A Multi-Phase Approach for Developing a Conceptual Model for Human Resources for Health Observatory (Hrho) Toward Integrating Data and Evidence: A Case Study of Iran Publisher Pubmed



Najafpour Z¹ ; Arab M² ; Shayanfard K³
Source: Health Research Policy and Systems Published:2023

Abstract

Background: Evidence-informed policymaking on human resources for health (HRH) has been directly linked with health system productivity, accessibility, equity, quality, and efficiency. The lack of reliable HRH data has made the task of planning the HRH more difficult in all settings. Aim: This study aimed to develop a conceptual model to integrate HRH data and evidence. Methods: The current study is a mixed-method study conducted in three phases: a rapid literature review, a qualitative phase, and an expert panel. Firstly, the electronic databases were searched up to 2018. Then, in the qualitative phase, semi-structured interviews with 50 experts were conducted. Data analysis was performed using the content analysis approach. After several expert panels, the draft of the model was validated with 15 key informants via two Delphi rounds. Results: Our proposed model embraces all dominant elements on the demand and supply side of the HRH in Iran. The conceptual model consists of several components, including input (regulatory system, structure, functions), educational system (pre-service and in-service education), health labor market structure, process (technical infrastructure), and output (productions, policymaking process). We considered networking toward sustainable interaction among stakeholders, and also the existence of capacity to integrate HRH information and produce evidence for actions. Conclusion: The proposed model can be considered a platform for developing a harmonized system based on the HRH data flow to evidence-informed decision-making via networking. We proposed a step-by-step approach for the sustainability of establishing a national human resources for health observatory (HRHO). The proposed HRHO model can be replicable and flexible enough to be used in different context domains. © 2023, The Author(s).