Perceptions of Barriers and Facilitators to a Pilot Implementation of an Algorithm-Supported Care Navigation Model of Care: A Qualitative Study

Rebecca K. Pang, Nadine E. Andrew, Velandai Srikanth, Carolina D. Weller, David A. Snowdon

Research output: Contribution to journalArticleResearchpeer-review

Abstract

We aimed to explore managerial and project staff perceptions of the pilot implementation of an algorithm-supported care navigation model, targeting people at risk of hospital readmission. The pilot was implemented from May to November 2017 at a Victorian health service (Australia) and provided to sixty-five patients discharged from the hospital to the community. All managers and the single clinician involved participated in a semi-structured interview. Participants (n = 6) were asked about their perceptions of the service design and the enablers and barriers to implementation. Interviews were transcribed verbatim and analysed according to a framework approach, using inductive and deductive techniques. Constructed themes included the following: an algorithm alone is not enough, the health service culture, leadership, resources and the perceived patient experience. Participants felt that having an algorithm to target those considered most likely to benefit was helpful but not enough on its own without addressing other contextual factors, such as the health service’s capacity to support a large-scale implementation. Deductively mapping themes to the integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) framework highlighted that a formal facilitation would be essential for future sustainable implementations. The systematic identification of barriers and enablers elicited critical information for broader implementations of algorithm-supported models of care.

Original languageEnglish
Article number3011
Number of pages17
JournalHealthcare
Volume11
Issue number23
DOIs
Publication statusPublished - Dec 2023

Keywords

  • care navigation
  • hospital readmission
  • i-PARIHS
  • risk algorithm
  • staff perception

Cite this