Methadone treatment for opioid use disorder is not available in most suburban and rural US commun... more Methadone treatment for opioid use disorder is not available in most suburban and rural US communities. We examined 2 options to expand methadone availability: (1) addiction specialty physician or (2) all clinician prescribing. Using 2022 Health Resources and Services Administration data, we used mental health professional shortage areas to indicate the potential of addiction specialty physician prescribing and the location of federally qualified health centers (ie, federally certified primary care clinics) to indicate the potential of all clinician prescribing. We examined how many census tracts without an available opioid treatment program (ie, methadone clinic) are (1) located within a mental health professional shortage area and (2) are also without an available federally qualified health center. Methadone was available in 49% of tracts under current regulations, 63% of tracts in the case of specialist physician prescribing, and 86% of tracts in the case of all clinician prescri...
The Opioid Environment Policy Scan provides access to data at multiple spatial scales to help cha... more The Opioid Environment Policy Scan provides access to data at multiple spatial scales to help characterize the multi-dimensional risk environment impacting opioid use in justice populations across the United States. You can now explore and visualize the data on the OEPS Explorer at oeps.ssd.uchicago.edu.
Given that COVID-19 and recent natural disasters exacerbated the shortage of medication for opioi... more Given that COVID-19 and recent natural disasters exacerbated the shortage of medication for opioid use disorder (MOUD) services and were associated with increased opioid overdose mortality, it is important to examine how a community's ability to respond to natural disasters and infectious disease outbreaks is associated with MOUD access. OBJECTIVE To examine the association of community vulnerability to disasters and pandemics with geographic access to each of the 3 MOUDs and whether this association differs by urban, suburban, or rural classification. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study of zip code tabulation areas (ZCTAs) in the continental United States excluding Washington, DC, conducted a geospatial analysis of 2020 treatment location data. EXPOSURES Social vulnerability index (US Centers for Disease Control and Prevention measure of vulnerability to disasters or pandemics). MAIN OUTCOMES AND MEASURES Drive time in minutes from the population-weighted center of the ZCTA to the ZCTA of the nearest treatment location for each treatment type (buprenorphine, methadone, and extended-release naltrexone). RESULTS Among 32 604 ZCTAs within the continental US, 170 within Washington, DC, and 20 without an urban-rural classification were excluded, resulting in a final sample of 32 434 ZCTAs. Greater social vulnerability was correlated with longer drive times for methadone (correlation, 0.10; 95% CI, 0.09 to 0.11), but it was not correlated with access to other MOUDs. Among rural ZCTAs, increasing social vulnerability was correlated with shorter drive times to buprenorphine (correlation, -0.10; 95% CI, -0.12 to -0.08) but vulnerability was not correlated with other measures of access. Among suburban ZCTAs, greater vulnerability was correlated with both longer drive times to methadone (correlation, 0.22; 95% CI, 0.20 to 0.24) and extended-release naltrexone (correlation, 0.15; 95% CI, 0.13 to 0.17). In this study, communities with greater vulnerability did not have greater geographic access to MOUD, and the mismatch between vulnerability and medication access was greatest in suburban communities. Rural communities had poor geographic access regardless of vulnerability status. Future disaster preparedness planning should match the location of services to communities with greater vulnerability to prevent inequities in overdose deaths.
IMPORTANCE Although social determinants of health (SDOH) are important factors in health inequiti... more IMPORTANCE Although social determinants of health (SDOH) are important factors in health inequities, they have not been explicitly associated with COVID-19 mortality rates across racial and ethnic groups and rural, suburban, and urban contexts. OBJECTIVES To explore the spatial and racial disparities in county-level COVID-19 mortality rates during the first year of the pandemic. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study analyzed data for all US counties in 50 states and the District of Columbia for the first full year of the COVID-19 pandemic (January 22, 2020, to February 28, 2021). Counties with a high concentration of a single racial and ethnic population and a high level of COVID-19 mortality rate were identified as concentrated longitudinalimpact counties. The SDOH that may be associated with mortality rate across these counties and in urban, suburban, and rural contexts were examined. The 3 largest racial and ethnic groups in the US were selected: Black or African American, Hispanic or Latinx, and non-Hispanic White populations. EXPOSURES County-level characteristics and community health factors (eg, income inequality, uninsured rate, primary care physicians, preventable hospital stays, severe housing problems rate, and access to broadband internet) associated with COVID-19 mortality. MAIN OUTCOMES AND MEASURES Data on county-level COVID-19 mortality rates (deaths per 100 000 population) reported by the US Centers for Disease Control and Prevention were analyzed. Four indexes were used to measure multiple dimensions of SDOH: socioeconomic advantage index, limited mobility index, urban core opportunity index, and mixed immigrant cohesion and accessibility index. Spatial regression models were used to examine the associations between SDOH and countylevel COVID-19 mortality rate. RESULTS Of the 3142 counties included in the study, 531 were identified as concentrated longitudinal-impact counties. Of these counties, 347 (11.0%) had a large Black or African American population compared with other counties, 198 (6.3%) had a large Hispanic or Latinx population compared with other counties, and 33 (1.1%) had a large non-Hispanic White population compared with other counties. A total of 489 254 COVID-19-related deaths were reported. Most concentrated longitudinal-impact counties with a large Black or African American population compared with other counties were spread across urban, suburban, and rural areas and experienced numerous disadvantages, including higher income inequality (297 of 347 [85.6%]) and more preventable hospital stays (281 of 347 [81.0%]). Most concentrated longitudinal-impact counties with a large Hispanic or Latinx population compared with other counties were located in urban areas (114 of 198 [57.6%]), and 130 (65.7%) of these counties had a high percentage of people who lacked health insurance. Most concentrated longitudinal-impact counties with a large non-Hispanic White population compared with other counties were in rural areas (23 of 33 [69.7%]), included a large (continued) Key Points Question How do the associations between structural factors and COVID-19 mortality help explain the disproportionate outcomes experienced by different racial and ethnic groups? Findings In this cross-sectional study of 3142 counties in 50 US states and the District of Columbia, the associations between different measures of social determinants of health and COVID-19 mortality varied across racial and ethnic groups (Black or African American, Hispanic or Latinx, and non-Hispanic White populations) and different community types (rural, suburban, and urban areas). Meaning Findings from this study suggest the need for future research that addresses health inequity and guides policies and programs by further exploring the different dimensions and regional patterns of social determinants of health.
The COVID-19 pandemic, like past natural disasters, was associated with significant disruptions i... more The COVID-19 pandemic, like past natural disasters, was associated with significant disruptions in medications for opioid use disorder services and increased opioid overdose and mortality. We examined the association between community vulnerability to disasters and pandemics and geographic access to each of the three medications for opioid use disorder within the continental US and if this association was impacted by urban, suburban, or rural classification. We found communities with greater vulnerability did not have greater geographic access to medications for opioid use disorder and the mismatch between vulnerability and medication access was greatest in suburban communities. Rural communities had poor geographic access to all three medications regardless of vulnerability. Future disaster preparedness planning should include anticipation of access to medications for opioid use disorder and better match the location of services to communities with greater vulnerability to prevent ...
Methadone treatment for opioid use disorder is not available in most suburban and rural US commun... more Methadone treatment for opioid use disorder is not available in most suburban and rural US communities. We examined 2 options to expand methadone availability: (1) addiction specialty physician or (2) all clinician prescribing. Using 2022 Health Resources and Services Administration data, we used mental health professional shortage areas to indicate the potential of addiction specialty physician prescribing and the location of federally qualified health centers (ie, federally certified primary care clinics) to indicate the potential of all clinician prescribing. We examined how many census tracts without an available opioid treatment program (ie, methadone clinic) are (1) located within a mental health professional shortage area and (2) are also without an available federally qualified health center. Methadone was available in 49% of tracts under current regulations, 63% of tracts in the case of specialist physician prescribing, and 86% of tracts in the case of all clinician prescri...
The Opioid Environment Policy Scan provides access to data at multiple spatial scales to help cha... more The Opioid Environment Policy Scan provides access to data at multiple spatial scales to help characterize the multi-dimensional risk environment impacting opioid use in justice populations across the United States. You can now explore and visualize the data on the OEPS Explorer at oeps.ssd.uchicago.edu.
Given that COVID-19 and recent natural disasters exacerbated the shortage of medication for opioi... more Given that COVID-19 and recent natural disasters exacerbated the shortage of medication for opioid use disorder (MOUD) services and were associated with increased opioid overdose mortality, it is important to examine how a community's ability to respond to natural disasters and infectious disease outbreaks is associated with MOUD access. OBJECTIVE To examine the association of community vulnerability to disasters and pandemics with geographic access to each of the 3 MOUDs and whether this association differs by urban, suburban, or rural classification. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study of zip code tabulation areas (ZCTAs) in the continental United States excluding Washington, DC, conducted a geospatial analysis of 2020 treatment location data. EXPOSURES Social vulnerability index (US Centers for Disease Control and Prevention measure of vulnerability to disasters or pandemics). MAIN OUTCOMES AND MEASURES Drive time in minutes from the population-weighted center of the ZCTA to the ZCTA of the nearest treatment location for each treatment type (buprenorphine, methadone, and extended-release naltrexone). RESULTS Among 32 604 ZCTAs within the continental US, 170 within Washington, DC, and 20 without an urban-rural classification were excluded, resulting in a final sample of 32 434 ZCTAs. Greater social vulnerability was correlated with longer drive times for methadone (correlation, 0.10; 95% CI, 0.09 to 0.11), but it was not correlated with access to other MOUDs. Among rural ZCTAs, increasing social vulnerability was correlated with shorter drive times to buprenorphine (correlation, -0.10; 95% CI, -0.12 to -0.08) but vulnerability was not correlated with other measures of access. Among suburban ZCTAs, greater vulnerability was correlated with both longer drive times to methadone (correlation, 0.22; 95% CI, 0.20 to 0.24) and extended-release naltrexone (correlation, 0.15; 95% CI, 0.13 to 0.17). In this study, communities with greater vulnerability did not have greater geographic access to MOUD, and the mismatch between vulnerability and medication access was greatest in suburban communities. Rural communities had poor geographic access regardless of vulnerability status. Future disaster preparedness planning should match the location of services to communities with greater vulnerability to prevent inequities in overdose deaths.
IMPORTANCE Although social determinants of health (SDOH) are important factors in health inequiti... more IMPORTANCE Although social determinants of health (SDOH) are important factors in health inequities, they have not been explicitly associated with COVID-19 mortality rates across racial and ethnic groups and rural, suburban, and urban contexts. OBJECTIVES To explore the spatial and racial disparities in county-level COVID-19 mortality rates during the first year of the pandemic. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study analyzed data for all US counties in 50 states and the District of Columbia for the first full year of the COVID-19 pandemic (January 22, 2020, to February 28, 2021). Counties with a high concentration of a single racial and ethnic population and a high level of COVID-19 mortality rate were identified as concentrated longitudinalimpact counties. The SDOH that may be associated with mortality rate across these counties and in urban, suburban, and rural contexts were examined. The 3 largest racial and ethnic groups in the US were selected: Black or African American, Hispanic or Latinx, and non-Hispanic White populations. EXPOSURES County-level characteristics and community health factors (eg, income inequality, uninsured rate, primary care physicians, preventable hospital stays, severe housing problems rate, and access to broadband internet) associated with COVID-19 mortality. MAIN OUTCOMES AND MEASURES Data on county-level COVID-19 mortality rates (deaths per 100 000 population) reported by the US Centers for Disease Control and Prevention were analyzed. Four indexes were used to measure multiple dimensions of SDOH: socioeconomic advantage index, limited mobility index, urban core opportunity index, and mixed immigrant cohesion and accessibility index. Spatial regression models were used to examine the associations between SDOH and countylevel COVID-19 mortality rate. RESULTS Of the 3142 counties included in the study, 531 were identified as concentrated longitudinal-impact counties. Of these counties, 347 (11.0%) had a large Black or African American population compared with other counties, 198 (6.3%) had a large Hispanic or Latinx population compared with other counties, and 33 (1.1%) had a large non-Hispanic White population compared with other counties. A total of 489 254 COVID-19-related deaths were reported. Most concentrated longitudinal-impact counties with a large Black or African American population compared with other counties were spread across urban, suburban, and rural areas and experienced numerous disadvantages, including higher income inequality (297 of 347 [85.6%]) and more preventable hospital stays (281 of 347 [81.0%]). Most concentrated longitudinal-impact counties with a large Hispanic or Latinx population compared with other counties were located in urban areas (114 of 198 [57.6%]), and 130 (65.7%) of these counties had a high percentage of people who lacked health insurance. Most concentrated longitudinal-impact counties with a large non-Hispanic White population compared with other counties were in rural areas (23 of 33 [69.7%]), included a large (continued) Key Points Question How do the associations between structural factors and COVID-19 mortality help explain the disproportionate outcomes experienced by different racial and ethnic groups? Findings In this cross-sectional study of 3142 counties in 50 US states and the District of Columbia, the associations between different measures of social determinants of health and COVID-19 mortality varied across racial and ethnic groups (Black or African American, Hispanic or Latinx, and non-Hispanic White populations) and different community types (rural, suburban, and urban areas). Meaning Findings from this study suggest the need for future research that addresses health inequity and guides policies and programs by further exploring the different dimensions and regional patterns of social determinants of health.
The COVID-19 pandemic, like past natural disasters, was associated with significant disruptions i... more The COVID-19 pandemic, like past natural disasters, was associated with significant disruptions in medications for opioid use disorder services and increased opioid overdose and mortality. We examined the association between community vulnerability to disasters and pandemics and geographic access to each of the three medications for opioid use disorder within the continental US and if this association was impacted by urban, suburban, or rural classification. We found communities with greater vulnerability did not have greater geographic access to medications for opioid use disorder and the mismatch between vulnerability and medication access was greatest in suburban communities. Rural communities had poor geographic access to all three medications regardless of vulnerability. Future disaster preparedness planning should include anticipation of access to medications for opioid use disorder and better match the location of services to communities with greater vulnerability to prevent ...
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Papers by Susan Paykin