A Primary Care Workload Production Model for Estimating Relative Value Unit Output

Abstract

Health care costs have grown to unsustainable levels nationally and within the Department of Defense. Military health care costs have historically been difficult to isolate, causing budget cuts to be the vehicle for cost control. Maximum efficiency, therefore, is the goal in order to show improvement. With the Air Force's new preventive health plan, they aim to drive a long-term posture for cost reduction through prevention. This research effort aimed to develop a tool to assist in future efforts to understand and improve efficiency in workload output, and whether a relationship exists between patient workload demand and the per-encounter variables collected at the Wright-Patterson AFB Medical Center Primary Care Clinic. This study examined primary care production data from the Military Health System Management Analysis and Reporting Tool from fiscal years 2009 and 2010, measuring patient workload in Relative Value Units (RVU) per encounter. The model produced shows a predictive adjusted R (2) value of 82%, indicating the variable appointment type shows an explanatory capability of the differences in RVU output per encounter and is a demand-based estimating tool for RVU throughput. When applied, the results could lead to a better understanding of efficiency of workload production.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2011
Accession Number
ADA540283

Entities

People

  • Rachel G. Murphy

Organizations

  • Air Force Institute of Technology

Tags

DTIC Thesaurus Topics

  • Air Force
  • Data Mining
  • Data Science
  • Databases
  • Demographic Cohorts
  • Department Of Defense
  • Health Care
  • Health Services
  • Information Processing
  • Information Science
  • Information Systems
  • Knowledge Management
  • Medical Personnel
  • Military Medicine
  • Regression Analysis
  • Surveys
  • Therapy

Fields of Study

  • Medicine

Readers

  • Life Cycle Cost Analysis
  • Logistics and Supply Chain Management.
  • Medical or Health Care Field.