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1.
JMIR Hum Factors ; 9(3): e35125, 2022 Jul 14.
Artigo em Inglês | MEDLINE | ID: mdl-35834315

RESUMO

BACKGROUND: Researchers have conducted numerous studies seeking to understand how to improve the implementation of changes in health care organizations, but less focus has been given to applying lessons already learned from implementation science. Finding innovative ways to apply these findings efficiently and consistently will improve current research on implementation strategies and allow organizations utilizing these techniques to make changes more effectively. OBJECTIVE: This research aims to compare a practical implementation approach that uses principles from prior implementation studies to more traditional ways of implementing change. METHODS: A total of 43 addiction treatment sites in Iowa were randomly assigned to 2 different implementation strategies in a randomized comparative effectiveness trial studying the implementation of an eHealth substance use disorder treatment technology. One strategy used an adaptation of the Network for the Improvement of Addiction Treatment (NIATx) improvement approach, while the other used a traditional product training model. This paper discusses lessons learned about implementation. RESULTS: This midterm report indicates that use of the NIATx approach appears to be leading to improved outcomes on several measures, including initial and sustained use of new technology by both counselors and patients. Additionally, this research indicates that seamlessly integrating organizational changes into existing workflows and using coaching to overcome hurdles and assess progress are important to improve implementation projects. CONCLUSIONS: At this interim point in the study, it appears that the use of the NIATx improvement process leads to better outcomes in implementation of changes within health care organizations. Moreover, some strategies used in this improvement process are particularly useful and should be drawn on more heavily in future implementation efforts. TRIAL REGISTRATION: ClinicalTrials.gov NCT03954184; https://clinicaltrials.gov/ct2/show/NCT03954184.

2.
J Am Med Inform Assoc ; 17(6): 707-13, 2010.
Artigo em Inglês | MEDLINE | ID: mdl-20962135

RESUMO

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.


Assuntos
Informação de Saúde ao Consumidor , Técnicas de Apoio para a Decisão , Implementação de Plano de Saúde , Sistemas de Informação , Participação do Paciente , Interface Usuário-Computador , Humanos , Modelos Teóricos , Inovação Organizacional , Reprodutibilidade dos Testes , Estados Unidos
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