Why physicians' performances benefit from healthcare data analytics

Convincing struggling physicians to change their care strategies can be difficult, but data analytics can help.

Although physicians are highly driven and motivated people, they still require ongoing reports on their performance or else they won't know what to improve. Healthcare data analytics is increasingly being used as a way for physicians to receive feedback on their care. Many hospitals still face problems with preventable blood clots -- also known as venous thromboembolism (VTE). Between 350,000 and 650,000 people develop VTE per year, and as many as 200,000 deaths per year result from VTE.

Blood clots are highly preventable if the proper medications are ordered on patients who have certain risk factors. In one large study, researchers looked at more than 70,000 patients at 358 hospitals and found that less than 60% of the surgical patients and less than 40% of the hospitalized medical patients received appropriate prophylaxis or preventative care advice. Only 50% of patients are getting enough prophylaxis as it's defined by national guidelines.

So why is this still happening if hospitals have electronic health records and clinical-decision support tools at the point of care? The candid truth is that some physicians are performing more poorly than others when it comes to ordering proper blood clot prophylaxis regimens. Hospital administrators and physicians do not like to point out physicians who are underperforming because that can make the hospital look bad and make the physician feel bad. Or, in many cases, that physician may get angry, hostile and argumentative. In fact, some of the worst-performing physicians are the ones who have terrible bedside manners and poor interpersonal skills. They are the last ones whom you would want to inform about poor performance.

Healthcare data analytics provided on an ongoing basis can help physicians have a common denominator when they review their own performance. That common denominator is the aggregate performance of all their peers. This way, if 15 preventable blood clots are traced back to Doctor A and only three clots are traced back to Doctor B, then we can run the data through some analytics to see if Doctor A is really doing a worse job preventing clots compared with Doctor B. We would have to review variables such as patient risk factors, patient volume, complicating factors, etc.

Ongoing data analytics could generate physician report cards. This would give the poor-performing physicians time to improve. They may need some continuing medication education to improve their knowledge about evidence-based blood clot prevention strategies. Or they may benefit from more reminders to prescribe prophylaxis in high-risk patients. They may need more clinical-decision support tools to help them assess the risk of blood clots in their patients. Maybe some of these physicians are not adopting their hospital's risk-assessment protocol. Or maybe they are ignoring protocol because they think they know how to treat patients.

Hospital leaders may need to do a better job at achieving physician buy-in on proper prophylaxis care strategies. Or perhaps hospitals need to do more to penalize physicians who are performing poorly and doing an unsatisfactory job prescribing prophylaxis to their patients. The data is there. Hospitals can identify those physicians. However, providing negative feedback and constructive criticism to physicians can be challenging. It goes against the culture of medicine, where physicians traditionally view themselves as the "captain of the ship" when it comes to making treatment decisions about their patients. Some physicians want to avoid the notion of "cookbook medicine," which is primarily driven by algorithmic processes and automation. They want to rely on the traditional art of medicine and less on the evidence-based science of medicine.

To convince some of these physicians about their need to change their clinical behaviors, hospitals need to use more data analytics and present this in an ongoing fashion to their physicians. They need to do this in a way that fits the culture of their medical staff. They need support and buy-in from the senior executive leadership and the medical staff leadership.

The practice of medicine is changing as healthcare data analytics becomes more closely integrated with clinical care delivery models. Some doctors do not like this fact, but others are embracing this change and looking forward to seeing more integration of data analytics into their clinical practice.

About the author:
Joseph Kim is a physician technologist who has a passion to leverage health IT to improve public health. Dr. Kim is the founder of NonClinicalJobs.com and is an active social media specialist. Let us know what you think about the story; email editor@searchhealthit.com or contact @SearchHealthIT on Twitter.

This was first published in September 2013

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