JAMIA: Lessons learned from community-based health IT

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Implementing health IT in the community setting is a national priority designed to improve the quality, safety and efficiency of healthcare. However, community-based organizations who are implementing health IT often lack the expertise to effectively evaluate the systems, according to a perspective published Aug. 1 in the Journal of the American Medical Informatics Association.

Most of today’s research on health IT’s efficacy has come from academic medical centers that have refined their home-grown systems over the years. With the objective of the American Recovery and Reinvestment Act of 2009 (ARRA) in promoting the adoption of commercial systems by community-based providers through $30 billion in meaningful use incentive payments, physicians and hospitals are expected to eventually start exchanging data electronically. This change in the U.S. health IT landscape is examining how effective health IT is for community providers, where most Americans receive their care. Such research and evaluation are necessary to ensure that the U.S. makes the best investments in health IT.

Researchers at Weill Cornell Medical College in New York City, the New York Health IT Evaluation Collaborative (HITEC) and New York-Presbyterian Hospital examined efforts in working with multiple academic institutions to evaluate effective community-based health IT initiatives. 

Lisa M. Kern, MD, MPH, in the department of public health at Weill Cornell, and colleagues used four themes in evaluating community health IT:

  • The structure of partnerships between academic investigators and the community;
  • Communication issues;
  • The relationship between implementation timing and evaluation studies; and
  • Study methodology.

Researchers discovered that e-prescribing by community-based primary care physicians led to reduced prescribing errors. Also, health information exchange portals helped improve the quality of care among community-based physicians.

The state of New York has invested more than $400 million in interoperable health IT through the state’s Healthcare Efficiency and Affordability Law for New Yorkers (HEAL-NY) capital grant program. As part of HEAL-NY, each community-based alliance evaluated the effects of its respective interventions. Several community alliances collaborated with an investigator at Weill Cornell Medical College and HITEC (an academic collaboration between Weill Cornell Medical College, Columbia University, the University of Rochester, the State University of New York at Albany and the University at Buffalo). HITEC was established and endorsed by the New York State Department of Health to conduct independent evaluations on health IT initiatives funded by HEAL-NY.

Lessons learned from the community-based health IT research from 2007 to 2010 include:
Need for partnerships

  • Respond to the priorities of the community.
  • Balance the academic preference for standardizing and customizing evaluations.
  • Include a clinician investigator who is based in the community.
  • Decide who will pay for what and estimate the costs.

Communication

  • Prepare to share interim results within the community.

Implementations

  • Anticipate implementation delays and evolve the implementation plans.

Research methodology

  • Include reference to the evaluation and research in community-based participation agreements.
  • Plan sufficient resources for developing, submitting and modifying protocols for institutional review boards.
  • Identify data sources in collaboration with data experts.
  • Address data aggregation needs and case-mix adjustments.

To develop these partnerships, the communities and evaluators had to understand each other's priorities. Communities want to generate more formative findings; to improve IT implementations and demonstrate their value to providers, payors and consumers.

In contrast, academic investigators want to combine several evaluations across communities to increase the sample size and precision of their estimates. These differing views led to difficulties in one aspect of the study, where researchers suggested that two communities implementing the same e-prescribing software should study its impact on formulary compliance. However, only one of the two communities participated in the study after a stakeholder, who had previously examined the issue in a different context declined to build a new study. This indicates that there may need to be a balance between academic preferences for standardized evaluations and the community