A comprehensive prognostic tool for older adults: Predicting death, ADL disability, and walking disability simultaneously

Abstract

Background Many clinical and financial decisions for older adults depend on the future risk of disability and mortality. Prognostic tools for long‐term disability risk in a general population are lacking. We aimed to create a comprehensive prognostic tool that predicts the risk of mortality, of activities of daily living (ADL) disability, and walking disability simultaneously using the same set of variables. Methods We conducted a longitudinal analysis of the nationally‐representative Health and Retirement Study (HRS). We included community‐dwelling adults aged ≥70 years who completed a core interview in the 2000 wave of HRS, with follow‐up through 2018. We evaluated 40 predictors encompassing demographics, diseases, physical functioning, and instrumental ADLs. We applied novel methods to optimize three models simultaneously while prioritizing variables that take less time to ascertain during backward stepwise elimination. The death prediction model used Cox regression and both the models for walking disability and for ADL disability used Fine and Gray competing‐risk regression. We examined calibration plots and generated optimism‐corrected statistics of discrimination using bootstrapping. To simulate unavailable patient data, we also evaluated models excluding one or two variables from the final model. Results In 6646 HRS participants, 2662 developed walking disability, 3570 developed ADL disability, and 5689 died during a median follow‐up of 9.5 years. The final prognostic tool had 16 variables. The optimism‐corrected integrated area under the curve (iAUC) was 0.799 for mortality, 0.685 for walking disability, and 0.703 for ADL disability. At each percentile of predicted mortality risk, there was a substantial spread in the predicted risks of walking disability and ADL disability. Discrimination and calibration remained good even when missing one or two predictors from the model. This model is now available on ePrognosis (https://eprognosis.ucsf.edu/alexlee.php) Conclusions Given the variability in disability risk for people with similar mortality risks, using individualized risks of disabilities may inform clinical and financial decisions for older adults.

Impact of Advance Care Planning on the Hospitalization-Associated Utilization and Cost of Patients with Alzheimer’s Disease-Related Disorders Receiving Primary Care via Telehealth in a Provider Shortage Area: A Quantitative Pre-Study

“…Under the LHS paradigm, data collection, analysis using artificial intelligence, applications to the real world and real-time practice may enhance confidence in ADRD care planning [ 13 ]. Although ePrognosis has been widely used to predict mortality and disability for the past two decades from the self-report dataset, the Health and Retirement Study (HRS), the data were collected from a sample with an over-representation of non-Hispanic white subjects (85.7%) [ 31 ]. The paucity of racial and ethnic minorities in the data set encourages further efforts to both identify and eliminate bias within healthcare systems, which will help advance healthcare equity [ 32 ].…”