Theresa Teta Barry1, Peter Kemper, S Diane Brannon. 1. Department of Health Policy and Administration, The Pennsylvania State University, University Park, PA, USA. tetabarry@gmail.com
Abstract
PURPOSE: Turnover among direct-care workers (DCWs) continues to be a challenge in long-term care. Both policy makers and provider organizations recognize this issue as a major concern and are designing efforts to reduce turnover among these workers. However, there is currently no standardized method of measuring turnover to define the scope of the problem or to assess the effectiveness of interventions. This article draws on our experience of the Better Jobs Better Care Demonstration (BJBC) to explicate some important issues in measuring and interpreting turnover related to interventions designed to improve DCW jobs. DESIGN AND METHODS: We used turnover data from a selected group of BJBC providers (N = 9) to demonstrate some of the measurement issues we uncovered in developing a turnover tracking system for BJBC. We also illustrate how the data elements collected in the tracking system make it possible to construct measures that are useful at both policy and practice levels. RESULTS: Differences in definitions of turnover and the data elements used to construct the measure can have large effects on turn over rates, how they are used, and what they mean. IMPLICATIONS: Policy makers, researchers, and managers who need comparative turnover information to address the impending demand for DCWs should be aware that turnover measures differ, and they should take steps to ensure that measures they use have common definitions and data elements.
PURPOSE: Turnover among direct-care workers (DCWs) continues to be a challenge in long-term care. Both policy makers and provider organizations recognize this issue as a major concern and are designing efforts to reduce turnover among these workers. However, there is currently no standardized method of measuring turnover to define the scope of the problem or to assess the effectiveness of interventions. This article draws on our experience of the Better Jobs Better Care Demonstration (BJBC) to explicate some important issues in measuring and interpreting turnover related to interventions designed to improve DCW jobs. DESIGN AND METHODS: We used turnover data from a selected group of BJBC providers (N = 9) to demonstrate some of the measurement issues we uncovered in developing a turnover tracking system for BJBC. We also illustrate how the data elements collected in the tracking system make it possible to construct measures that are useful at both policy and practice levels. RESULTS: Differences in definitions of turnover and the data elements used to construct the measure can have large effects on turn over rates, how they are used, and what they mean. IMPLICATIONS: Policy makers, researchers, and managers who need comparative turnover information to address the impending demand for DCWs should be aware that turnover measures differ, and they should take steps to ensure that measures they use have common definitions and data elements.