By DAVID C. KIBBE, MD, and BRIAN KLEPPER, PhD
Imagine that an innovative health plan – aware that half or more of health care cost is waste and that physician costs to obtain the identical outcome can vary by as much as eight fold – hopes to sweep market share by producing better quality health care for a dramatically lower cost. So it begins to evaluate its vast data stores. It’s goal is to identify the specialists, outpatient services and hospitals within each market that, for episodes of specific high-frequency or high value conditions, consistently produce the best outcomes at the lowest cost. Imagine that, because higher quality is typically produced at lower costs – there are generally fewer complications and lower incidences of revisiting treatment – the health plan will pay high performers more than low performers. Just as importantly, it will limit the network, steering more patients to high performers and away from low performers.
Suddenly, it will become very important for physicians and other providers to understand, in detail, how they compare to their peers within specialty, and how to provide the best care possible. And if they find the results aren’t so positive, they may want to figure out where their deficiencies lie, and how they can improve.
Now imagine that clinicians could easily view data about their patients and themselves.
- Basic demographics: e.g. age, gender, length of time since last visit.
- A problem list based on diagnoses within the past year.
- A list of medications prescribed, including ordering physician, dates and fulfillment information.
- A list of lab tests ordered, by physician and date.
- A list of immunizations.
Suppose the clinician could review, revise or copy this information to create a lasting “patient profile,” saving it online and retrieving it for use at each subsequent visit as appropriate.
