Who hasn’t watched an episode of a medical drama on television? In a typical weekly segment, the doctor runs all sorts of tests and tries a number of different treatments in a Herculean effort to save the patient. Many times the doctor is successful, but sometimes the consequences are unexpected. Regardless, we hold these characterizations of doctors in high esteem. These practitioners are the patients’ heroes…but they are also the health administrator’s nightmare. Unorthodox diagnostic approaches, radical therapeutic moves, and actions which ignore medical protocol increase the risk to the patient, and incur huge medical costs, often for no return.
But even the smartest physicians – the providers who know and believe in evidence-based best practices – can’t deliver consistently reliable care if there isn’t a meaningful data system in place to support them as practitioners.
From “common sense” remedies to the scientific method
Hippocrates wrote that a physician’s judgement mattered more than any external measurement, and the practice of medicine was long organized accordingly. Heuristics, or experience-based techniques for solving problems, created “common sense” remedies. These methods seemed to work (or were good enough) until the 17th century, when the scientific method became prominent in natural science. The evidence-based techniques encompassed in the scientific method represented a significant change – they were the critical difference between, for example, chemistry and the prevailing pseudo-science of alchemy.
Medicine, too, finally adopted the scientific method and overturned centuries of intuitive wisdom. This transformed the life expectancy from 50 years in 1910, to 76 years for males and 81 years for females by 2013. Medical practice is now rooted in measurement. We tabulate, graph, normalize, and apply any number of statistical processes to both claims and EHR data. But despite the best of intentions, this effort has been accompanied by unforeseen repercussions which overshadow the principal endeavor. In our zeal to measure, we have forgotten to first ensure that we have the correct, complete data.
The unintended consequences of the EHR
The complexity of medical science and fragmented data storage has fostered a resurgence of the heuristical approach. Originally, providers were asked to manage patients with limited and laggy claims-based data. Depending upon the source, claims-based data may not fully represent care outside of the home network, and is often 60 days past the date of service when received for analysis. EHR data may be timelier, but it also presents a number of challenges that must be resolved before it can become easily digestible and meaningful to the practitioner.
Most large health systems employ multiple EHR systems, which typically translates into a fragmented understanding of the patient’s condition. Additionally, due to the complexity and flexibility of these large clinical systems, individual data elements can be recorded in multiple ways and in differing locations. Edward Tenner, author of “Why Things Bite Back: Technology and the Revenge of Unintended Consequences”, provides several examples where the “fix” creates its own, perhaps even larger problem. Health care workplaces are the extremely complex organizations and increasingly complex EHRs can spawn subtle, unintended consequences. For example, EHRs can offer many benefits including improved communication between clinicians and their patients using email and instant messaging and improved access to clinical guidelines. However the same technology has left patients and providers feeling disconnected from one another as the computer has become the focus of the conversation and the driver of the exam. A poor fit between the EHR and other IT systems can lead to data loss, errors, down times, and system driven care gaps.
Better data supports better care
So when it comes to thinking about what makes a good doctor, we have look at what it means to be in a good system, one in which data is used to continually reassess and enhance the practice of medicine. In the absence of complete, unified, and actionable data about their patients, providers are challenged to deliver the right care on a consistent basis. Just as too many cooks can spoil the broth, too many individual decision makers responsible for only one fragment of healthcare of a patient, without the full picture, lead to widely variable actions and outcomes. It is this variability that leads to the high cost and scattered results of the US healthcare system. Variation leads to low value, and is the unintended consequence of disparate technology in healthcare. Our beliefs and biases, which support intuitive medicine in our favorite dramatic television series, need to remain the stuff of Hollywood.
It is time to write an alternative ending to our medical television series. We can link data between claims and EMR systems that provide a full patient profile and allow us to share knowledge. The system, which is accessible to physicians in any location brings about better, safer care, fewer redundancies and ultimately cost savings for our patients. Quality in health care must be based on a comprehensive look at the entirety of a patient’s experience and, thankfully, this is not a Hollywood fantasy. When data is complete, accurate, and timely, it is the cornerstone of a happy ending.
Sue Marsh is a senior business analyst in our Chicagoland office whose practice is focused on helping health systems and provider groups take on risk while remaining financially viable.