Judith H Hibbard1, Jessica Greene, Martin Tusler. 1. Department of Planning, Public Policy, and Management, University of Oregon-1209, Eugene, OR 97403-1209, USA. jhibbard@uoregon.edu
Abstract
OBJECTIVE: To determine whether an approach that assesses patient capabilities for self-management and then tailors coaching support based on this assessment would be more effective in improving outcomes than the usual disease management approach. STUDY DESIGN: A quasi-experimental pre-post design was used, with an intervention group coached with a tailored approach and a control group coached in the usual way. METHODS: Data derived from telephonic coaching and from archival utilization data were used in the analysis. Differences in activation scores, clinical indicators, and utilization rates between intervention and control group members were assessed. Propensity scores were used to weigh the data and equalize baseline differences between the intervention and control groups. Analysis of variance repeated measures were used to examine changes over time. This analytic approach assessed whether individual changes over time in the intervention group were significantly different from individual changes over time in the control group. RESULTS: Overall, the findings showed a consistent picture that indicated a positive impact of the tailored intervention. Activation scores increased, clinical indicators improved, and utilization rates declined to a greater extent in the intervention group than in the control group. CONCLUSION: The findings suggest that tailoring coaching to patients' activation level and using the same metric to track progress improves the outcomes of disease management.
RCT Entities:
OBJECTIVE: To determine whether an approach that assesses patient capabilities for self-management and then tailors coaching support based on this assessment would be more effective in improving outcomes than the usual disease management approach. STUDY DESIGN: A quasi-experimental pre-post design was used, with an intervention group coached with a tailored approach and a control group coached in the usual way. METHODS: Data derived from telephonic coaching and from archival utilization data were used in the analysis. Differences in activation scores, clinical indicators, and utilization rates between intervention and control group members were assessed. Propensity scores were used to weigh the data and equalize baseline differences between the intervention and control groups. Analysis of variance repeated measures were used to examine changes over time. This analytic approach assessed whether individual changes over time in the intervention group were significantly different from individual changes over time in the control group. RESULTS: Overall, the findings showed a consistent picture that indicated a positive impact of the tailored intervention. Activation scores increased, clinical indicators improved, and utilization rates declined to a greater extent in the intervention group than in the control group. CONCLUSION: The findings suggest that tailoring coaching to patients' activation level and using the same metric to track progress improves the outcomes of disease management.
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