Changes In Longitudes, Changes In Attitudes


With all due respect to Jimmy Buffet, the real opportunity for progress on the use of data to predict, steer, or bemoan our ongoing care and cost conundrum lies not in the latitudes but in the longitudes.

By way of brief background, for quite sometime the bedrock on which most data analytics programs were based was (and in many cases, is) claims data. Paid claims data, no matter how ugly, can at least be a predictor of future cost. Moreover, claims data reflects the soul of how we historically have delivered health care services, one ICD 9 code at a time, and how we diagnosed patients based upon their physiologic conditions at the moments in time when they were standing mostly naked in front of their doctors.

Skeptics about using claims data for health analytics purposes rightfully assert issues around the three “A’s”- Age, Aggregation and Accuracy of the data. To which I would add three “I’s” Integration, Information and Institutionalization. Claims data is not always timely available, not always fully complete (particularly in migratory populations such as Medicaid patients who may move in and out of health coverage), and may not always be accurate due to billing errors, coding opportunities and other challenges. We certainly receive plenty of “clean claims” which appear to have covered mammography for males, as an example. (Of course, I defer in cases when this is appropriate.)

My concerns also revolve around the fact that claims are only one part of a patients’ story, and quite frankly the least important. To be fair, claims can include pharmacy data, and some evidence of quality standards met or missed. But even then, if the central object of this exercise is to answer the fundamental question, ‘How healthy is this patient?” claims data alone leaves us wanting more.

Moreover, claims data is simply a reflection of the institutional practice of medicine – it’s a bill after all. I would suggest there are times when claims data is no more reflective of a patient’s health than a lawyers’ bill is reflective of the likelihood of successful outcome in a case. Now obviously, claims data are far more useful than legal bills, but you get my point.

What is needed is the opportunity to augment claims data, which in the best circumstances are helpful, along with other longitudinal data – labs certainly – but also physiologic data collected on a daily or at least regular interval.

We stand at a moment – smartphone in hand, iPad at the ready – when many of our patients are mobile, multimedia, and now monitored, measured and compared (or at least capable of being compared) with other patients. Some would suggest this is the beginning of personalized health care. (Which it is, though, in subsequent blogs, I will argue that personalized health care may still be a decade away.) But for the moment consider this, health care can and is using phone, video conferencing, email, social networking web sites (Patients Like Me or Diabetes Mine for instance), GIS, tweets, on-body/in-body sensors, digestibles, implantables, wearables, and now medical body area networks.

Each of these communication tools collect ongoing, longitudinal patient data. In this evolving “there-is-an-app-for-that medicine,” investments by HHS through the Office of the National Coordinator are pushing providers toward a digital health enterprise containing electronic health records, patient-controlled records and health information exchanges.

We are on the verge of creating zetabytes of medical data. But this explosion in data for the moment runs ahead of our legacy systems’ claims-based analytic architecture. (By the way, it also runs ahead of our legacy-based, episodic care medical architecture.)

So what is needed to turn longitudinal data into information, knowledge and wisdom?

First we need integrated technology platforms that can absorb active or passive collected data from diagnostic/monitoring devices, and then combine that information with more traditional sources of health, pharmaceutical and lab data.

Second, we need a new suite of data mining and integrative analytics and network solutions.

Third, we need new performance and outcomes analysis metrics. That is, we need to turn our focus to measuring outcomes rather than process.

Fourth, we need the output of this analysis to be translated to bedside practice, producing more targeted care and increasingly efficient use of resources.

Which, of course and interestingly enough is exactly what this new forum is all about.

Carl Taylor is a Partner at the Fraser Institute for Health Research, Princeton, and Assistant Dean in the University of Southern Alabama’s College of Medicine.

4 thoughts on “Changes In Longitudes, Changes In Attitudes

  1. Carl: Great piece! I am struck by how close your analysis of what is needed comes to Paul Ellwood’s classic article on “Outcomes Management,” delivered in 1989 I believe as the Shattuck Lecture at Harvard, and published in NEJM. He said (I’m paraphrasing from memory here) we need three things for a science of outcomes management: 1) a patient-understood language of outcomes and results; 2) national databases accumulating these data along with other, e.g. costs, and; 3) physician access to these data and their analysis, to direct care in the best possible directions.

    In your critique of the use of claims data for analytics for improvement, I think you are certainly touching on that first point, as well as when you point out the enormous amount of clinical data that are available directly from patients via modern communications devices — regular people/consumers/patients as well as doctors can understand high blood pressure readings, but haven’t a clue what a particular ICD code means.

    I have to ask: who pays for this turning of “longitudinal data into information” in you mind? Another way of asking this is: why haven’t we done this sort of thing all along, given its potential for helping us make better decisions? I’d like to hear your thoughts on that.

    Kind regards, DCK

  2. I think it important to acknowedge that the ability of technology to impact the health of the massess will be significantly impacted by the adoption curve. Until we apply consistent behavioral economic principles to drive engagement the technology will hold limitless potential but limited impact. I agree that the innovations in technology are incredibly powerful tools that create the opportunity to drive incredible change however – this impact will be limited by individual application. How can we influence social norms to promote health as a way of influencing the culture of the community? I would submit tha just as we need improved integration between health care providers and health information we also need enhanced integration between all the stakeholders in a community. After all, we are limited and inlfuenced by the environment in which we live.

  3. I agree with David wholeheartedly and will offer some quick thoughts and then a longer blog soon. First, I tend to suggest that people have been far better partners in creating their illness than partners in their health (the challenge of living a life divided between net negatives such as desserts and net positives like diet/exercise). So how to make people their own health partner. One way is to cross the us vs them divide. We need to reinvent health care from a perspective of what is the right system of care for me. Not as a provider, or a payor but from a point that we all have in common and that is as a patient. I have to believe that doctors would create a better health system if they only looked at care from the perspective of a patient. Second, we need to encourage patients to believe they can tell their own story. Jim Loehr has a wonderful book out called the Power of Story in which he encourages us to write (or maybe rewrite) our story of our lives from a position of control, not simply as a patient suffering from an illness but from a space of empowered direction. Third, as Gresham Bayne says the answer is money what is the question. We need to find a way to create a patient consumer. I will write more about this later. Fourth, in a recent Gallup Press publication entitled Well Being we see the power not just of the clinical or biological world around us, but the impact on our health because of where we live, where we work and who we work for. We need to think of health as a far more complex ecosystem than just what a lab test tells us. What I do find encouraging in the thousands of patients we touch is that people when engaged will participate. They will search web sites, they will receive text messages, they will call 1-800 numbers to report their health and they will answer surveys far longer than I ever thought. And when confronted with good health ideas-like teen pregnant moms ought to stop smoking- many do. So we can drive change if we just get the approach and the tools right.

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