The Health Care Payment Learning Action Network (HCPLAN) has released a white paper on data sharing within alternative payment models (APMs).  HCPLAN work products will be considered by the Centers for Medicare and Medicaid Services (CMS)  for implementation of the Medicare Access and Children’s Health Insurance Program Reauthorization Act (MACRA) and other health care payment reform initiatives.  This white paper was developed by the Population-Based Payment Work Group and documents principles and recommendations that should guide approaches to data sharing in population-based payment models. The goal should be to share important patient data to inform clinical decision making, allow payers to assess provider performance, and support increased alignment across public and private payers.

Data sharing currently faces multiple challenges, including proprietary approaches to data collection and reporting, inconsistent and underdeveloped data architecture, a lack of funding and standards, and technical limitations to the collection of rich clinical and patient-reported data. The white paper recommends the following principles for data sharing:

  • Data sharing is foundational for the successful operation of population-based payment models and makes it possible for stakeholders to carry out their respective roles;
  • Data sharing in population-based payment models will need to be fundamentally different from data sharing in traditional fee-for-service models;
  • Data sharing for population-based payment models requires multi-stakeholder relationships built on trust, cooperation, and transparency;
  • Identifiable, patient-level data should follow the patient;
  • De-identified, population-level data should be treated as a public good; and
  • Providers who participate in population-based [payment models with multiple payers will need to receive, use, and share data with each of them, giving rise to complexities that may benefit from collaboration with third-party data intermediaries.

The white paper makes the following recommendations:

  • Payers and providers should identify in advance aligned approaches and policies for data sharing to support population-based payment models;
  • For data to follow the patient, payers and providers should collaborate on approaches to patient identifiers that enable mapping across systems and data types (e.g., clinical, administrative, and patient-reported data); this effort should be scalable;
  • Payers, providers, purchasers, and patients should convene a multi-stakeholder group to recommend solutions that assure patients that their personal data are appropriately used;
  • Requirements for data sharing should be made explicit in agreements between purchasers and payers that participate in population-based payment  models;
  • Payers should give patients and purchasers easy access to information on what it costs to see different providers for the same, common procedure, alongside relevant quality indicators; and
  • Payers, providers, and purchasers should actively participate in pilot programs to evaluate approaches to the sharing of data across multiple payers and providers.

The white paper also discusses a number of use cases and includes several case studies that provide examples how the principles and recommendations could be implemented.

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