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Value-based reimbursement will change the way life sciences companies decide which medicines to advance through their R&D pipelines, the therapies available to patients, and how care is organised by providers.

By Jeff Elton on Sep 19, 2012

Value-based reimbursement will help bring needed efficiencies and innovations such as improved care management to health care delivery and the accelerated implementation of personalised health care. 

While value-based reimbursement approaches have been piloted by health systems such as NICE in the UK, these approaches are receiving more consideration because of the increasing accessibility of in-depth, patient specific, clinical data that are collected by and which can be derived from electronic medical records (EMRs).  The existence of these systems in the US and the increasing population coverage in Europe and elsewhere are providing unprecedented amounts of data and consequently analyses of total costs and outcomes.

Consistent Data Can Equal Greater Accuracy

The availability of such high-quality and consistent data offers the potential to model, plan and direct therapies with greater accuracy - giving life sciences companies for instance certain specifics that they can target and address to improve a therapy and provide the greatest value for a specific patient population. The drive for value in reimbursement for services, therapeutics, and devices is creating a demand for such EMR data and an imperative for analytics to define and validate value delivered.

The availability of EMR data offers opportunities for life sciences companies. In the past, life sciences companies used sales data to model market share and growth.  The number of new prescriptions written usually equated to the number of new patients placed on a treatment. The total prescriptions indicated the current size of the market for that therapy. Now, life sciencescompanies are finding value in EMR-derived data that offer insight into individual patient medical history, clinical interventions including prescription history, outcomes, and costs. Because these data are generally organised around the patient, collected in the context of a care management process, and are in-depth in nature, they give life sciences companies a perspective on process and outcomes previously unavailable except through expensive customised studies.  

The Clinical Digital Revolution

Several forces are accelerating this clinical digital information revolution. Health systems are developing the ability to use these data:

• To make tradeoffs as to where to place their services and facilities;
• To allocate expense in delivering services to patients;
• To drive productivity;
• To achieve cost positions on services that reach targeted profitability.

New ventures and spinout companies from health systems are providing advanced health data analytics. Payers are using their claims data in comparable ways with increasingly powerful analytics and are forging partnerships with life sciences companies and other organisations. Many are creating new approaches to care management predicated on use of EMR-derived clinical data to drive the grouping of patients to evidence-based care management pathways, which show evidence of therapeutic value. Government affiliated entities and funded initiatives are targeting use of these data by regulators and for new reimbursement models.

Harnessing EMR data has several implications for life sciences companies. Gaining access to EMR derived real-world clinical data in focal disease areas and in specific regions of emphasis will help drug manufacturers better target therapeutics and stratify populations, optimising value and patient outcomes. Building capabilities for analytics across proprietary data, public data sources, and dynamic real world clinical data sets may allow companies to generate cutting-edge insights, develop proprietary approaches, and gain unique or reinforce existing intellectual property. Different types of analytics and partnerships formed through clinical development, for managed markets and for commercialisation strategies, can be centered on the same underlying data. Unique, value-adding analytics can help in each phase of the value chain.  

The move to in-depth clinical data as the basis for decision making also could bring life sciences companies closer to providers.  Companies and providers could identify specific opportunities within populations of patients, look for collaborative approaches, and measure the benefits from their unified approach.  This brings the expertise and insights of life sciences companies more directly to bear on the care of patients, and provides life sciences companies with a more practical view of the benefits and constraints of alternative therapeutic and care management approaches     

Many life sciences companies are committed to taking advantage of the EMR data revolution.  They are replacing traditional transaction data with higher-value and insight-rich EMR data to guide them in making more precise decisions, and to force a more disciplined focus on outcomes, giving value to patients and health systems.  These companies intend to use their combined insights to develop novel programs that may be delivered to the individual patient, but which will change the performance and outcomes of an entire patient population.  Overall, this trend bodes well for life sciences companies looking to deliver more value to patients and health systems.