Evidence map›Paper›PMID 41633538›Full record

ArticleJournal of the American Medical Directors Association2026

An Updated Mortality and Community Discharge Prognostic Model for Older Adults Admitted to Skilled Nursing Facilities for Post-Acute Care.

W James Deardorff, Siqi Gan, Bocheng Jing, Kenneth Lam, W John Boscardin, Alexander K Smith, Sei J Lee

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the American Medical Directors Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

W James DeardorffDivision of Geriatrics, University of California, San Francisco, San Francisco, CA, USA; Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, San Francisco, CA, USA. Electronic address: william.deardorff@ucsf.edu.
Siqi GanDivision of Geriatrics, University of California, San Francisco, San Francisco, CA, USA; Northern California Institute for Research and Education, San Francisco, CA, USA.
Bocheng JingDivision of Geriatrics, University of California, San Francisco, San Francisco, CA, USA; Department of Epidemiology and Population Health, Stanford University, Palo Alto, CA, USA.
Kenneth LamDivision of Geriatric Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA.
W John BoscardinDivision of Geriatrics, University of California, San Francisco, San Francisco, CA, USA; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.
Alexander K SmithDivision of Geriatrics, University of California, San Francisco, San Francisco, CA, USA; Geriatrics, Palliative and Extended Care Service Line, San Francisco Veterans Affairs Health Care System, San Francisco, CA, USA.
Sei J LeeDivision of Geriatrics, University of California, San Francisco, San Francisco, CA, USA; Geriatrics, Palliative and Extended Care Service Line, San Francisco Veterans Affairs Health Care System, San Francisco, CA, USA.

Funding

Enhancing prognosis communication for older adults in skilled nursing facilitiesK76AG094730 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI William James Deardorff · 2025 to 2026
$480k
A comprehensive prognostic model for older adults discharged to skilled nursing facilities.R03AG082859 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI DEARDORFF, WILLIAM JAMES · 2023 to 2024
$323k
NIA NIH HHS K76 AG094730NIA NIH HHS R03 AG082859
6 · The paper itself

Abstract

objectivesWe previously developed a multi-outcome prognostic model for older adults admitted to skilled nursing facilities (SNFs) for short-term rehab using Medicare data. However, incorporating predictors from the Minimum Data Set (MDS), a mandated comprehensive assessment, may improve model performance. This study sought to develop an updated model with MDS elements for use on day 7 of SNF admission when clinical trajectories are more established.

designRetrospective cohort study. SETTING AND

participantsTwenty percent national sample of community-dwelling Medicare Fee-for-Service beneficiaries aged ≥66 admitted to an SNF for at least 7 days following a hospitalization between 2017 and 2019.

methodsWe predicted 2 outcomes: 6-month mortality and successful community discharge (community discharge without rehospitalization or death in the subsequent 30 days). For model development, we started with predictors from our published Medicare-based model (age, sex, Medicaid status, discharge diagnosis, hospital length of stay, admission type, comorbidities, prior hospitalizations), used Least Absolute Shrinkage and Selection Operator (LASSO) on MDS elements for variable selection, and performed logistic regression to determine predictor coefficients. Model performance was assessed by concordance statistics (c-statistics), calibration plots, and decision curve analysis.

resultsThe cohort included 426,680 individuals [mean age 81.3 years (SD = 8.3), 62.7% female, 7.9% Black]. Overall, 19.9% died within 6 months, and 57.6% experienced a successful community discharge. The updated MDS model, which included Medicare predictors and 6 MDS items (activities of daily living score, cognitive status, urinary incontinence, bowel incontinence, oxygen use, walking balance), showed improvements over the Medicare model in discrimination [bootstrapped optimism-corrected c-statistic of 0.789 (95% CI, 0.787-0.790) vs 0.747 (95% CI, 0.745-0.749) for 6-month mortality and 0.730 (95% CI, 0.728-0.731) vs 0.685 (95% CI, 0.683-0.687) for successful community discharge, respectively], net benefit, and fraction of new information. Models showed good calibration. CONCLUSIONS AND IMPLICATIONS: Incorporating MDS data from the first 7 days of SNF admission improved the accuracy of predictions of 6-month mortality and successful community discharge.

Indexed as

MortalityPatient DischargeSkilled Nursing FacilitiesSubacute CareAgedAged, 80 and overFemaleHumansMaleMedicarePrognosisRetrospective StudiesUnited StatesMinimum Data Setmortalitypost-acute carePrognostic modelskilled nursing facility

Identifiers

PMID41633538
PMCPMC13070420

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.