A principal components analysis of factors associated with successful implementation of an LVAD decision support tool
Abstract 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 cultu...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2021-03-01
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| Series: | BMC Medical Informatics and Decision Making |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12911-021-01468-z |
| _version_ | 1818416567767007232 |
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| author | Kristin M. Kostick Meredith Trejo Arvind Bhimaraj Andrew Civitello Jonathan Grinstein Douglas Horstmanshof Ulrich P. Jorde Matthias Loebe Mandeep R. Mehra Nasir Z. Sulemanjee Vinay Thohan Barry H. Trachtenberg Nir Uriel Robert J. Volk Jerry D. Estep J. S. Blumenthal-Barby |
| author_facet | Kristin M. Kostick Meredith Trejo Arvind Bhimaraj Andrew Civitello Jonathan Grinstein Douglas Horstmanshof Ulrich P. Jorde Matthias Loebe Mandeep R. Mehra Nasir Z. Sulemanjee Vinay Thohan Barry H. Trachtenberg Nir Uriel Robert J. Volk Jerry D. Estep J. S. Blumenthal-Barby |
| author_sort | Kristin M. Kostick |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-12-14T11:52:57Z |
| format | Article |
| id | doaj.art-9695199d1d6a42ae9161fd1129c7f276 |
| institution | Directory Open Access Journal |
| issn | 1472-6947 |
| language | English |
| last_indexed | 2024-12-14T11:52:57Z |
| publishDate | 2021-03-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Informatics and Decision Making |
| spelling | doaj.art-9695199d1d6a42ae9161fd1129c7f2762022-12-21T23:02:15ZengBMCBMC Medical Informatics and Decision Making1472-69472021-03-0121111410.1186/s12911-021-01468-zA principal components analysis of factors associated with successful implementation of an LVAD decision support toolKristin M. Kostick0Meredith Trejo1Arvind Bhimaraj2Andrew Civitello3Jonathan Grinstein4Douglas Horstmanshof5Ulrich P. Jorde6Matthias Loebe7Mandeep R. Mehra8Nasir Z. Sulemanjee9Vinay Thohan10Barry H. Trachtenberg11Nir Uriel12Robert J. Volk13Jerry D. Estep14J. S. Blumenthal-Barby15Center for Medical Ethics and Health Policy, Baylor College of MedicineCenter for Medical Ethics and Health Policy, Baylor College of MedicineDivision of Heart Failure, Houston Methodist HospitalBaylor St. Luke’s Medical Center, Texas Heart InstituteDuchossois Center for Advanced Medicine – Hyde Park, University of Chicago MedicineINTREGIS Advanced Cardiac CareDivision of Cardiology, Montefiore Medical CenterMiami Transplant Institute, University of Miami Health SystemCardiovascular Medicine, Brigham and Women’s HospitalAurora St. Luke’s Medical CenterAsheville Cardiology AssociatesDivision of Heart Failure, Houston Methodist HospitalColumbia Presbyterian Medical Center, Columbia University Irving Medical CenterDepartment of Health Services Research, Division of Cancer Prevention and Population Services, University of Texas MD Anderson Cancer CenterMiller Family Heart and Vascular Institute, Cleveland ClinicCenter for Medical Ethics and Health Policy, Baylor College of MedicineAbstract 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.https://doi.org/10.1186/s12911-021-01468-zImplementation successFacilitators and barriersDecision support interventionPrincipal components analysis |
| spellingShingle | Kristin M. Kostick Meredith Trejo Arvind Bhimaraj Andrew Civitello Jonathan Grinstein Douglas Horstmanshof Ulrich P. Jorde Matthias Loebe Mandeep R. Mehra Nasir Z. Sulemanjee Vinay Thohan Barry H. Trachtenberg Nir Uriel Robert J. Volk Jerry D. Estep J. S. Blumenthal-Barby A principal components analysis of factors associated with successful implementation of an LVAD decision support tool BMC Medical Informatics and Decision Making Implementation success Facilitators and barriers Decision support intervention Principal components analysis |
| title | A principal components analysis of factors associated with successful implementation of an LVAD decision support tool |
| title_full | A principal components analysis of factors associated with successful implementation of an LVAD decision support tool |
| title_fullStr | A principal components analysis of factors associated with successful implementation of an LVAD decision support tool |
| title_full_unstemmed | A principal components analysis of factors associated with successful implementation of an LVAD decision support tool |
| title_short | A principal components analysis of factors associated with successful implementation of an LVAD decision support tool |
| title_sort | principal components analysis of factors associated with successful implementation of an lvad decision support tool |
| topic | Implementation success Facilitators and barriers Decision support intervention Principal components analysis |
| url | https://doi.org/10.1186/s12911-021-01468-z |
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