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Bretsch JK, Wallace AS, McCoy R. Social Needs Screening in Academic Health Systems: A Landscape Assessment. Popul Health Manag 2024. [PMID: 39069945 DOI: 10.1089/pop.2024.0111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/30/2024] Open
Abstract
Screening for social needs has gained traction as an approach to addressing social determinants of health, but it faces challenges regarding standardization, resource allocation, and follow-up care. The year-long study, conducted by the Association of American Medical Colleges, integrated data from conferences, surveys, and key informant interviews to examine the integration of social needs screening into health care services within Academic Health Systems (AHS). The authors' analysis unveiled eight key themes, showcasing AHS's active involvement in targeted social needs screening alongside persistent resource allocation obstacles. AHS are dedicated to efficiently identifying high-risk populations, fostering partnerships with community-based organizations, and embracing technology for closed-loop referrals. However, concerns endure about the utilization of reimbursement codes for social needs and regulatory compliance. AHS confront staffing issues, resource allocation intricacies, and the imperative for seamless integration across clinical and nonclinical departments. Notably, opportunities arise in standardized training, alignment of AHS priorities, exploration of social investment models, and engagement with state-level health information exchanges. Aligning clinical care, research pursuits, and community engagement endeavors holds promise for AHS in effectively addressing social needs.
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Affiliation(s)
- Jennifer K Bretsch
- Association of American Medical Colleges, Washington, District of Columbia, USA
| | - Andrea S Wallace
- University of Utah College of Nursing, Salt Lake City, Utah, USA
- University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Rosha McCoy
- Association of American Medical Colleges, Washington, District of Columbia, USA
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Stacherl B, Sauzet O. Gravity models for potential spatial healthcare access measurement: a systematic methodological review. Int J Health Geogr 2023; 22:34. [PMID: 38041129 PMCID: PMC10693160 DOI: 10.1186/s12942-023-00358-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 11/21/2023] [Indexed: 12/03/2023] Open
Abstract
BACKGROUND Quantifying spatial access to care-the interplay of accessibility and availability-is vital for healthcare planning and understanding implications of services (mal-)distribution. A plethora of methods aims to measure potential spatial access to healthcare services. The current study conducts a systematic review to identify and assess gravity model-type methods for spatial healthcare access measurement and to summarize the use of these measures in empirical research. METHODS A two-step approach was used to identify (1) methodological studies that presented a novel gravity model for measuring spatial access to healthcare and (2) empirical studies that applied one of these methods in a healthcare context. The review was conducted according to the PRISMA guidelines. EMBASE, CINAHL, Web of Science, and Scopus were searched in the first step. Forward citation search was used in the second step. RESULTS We identified 43 studies presenting a methodological development and 346 empirical application cases of those methods in 309 studies. Two major conceptual developments emerged: The Two-Step Floating Catchment Area (2SFCA) method and the Kernel Density (KD) method. Virtually all other methodological developments evolved from the 2SFCA method, forming the 2SFCA method family. Novel methodologies within the 2SFCA family introduced developments regarding distance decay within the catchment area, variable catchment area sizes, outcome unit, provider competition, local and global distance decay, subgroup-specific access, multiple transportation modes, and time-dependent access. Methodological developments aimed to either approximate reality, fit a specific context, or correct methodology. Empirical studies almost exclusively applied methods from the 2SFCA family while other gravity model types were applied rarely. Distance decay within catchment areas was frequently implemented in application studies, however, the initial 2SFCA method remains common in empirical research. Most empirical studies used the spatial access measure for descriptive purposes. Increasingly, gravity model measures also served as potential explanatory factor for health outcomes. CONCLUSIONS Gravity models for measuring potential spatial healthcare access are almost exclusively dominated by the family of 2SFCA methods-both for methodological developments and applications in empirical research. While methodological developments incorporate increasing methodological complexity, research practice largely applies gravity models with straightforward intuition and moderate data and computational requirements.
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Affiliation(s)
- Barbara Stacherl
- Socio-Economic Panel (SOEP), German Institute for Economic Research (DIW Berlin), Mohrenstraße 58, 11017, Berlin, Germany
| | - Odile Sauzet
- School of Public Health, Bielefeld University, Universitätsstraße 25, 33615, Bielefeld, Germany.
- Department of Business Administration and Economics, Bielefeld University, Universitätsstraße 25, 33615, Bielefeld, Germany.
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Shrestha S, Lindstrom MR, Harris D, Rock P, Srinivasan S, Pustz JC, Bayly R, Stopka TJ. Spatial access to buprenorphine-waivered prescribers in the HEALing communities study: Enhanced 2-step floating catchment area analyses in Massachusetts, Ohio, and Kentucky. JOURNAL OF SUBSTANCE USE AND ADDICTION TREATMENT 2023; 150:209077. [PMID: 37211155 PMCID: PMC10330859 DOI: 10.1016/j.josat.2023.209077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 04/08/2023] [Accepted: 05/02/2023] [Indexed: 05/23/2023]
Abstract
INTRODUCTION The opioid overdose epidemic continues to impact a large swath of the population in the US. Medications for opioid use disorders (MOUD) are an effective resource to combat the epidemic; however, there is limited research on MOUD treatment access that accounts for both supply of and demand for services. We aimed to examine access to buprenorphine prescribers in the HEALing Communities Study (HCS) Wave 2 communities in Massachusetts, Ohio, and Kentucky during 2021, and the association between buprenorphine access and opioid-related incidents, specifically fatal overdoses and opioid-related responses by emergency medical services (EMS). METHODS We calculated Enhanced 2-Step Floating Catchment Area (E2SFCA) accessibility indices for each state, as well as Wave 2 communities in each state, based on the location of providers (buprenorphine-waivered clinicians from the US Drug Enforcement Agency Active Registrants database), population-weighted centroids at the census block group level, and catchment areas defined by the state or community's average commute time. In advance of intervention initiation, we quantified the opioid-related risk environment of communities. We assessed gaps in services by using bivariate Local Moran's I analysis, incorporating accessibility indices and opioid-related incident data. RESULTS Massachusetts Wave 2 HCS communities had the highest rates of buprenorphine prescribers per 1000 patients (median: 165.8) compared to Kentucky (38.8) and Ohio (40.1). While urban centers in all three states had higher E2SFCA index scores compared to rural communities, we observed that suburban communities often had limited access. Through bivariate Local Moran's I analysis, we identified numerous locations with low buprenorphine access surrounded by high opioid-related incidents, particularly in communities that surrounded Boston, Massachusetts; Columbus, Ohio; and Louisville, Kentucky. CONCLUSION Rural communities demonstrated a great need for additional access to buprenorphine prescribers. However, policymakers should also direct attention toward suburban communities that have experienced significant increases in opioid-related incidents.
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Affiliation(s)
- Shikhar Shrestha
- Department of Public Health and Community Medicine, Tufts University School of Medicine, 136 Harrison Ave., Boston, MA 02111, United States of America
| | - Megan R Lindstrom
- Department of Geography, Ohio State University, 154 North Oval Mall, Columbus, OH 43210, United States of America
| | - Daniel Harris
- Department of Pharmacy Practice and Science, College of Pharmacy, Lee T. Todd Building, University of Kentucky, Lexington, KY 40506, United States of America; Institute of Pharmaceutical Outcomes and Policy, College of Pharmacy, Lee T. Todd Building, University of Kentucky, Lexington, KY 40506, United States of America
| | - Peter Rock
- Institute for Biomedical Informatics, College of Medicine, University of Kentucky, Lexington, KY 40506, United States of America
| | - Sumeeta Srinivasan
- Department of Urban and Environmental Policy and Planning, Tufts University Graduate School of Arts and Sciences, 97 Talbot Ave., Medford, MA, United States of America
| | - Jennifer C Pustz
- Department of Public Health and Community Medicine, Tufts University School of Medicine, 136 Harrison Ave., Boston, MA 02111, United States of America
| | - Ric Bayly
- Department of Public Health and Community Medicine, Tufts University School of Medicine, 136 Harrison Ave., Boston, MA 02111, United States of America
| | - Thomas J Stopka
- Department of Public Health and Community Medicine, Tufts University School of Medicine, 136 Harrison Ave., Boston, MA 02111, United States of America; Clinical and Translational Sciences Institute, Tufts University School of Medicine, 35 Kneeland St., Boston, MA 02111, United States of America; Department of Community Health, Tufts University, 574 Boston Ave, Medford, MA, United States of America; Department Urban and Environmental Policy and Planning, Tufts University, 97 Talbot Ave, Medford, MA, United States of America.
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Ab Hamid J, Juni MH, Abdul Manaf R, Syed Ismail SN, Lim PY. Spatial Accessibility of Primary Care in the Dual Public-Private Health System in Rural Areas, Malaysia. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:3147. [PMID: 36833838 PMCID: PMC9959538 DOI: 10.3390/ijerph20043147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 01/28/2023] [Accepted: 02/04/2023] [Indexed: 06/18/2023]
Abstract
Disparities in access to health services in rural areas represent a global health issue. Various external factors contribute to these disparities and each root requires specific remedial action to alleviate the issue. This study elucidates an approach to assessing the spatial accessibility of primary care, considering Malaysia's dual public-private system specifically in rural areas, and identifies its associated ecological factors. Spatial accessibility was calculated using the Enhance 2-Step Floating Catchment Area (E2SFCA) method, modified as per local context. Data were secondary sourced from Population and Housing Census data and administrative datasets pertaining to health facilities and road network. The spatial pattern of the E2SFCA scores were depicted using Hot spot Analysis. Hierarchical multiple linear regression and geographical weight regression were performed to identify factors that affect E2SFCA scores. Hot spot areas revolved near the urban agglomeration, largely contributed by the private sector. Distance to urban areas, road density, population density dependency ratios and ethnic composition were among the associated factors. Accurate conceptualization and comprehensive assessment of accessibility are crucial for evidence-based decision making by the policymakers and health authorities in identifying areas that need attention for a more specific and localized planning and development.
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Affiliation(s)
- Jabrullah Ab Hamid
- Department of Community Health, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia
- Institute for Health Systems Research, National Institutes of Health, Ministry of Health Malaysia, Blok B2, Kompleks NIH, No. 1, Jalan Setia Murni U13/52, Seksyen U13 Setia Alam, Shah Alam 40170, Selangor, Malaysia
| | - Muhamad Hanafiah Juni
- Department of Community Health, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia
| | - Rosliza Abdul Manaf
- Department of Community Health, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia
| | - Sharifah Norkhadijah Syed Ismail
- Department of Environmental and Occupational Health, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia
- Research Institute on Ageing (MyAgeing), Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
| | - Poh Ying Lim
- Department of Community Health, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia
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Sauer J, Stewart K. Geographic information science and the United States opioid overdose crisis: A scoping review of methods, scales, and application areas. Soc Sci Med 2023; 317:115525. [PMID: 36493502 DOI: 10.1016/j.socscimed.2022.115525] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 09/23/2022] [Accepted: 11/08/2022] [Indexed: 11/27/2022]
Abstract
BACKGROUND The Opioid Overdose Crisis (OOC) continues to generate morbidity and mortality in the United States, outpacing other prominent accident-related reasons. Multiple disciplines have applied geographic information science (GIScience) to understand geographical patterns in opioid-related health measures. However, there are limited reviews that assess how GIScience has been used. OBJECTIVES This scoping review investigates how GIScience has been used to conduct research on the OOC. Specific sub-objectives involve identifying bibliometric trends, the location and scale of studies, the frequency of use of various GIScience methodologies, and what direction future research can take to address existing gaps. METHODS The review was pre-registered with the Open Science Framework ((https://osf.io/h3mfx/) and followed the PRISMA-ScR guidelines. Scholarly research was gathered from the Web of Science Core Collection, PubMed, IEEE Xplore, ACM Digital Library. Inclusion criteria was defined as having a publication date between January 1999 and August 2021, using GIScience as a central part of the research, and investigating an opioid-related health measure. RESULTS 231 studies met the inclusion criteria. Most studies were published from 2017 onward. While many (41.6%) of studies were conducted using nationwide data, the majority (58.4%) occurred at the sub-national level. California, New York, Ohio, and Appalachia were most frequently studied, while the Midwest, north Rocky Mountains, Alaska, and Hawaii lacked studies. The most common GIScience methodology used was descriptive mapping, and county-level data was the most common unit of analysis across methodologies. CONCLUSIONS Future research of GIScience on the OOC can address gaps by developing use cases for machine learning, conducting analyses at the sub-county level, and applying GIScience to questions involving illicit fentanyl. Research using GIScience is expected to continue to increase, and multidisciplinary research efforts amongst GIScientists, epidemiologists, and other medical professionals can improve the rigor of research.
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Affiliation(s)
- Jeffery Sauer
- Department of Geographical Sciences, University of Maryland at College Park, 4600 River Road, Suite 300, Riverdale, MD, 20737, USA.
| | - Kathleen Stewart
- Department of Geographical Sciences, University of Maryland at College Park, 4600 River Road, Suite 300, Riverdale, MD, 20737, USA.
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Lalani K, Bakos-Block C, Cardenas-Turanzas M, Cohen S, Gopal B, Champagne-Langabeer T. The Impact of COVID-19 on Opioid-Related Overdose Deaths in Texas. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:13796. [PMID: 36360676 PMCID: PMC9657935 DOI: 10.3390/ijerph192113796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 09/20/2022] [Accepted: 10/18/2022] [Indexed: 06/16/2023]
Abstract
Prior to the COVID-19 pandemic, the United States was facing an epidemic of opioid overdose deaths, clouding accurate inferences about the impact of the pandemic at the population level. We sought to determine the existence of increases in the trends of opioid-related overdose (ORO) deaths in the Greater Houston metropolitan area from January 2015 through December 2021, and to describe the social vulnerability present in the geographic location of these deaths. We merged records from the county medical examiner's office with social vulnerability indexes (SVIs) for the region and present geospatial locations of the aggregated ORO deaths. Time series analyses were conducted to determine trends in the deaths, with a specific focus on the years 2019 to 2021. A total of 2660 deaths were included in the study and the mean (standard deviation, SD) age at death was 41.04 (13.60) years. Heroin and fentanyl were the most frequent opioids detected, present in 1153 (43.35%) and 1023 (38.46%) ORO deaths. We found that ORO deaths increased during the years 2019 to 2021 (p-value ≤ 0.001) when compared with 2015. Compared to the year 2019, ORO deaths increased for the years 2020 and 2021 (p-value ≤ 0.001). The geographic locations of ORO deaths were not associated with differences in the SVI. The COVID-19 pandemic had an impact on increasing ORO deaths in the metropolitan Houston area; however, identifying the determinants to guide targeted interventions in the areas of greatest need may require other factors, in addition to community-level social vulnerability parameters.
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State-Level Social Vulnerability Index and Healthcare Access: The Behavioral Risk Factor Surveillance System Survey. Am J Prev Med 2022; 63:403-409. [PMID: 35504796 DOI: 10.1016/j.amepre.2022.03.008] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 03/07/2022] [Accepted: 03/09/2022] [Indexed: 11/20/2022]
Abstract
INTRODUCTION Access to health care is affected by social determinants of health. The social vulnerability index encompasses multiple social determinants of health simultaneously and may therefore be associated with healthcare access. METHODS Cross-sectional data were used from the 2016‒2019 Behavioral Risk Factor Surveillance System, a nationally representative U.S. telephone-based survey of adults aged ≥18 years. State-level social vulnerability index was derived using county-level social vulnerability index estimates from the Centers for Disease Control and Prevention Agency for Toxic Substances and Disease Registry. Analyses were performed in October 2021. Social vulnerability index was ranked according to percentiles, which were divided into tertiles: Tertile 1 (0.10-0.32), Tertile 2 (0.33-0.53), and Tertile 3 (0.54-0.90). RESULTS In multivariable-adjusted models comparing U.S. states in Tertile 3 with those in Tertile 1 of social vulnerability index, there was a higher prevalence of absence of healthcare coverage (OR=1.39 [95% CI=1.22, 1.58]), absence of primary care provider (OR=1.34 [95% CI=1.22, 1.48]), >1-year duration since last routine checkup (OR=1.18 [95% CI=1.10, 1.27]), inability to see a doctor because of cost (OR=1.38 [95% CI=1.23, 1.54]), and the composite variable of any difficulty in accessing healthcare (OR=1.15 [95% CI=1.08, 1.22]). CONCLUSIONS State-level social vulnerability is associated with several measures related to healthcare access. These results can help to identify targeted interventions to improve access to health care in U.S. states with high social vulnerability index burden.
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Bozorgi P, Porter DE, Eberth JM, Eidson JP, Karami A. The leading neighborhood-level predictors of drug overdose: A mixed machine learning and spatial approach. Drug Alcohol Depend 2021; 229:109143. [PMID: 34794060 DOI: 10.1016/j.drugalcdep.2021.109143] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Revised: 10/11/2021] [Accepted: 10/12/2021] [Indexed: 11/26/2022]
Abstract
BACKGROUND Drug overdose is a leading cause of unintentional death in the United States and has contributed significantly to a decline in life expectancy during recent years. To combat this health issue, this study aims to identify the leading neighborhood-level predictors of drug overdose and develop a model to predict areas at the highest risk of drug overdose using geographic information systems and machine learning (ML) techniques. METHOD Neighborhood-level (block group) predictors were grouped into three domains: socio-demographic factors, drug use variables, and protective resources. We explored different ML algorithms, accounting for spatial dependency, to identify leading predictors in each domain. Using geographically weighted regression and the best-performing ML algorithm, we combined the output prediction of three domains to produce a final ensemble model. The model performance was validated using classification evaluation metrics, spatial cross-validation, and spatial autocorrelation testing. RESULTS The variables contributing most to the predictive model included the proportion of households with food stamps, households with an annual income below $35,000, opioid prescription rate, smoking accessories expenditures, and accessibility to opioid treatment programs and hospitals. Compared to the error estimated from normal cross-validation, the generalized error of the model did not increase considerably in spatial cross-validation. The ensemble model using ML outperformed the GWR method. CONCLUSION This study identified strong neighborhood-level predictors that place a community at risk of experiencing drug overdoses, as well as protective factors. Our findings may shed light on several specific avenues for targeted intervention in neighborhoods at risk for high drug overdose burdens.
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Affiliation(s)
- Parisa Bozorgi
- Department of Environmental Health Sciences, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA; South Carolina Department of Health and Environmental Control (SCDHEC), Columbia, SC 29201, USA.
| | - Dwayne E Porter
- Department of Environmental Health Sciences, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA.
| | - Jan M Eberth
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA; Rural and Minority Health Research Center, Arnold School of Public Health, University of South Carolina, Columbia, SC 29210, USA.
| | - Jeannie P Eidson
- South Carolina Department of Health and Environmental Control (SCDHEC), Columbia, SC 29201, USA.
| | - Amir Karami
- School of Information Science, University of South Carolina, Columbia, SC 29208, USA.
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