Health worker transfer processes within the public health sector in Ghana: a study of three districts in the Eastern Region.

INTRODUCTION: The lack of appropriate policies and procedures to ensure transparent transfer practices is an important source of dissatisfaction among health workers in low- and middle-income countries. In order to alter and improve current practices, a more in-depth and context-specific understanding is needed. This study aims to (1) identify rationales behind transfer decisions in Ghana and (2) examine how transfers are managed in practice versus in policies. METHODS: The study took place in 2014 in three districts in Eastern Ghana. The study population included (1) national, regional, and district health administrators with decision-making authority in terms of transfer decisions and (2) health workers who had transferred between 2011 and 2014. Data was collected through semi-structured and structured face-to-face interviews focusing on rationales behind transfer decisions, health administrators' role in managing transfers, and health workers' experience of transfers. A data triangulation approach was applied to compare identified practices with national policies and procedures. RESULTS: A total of 44 health workers and 21 administrators participated in the study. Transfers initiated by health workers were mostly based on family conditions and preferences to move away from rural areas, while transfers initiated by administrators were based on service requirements, productivity, and performance. The management of transfers was not guided by clear and explicit procedures and thus often depended on the discretion of decision-makers. Moreover, health workers frequently reported not being involved in transfer decision-making processes. We found existing staff perceptions of a non-transparent system. CONCLUSION: Our findings suggest a need to foster incentives to attract and retain health workers in rural areas. Moreover, health worker-centered procedures and systems that effectively guide and monitor transfer practices must be developed to ensure that transfers are carried out in a timely, fair, and transparent way.

Perception of cure in prostate cancer: human-led and artificial intelligence-assisted landscape review and linguistic analysis of literature, social media and policy documents.

BACKGROUND: Understanding stakeholders' perception of cure in prostate cancer (PC) is essential to preparing for effective communication about emerging treatments with curative intent. This study used artificial intelligence (AI) for landscape review and linguistic analysis of definition, context and value of cure among stakeholders in PC. MATERIALS AND METHODS: Subject-matter experts (SMEs) selected cure-related key words using Elicit, a semantic literature search engine, and extracted hits containing the key words from Medline, Sermo and Overton, representing academic researchers, health care providers (HCPs) and policymakers, respectively. NetBase Quid, a social media analytics and natural language processing tool, was used to carry out key word searches in social media (representing the general public). NetBase Quid analysed linguistics of key word-specific hit sets for key word count, geolocation and sentiments. SMEs qualitatively summarised key word-specific insights. Contextual terms frequently occurring with key words were identified and quantified. RESULTS: SMEs identified seven key words applicable to PC (number of acquired hits) across four platforms: Cure (12429), Survivor (6063), Remission (1904), Survivorship (1179), Curative intent (432), No evidence of disease (381) and Complete remission (83). Most commonly used key words were Cure by the general public and HCPs (11815 and 224 hits), Survivorship by academic researchers and Survivor by policymakers (378 hits each). All stakeholders discussed Cure and cure-related key words primarily in early-stage PC and associated them with positive sentiments. All stakeholders defined cure differently but communicated about it in relation to disease measurements (e.g. prostate-specific antigen) or surgery. Stakeholders preferred different terms when discussing cure in PC: Cure (academic researchers), Cure rates (HCPs), Potential cure and Survivor/Survivorship (policymakers) and Cure and Survivor (general public). CONCLUSION: This human-led, AI-assisted large-scale qualitative language-based research revealed that cure was commonly discussed by academic researchers, HCPs, policymakers and the general public, especially in early-stage PC. Stakeholders defined and contextualised cure in their communications differently and associated it with positive value.