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Using Real-World Data to Power Population Health Analytics

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Insights for Life Sciences Companies

As the quality of payers’ data on their members’ health outcomes gets better with each passing day, achieving measurable quality targets is increasingly becoming the basis for payments in contracts with providers and suppliers – including pharmaceutical companies. In the previous article in this series on population health, I described how pharmacy benefit managers are negotiating agreements that include terms to reduce therapy costs where patients do not achieve the clinical outcomes promised.

This trend has major implications for the pharmaceutical team responsible for a drug that is relatively expensive or has significant competition. Formulary placement, market share, and competitive position are all subject to new risks. To understand the risks and turn them into opportunities, the pharma company needs to be at the table with its payer and provider partners as population health management (PHM) programs – particularly the data analytics components – are implemented.

Almost one-half of payers and providers have PHM technology in place, enabling them to leverage data on defined populations to improve outcomes and reduce costs like never before. Let’s take a look at two examples where the dynamics of drug prescribing are changing because of improved population health analytics technologies:

  • A health system discovers that a drug for multiple sclerosis with a higher initial cost than comparable therapies resulted in lower overall healthcare costs for a defined population. You can bet that the response to this finding is making the more expensive drug the drug of choice in clinical protocols and awarding it preferred status in drug formularies.
  • By analyzing patients with similar demographic (e.g., race, ethnicity, age), health (e.g., comorbidities, family medical history), and socioeconomic (e.g., education, social support) attributes, the drug therapy for a particular condition with the best outcomes can be identified by the provider, resulting in a more targeted and clinically effective protocol. These precision medicine efforts will elevate the position of certain drugs at the expense of others – a dynamic that is magnified as health systems standardize care pathways across their doctors and the influence of drug detailing on physician prescribing diminishes.

So, here’s the burning question: How does the pharmaceutical brand team proactively respond to these new dynamics that are influencing which drugs are prescribed to a particular population of patients?

Answer: By adding value to the population health management program of strategic payers and health systems and in return, receiving de-identified data from the health systems’ electronic health records (EHRs) for your pharma company’s real-world data warehouse. Pharma is uniquely positioned to optimize the analytics that is core to a successful PHM program, making this type of arrangement beneficial for all stakeholders. Here’s how:

  1. Start by working with health systems on a basic building block of population health management – the identification, analysis, and reporting of clinical quality measures where effective medication management has a significant impact. Before even bringing in real-word data, pharma’s knowledge and experience with how to measure and influence outcomes of particular patient populations – using the health system’s data – can help to demonstrate positive results in the early stages of ramping up population health management systems to support value-based contracting.
  2. Accumulate and leverage the large samples of patients in the pharmaceutical company’s real-world data to improve the accuracy of predictors of health risks and outcomes. A major challenge the leaders of a population health program at a health system encounter is limitations of the patient sample, which is slowly collected over time and usually limited to patients in the health system’s service area. Payers may have a more representative sample but lack important clinical and socioeconomic data. The accumulation of real-world data by pharma companies, including the rich clinical data sets now available in EHRs, is of growing interest to payers and health systems because of the very large samples and quality data that can improve the accuracy of therapy risk assessments and precision of predicting outcomes. Evidence of a particular medication therapy’s effectiveness in comorbid patients or when certain non-clinical factors exist (e.g., race/ethnicity) are especially attractive because these are considered high leverage points in improving the quality of recommended care pathways – key to gaining clinician acceptance and the overall cost-effectiveness of a population health program.
  3. Provide real-world data and analytics to predict continued adherence and drug-specific non-adherence interventions. A study conducted by Brigham and Women’s Hospital and CVS Health showed distinct types of non-adherers, including patients who struggle with continuing medication therapy at different points in time. In addition to providing insights into these types of patterns within its RWD samples, the pharma company is uniquely positioned to deliver drug-specific intervention recommendations (e.g., change in route of administration or strength). To be effective, these recommendations must be presented from within the EHR system workflow supporting the care teams.

Value-based contracting for drugs is a framework that benefits all parties. Payers lower the overall medical expense; providers meet quality targets to qualify for incentives or avoid penalties; pharmaceutical companies that meet clinical outcome targets in the contracts expand their market and avoid having to discount their fees. To achieve this win/win/win scenario, these health care stakeholders must all be at the table when designing and implementing the data analytics infrastructure to manage a defined population. Despite the uncertainty and risks of value-based contracts, the growing number of collaborations in PHM initiatives indicates that leaders in each of these sectors recognize the strategic importance of this imperative.  An assessment of your strategies and programs to leverage real-world data and build out effective population health analytics capabilities is critical to answering the question: Will your company be a leader or a laggard in the new era of value-based drug contracting?

Michael Solomon

Michael Solomon