Michelle S Wong, Chi-Hong Tseng, Ernest Moy, Kenneth T Jones, Amit J Kothari, Donna L. Washington
Failing to consider disparities in quality measures, such as by race and ethnicity, may obscure inequities in care, which could exist in facilities with overall high-quality ratings. We examined the relationship between overall quality and racial and ethnic disparities in diabetes care quality by healthcare facility-level performance on a diabetes-related quality measure within a national dataset of Veterans using Veterans Health Administration (VA) ambulatory care between 10/1/2019-9/31/2020, and were eligible for diabetes quality assessment. We found racial and ethnic disparities in diabetes care quality existed in top-performing VA medical centers (VAMCs) among American Indian or Alaska Native (AIAN; predicted probability = 30%), Black (predicted probability = 29%) and Hispanic VA-users (predicted probability = 30%)versus White VA-users (predicted probability = 26%). While disparities among Black and Hispanic VA-users were similar relative to white VA-users across VAMCs at all performance levels, disparities were exacerbated for AIAN and Native Hawaiian or Other Pacific Islander VA-users in bottom-performing VAMCs. Equity remains an issue even in facilities providing overall high-quality care. Integrating equity as a component of quality measures can incentivize greater focus on equity in quality improvement.
{"title":"Relationship between health system quality and racial and ethnic equity in diabetes care","authors":"Michelle S Wong, Chi-Hong Tseng, Ernest Moy, Kenneth T Jones, Amit J Kothari, Donna L. Washington","doi":"10.1093/haschl/qxae073","DOIUrl":"https://doi.org/10.1093/haschl/qxae073","url":null,"abstract":"\u0000 Failing to consider disparities in quality measures, such as by race and ethnicity, may obscure inequities in care, which could exist in facilities with overall high-quality ratings. We examined the relationship between overall quality and racial and ethnic disparities in diabetes care quality by healthcare facility-level performance on a diabetes-related quality measure within a national dataset of Veterans using Veterans Health Administration (VA) ambulatory care between 10/1/2019-9/31/2020, and were eligible for diabetes quality assessment. We found racial and ethnic disparities in diabetes care quality existed in top-performing VA medical centers (VAMCs) among American Indian or Alaska Native (AIAN; predicted probability = 30%), Black (predicted probability = 29%) and Hispanic VA-users (predicted probability = 30%)versus White VA-users (predicted probability = 26%). While disparities among Black and Hispanic VA-users were similar relative to white VA-users across VAMCs at all performance levels, disparities were exacerbated for AIAN and Native Hawaiian or Other Pacific Islander VA-users in bottom-performing VAMCs. Equity remains an issue even in facilities providing overall high-quality care. Integrating equity as a component of quality measures can incentivize greater focus on equity in quality improvement.","PeriodicalId":502462,"journal":{"name":"Health Affairs Scholar","volume":"2 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141266210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Benjamin Thornburg, Emma E. McGinty, Julia C P Eddelbuettel, Alene Kennedy-Hendricks, Robert Tyler Braun, Matthew D Eisenberg
Private equity and other for-profit ownership of behavioral health (mental health and substance use) treatment facilities has become increasingly prevalent, but data on these acquisitions are not readily available. In this study, we describe a novel database that contains information on the universe of behavioral health acquisitions that occurred between 2010-2021. We found that the frequency of behavioral health facilities involved in acquisitions increased substantially, from 32 facilities in 2010 to 1,330 in 2021. The total number of facilities involved in acquisitions was 2,806. Most of these facilities provided outpatient services only (N=2,073) and offered only mental health services (N=1,428). Private equity-backed acquisitions accounted for around 60% of all acquisition activity (N=1,678 facilities private equity, N=1,128 facilities other for-profit). 25% of acquired facilities were located within 20 miles of one another (N=561), 50% occurred within 80 miles (N=1,403), and 75% occurred within 319 miles (N=2,104). Future research should evaluate the effects of this consolidation on behavioral healthcare access, quality, spending, and patient outcomes.
{"title":"Acquisitions of Behavioral Health Treatment Facilities from 2010-2021","authors":"Benjamin Thornburg, Emma E. McGinty, Julia C P Eddelbuettel, Alene Kennedy-Hendricks, Robert Tyler Braun, Matthew D Eisenberg","doi":"10.1093/haschl/qxae080","DOIUrl":"https://doi.org/10.1093/haschl/qxae080","url":null,"abstract":"\u0000 Private equity and other for-profit ownership of behavioral health (mental health and substance use) treatment facilities has become increasingly prevalent, but data on these acquisitions are not readily available. In this study, we describe a novel database that contains information on the universe of behavioral health acquisitions that occurred between 2010-2021. We found that the frequency of behavioral health facilities involved in acquisitions increased substantially, from 32 facilities in 2010 to 1,330 in 2021. The total number of facilities involved in acquisitions was 2,806. Most of these facilities provided outpatient services only (N=2,073) and offered only mental health services (N=1,428). Private equity-backed acquisitions accounted for around 60% of all acquisition activity (N=1,678 facilities private equity, N=1,128 facilities other for-profit). 25% of acquired facilities were located within 20 miles of one another (N=561), 50% occurred within 80 miles (N=1,403), and 75% occurred within 319 miles (N=2,104). Future research should evaluate the effects of this consolidation on behavioral healthcare access, quality, spending, and patient outcomes.","PeriodicalId":502462,"journal":{"name":"Health Affairs Scholar","volume":"86 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141267890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A growing literature has identified substantial inaccuracies in consumer-facing provider directories, but it is unclear how long these inaccuracies persist. We re-surveyed inaccurately listed Pennsylvania providers (N=5,170) between 117 to 280 days after a previous secret shopper survey. Overall, 19.0% (N=983) of provider directory listings that had been identified as inaccurate were subsequently removed; 44.8% (N=2,316) of provider listings continued to show at least one inaccuracy; and 11.6% (N=600) were accurate at follow-up. We were unable to reach 24.6% (N=1,271) of providers. Longer passage of time was associated with reductions in directory inaccuracies, particularly related to contact information, and to a lesser degree, with removal of inaccurate listings. We found substantial differences in corrective action by carrier. Together, these findings suggest persistent barriers to maintaining and updating provider directories, with implications for how well these tools can help consumers select health plans and access care.
{"title":"Inaccuracies in Provider Directories Persist for Long Periods of Time","authors":"Simon F. Haeder, Jane M Zhu","doi":"10.1093/haschl/qxae079","DOIUrl":"https://doi.org/10.1093/haschl/qxae079","url":null,"abstract":"\u0000 A growing literature has identified substantial inaccuracies in consumer-facing provider directories, but it is unclear how long these inaccuracies persist. We re-surveyed inaccurately listed Pennsylvania providers (N=5,170) between 117 to 280 days after a previous secret shopper survey. Overall, 19.0% (N=983) of provider directory listings that had been identified as inaccurate were subsequently removed; 44.8% (N=2,316) of provider listings continued to show at least one inaccuracy; and 11.6% (N=600) were accurate at follow-up. We were unable to reach 24.6% (N=1,271) of providers. Longer passage of time was associated with reductions in directory inaccuracies, particularly related to contact information, and to a lesser degree, with removal of inaccurate listings. We found substantial differences in corrective action by carrier. Together, these findings suggest persistent barriers to maintaining and updating provider directories, with implications for how well these tools can help consumers select health plans and access care.","PeriodicalId":502462,"journal":{"name":"Health Affairs Scholar","volume":"4 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141267277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Consumers in health insurance markets have inertia stemming from the desire to maintain relationships with providers and other frictions involved in switching plans. In other markets that feature inertia, suppliers respond with pricing strategies that vary by market share: lowering markups to capture consumers when market shares are low, and raising markups to harvest profits once market share has been established. I tested for this behavior in the Medicare Advantage market by examining how MA plan sponsors changed the financial terms of their plans in response to changes in market share from 2007-2021 using a first-difference model with fixed effects. I found evidence that plans increase premiums, copays, and out-of-pocket limits when market shares increase. The results imply that for every 1% increase in market share, plan sponsors subsequently increase out-of-pocket costs by 1% in the following year.
{"title":"Capturing and harvesting in Medicare Advantage plan design","authors":"Keaton Miller","doi":"10.1093/haschl/qxae077","DOIUrl":"https://doi.org/10.1093/haschl/qxae077","url":null,"abstract":"\u0000 Consumers in health insurance markets have inertia stemming from the desire to maintain relationships with providers and other frictions involved in switching plans. In other markets that feature inertia, suppliers respond with pricing strategies that vary by market share: lowering markups to capture consumers when market shares are low, and raising markups to harvest profits once market share has been established. I tested for this behavior in the Medicare Advantage market by examining how MA plan sponsors changed the financial terms of their plans in response to changes in market share from 2007-2021 using a first-difference model with fixed effects. I found evidence that plans increase premiums, copays, and out-of-pocket limits when market shares increase. The results imply that for every 1% increase in market share, plan sponsors subsequently increase out-of-pocket costs by 1% in the following year.","PeriodicalId":502462,"journal":{"name":"Health Affairs Scholar","volume":"3 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141267253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Over the past 25 years, the gap between the increase in health insurance costs and workers’ wages has significantly expanded. This trend has led to significant concerns about healthcare affordability, with surveys revealing conflicting opinions regarding whether hospitals or health insurance companies bear the blame for escalating costs. To better understand these dynamics, we examined consumer price indices for health insurance, hospital services, and professional services over from 2006 to 2023 using Bureau of Labor Statistics data. Our analysis shows that the hospital price index rose steadily between 2006 and 2023, faster than insurance premiums or professional services. To examine whether differences in underlying costs are driving higher hospital price increases, we evaluated the profit margins of hospitals and health insurance companies using the National Academy for State Health Policy's Hospital Cost Tool and National Association of Insurance Commissioners Industry Reports. Our findings reveal that hospitals (for-profit and non-profit) have consistently maintained higher profit margins than insurance companies. As health insurance costs continue to weigh heavily on working Americans, our analysis suggests that high hospital prices drive insurance premiums.
{"title":"Why Does the Cost of Employer Sponsored Coverage Keep Rising?","authors":"Salpy Kanimian, Vivian Ho","doi":"10.1093/haschl/qxae078","DOIUrl":"https://doi.org/10.1093/haschl/qxae078","url":null,"abstract":"\u0000 Over the past 25 years, the gap between the increase in health insurance costs and workers’ wages has significantly expanded. This trend has led to significant concerns about healthcare affordability, with surveys revealing conflicting opinions regarding whether hospitals or health insurance companies bear the blame for escalating costs. To better understand these dynamics, we examined consumer price indices for health insurance, hospital services, and professional services over from 2006 to 2023 using Bureau of Labor Statistics data. Our analysis shows that the hospital price index rose steadily between 2006 and 2023, faster than insurance premiums or professional services. To examine whether differences in underlying costs are driving higher hospital price increases, we evaluated the profit margins of hospitals and health insurance companies using the National Academy for State Health Policy's Hospital Cost Tool and National Association of Insurance Commissioners Industry Reports. Our findings reveal that hospitals (for-profit and non-profit) have consistently maintained higher profit margins than insurance companies. As health insurance costs continue to weigh heavily on working Americans, our analysis suggests that high hospital prices drive insurance premiums.","PeriodicalId":502462,"journal":{"name":"Health Affairs Scholar","volume":"90 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141268063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Uscher-Pines, Jessica Sousa, Pushpa Raja, A. Mehrotra, Alisa B. Busch, H. Huskamp
There is ongoing policy debate on the prescribing of controlled substances such as buprenorphine and stimulants via telemedicine. The goal of federal and state policymakers is to ensure access to care while limiting diversion risk. However, there is little evidence on how clinicians view and address diversion and on telemedicine's role in diversion. From December 2023-January 2024, we conducted semi-structured interviews with 21 psychiatrists and primary care physicians engaged in hybrid (telemedicine and in-person) care models in which we explored perceptions of diversion and strategies used to monitor for diversion. Most physicians reported monitoring for diversion, but there was little consistency on how monitoring was done and reported strategies did not differ between telemedicine vs. in-person care. When physicians suspected diversion, there was also wide variation in responses. Few physicians had ever reported a case of suspected diversion to law enforcement. Our findings suggest that the Drug Enforcement Administration could clarify reporting requirements and professional societies could provide additional guidance on how to respond to suspected diversion, given the current variation in practice across clinicians could be exploited by individuals who want to divert.
{"title":"Perceptions of Stimulant and Buprenorphine Diversion and Strategies to Address It","authors":"L. Uscher-Pines, Jessica Sousa, Pushpa Raja, A. Mehrotra, Alisa B. Busch, H. Huskamp","doi":"10.1093/haschl/qxae074","DOIUrl":"https://doi.org/10.1093/haschl/qxae074","url":null,"abstract":"\u0000 There is ongoing policy debate on the prescribing of controlled substances such as buprenorphine and stimulants via telemedicine. The goal of federal and state policymakers is to ensure access to care while limiting diversion risk. However, there is little evidence on how clinicians view and address diversion and on telemedicine's role in diversion. From December 2023-January 2024, we conducted semi-structured interviews with 21 psychiatrists and primary care physicians engaged in hybrid (telemedicine and in-person) care models in which we explored perceptions of diversion and strategies used to monitor for diversion. Most physicians reported monitoring for diversion, but there was little consistency on how monitoring was done and reported strategies did not differ between telemedicine vs. in-person care. When physicians suspected diversion, there was also wide variation in responses. Few physicians had ever reported a case of suspected diversion to law enforcement. Our findings suggest that the Drug Enforcement Administration could clarify reporting requirements and professional societies could provide additional guidance on how to respond to suspected diversion, given the current variation in practice across clinicians could be exploited by individuals who want to divert.","PeriodicalId":502462,"journal":{"name":"Health Affairs Scholar","volume":"29 30","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141270756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PROMs are becoming more widely implemented across health care for important reasons. However, with thousands of PROMs available and the science of psychometrics becoming more widely applied in health measurement, choosing the right ones to implement can be puzzling. This article provides a framework of the different types of PROMs by organizing them into four categories based upon “what” is being measured and “from whom” the questions are asked: (1) condition-specific and domain-specific, (2) condition-specific and global, (3) universal and global, and (4) universal and domain-specific. We delve deeper into each category with clinical examples. This framework can empower health care leaders and policymakers to make more informed decisions when selecting the best PROMs to implement, ensuring PROMs deliver on their potential to promote value-based care.
{"title":"Selecting Patient-Reported Outcome Measures: “What” and “For Whom”","authors":"Jason B Liu, Nan E. Rothrock, Maria O Edelen","doi":"10.1093/haschl/qxae038","DOIUrl":"https://doi.org/10.1093/haschl/qxae038","url":null,"abstract":"\u0000 PROMs are becoming more widely implemented across health care for important reasons. However, with thousands of PROMs available and the science of psychometrics becoming more widely applied in health measurement, choosing the right ones to implement can be puzzling. This article provides a framework of the different types of PROMs by organizing them into four categories based upon “what” is being measured and “from whom” the questions are asked: (1) condition-specific and domain-specific, (2) condition-specific and global, (3) universal and global, and (4) universal and domain-specific. We delve deeper into each category with clinical examples. This framework can empower health care leaders and policymakers to make more informed decisions when selecting the best PROMs to implement, ensuring PROMs deliver on their potential to promote value-based care.","PeriodicalId":502462,"journal":{"name":"Health Affairs Scholar","volume":"30 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140375693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Accountable care organizations (ACOs) were created to promote healthcare value by improving health outcomes while curbing healthcare expenditures. Although a decade has passed, the value of care delivered by ACOs is yet to be fully understood. We proposed a novel measure of healthcare value using data envelopment analysis and examined its association with ACO organizational characteristics and social determinants of health (SDOH). We observed that the value of care delivered by ACOs stagnated in recent years, which may be partially attributed to challenges in care continuity and coordination across providers. ACOs that were solely led by physicians and included more participating entities exhibited lower value, highlighting the role of coordination across ACO networks. Furthermore, SDOH factors, such as economic well-being, healthy food consumption, and access to health resources, were significant predictors of ACO value. Our findings suggest a “skinny in scale, broad in scope” approach for ACOs to improve the value of care. Healthcare policy should also incentivize ACOs to work with local communities and enhance care coordination of vulnerable patient populations across siloed and disparate care delivery systems.
{"title":"Measuring Value in Healthcare: Lessons from Accountable Care Organizations","authors":"Chenzhang Bao, I. Bardhan","doi":"10.1093/haschl/qxae028","DOIUrl":"https://doi.org/10.1093/haschl/qxae028","url":null,"abstract":"\u0000 Accountable care organizations (ACOs) were created to promote healthcare value by improving health outcomes while curbing healthcare expenditures. Although a decade has passed, the value of care delivered by ACOs is yet to be fully understood. We proposed a novel measure of healthcare value using data envelopment analysis and examined its association with ACO organizational characteristics and social determinants of health (SDOH). We observed that the value of care delivered by ACOs stagnated in recent years, which may be partially attributed to challenges in care continuity and coordination across providers. ACOs that were solely led by physicians and included more participating entities exhibited lower value, highlighting the role of coordination across ACO networks. Furthermore, SDOH factors, such as economic well-being, healthy food consumption, and access to health resources, were significant predictors of ACO value. Our findings suggest a “skinny in scale, broad in scope” approach for ACOs to improve the value of care. Healthcare policy should also incentivize ACOs to work with local communities and enhance care coordination of vulnerable patient populations across siloed and disparate care delivery systems.","PeriodicalId":502462,"journal":{"name":"Health Affairs Scholar","volume":"81 16","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140087302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Medical crowdfunding is a key source of finance for individuals facing high out of pocket costs, including organ transplant candidates. However, little is known about racial disparities in campaigning activity and outcomes, or how these relate to access to care. In this exploratory nationwide cross-sectional study, we examined racial disparities in campaigning activity across states and the association between U.S. campaigners’ race and ethnicity and crowdfunding outcomes using a novel database of organ-transplant related campaigns, and an algorithm to identify race and ethnicity based on name and geographic location. This analysis suggests that there are racial disparities in individuals’ ability to successfully raise requested funds, with Black and Hispanic campaigners fundraising lower amounts and less likely to achieve their monetary goals. We also find that crowdfunding among White, Black, and Hispanic populations exhibit different patterns of activity at the state level, and in relation to race specific uninsurance and wait list additions, highlighting potential differences in fundraising need across the three groups. Policy efforts should consider not only how inequalities in fundraising ability for associated costs influences accessibility to care, but also how to identify clinical need among minorities.
{"title":"The Role of Race and Ethnicity in Healthcare Crowdfunding: an exploratory analysis","authors":"Sara Machado, Beatrice Perez, Irene Papanicolas","doi":"10.1093/haschl/qxae027","DOIUrl":"https://doi.org/10.1093/haschl/qxae027","url":null,"abstract":"\u0000 Medical crowdfunding is a key source of finance for individuals facing high out of pocket costs, including organ transplant candidates. However, little is known about racial disparities in campaigning activity and outcomes, or how these relate to access to care. In this exploratory nationwide cross-sectional study, we examined racial disparities in campaigning activity across states and the association between U.S. campaigners’ race and ethnicity and crowdfunding outcomes using a novel database of organ-transplant related campaigns, and an algorithm to identify race and ethnicity based on name and geographic location. This analysis suggests that there are racial disparities in individuals’ ability to successfully raise requested funds, with Black and Hispanic campaigners fundraising lower amounts and less likely to achieve their monetary goals. We also find that crowdfunding among White, Black, and Hispanic populations exhibit different patterns of activity at the state level, and in relation to race specific uninsurance and wait list additions, highlighting potential differences in fundraising need across the three groups. Policy efforts should consider not only how inequalities in fundraising ability for associated costs influences accessibility to care, but also how to identify clinical need among minorities.","PeriodicalId":502462,"journal":{"name":"Health Affairs Scholar","volume":"27 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140423042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Antonios M. Koumpias, Owen Fleming, Lewei Allison Lin
During the COVID-19 public health emergency, states waived in-state licensure and pre-existing patient-physician relationship requirements to increase access to care. We exploit this state telehealth policy variation to estimate the association of in-state licensure requirement waivers and pre-existing patient-physician relationship requirement waivers with out-of-state tele-mental healthcare utilization of patients diagnosed with COVID-19. Using claims from January 2019 till December 2021 of 2,037,977 commercially insured individuals in 3 metropolitan statistical areas (MSA) straddling Midwestern state borders, we find increased out-of-state telehealth utilization as a share of out-of-state mental healthcare by 0.1411 and 0.0575 visits per month or 1,679.76% and 467.48% after licensure and relationship waivers, respectively. Within-MSA analyses illustrate an urban-rural digital divide in out-of-state utilization as a share of total or telehealth mental healthcare. Our findings indicate waivers primarily enhance access to care of established patients by enabling the transition of in-person out-of-state healthcare online. Interstate medical licensure compact participation may provide broader access to out-of-state tele-mental healthcare than emergency waivers.
{"title":"Association of Licensure and Relationship Requirement Waivers with Out-of-State Tele-Mental Healthcare, 2019-2021","authors":"Antonios M. Koumpias, Owen Fleming, Lewei Allison Lin","doi":"10.1093/haschl/qxae026","DOIUrl":"https://doi.org/10.1093/haschl/qxae026","url":null,"abstract":"\u0000 During the COVID-19 public health emergency, states waived in-state licensure and pre-existing patient-physician relationship requirements to increase access to care. We exploit this state telehealth policy variation to estimate the association of in-state licensure requirement waivers and pre-existing patient-physician relationship requirement waivers with out-of-state tele-mental healthcare utilization of patients diagnosed with COVID-19. Using claims from January 2019 till December 2021 of 2,037,977 commercially insured individuals in 3 metropolitan statistical areas (MSA) straddling Midwestern state borders, we find increased out-of-state telehealth utilization as a share of out-of-state mental healthcare by 0.1411 and 0.0575 visits per month or 1,679.76% and 467.48% after licensure and relationship waivers, respectively. Within-MSA analyses illustrate an urban-rural digital divide in out-of-state utilization as a share of total or telehealth mental healthcare. Our findings indicate waivers primarily enhance access to care of established patients by enabling the transition of in-person out-of-state healthcare online. Interstate medical licensure compact participation may provide broader access to out-of-state tele-mental healthcare than emergency waivers.","PeriodicalId":502462,"journal":{"name":"Health Affairs Scholar","volume":"73 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140421245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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