One of the problems dragging down the US health care system is that nobody trusts one another. Most of us, as individuals, place faith in our personal health care providers, which may or may not be warranted. But on a larger scale were all suspicious of each other:

Yet everyone has beneficent goals and good ideas for improving health care. Doctors want to feel effective, patients want to stay well (even if that desire doesnt always translate into action), the Department of Health and Human Services champions very lofty goals for data exchange and quality improvement, clinical researchers put their work above family and comfort, and even private insurance companies are trying moving to fee for value programs that ensure coordinated patient care.

What can we do to stop pulling in different directions and put our best ideas into practice? Data is often the impetus to trust. If we collect data on the most important activities in health and use it wisely, we mayperhapsbe able to set up a system in which everyone can place their trust.

So lets look at four key areas of health care reformfee for value cost containment, patient engagement, clinical research, and quality improvementsto see how data can interact with new ways of working to fix the problem of trust.

Software companies have learned not to pay programmers by the amount of code they write, and corporations are learning not to pay lawyers by billable hours. Medicare and private insurers are trying hard to move similarly from paying doctors for the number of procedures performed to paying them to actually cure the patient.

The key to paying doctors fairly is risk stratification, which places each patient in a stratum based on how hard he or she is to cure. If I have high blood pressure, it makes my heart disease harder to cure, and if I have high blood pressure along with diabetes and obesity, it makes the job even harder. Fee-for-value pays doctors a different amount if the patient has contributing problems (appealingly called comorbidities), and thus forces them to consider all the factors instead of just treating one condition in isolation.

But how much should each patient cost? Here is where data becomes critical. We need to know how much care was needed by a large set of patients who suffer from high blood pressure, diabetes, obesity, and heart disease. Throw in tobacco use and other comorbidities and you see how complicated risk stratification is.

To get straight to the point: we cant figure all that out now. We just dont have the data. To do risk stratification right:

I think the institutions driving fee-for-value (Centers for Medicare & Medicaid Services, and private insurers such as Blue Cross Blue Shield of Massachusetts) have to bite the bullet and accept that we are not ready for risk stratification on a scale that will put fee-for-value on a valid foundation. When we factor in health provider qualitywhich Ill cover laterthe hill becomes even harder to climb.

Before I look for solutions to this dilemma, Ill turn to the other issues of trust.

Original post:

Can data provide the trust we need in health care?