Evidence map›Paper›PMID 30295927›Full record

Observational studyJournal of the American Geriatrics Society2018

Long-Term Acute Care Hospital Use of Non-Mechanically Ventilated Hospitalized Older Adults.

Anil N Makam, Oanh Kieu Nguyen, Lei Xuan, Michael E Miller, Ethan A Halm

Abstract readObservational Study
In one paragraph

Observational study in Journal of the American Geriatrics Society, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

5 authors.

Anil N MakamDepartments of Internal Medicine.
Oanh Kieu NguyenDepartments of Internal Medicine.
Lei XuanClinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas.
Michael E MillerClinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas.
Ethan A HalmDepartments of Internal Medicine.

Funding

UT Southwestern Center for Translational Medicine (UL1/KL2/TL1)UL1TR001105 · NCATS · UT SOUTHWESTERN MEDICAL CENTER · PI TOTO, ROBERT DANIEL · 2013 to 2017
$24.5M
UT Southwestern Center of Patient-Centered Outcomes Research (PCOR)R24HS022418 · AHRQ · UT SOUTHWESTERN MEDICAL CENTER · PI HALM, ETHAN A · 2013 to 2017
$5.0M
Post-Acute Care in the Elderly: the Role of Long-Term Acute Care HospitalsK23AG052603 · NIA · UT SOUTHWESTERN MEDICAL CENTER · PI MAKAM, ANIL NAGA · 2016 to 2021
$1.1M
Addressing Social Vulnerabilities to Prevent Hospital Readmissions in Adults with Cardiovascular DiseaseK23HL133441 · NHLBI · UT SOUTHWESTERN MEDICAL CENTER · PI NGUYEN, OANH KIEU · 2017 to 2021
$932k
Role of Long-Term Acute Care HospitalsR03AG053291 · NIA · UT SOUTHWESTERN MEDICAL CENTER · PI HALM, ETHAN A · 2016 to 2017
$243k
AHRQ HHS R24 HS022418NCATS NIH HHS UL1 TR001105NCATS NIH HHS UL1TR001105NHLBI NIH HHS K23 HL133441NHLBI NIH HHS K23HL133441NIA NIH HHS K23 AG052603NIA NIH HHS K23AG052603NIA NIH HHS R03 AG053291NIA NIH HHS R03AG053291
6 · The paper itself

Abstract

objectivesTo determine why non-mechanically ventilated hospitalized older adults are transferred to long-term acute care (LTAC) hospitals rather than remaining in the hospital.

designObservational cohort.

settingNational Medicare data.

participantsNon-mechanically ventilated hospitalized adults aged 65 and older with fee-for-service Medicare in 2012 who were transferred to an LTAC hospital (n=1,831) or had a prolonged hospitalization without transfer (average hospital length of stay or longer of those transferred to an LTAC hospital) and had one of the 50 most common hospital diagnoses leading to LTAC transfer (N=12,875). MEASUREMENTS: We assessed predictors of transfer using a multilevel model, adjusting for patient-, hospital-, and hospital referral region (HRR)-level factors. We estimated proportions of variance at each level and adjusted hospital- and HRR-specific LTAC transfer rates using sequential models.

resultsThe strongest predictor of transfer was being hospitalized near an LTAC hospital (<1.4 vs > 33.6 miles, adjusted odds ratio=6.2, 95% confidence interval (CI)=4.2-9.1). After adjusting for case mix, differences between hospitals explained 15.4% of the variation in LTAC use and differences between regions explained 27.8%. Case mix-adjusted LTAC use was high in the South, where many HRRs had rates between 20.3% and 53.1%, whereas many HRRs were less than 5.4% in the Pacific Northwest, North, and New England. From our fully adjusted model, the median adjusted hospital LTAC transfer rate was 7.2% (interquartile range 2.8-17.5%), with substantial within-region variation (intraclass coefficient=0.25, 95% CI=0.21-0.30).

conclusionsNearly half of the variation in LTAC use is independent of illness severity and is explained by which hospital and what region the individual was hospitalized in. Because of the greater fragmentation of care and Medicare spending with LTAC transfers (because LTAC hospitals generate a separate bundled payment from the hospital), greater attention is needed to define the optimal role of LTAC hospitals in caring for older adults. J Am Geriatr Soc 66:2112-2119, 2018.

Indexed as

Health ExpendituresHospitalsPatient TransferAgedAged, 80 and overFee-for-Service PlansFemaleHospitalizationHumansLong-Term CareMaleMedicareRespiration, ArtificialRetrospective StudiesUnited Stateshealth policylong-term acute care hospitalMedicarepostacute carevariation

Identifiers

PMID30295927
PMCPMC6239216

What OpenQuestion holds

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Registered trials

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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.