Tools, Technologies and Training for Healthcare Laboratories

Medical Errors - Complexity and Solutions

An updated version of this essay appears on the Nothing but the Truth about Quality book.

Recently, a JAMA study revealed that medical errors cost the US at least $9 billion in extra charges and treatment, and kill over 32,000 people, every year. Also recently, a Misys software flaw was discovered, "work-around-ed", and patched. Still more recently, everyone has been talking about getting their processes "Lean." What's the unifying thread here? Complexity and its many solutions: automation, computerization, and simplification. Examine the stories of the day and understand the source of today's problems - and maybe even understand where problems will occur in the future.

October 21, 2003

Recently, there has been a strange convergence of news about healthcare. Usually it is relatively hard to find stories in the mainstream media that have relevance to the laboratory. But over the course of a recent week, there was a storm of news and new information that is relevant to our work.

More medical errors in the news

First and foremost was the release of yet another study showing the financial impact of medical errors. A study that appears in the Journal of the American Medical Association, "Excess length of Stay, Charges, and Mortality Attributable to Medical Injuries During Hospitalization", estimated that - for just 18 specific categories of injury - medical errors extend hospital stays by a combined 2.4 millions days per year, adding up to 9.3 billion dollars in hospital charges, and kill 32,500 patients per year.[1]

While even the authors admit that this was an imperfect study, based on computer analysis of just 18 diagnostic codes that have been associated with medical injuries, the study nevertheless provides another sign that medical errors are a huge cost, both in lives and in dollars. Coming on the heels of the well-known 1999 Institute of Medicine report that estimated up to 98,000 deaths a year occurred in hospitals due to medical errors, it looks like we will soon have a chorus of evidence in the literature saying that healthcare has serious quality problems.

With such strong evidence, it will be easier for executives in healthcare to devote more resources to the improvement of patient safety. Before, patient safey efforts were largely a defensive move - you invest in patient safety to prevent being sued by injured patients, and to prevent being shut down by the government. This was a compliance mentality - do just enough to comply with the regulations, but no more, since the additional cost would take away from the bottom line. Now it becomes clear that medical errors are such a big cost that improving patient safety will save lives, insure compliance, and improve the bottom line for healthcare businesses.

We certainly are not shocked that better quality leads to more efficient care and avoids the greater costs of errors caused by poor care. Prevention costs are always lower than failure costs, particularly in healthcare.

Lean Six Sigma for service

A new book has just been published on Lean Six Sigma for service organizations [2]. “Lean” is an improvement methodology that focuses on reducing the time required to complete an operation or production. Six Sigma, as regular visitors to this website know, is an improvement methodology that focuses on reducing errors. Together, Lean Six Sigma provides an approach for improving both efficiency and quality.

The convergence with the story on medical errors has to do with one of the cited causes of errors - postoperative foreign bodies, i.e., leaving a sponge, instrument, etc., in the patient. The "rate per 1000 discharges at risk" was 0.09, which would be 90 DPM or a 5.25 sigma process. That's generally considered to be pretty good performance, but obviously, still not good enough for the health of our patients. Improvement is still needed, but what to do?

George's book includes an example dealing with surgery.[3] "It is standard in medicine for every surgeon to specify his or her own surgical tray of instruments and supplies for any procedure. In Stanford's cardiac surgical unit, that meant there were six different surgical trays for each type of case, one for each surgeon."

Wonder why hospitals can't keep track of the materials that end up inside patients? It's the complexity introduced by the individual physicians - the "art of medicine"! By standardizing the materials on the surgical tray, Stanford simplified operations, improved quality, and saved material costs of $25 million by reducing the number of materials and the number of suppliers.

According to George, the benefits of adding Lean to Six Sigma include the following:

  • Lean focuses on maximizing process velocity;
  • Provides tools for analyzing process flow and delay times at each activity in a process;
  • Centers on the separation of ’value-added’ from ‘non-value-added’ work with tools to eliminate the root causes of non-value added activities and their cost;
  • Provides a means for quantifying and eliminating the cost of complexity.”

[ In the next few months, we will provide you with more background on Lean and its methodology and tools for simplifying processes. ]

Automation and Computerizaion - partial solutions for complexity

Another solution being recommended to deal with the complexity of healthcare processes is Information Technology. In the wake of the 1999 IOM report, the FDA began recommending that processes now done by hand, like drug and order-entry, be computerized. By automating processes, we should avoid the errors introduced by manual methods - a similar trend occurred in diagnostic testing decades ago, you may recall. The software and Internet revolution have created an explosion in solutions and systems for healthcare. There are electronic medical records, hospital information systems, decision support systems, imaging and archiving systems, and our familiar laboratory information systems. Today's doctor, who once wrote everything by hand onto paper patient charts and paper prescription slips, is increasingly using software to document patient diagnoses and treatment. The patient record may be stored on a central server inside the hospital, which the doctor can consult from any monitor within the hospital. Test orders and results can also be done through browsers on the internal "web" of the hospital.[4]

However, there is a cautionary note. We have the recent news that software from Misys had been recalled or withdrawn from the market because of defective performance. B-AUT-RAPID-LAB Software versions 5.2, 5.23, and 5.3 has demonstrated "a defect that could result in inaccurate results being used in the diagnosis and treatment of patients". In other words, "it was failing to check that all necessary steps in certain tests were being carried out. This would allow faulty tests to be returned to doctors". Some test results that should have been rejected by the software were getting through and being reported and recorded in patient medical records.[5]

Misys represents one of the largest information system providers in the industry, and they represent the consolidated might of Sunquest and Antrim. They have systems for nearly every aspect of healthcare, from clinical decision support, clinical patient record, clinical decision entry, and of course laboratory information systems. To their credit, when the flaw was detected by customers, Misys immediately and dutifully notified the FDA. Misys then issued a "work around" to the affected customers, then created a "patch" to fix the error in the existing installed software. Finally, new software versions will not have that flaw. All in all, Misys did a good job of handling the error. But they are one of the bigger companies, and the fact remains that this is one of the few publicly reported errors with an LIS. We don't have a true picture of how often errors like this occur, or how often they are detected.

An error of this sort is very, very hard to detect. Nothing on the flawed lab report would look different to the doctor. It's possible that nothing would look different to the lab technologist, who would simply see results being reported out. And certainly the patient would have no way of knowing that there was a software flaw deep in his or her treatment. Perhaps only a very knowledgable lab manager or pathologist would be able to figure out what was going on - by manually checking the test process against what was happening with the software. And then only a software engineer could really do anything about the problem.

We will increasingly see errors of this nature, software bugs in clinical systems that are subtle, hard to detect, and difficult to fix without the specialized technical skills of both a software engineer and an expert in medical care and test diagnosis. These errors exceed our capability to detect them and to fix them, particularly with the de-skilling of the laboratory workforce. A further problem will be that our reliance on this technically sophisticated system will mean that we have to wait for a fix from the software provider. While we wait, we may be forced to "go low tech" and use those old manual processes again, which will inevitably lead to even more errors.

Complexity, Automation, and Computerization

Information Technology has been presented to us, in healthcare, as the solution to the problems caused by our old, manual, error-prone ways. And yet as we see in the case of Misys, we may not have eliminated errors - we may only have replaced them with new errors.

There is a hidden truth here, a characteristic of healthcare that makes it distinct from many other industries. Here is the truth: healthcare has a complexity problem that can't be eliminated just by automation or computerization. In some cases, automation and computerization will in fact amplify the problems caused by the complexity of healthcare. As a result of this trait, healthcare doesn't scale as well as other industries do, and the savings that come with scale elsewhere may never be reaped in hospitals and laboratories.

Why is this true? Here we call to our aid the author Eward Tenner, who wrote an illuminating book called Why Things Bite Back: Technology and the Revenge of Unintended Consequences [6] as well as the work of the sociologist Claude Perrow, as quoted in Tenner's book.

From Mr. Perrow we get some critical definitions. He introduces us to the concepts of complexity and tightly coupled systems. A tightly coupled system is one in which errors can travel rapidly from the error source to the entire system - as opposed to a loosely coupled system, where errors remain localized at the source. A tightly coupled system propogates errors quickly. An example of a loosely coupled system would be a car, where a dent on the fender doesn't impede the performance of the vehicle. Contrast that with the Shuttle Columbia, where a hole in the wing produced a catastrophic failure during re-entry. The Shuttle is, without doubt, a tightly coupled system.

Finally, a complex system is one in which the effects of an action on a system are not predictable. When you have a complex and tightly coupled system, you have errors that spread quickly in unpredictable ways.

What is healthcare if not a complex, tightly coupled system? The body itself is complex and tightly coupled - why else would a drug intended for heart patients (Viagra) have the unexpected effect of increasing libido? Complications and side effects reveal how unpredictably the body reacts to drug therapy.

On top of that we lay another complex, tightly coupled system: the heathcare business. Doctors, nurses, medical technologists, government agencies, HMOs, PPOs, diagnostic and reagent manufacturers, their engineers, their marketing and sales personnel (who define the priorities of the instruments), their technical support staff - how much more complex and unpredictable can a system get? That we are told that medicine is an "art" is an overt admission of complexity and unpredictability. Art is inherently unpredictable.

In other businesses, complexity can be reduced by the application of technology and automation, making processes easier to manage and more profitable in execution. For instance, given equal traffic volume, a paved road requires far less maintenance than a dirt or gravel road,. The automobile is another case where advanced technology has made it simpler for the driver - there are fewer gauges on a modern car (for instance, no oil pressure gauge), and more safety devices (passive and active) to protect the passengers. The rise of industry is the history of successfully applying technology and automation to reap profit through scale.

Our expectation is that as technology advances in healthcare, it will have more safeguards, require less skill and attention, and reduce the "art" of medicine to a science. Businesses in healthcare expect that the advanced technology will mean less need for human attention - that is, the healthcare professional can manage more patients because each patient will require less attention. In the lab, we expect that the advanced technology will allow us to process more tests while requiring less attention from us - and perhaps less skills from laboratory personnel.

"But because the human body is a tightly coupled system, in which treatments can make parts interact in unexpected ways, advanced medicine usually requires more rather than less human attention. More and more care becomes intensive, potential complications multiply, and deviations can be fatal. For physicians, new technology requires more rather than less craft. For all health workers, it demands more rather than less vigilance. Medicine costs as much as it does not simply because machines are so expensive, but because successful medical technology multiplies the need for nontechnical services." [7]

The reality that we may have to face in healthcare is that our technology may automate and speed complex operations, but it may never be able to make them simple. Software and information technology will automate processes, and produce results at a dizzying pace. Tests can already be generated faster than the lab's ability to review them - hence the invention of autoverification. But who verifies the autoverification software? Who provides the quality control for the software that provides quality control?

Conclusion: Complexity and the importance of Lean and Six Sigma

There is no case for luddite medicine. We cannot maintain a system where illegible handwriting can cause an improper dose of medicine. But the automation and computerization is not a panacea. Even greater scrutiny will be necessary to monitor the software that automates today's error-prone manual processes. That's why processes must be improved in addition to being automated and computerized. That's why the methodology and tools of "Lean" are becoming more and more important.

Lean and Six Sigma are critical methodologies that will help us to reduce the complexity of systems. Eliminating sources of errors, standardizing and speeding the processes, will help to rid us of many of the problems in the current system. Both are also active methodologies - you don't just do them once and sit back. You continually apply them to further and further reduce complexity, eliminate errors, and improve the process performance and speed.

Undoubtedly this makes our life a bit harder. We can't simply assume that the software and instrumentation we buy is going to work correctly. We have to improve our competencies and increase our vigiliance. But that's our job as laboratory professionals. Whether or not advanced technology makes our job easier, it's our responsibility to master those details and make the patient's journey through the healthcare system better.

If we don't do our job, then we pass that task onto our already overburdened patients. In addition to worrying about the qualifications of the physician who is treating them, a patient may soon have to ask, "Are you giving me healthcare version 1.1 or version 1.2, the workaround/patch/upgrade?”

References

  1. Bell, Julie, "Study of medical errors puts tentative price tag on impact: Hospital charges alone boosted 9.3 billion a year", October 8, 2003, Sunspot website, http://www.sunspot.net/news/nationworld/bal-te.mederrors08oct08,0,3967002.story?
  2. The specific report is Zhan C, Miller MR. Excess length of stay, charges, and motality attributable to medical injuries during hospitalization. JAMA 2003;290:1868-1874.
  3. George ML. Lean Six Sigma for Service. McGraw-Hill, New York, 2003.
    Ibid, pp.10-11, 169-178.
  4. Kolbasuk-McGee, Marianne,"Providers turn to IT to reduce Healthcare Errors", October 8, 2003, InformationWeek, http://www.informationweek.com/story/showArticle.jhtml?articleID=15201841
  5. Reece, Damian, "US forces Misys to withdraw hospital software", money.telegraph website, October 12, 2003, http://www.money.telegraph.co.uk/money/main.jhtml?xml=%2Fmoney%2F2003%2F10%2F12%2Fcnmisys12.xml&secureRefresh=true&_requestid=208470.
  6. Tenner, Edward, Why Things Bite Back: Technology and the Revenge of Unintended Consequences, Vintage Books, New York, 1996
  7. Ibid, p.59.


James O. Westgard, PhD, is a professor of pathology and laboratory medicine at the University of Wisconsin Medical School, Madison. He also is president of Westgard QC, Inc., (Madison, Wis.) which provides tools, technology, and training for laboratory quality management.