Effectiveness of knowledge brokering and recommendation dissemination for influencing healthcare resource allocation decisions: A cluster randomised controlled implementation trial

PLoS Med. 2021 Oct 22;18(10):e1003833. doi: 10.1371/journal.pmed.1003833. eCollection 2021 Oct.

Abstract

Background: Implementing evidence into clinical practice is a key focus of healthcare improvements to reduce unwarranted variation. Dissemination of evidence-based recommendations and knowledge brokering have emerged as potential strategies to achieve evidence implementation by influencing resource allocation decisions. The aim of this study was to determine the effectiveness of these two research implementation strategies to facilitate evidence-informed healthcare management decisions for the provision of inpatient weekend allied health services.

Methods and findings: This multicentre, single-blinded (data collection and analysis), three-group parallel cluster randomised controlled trial with concealed allocation was conducted in Australian and New Zealand hospitals between February 2018 and January 2020. Clustering and randomisation took place at the organisation level where weekend allied health staffing decisions were made (e.g., network of hospitals or single hospital). Hospital wards were nested within these decision-making structures. Three conditions were compared over a 12-month period: (1) usual practice waitlist control; (2) dissemination of written evidence-based practice recommendations; and (3) access to a webinar-based knowledge broker in addition to the recommendations. The primary outcome was the alignment of weekend allied health provision with practice recommendations at the cluster and ward levels, addressing the adoption, penetration, and fidelity to the recommendations. The secondary outcome was mean hospital length of stay at the ward level. Outcomes were collected at baseline and 12 months later. A total of 45 clusters (n = 833 wards) were randomised to either control (n = 15), recommendation (n = 16), or knowledge broker (n = 14) conditions. Four (9%) did not provide follow-up data, and no adverse events were recorded. No significant effect was found with either implementation strategy for the primary outcome at the cluster level (recommendation versus control β 18.11 [95% CI -8,721.81 to 8,758.02] p = 0.997; knowledge broker versus control β 1.24 [95% CI -6,992.60 to 6,995.07] p = 1.000; recommendation versus knowledge broker β -9.12 [95% CI -3,878.39 to 3,860.16] p = 0.996) or ward level (recommendation versus control β 0.01 [95% CI 0.74 to 0.75] p = 0.983; knowledge broker versus control β -0.12 [95% CI -0.54 to 0.30] p = 0.581; recommendation versus knowledge broker β -0.19 [-1.04 to 0.65] p = 0.651). There was no significant effect between strategies for the secondary outcome at ward level (recommendation versus control β 2.19 [95% CI -1.36 to 5.74] p = 0.219; knowledge broker versus control β -0.55 [95% CI -1.16 to 0.06] p = 0.075; recommendation versus knowledge broker β -3.75 [95% CI -8.33 to 0.82] p = 0.102). None of the control or knowledge broker clusters transitioned to partial or full alignment with the recommendations. Three (20%) of the clusters who only received the written recommendations transitioned from nonalignment to partial alignment. Limitations include underpowering at the cluster level sample due to the grouping of multiple geographically distinct hospitals to avoid contamination.

Conclusions: Owing to a lack of power at the cluster level, this trial was unable to identify a difference between the knowledge broker strategy and dissemination of recommendations compared with usual practice for the promotion of evidence-informed resource allocation to inpatient weekend allied health services. Future research is needed to determine the interactions between different implementation strategies and healthcare contexts when translating evidence into healthcare practice.

Trial registration: Australian New Zealand Clinical Trials Registry ACTRN12618000029291.

Publication types

  • Randomized Controlled Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Australia
  • Cluster Analysis
  • Decision Making*
  • Delivery of Health Care* / organization & administration
  • Evidence-Based Practice
  • Female
  • Follow-Up Studies
  • Health Planning Guidelines*
  • Health Policy
  • Humans
  • Knowledge*
  • Male
  • Middle Aged
  • Outcome Assessment, Health Care
  • Resource Allocation*

Associated data

  • ANZCTR/ACTRN12618000029291

Grants and funding

This work was funded by the National Health and Medical Research Council (NHMRC) Australia (APP1114210); https://www.nhmrc.gov.au/ to TPH. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.