Exploring the barriers and facilitators of training as well as post-training follow-up interventions to enhance data quality and utilization: Utilizing the CFIR Implementation Framework

Abstract

Abstract
Introduction: Despite significant investments have been made in improving data quality and information utilization, progress in this area continues to lag behind the target set by the government of Ethiopia. Data incompleteness and inaccurate reporting remain major challenges of the healthcare system. While capacity building for healthcare system leaders is recommended as a solution to enhance the production and use of quality health data, existing evidence suggests that poor health data production and utilization continue to impede effective health system planning and decision-making. Consequently, this study aims to explore the facilitators and barriers of training and post training follow up intervention aimed at enhance health data quality and utilization at Benishangul regional state.
Objective: The aim of the study is to explore the barriers and facilitators of training and post-training follow-up intervention through capacitating health system leaders to enhance health data quality and use.
Methods: A phenomenological study was conducted among 11 participants from multiple sites. In-depth interviews was conducted to explore the barriers and facilitators of training and post training follow up intervention. The data were collected throughout the entire process starting from the initiation of the implementation. The interview guide was adapted from the consolidated framework for implementation research (CFIR), and after transcribing and translating the data, the Open code version 4.03 was used to code and analyse them thematically. The results were presented under the CFIR domain and its framed constructs, along with quotations of participants’ sayings. Results: The findings showed that, based on the intervention characteristics, positive staff attitude, and the existence of regular performance monitoring team meetings, regular feedback mechanisms, and health system leaders' engagement were facilitators of the intervention. However, staff resistance, political instability, and workload challenged the implementation. From an outer-setting perspective, the policy initiative to engage health system leaders was mentioned as a implementation facilitator. On the other hand, limited awareness among staff regarding intervention packages and communication, lack of resources, and frequent campaign activities acted as barriers to implementation. Regarding the inner setting, implementers who were young showed interest in the intervention package and easily adapted to it. However, the implementation was constrained by the lack of peer-to-peer support, a poor culture of valuing health data, expectations of extensive trainings, and a shortage of trained personnel. In terms of the individual's characteristics, low beliefs and perceptions towards the intervention during the initial phase were barriers to implementation. However, health staff gradually accepted the intervention and began delivering it themselves. Lastly, the presence of a clear plan, leaders' involvement, evaluation, and monitoring of activities facilitated the implementation. However, the implementation schedule was not strictly followed as per the protocol due to political instability in the region.
Conclusion: The barriers and facilitators identified can be modified during the study. By providing the capacity building training and post training follow-up intervention to the health system is paramount to enhance data quality and utilization. Focusing on the barriers and facilitators identified in this study could help to improve health data quality and utilization through proper design of strategies and scaling up its effectiveness to larger settings where a similar contextual environment with the current study could enhance better data quality production and use. [Ethiop. J. Health Dev. 2023;37 (SI-1)]
Keywords: Barriers, facilitators, intervention, implementation, CFIR, framework, Benishangul Gumz, Ethiopia