Any healthcare entity that maintains a provider network is always on the lookout for predictive models and analytics to help them find fraud, waste and abuse. But do you have a tool that can detail the effectiveness of a provider’s treatment or for measuring patient outcomes? The effectiveness of your provider network in treating your members should be and probably is your primary concern. Having a provider in your network with subpar standards of practice and poor treatment outcomes has many negative effects. It can affect the perception of your plan quality and brand, cost you more in repeated or unnecessary services, and most tragically, violate the covenant of those entrusted to your care.
Do your predictive models or analytics test for patient outcomes or other indicators of quality of care? Here are a few examples of measures, and uses for them beyond just the numeric results. After all, it’s not only the analytics you should care about, but also the business intelligence accompanying the analysis that provides the best value.
General Treatment Outcomes
Consider a child diagnosed with asthma and managed by a specialist. Are there asthma-related emergencies leading to additional services for that child? If yes, what are they, and how severe? How does the initial treating provider rank on this and similar measures as compared to their peers?
With this information, it is possible to not only track these scores but to compare treatments including medication, dosages, and other factors to determine if providers with poor outcomes scores are in line with treatment practices of those with higher scores. This analytic is not designed to tell doctors how to treat patients or in any way attempt to replace physician judgments. These measures are simply to allow a plan’s staff physicians to compare treatments and make determinations of when and if best practices are followed with successful outcomes as a result.
Uses in Workers’ Compensation and Automobile Insurance
Analytics can also focus on treatments following a workers’ compensation injury or a motor vehicle accident. Take for instance a work-related back injury. Tailored analytics are key to uncovering clues to provider performance and network effectiveness.
What is the average length of treatment on a patient complaining of a lower back strain? What is the average return-to-work time for patients treated by a specific physician? How does that treatment time compare to peer physicians? Are certain physicians constantly exceeding reserves and expected timeframes? If we see consistently better performance from a particular treating provider, we may want to analyze their process to identify those techniques that are leading to better outcomes.
The analytics above would not only be good determinants of practitioner effectiveness but are also easily pivoted toward combatting healthcare provider fraud, waste and abuse. In the context of analyzing workers’ compensation and automobile insurance claims, analytics such as those highlighted above are immensely valuable tools. They can help determine which providers to review for potentially providing unnecessary treatment, or at a patient level for use in the scheduling of IME (Independent Medical Evaluation) appointments, allowing a specialist to look at the patient and provide a detailed independent report to the plan. You could even use measures and data like this to track the results and accuracy of the IME physicians against actual completed treatments and return-to-work dates.
Benefit to Consumers
As a consumer, I would like a way to base my healthcare provider choices on something other than an online review. Don’t get me wrong, online reviews do help guide some choices, especially if the review refers to the lack of cleanliness of the office or rudeness of the staff. But I am really looking to find out which practitioner to bring my child to when they sprain their ankle. Which doctor is most effective in getting them back to 100%? Which physical therapy center has the best after-surgery results? Which doctor has the best track record in preventing serious asthma incidents?
Roadmap to Better and More Informed Choices
Today we have at our fingertips a treasure trove of bits and bytes that can help paint a strategic picture for plans providers, and consumers. Of course, each group comes at data with a different set of questions. The secret sauce in the recipe is designing purpose-built analytics that provides useful information for healthcare practice management, increasing accuracy, efficiency and hopefully lowering costs for all.