Using clinical decision support to get the right diagnosis the first time

Joseph Britto is co-CEO of Isabel Healthcare, a clinical software vendor that helps clinicians with diagnosis. He practiced medicine in the UK before joining with co-CEO Joseph Maude to start Isabel, named after Joseph’s daughter who was wrongly diagnosed with Chicken Pox and nearly died as a result. Joseph has a personal connection as he was the physician in charge of Isabel’s recovery.

Remember President Bush’s goal, first stated in the 2004 State of the Union message, of giving “every American” his own EMR by 2014?

That goal seems as elusive as ever, especially in light of a recently released study by the The Center for Studying Health System Change which found a discouragingly low rate of EMR adoption among physicians. The new study, released last month, reported that only 29 percent of the hospitals surveyed were actively supporting physician acquisition of EMRs through financial or technical support. This number was disappointing in light of the current government initiative that has relaxed federal rules on physician self-referral and made available hundreds of millions of dollars in various subsidies for EMR adoption by physicians.

Many health policy experts believed that “if you subsidize it, they will come.” While that approach has worked in persuading people to take mass transit, it hasn’t lured many physicians into using EMRs.

Why the reluctance? One reason is cost. On September 25, 2008, the Certification Commission for Healthcare Information Technology (CCHIT) issued a report that reviewed 90 EMR incentive programs (state, federal, private) with a total funding of $700 million available.

Health Industry Insights,
a private research firm, reviewing the CCHIT report, estimated that the
cost to implement an EMR is roughly $25,000 per physician and that the
$700 million currently available would represent only 9% of the
expected total national cost  to furnish all physicians in private
practice with an EMR.

As we endure financially difficult times, we believe it is time for IT leaders at hospitals and medical groups to take second look at a different set of technologies, one which, like EMRs, can align physicians and hospitals in the shared goals of improving patient care and reducing clinical risk.

Clinical decision support (CDS) technology is not new, it has been available in various forms since 1986, but as computer hardware has become vastly more powerful, the newer versions of the systems have become faster and more practical for physicians to use. One particular kind of CDS technology, diagnosis decision support (DDS), has been adopted in many hospitals in the past two years, as medical executives realize its value in attracting leading physicians who understand and value medical knowledge tools. 

DDS systems, as defined by a leading medical textbook, “link health observations with health knowledge to influence health choices by clinicians for improved health care.”

DDS systems include two key components: a dynamic medical knowledge data base and an inferencing or logic engine to sort and select decision options for clinicians.

Medical leaders have been looking at computers as potential tools to improve clinical decision-making since the early mainframe systems were first installed in hospitals in the 1960s.  After many years of development, one of the first  DDS systems, Dxplain, was installed at Massachusetts General Hospital in 1986, with a data base including 2,000 diseases.

These early versions of DDS technology were frustratingly slow. At the heart of these early systems was a crude form of artificial intelligence (AI). The software required the input of multiple experts to provide semi probabilistic relationships between thousands of clinical features and hundreds of diseases.

These early systems required physicians to spend a considerable amount of time interacting with them, answering a hierarchy of questions. Published trials reported that it took physicians 20 or 30 minutes to enter the data and arrive at a final set of decision options.

Dr. Robert Wachter is Associate Chairman of the Department of Medicine at the University of California, San Francisco and author of two books, Internal Bleeding: The Truth Behind America’s Terrifying Epidemic of Medical Mistakes and Understanding Patient Safety. He has oft written of the frustrations and “overhyping” of the early diagnosis decision support programs.

According to Dr. Wachter, “the disappointment over the ineffectiveness of the early programs led to widespread skepticism that any DDS could help physicians be better diagnosticians. This skepticism is getting in the way of today’s markedly improved systems, such as the Isabel System, from gaining the traction they deserve.”

Today’s computer systems are thousands of times more powerful than those of the 1980s. This vastly improved performance has enabled a variety of different clinical decision support systems to be adopted in hospitals, large and small, across the country. CDS systems today provide clinicians with prescribing decision support, image recognition and interpretation, therapy planning and patient alerts.

My company, Isabel Healthcare, makes a diagnosis decision support that uses  advanced pattern recognition software from Autonomy Inc. The use of pattern-matching software, rather than keyword searching or Boolean query techniques, enables searches to be made against a complex cluster of signs and symptoms entered in free text and the results to be returned as a list of likely diagnoses . Diagnoses are then linked to knowledge effectively allowing the DDS to mobilize knowledge from disparate sources around specific diagnoses right at the point of care.

The Isabel System contains a knowledge library of more than 100,000 documents made up of medical journal articles and textbooks and it is continually updated. Physicians using laptop computers can enter queries in free text and receive a list of the most likely diagnoses in seconds thereby helping them reduce excessive bed days due to delays in diagnosis, improve the appropriateness of testing and reduce clinical risk.

While hospitals have found value in many different kinds of clinical decision support systems, we believe diagnosis support is particularly important. As Dr. Wachter has noted, until we resolve the issue of diagnostic errors, we face a fundamental problem in patient safety:that hospitals can be rewarded for high quality in performance even if every diagnosis was wrong.

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