A principal components analysis of factors associated with successful implementation of an LVAD decision support tool.

Publisher: BioMed Central Country of Publication: England NLM ID: 101088682 Publication Model: Electronic Cited Medium: Internet ISSN: 1472-6947 (Electronic) Linking ISSN: 14726947 NLM ISO Abbreviation: BMC Med Inform Decis Mak Subsets: MEDLINE

Original Publication: London : BioMed Central, [2001-

Health Literacy* ; Heart-Assist Devices*; Humans ; Motivation

Background: A central goal among researchers and policy makers seeking to implement clinical interventions is to identify key facilitators and barriers that contribute to implementation success. Despite calls from a number of scholars, empirical insights into the complex structural and cultural predictors of why decision aids (DAs) become routinely embedded in health care settings remains limited and highly variable across implementation contexts.
Methods: We examined associations between "reach", a widely used indicator (from the RE-AIM model) of implementation success, and multi-level site characteristics of nine LVAD clinics engaged over 18 months in implementation and dissemination of a decision aid for left ventricular assist device (LVAD) treatment. Based on data collected from nurse coordinators, we explored factors at the level of the organization (e.g. patient volume), patient population (e.g. health literacy; average sickness level), clinician characteristics (e.g. attitudes towards decision aid; readiness for change) and process (how the aid was administered). We generated descriptive statistics for each site and calculated zero-order correlations (Pearson's r) between all multi-level site variables including cumulative reach at 12 months and 18 months for all sites. We used principal components analysis (PCA) to examine any latent factors governing relationships between and among all site characteristics, including reach.
Results: We observed strongest inclines in reach of our decision aid across the first year, with uptake fluctuating over the second year. Average reach across sites was 63% (s.d. = 19.56) at 12 months and 66% (s.d. = 19.39) at 18 months. Our PCA revealed that site characteristics positively associated with reach on two distinct dimensions, including a first dimension reflecting greater organizational infrastructure and standardization (characteristic of larger, more established clinics) and a second dimension reflecting positive attitudinal orientations, specifically, openness and capacity to give and receive decision support among coordinators and patients.
Conclusions: Successful implementation plans should incorporate specific efforts to promote supportive and mutually informative interactions between clinical staff members and to institute systematic and standardized protocols to enhance the availability, convenience and salience of intervention tool in routine practice. Further research is needed to understand whether "core predictors" of success vary across different intervention types.

Implement Sci. 2012 Jun 09;7:53. (PMID: 22682656)
Health Res Policy Syst. 2015 Mar 14;13:16. (PMID: 25885055)
Implement Sci. 2015 Aug 07;10:109. (PMID: 26249843)
J Heart Lung Transplant. 2016 Jun;35(6):768-76. (PMID: 26922278)
J Card Fail. 2018 Oct;24(10):661-671. (PMID: 30195826)
Patient Educ Couns. 2011 May;83(2):234-9. (PMID: 20696543)
Patient Educ Couns. 2008 Dec;73(3):526-35. (PMID: 18752915)
Med Decis Making. 2013 Jan;33(1):85-97. (PMID: 23300204)
J Asthma. 2018 Mar;55(3):310-317. (PMID: 28548896)
Urol Pract. 2019 Mar;6(2):93-99. (PMID: 34350322)
J Heart Lung Transplant. 2015 Sep;34(9):1182-9. (PMID: 26087668)
J Med Syst. 2012 Feb;36(1):241-77. (PMID: 20703721)
Cochrane Database Syst Rev. 2017 Apr 12;4:CD001431. (PMID: 28402085)
Implement Sci. 2013 Feb 17;8:22. (PMID: 23414420)
MDM Policy Pract. 2020 Apr 26;5(1):2381468320915906. (PMID: 32440570)
Health Aff (Millwood). 2016 Apr;35(4):630-6. (PMID: 27044963)
N C Med J. 2009 Mar-Apr;70(2):136-9. (PMID: 19489371)
Implement Sci. 2007 Dec 20;2:44. (PMID: 18096040)
BMJ. 2017 Nov 6;359:j4891. (PMID: 29109079)
J Comp Eff Res. 2016 Jul;5(4):407-15. (PMID: 27298206)
BMC Med Inform Decis Mak. 2013;13 Suppl 2:S14. (PMID: 24625083)
Health Informatics J. 2020 Jun;26(2):1194-1207. (PMID: 31566466)
Med Decis Making. 2019 Oct;39(7):805-815. (PMID: 31423911)
Implement Sci. 2018 Mar 9;13(1):40. (PMID: 29523167)
Health Expect. 2014 Jun;17(3):353-64. (PMID: 22212453)
Implement Sci. 2009 Aug 07;4:50. (PMID: 19664226)
Implement Sci. 2016 Jul 16;11:94. (PMID: 27422011)
Health Expect. 2000 Sep;3(3):182-191. (PMID: 11281928)
Implement Sci. 2014 Jan 10;9:7. (PMID: 24410955)
Implement Sci. 2017 Jun 21;12(1):77. (PMID: 28637486)
Patient Educ Couns. 2011 Nov;85(2):219-24. (PMID: 21282030)
Am J Public Health. 1999 Sep;89(9):1322-7. (PMID: 10474547)
Implement Sci. 2015 Feb 07;10:17. (PMID: 25757139)
Med Decis Making. 2015 Nov;35(8):987-98. (PMID: 26314727)
Pediatr Rheumatol Online J. 2017 Jun 5;15(1):48. (PMID: 28583183)
BMC Med Inform Decis Mak. 2017 Aug 18;17(1):124. (PMID: 28821256)
Milbank Q. 2004;82(4):581-629. (PMID: 15595944)
Implement Sci. 2011 Apr 23;6:42. (PMID: 21513547)
Health Expect. 2011 Mar;14 Suppl 1:85-95. (PMID: 21323821)
J Cancer Educ. 2020 Dec;35(6):1141-1148. (PMID: 31278659)
Implement Sci. 2012 Apr 24;7:37. (PMID: 22530986)

Keywords: Decision support intervention; Facilitators and barriers; Implementation success; Principal components analysis

Date Created: 20210321 Date Completed: 20210423 Latest Revision: 20240331

20240331

PMC7980808

10.1186/s12911-021-01468-z

33743685