Evidence map›Paper›PMID 41865059›Full record

ArticlePilot and feasibility studies2026

Optimization of care and recovery in older colorectal cancer surgery patients: a hybrid effectiveness-implementation pilot study protocol.

Ferhat Yildiz, Stephen J Bartels, Christy Cauley, Matthew Vrees, Benjamin F Crabtree, Edward R Marcantonio, Christine S Ritchie, John O Hwabejire, Rocco Ricciardi, Stacie G Deiner and 1 more

Registry-linked trialAbstract read
In one paragraph

Article in Pilot and feasibility studies, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06752031 (Optimization of Care and Recovery in Older Colorectal Surgery Patients), which is not on this map. Not yet cited in PubMed.

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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.

NCT06752031 narecruitingnot on this map

Optimization of Care and Recovery in Older Colorectal Surgery Patients: A Hybrid Effectiveness-Implementation Pilot Study Protocol

TypeinterventionalSponsorMassachusetts General HospitalRan2025 to 2027Enrolled30ConditionsColorectal Surgery, Care Transition, Older Adults (65 Years and Older)ArmsOSCAR-S Care Transition Model
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

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5 · Who and what money

Authors and funding

11 authors.

Ferhat YildizCenter for Aging and Serious Illness, Massachusetts General Hospital, Boston, MA, USA.
Stephen J BartelsHarvard Medical School, Boston, MA, USA.
Christy CauleyCenter for Aging and Serious Illness, Massachusetts General Hospital, Boston, MA, USA.
Matthew VreesDepartment of Surgery, The Miriam Hospital, Providence, RI, USA.
Benjamin F CrabtreeDepartment of Family Medicine and Community Health, Division of Research, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, USA.
Edward R MarcantonioHarvard Medical School, Boston, MA, USA.
Christine S RitchieCenter for Aging and Serious Illness, Massachusetts General Hospital, Boston, MA, USA.
John O HwabejireHarvard Medical School, Boston, MA, USA.
Rocco RicciardiHarvard Medical School, Boston, MA, USA.
Stacie G DeinerDepartment of Anesthesiology and Perioperative Medicine, Dartmouth Hitchcock Medical Center and Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
Sevdenur CizginerCenter for Aging and Serious Illness, Massachusetts General Hospital, Boston, MA, USA. scizginer1@mgh.harvard.edu.

Funding

Optimizing care for older surgical patients: atheory-guided implementation science approachK76AG078620 · NIA · RHODE ISLAND HOSPITAL · PI Sevdenur Cizginer · 2022 to 2026
$1.2M
NIA NIH HHS K76 AG078620NIA NIH HHS K76AG078620
6 · The paper itself

Abstract

backgroundThe exponential rise in colorectal cancer surgeries among older adults combined with 30-day readmission rates as high as 25% highlights the crucial need to optimize post-discharge care. While geriatrics surgery programs such as the Optimization of Senior Care and Recovery (OSCAR) model improve outcomes, they do not address the post-discharge transition. This study will address this gap by systematically integrating the OSCAR program with an evidence-based Care Transitions Intervention (CTI), using implementation science frameworks to guide adaptation. The resulting integrated model, OSCAR-S, will be evaluated in a pilot feasibility hybrid type 1 implementation-effectiveness trial.

methodsThis three-phase project will apply implementation science frameworks to adapt and test an integrated care transition model (OSCAR-S) for older colorectal surgery patients. The first phase involves qualitative interviews with stakeholders to inform the adaptation of the combined model (OSCAR-S), guided by the ADAPT, Consolidated Framework for Implementation Research (CFIR), and FRAME frameworks. Subsequently, we will determine an optimal implementation strategy, guided by the Expert Recommendations for Implementing Change (ERIC). The final phase will include a pilot feasibility type I implementation-effectiveness trial. Guided by the RE-AIM framework and through a mixed methods approach, we will collect quantitative data from electronic medical records and qualitative data from post-implementation interviews to evaluate reach, effectiveness, adoption, implementation, and maintenance. DISCUSSION: This study will offer insights into the adaptation, implementation, and assessment of an integrated care transition model (OSCAR-S) for older adults undergoing major colorectal surgery. The model integrates core components of two evidence-based interventions: OSCAR (geriatrics surgery co-management) and CTI (Care Transitions Intervention) programs. A novel aspect of this work is the application of multiple implementation science frameworks to guide this process. The findings will inform future strategies to optimize care transitions and postoperative outcomes, demonstrating how the implementation science approach can enhance the effectiveness and scalability of integrated care models.

trial registrationThis trial was registered at ClinicalTrials.gov ( NCT06752031 ). Registered December 30, 2024.

Indexed as

Care transitionColorectal surgeryGeriatric surgeryImplementation science

Identifiers

PMID41865059
PMCPMC13130537

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Registered trials

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.