Do functional status and Medicare claims data improve the predictive accuracy of an electronic health record mortality index? Findings from a national Veterans Affairs cohort

Performance of the Physical Functioning Activities of Daily Living Scale in the 2020 Medicare Health Outcomes Survey

OBJECTIVE

Assessing functional limitations for adults at high risk of frailty yields valuable information for identifying those in need of therapy. We evaluate a self-report measure used to assess physical function among Medicare recipients in the United States.

DESIGN

Secondary analysis of the 2020 Medicare Health Outcomes Survey.

SETTING

A random sample of adult enrollees of 510 managed care plans.

PARTICIPANTS

287,476 adults (37% completion rate): 58% women; 16% were <65 years old (entitled via disability), 50% 65-74, and 34% 75 or older; 77% White, 14% Black, and 8% another race; 19% had

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURE

We evaluate item distributions, dimensionality, monotonicity of response options, reliability, and validity of the 8-item Physical Functioning Activities of Daily Living (PFADL) scale.

RESULTS

Most reported they could do 6 basic activities of daily living without difficulty. More limitations were reported for the other 2 PFADL items: 32% were not limited at all in climbing several flights of stairs and 40% in moderate activities. Product-moment correlations among the 8 items ranged from r=0.19 between the easiest-to-do (eating) and most difficult-to-do (climbing several flights of stairs) items to r=0.73 between bathing and dressing. The coefficient alpha and omega for the 8-item scale were both 0.86. Item slopes ranged from 2.6 (climbing several flights of stairs and eating) to 4.8 (dressing). Item characteristic curves revealed that response options were most likely to be selected in the appropriate order along the physical functioning continuum. The PFADL had at least 0.80 reliability between about -3 SDs below the mean to the mean. It was negatively correlated with comorbid condition count, disability days, problems with balance or walking, falling, and obesity.

CONCLUSIONS

The PFADL is useful for assessing average or below physical function in Medicare recipients.

Collapse

Key Words

• Aged
• Functional status
• Medicare
• Rehabilitation
• Self-assessment

Collapse

MESH Headings

• Adult
• Humans
• Female
• Aged
• United States
• Male
• Activities of Daily Living
• Reproducibility of Results
• Medicare
• Surveys and Questionnaires
• Outcome Assessment, Health Care
• Disability Evaluation

Collapse

Grants

• P30 AG021684 NIA NIH HHS

Collapse

Affiliation(s)

Ron D Hays UCLA Division of General Internal Medicine, Department of Medicine, Los Angeles, CA.
Marc N Elliott RAND Corporation, Santa Monica, CA

Collapse

High dimensional predictions of suicide risk in 4.2 million US Veterans using ensemble transfer learning

We present an ensemble transfer learning method to predict suicide from Veterans Affairs (VA) electronic medical records (EMR). A diverse set of base models was trained to predict a binary outcome constructed from reported suicide, suicide attempt, and overdose diagnoses with varying choices of study design and prediction methodology. Each model used twenty cross-sectional and 190 longitudinal variables observed in eight time intervals covering 7.5 years prior to the time of prediction. Ensembles of seven base models were created and fine-tuned with ten variables expected to change with study design and outcome definition in order to predict suicide and combined outcome in a prospective cohort. The ensemble models achieved c-statistics of 0.73 on 2-year suicide risk and 0.83 on the combined outcome when predicting on a prospective cohort of [Formula: see text] 4.2 M veterans. The ensembles rely on nonlinear base models trained using a matched retrospective nested case-control (Rcc) study cohort and show good calibration across a diversity of subgroups, including risk strata, age, sex, race, and level of healthcare utilization. In addition, a linear Rcc base model provided a rich set of biological predictors, including indicators of suicide, substance use disorder, mental health diagnoses and treatments, hypoxia and vascular damage, and demographics.