A Proposed Universal "Home Time" Quality of Life Measure for Older Adults.

Background: Researchers and insurers use "home time," or an individual's time at home compared to time in different health care settings, as a population-level quality of life (QoL) or quality of care measure. With varying definitions, it is unknown which components of a home time measure most closely reflect QoL. Our objective is to develop a person-centered universal home time measure agnostic to condition.

Methods: We used an iterative, structured approach based on Delphi methods to obtain expert input on what a measure should include, using qualitative and quantitative evidence from prior work. A total of 28 expert panelists, including Veterans Affairs (VA) leaders, clinician researchers, and non-clinician researchers, participated. In the first round, panelists voted on components (settings, weights, timeframes) to include in a home time measure. In the second round, panelists discussed results. The third round was final voting and explanations of choices and caveats.

Results: Qualitative and quantitative data suggested that emergency department, inpatient care, and post-acute care settings all affect older adults' QoL in different ways, supporting inclusion; 75% of the experts endorsed all settings, and discussion suggested that future work should limit ED days to visits resulting in an inpatient admission. Our data did not reveal a clear indication for weighting settings: 56% of the expert panel suggested continuing to explore the use of weights to arrive at values that would reflect qualitative differences in settings, and 44% did not support the use of any weights. Our 6-month models resulted in QoL outcomes for all settings, and 30% of experts endorsed a 6-month timeframe, while 65% said that timeframe would depend on the situation.

Conclusion: A "1.0" universal person-centered home time measure that reflects QoL should include days in the emergency department, inpatient care, and post-acute care. Expert input revealed domains of agreement and disagreement. Future validation efforts that incorporate expert input are needed to iterate and arrive at the optimal measure.