The predictive utility of functional status at discharge: a population-level cohort analysis

Mats L Junek,George Heckman,Catherine Demers,Andrew P Costa,Lauren E Griffith,Aaron Jones

doi:10.1186/s12877-021-02652-6

Abstract

BackgroundFunctional status is a patient-important, patient-centered measurement. The utility of functional status measures to inform post-discharge patient needs is unknown. We sought to examine the utility of routinely collected functional status measures gathered from older hospitalized patients to predict a panel of post-discharge outcomes.MethodsIn this population-based retrospective cohort study, Adults 65+ discharged from an acute hospitalization between 4 November 2008 and 18 March 2016 in Ontario, Canada and received an assessment of functional status at discharge using the Health Outcomes for Better Information and Care tool were included. Multivariable regression analysis was used to determine the relationship between functional status and emergency department (ED) re-presentation, hospital readmission, long term care facility (LTCF) admission or wait listing (‘LTCF readiness’), and death at 180 days from discharge.ResultsA total of 80 020 discharges were included. 38 928 (48.6%) re-presented to the ED, 24 222 (30.3%) were re-admitted, 5 037 (6.3%) were LTCF ready, and 9 047 (11.3%) died at 180 days. Beyond age, diminished functional status at discharge was the factor most associated with LTCF readiness (adjusted Odds Ratio [OR] 4.11 for those who are completely dependent for activities of daily living compared to those who are independent; 95% Confidence Interval [CI]: 3.70-4.57) and death (OR 3.99; 95% CI: 3.67-4.35). Functional status also had a graded relationship with each outcome and improved the discriminability of the models predicting death and LTCF readiness (p<0.01) but not ED re-presentation or hospital re-admission.ConclusionRoutinely collected functional status at discharge meaningfully improves the prediction of long term care home readiness and death. The routine assessment of functional status can inform post-discharge care and planning for older adults.

Highlights

Functional status is a patient-important, patient-centered measurement
Population Characteristics A total of 53 (28.8%) public hospitals in Ontario completed sufficient Health Outcomes for Better Information in Care (HOBIC) assessments to be included in the analysis, which allowed for the inclusion of 80,020 patient discharges across 73,813 patients (Supplementary figure SF2)
Patients who had the lowest rate of intensive care unit (ICU) admission, higher discharge a bADL hierarchy (ADLH) and the longest length of stay were most likely to be long term care facility (LTCF) ready; patients with the lowest discharge ADLH and shortest length of stay tended to have no outcome at 180 days (Table 1)

Summary

Introduction

Functional status is a patient-important, patient-centered measurement. The utility of functional status measures to inform post-discharge patient needs is unknown. We sought to examine the utility of routinely collected functional status measures gathered from older hospitalized patients to predict a panel of post-discharge outcomes. Predicting health service use after discharge from acute hospital admissions is generally based on physiologic measurements such as age, diagnoses, or test results Such parameters, are narrow definitions of health that do not fully reflect the patient as an. The Health Outcomes for Better Information in Care (HOBIC) initiative was a large-scale pilot program implemented in Ontario, Canada from 2008 to 2016 that sought to routinely capture data concerning patient function, self-care, symptom burden, and safety for all hospitalized patients at admission and discharge [16]. Using discharge functional status data collected during the program, we sought to examine its utility in predicting a panel of post-hospital discharge outcomes. We hypothesized that for all outcomes, discharge functional status will be an independent predictor positively associated with each outcome, and the strongest predictors of future placement on waitlist for or admission to an LTCF and death post-discharge

Methods

Results

Conclusion