TY - JOUR
T1 - A comparison of three methods in categorizing functional status to predict hospital readmission across post-acute care
AU - Li, Chih Ying
AU - Karmarkar, Amol
AU - Kuo, Yong Fang
AU - Mehta, Hemalkumar B.
AU - Mallinson, Trudy
AU - Haas, Allen
AU - Kumar, Amit
AU - Ottenbacher, Kenneth J.
N1 - Publisher Copyright:
© 2020 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2020/5
Y1 - 2020/5
N2 - Background Methods used to categorize functional status to predict health outcomes across post-acute care settings vary significantly. Objectives We compared three methods that categorize functional status to predict 30-day and 90-day hospital readmission across inpatient rehabilitation facilities (IRF), skilled nursing facilities (SNF) and home health agencies (HHA). Research design Retrospective analysis of 2013–2014 Medicare claims data (N = 740,530). Data were randomly split into two subsets using a 1:1 ratio. We used half of the cohort (development subset) to develop functional status categories for three methods, and then used the rest (testing subset) to compare outcome prediction. Three methods to generate functional categories were labeled as: Method I, percentile based on proportional distribution; Method II, percentile based on change score distribution; and Method III, functional staging categories based on Rasch person strata. We used six differentiation and classification statistics to determine the optimal method of generating functional categories. Setting IRF, SNF and HHA. Subjects We included 130,670 (17.7%) Medicare beneficiaries with stroke, 498,576 (67.3%) with lower extremity joint replacement and 111,284 (15.0%) with hip and femur fracture. Measures Unplanned 30-day and 90-day hospital readmission. Results For all impairment conditions, Method III best predicted 30-day and 90-day hospital readmission. However, we observed overlapping confidence intervals among some comparisons of three methods. The bootstrapping of 30-day and 90-day hospital readmission predictive models showed the area under curve for Method III was statistically significantly higher than both Method I and Method II (all paired-comparisons, p<.001), using the testing sample. Conclusions Overall, functional staging was the optimal method to generate functional status categories to predict 30-day and 90-day hospital readmission. To facilitate clinical and scientific use, we suggest the most appropriate method to categorize functional status should be based on the strengths and weaknesses of each method.
AB - Background Methods used to categorize functional status to predict health outcomes across post-acute care settings vary significantly. Objectives We compared three methods that categorize functional status to predict 30-day and 90-day hospital readmission across inpatient rehabilitation facilities (IRF), skilled nursing facilities (SNF) and home health agencies (HHA). Research design Retrospective analysis of 2013–2014 Medicare claims data (N = 740,530). Data were randomly split into two subsets using a 1:1 ratio. We used half of the cohort (development subset) to develop functional status categories for three methods, and then used the rest (testing subset) to compare outcome prediction. Three methods to generate functional categories were labeled as: Method I, percentile based on proportional distribution; Method II, percentile based on change score distribution; and Method III, functional staging categories based on Rasch person strata. We used six differentiation and classification statistics to determine the optimal method of generating functional categories. Setting IRF, SNF and HHA. Subjects We included 130,670 (17.7%) Medicare beneficiaries with stroke, 498,576 (67.3%) with lower extremity joint replacement and 111,284 (15.0%) with hip and femur fracture. Measures Unplanned 30-day and 90-day hospital readmission. Results For all impairment conditions, Method III best predicted 30-day and 90-day hospital readmission. However, we observed overlapping confidence intervals among some comparisons of three methods. The bootstrapping of 30-day and 90-day hospital readmission predictive models showed the area under curve for Method III was statistically significantly higher than both Method I and Method II (all paired-comparisons, p<.001), using the testing sample. Conclusions Overall, functional staging was the optimal method to generate functional status categories to predict 30-day and 90-day hospital readmission. To facilitate clinical and scientific use, we suggest the most appropriate method to categorize functional status should be based on the strengths and weaknesses of each method.
UR - http://www.scopus.com/inward/record.url?scp=85084325512&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85084325512&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0232017
DO - 10.1371/journal.pone.0232017
M3 - Article
C2 - 32379765
AN - SCOPUS:85084325512
SN - 1932-6203
VL - 15
JO - PloS one
JF - PloS one
IS - 5
M1 - e0232017
ER -