I’m envisioning a young woman with a strange rash on her hands. She is visiting two different physicians. She shows him the rash with the first doctor and explains the scratching. She states that, to no avail, she tried various over-the-counter creams. The doctor looks up from the desk’s screen long enough to see red patches on her wrists and hands. He is writing a prescription for X for her. She fills out and takes the drug for a few days, but the rash continues.
A week later, she returns to the same clinic and sees a new provider. Again, she demonstrates her rash to the doctor and describes the itchiness. The provider inserts this data into the machine, but then proceeds to ask the woman a series of questions. The woman responds that she works in the food court at her university as a first-year college student. The doctor continues the interview and asks questions about the history of the woman and inserts her health status information into the computer program.
The woman also feels relaxed enough in her discussion to admit that as a child she had congenital urinary tract problems. The doctor recognizes that the risk of such allergic conditions is greater for patients with congenital urinary tract problems. The doctor admits, after a few more questions, that the woman is one of a group of people who are likely to have a latex allergy and that the gloves she uses for work triggers an allergic reaction.
Healthcare Technology In the Way
This is a reasonably clear example of the healthcare use of data and why it is necessary to correctly collect and use that data. Actually, this is nothing new. We still had details, but we didn’t call it “data.” We called it “patient charts,” “laboratory outcomes,” “X-ray outcomes,” etc., instead.
Like every other surgeon, before the development of sophisticated monitoring systems and EMRs, I can testify to the fact that ICUs and operating rooms were some of the most data-intensive places around. The background is different now though and things are more complicated. We have technologies that can do powerful analytics, showing us possibilities to reduce costs or decrease treatment variability.
In today’s healthcare climate, I believe the value of actionable data is paramount, but I am also worried about unintended effects, as seen in the above tale of the young woman with the rash. We must insist that patients are treated as individuals, not data points, i.e. “covered lives.” Patients need to know that they are listening to their doctor.
Doctors in an environment that emphasizes quality, value, and improving patient outcomes are well on their way to providing the kind of care value-based reimbursement models will require. Using the technology at their disposal with this solid cultural base will pave the way for actionable data—data physicians can use to reduce waste and variation and improve patient outcomes.