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Pre-implementation adaptation of primary care cancer prevention clinical decision support in a predominantly rural healthcare system

  • Melissa L. Harry
  • , Daniel M. Saman
  • , Anjali R. Truitt
  • , Clayton I. Allen
  • , Kayla M. Walton
  • , Patrick J. O'Connor
  • , Heidi L. Ekstrom
  • , Jo Ann M. Sperl-Hillen
  • , Joseph A. Bianco
  • , Thomas E. Elliott

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Cancer is a leading cause of death in the United States. Primary care providers (PCPs) juggle patient cancer prevention and screening along with managing acute and chronic health problems. However, clinical decision support (CDS) may assist PCPs in addressing patients' cancer prevention and screening needs during short clinic visits. In this paper, we describe pre-implementation study design and cancer screening and prevention CDS changes made to maximize utilization and better fit a healthcare system's goals and culture. We employed the Consolidated Framework for Implementation Research (CFIR), useful for evaluating the implementation of CDS interventions in primary care settings, in understanding barriers and facilitators that led to those changes. Methods: In a three-arm, pragmatic, 36 clinic cluster-randomized control trial, we integrated cancer screening and prevention CDS and shared decision-making tools (SDMT) into an existing electronic medical record-linked cardiovascular risk management CDS system. The integrated CDS is currently being tested within a predominately rural upper Midwestern healthcare system. Prior to CDS implementation, we catalogued pre-implementation changes made from 2016 to 2018 based on: pre-implementation site engagement; key informant interviews with healthcare system rooming staff, providers, and leadership; and pilot testing. We identified influential barriers, facilitators, and changes made in response through qualitative content analysis of meeting minutes and supportive documents. We then coded pre-implementation changes made and associated barriers and facilitators using the CFIR. Results: Based on our findings from system-wide pre-implementation engagement, pilot testing, and key informant interviews, we made changes to accommodate the needs of the healthcare system based on barriers and facilitators that fell within the Intervention Characteristics, Inner Setting, and Outer Setting CFIR domains. Changes included replacing the expansion of medical assistant roles in one intervention arm with targeted SDMT, as well as altering cancer prevention CDS and study design elements. Conclusions: Pre-implementation changes to CDS may help meet healthcare systems' evolving needs and optimize the intervention by being responsive to real-world implementation barriers and facilitators. Frameworks like the CFIR are useful tools for identifying areas where pre-implementation barriers and facilitators may result in design changes, both to research studies and CDS systems.

Original languageEnglish (US)
Article number117
JournalBMC medical informatics and decision making
Volume20
Issue number1
DOIs
StatePublished - Jun 23 2020

Bibliographical note

Funding Information:
National Cancer Institute R01CA193396. The funding body had no role in the design of the study, collection, analysis, interpretation of data, or in writing the manuscript.

Publisher Copyright:
© 2020 The Author(s).

UN SDGs

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

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Cancer prevention and screening
  • Clinical decision support
  • Consolidated Framework for Implementation Research
  • Pre-implementation adaptation
  • Primary care
  • Shared decision-making tools

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