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Saturday, July 12, 2014

"No clinical metric conforms to a six sigma standard"

Nortin Hadler, MD, posting on THCB:
"If patients were widgets, if care givers were production workers, and if caring conformed to “six sigma” principals [sic], even slight deviations from standards of care would be as easy to recognize, those responsible could be singled out for improvement, and remedies would be obvious. This is the mantra of the quality agenda that drives health policy. In a corollary exercise in linguistic determinism, health economists and hospital administrators are wont to speak of patients as “units of care”, physicians as “providers”, and clinical demand as “throughput.”  But manufacturing cell phones or producing fast food has little in common with managing the care of patients in all their variability and with all their unpredictability. No clinical metric conforms to a six sigma standard; we in medicine are barely comfortable defining “normal” with a 95% confidence interval and we are fully aware that “outliers” can be clinically normal and those in the normal range can be abnormal. Forcing the clinic into the six sigma paradigm is worse than an exercise in futility; it is an exercise in iatrogenicity."
When Dr Hadler speaks, we do well to listen. His criticism of Health IT goes beyond the usual UX carping:
"It was the end of a long day in clinic a couple of weeks ago. I found myself sitting next to a colleague, a young, talented and well-read academic orthopedic surgeon. Each of us was staring at a computer screen displaying our “Physician’s Dashboard”, the gateway to the granularity-generating Electronic Medical Record (EMR) purveyed by EPIC. EPIC is a privately-held, exceedingly profitable company that dominates the multi-billion dollar EMR marketplace. Both of us are novitiates with the interface; UNC Hospitals only recently “went live” with EPIC at great cost in terms of personnel time and in terms of hundreds of millions of dollars. I was grumbling as I fought with the program to create a clinically useful medical record for the sake of the patients I had been seeing that day. My surgical colleague urged me to create templates and “smart sets”; he found EPIC easily manageable thanks to these short-cuts to record keeping which took advantage of any and all aspects of patient care that were stereotypical.

First, I took him to task on behalf of my patients. I explained that for a rheumatologist like me, and all others who are labeled “cognitive” specialists, the care of the patient revolves around the “granularity” of the narrative. I needed to listen actively to my patient to understand the particular idioms that populate any narrative of distress. And I need to communicate the approach the patient and I would take to sorting out the illness and formulating management to all involved in this patient’s care. It is an exercise that takes advantage of individual differences and idiosyncrasies rather than pummeling narratives into common denominators. I never assume the average, nor do I ever presume the outcome. Templates and “smart sets” are anathema."
Read the entire post, including the comments. Lots to think about. For openers, it has me reaching back down in the Weeds'

Essential to health care reform are two elements:  standards of care for managing clinical information (analogous to accounting standards for managing financial information), and electronic tools designed to implement those standards. Both  elements are external to the physician’s mind. Although in large part already developed, these elements are virtually absent from health care. Without these elements, the physician continues to be relied upon as a repository of knowledge and a vehicle for information processing. The resulting disorder blocks health information technology from realizing its enormous potential, and deprives health care reform of an essential foundation. In contrast, standards and tools designed to integrate detailed patient data with comprehensive medical knowledge make it possible to define the data and knowledge taken into account for decision making. Similarly, standards for organizing patient data over time in medical records make it possible to trace connections among the data collected, the patient’s problems, the practitioner’s assessments, the actions taken, the patient’s progress, the patient’s behaviors and ultimate outcomes.

Two basic standards of care, and corresponding tools, bring order and transparency to medical decision making:
  • First, from the outset of care, relevant patient data must be chosen, and its implications determined, based on the best available medical knowledge, independent of the limited personal knowledge of the practitioners involved. Patient data must be systematically linked to medical knowledge in a combinatorial manner, before the exercise of clinical judgment, using information tools to elicit all possibilities relevant to the problem situation, while defining and documenting the information taken into account. Practitioners’ clinical judgments may add to, but must not subtract from, high standards of accuracy, completeness and objectivity for that information.
  • Second, in complex cases, particularly in cases of chronic disease, the organization of data in medical records must be optimized for managing multiple problems over time. This means that each medical record must begin with a complete list of carefully defined patient problems, and that other clinical information in the record must be linked to the problem or problems to which it relates. Without that structure for the medical record, decisions are made out of context, follow-up and coordination of care are haphazard, and records are not usable for rigorous clinical research.
With these two basic standards of care, and the information tools needed to implement them, practitioners and patients can manage the flood of detailed information required for sound decision making over time. With this detailed information, made usable for research in structured electronic medical records, medical care can become increasingly refined and individualized. In contrast, so-called “evidence-based medicine” is derived from large population studies that fail to account for the medical uniqueness of each patient.

Enforcing the necessary standards and tools depends on changing medicine’s culture of professional autonomy for highly educated physicians. Indeed, the concept of a physician as we know it is not viable. All practitioners must submit to meticulous definition and control of their inputs to care (a principle recognized by the patient safety movement). The primary barrier to this cultural change is graduate medical education and credentialing. These social institutions (1) fail to define, disseminate and enforce high standards of quality for provider inputs to care, (2) inhibit effective design and use of information technology to manage clinical information, and (3) suppress competition among providers who might otherwise exploit information technology to generate remarkable advances in patient care and medical knowledge.
“The consequences of that digitization of information in a reasonably systematic way, guided by meaningful use, will have enormous, difficult to predict, and generally positive effect on the American health system over a generation to come. That’s my view of it. I know that physicians find certain aspects of meaningful use problematic. Some find it too aggressive. Some find it not aggressive enough. But, I still think it was a reasonable way to proceed, and we’ll see the results over decades.”

- David Blumenthal, MD

The Misuse of Meaningful Use, Part II

Originally Certified EMRs and Meaningful Use policies were created so as to provide the financially incentive to encourage primary care physicians to adopt electronic medical record programs and then use these electronic medical record programs according to specified “meaningful use” mandates. It was the hope that the appropriate use of EMRs would improve the quality or reduce the cost of healthcare. Since the program’s introduction, Meaningful Use has been expanded to almost every medical specialty and subspecialty, regardless of the appropriateness/relevance.

There has now been a fair amount of data accumulated regarding the effectiveness of electronic medical record programs. Unfortunately, most of the published data is not high quality and the majority of clinical trials are now being funded by the EMR industry. As we have seen with clinical trial sponsored by the pharmaceutical industry, only an irrational person would accept the results of a vendor sponsored EMR trial on face value...

In recognition of the federal government’s desire to promote electronic medical record programs, and despite the lack of “proof of efficacy,” the Massachusetts insurance industry appears to feel that they too should promote the use of EMRs/ and Meaningful Use. As a result, some of the large Massachusetts insurers are including clauses in their contract which mandate that physicians use certified EMRs according to Meaningful Use standards, and they are applying these mandates both to primary care physicians and specialists.

Given the lack of objective data about the effectiveness of EMRs, this is an outlandish overreach by the Massachusetts insurance companies which will interfere with the patient-physician interaction. As a practicing physician I am appalled to learn that the Massachusetts insurance companies seriously believe that they know how I should structure the use of my time in the exam room...
Read all of it, including the comments. Massachusetts is trying to be the first state to make Meaningful Use Certified EHR use a condition of physician licensure and insurance carrier acceptance. We'll see how that plays out.


The past decade has witnessed an explosion of electronic health data. Diagnostic images, lab results, and biometric information are generated and stored in digital form. Key elements of medical records are abstracted using natural language processing. Medical claims provide a treasure trove of longitudinal data. Those who bring these disparate threads together and apply them to real-life situations have created the next big thing in health care: big data.

Big data has the potential to improve clinical decision making at the point of care. Tapping into vast databases, a physician can access knowledge relevant to the individual patient, yielding better decisions and outcomes. Big data also has the potential to revolutionize research. Massive databases enable observational studies on a scale and at a speed randomized controlled trials cannot approach...
I now subscribe. Stay tuned...





Building Clinical Care Software Systems, Part I: Issues and Challenges

by Jerome Carter on July 14, 2014
Creating software is hard. The entire process, from deciding that a piece of software is needed to implementation, requires analysis and problem-solving–every step. I was reminded of this reality anew when I began the latest round of coding for my seemingly mythical startup. There are so many decisions to make that affect the final product, even though I consider what I am trying to build to be fairly straightforward in design and features. Building a good clinical care software system is many times more difficult.

Given the troubles that are plaguing EHR vendors in meeting MU stage 2 requirements, this seems like a good time to talk about what goes into building a system that supports clinical care...
Well worth your time. Jerome is definitely a SME. Below, I annotated his table of the components of Health IT architecture.

Recall my "standard data dictionary" rant:
One. That’s what the word “Standard” means -- er, should mean. To the extent that you have a plethora of contending “standards” around a single topic, you effectively have none. You have simply a no-value-add “standards promulgation” blindered busywork industry frenetically shoveling sand in the Health IT gears under the illusory guise of doing something goalworthy.

One. Then stand back and watch the private HIT market work its creative, innovative, utilitarian magic in terms of features, functionality, and usability. Let a Thousand RDBMS Schema and Workflow Logic Paths Bloom. Let a Thousand Certified Health IT Systems compete to survive on customer value (including, most importantly, seamless patient data interchange for that most important customer). You need not specify by federal regulation (other than regs pertaining to ePHI security and privacy) any additional substantive “regulation” of the “means” for achieving the ends that we all agree are necessary and desirable. There are, after all, only three fundamental data types at issue: text (structured, e.g., ICD9, those within other normative vocabulary code sets, and unstructured, e.g., open-ended free-form SOAP note narratives), numbers (integer and floating-point decimal), and images. All things above that are mere “representations” of the basic data (e.g., text lengths, datetime formats, Boolean/logical, .pngs, bmps, .tiffs, .jpegs etc)...

More to come.

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