Statistical analysis plan for the NU IMPACT stepped-wedge cluster randomized trial

Denise M. Scholtens; Nicola Lancki; Karla Hemming; David Cella; Justin D. Smith

doi:10.1016/j.cct.2024.107603

Statistical analysis plan for the NU IMPACT stepped-wedge cluster randomized trial

Denise M. Scholtens^*, Nicola Lancki, Karla Hemming, David Cella, Justin D. Smith

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

Background: As part of the IMPACT Consortium of three effectiveness-implementation trials, the NU IMPACT trial was designed to evaluate implementation and effectiveness outcomes for an electronic health record (EHR)-embedded symptom monitoring and management program for outpatient cancer care. NU IMPACT uses a unique stepped-wedge cluster randomized design, involving six clusters of 26 clinics, for evaluation of implementation outcomes with an embedded patient-level randomized trial to evaluate effectiveness outcomes. Collaborative, consortium-wide efforts to ensure use of the most robust and recent analytic methodologies for stepped-wedge trials motivated updates to the statistical analysis plan for implementation outcomes in the NU IMPACT trial. Methods: In the updated statistical analysis plan for NU IMPACT, the primary implementation outcome patient adoption, as measured by clinic-level monthly proportions of patient engagement with the EHR-based cancer symptom monitoring system, will be analyzed using generalized least squares linear regression with auto-regressive errors and adjustment for cluster and time effects (underlying secular trends). A similar strategy will be used for secondary patient and provider implementation outcomes. Discussion: The analytic updates described here resulted from highly iterative, collaborative efforts among statisticians, implementation scientists, and trial leads in the IMPACT Consortium. This updated statistical analysis plan will serve as the a priori specified approach for analyzing implementation outcomes for the NU IMPACT trial.

Original language	English (US)
Article number	107603
Journal	Contemporary Clinical Trials
Volume	143
DOIs	https://doi.org/10.1016/j.cct.2024.107603
State	Published - Aug 2024

Funding

The Improving the Management of symPtoms during And following Cancer Treatment (IMPACT) Consortium is a Cancer Moonshot Research Initiative under the authorization of the 2016 United States 21st Century Cures Act. Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number UM1CA233035 to D. Cella. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Keywords

Cancer symptom monitoring
Electronic health record
Implementation outcomes
Stepped-wedge trial

ASJC Scopus subject areas

Pharmacology (medical)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.cct.2024.107603

Cite this

@article{6e0e2d5829514edfa78be90f59547476,

title = "Statistical analysis plan for the NU IMPACT stepped-wedge cluster randomized trial",

abstract = "Background: As part of the IMPACT Consortium of three effectiveness-implementation trials, the NU IMPACT trial was designed to evaluate implementation and effectiveness outcomes for an electronic health record (EHR)-embedded symptom monitoring and management program for outpatient cancer care. NU IMPACT uses a unique stepped-wedge cluster randomized design, involving six clusters of 26 clinics, for evaluation of implementation outcomes with an embedded patient-level randomized trial to evaluate effectiveness outcomes. Collaborative, consortium-wide efforts to ensure use of the most robust and recent analytic methodologies for stepped-wedge trials motivated updates to the statistical analysis plan for implementation outcomes in the NU IMPACT trial. Methods: In the updated statistical analysis plan for NU IMPACT, the primary implementation outcome patient adoption, as measured by clinic-level monthly proportions of patient engagement with the EHR-based cancer symptom monitoring system, will be analyzed using generalized least squares linear regression with auto-regressive errors and adjustment for cluster and time effects (underlying secular trends). A similar strategy will be used for secondary patient and provider implementation outcomes. Discussion: The analytic updates described here resulted from highly iterative, collaborative efforts among statisticians, implementation scientists, and trial leads in the IMPACT Consortium. This updated statistical analysis plan will serve as the a priori specified approach for analyzing implementation outcomes for the NU IMPACT trial.",

keywords = "Cancer symptom monitoring, Electronic health record, Implementation outcomes, Stepped-wedge trial",

author = "Scholtens, {Denise M.} and Nicola Lancki and Karla Hemming and David Cella and Smith, {Justin D.}",

note = "Publisher Copyright: {\textcopyright} 2024 The Authors",

year = "2024",

month = aug,

doi = "10.1016/j.cct.2024.107603",

language = "English (US)",

volume = "143",

journal = "Contemporary Clinical Trials",

issn = "1551-7144",

publisher = "Elsevier Inc.",

}

TY - JOUR

T1 - Statistical analysis plan for the NU IMPACT stepped-wedge cluster randomized trial

AU - Scholtens, Denise M.

AU - Lancki, Nicola

AU - Hemming, Karla

AU - Cella, David

AU - Smith, Justin D.

PY - 2024/8

Y1 - 2024/8

N2 - Background: As part of the IMPACT Consortium of three effectiveness-implementation trials, the NU IMPACT trial was designed to evaluate implementation and effectiveness outcomes for an electronic health record (EHR)-embedded symptom monitoring and management program for outpatient cancer care. NU IMPACT uses a unique stepped-wedge cluster randomized design, involving six clusters of 26 clinics, for evaluation of implementation outcomes with an embedded patient-level randomized trial to evaluate effectiveness outcomes. Collaborative, consortium-wide efforts to ensure use of the most robust and recent analytic methodologies for stepped-wedge trials motivated updates to the statistical analysis plan for implementation outcomes in the NU IMPACT trial. Methods: In the updated statistical analysis plan for NU IMPACT, the primary implementation outcome patient adoption, as measured by clinic-level monthly proportions of patient engagement with the EHR-based cancer symptom monitoring system, will be analyzed using generalized least squares linear regression with auto-regressive errors and adjustment for cluster and time effects (underlying secular trends). A similar strategy will be used for secondary patient and provider implementation outcomes. Discussion: The analytic updates described here resulted from highly iterative, collaborative efforts among statisticians, implementation scientists, and trial leads in the IMPACT Consortium. This updated statistical analysis plan will serve as the a priori specified approach for analyzing implementation outcomes for the NU IMPACT trial.

AB - Background: As part of the IMPACT Consortium of three effectiveness-implementation trials, the NU IMPACT trial was designed to evaluate implementation and effectiveness outcomes for an electronic health record (EHR)-embedded symptom monitoring and management program for outpatient cancer care. NU IMPACT uses a unique stepped-wedge cluster randomized design, involving six clusters of 26 clinics, for evaluation of implementation outcomes with an embedded patient-level randomized trial to evaluate effectiveness outcomes. Collaborative, consortium-wide efforts to ensure use of the most robust and recent analytic methodologies for stepped-wedge trials motivated updates to the statistical analysis plan for implementation outcomes in the NU IMPACT trial. Methods: In the updated statistical analysis plan for NU IMPACT, the primary implementation outcome patient adoption, as measured by clinic-level monthly proportions of patient engagement with the EHR-based cancer symptom monitoring system, will be analyzed using generalized least squares linear regression with auto-regressive errors and adjustment for cluster and time effects (underlying secular trends). A similar strategy will be used for secondary patient and provider implementation outcomes. Discussion: The analytic updates described here resulted from highly iterative, collaborative efforts among statisticians, implementation scientists, and trial leads in the IMPACT Consortium. This updated statistical analysis plan will serve as the a priori specified approach for analyzing implementation outcomes for the NU IMPACT trial.

KW - Cancer symptom monitoring

KW - Electronic health record

KW - Implementation outcomes

KW - Stepped-wedge trial

UR - http://www.scopus.com/inward/record.url?scp=85195602220&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85195602220&partnerID=8YFLogxK

U2 - 10.1016/j.cct.2024.107603

DO - 10.1016/j.cct.2024.107603

M3 - Article

C2 - 38852769

AN - SCOPUS:85195602220

SN - 1551-7144

VL - 143

JO - Contemporary Clinical Trials

JF - Contemporary Clinical Trials

M1 - 107603

ER -

Statistical analysis plan for the NU IMPACT stepped-wedge cluster randomized trial

Abstract

Funding

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this