Geiger Gibson / RCHN Community Health Foundation Research Collaborative, issuing body.
Geiger Gibson Program in Community Health Policy, issuing body.
George Washington University, issuing body.
Milken Institute School of Public Health. Department of Health Policy and Management, issuing body.
[Washington, D.C.] : Milken Institute School of Public Health, George Washington University, April 13, 2015
This study assessed the feasibility and usefulness of combining electronic health record (EHR) data with federal cost report data for the purposes of: 1) quantifying the provision of enabling services; and 2) for use as the basis of community health center payment rate-setting. The study used EHR data derived from the Center for Primary Care Informatics to isolate enabling services and perform the end-to-end analysis that might be required to develop or evaluate reimbursement rates. The study revealed that data extracted from federal cost reports combined with data from the EHR fall short of providing the information required to reasonably develop new rate setting approaches or evaluate existing rates as they might be applied to community health centers. Specifically, key findings include: (1) Use of internal, center-specific codes (for example, in CPT fields) complicates the translation into relative value units (RVUs) and the aggregation of comparable data across health centers. (2) Enabling services are difficult to quantify. (3) Vague and inconsistent position titles lead to potential inaccuracies in the allocation of expenses. (4) The current funding environment deters capture of new information. This study raises fundamental questions about how to quantify (let alone how to reimburse) the true value associated with the community health center model of care. The study recommends tailoring EHR products to better capture the unique services provided by health centers and their effective management of high-risk patients. Fully moving to value-based reimbursement models will likely require that health centers adapt workflow to ensure that additional critical information (e.g., social determinants of health) is properly entered as structured data and not merely as scanned notes and other documentation.
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