Big Data // Big Data Analytics
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8/20/2013
11:14 AM
Paul Cerrato
Paul Cerrato
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Why Physicians Don't Like Big Data

It limits their options. That's not always bad.

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Remote Patient Monitoring: 9 Promising Technologies
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Dr. Venkat Warren worries in a recent Wall Street Journal article that "some bean-counter will decide what performance is," and fears that the application of big data analytics and the pressure to meet a long list of performance metrics might force clinicians to avoid caring for older and sicker patients who could drag down their performance numbers. "If it isn't cost-cutting, what is it?" says Warren, a cardiologist in California's MemorialCare Health System.

Warren is not alone in his concern. Dr. Thomas Santo, a physician who lives and works in New York City, has come to a similar conclusion: "… for any physician who sees their reimbursement cut by providing 'sub-optimal care,' as deemed by CMS [the Centers for Medicare and Medicaid Services], what is to stop them from refusing to serve their sickest, most chronically ill and frequently hospitalized patients? In so doing, they raise the 'quality' of care they provide, and lower the cost at the same time …"

Many doctors also rightly point out that their scores in a pay-for-performance system are not completely under their control. They might do their utmost to make sure all their Type 2 diabetic patients get regular eye exams to check for retinopathy, for instance, or urge patients to take their oral hypoglycemic drugs. But when patients don't care enough about their own health, or are forced to choose between paying the rent and buying their medication, a doctor's metrics are going to suffer.

[ Time to start a family? Read Big Data Knows When You're Fertile. ]

The problems tied to economic disparity were well documented in a Harvard study that evaluated the performance rankings of primary care physicians. Their conclusion: "Among primary care physicians [PCPs] practicing within the same large academic primary care system, patient panels with greater proportions of underinsured, minority, and non–English-speaking patients were associated with lower quality rankings."

What's even more frustrating for doctors -- as well as the bean counters -- is if all the performance metrics are put in place and the system still doesn't generate savings.

The latest data from the Pioneer ACO program drives home that point. Thirty-two accountable care organizations enrolled in the experiment have been participating in the Medicare program for about a year. And in that time, all 32 have been able to demonstrate that pay for performance does in fact improve the quality of care. Patients have received more cancer screenings and blood pressure control has improved, for example. But only 18 of the ACOs managed to lower costs for their Medicare patients.

Although this research suggests that pay-for-performance metrics can frustrate both clinicians and CFOs, it's an overstatement to conclude that data analytics has no value in healthcare. Such analysis has demonstrated that many tests and treatment protocols have been oversold to the profession and to the public and need to be limited.

Among the tests and procedures that are probably wasting money because there just isn't enough scientific evidence to support their use: screening EKGs in healthy adults, routine annual Pap tests in women between 30 and 65, performing labor induction or cesarean delivery before 39 weeks when there is no medical indication, and giving antibiotics to a child with a sore throat, cough or runny nose. The list goes on and on.

And lest you think the list of unsupported tests and procedures was put together by a group of heartless efficiency experts, it's worth mentioning that it was compiled by the American Board of Internal Medicine Foundation in partnership with nine medical specialty associations and Consumer Reports.

In the final analysis, many physicians don't like big data being applied to their practice's quality and cost performance because it limits their options. In some circumstances, these limitations are dangerous because they impede a clinician's ability to provide good patient care by preventing him or her from ordering valuable tests that aren't on an officially recommended list. In other cases, it prevents needless tests and wasting insurers' and patients' money. Health IT leaders, along with tech vendors and public policy makers, shouldn't shrink from the challenge of putting in place the analytical systems and metrics that can separate the two.

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jaysimmons
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jaysimmons,
User Rank: Apprentice
8/26/2013 | 7:02:47 PM
re: Why Physicians Don't Like Big Data
I agree that data can play a major role in determining appropriate care and the quality of care being given by physicians. The more data, the better it is, as with all big data analysis programs, but as in other fields, the appropriate data needs to be collected and analysis has to include all the factors that could affect the quality of data being collected.

Jay Simmons
Information Week Contributor
adavis613
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adavis613,
User Rank: Apprentice
8/25/2013 | 2:54:55 AM
re: Why Physicians Don't Like Big Data
I don't think your average, non-academic, non-administrative physician could care less about data analytics at this point. While everyone has heard the term and has at least a general sense of what it's all about (cost cutting), the fact is that it has virtually no impact on almost any physician's practice, yet. Private institutions are beginning to publish articles extolling the findings of some analytical study, but these are very limited in scope and very tentative in their conclusions. The fact is - and the majority of physicians understand this, too - that almost no one, and certainly not the government, has as yet obtained enough _valid_ data to be of any use. Given that medicine's stock in trade for the last 50 years has been data analytics, albeit on a much smaller scale (what else do you call all those double-blind studies over the years), the low hanging fruit is long gone. To be useful data analytics on the scale envisioned by the IT community needs hundreds of thousands, if not millions, of data pieces, and the medical community does not yet have either the standardized dictionary or the data transmission standards necessary to obtain _valid_ data on that scale, except in a very few instances at large academic institutions, and a couple of private insurers.
cbabcock
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cbabcock,
User Rank: Strategist
8/24/2013 | 12:51:46 AM
re: Why Physicians Don't Like Big Data
Technology in general, big data in particular and recent federal health care initiatives all have little to do with what good doctors do best, provide high quality care. The former all have a lot to do with controlling what doctors get paid. We need an honest broker in the middle weighing what's best for the patient, In modern health care, there is no such broker.
rradina
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rradina,
User Rank: Ninja
8/22/2013 | 1:02:50 AM
re: Why Physicians Don't Like Big Data
Depending on how the stats are rolled, doctors could just as easily seek out sick patients if graded on a relative improvement factors. For instance, if someone is obese, has horrible cholesterol and high blood pressure, prescribing the right meds will likely rapidly improve 2 out of 3 symptoms.

Of course it's difficult to measure cost savings since achieving target blood cholesterol and pressure levels is the epitome of good preventive medicine, it'll take years to determine the savings.
GJHUGHES
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GJHUGHES,
User Rank: Apprentice
8/21/2013 | 11:15:05 PM
re: Why Physicians Don't Like Big Data
If our goal is to seek to understand, not only what is the most appropriate care for any patient but also what is a good outcome based on that patient's individual comorbidities, behaviors and beliefs, then I can't think if a better way to start than with data...and the more data the better. The trick is to set achievable targets, based on case mix and other factors (that today's overly simplsitic models don't take into account) to ensure that great care is appropriately rewarded. The alternative sounds like speculation and personal opinion, which doesn't sound like a good way to advance healthcare delivery.
Michael Endler
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Michael Endler,
User Rank: Author
8/21/2013 | 7:42:20 PM
re: Why Physicians Don't Like Big Data
Lorna, education was my first thought to. As currently devised, the idea of a "value-added" metrics has its heart in the right place, but it's pretty misguided overall. Just because we can capture more data than ever before doesn't mean everything can be quantified in a useful way, and even when useful quantification is possible, we don't always pick the right variables and definitions. Paul does a great job explaining why physicians are scared of data maniacs who can't see beyond the numbers.
Thomas Claburn
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Thomas Claburn,
User Rank: Author
8/21/2013 | 5:10:16 PM
re: Why Physicians Don't Like Big Data
The problem with metrics is that they encourage people to focus on meeting the metrics requirements, even when those requirements are not fully aligned with optimal outcomes. In fields where the definition of success is open to interpretation, whether that's medicine or the arts, over-reliance on meeting numerical targets produces mediocre results.
Lorna Garey
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Lorna Garey,
User Rank: Author
8/20/2013 | 7:01:39 PM
re: Why Physicians Don't Like Big Data
Paul, I see many corollaries to teachers being rated on test scores - yes, they're largely out of their control, much like a diabetic taking his insulin, but properly weighted such stats are a starting point.
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