MEDICAL ERROR FATALITIES 1
The Difficulties in Estimating Medical Error Fatalities
Mary Donnelly
For PSY 527/627
Missouri State University
An error on a school exam might cause a lower grade while an error in completing tax forms might cost money. They are unfortunate, but they are the reality of human existence. People make mistakes and they consistently overestimate their own abilities and accuracy (Ayres, 2007). In the medical profession, errors are not simply unfortunate, but also life threatening. As technology advances and more is known about the progress and treatment of diseases, both medical professionals and the general public should be doing everything they can to improve the quality of medical care and specifically to lower the number of deaths caused by medical errors. Statistics can be an incredibly useful tool, but only if treated with scrutiny and not as an all-powerful tool to be trusted without question (Best, 2004).
The Difficult Definitions - “Measurement requires that key terms be defined” (McGlynn, McDonald, & Cassel, 2015, p. 2501).
In order to analyze or even estimate the number of deaths caused by medical error, there are many factors that have to be taken into consideration. The most important consideration is the definition of a medical error. What is a medical error? It is clearly a medical error when a medication is given in the wrong dosage or a surgeon performs a surgery on the wrong appendage. But what if a doctor fails to notice a melanoma under the hairline of a patient that spreads and eventually leads to death? Or what if antibiotic treatment is delayed in hopes of natural recovery, but the patient later dies of respiratory complications linked to the infection? Were these medical errors? These hypothetical examples are cases with direct links in cause of death. What about indirect cases when there are many factors at play in a serious illness but among them is a minor medical error such as a missed injection?
One headline making study from earlier this year claimed that medical error fatalities are the third most common cause of death. It also defines medical errors in extremely open terms. To use extremely broad definitions in a topic as contentious as death caused by medical errors is not only unfair to medical professionals, but also inadequate as a measurement distinguishing what is and is not a medical error (Prasad, 2016). Though the same researchers are doing considerable work in promoting more accurate statistical data, they themselves seem to be using old data based a broad definition to draw attention to their argument (Allen & Pierce, 2016). A better definition at the very least must acknowledge that the medical professional did or did not do something within a standard treatment protocol based on known information or information they should know from patient history or tests (Prasad, 2016). Even this is difficult though because there is considerable variation in medical practice (Daniel, 2016). When standard protocols vary between practitioners questions may remain as to whether specific instances fall within a definition of medical error.
Within a thorough definition of medical errors, there would have to be clear delineations of diagnostic errors, which make up a large portion of medical errors today. Human health is an extremely intricate system with genetics and lifestyle playing an interesting game of timing in the human body. In his book Super Crunchers, Ayres discusses diagnostic errors and 2 types of systems being designed which use data crunching to either help doctors. One type helps filter and find relevant research and the other creates a list of possible causes for the patient’s symptoms (2007). He presents these data crunching systems as complete and having access to enough data to accurately do what he claims they do. But there are two things he fails to address: the issue of accurate data collection, to be addressed later, and incomplete medical histories because the patients may or may not recognize all relevant symptoms within themselves. Having a system such as Ayres describes that gives doctors a list of possible causes in connection to known symptoms is certainly beneficial, but it still depends on the medical professional asking the right questions and the patient or care giver answering correctly and truthfully (2007). Even if the doctor does have all relevant information, there may remain one than one possible cause for the patient’s symptoms particularly with the high percentage of patients with overlapping diseases or medical problems, comorbidity, which may or may not stem from one underlying cause. A decision may have to be made. Sometimes the wrong course of treatment is taken and in the worst of circumstances this wrong path could lead to death. There is great benefit in collecting the data and further researching these cases. However, there is nothing gained by using a definition which would put a condemnatory label such as death caused by diagnostic error on these cases.
If the US desires accurate estimates on the rate of deaths caused by medical errors, then the medical community, statisticians, and related computer programmers must start by creating a comprehensive definition with clear delineations of what does or does not constitute a medical error. Gray areas within the definition should be shown as such within the data and within the statistical output.
Difficulties With Data.
The second major consideration is the collection and accuracy of the data used. It is well recognized that the current national data collecting system for deaths caused by medical errors is not enough (Laday, 2016; Allen & Pierce, 2016; Prasad, 2016). In reading many of the articles written in May of 2016 on this topic it would be assumed that the main problem lies in the death certificates. There are other problems with cause of death findings and how certificates are completed. However the issue they are addressing is the process of how the information from the cause of death certificate is turned into numerical data for final reports. The Centers for Disease Control and Prevention, the CDC, collects the data of all deaths in the US and its territories and gives the public access to this data. In looking at the data and final report, it would be assumed that the cause of death certificate lists only the end, specific cause of death such as renal heart failure, which is renamed into the specific numeric code associated with it (CDC, n.d., Kaggle, n.d.). The complaint is that this final cause of death is often not medical error, so statistically medical errors go unrecognized even if they were a major contributing factor in the final cause of death (Laday, 2016). While it is true that medical errors are not being recorded in the final data, this is not the fault of the original death certificate or of the numerical coding system. Rather the problem is in the data collection process, which only codes the end cause even though the original death certificate is supposed to list any contributing causes or significant conditions even if they do not technically result in death (Instructions, 2004). A new data recording process for the death certificates themselves and a number crunching system that can interpret multiple causes of death seem to be the first necessities towards collecting complete data to use for research purposes.
However, there would still remain problems with the cause of death certificates. One of those problems is how cause of death is determined and thus recorded on the death certificate. Because diagnostic errors are sometimes made, the cause of death can be inaccurately assumed for many reasons. Research on autopsy results in the late 20th century showed that if an autopsy was completed the results would reveal a different cause of death than originally diagnosed 32 % of the time. When it is considered that autopsies are only completed selectively in about 5% of hospital deaths, it would seem to create a very significant margin of error in cause of death statistics (Hanzlick, 2001). If a more accurate estimate is desired on national rate of medical error fatalities, there may need to be a move toward random selection in autopsies and for them to be completed at higher percentages.
Another issue in the accuracy of the data is the underreporting of medical errors. A study was completed internationally on the barriers to reporting medical errors. The study anonymously surveyed medical professionals. Of the 329 respondents, 191 admitted to having made errors and 96 of those had made an error without reporting it. Within those who responded 29% of a variety of medical professionals had made errors without reporting them. The 2 highest reasons given for why they felt medical errors were non-reported was a lack of an efficient system for reporting and a lack of personal attention to the importance of medical errors. Though most of these errors made likely did not result in death, the realization that medical professional would knowingly underreport errors is a significant when added to how many errors were also unknowingly committed (Poorolajal, Rezaie, & Aghighi, 2015).
Another issue -
The study by Makary and Daniel, while flawed in its procedure, does prove an example of another issue – money and politics. The reason for their new presentation of older study was an effort to gain interest and hopefully research focus and funding on this issue. The leading causes of death get the most money for research because they appear to be the first things that should be dealt with by the medical community. They listed medical errors as 3rd in the causes of death and thus stating the need for greater focus and funding in this area (Abbasi, 2016). In 1999, when the Institute of Medicine published a study saying that at least 44,000 and upwards to 98,000 die from preventable medical errors both Congress and the president were reacting and moving towards further studies and funding to improve this factor within two weeks (Leape, 2000). Makary and Daniel were trying to revive this reaction and by some opinions scare America into making changes. It can be questioned though, whether the practical ideas they presented on the need for better data collection and research were not lost within the arguments over their numbers (Prasad, 2016).
Conclusion -
An elderly woman experiencing sudden abdominal pain went to the hospital and ended up being diagnosed with cancer that that had spread to 2 organs. Within 10 days she went from active and living alone to dying because her system never recovered from the tests the hospital performed to reach this diagnosis. Not knowing how significantly the cancer had already damaged her kidneys, the doctors had no reason to assume her body would not be able to recover from the diagnostic test. By broad definitions this could be ruled death caused by medical error as the patient would have continued living and the direct cause of death would have been completely different. But had the tests not been performed and she died 2 months later with undiagnosed cancer, it could have equally been recorded as diagnostic error. The circumstances of this woman’s death provide helpful information on possible adverse effects of the tests run. However, that data should not be included in broad definitions of medical error in treatment or diagnosis that can be used to scare the general public or condemn the medical profession. Until better definitions are written and understood by all professions who write and process the data of cause of death certificates all estimates just be will be guesses. Guesses are dangerous in an issue with major personal, emotional, and legal implications. For research purposes, blame and fault needs to be taken out of the data record to encourage openness in reporting and a willingness of medical professionals to accept any implicates of the data.
References
Abbasi, J. (2016). Headline-grabbing study brings attention back to medical errors. Journal of the American Medical Association, 316(7), 698-700.
Allen, M. & Pierce, O. (2016). Medical errors are no. 3 cause of U.S. death, researchers say, NPR, [audio program transcript]. Retrieved from http://www.npr.org/sections/health-shots/2016/05/03/476636183/death-certificates-undercount-toll-of-medical-errors
Ayres, Ian. (2007). Super Crunchers. New York: Bantam.
Best, Joel. (2004). More Damned Lies and Statistics: How Numbers Confuse Public Issues. London: University of California Press.
Brennan, T. A., Leape, L. L., Laird, N. M., Hebert, L., Localio, A. R., Lawthers, A. G., Newhouse, J. P., Weiler, P. C., Hiatt, H. H. (1991). Incidence of Adverse Events and Negligence in Hospitalized Patients: Results of the Harvard Medical Practice Study I. New England Journal of Medicine, 324, 370-6. DOI: 10.1056/NEJM199102073240604
British Medical Journal. (2016, May 4). Medical error is third biggest cause of death in the US, say expert [Press Release]. Retrieved from http://www.bmj.com/company/wp-content/uploads/2016/05/medical-errors.pdf
CDC. Mortality multiple cause-of-death public use record 2014. National Vital Statistics System. Retrieved from http://www.cdc.gov/nchs/data/dvs/Record_Layout_2014.pdf
Generations (2015). Truth and transparency: a conversation with Dr. Martin Makary of fairness, patient choice, and optimal outcomes. 39(1), 65-8.
Hanzlick R. (2001). The Autopsy, medicine, and mortality statistics: National Center for Health Statistics. Vital Health Stat 3(32). Retrieved from https://www.cdc.gov/nchs/data/series/sr_03/sr03_032.pdf
Harris, C. T. & Peeple, R. A. (2015). Medical errors, medical malpractice and death cases in North Carolina: the impact of demographic and medical systems variables. Contemporary Readings in Law and Social Justice, 7(2), 46-59.