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Outcome Data – One Key to
Consumerism In order to introduce Consumerism into health care commerce, it is necessary to measure outcomes by providers. Without reliable information about the success rates of a particular treatment by a particular provider, it is impossible for a patient to choose wisely. While it is true that medical outcome data is particularly difficult to fairly measure, it is not impossible. The Utah Association of Health Underwriters recommends that the Department of Health be required to develop and collect outcome data from its licensees. They should not rank or judge the data in any way, but rather just make it available. Outcome data requirements will vary widely depending upon specialty. The DOH should work with provider associations to collect meaningful information. We believe that it is not necessary to allow the general public direct access to complex provider outcome statistics. This would subject providers to misinterpretation that may cause an unfair and unnecessary loss of reputation. It would not hurt Consumerism to limit outcome data to professional data analysts and allow them to charge consumers for their interpretations. While we would rather have the private sector accumulate data, it would require some independent organization to do so. Lacking that, the DOH seems like a logical choice. The DOH could gather data either directly from the providers or they could combine private sector and government claims statistics behind the scenes. Or they could do some combination of both. A centralized data center has many advantages. First of all it is much more efficient to have a central data depository rather than isolated pockets of information. Second, statistics are more reliable when they include all of the data. And most importantly it will give providers a way to improve their patient care. Insurance companies will be able to analyze all the data instead of just their share of the market. Physicians will be able compare their own outcome statistics to those of their peers. The State will be able monitor the health care needs and trends of all Utahans. And the public will be able to access appropriate information to help choose the care that they need. Clearly a Consumerism system of outcome statistics will help improve quality and lower the costs of health care commerce. How Complex Medical Data Can Become Useful There are lessons to be learned from the pension market that apply here. Pensions use to be primarily defined benefit. This meant that the pension promised a certain monthly benefit based on one’s total years of service and salary. The pension manager took full responsibility for the investments, making sure that this promise was kept. The consumer simply cashed their monthly checks. But then things changed from defined benefit to defined contribution. In essence, employees were given an “investment coupon” and allowed to invest in whatever they wanted. At first, experts believed that the average Joe could not possibly understand the marketplace and would be unwise with their investments. But it turned out that; a) Joe could understand investments, and b) Joe didn’t have to understand to invest wisely. Now in hindsight, 401(k) type investments on average, managed by a bunch of “Joe’s”, actually have out performed the old pension manager’s rates of return. How did Joe become so sophisticated? He didn’t. Joe lets experts interpret the data and explain it to him in a way he can understand. He watched MSNBC and Bloomberg. He read Morningstar & Motley Fool reports. Basically Joe found that the free market of data analysis gave him timely and accurate analysis of those complex SEC filings required for publicly traded businesses. Health care data will go through the same process. “Jane” does not have to interpret complex surgical outcome data to pick a doctor for her shoulder replacement. She just has to subscribe to WebMD, Milliman actuaries, or some other data broker that hires epidemiologists and statisticians to analyze and grade the outcomes. Jane lets them figure it out and rank the providers. She then takes her Benefit Credit and decides which doctor has the optimal global price and outcome combination for her. While some outcome data is very tricky to interpret correctly (the best surgeons tend to be referred the most difficult cases), some is quite easy. For example, a simple count can be reasonably effective in gauging an approximation of quality: · Surgeon A did 100 standard surgeries a year – all successful, and 10 complex cases – 3 of which died. · Surgeon B did 160 standard surgeries last year with one death. · Surgeon C did 12 standard surgeries, no deaths. While surgeon C had the best “results”, the simple count suggests that Surgeon A is the most skilled, because no one else touches the complex cases. Even Surgeon B may be a better choice than C because he seems more experienced. Of course more data is needed to get a more definitive answer. Similarly, a diabetic might want to know how many other diabetics that his physician treats. If he is one of only three, there may be good reason to change to a doctor that treats 80 diabetics – even without knowing the outcomes. Thus, UAHU would propose that we start gathering data with a simple count of procedures and treatments. Then allow each provider specialty area to develop their own unique set of outcome measures as they see fit. These complex measures would be developed based on a consensus of providers and the DOH. |
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