Geographers play important roles in public health research, particularly in understanding healthcare accessibility, utilisation, and individual healthcare experiences. Most accessibility studies have benefited from the increased sophistication of geographic information systems (GIS). Some studies have been enhanced with semi-structured in-depth interviews to understand individual experiences of people as they access healthcare. However, few accessibility studies have explicitly utilised individual in-depth interview data in the construction of new GIS accessibility measures. Using mixed methods including GIS analysis and individual data from semi-structured in-depth interviews, we offer satisfaction-adjusted distance as a new way of conceptualising accessibility in GIS. Based on fieldwork in a predominantly lower-income community in Columbus, Ohio (USA), we find many residents felt neighbourhood healthcare facilities offered low-quality care, which suggested an added perceived distance as they attempt to access high-quality healthcare facilities. The satisfaction-adjusted distance measure accounts for the perceived distance some residents feel as they search for high-quality healthcare in lower-income urban neighbourhoods. In moving beyond conventional GIS and re-conceptualising accessibility in this way, we offer a more realistic portrayal of the issues lower-income urban residents face as they attempt to access high-quality healthcare facilities. The work has theoretical implications for conceptualising healthcare accessibility, advances the mixed-methodologies literature, and argues for a more equitable distribution of high-quality healthcare in urban neighbourhoods.
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http://dx.doi.org/10.1111/j.1475-4959.2011.00411.x | DOI Listing |
Pharmacoeconomics
January 2025
Belgian Health Care Knowledge Centre, Brussels, Belgium.
Background: Forecasting future public pharmaceutical expenditure is a challenge for healthcare payers, particularly owing to the unpredictability of new market introductions and their economic impact. No best-practice forecasting methods have been established so far. The literature distinguishes between the top-down approach, based on historical trends, and the bottom-up approach, using a combination of historical and horizon scanning data.
View Article and Find Full Text PDFNutrients
January 2025
Department of Clinical Nutrition and Dietetics, College of Health Sciences, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates.
Background: Artificial Intelligence (AI) technologies are now essential as the agenda of nutrition research expands its scope to look at the intricate connection between food and health in both an individual and a community context. AI also helps in tracing and offering solutions in dietary assessment, personalized and clinical nutrition, as well as disease prediction and management, such as cardiovascular diseases, diabetes, cancer, and obesity. This review aims to investigate and assess the different applications and roles of AI in nutrition and research and understand its potential future impact.
View Article and Find Full Text PDFUrol Oncol
January 2025
Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD. Electronic address:
Prostate cancer is the most commonly diagnosed cancer and the second leading cause of cancer-related death among men in the United States. The global burden of this disease is rising, placing significant strain on healthcare systems worldwide. Although definitive therapies like surgery and radiation are often effective, prostate cancer can recur and progress to castration-resistant prostate cancer in some cases.
View Article and Find Full Text PDFBMJ Open Qual
January 2025
Strangeways Research Laboratory, Cambridge, UK.
Objective: Variations in the quality and safety of surgical care remain persistent. Efforts to improve are needed, but are themselves variably effective, with often disappointing impacts. When compared with large-scale, multisite and better resourced improvement efforts, the evidence base for small-scale quality improvement (QI) has remained under-developed and lacking in clarity on good practice.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
College of Medicine and Public Health, Flinders University, Bedford Park, Australia.
Background: There is limited evidence of high-quality, accessible, culturally safe, and effective digital health interventions for Indigenous mothers and babies. Like any other intervention, the feasibility and efficacy of digital health interventions depend on how well they are co-designed with Indigenous communities and their adaptability to intracultural diversity.
Objective: This study aims to adapt an existing co-designed mobile health (mHealth) intervention app with health professionals and Aboriginal and/or Torres Strait Islander mothers living in South Australia.
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