Literature DB >> 31327646

The Role of Social Support and Psychological Distress in Predicting Discharge: A Pilot Study for Hip and Knee Arthroplasty Patients.

Kathryn E Zeppieri1, Katie A Butera2, Dane Iams3, Hari K Parvataneni4, Steven Z George5.   

Abstract

BACKGROUND: Bundled payment initiatives for joint replacement have prompted re-evaluation of the continuum of care with emphasis on anticipating disposition needs. The purpose of this study is to investigate the role of social support and psychological distress in patient optimization after lower joint replacement.
METHODS: Two hundred thirty-one patients undergoing elective joint replacement completed the Risk Assessment and Predictive Tool (RAPT) (social support assessment) and modified STarT Back Tool (mSBT) (assessment of pain-related psychological distress). Outcomes of interest were length of stay (LOS) and discharge location (home vs facility).
RESULTS: No significant differences in mSBT scores were observed across RAPT levels when comparing individuals by discharge location (P > .05). There was significant indirect effect (0.07; P < .001) between mSBT and LOS. Therefore, the mSBT does not predict discharge location as a standalone metric for this sample. Mediation analysis for LOS indicates that higher psychological distress was predictive of longer LOS. Higher psychological distress and lower social support are associated with longer LOS. Despite higher psychological distress scores, higher social support scores are associated with shorter LOS.
CONCLUSION: Analysis of this cohort suggests that pre-operative assessments of social and psychological constructs may provide preparatory information for patient discharge status. The RAPT is important for predicting LOS and discharge location. The mSBT may be important for predicting LOS for individuals with low to moderate social support.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Risk Assessment and Predictive Tool; bundling; joint replacement; modified STarT Back Tool; optimization; outcomes

Year:  2019        PMID: 31327646     DOI: 10.1016/j.arth.2019.06.033

Source DB:  PubMed          Journal:  J Arthroplasty        ISSN: 0883-5403            Impact factor:   4.757


  4 in total

1.  Assessment of postoperative health functioning after knee arthroplasty in relation to pain catastrophizing: a 6-month follow-up cohort study.

Authors:  Marc Terradas-Monllor; Mirari Ochandorena-Acha; Julio Salinas-Chesa; Sergi Ramírez; Hector Beltran-Alacreu
Journal:  PeerJ       Date:  2020-09-09       Impact factor: 2.984

2.  Phenotypic profile clustering pragmatically identifies diagnostically and mechanistically informative subgroups of chronic pain patients.

Authors:  Sheila M Gaynor; Andrey Bortsov; Eric Bair; Roger B Fillingim; Joel D Greenspan; Richard Ohrbach; Luda Diatchenko; Andrea Nackley; Inna E Tchivileva; William Whitehead; Aurelio A Alonso; Thomas E Buchheit; Richard L Boortz-Marx; Wolfgang Liedtke; Jongbae J Park; William Maixner; Shad B Smith
Journal:  Pain       Date:  2021-05-01       Impact factor: 7.926

Review 3.  Compilation and Analysis of Web-Based Orthopedic Personalized Predictive Tools: A Scoping Review.

Authors:  Patrick Curtin; Alexandra Conway; Liu Martin; Eugenia Lin; Prakash Jayakumar; Eric Swart
Journal:  J Pers Med       Date:  2020-11-12

4.  Influence of weekday of admission and level of distress on length of hospital stay in patients with low back pain: a retrospective cohort study.

Authors:  Emanuel Brunner; André Meichtry; Davy Vancampfort; Reinhard Imoberdorf; David Gisi; Wim Dankaerts; Anita Graf; Stefanie Wipf Rebsamen; Daniela Suter; Lukas Martin Wildi; Stefan Buechi; Cornel Sieber
Journal:  BMC Musculoskelet Disord       Date:  2021-08-05       Impact factor: 2.362

  4 in total

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