When I was in medical school, I didn’t realize the potential data would have in health care. Back then I learned from 1000+ page hardcover textbooks and handwrote notes in paper medical records.
Fast forward twenty years — data and analytics are at the forefront of health care. Other doctors and I now have electronic medical records in the majority of hospitals and medical offices; there are claims data warehouses, and there is a host of other forms of data. Along with this big data, we have ever-evolving ways to analyze and visualize data which enable more precise measurement, the ability to compare, and the opportunity to predict future events and outcomes. According to a McKinsey report, health care analytics has the potential to create $ 300 billion in value. New health care start-ups are poised to disrupt the industry by using a tactical, analytical approach to drive value. Similarly, life sciences companies are doubling down on the value of data to demonstrate real-world efficacy.
I have had the privilege to be a part of the innovation that’s occurring in health care analytics. This experience has made me realize that doctors, given our clinical knowledge and real-world experience in hospitals, offices, and other health care settings, bring a unique and valuable set of skills to companies and organizations building and using health care analytics. Doctors can leverage this knowledge and experience in three ways.
Understanding of the value proposition. For analytics to be effective in health care, they must address important problems and generate value. Doctors understand both. From their clinical practice, doctors can offer real-world experiences in health care which can be very useful for framing problems and articulating the value of analytic solutions. Doctors who have specific knowledge of health care policy, delivery, and value can be particularly beneficial explaining how analytics drive value.
For example, waste in health care is a common issue that analytics teams can identify and quantify. But waste is difficult to define. Clinically experienced doctors can share their understanding of waste (and the various clinical nuances of it), help teams set realistic targets for reducing waste, and inform teams on what has worked or not worked to reduce waste.
Similarly, when teams are poised to use advanced analytics methods like machine learning and artificial intelligence, doctors can define what is clinically or financially important to predict and act on.
Ability to be a critical translator. Data scientists and analytic teams use data elements to define and quantify everything in health care. Data elements include codes such as the International Classification of Disease (ICD) and the Current Procedural Terminology (CPT) as well as clinical data like laboratory results and prescriptions. Data may also include a plethora of unstructured information that come from consumer intake tools or medical records. Doctors who have a thorough knowledge of clinical and operational medicine understand how diseases and health care services are classified and those who can take their clinical knowledge and explain it with data elements are poised to be critical translators for analytics teams.
For example, in my role, I often work with analytics teams to help them define conditions, symptoms, medical procedures, and medications using data elements. I then work closely with them to review outputs and ensure they are clinically accurate and meet the business needs of our organization. For example, I have worked with analytics teams to design outputs from benchmark diagnostics and have worked closely with them to ensure that data findings are organized and visualized in a way that decision-makers can easily interpret.
Doctors can also support the translation of more complex, analytic techniques which often seem unclear to health care leaders and clinicians. This gives clinical and business audiences a greater understanding of the underlying principles of complex analytics rather than feeling like it is all a black box.
Capacity to drive change. Either through their expertise or their roles in an organization, doctors are in a position to not only translate data and analytic outputs but to produce change using data. Their roles as leaders, committee members, and users of data outputs can drive organizations to be more data-driven.
In my experience, I have seen doctors use data to drive business decisions, integrate data outputs into workflows, and propel innovation using data and technology. For example, I have seen predictive models used to predict patients at risk for hospital readmissions and the subsequent improvement of those models using machine learning. Doctors using this information often play a critical role to integrate data outputs into workflows for care management or discharge planning.
Doctors often have leadership or other influential roles in health care delivery, payer, and other health care organizations and if they are champions on the use of data, they can create data-driven cultures.
With health care continuing to be more data-driven, there is more potential for doctors to stay relevant and be at the forefront of health care information than ever before. There was a time when doctors were fearful and circumspect on how data might impact their roles. That period is over. Doctors who can embrace the data revolution are poised to be critical players in the future of health care.
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