Evidence map›Paper›PMID 39987567›Full record

ArticleJournal of evaluation in clinical practice2025

Implementation of a "People-Like-Me" Tool for Personalized Rehabilitation After Total Knee Arthroplasty: A Mixed Methods Pilot Study.

Jeremy Graber, Lauren A Hinrichs-Kinney, Laura Churchill, Daniel D Matlock, Andrew Kittelson, Adam Lutz, Michael Bade, Jennifer Stevens-Lapsley

Abstract read
In one paragraph

Article in Journal of evaluation in clinical practice, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Jeremy GraberEastern Colorado VA Health Care System, Geriatric Research Education and Clinical Center (GRECC), Aurora, Colorado, USA.ORCID 0000-0002-2365-7780
Lauren A Hinrichs-KinneyEastern Colorado VA Health Care System, Geriatric Research Education and Clinical Center (GRECC), Aurora, Colorado, USA.
Laura ChurchillPhysical Therapy Program, Department of Physical Medicine and Rehabilitation, University of Colorado, Aurora, Colorado, USA.
Daniel D MatlockEastern Colorado VA Health Care System, Geriatric Research Education and Clinical Center (GRECC), Aurora, Colorado, USA.
Andrew KittelsonSchool of Physical Therapy and Rehabilitation Science, University of Montana, Missoula, Montana, USA.
Adam LutzATI Physical Therapy, Greenville, South Carolina, USA.
Michael BadeEastern Colorado VA Health Care System, Geriatric Research Education and Clinical Center (GRECC), Aurora, Colorado, USA.
Jennifer Stevens-LapsleyEastern Colorado VA Health Care System, Geriatric Research Education and Clinical Center (GRECC), Aurora, Colorado, USA.

Funding

AHRQ HHS R01 HS025692This work was supported by the Agency for Healthcare Research and Quality (R01 HS025692) and the VA Eastern Colorado Geriatric Research Education and Clinical Center (GRECC) Advanced Geriatrics Research Fellowship. The contents do not represent the view of the U.S. Department of Veterans Affairs or the United States Government.
6 · The paper itself

Abstract

rationaleWhile there are numerous tools available to inform if and when to use total knee arthroplasty (TKA), very few tools exist to help guide the recovery period after surgery. AIMS AND

objectivesWe piloted a decision support tool that promotes a "people-like-me" (PLM) approach to rehabilitation after total knee arthroplasty (TKA). The PLM approach encourages person-centered care by "using historical outcomes data from similar (past) patients as a template of what to expect for a new patient". In this study, we evaluated how successfully the PLM tool was implemented and examined contextual factors that may have influenced its implementation.

methodsTwo outpatient physical therapy clinics (Clinics A and B) piloted the PLM tool from September 2020 - December 2022. We gathered data related to its implementation from multiple sources including the electronic health record (EHR), the tool itself, and surveys and interviews with patients and clinicians. We used an explanatory sequential mixed methods design to analyze the data overall and separately by each clinic.

resultsOverall, the clinics met most pre-specified implementation targets, but did not use the tool as frequently as intended. Both clinics identified time, technology, and scheduling barriers to using the tool, but Clinic A scored higher in nearly every implementation outcome. Clinic A's success may have been related to its clinicians' higher level of experience, more positive attitudes towards the tool, and more active approach to implementation compared to Clinic B.

conclusionsThe clinics met most of our implementation targets, but Clinic A experienced more success than Clinic B. Future efforts to implement this PLM tool should (1) engage clinicians as active participants in the implementation process, (2) explore whether incorporating treatment recommendations into the PLM tool and/or using alternative training strategies can enhance its ability to alter clinician behavior, (3) integrate the tool within the EHR to complement existing workflows and mitigate implementation barriers, and (4) include randomized controlled trials that evaluate the tool's effectiveness and scalability across diverse clinical settings.

Indexed as

Arthroplasty, Replacement, KneeDecision Support TechniquesAgedElectronic Health RecordsFemaleHumansMaleMiddle AgedPatient-Centered CarePhysical Therapy ModalitiesPilot Projectsclinical decision supportimplementation sciencemixed methodsprecision medicinetotal knee arthroplasty

Identifiers

PMID39987567
PMCPMC13116475

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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.