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Quture International

Learning from Medical Malpractice Claims (HFACS,Part 8):

Martin Makary, in his recent article[1] “Medical error—the third leading cause of death in the US.”  He begins with his observations: “The science of safety has matured to describe how communication breakdowns, diagnostic errors, poor judgment, and inadequate skill can directly result in patient harm and death.”

Dr. Makary’s perspectives of human factors in medical errors mirrors the positions of learning from errors and scientific approach of Quture.  He observes: “Human error is inevitable. Although we cannot eliminate human error, we can better measure the problem to design safer systems mitigating its frequency, visibility, and consequences.”

Quture advocates the strategy for hospitals to carry out a rapid and efficient independent investigation into deaths to determine the potential contribution of error, the very same words as Dr. Makary. He proposes a root cause analysis approach medico-legal protections to maintain anonymity would enable local earning while using. QualOptima HFCAS introduces a standardized data collection and reporting processes; such a standardized and common database is essential to an accurate national picture of the problem, its causes and solutions.

Healthcare Science

Healthcare Science

Optimal outcomes, clinical, operational and financial, depend upon creating a culture of learning from mistakes.   The Institute of Medicine’s goal of creating learning health systems depends upon advancing the science of safety.  Dr. Makary concludes his article stating: “To achieve more reliable health care systems, the science of improving safety should benefit from sharing data nationally and internationally, in the same way as clinicians share research and innovation about coronary artery disease, melanoma, and influenza. Sound scientific methods, beginning with an assessment of the problem, are critical to approaching any health threat to patients. The problem of medical error should not be exempt from this scientific approach. More appropriate recognition of the role of medical error in patient death could heighten awareness and guide both collaborations and capital investments in research and prevention.”

Drs. Shappell and Wiegmann observed[2] in the 1990’s, as aviation safety was embracing HFACS: “Human error has been implicated in 70 to 80% of all civil and military aviation accidents.”  This is a significantly different approach to error than medicine, which is focused more on systems as the cause of mistakes.  For example, a report[3] by CRICO found that errors in clinical judgment were cited in 77% percent of more than 800 clinically coded obstetrical (OB) medical malpractice cases. QualOptima HFACS is positioned to transform health care patient safety, based on the scientific approach to human factors classification and analysis, to empower health care providers and organizations, as well as the medical malpractice insurance entities responsible for the liability of preventable errors, to become learning organizations.

These challenges and opportunities are the same in health care as aviation safety in the 1990’s when Shappell and Wiegmann stated to the FAA: “most accident reporting systems are not designed around any theoretical framework of human error. As a result, most accident databases are not conducive to a traditional human error analysis, making the identification of intervention strategies onerous.”

Medical Errors, Outcomes and Malpracitice

Medical Errors, Outcomes and Malpractice

Quture intends to begin developing the QualOptima HFACS medical errors database from existing medical malpractice claims databases.  This approach and the potential value of claims databases is a strategy of CRICO, affiliated with the Risk Management Foundation of the Harvard Medical Institutions. The optimal beginning sources of medical error data and databases are the massive experiences with alleged negligence and liability in medical malpractice claims data.  Indeed, the medical literature provides convincing evidence for the value of evaluating claims data for insight into medical errors, even without the HFACS of Drs. Wiegmann and Shappell.

Drs. Wiegmann and Shappell prefer HFACS prospectively rather than in archived databases, like medical malpractice claims.  This will be discussed in the following section, considering the three (3) factors that limit its use retrospectively.  However, the meta-analysis of aviation accidents retrospectively served as the basis for the development of HFACS, as opposed to the development of the Joint Commission’s Patient Safety Event Taxonomy (PSET).  The inherent value in beginning to classify medical malpractice claims is demonstrated by review of the literature.

A study[4] published in 2004 which considered learning from malpractice claims about negligent, adverse events United States is an example of the potential value to patient safety from claims analysis.  The study concluded that learning from negligent adverse events offers potential targets for prioritized research and intervention. The researchers singled out targets to refine the taxonomy of factors that cause or facilitate errors. The benefit of Drs. Shappell & Wiegmann’s HFACS is the ultimate conclusion of the study regarding potential value of using HFACS for medical malpractice claims data: “These targets include refining the taxonomy of factors that cause or facilitate errors” (emphasis added).  The findings of the study as to the potential for using HFACS to analyze medical malpractice claims data is significant. “More complete characterization in malpractice claims data of system failures that contribute to negligent adverse events may be one of the richest opportunities for future research and efforts to help good doctors prevent lapses in care.”[5]

A very significant finding was that just over half of closed claims were reported as having been reviewed for negligence (53%).  This is an extraordinarily significant finding in our experience, in the inpatient setting of hospitals and the outpatient (e.g. surgery centers) and ambulatory settings (e.g. physician care and testing).  Quture has worked extensively with the co-author of the famous study that was the basis of the calculations of error in the IOM To Err is Human, Troyen Brennan, MD, JD.[6]  Indeed, Quture’s expertise is founded in 40+ years as the leading external review source of expert physician panels to review single cases, series of cases based on identified patterns, and root causes of errors.  External peer review, by the very nature of the context of these engagements, specifically requires examinations of human error.  Quture has reviewed cases and patterns in hundreds of hospitals by thousands of physicians for hundreds of thousands of patients.

QualOptima, the solution for healthcare data, where it resides and analytics

QualOptima, the solution for healthcare data, where it resides and analytics

Quture is extraordinarily different from other clinical data companies, because we have been engaged not to study medical errors but to solve their root causes.  Data for the sake of data (and revenue) and data to simply quantify clinical problems is alien to our expertise, runs contrary to our vision and value proposition, and is a fundamental reason medical error continues at the same rates in America, if not increasing.  Our shared vision, experience and expertise are the reasons we are engaging with our contemporaries at HFACS.

Quture also has extensive experience and expertise in reviewing medical malpractice claims and databases.  Our initial funding in the 1990’s to develop quality and risk software for $1.3 was from a medical malpractice company that embraced the value of reducing medical errors, understanding their root causes, and why our work with other medical malpractice companies in proactive clinical risk management had dramatically increased their profits.

Fast forward to more current medical literature considering the value of evaluating medical errors from medical liability insurance in Sweden.[7]  The study begins with the same limitations that we experience in America, that objective data on the incidence and pattern of adverse events remain scarce, secondary to the reluctance for encompassing reporting of surgical complications.

Interestingly, in Sweden patients may claim economic compensation from a national no-fault insurance system. If they believe they have been injured by the health care system, these patients receive economic compensation but only for injuries that are considered preventable by medical experts in the national insurance company. About 1% of Swedish inhabitants file claims every year in Sweden, and about half of these patients receive economic compensation.

Another interesting discussion in the Swedish study considers the nature of the national systems for compensation of adverse events.  The authors note they may influence the extent to which review of claims data can be used to learn more about adverse events. Claims data in the United States are primarily used by medical malpractice companies to determine insurance premiums, risk managers, attorneys, and others for determining legal liability. The Swedish authors note a well-known study[8] in America that there are questions about the relationship between errors and malpractice claims. “The no-fault system in Sweden, in contrast, does not place the responsibility for a medical error on an individual practitioner and may reduce barriers to filing for compensation and increase the probability that an error is disclosed. The relative rate of claims in Sweden exceeds that of countries with a litigation system, suggesting that its reporting system may contribute to making claims data more useful for identifying and learning more about adverse events.”[9]

HFACS International Classification

HFACS International Classification

The basic findings from reviewing liability claims data is readily demonstrated in the Swedish study.  Examples of the value of such data includes the most common reason for rejecting a patient claim, that the injury was assessed as an “unavoidable consequence” of the treatment (27%) or “injury not related to treatment” (24%). The gender distribution was 57% women and 43% men. The average age of the patients was 51 years (median 53 years, range 0-98 years).  These insights are valuable as targets for refining taxonomy in QualOptima HFACS.

These studies illuminate the logic and strategies Quture advocates for evaluating medical malpractice databases in our HFACS classification and taxonomy framework.  These more recent reports of evaluating malpractice databases for insights into medical errors focus more on specific considerations, primarily on specific medical specialties or categories of errors.

The study discussed from America in 2004 was specifically about primary care.[10] While most medical errors research has focused on the inpatient hospital setting, 68% of claims for primary care physicians were for negligent events in outpatient settings. Similar frequency would apply to the orthopaedic surgeon data from claims in the Swedish study, as most of that care is not hospital based.

Settings of care, comparing inpatient and outpatient settings, was evaluated in the U.S. using claims reported to the National Practitioner Database reported in a 2011 study.[11] The study reports that in 2009, 47.6% were for events in the inpatient setting, 43.1% were for events in the outpatient setting, and 9.4% involved events in both settings.

There are important overlaps in studying the settings of care, such as the events in both settings, especially patients that are seen in emergency departments (ED) of hospitals.  A 2020 epidemiologic study of closed ED claims in the U.S. was published in the Society for Academic Emergency Medicine journal.[12]

This study found that emergency physicians were the primary defendants in a relatively small proportion (only 19%) of ED claims. The largest sources of error included errors in diagnosis (37%), followed by improper performance of a procedure (17%). In 18% of claims, no error could be identified. Acute myocardial infarction (5%), fractures (6%), and appendicitis (2%) were the health conditions associated with the highest number of claims. Over two-thirds of claims (70%) closed without payment to the claimant. Most claims that paid out did so through settlement (29%). Only 7% of claims were resolved by verdict, and 85% of those were in favor of the clinician. Over time, the average indemnity payments and expenses of litigation, adjusted for inflation, more than doubled, while both the total number of claims and number of paid claims decreased.

Emergency department claims, and the publicity of those cases, is extremely important to hospital boards and C-level executives.  A major Quture engagement involved the emergency department even though that was not the basis for the original assignment.  The hospital board had spent millions of dollars to a company who developed the hospital’s strategic plan. The plan was to increase admissions by improving care in the emergency department.  Unfortunately, the board did not recognize that ambulance drivers only brought two (2) types of patients to the ED:  patients that are classified as “no pay,” or patients essentially evaluated as dead on arrival (DOA).  That’s how bad emergency care was at the hospital.

Why didn’t the board know this information?  First, they had never asked the right questions of experts who would know.  Second, the quality of care and patient safety concerns were not known, even to the internal departments of quality and risk, because the contract with the ED company, owned by a physician, were only peer reviewed by the physicians in that group.  Their results were not shared by the hospital.  One of the most remarkable findings of the Quture analysis was that the dramatic rate of readmissions was because the hospital had purchased physician practices.  These groups were not changing their treatment of patients after emergency room encounters, so they just kept coming back.  The federal initiatives to limit payment for readmissions have changed the financial incentives since then, so reducing unanticipated emergency department readmissions is a major focus of QualOptima.

QualOptima Analytics and Repoting

QualOptima Analytics and Reporting

Quture worked with hospital legal counsel to cancel the contract without any further compensation, not easy without the incredibly damaging data but developed by Quture, and consulted with our expert ED resources and physician panels to contract with their replacement.  Quture now consults in such physician contracting agreements with inclusion of financial incentives and disincentives based not only on “productivity” metrics but on performance and outcomes measurement (the sweet spot of QualOptima software).

Evaluation of the studies reported in the medical literature are important to our approach to analysis of medical malpractice claims data, in part because they consider the relative value of various databases that are available for closed claims.  For example, the primary care and emergency department studies used data maintained by the Physician Insurers Association of America (PIAA), a trade association whose participating malpractice insurance carriers collectively insure over 60% of practicing physicians in the United States.  There are significant sources of clinical data available in the vast array of databases, some public by federal and state organizations, most requiring expensive licenses, and medical specialty organization databases maintained by private data companies focused on patient outcomes.

Quture intends to develop contracts to review not only closed claims databases, but to contract for real-time analytics using HFACS as claims are opened by claims representatives of insurers.  There are two (2) significant different types of medical malpractice insurers: those that are private insurance companies and those that are insurance trusts of hospital systems and physician groups.  The ultimate value is in aggregated data from retrospective analysis and transferred through predictive modeling scientific methods to manage errors using rescue modalities, disclosure protocols, and converting clinical practice to becoming true learning organizations (Quture’s Value Data Centers using QualOptima).

A weakness reported in the literature[13] is that the ‘‘contributing factor’’ variable is not more robust. This variable is secondary for risk management analyses. Malpractice data might be more useful for patient safety purposes if these factors were more consistently captured and if the categories were classified in the HFACS framework.  These weaknesses, and how HFACS classification will be used in archived database is discussed in the Section Quture Medical Malpractice Claims Model.

The significance of setting of care is illustrated in summary medical errors data in the literature.  In the outpatient setting, the most common reason for a paid claim was a diagnostic error (45.9%), whereas in the inpatient setting the most common reason was surgical (34.1%).  Major injury and death were the 2 most common outcomes in both settings. The mean payment amount for events in the inpatient setting ($362,965) was significantly higher than in the outpatient setting ($290,111).[14]

No single condition accounted for more than 5% of all negligent claims, but the underlying causes were more clustered with ‘‘diagnosis error’’ making up one third of claims. The ratios of condition-specific negligent event claims, relative to the frequency of those conditions in primary care, revealed a significantly disproportionate risk for a number of conditions (for example, appendicitis was 25 times more likely to generate a claim for negligence than breast cancer).

Section Conclusion:

Review of the medical literature supports learning from malpractice claims about negligent, adverse events United States, as well as studies internationally. demonstrate the value of analysis of archived claims data. Analysis of malpractice databases offer valuable insights into the conditions, causes, contributing issues, and severity of errors. However, learning from analysis of medical malpractice databases in the HFACS framework will transform patient safety as this system has done in aviation safety.

[1] Makary MA, Daniel M, “Medical error – the third leading cause of ceath in the US,” British Medical Journal 353:2139-44 (2016).

[2] Shappell SA, Wiegmann DA, “The human factors analysis and classification system – HFACS,” Final Report, Office of Aviation Medicine, Federal Aviation Administration (2000).

[3] CRICO Strategies’ “Report on malpractice errors in obstetrical care provides roadmap for enhanced patient safety: second annual benchmarking report uses malpractice data to identify risks and deliver solutions,” https://www.rmf.harvard.edu/ (last accessed 05/26/16).

[4] Phillips RL Jr, Bartholomew LA, Dovey SM, Fryer GE Jr, Miyoshi TJ, Green LA, “Learning from malpractice claims about negligent, adverse events in primary care in the United States,” Quality & Safety in Health Care 13:121–126 (2004)

[5] Id. at 126,

[6] Leape LL, Brennan TA, Laird N, Lawthers AG, Localio AR, Barnes BA, Hebert L, Newhouse JP, Weiler PC, Hiatt H: “The nature of adverse events in hospitalized patients: results of the Harvard Medical Practice Study, II. New England Journal of Medicine 324(6):377-384 (1991).

[7] Öhrn A, Elfström J, Tropp H, Rutberg H, “What can we learn from patient claims? a retrospective analysis of incidence and patterns of adverse events after orthopaedic procedures in Sweden,” BioMed Central http://www.pssjournal.com/content/6/1/2  (2012).

[8] Studdert DM, Thomas EJ, Burstin HR, Zbar BI, Orav EJ, Brennan TA, “Negligent care and malpractice claiming behavior in Utah and Colorado,” Medical Care 38(3):250-260 (2000).

[9] Ohm, op. cit., p. 3.

[10] Phillips, op. cit., p .

[11] Bishop TF, Ryan AM, Ryan AK, Casalino LP, “Paid malpractice claims for adverse events in inpatient and outpatient settings,” Journal of the American Medical Association 305(23):2427-31 (2011).

[12] Brown TW, McCarthy ML, Kelen GD, Levy F, “An epidemiologic study of closed emergency department malpractice claims in a national database of physician malpractice insurers,” Academic Emergency Medicine, 17(5):553-560 (2010).

[13] Vincent C, Davy C, Esmail A, Neale G, Elstein M, Cozens JF, Walshe K, “Learning from litigation: the role of claims analysis in patient safety,” Journal of Evaluation in Clinical Practice 12(6):665-74 (2006).

[14] Bishop op.cit.