Developing and validating a model to predict the success of an IHCS implementation: the Readiness for Implementation Model - PubMed (original) (raw)
Multicenter Study
Developing and validating a model to predict the success of an IHCS implementation: the Readiness for Implementation Model
Kuang-Yi Wen et al. J Am Med Inform Assoc. 2010 Nov-Dec.
Abstract
Objective: To develop and validate the Readiness for Implementation Model (RIM). This model predicts a healthcare organization's potential for success in implementing an interactive health communication system (IHCS). The model consists of seven weighted factors, with each factor containing five to seven elements.
Design: Two decision-analytic approaches, self-explicated and conjoint analysis, were used to measure the weights of the RIM with a sample of 410 experts. The RIM model with weights was then validated in a prospective study of 25 IHCS implementation cases.
Measurements: Orthogonal main effects design was used to develop 700 conjoint-analysis profiles, which varied on seven factors. Each of the 410 experts rated the importance and desirability of the factors and their levels, as well as a set of 10 different profiles. For the prospective 25-case validation, three time-repeated measures of the RIM scores were collected for comparison with the implementation outcomes.
Results: Two of the seven factors, 'organizational motivation' and 'meeting user needs,' were found to be most important in predicting implementation readiness. No statistically significant difference was found in the predictive validity of the two approaches (self-explicated and conjoint analysis). The RIM was a better predictor for the 1-year implementation outcome than the half-year outcome.
Limitations: The expert sample, the order of the survey tasks, the additive model, and basing the RIM cut-off score on experience are possible limitations of the study.
Conclusion: The RIM needs to be empirically evaluated in institutions adopting IHCS and sustaining the system in the long term.
Conflict of interest statement
Competing interests: None.
Figures
Figure 1
The RIM development process. The headings describe the phases of the process and beneath are descriptions of the key components in each phase. Phases 3 and 4 are the focus of this paper.
Figure 2
RIM predictive scores compared with perceived implementation success. The bolded lines indicate the cut-off points. ○, Correctly predicted successful IHCS initiatives; ◊, under-predicted successful IHCS initiatives; +, correctly predicted unsuccessful IHCS initiatives; ×, falsely predicted unsuccessful IHCS initiatives.
Similar articles
- Web-based cancer communication and decision making systems: connecting patients, caregivers, and clinicians for improved health outcomes.
DuBenske LL, Gustafson DH, Shaw BR, Cleary JF. DuBenske LL, et al. Med Decis Making. 2010 Nov-Dec;30(6):732-44. doi: 10.1177/0272989X10386382. Epub 2010 Nov 1. Med Decis Making. 2010. PMID: 21041539 Free PMC article. - Development and implementation of a clinician reporting system for advanced stage cancer: initial lessons learned.
Dubenske LL, Chih MY, Dinauer S, Gustafson DH, Cleary JF. Dubenske LL, et al. J Am Med Inform Assoc. 2008 Sep-Oct;15(5):679-86. doi: 10.1197/jamia.M2532. Epub 2008 Jun 25. J Am Med Inform Assoc. 2008. PMID: 18579837 Free PMC article. - Development and validation of the Readiness to Train Assessment Tool (RTAT).
Zlateva I, Schiessl A, Khalid N, Bamrick K, Flinter M. Zlateva I, et al. BMC Health Serv Res. 2021 Apr 28;21(1):396. doi: 10.1186/s12913-021-06406-3. BMC Health Serv Res. 2021. PMID: 33910561 Free PMC article. - Organizational- and system-level characteristics that influence implementation of shared decision-making and strategies to address them - a scoping review.
Scholl I, LaRussa A, Hahlweg P, Kobrin S, Elwyn G. Scholl I, et al. Implement Sci. 2018 Mar 9;13(1):40. doi: 10.1186/s13012-018-0731-z. Implement Sci. 2018. PMID: 29523167 Free PMC article. Review. - Avoiding and identifying errors in health technology assessment models: qualitative study and methodological review.
Chilcott J, Tappenden P, Rawdin A, Johnson M, Kaltenthaler E, Paisley S, Papaioannou D, Shippam A. Chilcott J, et al. Health Technol Assess. 2010 May;14(25):iii-iv, ix-xii, 1-107. doi: 10.3310/hta14250. Health Technol Assess. 2010. PMID: 20501062 Review.
Cited by
- Comparison of Use Rates of Telehealth Services for Substance Use Disorder During and Following COVID-19 Safety Distancing Recommendations: Two Cross-Sectional Surveys.
Pusnik A, Hartzler B, Vjorn O, Rutkowski BA, Chaple M, Becker S, Freese T, Nichols M, Molfenter T. Pusnik A, et al. JMIR Ment Health. 2024 Aug 12;11:e52363. doi: 10.2196/52363. JMIR Ment Health. 2024. PMID: 39136186 Free PMC article. - Implementing a Mobile Health System to Integrate the Treatment of Addiction Into Primary Care: A Hybrid Implementation-Effectiveness Study.
Quanbeck A, Gustafson DH, Marsch LA, Chih MY, Kornfield R, McTavish F, Johnson R, Brown RT, Mares ML, Shah DV. Quanbeck A, et al. J Med Internet Res. 2018 Jan 30;20(1):e37. doi: 10.2196/jmir.8928. J Med Internet Res. 2018. PMID: 29382624 Free PMC article. - Integrating addiction treatment into primary care using mobile health technology: protocol for an implementation research study.
Quanbeck AR, Gustafson DH, Marsch LA, McTavish F, Brown RT, Mares ML, Johnson R, Glass JE, Atwood AK, McDowell H. Quanbeck AR, et al. Implement Sci. 2014 May 29;9:65. doi: 10.1186/1748-5908-9-65. Implement Sci. 2014. PMID: 24884976 Free PMC article. Clinical Trial. - Organizational readiness for knowledge translation in chronic care: a Delphi study.
Attieh R, Gagnon MP, Estabrooks CA, Légaré F, Ouimet M, Vazquez P, Nuño R. Attieh R, et al. BMC Health Serv Res. 2014 Nov 8;14:534. doi: 10.1186/s12913-014-0534-0. BMC Health Serv Res. 2014. PMID: 25380653 Free PMC article. - Application of discrete choice experiments to enhance stakeholder engagement as a strategy for advancing implementation: a systematic review.
Salloum RG, Shenkman EA, Louviere JJ, Chambers DA. Salloum RG, et al. Implement Sci. 2017 Nov 23;12(1):140. doi: 10.1186/s13012-017-0675-8. Implement Sci. 2017. PMID: 29169397 Free PMC article. Review.
References
- Eng TR, Gustafson DH, Henderson J, et al. Introduction to evaluation of interactive health communication applications. Am J Prev Med 1999;16:10–15 - PubMed
- Robinson TN, Patrick K, Eng TR, et al. ; for the Science Panel on Interactive Communication and Health An evidence-based approach to interactive health communication: A challenge to medicine in the information age. JAMA 1998;280:1264–9 - PubMed
- Gustafson DH, Robinson TN, Ansley D, et al. Consumers and evaluation of interactive health communication applications. Am J Prev Med 1999;16:23–9 - PubMed
- Henderson J, Noell J, Reeves T, et al. Developers and evaluation of interactive health communication applications. Am J Prev Med 1999;16:30–4 - PubMed
- Murray E, Burns J, See TS, et al. Interactive health communication applications for people with chronic disease. Cochrane Database Syst Rev 2005;4:CD004274. - PubMed