer, Smarter Health Care System: AMA
Foundation Looks at Ways to Prevent Mistakes," American Medical News
40(40):1 (Oct. 27, 1997).

⁴ Reduction of medical error
is listed as one of "Six National Aims" in the Report of the President's
Advisory Commission on Consumer Protection and Quality in the Health Care
Industry (March 1998).

⁵ Patients, Doctors, and Lawyers: Medical Injury, Malpractice
Litigation, and Patient Compensation in New York. The Report of the Harvard
Medical Practice Study to the State of New York. Harvard Medical Practice
Study, 1990, 6-23.

⁶ Ibid.

⁷ "Public Opinion of Patient Safety Issues: Research Findings,"
National Patient Safety Foundation at the AMA, September 1997.

⁸ Ibid.

⁹ Ibid.

¹⁰ Ibid.

¹¹ "Medical injuries" here refer to "iatrogenic injuries," i.e.,
injuries or conditions resulting from treatment by physicians or surgeons.

¹² Andrews, et al. (1997).

¹³ Harvard Medical Practice Study (1990).

¹⁴ Leape (1994).

¹⁵ Ibid.

¹⁶ There were 43,910 deaths in 1997 resulting from motor vehicle
accidents. National Center for Health Statistics. "Births, Marriages, Divorces,
and Deaths for February 1997. Monthly Vital Statistics Report." 46: 2. (1997).

¹⁷ Leape (1994).

¹⁸ Andrews and her colleagues used a prospective, observational
approach that followed the care of all patients admitted over a period of time
to three units of a teaching hospital, as opposed to the Harvard Medical
Practice Study that used retrospective reviews of medical records. Andrews, et
al. (1997).

¹⁹ "Interactive causes" refers to "interactions between individuals,
or between individuals and hospital entities, or between hospital entities, such
as the failure of a consultant team to communicate adequately with the
requesting team." Andrews, et al. (1997) at p. 311.

²⁰ Harvard Medical Practice
Study (1990).

²¹ Bates, David W., David J. Cullen, Nan Laird, et al. "Incidence of
Adverse Drug Events and Potential Adverse Drug Events: Implications for
Prevention." Journal of the American Medical Association 274(1): 29-34
(July 5, 1995).

²² Classen,, David C., Stanley L. Pestotnik, R. Scott Evans, et. al.
Adverse Drug Events in Hospitalized Patients," Journal of the American
Medical Association 277(4):301-06 (Jan. 22/29, 1997).

²³ Perrone (1997).

²⁴ Johnson, Jeffrey A. and J. Lyle Bootman. "Drug-Related Morbidity
and Mortality: A Cost-of-Illness Model," Archives of Internal Medicine
155:1949-56 (Oct. 6, 1995). This estimate includes all types of medication
error, both preventable and non-preventable. It does not include costs
associated with injuries that are the result of unforseeable
allergic/idiosyncratic responses or those that occur when the provider knows
that there are risks associated with a drug but prescribes it anyway because, in
his/her judgment, the potential benefits outweigh the risks.

²⁵ When indirect costs due to non-compliance are added to the direct
cost figures, total economic costs rise to approximately $100 billion. Berg, J.S.,
J. Dischler, J.J. Raia, and N. Palmer-Shevlin, "Medication Compliance: A
Healthcare Problem," Annals of Pharmacotherapy 27(9):S3-S22 (1993).

²⁶ Ibid.

²⁷ Bates, David W., Nathan Spell, David J. Cullen, et al. "The Costs
of Adverse Drug Events in Hospitalized Patients," Journal of the American
Medical Association 277(4):307-11 (Jan. 22/29, 1997).

²⁸ See Richards, Edward P. and Katharine C. Rathbun, Law and the
Physician: A Practical Guide. Little, Brown, and Co.:New York (1996).

²⁹ Ibid.

³⁰ See, for example, Public Citizen, "16,638 Questionable Doctors."
(March 1998). It is noted that, although there have been more disciplinary
actions taken against physicians recently, few have been required to stop
practicing medicine, even for a short time. In 1996, 16,638 physicians were
disciplined by state boards or federal agencies. The rate of "serious
disciplinary actions" was 3.96 per 1,000 doctors (2,731 actions).

³¹ Title IV of the Health Care Quality Improvement Act of 1986 (P.L.
99-660) established the National Practitioner Data Bank (NPDB). Regulations
governing the NPDB may be found at 45 CFR Part 60. The information in the NPDB
is available only to state licensing boards, hospitals and other health care
entities, professional societies, certain Federal agencies, and others as
specified in the law. Only hospitals are mandated by law to query the Data Bank.

³² Nonetheless, many states passed "tort reform" measures in the wake
of the alleged medical malpractice insurance crisis of the late 1980s. They
included such measures as placing caps on possible damage awards (particularly
on awards for "pain and suffering"), restrictions on statutes of limitations,
limitations of plaintiff attorneys' fees, and other measures to discourage
potential complainants from filing malpractice actions.

³³ For a brief overview of relevant developments in cognitive
psychology and human factors research, see Leape, p. 1853 (1994).

³⁴ An "activity" is defined as any interaction between health care
personnel and patients that presents an opportunity for an adverse patient
outcome.

³⁵ Leape (1994).

³⁶ W.E. Deming, written communication quoted in Leape (1994).

³⁷ Orkin, P.K. "Patient Monitoring During Anesthesia as an Exercise
in Technology Assessment." In Saidman, L. J. and N.T. Smith, eds. Monitoring in
Anesthesia 3rd Ed. London, England: Butterworth Publishers, Inc. (1993).

³⁸ See Gaba, D.M., "Human Errors in Anesthetic Mishaps,"
International Anesthesiology Clinics 27(3):137-47 (Fall 1989). Also see
Cooper, J.B., R.S. Newbower, and P.J. Kitz, "An Analysis of Major Errors and
Equipment Failures in Anesthesia Management: Considerations for Prevention and
Detection," Anesthesiology 60(1):34-42 (Jan. 1984).

³⁹ Leape, p. 1856 (1994).

⁴⁰ Ibid.

⁴¹ It is recognized that errors are inevitable in any human endeavor,
including the provision of health care. Error "absorption" refers to the notion
that well-designed error prevention systems will "absorb" errors, keeping them
from reaching the patient and causing injury.

⁴² See U.S.P., "Medications Errors Council Recommends Changes to
Medical Product Packaging and Labeling," The Standard (Sep. 16, 1997).

⁴³ U.S.P., "Medication Errors Council Promotes Categorization Index,"
The Standard (October 1996).

⁴⁴ See Helmreich, R.L. "Managing Human Error in Aviation,"
Scientific American 276(5):62-67 (May 1997).

Top
of Page

Written by Drew Smith, AARP Public Policy Institute

September 1998

©1998 AARP

May be copied only for noncommercial purposes and with attribution; permission
required for all other purposes.

Public Policy Institute, AARP, 601 E Street, NW, Washington, DC 20049

ABSTRACT OF THE HARVARD MEDICAL PRACTICE STUDY

2006-10-19T20:56:00.000-07:00

Brennan T, Leape L, Laird N, Hebert L, Localio A, Lawthers A, et al. Incidence of adverse events and negligence in hospitalized patients: results of the Harvard Medical Practice Study I. N Engl J Med 1991;324:370-6.[Abstract]

Abstract

BACKGROUND. As part of an interdisciplinary study of medical injury and malpractice litigation, we estimated the incidence of adverse events, defined as injuries caused by medical management, and of the subgroup of such injuries that resulted from negligent or substandard care. METHODS. We reviewed 30,121 randomly selected records from 51 randomly selected acute care, nonpsychiatric hospitals in New York State in 1984. We then developed population estimates of injuries and computed rates according to the age and sex of the patients as well as the specialties of the physicians. RESULTS. Adverse events occurred in 3.7 percent of the hospitalizations (95 percent confidence interval, 3.2 to 4.2), and 27.6 percent of the adverse events were due to negligence (95 percent confidence interval, 22.5 to 32.6). Although 70.5 percent of the adverse events gave rise to disability lasting less than six months, 2.6 percent caused permanently disabling injuries and 13.6 percent led to death. The percentage of adverse events attributable to negligence increased in the categories of more severe injuries (Wald test chi 2 = 21.04, P less than 0.0001). Using weighted totals, we estimated that among the 2,671,863 patients discharged from New York hospitals in 1984 there were 98,609 adverse events and 27,179 adverse events involving negligence. Rates of adverse events rose with age (P less than 0.0001). The percentage of adverse events due to negligence was markedly higher among the elderly (P less than 0.01). There were significant differences in rates of adverse events among categories of clinical specialties (P less than 0.0001), but no differences in the percentage due to negligence. CONCLUSIONS. There is a substantial amount of injury to patients from medical management, and many injuries are the result of substandard care.

SO MANY MEDICAL ERRORS...SO LITTLE TIME

2006-10-19T20:41:00.000-07:00

Since the Texas Medical Association set themselves
up to decide what is safe and what is not, and to pursue a course of suing the
Board of Chiropractic Examiners in Texas because they don't think Chiropractic
Doctors should be able to diagnose their patients, I thought I should look more
into the Medical Doctor's side of safety, since the pretext of the lawsuit by
the TMA was "protecting the safety of Texas citizens" (my interpretation of
their assertion).

There are so MANY errors committed by Medical
doctors, that a government page is setup to classify them.

A	Back to Top

Active Error (or Active Failure) – The terms
"active" and "latent" as applied to
errors were coined by
James Reason.(1 ,2)
Active errors occur at the point of contact between a human and some aspect of a
larger system (eg, a human-machine interface). They are generally readily
apparent (eg, pushing an incorrect button, ignoring a warning light) and almost
always involve someone at the frontline.
Latent errors (or
latent conditions), in contrast, refer to less apparent failures of
organization or design that contributed to the occurrence of errors or allowed
them to cause harm to patients.

Active failures are sometimes referred to as errors at the "sharp
end," figuratively referring to a scalpel. In other words, errors at the
sharp end are noticed first because they are committed by the person closest to
the patient. This person may literally be holding a scalpel (eg, an orthopedist
who operates on the wrong leg) or figuratively be administering any kind of
therapy (eg, a nurse programming an intravenous pump) or performing any aspect
of care. To complete the metaphor, latent errors are those at the other end of
the scalpel—the "blunt
end"—referring to the many layers of the health care system that affect the
person "holding" the scalpel.

1. Reason JT. Human Error. New York, NY: Cambridge University Press; 1990. [
go
to PSNet listing ]

2. Reason J. Human error: models and management. BMJ. 2000;320:768-770. [

go to PubMed ]

Adverse Drug Event (ADE) – An adverse event involving medication use.

Examples:

anaphylaxis to penicillin

major hemorrhage from heparin

aminoglycoside-induced renal failure

agranulocytosis from chloramphenicol

As with the more general term
adverse event,
there is no necessary relation to error or poor quality of care. In other words,
ADEs include expected adverse drug reactions (or "side effects") defined below,
as well as events due to error.

Thus, a serious allergic reaction to penicillin in a patient with no prior such
history is an ADE, but so is the same reaction in a patient who does have a
known allergy history but receives penicillin due to a prescribing oversight.

Ignoring the distinction between expected medication side effects and ADEs due
to errors may seem misleading, but a similar distinction can be achieved with
the concept of preventability. All ADEs due to error are preventable, but other
ADEs not warranting the label
error may also be
preventable.

Adverse Drug Reaction – Adverse effect produced by the use of a
medication in the recommended manner. These effects range from "nuisance
effects" (eg, dry mouth with anticholinergic medications) to severe reactions,
such as anaphylaxis to penicillin.

Adverse Event – Any injury caused by medical care.

Examples:

pneumothorax from central venous catheter placement

anaphylaxis to penicillin

postoperative wound infection

hospital-acquired delirium (or "sun downing") in elderly patients

Identifying something as an adverse event does not imply "error,"
"negligence," or poor quality care. It simply indicates that an undesirable
clinical outcome resulted from some aspect of diagnosis or therapy, not an
underlying disease process.

Thus, pneumothorax from central venous catheter placement counts as an adverse
event regardless of insertion technique. Similarly, postoperative wound
infections count as adverse events even if the operation proceeded with optimal
adherence to sterile procedures, the patient received appropriate antibiotic
prophylaxis in the peri-operative setting, and so on. (See also
iatrogenic)

Anchoring Error (or Bias) — Refers to the common
cognitive trap of allowing first impressions to exert undue influence on the
diagnostic process. Clinicians often latch on to features of a patient's
presentation that suggest a specific diagnosis. Often, this initial diagnostic
impression will prove correct, hence the use of the phrase "anchoring heuristic"
in some contexts, as it can be a useful rule of thumb to "always trust your
first impressions." However, in some cases, subsequent developments in the
patient's course will prove inconsistent with the first impression. Anchoring
bias refers to the tendency to hold on to the initial diagnosis, even in the
face of disconfirming evidence.

1. Redelmeier DA. Improving patient care. The cognitive psychology of missed
diagnoses. Ann Intern Med. 2005;142:115-120.

[go to PubMed]

2. Croskerry P. Cognitive forcing strategies in clinical decisionmaking. Ann
Emerg Med. 2003;41:110-120.

[go to PubMed]

3. Croskerry P. The importance of cognitive errors in diagnosis and strategies
to minimize them. Acad Med. 2003;78:775-780.

[go to PubMed]

APACHE –The Acute Physiologic and Chronic Health Evaluation (APACHE)
scoring system has been widely used in the United States. APACHE II is the most
widely studied version of this instrument (a more recent version, APACHE III, is
proprietary, whereas APACHE II is publicly available); it derives a severity
score from such factors as underlying disease and chronic health status.(1,2)
Other points are added for 12 physiologic variables (ie, hematocrit, creatinine,
Glasgow Coma Score, mean arterial pressure) measured within 24 hours of
admission to the ICU. The APACHE II score has been validated in several studies
involving tens of thousands of ICU patients.

1. Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of
disease classification system. Crit Care Med. 1985;13:818-29.[

go to PubMed ]

2. Knaus WA, Wagner DP, Zimmerman JE, Draper EA. Variations in mortality and
length of stay in intensive care units. Ann Intern Med. 1993;118:753-61.[

go to PubMed ]

Authority Gradient – Refers to the balance of decision-making power or
the steepness of command hierarchy in a given situation. Members of a crew or
organization with a domineering, overbearing, or dictatorial team leader
experience a steep authority gradient. Expressing concerns, questioning, or even
simply clarifying instructions would require considerable determination on the
part of team members who perceive their input as devalued or frankly unwelcome.

Most teams require some degree of authority gradient; otherwise roles are
blurred and decisions cannot be made in a timely fashion. However, effective
team leaders consciously establish a command hierarchy appropriate to the
training and experience of team members.

Authority gradients may occur even when the notion of a team is less well
defined. For instance, a pharmacist calling a physician to clarify an order may
encounter a steep authority gradient, based on the tone of the physician's voice
or a lack of openness to input from the pharmacist. A confident, experienced
pharmacist may nonetheless continue to raise legitimate concerns about an order,
but other pharmacists might not.

Availability Bias (or Heuristic) — Refers to the tendency to assume, when
judging probabilities or predicting outcomes, that the first possibility that
comes to mind (ie, the most cognitively "available" possibility) is also the
most likely possibility. For instance, suppose a patient presents with
intermittent episodes of very high blood pressure. Because episodic hypertension
resembles textbook descriptions of pheochromocytoma, a memorable but uncommon
endocrinologic tumor, this diagnosis may immediately come to mind. A clinician
who infers from this immediate association that pheochromocytoma is the most
likely diagnosis would be exhibiting availability bias. In addition to
resemblance to classic descriptions of disease, personal experience can also
trigger availability bias, as when the diagnosis underlying a recent patient's
presentation immediately comes to mind when any subsequent patient presents with
similar symptoms. Particularly memorable cases may similarly exert undue
influence in shaping diagnostic impressions.

1. Redelmeier DA. Improving patient care. The cognitive psychology of missed
diagnoses. Ann Intern Med. 2005;142:115-120.

[go to PubMed]

2. Croskerry P. Cognitive forcing strategies in clinical decisionmaking. Ann
Emerg Med. 2003;41:110-120.

[go to PubMed]

3. Croskerry P. The importance of cognitive errors in diagnosis and strategies
to minimize them. Acad Med. 2003;78:775-780.

[go to PubMed]

B	Back to Top

Bayesian Approach – Probabilistic reasoning in which test results (not
just laboratory investigations, but history, physical exam, or any aspect for
the diagnostic process) are combined with prior beliefs about the probability of
a particular disease. One way of recognizing the need for a Bayesian approach is
to recognize the difference between the performance of a test in a population
vs. in an individual. At the population level, we can say that a test has a
sensitivity and specificity of, say, 90%—ie, 90% of patients with the condition
of interest have a positive result and 90% of patients without the condition
have a negative result. In practice, however, a clinician needs to attempt to
predict whether an individual patient with a positive or negative result does or
does not have the condition of interest. This prediction requires combining the
observed test result not just with the known sensitivity and specificity, but
also with the chance the patient could have had the disease in the first place
(based on demographic factors, findings on exam, or general clinical gestalt).

Benchmark – A "benchmark" in health care refers to an attribute or
achievement that serves as a standard for other providers or institutions to
emulate.

Benchmarks differ from other "standard of care" goals, in that they derive from
empiric data—specifically, performance or outcomes data. For example, a
statewide survey might produce risk-adjusted 30-day rates for death or other
major adverse outcomes. After adjusting for relevant clinical factors, the top
10% of hospitals can be identified in terms of particular outcome measures.
These institutions would then provide benchmark data on these outcomes. For
instance, one might benchmark "door-to-balloon" time at 90 minutes, based on the
observation that the top-performing hospitals all had door-to-balloon times in
this range.

In the present example regarding infection control, benchmarks would typically
be derived from national or regional data on the rates of relevant nosocomial
infections. The lowest 10% of these rates might be regarded as benchmarks for
other institutions to emulate.

The article below provides an excellent discussion of the principles of
benchmarking and the specific steps in using outcomes data to generate
benchmarks.

Kiefe CI, Weissman NW, Allison JJ, et al. Identifying achievable benchmarks of
care: concepts and methodology. Int J Qual Health Care. 1998;10:443-47. [

go to pubmed ]

Blunt End – The "blunt end" refers to the many layers of the health care
system not in direct contact with patients, but which influence the personnel
and equipment at the “sharp
end” who do contact patients. The blunt end thus consists of those who set
policy, manage health care institutions, design medical devices, and other
people and forces, which, though removed in time and space from direct patient
care, nonetheless affect how care is delivered.

Thus, an error programming an intravenous pump would represent a problem at the
sharp end, while the institution’s decision to use multiple different types of
infusion pumps, making programming errors more likely, would represent a problem
at the blunt end. The terminology of “sharp” and “blunt” ends corresponds
roughly to “active
failures” and “latent
conditions.”

C	Back to Top

Checklist – Algorithmic listing of actions to be performed in a given
clinical setting (eg, Acute Cardiac Life Support [ACLS] protocols for treating
cardiac arrest) to ensure that, no mater how often performed by a given
practitioner, no step will be forgotten. An analogy is often made to flight
preparation in aviation, as pilots and air-traffic controllers follow
pre-take-off checklists regardless of how many times they have carried out the
tasks involved.

Clinical Decision Support System (CDSS) – Any system designed to improve
clinical decision making related to diagnostic or therapeutic processes of care.
CDSSs thus address activities ranging from the selection of drugs (eg, the
optimal antibiotic choice given specific microbiologic data [1])
or diagnostic tests (2)
to detailed support for optimal drug dosing (3 ,4)
and support for resolving diagnostic dilemmas.(5)

Structured antibiotic order forms (6)
represent a common example of paper-based CDSSs. Although such systems are still
commonly encountered, many people equate CDSSs with computerized systems in
which software algorithms generate patient-specific recommendations by matching
characteristics, such as age, renal function, or allergy history, with rules in
a computerized knowledge base.

The distinction between decision support and simple reminders can be unclear,
but usually reminder systems are included as decision support if they involve
patient-specific information. For instance, a generic reminder (eg, “Did you
obtain an allergy history?”) would not be considered decision support, but a
warning (eg, “This patient is allergic to codeine.”) that appears at the time of
entering an order for codeine would be.

1. Evans RS, Pestotnik SL, Classen DC, et al. A computer-assisted management
program for antibiotics and other antiinfective agents. N Engl J Med.
1998;338:232-238.

[

go to PubMed ]

2. Harpole LH, Khorasani R, Fiskio J, Kuperman GJ, Bates DW. Automated
evidence-based critiquing of orders for abdominal radiographs: impact on
utilization and appropriateness. J Am Med Inform Assoc. 1997;4:511-521.

[

go to PubMed ]

3. Walton RT, Harvey E, Dovey S, Freemantle N. Computerised advice on drug
dosage to improve prescribing practice. Cochrane Database Syst Rev.
2001:CD002894.

[

go to PubMed ]

4. Chertow GM, Lee J, Kuperman GJ, et al. Guided medication dosing for
inpatients with renal insufficiency. JAMA. 2001;286:2839-2844.

[

go to PubMed ]

5. Friedman CP, Elstein AS, Wolf FM, et al. Enhancement of clinicians'
diagnostic reasoning by computer-based consultation: a multisite study of 2
systems. JAMA. 1999;282:1851-1856.

[

go to PubMed ]

6. Avorn J, Soumerai SB, Taylor W, Wessels MR, Janousek J, Weiner M.
Reduction of incorrect antibiotic dosing through a structured educational order
form. Arch Intern Med. 1988;148:1720-1724.

[

go to PubMed ]

Close Call – An event or situation that did not produce patient injury,
but only because of chance. This good fortune might reflect robustness of the
patient (eg, a patient with penicillin allergy receives penicillin, but has no
reaction) or a fortuitous, timely intervention (eg, a nurse happens to realize
that a physician wrote an order in the wrong chart). Such events have also been
termed "near miss"
incidents.

Competency – Having the necessary knowledge or technical skill to perform
a given procedure within the bounds of success and failure rates deemed
compatible with acceptable care.

Complexity Science (or Complexity Theory) - Provides an approach to
understanding the behavior of systems that exhibit non-linear dynamics, or the
ways in which some adaptive systems produce novel behavior not expected from the
properties of their individual components. Such behaviors emerge as a result of
interactions between agents at a local level in the complex system and between
the system and its environment.(1,2)

At first, this may sound indistinguishable from the “systems thinking” commonly
encountered in the patient safety literature. Some people probably use these
terms loosely and occasionally interchangeably, but complexity theory differs
importantly from systems thinking in its emphasis of the interaction between
local systems and their environment (such as the larger system in which a given
hospital or clinic operates). It is often tempting to ignore the larger
environment as unchangeable and therefore outside the scope of quality
improvement or patient safety activities. According to complexity theory,
however, behavior within a hospital or clinic (eg, non-compliance with a
national practice guideline) can often be understood only by identifying
interactions between local attributes and environmental factors.

Another key feature of complexity theory is the emphasis on achieving deep
understanding of a given problem prior to engaging in efforts to change
practice. For instance, instead of simply identifying that providers’ behavior
fails to comply with some target guideline and then implementing an “off the
shelf” means of achieving behavior change (eg, a financial incentive),
complexity theorists might identify what currently works well in a given
practice and the attitudes or structures that provide the basis for what works
well. This process may then reveal an important negative interaction between
local values and perceptions about the national guideline. A more effective
change strategy may then emerge in which the national guideline is adapted for
the local setting. The alternative approach of attempting to force behavioral
change may lead to no improvement or, worse, perverse collateral effects. This
phenomenon is certainly familiar when the complex adaptive system in question is
an ecosystem; complexity theorists advocate that we view health care systems
through a similar lens and not rush into change strategies, however plausible
they may seem. The two references below provide concrete examples to flesh out
the ideas of complexity theory and distinguish it from other major theories of
organizational behavior.(1,2)

1. Rhydderch M, Elwyn G, Marshall M, Grol R. Organisational change theory
and the use of indicators in general practice. Qual Saf Health Care.
2004;13:213-217.

[

go to PubMed ]

2. Plsek PE, Wilson T. Complexity, leadership, and management in healthcare
organisations. BMJ. 2001;323:746-749.

[

go to PubMed ]

Computerized Physician Order Entry or Computerized Provider Order Entry
(CPOE) – Refers to a computer-based system of ordering medications and often
other tests. Physicians (or other providers) directly enter orders into a
computer system that can have varying levels of sophistication. Basic CPOE
ensures standardized, legible, complete orders, and thus primarily reduces
errors due to poor handwriting and ambiguous abbreviations. Almost all CPOE
systems offer some additional capabilities, which fall under the general rubric
of Clinical Decision Support System (CDSS). Typical CDSS features involve
suggested default values for drug doses, routes of administration, or frequency.
More sophisticated CDSSs can perform drug allergy checks (eg, the user orders
ceftriaxone and a warning flashes that the patient has a documented penicillin
allergy), drug-laboratory value checks (eg initiating an order for gentamicin
prompts the system to alert you to the patient’s last creatinine), drug-drug
interaction checks, and so on. At the highest level of sophistication, CDSS
prevents not only errors of commission (eg, ordering a drug in excessive doses
or in the setting of a serious allergy), but also of omission. (For example, an
alert may appear such as, "You have ordered heparin; would you like to order a
PTT in 6 hours?" Or, even more sophisticated: "The admitting diagnosis is hip
fracture; would you like to order heparin DVT prophylaxis?")

Confirmation Bias - Refers to the tendency to focus on evidence that
supports a working hypothesis, such as a diagnosis in clinical medicine, rather
than to look for evidence that refutes it or provides greater support to an
alternative diagnosis.(1,2)
Suppose that a 65-year-old man with a past history of angina presents to the
emergency department with acute onset of shortness of breath. The physician
immediately considers the possibility of cardiac ischemia, so asks the patient
if he has experienced any chest pain. The patient replies affirmatively. Because
the physician perceives this answer as confirming his working diagnosis, he does
not ask if the chest pain was pleuritic in nature, which would decrease the
likelihood of an acute coronary syndrome and increase the likelihood of
pulmonary embolism (a reasonable alternative diagnosis for acute shortness of
breath accompanied by chest pain). The physician then orders an EKG and cardiac
troponin. The EKG shows nonspecific ST changes and the troponin returns slightly
elevated.

Of course, ordering an EKG and testing cardiac enzymes is appropriate in the
work-up of acute shortness of breath, especially when it is accompanied by chest
pain and in a patient with known angina. The problem is that these tests may be
misleading, since positive results are consistent not only with acute coronary
syndrome but also with pulmonary embolism. To avoid confirmation in this case,
the physician might have obtained an arterial blood glass or a D-dimer level.
Abnormal results for either of these tests would be relatively unlikely to occur
in a patient with an acute coronary syndrome (unless complicated by pulmonary
edema), but likely to occur with pulmonary embolism. These results could be
followed up by more direct testing for pulmonary embolism (eg, with a helical CT
scan of the chest), whereas normal results would allow the clinician to proceed
with greater confidence down the road of investigating and managing cardiac
ischemia.

This vignette was presented as if information were sought in sequence. In many
cases, especially in acute care medicine, clinicians have the results of
numerous tests in hand when they first meet a patient. The results of these
tests often do not all suggest the same diagnosis. The appeal of accentuating
confirmatory test results and ignoring nonconfirmatory ones is that it minimizes
cognitive dissonance.(3)

A related cognitive trap that may accompany confirmation bias and compound the
possibility of error is “anchoring
bias”—the tendency to stick with one’s first impressions, even in the face
of significant disconfirming evidence.

1. Croskerry P. The importance of cognitive errors in diagnosis and
strategies to minimize them. Acad Med. 2003;78:775-780.

[

go to PubMed ]

2. Redelmeier DA. Improving patient care. The cognitive psychology of missed
diagnoses. Ann Intern Med. 2005;142:115-120.

[

go to PubMed ]

3. Pines JM. Profiles in patient safety: confirmation bias in emergency
medicine. Acad Emerg Med. 2006;13:90-94.

[

go to PubMed ]

Crew Resource Management – Crew resource management (CRM), also called
crisis resource management in some contexts (eg, anesthesia), encompasses a
range of approaches to training groups to function as teams, rather than as
collections of individuals. Originally developed in aviation, CRM emphasizes the
role of "human factors"-the effects of fatigue, expected or predictable
perceptual errors (such as misreading monitors or mishearing instructions), as
well as the impact of different management styles and organizational cultures in
high-stress, high-risk environments.

CRM training develops communication skills, fosters a more cohesive environment
among team members, and creates an atmosphere in which junior personnel will
feel free to speak up when they think the something is amiss. Some CRM programs
emphasize education on the settings in which errors occur and the aspects of
team decision making conducive to "trapping" errors before they cause harm.
Other programs may provide more hands-on training involving simulated crisis
scenarios followed by debriefing sessions in which participants assess their own
and others' behavior.

Critical Incidents – A term made famous by a classic human factors study
by Cooper (1)
of “anesthetic mishaps,” though the term had first been coined in the 1950s.
Cooper and colleagues brought the technique of critical incident analysis to a
wide audience in health care but followed the definition of the originator of
the technique.(2)
They defined critical incidents as occurrences that are “significant or pivotal,
in either a desirable or an undesirable way,” though Cooper and colleagues (and
most others since) chose to focus on incidents that had potentially undesirable
consequences. This definition by itself conveys little—what does “significant or
pivotal” mean? It is best understood in the context of the type of investigation
that follows, which is very much in the style of
root cause
analysis. Thus, “significant or pivotal” means that there was significant
potential for harm (or actual harm), but also that the event has the potential
to reveal important hazards in the organization. In many ways, it is the spirit
of the expression in quality improvement circles, “every defect is a treasure.”(3)
In other words, these incidents, whether
close calls or
disasters in which significant harm occurred, provide valuable opportunities to
learn about individual and organizational factors that can be remedied to
prevent similar incidents in the future.

1. Cooper JB, Newbower RS, Long CD, McPeek B. Preventable anesthesia
mishaps: a study of human factors. Anesthesiology. 1978;49:399-406.

[

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2. Flanagan JC. The critical incident technique. Psychol Bull.
1954;51:327-358.

[

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3. James BC. Every defect a treasure: learning from adverse events in
hospitals. Med J Aust. 1997;166:484-487.

[

go to PubMed ]

D	Back to Top

Decision Support – Refers to any system for advising or providing
guidance about a particular clinical decision at the point of care. For example,
a copy of an algorithm for antibiotic selection in patients with community
acquired pneumonia would count as clinical decision support if made available at
the point of care. Increasingly, decision support occurs via a computerized
clinical information or order entry system. Computerized decision support
includes any software employing a knowledge base designed to assist clinicians
in decision making at the point of care.

Typically a decision support system responds to "triggers" or "flags"—specific
diagnoses, laboratory results, medication choices, or complex combinations of
such parameters—and provides information or recommendations directly relevant to
a specific patient encounter. For instance, ordering an aminoglycoside for a
patient with creatinine above a certain value might trigger a message suggesting
a dose adjustment based on the patient's decreased renal function.

E	Back to Top

Error – An act of commission (doing something wrong) or omission (failing
to do the right thing) that leads to an undesirable outcome or significant
potential for such an outcome. For instance, ordering a medication for a patient
with a documented allergy to that medication would be an act of commission.
Failing to prescribe a proven medication with major benefits for an eligible
patient (eg, low-dose unfractionated heparin as venous thromboembolism
prophylaxis for a patient after hip replacement surgery) would represent an
error of omission.

Errors of omission are more difficult to recognize than errors of commission but
likely represent a larger problem. In other words, there are likely many more
instances in which the provision of additional diagnostic, therapeutic, or
preventive modalities would have improved care than there are instances in which
the care provided quite literally should not have been provided. In many ways,
this point echoes the generally agreed-upon view in the health care quality
literature that underuse far exceeds overuse, even though the latter
historically received greater attention. (See definition for for
Underuse,
Overuse, Misuse.)

In addition to commission vs. omission, three other dichotomies commonly appear
in the literature on errors:
active failures
vs. latent conditions,
errors at the "sharp end"
vs. errors at the "blunt
end," and slips vs.
mistakes.

Error Chain – Error chain generally refers to the series of events that
led to a disastrous outcome, typically uncovered by a
root cause
analysis. Sometimes the chain metaphor carries the added sense of
inexorability, as many of the causes are tightly coupled, such that one problem
begets the next. A more specific meaning of error chain, especially when used in
the phrase break the error chain, relates to the common themes or categories of
causes that emerge from root cause analyses. These categories go by different
names in different settings, but they generally include (1) failure to follow
standard operating procedures (2) poor leadership (3) breakdowns in
communication or teamwork (4) overlooking or ignoring individual fallibility and
(5) losing track of objectives. Used in this way, break the error chain is
shorthand for an approach in which team members continually address these links
as a crisis or routine situation unfolds. The checklists that are included in
teamwork training programs have categories corresponding to these common links
in the error chain (e.g., establish team leader, assign roles and
responsibilities, monitor your teammates).

F	Back to Top

Face Validity – The extent to which a technical concept, instrument, or
study result is plausible, usually because its findings are consistent with
prior assumptions and expectations.

Failure Mode and Effect Analysis (FMEA) – Error analysis may involve
retrospective investigations (as in
Root Cause
Analysis) or prospective attempts to predict "error modes." Different
frameworks exist for predicting possible errors. One commonly used approach is
failure mode and effect analysis (FMEA), in which the likelihood of a particular
process failure is combined with an estimate of the relative impact of that
error to produce a "criticality index." By combining the probability of failure
with the consequences of failure, this index allows for the prioritization of
specific processes as quality improvement targets. For instance, an FMEA
analysis of the medication dispensing process on a general hospital ward might
break down all steps from receipt of orders in the central pharmacy to filling
automated dispensing machines by pharmacy technicians. Each step in this process
would be assigned a probability of failure and an impact score, so that all
steps could be ranked according to the product of these two numbers. Steps
ranked at the top (ie, those with the highest "criticality indices") would be
prioritized for error proofing.

Failure to Rescue – "Failure to rescue" is shorthand for failure to
rescue (ie, prevent a clinically important deterioration, such as death or
permanent disability) from a complication of an underlying illness (eg, cardiac
arrest in a patient with acute myocardial infarction) or a complication of
medical care (eg, major hemorrhage after thrombolysis for acute myocardial
infarction). Failure to rescue thus provides a measure of the degree to which
providers responded to adverse occurrences (eg, hospital-acquired infections,
cardiac arrest or shock) that developed on their watch. It may reflect the
quality of monitoring, the effectiveness of actions taken once early
complications are recognized, or both.

The technical motivation for using failure to rescue to evaluate the quality of
care stems from the concern that some institutions might document adverse
occurrences more assiduously than other institutions.(1,2)
Therefore, using lower rates of in-hospital complications by themselves may
simply reward hospitals with poor documentation. However, if the medical record
indicates that a complication has occurred, the response to that complication
should provide an indicator of the quality of care that is less susceptible to
charting bias.

Initial studies of mortality and complication rates after surgical procedures
indicated that lower rates of failure to rescue correlated with other plausible
quality measures.(1,2)
Rates of failure to rescue have since served as outcome measures in prominent
studies of the impacts of nurse-staffing ratios (3,4)
and nurse educational levels (5)
on the quality of care. Examples of the specific "rescue-able" adverse
occurrences in such studies include pneumonia, shock, cardiac arrest, upper
gastrointestinal bleeding, sepsis, and deep venous thrombosis.(4)
Death after any of these in-hospital occurrences would count as failure to
rescue, on the view that early identification by providers can influence the
risk of death.

The AHRQ technical report that developed the AHRQ Patient Safety Indicators (6)
reviews the evidence supporting failure to rescue as a measure of the quality
and safety of hospital care. Although failure to rescue made the final set of
approved indicators, the expert panels that reviewed each candidate indicator
identified some unresolved concerns about its use. For instance, patients with
advanced illnesses may be particularly difficult to rescue from complications
such as sepsis and cardiac arrest. Moreover, patients with advanced illness may
not wish "rescue" from such complications. The initial studies that examined
failure to rescue focused on surgical care, where these issues may not be as
problematic. Nonetheless, the concept of failure to rescue is an important one
and finds increasing application in studies of health care quality and safety.

1. Silber JH, Williams SV, Krakauer H, Schwartz JS. Hospital and patient
characteristics associated with death after surgery. A study of adverse
occurrence and failure to rescue. Med Care. 1992;30:615-629.

[

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2. Silber JH, Rosenbaum PR, Schwartz JS, Ross RN, Williams SV. Evaluation of
the complication rate as a measure of quality of care in coronary artery bypass
graft surgery. JAMA. 1995;274:317-323.

[

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3. Aiken LH, Clarke SP, Sloane DM, Sochalski J, Silber JH. Hospital nurse
staffing and patient mortality, nurse burnout, and job dissatisfaction. JAMA.
2002;288:1987-1993.

[

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4. Needleman J, Buerhaus P, Mattke S, Stewart M, Zelevinsky K.
Nurse-staffing levels and the quality of care in hospitals. N Engl J Med.
2002;346:1715-1722.

[

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5. Aiken LH, Clarke SP, Cheung RB, Sloane DM, Silber JH. Educational levels
of hospital nurses and surgical patient mortality. JAMA. 2003;290:1617-1623.

[

go to PubMed ]

6. McDonald KM, Romano PS, Geppert J, et al. Measures of Patient Safety
Based on Hospital Administrative Data—The Patient Safety Indicators. Rockville,
MD: Agency for Healthcare Research and Quality; 2002. AHRQ Publication No.
02-0038.

Available at:

http://www.ahrq.gov/clinic/evrptfiles.htm#psi.

Forcing Function – An aspect of a design that prevents a target action
from being performed or allows its performance only if another specific action
is performed first. For example, automobiles are now designed so that the driver
cannot shift into reverse without first putting her foot on the brake pedal.
Forcing functions need not involve device design. For instance, one of the first
forcing functions identified in health care is the removal of concentrated
potassium from general hospital wards. This action is intended to prevent the
inadvertent preparation of intravenous solutions with concentrated potassium, an
error that has produced small but consistent numbers of deaths for many years.

H	Back to Top

Health Literacy – Individuals' ability to find, process, and comprehend
the basic health information necessary to act on medical instructions and make
decisions about their health.(1)

1. Ad Hoc Committee on Health Literacy for the Council on Scientific Affairs
AMA. Health literacy: report of the Council on Scientific Affairs. JAMA.
1999;281:552-7. [

go to PubMed ]

Heuristic – Loosely defined or informal rule often arrived at through
experience or trial and error (eg, gastrointestinal complaints that wake
patients up at night are unlikely to be functional). Heuristics provide
cognitive shortcuts in the face of complex situations, and thus serve an
important purpose. Unfortunately, they can also turn out to be wrong.

The Health Insurance Portability and Accountability Act (HIPAA) – The
Health Insurance Portability and Accountability Act of 1996 (HIPAA) contains new
federal regulations intended to increase privacy and security of patient
information during electronic transmission or communication of "protected health
information" (PHI) among providers or between providers and payers or other
entities.

"Protected health information" (PHI) includes all medical records and other
individually identifiable health information. "Individually identifiable
information" includes data that explicitly linked to a patient as well as health
information with data items with a reasonable potential for allowing individual
identification.

HIPAA also requires providers to offer patients certain rights with respect to
their information, including the right to access and copy their records and the
right to request amendments to the information contained in their records.

Administrative protections specified by HIPAA to promote the above regulations
and rights include requirements for a Privacy Officer and staff training
regarding the protection of patients' information.

High Reliability Organizations (HROs) – High reliability organizations
refer to organizations or systems that operate in hazardous conditions but have
fewer than their fair share of adverse events. (1,2)
Commonly discussed examples include air traffic control systems, nuclear power
plants, and naval aircraft carriers. (3,4)
It is worth noting that, in the patient safety literature, HROs are considered
to operate with nearly failure-free performance records, not simply better than
average ones. This shift in meaning is somewhat understandable given that the
“failure rates” in these other industries are so much lower than rates of errors
and adverse events in health care. This comparison glosses over the difference
in significance of a “failure” in the nuclear power industry compared with one
in health care. The point remains, however, that some organizations achieve
consistently safe and effective performance records despite unpredictable
operating environments or intrinsically hazardous endeavors. Detailed case
studies of specific HROs have identified some common features, which have been
offered as models for other organizations to achieve substantial improvements in
their safety records. These features include:

Preoccupation with failure—the acknowledgment of the high-risk,
error-prone nature of an organization’s activities and the determination to
achieve consistently safe operations.

Commitment to resilience—the development of capacities to detect
unexpected threats and contain them before they cause harm, or bounce back
when they do.

Sensitivity to operations—an attentiveness to the issues facing workers at
the frontline. This feature comes into play when conducting analyses of
specific events (eg, frontline workers play a crucial role in root cause
analyses by bringing up unrecognized latent threats in current operating
procedures), but also in connection with organizational decision making, which
is somewhat decentralized. Management units at the frontline are given some
autonomy in identifying and responding to threats, rather than adopting a
rigid top-down approach.

A culture of
safety, in which individuals feel comfortable drawing attention to
potential hazards or actual failures without fear of censure from management.

1. Weick KE, Sutcliffe KM. Managing the Unexpected: Assuring High
Performance in an Age of Complexity. San Francisco, CA: Jossey-Bass; 2001.

2. Reason J. Human error: models and management. BMJ. 2000;320:768-770.

[

go to pubmed ]

3. LaPorte TR. The United States air traffic control system: increasing
reliability in the midst of rapid growth. In: Mayntz R, Hughes TP, eds. The
Development of Large Technical Systems. Boulder, CO: Westview Press; 1988.

4. Roberts KH. Managing high reliability organizations. Calif Manage Rev.
1990;32:101-113.

Hindsight Bias – In a very general sense, hindsight bias relates to the
common expression “hindsight is 20/20.” This expression captures the tendency
for people to regard past events as expected or obvious, even when, in real
time, the events perplexed those involved. More formally, one might say that
after learning the outcome of a series of events—whether the outcome of the
World Series or the steps leading to a war—people tend to exaggerate the extent
to which they had foreseen the likelihood of its occurrence.

In the context of safety analysis, hindsight bias refers to the tendency to
judge the events leading up to an accident as errors because the bad outcome is
known. The more severe the outcome, the more likely that decisions leading up to
this outcome will be judged as errors. Judging the antecedent decisions as
errors implies that the outcome was preventable. In legal circles, one might use
the phrase “but for,” as in “but for these errors in judgment, this terrible
outcome would not have occurred.” Such judgments return us to the concept of
“hindsight is 20/20.” Those reviewing events after the fact see the outcome as
more foreseeable and therefore more preventable than they would have appreciated
in real time.

Psychologist Baruch Fischhoff drew attention to the importance of this problem
in a classic paper published in 1975 (1),
since which time multiple examples of the impacts of this bias have been
explored in the psychology literature.

The impact of hindsight on judgments by peer reviewers regarding the quality of
clinical care in medicine has also been demonstrated.(2)
One of the case-based discussions in “Quality Grand Rounds,” published in
Annals of Internal Medicine, provides a detailed exploration of the extent
to which difficult decisions are cast as errors after an undesirable outcome
occurs.(3)

1. Fischhoff B. Hindsight ? foresight: the effect of outcome knowledge on
judgment under uncertainty [reprint of Fischhoff B. Hindsight does not equal
foresight: the effect of outcome knowledge on judgment under uncertainty. J of
Exp Psychol: Hum Perform and Perception. 1975;1:288–299.]. Qual Saf Health Care.
2003;12:304-112.

[

go to PubMed ]

2. Caplan RA, Posner K., Cheney FW. Effect of outcome on physician judgments
of appropriateness of care. JAMA. 1991;265:1957-1960.

[

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3. Hofer TP, Hayward RA. Are bad outcomes from questionable clinical
decisions preventable medical errors? A case of cascade iatrogenesis. Ann Intern
Med. 2002; 137:327-333.

[

go to PubMed ]

Human Factors (or Human Factors Engineering) – Refers to the study of
human abilities and characteristics as they affect the design and smooth
operation of equipment, systems, and jobs. The field concerns itself with
considerations of the strengths and weaknesses of human physical and mental
abilities and how these affect the systems design. Human factors analysis does
not require designing or redesigning existing objects. For instance, the now
generally accepted recommendation that hospitals standardize equipment such as
ventilators, programmable IV pumps, and defibrillators (ie, that each hospital
pick a single type, so that different floors do not have different
defibrillators) is an example of a very basic application of a
heuristic from
human factors that equipment be standardized within a system wherever possible.
In general, human factors engineering examines a particular activity in terms of
its component tasks and then considers each task in terms of: physical demands,
skill demands, mental workload, and other such factors, along with their
interactions with aspects of the work environment (eg, adequate lighting,
limited noise, or other distractions), device design, and team dynamics.

I	Back to Top

Iatrogenic – An adverse effect of medical care, rather than of the
underlying disease (literally "brought forth by healer," from Greek iatros, for
healer, and gennan, to bring forth); equivalent to
adverse event.

Incident Reporting – Refers to the identification of occurrences that
could have led, or did lead, to an undesirable outcome. Reports usually come
from personnel directly involved in the incident or events leading up to it (eg,
the nurse, pharmacist, or physician caring for a patient when a medication error
occurred) rather than, say, floor managers.

Incident reporting represents a species of the more general activity of
surveillance for errors, adverse events, or other quality problems. From the
perspective of those collecting the data, incident reporting counts as a
passive form of surveillance. It relies on those involved in target
incidents choosing to provide the desired information. More active
methods of surveillance range from activities such as going to gatherings of
frontline workers and asking if any recent incidents have occurred (1)
to retrospective medical record review (2)
to direct observation.(3)
Compared with medical record review and direct observation, incident reporting
captures only a fraction of incidents.(3 ,4)

Despite their low yield, spontaneous incident reporting systems have some
advantages, including their relatively low cost and the involvement of frontline
personnel in the process of identifying important problems for the organization.
The involvement of frontline workers, however, also raises the issue of
confidentiality. Because incident reports tend to come from personnel involved
in the incidents, these personnel may have legitimate concerns about the effects
reporting will have on their performance records. To encourage reporting, some
organizations make incident reporting anonymous. In other words, personnel can
report an incident without identifying themselves.

Absent anonymity, some incident reporting systems assure confidentiality
regarding the identity of individuals who submit reports. The Aviation Safety
Reporting System (http://asrs.arc.nasa.gov)
represents a confidential reporting system. As long as the persons reporting
incidents have not committed any breaches of professional conduct, their
identities remain in strict confidence and play no role in the investigations.

1. Weingart SN, Ship AN, Aronson MD. Confidential clinician-reported
surveillance of adverse events among medical inpatients. J Gen Intern Med.
2000;15:470-477.

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2. Bates DW, Cullen DJ, Laird N, et al. Incidence of adverse drug events and
potential adverse drug events. Implications for prevention. ADE Prevention Study
Group. JAMA. 1995;274:29-34.

[

go to PubMed ]

3. Flynn EA, Barker KN, Pepper GA, Bates DW, Mikeal RL. Comparison of
methods for detecting medication errors in 36 hospitals and skilled-nursing
facilities. Am J Health Syst Pharm. 2002;59:436-446.

[

go to PubMed ]

4. Cullen DJ, Bates DW, Small SD, Cooper JB, Nemeskal AR, Leape LL. The
incident reporting system does not detect adverse drug events: a problem for
quality improvement. Jt Comm J Qual Improv. 1995;21:541-548.

[

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Informed Consent – Refers to the process whereby a physician informs a
patient about the risks and benefits of a proposed therapy or test. Informed
consent aims to provide sufficient information about the proposed treatment and
any reasonable alternatives that the patient can exercise autonomy in deciding
whether to proceed.

Legislation governing the requirements of, and conditions under which, consent
must be obtained varies by jurisdiction. Most general guidelines require
patients to be informed of the nature of their condition, the proposed
procedure, the purpose of the procedure, the risks and benefits of the proposed
treatments, the probability of the anticipated risks and benefits, alternatives
to the treatment and their associated risks and benefits, and the risks and
benefits of not receiving the treatment or procedure.

Although the goals of informed consent are irrefutable, consent is often
obtained in a haphazard, pro forma fashion, with patients having little true
understanding of procedures to which they have consented. Evidence suggests that
asking patients to restate the essence of the informed consent improves the
quality of these discussions and makes it more likely that the consent is truly
"informed."

[
Procedures For Obtaining Informed Consent ]

J	Back to Top

Just Culture — The phrase “just culture” was popularized in the patient
safety lexicon by a report (1)
that outlined principles for achieving a culture in which frontline personnel
feel comfortable disclosing errors—including their own—while maintaining
professional accountability. The examples in the report relate to transfusion
safety, but the principles clearly generalize across domains within health care
organizations.

Traditionally, health care’s culture has held individuals accountable for all
errors or mishaps that befall patients under their care. By contrast, a just
culture recognizes that individual practitioners should not be held accountable
for system failings over which they have no control. A just culture also
recognizes many individual or “active”
errors represent predictable interactions between human operators and the
systems in which they work. However, in contrast to a culture that touts “no
blame” as its governing principle, a just culture does not tolerate conscious
disregard of clear risks to patients or gross misconduct (eg, falsifying a
record, performing professional duties while intoxicated).

In summary, a just culture recognizes that competent professionals make mistakes
and acknowledges that even competent professionals will develop unhealthy norms
(shortcuts, “routine rule violations”), but has zero tolerance for reckless
behavior.

1. Marx D. Patient Safety and the “Just Culture”: A Primer for Health Care
Executives. New York, NY: Columbia University; 2001. Available at:

http://www.mers-tm.net/support/marx_primer.pdf

L	Back to Top

Latent Error (or Latent Condition) – The terms "active" and "latent" as
applied to errors were
coined by James Reason.(1 ,2)
Latent errors (or latent conditions) refer to less apparent failures of
organization or design that contributed to the occurrence of errors or allowed
them to cause harm to patients. For instance, whereas the
active failure
in a particular adverse event may have been a mistake in programming an
intravenous pump, a latent error might be that the institution uses multiple
different types of infusion pumps, making programming errors more likely. Thus,
latent errors are quite literally "accidents waiting to happen."

Latent errors are sometimes referred to as errors at the "blunt
end," referring to the many layers of the health care system that affect the
person "holding" the scalpel. Active failures, in contrast, are sometimes
referred to as errors at the “sharp
end,” or the personnel and parts of the health care system in direct contact
with patients.

1. Reason JT. Human Error. New York, NY: Cambridge University Press; 1990.

[

go to PSNet listing ]

2. Reason J. Human error: models and management. BMJ. 2000;320:768-770.

[

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Learning Curve – The acquisition of any new skill is associated with the
potential for lower-than-expected success rates or higher-than-expected
complication rates. This phenomenon is often known as a "learning curve." In
some cases, this learning curve can be quantified in terms of the number of
procedures that must be performed before an operator can replicate the outcomes
of more experienced operators or centers.

While learning curves are almost inevitable when new procedures emerge or new
providers are in training, minimizing their impact is a patient safety
imperative. One option is to perform initial operations or procedures under the
supervision of more experienced operators. Surgical and procedural simulators
may play an increasingly important role in decreasing the impact of learning
curves on patients, by allowing acquisition of relevant skills in laboratory
settings.

M	Back to Top

Magnet Hospital Status – Refers to a designation by the Magnet Hospital
Recognition Program administered by the American Nurses Credentialing Center.
The program has its genesis in a 1983 study conducted by the American Academy of
Nursing that sought to identify hospitals that retained nurses for longer than
average periods of time. The study identified institutional characteristics
correlated with high retention rates, an important finding in light of a major
nursing shortage at the time.(1)
These findings provided the basis for the concept of “magnet hospital” and led
10 years later to the formal Magnet Program.

Without taking anything away from the particular hospitals that have achieved
Magnet status, the program as a whole has its critics. In fact, at least one
state nurses’ association (Massachusetts) has taken an official position
critiquing the program, charging that its perpetuation reflects the financial
interests of its sponsoring organization and the participating hospitals more
than the goals of improving health care quality or improving working conditions
for nurses.(2)

Regardless of the particulars of the Magnet Recognition Program and the lack of
persuasive evidence linking magnet status to quality, to many the term “magnet
hospital” connotes a hospital that delivers superior patient care and, partly on
this basis, attracts and retains high-quality nurses.

1. Magnet hospitals. Attraction and retention of professional nurses. Task
Force on Nursing Practice in Hospitals. American Academy of Nursing. ANA Publ.
1983;(G-160):i-xiv, 1-135.

[

go to PubMed ]

2. Position Statement On the "Magnet Recognition Program for Nursing
Services in Hospitals" and Other Consultant-Driven Quality Improvement Projects
that Claim to Improve Care [Massachusetts Nurses Association Web site]. November
2004.

Available at:

http://www.massnurses.org/pubs/positions/magnet.htm.

Medical Emergency Team – The concept of medical emergency teams (also
known as rapid response teams) is that of a cardiac arrest team with more
liberal calling criteria. Instead of just frank respiratory or cardiac arrest,
medical emergency teams respond to a wide range of worrisome, acute changes in
patients’ clinical status, such as low blood pressure, difficulty breathing, or
altered mental status. In addition to less stringent calling criteria, the
concept of medical emergency teams de-emphasizes the traditional hierarchy in
patient care in that anyone can initiate the call. Nurses, junior medical staff,
or others involved in the care of patients can call for the assistance of the
medical emergency team whenever they are worried about a patient’s condition,
without having to wait for more senior personnel to assess the patient and
approve the decision to call for help.

Medication Reconciliation — Patients admitted to a hospital commonly
receive new medications or have changes made to their existing medications. As a
result, the new medication regimen prescribed at the time of discharge may
inadvertently omit needed medications that patients have been receiving for some
time.(1) Alternatively, new medications may unintentionally duplicate existing
medications. For example, a physician might prescribe a calcium channel blocker
to a patient who has hypertension but is already taking another medication from
the same drug class.

Such unintended inconsistencies in medication regimens may occur at any point of
transition in care (e.g., transfer from an intensive care unit to a general
ward), not just hospital admission or discharge. Medication reconciliation
refers to the process of avoiding such inadvertent inconsistencies across
transitions in care by reviewing the patient’s complete medication regimen at
the time of admission/transfer/discharge and comparing it with the regimen being
considered for the new setting of care.

In July 2004, the Joint Commission for Accreditation of Healthcare Organizations
(JCAHO) announced 2005 National Patient Safety Goal #8 to "accurately and
completely reconcile medications across the continuum of care."(2) The JCAHO
does not stipulate the details of the reconciliation process or who should
perform it. While most hospitals cannot afford to hire pharmacists to take on
this role, it is worth noting that more rigorous positive studies of medication
reconciliation have tended to involve pharmacists performing the medication
history and reconciliation process.(3-5)

1. Tam VC, Knowles SR, Cornish PL, Fine N, Marchesano R, Etchells EE. Frequency,
type and clinical importance of medication history errors at admission to
hospital: a systematic review. CMAJ 2005;173:510-515.

2. Using medication reconciliation to prevent errors. Sentinel Event Alert.
Issue 35 - January 25, 2006. Available at:

http://www.jointcommission.org/SentinelEvents/SentinelEventAlert/sea_35.htm.
Accessed May 15, 2006.

3. Schnipper JL, Kirwin JL, Cotugno MC, et al. Role of pharmacist counseling in
preventing adverse drug events after hospitalization. Arch Intern Med
2006;166:565-571.

4. Coleman EA, Smith JD, Raha D, Min SJ. Posthospital medication discrepancies:
prevalence and contributing factors. Arch Intern Med 2005;165:1842-1847.

5. Cornish PL, Knowles SR, Marchesano R, et al. Unintended medication
discrepancies at the time of hospital admission. Arch Intern Med
2005;165:424-429.

Mental Models – Mental models are psychological representations of real,
hypothetical, or imaginary situations. Scottish psychologist Kenneth Craik
(1943) first proposed mental models as the basis for anticipating events and
explaining events (ie, for reasoning). Though easiest to conceptualize in terms
of mental pictures of objects (eg, a DNA double helix or the inside of an
internal combustion engine) mental models can also include "scripts" or
processes and other properties beyond images. Mental models create differing
expectations, which suggest different courses of action. For instance, when you
walk into a fast-food restaurant, you are invoking a different mental model than
when in a fancy restaurant. Based on this model, you automatically go to place
your order at the counter, rather than sitting at a booth and expecting a waiter
to take your order.

Mistakes – In some contexts,
errors are dichotomized
as “slips” or
“mistakes,” based on the cognitive psychology of task-oriented behavior.
Attentional behavior is characterized by conscious thought, analysis, and
planning, as occurs in active problem solving. Schematic behavior refers to the
many activities we perform reflexively or as if acting on “autopilot.”
Complementary to these two behavior types are two categories of error: slips and
mistakes.

Mistakes reflect failures during attentional behaviors, or incorrect choices.
Rather than lapses in concentration (as with slips), mistakes typically involve
insufficient knowledge, failure to correctly interpret available information, or
application of the wrong cognitive “heuristic” or rule. Thus, choosing the wrong
diagnostic test or ordering a suboptimal medication for a given condition
represent mistakes. A slip, on the other hand, would be forgetting to check the
chart to make sure you ordered them for the right patient.

Distinguishing slips from mistakes serves two important functions. First, the
risk factors for their occurrence differ. Slips occur in the face of competing
sensory or emotional distractions, fatigue, and stress; mistakes more often
reflect lack of experience or insufficient training. Second, the appropriate
responses to these error types differ. Reducing the risk of slips requires
attention to the designs of protocols, devices, and work environments—using
checklists so key steps will not be omitted, reducing fatigue among personnel
(or shifting high-risk work away from personnel who have been working extended
hours), removing unnecessary variation in the design of key devices, eliminating
distractions (eg, phones) from areas where work requires intense concentration,
and other redesign strategies. Reducing the likelihood of mistakes typically
requires more training or supervision. Even in the many cases of slips, health
care has typically responded to all errors as if they were mistakes, with
remedial education and/or added layers of supervision.

Metacognition – Metacognition refers to thinking about thinking—that is,
reflecting on the thought processes that led to a particular diagnosis or
decision to consider whether biases or cognitive short cuts may have had a
detrimental effect. Numerous cognitive biases affect human reasoning.(1-3)

In some ways, metacognition amounts to playing devil's advocate with oneself
when it comes to working diagnoses and important therapeutic decisions. However,
the devil is often in the details—one must become familiar with the variety of
specific biases that commonly affect medical reasoning. For instance, when
discharging a patient with atypical chest pain from the emergency department,
you might step back and consider how much the discharge diagnosis of
"musculoskeletal pain" reflects the sign out as a "soft rule out" given by a
colleague on the night shift. Or, your might mull over the degree to which your
reaction to and assessment of a particular patient stemmed from his having been
labeled a "frequent flyer." Another cognitive bias is that clinicians tend to
assign more importance to pieces of information that required personal effort to
obtain (4)
(eg, the additional symptom elicited by your history compared with that given by
a colleague, or the lab result obtained though numerous phone calls.)

While metacognition refers to the general process of reflecting on the
possibility of cognitive biases affecting clinical diagnoses and decisions,
"cognitive forcing functions" refer to specific approaches to looking for such
biases.(1,5)
Just as a computer programmer might routinely check for errors during the
"debugging" process, clinicians should likewise consider routinely employing
cognitive strategies to check for "bugs." These should take into account the
different types of biases known to affect cognition (reviewed in the articles
below [1-3,5]),
details of the clinical context, and even personal details (eg, recognition that
you like to follow hunches or trust your initial gestalt).

1.
Croskerry P. The importance of cognitive errors in diagnosis and strategies to
minimize them. Acad Med. 2003;78:775-80. [

go to pubmed ]

2.
Croskerry P. Achieving quality in clinical decision making: cognitive strategies
and detection of bias. Acad Emerg Med. 2002;9:1184-1204. [

go to pubmed ]

3.
Graber M, Gordon R, Franklin N. Reducing diagnostic errors in medicine: what's
the goal? Acad Med. 2002;77:981-92. [

go to pubmed ]

4.
Redelmeier DA, Shafir E, Aujla PS. The beguiling pursuit of more information.
Med Decis Making. 2001;21:376-381. [

go to pubmed ]

5.
Croskerry P. Cognitive forcing strategies in clinical decisionmaking. Ann Emerg
Med. 2003;41:110-20. [

go to pubmed ]

N	Back to Top

Near Miss – An event or situation that did not produce patient injury,
but only because of chance. This good fortune might reflect robustness of the
patient (eg, a patient with penicillin allergy receives penicillin, but has no
reaction) or a fortuitous, timely intervention (eg, a nurse happens to realize
that a physician wrote an order in the wrong chart). This definition is
identical to that for
close call.

Normal Accident Theory – Though less often cited than
high
reliability theory in the health care literature, normal accident theory has
played a prominent role in the study of complex organizations. The phrase and
theory were developed by sociologist Charles Perrow (1)
in connection with a careful analysis of the accident at the Three Mile Island
nuclear power plant in 1979, among other industrial (near) catastrophes. In
contrast to the optimism of high reliability theory, normal accident theory
suggests that, at least in some settings, major accidents become inevitable and,
thus, in a sense, "normal."

Perrow proposed two factors that create an environment in which a major accident
becomes increasingly likely over time: "complexity" and "tight coupling." The
degree of complexity envisioned by Perrow occurs when no single operator can
immediately foresee the consequences of a given action in the system. Tight
coupling occurs when processes are intrinsically time-dependent–once a process
has been set in motion, it must be completed within a certain period of time.
Many health care organizations would illustrate Perrow’s definition of
complexity, but only hospitals would be regarded as exhibiting tight coupling.
Importantly, normal accident theory contends that accidents become inevitable in
complex, tightly coupled systems regardless of steps taken to increase safety.
In fact, these steps sometimes increase the risk for future accidents through
unintended collateral effects and general increases in system complexity.

Approximately 10 years after normal accident theory appeared, Scott Sagan, a
political scientist, conducted a detailed examination of the question of why
there has never been an accidental nuclear war (2)
with a view toward testing the competing paradigms of normal accident theory and
high reliability theory. The results of detailed archival research initially
appeared to confirm the predictions of high reliability theory. However,
interviews with key personnel uncovered several hair-raising near misses. The
study ultimately concluded that good fortune played a greater role than good
design in the safety record of the nuclear weapons industry to date.

Even if one does not believe the central contention of normal accident
theory–that the potential for catastrophe emerges as an intrinsic property of
certain complex systems–analyses informed by this theory’s perspective have
offered some fascinating insights into possible failure modes for high-risk
organizations, including hospitals.

1. Perrow C. Normal Accidents: Living with High-Risk Technologies.
Princeton, NJ; Princeton University Press; 1999. [
go
to PSNet listing ]

2. Sagan SD. The Limits of Safety: Organizations, Accidents and Nuclear
Weapons. Princeton, NJ: Princeton University Press; 1993. [
go
to PSNet listing] ]

Normalization of Deviance – Normalization of deviance was coined by Diane
Vaughan in her book

The Challenger Launch Decision: Risky Technology, Culture, and Deviance at NASA
(1),
in which she analyzes the interactions between various cultural forces within
NASA that contributed to the Challenger disaster. Vaughn used this expression to
describe the gradual shift in what is regarded as normal after repeated
exposures to “deviant behavior” (behavior straying from correct [or safe]
operating procedure). Corners get cut, safety checks bypassed, and alarms
ignored or turned off, and these behaviors become normal—not just common,
but stripped of their significance as warnings of impending danger. In their
discussion of a catastrophic error in healthcare, Mark Chassin and Elise Becher
used the phrase “a culture of low expectations.”(2)
When a system routinely produces errors (paperwork in the wrong chart, major
miscommunications between different members of a given healthcare team, patients
in the dark about important aspects of the care), providers in the system become
inured to malfunction. In such a system, what should be regarded as a major
warning of impending danger is ignored as a normal operating procedure.

1.
Vaughan D. The Challenger launch decision: risky technology, culture and
deviance at NASA. Chicago, IL: University of Chicago Press; 1996.

2.
Chassin MR, Becher EC. The wrong patient. Ann Intern Med 2002;136:826-833.[

go to pubmed ]

O	Back to Top

Onion – The "onion" model illustrates variables that affect the multiple
levels of a hierarchal system in which a task is performed and errors occur.

P	Back to Top

Patient Safety – Freedom from accidental or preventable injuries produced
by medical care.

Pay for Performance – (sometimes abbreviated as “P4P”) Refers to the
general strategy of promoting quality improvement by rewarding providers
(meaning individual clinicians or, more commonly, clinics or hospitals) who meet
certain performance expectations with respect to health care quality or
efficiency.

Performance can be defined in terms of patient outcomes but is more commonly
defined in terms of processes of care (eg, the percentage of eligible diabetics
who have been referred for annual retinal examinations, the percentage of
children who have received immunizations appropriate for their age, patients
admitted to the hospital with pneumonia who receive antibiotics within 6 hours).

Pay-for-performance initiatives reflect the efforts of purchasers of health
care—from the federal government to private insurers—to use their purchasing
power to encourage providers to develop whatever specific quality improvement
initiatives are required to achieve the specified targets. Thus, rather than
committing to a specific quality improvement strategy, such as a new information
system or a disease management program, which may have variable success in
different institutions, pay for performance creates a climate in which provider
groups will be strongly incentivized to find whatever solutions will work for
them.

A brief overview of pay for performance in general, with references and Web
sites for specific programs can be found in the reference below.

1. Pawlson LG. Pay for performance: two critical steps needed to achieve a
successful program. Am J Manag Care. November 2004 (suppl).

Available at:

http://www.ajmc.com/Article.cfm?Menu=1&ID=2771

Plan-Do-Study-Act – Commonly referred to as PDSA (or PDCA, for Plan-Do-Check-Act),
refers to the cycle of activities advocated for achieving process or system
improvement. The cycle was first proposed by Walter Shewhart, one of the
pioneers of statistical process control (see glossary definition for
run charts) and
popularized by his student, quality expert W. Edwards Deming. The PDSA cycle
represents one of the cornerstones of continuous quality improvement (CQI). The
components of the cycle are briefly described below:

Plan: Analyze the problem you intend to improve and devise a plan to
correct the problem.

Do: Carry out the plan (preferably as a pilot project to avoid major
investments of time or money in unsuccessful efforts).

Study: Did the planned action succeed in solving the problem? If not, what
went wrong? If partial success was achieved, how could the plan be refined?

Act: Adopt the change piloted above as is, abandon it as a complete
failure, or modify it and run through the cycle again. Regardless of which
action is taken, the PDSA cycle continues, either with the same problem or a
new one.

The references below discuss PDSA cycles and the
interpretation of articles reporting quality improvement activities driven by
the PDSA approach.

1. Walley P, Gowland B. Completing the circle: from PD to PDSA. Int J Health
Care Qual Assur Inc Leadersh Health Serv. 2004;17:349-358.

[

go to PubMed ]

2. Speroff T, James BC, Nelson EC, Headrick LA, Brommels M. Guidelines for
appraisal and publication of PDSA quality improvement. Qual Manag Health Care.
2004;13:33-39.

[

go to PubMed ]

3. Speroff T, O'Connor GT. Study designs for PDSA quality improvement
research. Qual Manag Health Care. 2004;13:17-32.

[

go to PubMed ]

Potential ADE – A potential adverse drug event is a medication error or
other drug-related mishap that reached the patient but happened not to produce
harm (eg, a penicillin-allergic patient receives penicillin but happens not to
have an adverse reaction).

Production Pressure – Represents the pressure to put quantity of
output—for a product or a service—ahead of safety. This pressure is seen in its
starkest form in the “line speed” of factory assembly lines, famously
demonstrated by Charlie Chaplin in Modern Times, as he is carried away on
a conveyor belt and into the giant gears of the factory by the rapidly moving
assembly line. The dark reality of production pressures was also vividly
described in Fast Food Nation (1)
in the section on workers in meat-packing factories. The furious pace at which
they must work—standing side by side and wielding sharp knives—to keep up with
the line speed often results in serious, even dismembering, injuries.

In health care, production pressure refers to delivery of services—the pressure
to run hospitals at 100% capacity, with each bed filled with the sickest
possible patients who are discharged at the first sign that they are stable, or
the pressure to leave no operating room unused and to keep moving through the
schedule for each room as fast as possible. In a survey of members of the
American Society of Anesthesiologists (2),
half of respondents stated that they had witnessed at least one case in which
production pressure resulted in what they regarded as unsafe care. Examples
included elective surgery in patients without adequate preoperative evaluation
and proceeding with surgery despite significant contraindications.

Production pressure produces an organizational culture in which frontline
personnel (and often managers as well) are reluctant to suggest any course of
action that compromises productivity, even temporarily. For instance, in the
survey of anesthesiologists (2),
respondents reported pressure by surgeons to avoid delaying cases through
additional patient evaluation or canceling cases, even when patients had clear
contraindications to surgery.

1. Schlosser E. Fast Food Nation. Boston, MA: Houghton Mifflin; 2001.

2. Gaba DM, Howard SK, Jump B. Production pressure in the work environment.
California anesthesiologists' attitudes and experiences. Anesthesiology.
1994;81:488-500. [

go to PubMed ]

R	Back to Top

Rapid Response Team - See
Medical
Emergency Team

Read-Backs – When information is conveyed verbally, miscommunication may
occur in a variety of ways, especially when transmission may not occur clearly
(eg, by telephone or radio, or if communication occurs under stress). For names
and numbers, the problem often is confusing the sound of one letter or number
with another. To address this possibility, the military, civil aviation, and
many high-risk industries use protocols for mandatory "read-backs," in which the
listener repeats the key information, so that the transmitter can confirm its
correctness.

Because mistaken substitution or reversal of alphanumeric information is such a
potential hazard, read-back protocols typically include the use of phonetic
alphabets, such as the NATO system ("Alpha-Bravo-Charlie-Delta-Echo...X-ray-Yankee-Zulu")
now familiar to many. In health care, traditionally, read-back has been
mandatory only in the context of checking to ensure accurate identification of
recipients of blood transfusions. However, there are many other circumstances in
which health care teams could benefit from following such protocols, for
example, when communicating key lab results or patient orders over the phone,
and even when exchanging information in person (eg, "sign outs" and other such
handoffs).

Red Rules - Rules that must be followed to the letter. In the language of
non-health care industries, red rules “stop the line.” In other words, any
deviation from a red rule will bring work to a halt until compliance is
achieved. Red rules, in addition to relating to important and risky processes,
must also be simple and easy to remember.

An example of a red rule in health care might be the following: “No hospitalized
patient can undergo a test of any kind, receive a medication or blood product,
or undergo a procedure if they are not wearing an identification bracelet.” The
implication of designating this a red rule is that the moment a patient is
identified as not meeting this condition, all activity must cease in order to
verify the patient’s identity and supply an identification band.

Health care organizations already have numerous rules and policies that call for
strict adherence. So what is it about red rules that makes them more than
particularly important rules? The reason that some organizations are using this
new designation is that, unlike many standard rules, red rules are ones that
will always be supported by the entire organization. In other words, when
someone at the frontline calls for work to cease on the basis of a red rule, top
management must always support this decision. Thus, when properly implemented,
red rules should foster a culture of safety, as frontline workers will know that
they can stop the line when they notice potential hazards, even when doing so
may result in considerable inconvenience or be time consuming and costly, for
their immediate supervisors or the organization as a whole.

Root Cause Analysis (RCA) – A structured process for identifying the
causal or contributing factors underlying
adverse events
or other
critical incidents.(1,2)
The key advantage of RCA over traditional clinical case reviews is that it
follows a pre-defined protocol for identifying specific contributing factors in
various causal categories (eg, personnel, training, equipment, protocols,
scheduling) rather than attributing the incident to the first error one finds or
to preconceived notions investigators might have about the case. For instance,
in a case involving a patient who mistakenly received someone else’s invasive
cardiac procedure,(3)
the initial reaction of many hearing about the case might be: the nurse should
have checked the wrist band. Or, how could the doctor not have looked at the
face of the patient on the operating table? Traditionally, an internal review of
such a case would do little more than reiterate these "first stories"(4)—typically
involving errors committed by personnel at the "sharp
end"—and miss the "second stories" that emerge from more detailed,
open-minded investigation.

Though the definition of RCA emphasizes analysis, the single most important
product of an RCA is descriptive—a detailed account of the events that led up to
the incident. For instance, in the case mentioned above,(3)
the detailed catalogue of events leading up to the "wrong person procedure"
included 17 distinct errors, rather than one or two "so-and-so should have
checked such-and-such" errors.

Root cause analysis is still a widely used term, but many now find it
misleading. Critics of the term argue that there are no true "causes," so much
as "contributing factors." This is not entirely a semantic distinction. As
illustrated by the
Swiss cheese model, multiple errors and system flaws must come together for
a critical incident to reach the patient. Labeling one or even several of these
factors as "causes" fosters undue emphasis on specific "holes in the cheese"
rather than the overall relationships between different layers and other aspects
of system design. Accordingly, some have suggested replacing the term "root
cause analysis" with "systems analysis."(5)

Specific resources that facilitate carrying out RCAs or "systems analyses" can
be found at:

Root Cause Analysis (RCA). Veterans Affairs National Center for Patient Safety
Web site.

Available at:
http://www.patientsafety.gov/rca.html.

Taylor-Adams S, Vincent C. Systems analysis of critical incidents: the London
Protocol. London, UK: Clinical Safety Research Unit, Imperial College London;
2004.

Available at:

http://www.csru.org.uk/downloads/SACI.pdf.

1. Wald H, Shojania KG. Root cause analysis. In: Shojania KG, Duncan BW,
McDonald KM, Wachter RM, eds. Making Health Care Safer: A Critical Analysis of
Patient Safety Practices. Evidence Report/Technology Assessment No. 43 from the
Agency for Healthcare Research and Quality: AHRQ Publication No. 01-E058; 2001.

Available at:

http://www.ahrq.gov/clinic/ptsafety/chap5.htm

2. Bagian JP, Gosbee J, Lee CZ, Williams L, McKnight SD, Mannos DM. The
Veterans Affairs root cause analysis system in action. Jt Comm J Qual Improv.
2002;28:531-545.

[

go to PubMed ]

3. Chassin MR, Becher EC. The wrong patient. Ann Intern Med.
2002;136:826-833.

[

go to PubMed ]

4. Cook RI, Woods DD, Miller C. A Tale of Two Stories: Contrasting Views of
Patient Safety. National Patient Safety Foundation at the AMA: Annenberg Center
for Health Sciences, Rancho Mirage, CA; 1998.

Available at:
http://www.npsf.org/exec/front.html.

5. Vincent CA. Analysis of clinical incidents: a window on the system not a
search for root causes. Qual Saf Health Care. 2004;13:242-243.

[

go to PubMed ]

Rule of Thumb (same as
heuristic) –
Loosely defined or informal rule often arrived at through experience or trial
and error (eg, gastrointestinal complaints that wake patients up at night are
unlikely to be functional). Heuristics provide cognitive shortcuts in the face
of complex situations, and thus serve an important purpose. Unfortunately, they
can also turn out to be wrong.

The phrase "rule of thumb" probably has it origin with trades such as carpentry
in which skilled workers could use the length of their thumb (roughly one inch
from knuckle to tip) rather than more precise measuring instruments and still
produce excellent results. In other words, they measured not using a "rule of
wood" (old-fashioned way of saying ruler), but by a "rule of thumb."

Run Charts – A type of "statistical process control" or "quality control"
graph in which some observation (eg, manufacturing defects or adverse outcomes)
is plotted over time to see if there are "runs" of points above or below a
center line, usually representing the average or median. In addition to the
number of runs, the length of the runs conveys important information. For run
charts with more than 20 useful observations, a run of 8 or more dots would
count as a "shift" in the process of interest, suggesting some non-random
variation.

Other key tests applied to run charts include tests for "trends" (sequences of
successive increases or decreases in the observation of interest) and "zigzags"
(alternation in the direction—up or down—of the lines joining pairs of dots). If
a non-random change for the better, or "shift," occurs, it suggests that an
intervention has succeeded. The expression "moving the dots" refers to this type
of shift.

Further information about run charts and statistical process control can be
found at:

Yeung S, MacLeod M. Using run charts and
control charts to monitor quality in healthcare [NHS Scotland Web site]. May
2004.

Available at:

http://www.show.scot.nhs.uk/indicators/Tutorial/TUTORIAL_GUIDE_V4.pdf

Mohammed MA. Using statistical process
control to improve the quality of health care. Qual Saf Health Care.
2004;13:243-245.

[

go to PubMed ]

S	Back to Top

Safety Culture – Safety culture and culture of safety are frequently
encountered terms referring to a commitment to safety that permeates all levels
of an organization, from frontline personnel to executive management. More
specifically, "safety culture" calls up a number of features identified in
studies of
high
reliability organizations, organizations outside of health care with
exemplary performance with respect to safety.(1,2)
These features include:

acknowledgment of the high-risk, error-prone nature of an organization’s
activities

a blame-free environment where individuals are able to report errors or
close calls without fear of reprimand or punishment

an expectation of collaboration across ranks to seek solutions to
vulnerabilities

a willingness on the part of the organization to direct resources for
addressing safety concerns (3)

The Veterans Affairs system has explicitly focused on
achieving a culture of safety, in addition to its focus on a number of specific
patient safety initiatives.(4)
The impact of such efforts are very difficult to assess, but some tools for
quantifying the degree to which organizations differ with respect to "safety
culture" have begun to emerge.(5)

1. Roberts KH. Managing high reliability organizations. Calif Manage Rev.
1990;32:101-113.

2. Weick KE. Organizational culture as a source of high reliability. Calif
Manage Rev. 1987;29:112-127.

3. Pizzi L, Goldfarb N, Nash D. Promoting a culture of safety. In: Shojania
KG, Duncan BW, McDonald KM, Wachter RM, eds. Making Health Care Safer: A
Critical Analysis of Patient Safety Practices. Evidence Report/Technology
Assessment No. 43 from the Agency for Healthcare Research and Quality: AHRQ
Publication No. 01-E058; 2001.

[

Available at: http://www.ncbi.nlm.nih.gov/books/bv.fcgi?rid=hstat1.section.61719
]

4. Weeks WB, Bagian JP. Developing a culture of safety in the Veterans
Health Administration. Eff Clin Pract 2000;3:270-276.

[

go to pubmed ]

5. Singer SJ, Gaba DM, Geppert JJ, Sinaiko AD, Howard SK, Park KC. The
culture of safety: results of an organization-wide survey in 15 California
hospitals. Qual Saf Health Care. 2003;12:112-118.

[

go to pubmed ]

Sentinel Event – An
adverse event in
which death or serious harm to a patient has occurred; usually used to refer to
events that are not at all expected or acceptable—eg, an operation on the wrong
patient or body part. The choice of the word "sentinel" reflects the
egregiousness of the injury (eg, amputation of the wrong leg) and the likelihood
that investigation of such events will reveal serious problems in current
policies or procedures.

Sensemaking – A term from organizational theory that refers to the
processes by which an organization takes in information to make sense of its
environment, to generate knowledge, and to make decisions. It is the
organizational equivalent of what individuals do when they process information,
interpret events in their environments, and make decisions based on these
activities. More technically, organizational sensemaking constructs the shared
meanings that define the organization's purpose and frame the perception of
problems or opportunities that the organization needs to work on.

Karl Weick, at the University of Michigan Business School, has written an
excellent book on the subject, titled Sensemaking in Organizations.(1)
Weick also discussed a specific example of what happens when organizational
sensemaking breaks down.(2)
This example, the Mann Gulch fire, was subsequently brought to the attention of
a wider audience by Don Berwick in his speech Escape Fire.(3)

1. Weick KE. Sensemaking in Organizations. Thousand Oaks, CA: SAGE
Publications; 1995.

[

go to PSNet listing ]

2. Weick KE. The collapse of sensemaking in organizations: the Mann Gulch
disaster. Adm Sci Q. 1993;38:628-652.

[

go to PSNet listing ]

3. Berwick DM. Escape Fire: Lessons for the Future of Health Care. New York,
NY: The Commonwealth Fund; 2002.

[

go to PSNet listing ]

Sharp End – The “sharp end” refers to the personnel or parts of the
health care system in direct contact with patients. Personnel operating at the
sharp end may literally be holding a scalpel (eg, an orthopedist who operates on
the wrong leg) or figuratively be administering any kind of therapy (eg, a nurse
programming an intravenous pump) or performing any aspect of care.

To complete the metaphor, the "blunt
end" refers to the many layers of the health care system that affect the
scalpels, pills, and medical devices, or the personnel wielding, administering,
and operating them.

Thus, an error in programming an intravenous pump would represent a problem at
the sharp end, while the institution’s decision to use multiple types of
infusion pumps (making programming errors more likely) would represent a problem
at the blunt end.

The terminology of “sharp” and “blunt” ends correspond roughly to “active
failures” and “latent
conditions.”

Situational Awareness – Situational awareness refers to the degree to
which one’s perception of a situation matches reality. In the context of crisis
management, where the phrase is most often used, situational awareness includes
awareness of fatigue and stress among team members (including oneself),
environmental threats to safety, appropriate immediate goals, and the
deteriorating status of the crisis (or patient). Failure to maintain situational
awareness can result in various problems that compound the crisis. For instance,
during a resuscitation, an individual or entire team may focus on a particular
task (a difficult central line insertion or a particular medication to
administer, for example). Fixation on this problem can result in loss of
situational awareness to the point that steps are not taken to address
immediately life-threatening problems such as respiratory failure or a pulseless
rhythm. In this context, maintaining situational awareness might be seen as
equivalent to keeping the “big picture” in mind. Alternatively, in assigning
tasks in a crisis, the leader may ignore signals from a team member, which may
result in escalating anxiety for the team member, failure to perform the
assigned task, or further patient deterioration.

Six Sigma - Refers loosely to striving for near perfection in the
performance of a process or production of a product. The name derives from the
Greek letter sigma, often used to refer to the standard deviation of a normal
distribution. By definition, 95% of a normally distributed population falls
within 2 standard deviations of the average (or "2 sigma"). This leaves 5% of
observations as “abnormal” or “unacceptable.” Six Sigma targets a defect rate of
3.4 per million opportunities—6 standard deviations from the population average.

When it comes to industrial performance, having 5% of a product fall outside the
desired specifications would represent an unacceptably high defect rate. What
company could stay in business if 5% of its product did not perform well? For
example, would we tolerate a pharmaceutical company that produced pills
containing incorrect dosages 5% of the time? Certainly not. But when it comes to
clinical performance—the number of patients who receive a proven medication, the
number of patients who develop complications from a procedure—we routinely
accept failure or defect rates in the 2% to 5% range, orders of magnitude below
Six Sigma performance.(1)

Not every process in health care requires such near-perfect performance. In
fact, one of the lessons of Reason’s
Swiss cheese model
is the extent to which low overall error rates are possible even when individual
components have many “holes.” However, many high-stakes processes are far less
forgiving, since a single “defect” can lead to catastrophe (eg, wrong-site
surgery, accidental administration of concentrated potassium).

One version of Six Sigma commonly emulated in health care derives from an
approach developed at General Electric (2)
and consists of five phases summarized by the acronym DMAIC: Define, Measure,
Analyze, Improve, and Control.(3)
Although this process is somewhat reminiscent of the
Plan-Do-Study-Act
(PDSA) approach to continuous quality improvement, the resemblance can be
misleading. Whereas PDSA seeks successive incremental improvements, Six Sigma
typically strives for quantum leaps in performance, which, by their nature,
often necessitate major organizational changes and substantial investments of
time and resources at all levels of the institution. Thus, a clinic trying to
improve the percentage of elderly patients who receive influenza vaccines might
reasonably adopt a PDSA-type approach and expect to see successive, modest
improvements without radically altering normal workflow at the clinic. By
contrast, an ICU that strives to reduce the rate at which patients develop
catheter-associated bacteremia virtually to zero will need major changes that
may disrupt normal workflow.(4)
In fact, the point of choosing Six Sigma is often that normal workflow is
recognized as playing a critical role in the unacceptably high defect rate.

Several examples (4 -6)
of the successful application of Six Sigma methodology to improving patient
safety are listed below.

1. Chassin MR. Is health care ready for Six Sigma quality? Milbank Q.
1998;76:565-591, 510.

[

go to PubMed ]

2. Buck CR Jr. Improving the quality of health care. Health care through a
Six Sigma lens. Milbank Q. 1998;76:749-753.

[

go to PubMed ]

3. Benedetto AR. Six Sigma: not for the faint of heart. Radiol Manage.
2003;25:40-53.

[

go to PubMed ]

4. Frankel HL, Crede WB, Topal JE, Roumanis SA, Devlin MW, Foley AB. Use of
corporate six sigma performance-improvement strategies to reduce incidence of
catheter-related bloodstream infections in a surgical ICU. J Am Coll Surg.
2005;201:349-358.

[

go to PubMed ]

5. Castle L, Franzblau-Isaac E, Paulsen J. Using Six Sigma to reduce
medication errors in a home-delivery pharmacy service. Jt Comm J Qual Patient
Safety. 2005;31:319-324.

[

go to PubMed ]

6. Chan AL. Use of Six Sigma to improve pharmacist dispensing errors at an
outpatient clinic. Am J Med Qual. 2004;19:128-131.

[

go to PubMed ]

Slips (or Lapses) – In some contexts,
errors are dichotomized
as “slips” or “mistakes,”
based on the cognitive psychology of task-oriented behavior. Attentional
behavior is characterized by conscious thought, analysis, and planning, as
occurs in active problem solving. Schematic behavior refers to the many
activities we perform reflexively or as if acting on “autopilot.” Complementary
to these two behavior types are two categories of error: slips (or lapses) and
mistakes.

Slips refer to failures of schematic behaviors, or lapses in concentration (eg,
overlooking a step in a routine task due to a lapse in memory, an experienced
surgeon nicking an adjacent organ during an operation due to a momentary lapse
in concentration). Mistakes, by contrast, reflect incorrect choices. A mistake
would be choosing the wrong diagnostic test or ordering a suboptimal medication
for a given condition represent mistakes. Forgetting to check the chart to make
sure you ordered them for the right patient would be a slip.

Distinguishing slips from mistakes serves two important functions. First, the
risk factors for their occurrence differ. Slips occur in the face of competing
sensory or emotional distractions, fatigue, and stress; mistakes more often
reflect lack of experience or insufficient training. Second, the appropriate
responses to these error types differ. Reducing the risk of slips requires
attention to the designs of protocols, devices, and work environments—using
checklists so key steps will not be omitted, reducing fatigue among personnel
(or shifting high-risk work away from personnel who have been working extended
hours), removing unnecessary variation in the design of key devices, eliminating
distractions (eg, phones) from areas where work requires intense concentration,
and other redesign strategies. Reducing the likelihood of mistakes typically
requires more training or supervision. Even in the many cases of slips, health
care has typically responded to all errors as if they were mistakes, with
remedial education and/or added layers of supervision.

Standard of Care – What the average, prudent clinician would be expected
to do under certain circumstances. The standard of care may vary by community
(eg, due to resource constraints). When the term is used in the clinical
setting, the standard of care is generally felt not to vary by specialty or
level of training. In other words, the standard of care for a condition may well
be defined in terms of the standard expected of a specialist, in which case a
generalist (or trainee) would be expected to deliver the same care or make a
timely referral to the appropriate specialist (or supervisor, in the case of a
trainee). Standard of care is also a term of art in malpractice law, and its
definition varies from jurisdiction to jurisdiction. When used in this legal
sense, often the standard of care is specific to a given specialty; it is often
defined as the care expected of a reasonable practitioner with similar training
practicing in the same location under the same circumstances.

Structure-Process-Outcome Triad – Quality has been defined as the “degree
to which health services for individuals and populations increase the likelihood
of desired health outcomes and are consistent with current professional
knowledge."(1)
This definition, like most others, emphasizes favorable patient outcomes as the
gold standard for assessing quality. In practice, however, one would like to
detect quality problems without waiting for poor outcomes to develop in such
sufficient numbers that deviations from expected rates of morbidity and
mortality can be detected. Avedis Donabedian first proposed that quality could
be measured using aspects of care with proven relationships to desirable patient
outcomes.(2 ,3)
For instance, if proven diagnostic and therapeutic strategies are monitored,
quality problems can be detected long before demonstrable poor outcomes occur.

Aspects of care with proven connections to patient outcomes fall into two
general categories: process and structure. Processes encompass all that is done
to patients in terms of diagnosis, treatment, monitoring, and counseling.
Cardiovascular care provides classic examples of the use of process measures to
assess quality. Given the known benefits of aspirin and beta-blockers for
patients with myocardial infarction, the quality of care for patients with
myocardial infarction can be measured in terms of the rates at which eligible
patients receive these proven therapies. The percentage of eligible women who
undergo mammography at appropriate intervals would provide a process-based
measure for quality of preventive care for women.

Structure refers to the setting in which care occurs and the capacity of that
setting to produce quality. Traditional examples of structural measures related
to quality include credentials, patient volume, and academic affiliation. More
recent structural measures include the adoption of organizational models for
inpatient care (eg, closed intensive care units and dedicated stroke units) and
possibly the presence of sophisticated clinical information systems.
Cardiovascular care provides another classic example of structural measures of
quality. Numerous studies have shown that institutions that perform more cardiac
surgeries and invasive cardiology procedures achieve better outcomes than
institutions that see fewer patients. Given these data, patient volume
represents a structural measure of quality of care for patients undergoing
cardiac procedures.

1. Lohr KN, ed. Medicare: A Strategy for Quality Assurance. Washington, DC:
National Academy Press; 1990.

2. Donabedian A. Evaluating the quality of medical care. Milbank Mem Fund Q.
1966;44 (suppl):166-206.

[

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3. Donabedian A. Explorations in Quality Assessment and Monitoring. The
definition of quality and approaches to its assessment. Vol 1. Ann Arbor, MI:
Health Administration Press; 1980.

[

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Swiss Cheese Model – James Reason developed the "Swiss cheese model" to
illustrate how analyses of major accidents and catastrophic systems failures
tend to reveal multiple, smaller failures leading up to the actual hazard.(1)

In the

model, each slice of cheese represents a safety barrier or precaution
relevant to a particular hazard. For example, if the hazard were wrong-site
surgery, slices of the cheese might include conventions for identifying
sidedness on radiology tests, a protocol for signing the correct site when the
surgeon and patient first meet, and a second protocol for reviewing the medical
record and checking the previously marked site in the operating room. Many more
layers exist. The point is that no single barrier is foolproof. They each have
"holes"; hence, the Swiss cheese. For some serious events (eg, operating on the
wrong site or wrong person), even though the holes will align infrequently, even
rare cases of harm (errors making it "through the cheese") will be unacceptable.

While the model may convey the impression that the slices of cheese and the
location of their respective holes are independent, this may not be the case.
For instance, in an emergency situation, all three of the surgical
identification safety checks mentioned above may fail or be bypassed. The
surgeon may meet the patient for the first time in the operating room. A hurried
x-ray technologist might mislabel a film (or simply hang it backwards and a
hurried surgeon not notice), "signing the site" may not take place at all (eg,
if the patient is unconscious) or, if it takes place, be rushed and offer no
real protection. In the technical parlance of accident analysis, the different
barriers may have a common failure mode, in which several protections are lost
at once (ie, several layers of the cheese line up). An aviation example would be
a scenario in which the engines on a plane are all lost, not because of
independent mechanical failure in all four engines (very unlikely), but because
the wings fell off due to a structural defect. This disastrous failure mode
might arise more often than the independent failure of multiple engines.

In health care, such failure modes, in which slices of the cheese line up more
often than one would expect if the location of their holes were independent of
each other (and certainly more often than wings fly off airplanes) occur
distressingly commonly. In fact, many of the systems problems discussed by
Reason and others—poorly designed work schedules, lack of teamwork, variations
in the design of important equipment between and even within institutions—are
sufficiently common that many of the slices of cheese already have their holes
aligned. In such cases, one slice of cheese may be all that is left between the
patient and significant hazard.

1. Reason J. Human error: models and management. BMJ. 2000;320:768-770.

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Systems Approach – Medicine has traditionally treated quality problems
and errors as failings on the part of individual providers, perhaps reflecting
inadequate knowledge or skill levels. The "systems approach," by contrast, takes
the view that most errors reflect predictable human failings in the context of
poorly designed systems (eg, expected lapses in human vigilance in the face of
long work hours or predictable mistakes on the part of relatively inexperienced
personnel faced with cognitively complex situations). Rather than focusing
corrective efforts on reprimanding individuals or pursuing remedial education,
the systems approach seeks to identify situations or factors likely to give rise
to human error and implement "systems changes" that will reduce their occurrence
or minimize their impact on patients. This view holds that efforts to catch
human errors before they occur or block them from causing harm will ultimately
be more fruitful than ones that seek to somehow create flawless providers.

This "systems focus" includes paying attention to
human factors
engineering (or ergonomics), including the design of protocols, schedules,
and other factors that are routinely addressed in other high-risk industries but
have traditionally been ignored in medicine. Relevant concepts defined elsewhere
in the glossary include
root cause
analysis, active
failures vs.
latent conditions, errors at the "sharp
end" vs. errors at the "blunt
end," slips vs.
mistakes, and the
Swiss cheese model.

T	Back to Top

"Time outs" – Refer to planned periods of quiet and/or interdisciplinary
discussion focused on ensuring that key procedural details have been addressed.
For instance, protocols for ensuring correct site surgery often recommend a
"time out" to confirm the identification of the patient, the surgical procedure,
site, and other key aspects, often stating them aloud for double-checking by
other team members. In addition to avoiding major misidentification errors
involving the patient or surgical site, such a time out ensures that all team
members share the same “game plan” so to speak. Taking the time to focus on
listening and communicating the plans as a team can rectify miscommunications
and misunderstandings before a procedure gets underway.

Triggers – Refer to signals for detecting likely adverse events. For
instance, if a hospitalized patient received naloxone (a drug used to reverse
the effects of narcotics), the patient probably received an excessive dose of
morphine or some other opiate. In the emergency department, the use of naloxone
would more likely represent treatment of a self-inflected opiate overdose, so
the trigger would have little value in that setting. But, among patients already
admitted to hospital, a pharmacy could use the administration of naloxone as a
“trigger” to investigate possible adverse drug events.

A common setting in which triggers have been employed is monitoring
anticoagulation with warfarin.(1 -3)
Triggers might consist of elevated laboratory measures of anticoagulation (eg,
International Normalized Ratio [INR] > 3) or any administration of vitamin K,
which reverses the effects of warfarin and therefore would likely signal the
need to correct particularly worrisome levels of anticoagulation.

In many studies, triggers alert providers involved in patient safety activities
to probable adverse events so they can review the medical record to determine if
an actual or potential adverse event has occurred. In cases in which the trigger
correctly identified an adverse event, causative factors can be identified and,
over time, interventions developed to reduce the frequency of particularly
common causes of adverse events (such as anticoagulant problems [1 -3]).
In these studies, the triggers provide an efficient means of identifying
potential adverse events after the fact.

The traditional use of triggers has been to generate these retrospective
reviews. However, using triggers in real time has tremendous potential as a
patient safety tool. In one study of real-time triggers in a single community
hospital, for example, more than 1000 triggers were generated in 6 months, and
approximately 25% led to physician action and would not have been recognized
without the trigger.(4)

As with any alert or alarm system, the threshold for generating triggers has to
balance true and false positives. The system will lose its value if too many
triggers prove to be false alarms.(5)
This concern is less relevant when triggers are used as chart review tools. In
such cases, the tolerance of “false alarms” depends only on the availability of
sufficient resources for medical record review. Reviewing four false alarms for
every true adverse event might be quite reasonable in the context of an
institutional safety program, but frontline providers would balk at (and
eventually ignore) a trigger system that generated four false alarms for every
true one.

1. Hartis CE, Gum MO, Lederer JW Jr. Use of specific indicators to detect
warfarin-related adverse events. Am J Health Syst Pharm. 2005;62:1683-1688.

[

go to PubMed ]

2. Lederer J, Best D. Reduction in anticoagulation-related adverse drug
events using a trigger-based methodology. Jt Comm J Qual Patient Saf.
2005;31:313-318.

[

go to PubMed ]

3. Cohen MM, Kimmel NL, Benage MK, et al. Medication safety program reduces
adverse drug events in a community hospital. Qual Saf Health Care.
2005;14:169-174.

[

go to PubMed ]

4. Raschke RA, Gollihare B, Wunderlich TA, et al. A computer alert system to
prevent injury from adverse drug events: development and evaluation in a
community teaching hospital. JAMA. 1998;280:1317-1320. Erratum in: JAMA.
1999;281:420.

[

go to PubMed ]

5. Edworthy J, Hellier E. Fewer but better auditory alarms will improve
patient safety. Qual Saf Health Care. 2005;14:212-215.

[

go to PubMed ]

U	Back to Top

Underuse, Overuse, Misuse – For process of care, quality problems can
arise in one of three ways: underuse, overuse, and misuse.

“Underuse” refers to the failure to provide a health care service when it would
have produced a favorable outcome for a patient. Standard examples include
failures to provide appropriate preventive services to eligible patients (eg,
Pap smears, flu shots for elderly patients, screening for hypertension) and
proven medications for chronic illnesses (steroid inhalers for asthmatics;
aspirin, beta-blockers, and lipid-lowering agents for patients who have suffered
a recent myocardial infarction).

“Overuse” refers to providing a process of care in circumstances where the
potential for harm exceeds the potential for benefit. Prescribing an antibiotic
for a viral infection like a cold, for which antibiotics are ineffective,
constitutes overuse. The potential for harm includes adverse reactions to the
antibiotics and increases in antibiotic resistance among bacteria in the
community. Overuse can also apply to diagnostic tests and surgical procedures.

“Misuse” occurs when an appropriate process of care has been selected but a
preventable complication occurs and the patient does not receive the full
potential benefit of the service. Avoidable complications of surgery or
medication use are misuse problems. A patient who suffers a rash after receiving
penicillin for strep throat, despite having a known allergy to that antibiotic,
is an example of misuse. A patient who develops a pneumothorax after an
inexperienced operator attempted to insert a subclavian line would represent
another example of misuse.

W	Back to Top

Workaround – From the perspective of frontline personnel trying to
accomplish their work, the design of equipment or the policies governing works
tasks can seem counterproductive. When frontline personnel adopt consistent
patterns of work or ways of bypassing safety features of medical equipment,
these patterns and actions are referred to as “workarounds.” Although
workarounds “fix the problem,” the system remains unaltered and thus continues
to present potential safety hazards for future patients.

A case on AHRQ WebM&M (Transfusion
“Slip”) describes a potentially fatal near miss in which the blood samples
drawn for crossmatching from husband and wife trauma victims were inadvertently
swapped. The error was caught when an alert laboratory technician noted that the
wife’s blood type differed from that recorded previously at the same hospital. A
comment on the

forum provides a striking example of a workaround. The reader noted that
after a similar incident had occurred at another hospital, the organization
instituted a policy requiring two screens for all transfusion crossmatches. The
intention was that, by requiring two separate samples, any mislabeled sample
would lead to a discrepancy with the other sample and provide a warning that
would virtually eliminate the risk of transfusion errors due to mislabeled
samples. However, frontline personnel at the hospital created a workaround: they
routinely drew both crossmatch samples from the same needle stick, saving them
time and patients discomfort, but completely undermining the value of double
samples to avoid labeling errors.

As pointed out by a second reader on the forum, the appearance of a workaround
at that hospital was expected because the new policy doubled the work associated
with a common task in order to prevent a very uncommon error—one that virtually
none of them would ever have encountered.

From a definitional point of view, it does not matter if frontline users are
justified in working around a given policy or equipment design feature. What
does matter is that the motivation for a workaround lies in getting work done,
not laziness or whim. Thus, the appropriate response by managers to the
existence of a workaround should not consist of reflexively reminding staff
about the policy and restating the importance of following it. Rather,
workarounds should trigger assessment of workflow and the various competing
demands for the time of frontline personnel. In busy clinical areas where
efficiency is paramount, managers can expect workarounds to arise whenever
policies create added tasks for frontline personnel, especially when the extra
work is out of proportion to the perceived importance of the safety goal.

SECOND NEWS PORTAL LAUNCED ON 15 OCTOBER 2006

2006-10-15T17:54:00.000-07:00

http://johnraymondbaker.php1h.com is the second news portal for Baker Chiropractic added today!

OUR GENERAL MANAGER, MRS. TAMMY BAKER, IS IN NURSING SCHOOL

2006-10-13T09:40:00.000-07:00

Our general manager, Ms. Tammy Baker, is
currently in Nursing School at the University of Texas

We are very proud of Ms. Baker for being able to help this practice, and to go
to school full time.

Her goal is to get her Doctor of Nurse
Practitioner degree. We can't wait !

Another information portal for BAKER CHIROPRACTIC launched

2006-10-13T04:50:00.000-07:00

The growing list of BAKER CHIROPRACTIC, PA informational portals has increased again.

We launched http://bakerchiropractic.orgfree.com
yesterday and it seems to be working fine.

Have a great day!

WordPress Blog added

2006-10-11T18:02:00.000-07:00

A new information portal is born and launched. The address is
http://bakerchiropractic.wordpress.com and is going great. Wordpress is quality blogging software, and BAKER CHIROPRACTIC, PA is proud to be able to include this site in its information portal news network.

Injured Worker...Do You Feel All Alone?

2006-09-26T19:35:00.000-07:00

You've been a good worker for some time. Always on time, working hard to do a full day's work. Suddenly, you get hurt, and now, you worry that you are being targeted for termination.

On top of this, you are hurting, and may have numbness in the arms or legs. You don't know how bad you are injured. What do you do? WHAT DO YOU DO?

You NEED a treating doctor who has years of experience in treating injured workers.
You NEED a treating doctor who cares about your problems.
You NEED a treating doctor who does the right things to find out how bad you are hurt.

Dr. John Raymond Baker,DC is such a doctor.

You aren't alone when you have the resources of BAKER CHIROPRACTIC on your side.

Call 903-753-5400 today!

LINKS FOR THIS SITE...

2006-09-26T06:01:00.000-07:00

TWO MORE BAKER CHIROPRACTIC NEWS PORTALS GO LIVE...

2006-09-13T08:01:00.000-07:00

http://johnraymondbaker.php1h.com

and

http://bakerchiro.php1h.com

went live, and will be updated.

Yet ANOTHER new Baker Chiropractic site goes live...Longviewdoctor.com

2006-09-01T08:23:00.001-07:00

We have even another news and information portal online now.

Located at http://www.longviewdoctor.com
it provides news and contact information for Baker Chiropractic of Longview.

Check it out.