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Payment rates for personal care assistants and the use of long-term services and supports among those dually eligible for Medicare and Medicaid.

ABSTRACT: To examine the association between payment rates for personal care assistants and use of long-term services and supports (LTSS) following hospital discharge among dual eligible Medicare and Medicaid beneficiaries.State hospital discharge, Medicaid and Medicare claims, and assessment data on California Medicaid LTSS users from 2006 to 2008.Cross-sectional study. We used multinomial logistic regression to analyze county personal care assistant payment rates and postdischarge LTSS use, and estimate marginal probabilities of each outcome across the range of rates paid in California.We identified dual eligible Medicare and Medicaid adult beneficiaries discharged from an acute care hospital with no hospitalizations or LTSS use in the preceding 12 months.Personal care assistant payment rates were modestly associated with home and community-based services (HCBS) use versus nursing facility entry following hospital discharge (RRR 1.2, 95 percent CI: 1.0-1.4). For a rate of $6.75 per hour, the probability of HCBS use was 5.6 percent (95 percent CI: 4.2-7.1); at $11.75 per hour, 18.0 percent (95 percent CI: 12.5-23.4). Payment rate was not associated with the probability of nursing facility entry.Higher payment rates for personal care assistants may increase utilization of HCBS, but with limited substitution for nursing facility care.

SUBMITTER: Ko M

PROVIDER: S-EPMC4254126 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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Payment rates for personal care assistants and the use of long-term services and supports among those dually eligible for Medicare and Medicaid.

Ko Michelle M Newcomer Robert R Kang Taewoon T Hulett Denis D Chu Philip P Bindman Andrew B AB

Health services research 20141018 6

<h4>Objective</h4>To examine the association between payment rates for personal care assistants and use of long-term services and supports (LTSS) following hospital discharge among dual eligible Medicare and Medicaid beneficiaries.<h4>Data sources</h4>State hospital discharge, Medicaid and Medicare claims, and assessment data on California Medicaid LTSS users from 2006 to 2008.<h4>Study design</h4>Cross-sectional study. We used multinomial logistic regression to analyze county personal care assi ...[more]

PMID: 25327166

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Project description:ImportancePredicting payments for particular conditions or populations is essential for research, benchmarking, public reporting, and calculations for population-based programs. Centers for Medicare & Medicaid Services (CMS) models often group codes into disease categories, but using single, rather than grouped, diagnostic codes and leveraging present on admission (POA) codes may enhance these models.ObjectiveTo determine whether changes to the candidate variables in CMS models would improve risk models predicting patient total payment within 30 days of hospitalization for acute myocardial infarction (AMI), heart failure (HF), and pneumonia.Design, setting, and participantsThis comparative effectiveness research study used data from Medicare fee-for-service hospitalizations for AMI, HF, and pneumonia at acute care hospitals from July 1, 2013, through September 30, 2015. Payments across multiple care settings, services, and supplies were included and adjusted for geographic and policy variations, corrected for inflation, and winsorized. The same data source was used but varied for the candidate variables and their selection, and the method used by CMS for public reporting that used grouped codes was compared with variations that used POA codes and single diagnostic codes. Combinations of use of POA codes, separation of index admission diagnoses from those in the previous 12 months, and use of individual International Classification of Diseases, Ninth Revision, Clinical Modification codes instead of grouped diagnostic categories were tested. Data analysis was performed from December 4, 2017, to June 10, 2019.Main outcomes and measuresThe models' goodness of fit was compared using root mean square error (RMSE) and the McFadden pseudo R2.ResultsAmong the 1 943 049 total hospitalizations of the study participants, 343 116 admissions were for AMI (52.5% male; 37.4% aged ≤74 years), 677 044 for HF (45.5% male; 25.9% aged ≤74 years), and 922 889 for pneumonia (46.4% male; 28.2% aged ≤74 years). The mean (SD) 30-day payment was $23 103 ($18 221) for AMI, $16 365 ($12 527) for HF, and $17 097 ($12 087) for pneumonia. Each incremental model change improved the pseudo R2 and RMSE. Incorporating all 3 changes improved the pseudo R2 of the patient-level models from 0.077 to 0.129 for AMI, from 0.042 to 0.129 for HF, and from 0.114 to 0.237 for pneumonia. Parallel improvements in RMSE were found for all 3 conditions.Conclusions and relevanceLeveraging POA codes, separating index from previous diagnoses, and using single diagnostic codes improved payment models. Better models can potentially improve research, benchmarking, public reporting, and calculations for population-based programs.

Dataset Information

Payment rates for personal care assistants and the use of long-term services and supports among those dually eligible for Medicare and Medicaid.

Publications

Payment rates for personal care assistants and the use of long-term services and supports among those dually eligible for Medicare and Medicaid.

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