ABSTRACT
INTRODUCTION: Telemedicine is designed to increase access to specialist care, especially in settings distant from tertiary-care centers. One of the more established telemedicine applications in hospitals is the tele-intensive care unit (tele-ICU). Perceptions of tele-ICU users are not well studied. Thus, we undertook a study focused on assessing staff acceptance at multiple hospitals that had implemented a tele-ICU system. MATERIALS AND METHODS: We designed a survey instrument that gathered perceptions on multiple facets of tele-ICU use and administered it to clinical and administrative staff at 28 hospitals that had implemented a tele-ICU system. We also conducted interviews at half of these hospitals to gain a deeper understanding of factors affecting staff perceptions of tele-ICU services. RESULTS: The 145 survey respondents were generally positive about all facets of the service. Analyses found no significant differences in comparisons between critical access and larger hospitals or between clinical and administrative/managerial respondents, although a few differences between providers and nurses emerged. Respondents at hospitals averaging more tele-ICU use and that had implemented it longer were significantly (p<0.05) more positive in their responses on multiple survey items than other respondents. Interviews corroborated and provided insight into survey responses. CONCLUSIONS: Tele-ICU was particularly valued when critical access hospitals retained critical care patients during special circumstances and when the tele-ICU hub could monitor patients to provide relief for local providers and nurses. Tele-ICU can aid rural hospitals, but multiple delivery models are warranted to meet disparate needs.
Subject(s)
Health Knowledge, Attitudes, Practice , Hospitals, Rural , Intensive Care Units , Medical Staff, Hospital/psychology , Telemedicine , Humans , Interviews as Topic , Qualitative Research , South Dakota , Surveys and QuestionnairesABSTRACT
BACKGROUND: Tele-emergency is an expanding telehealth service that provides real-time audio/visual consultation delivered by an emergency medicine team to a remote, often rural, emergency department (ED). Financial analyses of tele-emergency in the literature are limited. This article expands the tele-emergency literature to describe the business case for tele-emergency. "Business case" is defined as a reasoned argument, supported by objective data and/or qualitative judgment, to implement or continue a service or product. MATERIALS AND METHODS: To evaluate tele-emergency financing from the perspective of a critical access hospital (CAH), 10 financial analysis categories were defined. Telephone interviews, site visits, and financial data from the eEmergency program of Avera Health (Sioux Falls, SD) were used to populate the categories. Avera Health information was augmented with national data where available. Three financial scenarios were then analyzed for CAH profit/loss associated with tele-emergency. RESULTS: Tele-emergency financial analysis demonstrated an $187,614 profit in a high revenue/low expense scenario, $49,841 profit in a midrange scenario, and $69,588 loss in a low revenue/high expense scenario. CONCLUSIONS: Tele-emergency may be a profitable rural hospital service line if the participating hospital adjusts ED processes to take advantage of increased revenue/savings opportunities afforded by tele-emergency. Savings due to tele-emergency primarily accrue when physician ED backup and physician ED staffing costs are substituted.
Subject(s)
Emergency Service, Hospital/economics , Telemedicine/economics , Health Care Surveys , Interviews as Topic , Organizational Case Studies , South DakotaABSTRACT
INTRODUCTION: As competition for physicians intensifies in the USA, rural areas are at a disadvantage due to challenges unique to rural medical practice. Telemedicine improves access to care not otherwise available in rural settings. Previous studies have found that telemedicine also has positive effects on the work environment, suggesting that telemedicine may improve rural physician recruitment and retention, although few have specifically examined this. METHODS: Using a mixed-method approach, clients of a single telemedicine service in the Upper Midwestern USA were surveyed and interviewed about their views of the impact of tele-emergency on physician recruitment and retention and the work environment. Surveys were completed by 292 clinical and administrative staff at 71 hospitals and semi-structured interviews were conducted with clinicians and administrators at 16 hospitals. RESULTS: Survey respondents agreed that tele-emergency had a positive effect on physician recruitment and retention and related workplace factors. Interviewees elucidated how the presence of tele-emergency played an important role in enhancing physician confidence, providing educational opportunities, easing burden, and supplementing care, workplace factors that interviewees believed would impact recruitment and retention. However, gains were limited by hospitals' interpretation of the Emergency Medical Treatment and Labor Act as requiring on-site physician coverage even if tele-emergency was used. CONCLUSIONS: Results indicate that, all other factors being equal, tele-emergency increases the likelihood of physicians entering and remaining in rural practice. New regulatory guidance by the Centers for Medicare and Medicaid Services related to on-site physician coverage will likely accelerate implementation of tele-emergency services in rural hospitals. Telemedicine may prove to be an increasingly valuable recruitment and retention tool for rural hospitals as competition for physicians intensifies.
Subject(s)
Attitude of Health Personnel , Emergency Medical Services/methods , Physicians/psychology , Rural Health Services , Telemedicine/methods , Education, Medical, Continuing , Humans , Personnel Selection , Self Efficacy , United States , Workforce , WorkplaceABSTRACT
The Quality Payment Program (QPP) is a Medicare value-based payment program with 2 tracks: -Advanced Alternative Payment Models (A-APMs), including two-sided risk Accountable Care Organizations (ACOs), and Merit-based Incentive Payment System (MIPS). In 2020, A-APM eligible ACO clinicians received an additional 5% positive, and MIPS clinicians received up to 5% negative or 2% positive performance-based adjustments to their Medicare Part B medical services payments. It is unclear whether the different payment adjustments have differential impacts on total medical services payments for ACO and MIPS participants. We compare Medicare Part B medical services payments received by primary care clinicians participating in ACO and MIPS programs using Medicare Provider Utilization and Payment Public Use Files from 2014 to 2018 using difference-in-differences regressions. We have 254 395 observations from 50 879 unique clinicians (ACO = 37.86%; MIPS = 62.14%). Regression results suggest that ACO clinicians have significantly higher Medicare Part B medical services payments ($1003.88; 95% CI: [579.08, 1428.69]) when compared to MIPS clinicians. Our findings suggest that ACO clinicians had a greater increase in medical services payments when compared to MIPS clinicians following QPP participation. Increased payments for Medicare Part B medical services among ACO clinicians may be driven partly by higher payment adjustment rates for ACO clinicians for Part B medical services. However, increased Part B medical services payments could also reflect clinicians switching to increased outpatient services to prevent potentially costly inpatient services. Policymakers should examine both aspects when evaluating QPP effectiveness.
Subject(s)
Accountable Care Organizations , Medicare Part B , Aged , Humans , United States , Motivation , Ambulatory CareABSTRACT
PURPOSE: Nursing home closures have raised concerns about access to post-acute care (PAC) and long-term care (LTC) services. We estimate the additional distance rural residents had to travel to access PAC and LTC services because of nursing home closures. METHODS: We identify nursing home closures and the availability of PAC and LTC services in nursing homes, home health agencies, and hospitals with swing beds using the Medicare Provider of Services file (2008-2018). Using distances between ZIP codes, we summarize distances to the closest provider of PAC and LTC services for rural and urban ZIP codes with nursing home closures from 2008 to 2018 and no nursing homes in 2018. FINDINGS: Compared to urban ZIP codes, rural ZIP codes experiencing nursing home closure had higher distances to the closest nursing home providing PAC (6.4 vs. 0.94 miles; p < 0.05) and LTC services (7.2 vs. 1.1 miles; p < 0.05), and these differences remain even after accounting for the availability of home health agencies and hospitals with swing beds. Distances to the closest providers with PAC and LTC services were even higher for rural ZIP codes with no nursing homes in 2018. About 6.1%-15.7% of rural ZIP codes with a nursing home closure or with no nursing homes had no PAC or LTC providers within 25 miles. CONCLUSIONS: Nursing home closures increased distances to nursing homes, home health agencies, and hospitals with swing beds for rural residents. Access to PAC and LTC services is a concern, especially for rural areas with no nursing homes.
Subject(s)
Health Facility Closure , Health Services Accessibility , Long-Term Care , Nursing Homes , Rural Population , Subacute Care , Humans , Nursing Homes/statistics & numerical data , Nursing Homes/organization & administration , Long-Term Care/statistics & numerical data , Long-Term Care/organization & administration , Long-Term Care/standards , Long-Term Care/methods , Long-Term Care/trends , Health Services Accessibility/statistics & numerical data , Health Services Accessibility/standards , Health Facility Closure/statistics & numerical data , Health Facility Closure/trends , Rural Population/statistics & numerical data , Subacute Care/statistics & numerical data , Subacute Care/methods , United StatesABSTRACT
PURPOSE: To assess differences in Patient Aligned Care Team (PACT) performance between rural and urban primary care clinics within the Veterans Health Administration (VHA). METHODS: An Explanatory Sequential Mixed Methods design was conducted using VHA administrative data to assess performance of a national sample of 891 VHA primary care clinics. Generalized Estimating Equations with repeated measures were used to estimate associations between rurality and process-oriented endpoints including: chronic disease management through telehealth; use of telephone visits, group visits or secured messaging; same-day access; continuity with primary care provider; and postdischarge follow-up. Qualitative data collected during on-site visits with 5 clinics were used to provide insights into PACT processes from the perspectives of staff in rural and urban clinics. FINDINGS: After adjusting for patient- and practice-level characteristics, clinics located in large rural or small/isolated rural areas demonstrated difficulty enhancing access through use of telephone visits, group visits, or secured messaging and completing postdischarge follow-up calls, compared to urban clinics. Qualitative analysis indicated that staff from both rural and urban clinics reported similar barriers implementing these PACT processes. Both patient and staff behaviors and preferences impact implementation of these processes. Distance to care and access to high-speed Internet were also reported as barriers. CONCLUSIONS: This study contributes to the understanding of PACT performance in rural settings by highlighting ways contextual and behavioral factors relate to performance. Increasing implementation of patient-centered medical home (PCMH) models, such as PACT, will require additional attention to the complex relationships between the practice and surrounding context.
Subject(s)
Aftercare , United States Department of Veterans Affairs , Humans , Patient Care Team , Patient Discharge , Patient-Centered Care , Primary Health Care , United StatesABSTRACT
In order better to inform policymakers about financing uncompensated hospital care through appropriate allocation of resources among Nebraska communities, this study used seven years (1996-2002) of county-level data from multiple sources to examine the relationship between population economic factors and the hospital inpatient care use by uninsured patients. The generalized estimating equation (GEE) regression analysis showed that, at the county level, the population uninsurance rate and other economic factors (e.g., per capita income, the percentage of population receiving welfare) are statistically significant predictors of average hospital self-pay inpatient charge per resident. Residents in the three western regions of the state also incurred statistically higher per-resident hospital self-pay inpatient charges than did their counterparts in the three eastern regions. State policymakers in Nebraska can use our study results to allocate resources on the basis of community economic characteristics and geographic location, to help reduce the financial burden of caring for the uninsured to safety net hospitals. The study may have a wide application to other states examining the same policy issues. The model used in this study can be easily created for other states, as the required data are readily available.
Subject(s)
Hospitals/statistics & numerical data , Inpatients , Medically Uninsured , Policy Making , Uncompensated Care , Humans , Inpatients/statistics & numerical data , Medically Uninsured/statistics & numerical data , Models, Theoretical , Nebraska , Population Surveillance/methods , Regression AnalysisABSTRACT
Using data from the 2002 Nationwide Inpatient Sample of the Healthcare Cost and Utilization Project, we examined the magnitude, variation, and determinants of rural hospital resource utilization associated with hospitalizations due to ambulatory care sensitive conditions (ACSCs). An estimated $9.5 billion in charges incurred in rural hospitals nationwide in 2002 was found to be associated with hospitalizations due to ACSCs. Our findings suggest that the smaller a rural hospital, the greater the portion of its financial resources used to treat patients with ACSC. Regional variation in ACSC-related hospital charges is generally consistent with the geographic variation in the population's economic status and primary care physician supply-residents of the South region have the poorest access to primary healthcare. In summary, smaller rural communities spend more of their healthcare resources on avoidable hospital inpatient care than do larger rural communities, leaving smaller rural communities potentially fewer resources to spend on preventive and primary healthcare. Health intervention programs and health policies should be designed to increase access to and utilization of appropriate preventive and primary healthcare in rural areas, especially in small and remote communities.
Subject(s)
Hospitals, Rural/statistics & numerical data , Outpatient Clinics, Hospital/statistics & numerical data , Community Health Planning , Databases as Topic , Health Care Surveys , Health Facility Size , Humans , Outpatient Clinics, Hospital/economics , Poverty , Resource Allocation , Risk Factors , United StatesABSTRACT
OBJECTIVE: This study examined whether rural and urban hospitals differ in their level of responsiveness to community health needs. DESIGN: This study used a multivariate, longitudinal research design. RESEARCH SETTING: A cross-sectional survey was the setting for this study. PARTICIPANTS: The participants were rural or urban hospitals in the United States. MAIN OUTCOME MEASURES: The dependent variables were selected from the American Hospital Association hospital survey questions that are related to community health needs. The independent variable was rural or urban location. RESULTS: Rural hospitals improved more than urban hospitals in addressing community health needs from 1997 through 2006 for most of the indicators, especially in working with other providers to conduct a community health assessment. However, rural hospitals still lag significantly behind urban hospitals in tracking health information. CONCLUSIONS: This study suggests that rural hospitals do not lag behind urban hospitals in addressing community health needs. Further research is needed to understand the role of community hospitals in influencing local health delivery system activities regarding the potential community benefits and their impact on improving health of local populations.
Subject(s)
Community Health Services/trends , Hospitals, Rural/trends , Hospitals, Urban/trends , Community Health Services/organization & administration , Community Health Services/statistics & numerical data , Hospitals, Rural/organization & administration , Hospitals, Rural/statistics & numerical data , Hospitals, Urban/organization & administration , Hospitals, Urban/statistics & numerical data , Humans , Longitudinal Studies , United StatesABSTRACT
CONTEXT: Few studies have examined hospitalization patterns among the uninsured, especially from the perspective of rural and urban differences. PURPOSE: To examine whether the patterns of uninsured hospitalizations differ in rural and urban hospitals and to identify the most prevalent and costly diagnoses among uninsured hospitalizations. METHODS: We conducted a cross-sectional analysis of the Healthcare Cost and Utilization Project's National Inpatient Sample representing a total of 37,804,021 hospital discharges, with 4.9% of them generated by uninsured persons in 2002. We compared demographic and clinical characteristics and the proportion of frequent and costly diagnoses by rural and urban hospitals. We used multiple logistic regression models to examine the relationship between preventable conditions and rural and urban hospitals among uninsured hospitalizations. FINDINGS: Uninsured persons discharged from rural hospitals were more likely than their urban counterparts to be working-age adults (82% vs 79%) and to reside in a ZIP code area with a median household income of less than $35,000 per year (56% vs 26%). Rural uninsured hospitalizations were more likely to be for preventable conditions than were urban uninsured hospitalizations (P < .001). The proportion of total hospital charges related to preventable hospitalizations was 15.5% in rural hospitals versus 10.0% in urban hospitals. CONCLUSIONS: The patterns of uninsured hospitalizations in rural and urban hospitals were different in many ways. Providing adequate access to primary care could result in potential savings related to preventable hospitalizations for the uninsured, especially for rural hospitals.
Subject(s)
Hospitalization/statistics & numerical data , Medically Uninsured/statistics & numerical data , Rural Population , Urban Population , Adolescent , Adult , Age Factors , Aged , Child , Child, Preschool , Cross-Sectional Studies , Demography , Female , Hospitalization/economics , Humans , Infant , Infant, Newborn , Male , Sex Factors , Socioeconomic FactorsABSTRACT
This Policy Brief continues the series of reports from the RUPRI Center updating the number of pharmacy closures in rural America with annual data. See our website for other analyses of trends and assessment of issues confronting rural pharmacies. Key Findings: (1) Over the last 16 years, 1,231 independently owned rural pharmacies (16.1 percent) in the United States have closed. The most drastic decline occurred between 2007 and 2009. This decline has continued through 2018, although at a slower rate. (2) 630 rural communities that had at least one retail (independent, chain, or franchise) pharmacy in March 2003 had no retail pharmacy in March 2018.
Subject(s)
Health Facility Closure/statistics & numerical data , Pharmacies/supply & distribution , Rural Health Services/supply & distribution , Forecasting , Health Facility Closure/trends , Humans , Medicare Part D , Pharmacies/statistics & numerical data , Pharmacies/trends , Rural Health Services/trends , Rural Population , United StatesABSTRACT
PURPOSE: High rates of potentially preventable hospitalizations and emergency department (ED) visits indicate limited primary care access. Rural Health Clinics (RHCs) are intended to increase access to primary care. The goal of this study was to evaluate the role of RHCs and their impact on potentially preventable hospitalizations and ED visits among Medicare beneficiaries based on actual individual-level utilization patterns. METHODS: With Medicare Part A and Part B claims data from 2007 to 2010, we constructed a series of individual-level negative binomial regression models to examine the relationship between RHC use and the number of potentially preventable hospitalizations and ED visits. FINDINGS: RHC use was associated with a 27% increase in potentially preventable hospitalizations and a 24% increase in potentially preventable ED visits among older Medicare enrollees. Among younger, disabled Medicare beneficiaries, RHC use was associated with a 14% increase in potentially preventable hospitalizations and an 18% increase in potentially preventable ED visits. Potentially preventable hospitalizations and ED visits were more common among beneficiaries who were black or who had more chronic conditions. CONCLUSIONS: The results of our study highlight that the Medicare population using RHCs is at especially high risk for potentially preventable hospitalizations and ED visits. The mechanisms behind this are not well understood and should receive continued attention from policy makers and researchers.
Subject(s)
Emergency Service, Hospital/standards , Hospitalization/trends , Patient Acceptance of Health Care/statistics & numerical data , Rural Health Services/statistics & numerical data , Aged , Aged, 80 and over , Emergency Service, Hospital/organization & administration , Emergency Service, Hospital/statistics & numerical data , Female , Hospitalization/statistics & numerical data , Humans , Male , Medicare/organization & administration , Medicare/statistics & numerical data , Middle Aged , United StatesABSTRACT
Purpose: Since 2014, when the Health Insurance Marketplaces (HIMs) authorized by the Patient Protection and Affordable Care Act (PPACA) were implemented, considerable premium changes have been observed in the marketplaces across the 50 states and the District of Columbia. This policy brief assesses the changes in average HIM plan premiums from 2014 to 2018, before accounting for subsidies, with an emphasis on the widening variation across rural and urban places, providing information during Congressional debates on the future of the program. Key Findings: (1) Insurance issuers reduced HIM participation across both rural and urban places (with 1.7 and 2.2 issuers, respectively), both in states that expanded Medicaid under the PPACA and in non-expansion states. (2) The average adjusted premium (before premium subsidy) continues to rise across all of the above categories, and the gap has widened between the 32 Medicaid expansion and 19 non-expansion states. Average premiums in rural counties are higher than average premiums in urban counties in both expansion and non-expansion states (by $43 per month and $27 per month, respectively). (3) Prior trends of lower premium changes at greater population densities are no longer observed in the 2018 data. (4) In 2018, 1,581 counties (52 perent) have one participating insurance issuer. Nationwide, 42 percent of all urban counties and 55 percent of all rural counties only have one issuer.
Subject(s)
Health Insurance Exchanges/economics , Health Insurance Exchanges/statistics & numerical data , Health Insurance Exchanges/trends , Insurance Carriers/economics , Insurance Carriers/statistics & numerical data , Insurance Carriers/trends , Insurance, Health/economics , Insurance, Health/statistics & numerical data , Insurance, Health/trends , Rural Health Services/supply & distribution , Rural Health Services/statistics & numerical data , Rural Health Services/trends , Rural Population/statistics & numerical data , Forecasting , Humans , Medicaid , Patient Protection and Affordable Care Act , Population Density , United StatesABSTRACT
Purpose: This policy brief provides data assessing effects of Medicaid Disproportionate Share Hospital (DSH) payment on rural hospitals in 47 states. While the allocation of DSH funds to the state is determined by federal legislation utilizing a formula developed by the Centers for Medicare & Medicaid Services (CMS), each state determines distribution to hospitals using an approved State Plan Amendment (SPA) that meets minimum federal requirements. Our findings suggest that distribution to rural hospitals, and critical access hospitals (CAHs) in particular, varies considerably across states. Data presented in this document helps ground any changes to either federal requirements or to SPAs by showing the impact of DSH payment from the most recent data available. Key Findings: (1) Medicaid DSH payment methodology and distribution to hospitals varies considerably across states. (2) The percentage of rural hospitals in a state receiving any Medicaid DSH payment ranged from 0 percent to 100 percent. (3) For rural hospitals receiving Medicaid DSH payments, the impact on total patient revenue ranged from less than 0.5 percent to 8.8 percent.
Subject(s)
Hospitals, Rural/economics , Hospitals, Rural/statistics & numerical data , Hospitals, Urban/economics , Hospitals, Urban/statistics & numerical data , Medicaid/economics , Medicaid/statistics & numerical data , Reimbursement, Disproportionate Share/economics , Reimbursement, Disproportionate Share/statistics & numerical data , Critical Care/economics , Critical Care/statistics & numerical data , Humans , State Government , United StatesABSTRACT
Purpose. From October 2013before implementation of the Affordable Care Act (ACA)to November 2016, Medicaid enrollment grew by 27 percent. However, very little attention has been paid to date to how changes in Medicaid enrollment vary within states across the rural-urban continuum. This brief reports and analyzes changes in enrollment in metropolitan, micropolitan, and rural (noncore) areas in both expansion states (those that used ACA funding to expand Medicaid coverage) and nonexpansion states (those that did not use ACA funding to expand Medicaid coverage). The findings suggest that growth has been uneven across rural-urban geography, and that Medicaid enrollment growth is lower in rural counties, particularly in nonexpansion states. Key Findings. (1) Medicaid growth rates in metropolitan counties in nonexpansion states from 2012 to 2015 were twice as large as in rural counties (14 percent compared to 7 percent). (2) In contrast, the differential in growth rates between metropolitan, micropolitan, and rural counties was much less dramatic in expansion states (growth rates of 43 percent, 38 percent, and 38 percent, respectively). (3) Analysis at the state level shows much variability across the states, even when controlling for expansion status. For example, some states with an above-average rural population, such as Tennessee and Idaho, had higher-than-average enrollment increases, with strong rural increases, while other states with similar proportions of rural residents, such as Nebraska, Oklahoma, Maine, and Wyoming, experienced enrollment decreases in micropolitan and/or rural counties. (4) States' pre-ACA Medicaid eligibility levels for parents and children affected the potential for growth. For example, some states that had higher eligibility levels (e.g., Maryland and Illinois) experienced lower Medicaid growth rates from 2012 to 2015, in part because their baseline enrollment was higher. (5) In the expansion states of Colorado and Nevada, which both have State-Based Marketplaces (SBMs), enrollment increases were over four times the overall average.
Subject(s)
Medicaid/statistics & numerical data , Medicaid/trends , Rural Population/statistics & numerical data , Rural Population/trends , Urban Population/statistics & numerical data , Urban Population/trends , Forecasting , Humans , Patient Protection and Affordable Care Act/trends , State Government , United StatesABSTRACT
Purpose. In this brief, cumulative county-level enrollment in Health Insurance Marketplaces (HIMs) through March 2016 is presented for state HIMs operated as Federally Facilitated Marketplaces (FFMs) and for those operated as Federally Supported State-Based Marketplaces (FS-SBMs). Enrollment rates in metropolitan and non-metropolitan areas of each state, defined as the percentage of "potential market" participants selecting plans, are presented. Monitoring annual enrollment rates provides a gauge of how well state outreach and enrollment efforts are proceeding and helps identify states with strong non-metropolitan enrollment as models for other states to emulate. Key Findings. (1) Cumulative enrollment in the HIMs in non-metropolitan counties has grown to about 1.4 million in 2016, representing 40 percent of the potential market in non-metropolitan counties. (2) Estimated enrollment rates varied considerably across the United States. In particular, estimated enrollment rates in non-metropolitan areas were substantially higher than in metropolitan areas in Hawaii, Illinois, Michigan, Montana, Maine, Nebraska, Wisconsin, and Wyoming. (3) The states that achieved the highest absolute non-metropolitan enrollment totals were Michigan, Georgia, Missouri, North Carolina, Texas, and Wisconsin. Of these, Michigan, North Carolina, and Wisconsin also had non-metropolitan enrollment rates above 50 percent. (4) About half of all states, evenly distributed by Medicaid expansion status but mostly concentrated in the Midwestern census region, had higher enrollment growth in non-metropolitan areas from 2015 to 2016, and in fact aggregated non-metropolitan growth was greater than metropolitan growth in both expansion categories.
Subject(s)
Health Insurance Exchanges/statistics & numerical data , Insurance, Health/statistics & numerical data , Rural Population/statistics & numerical data , Humans , Medicaid/statistics & numerical data , State Government , United StatesABSTRACT
CONTEXT: Hospitalization due to ambulatory care sensitive conditions (ACSCs) is often used as an indicator for measuring access to primary care. Rural health clinics (RHCs) provide basic primary care services for rural residents in health professional shortage areas (HPSAs). The relationship between RHCs and ACSCs is unclear. PURPOSE: The purpose of this study was to examine the relationship between the presence of RHCs in rural HPSAs and the likelihood of having an acute or chronic ACSC as the reason for hospitalization. METHODS: Nebraska hospital discharge data (1999-2001) and the 2003 Area Resource File were used in this analysis. A multilevel logistic regression analysis was used to examine the relationship between the presence of RHCs in rural HPSAs and the likelihood of having an ACSC as the reason for hospitalization, after controlling for individual characteristics and county-level contextual factors stratified by 3 age groups. The eligibility for logistic regression was limited to patients from 28 rural Nebraska counties designated as HPSAs in 2001. Patients with commercial payers were excluded from the study. FINDINGS: Elderly patients residing in rural Nebraska HPSAs with at least one RHC were significantly less likely to have a hospitalization due to chronic ACSCs. CONCLUSIONS: The presence of RHC is a significant factor associated with fewer hospitalizations for chronic ACSCs among the rural elderly residing in HPSAs.
Subject(s)
Ambulatory Care/statistics & numerical data , Hospitalization/statistics & numerical data , Medically Underserved Area , Rural Health Services/statistics & numerical data , Adult , Aged , Female , Health Services Accessibility/statistics & numerical data , Humans , Income , Logistic Models , Male , Middle Aged , NebraskaABSTRACT
OBJECTIVES: We examined differences in health care ratings and reported health care experiences for active duty uniform services personnel using health care plans other than military treatment facilities. METHODS: We used a cross-sectional mail survey of a stratified sample of 3,871 beneficiaries enrolled in TRICARE Prime (TP) and TRICARE Prime Remote (TPR). The adjusted plan mean composite and global ratings were compared between TP and TPR participants. RESULTS: There were few significant differences between the two groups. Patient satisfaction was higher when patients chose their providers (TPR), and use of some preventive services was higher in managed-care plans (TP). Respondents in metropolitan locations differed significantly from those in nonmetropolitan locations in ratings of plans, quality of health care received, and access to services. CONCLUSIONS: The military health system is achieving some success in delivering uniform benefits but faces challenges in delivering high-quality uniform benefits in rural communities.
Subject(s)
Health Benefit Plans, Employee/standards , Health Services Accessibility , Military Medicine/standards , Military Personnel/psychology , Patient Satisfaction/statistics & numerical data , Quality of Health Care , Adolescent , Adult , Cross-Sectional Studies , Female , Health Benefit Plans, Employee/classification , Health Care Surveys , Hospitals, Military/supply & distribution , Humans , Male , Middle Aged , Military Medicine/economics , Rural Health Services/standards , United States , Urban Health Services/standardsABSTRACT
BACKGROUND: Rural communities have disproportionately faced primary care shortages for decades in spite of policy efforts to prepare and attract primary care health professionals to practice in rural locales. Insight into how primary care physicians' service patterns in rural areas differ from those in less rural places is important to better inform recruitment strategies that target primary care providers and rural communities. OBJECTIVES: The purpose of this research is to describe how primary care physician service patterns vary by rural-urban location for a large, privately insured population. We discuss implications of service pattern variation on policy efforts to attract primary care providers to underserved rural areas. METHODS: Claims data from fully insured commercial health insurance beneficiaries were used to develop service pattern profiles for primary care providers located in 1 of 4 types of rural-urban areas in Iowa in 2009. The 4 area types are metropolitan, micropolitan, noncore area adjacent to a metro area, and noncore/nonadjacent rural area. RESULTS: There were differences in primary care physicians' service patterns by rural-urban area type. Physicians in nonmetropolitan areas provided relatively more care on a per physician basis than those in the metropolitan area type, as well as more surgery, maternity, emergency, and nursing facility services than metropolitan physicians. CONCLUSION: Primary care physicians who value practicing a relatively diverse range of services may find locating in rural areas an appealing choice. Health systems and policy makers seeking to attract primary care physicians to rural areas can incorporate this reality into a recruitment strategy.
Subject(s)
Practice Patterns, Physicians'/statistics & numerical data , Primary Health Care/organization & administration , Primary Health Care/statistics & numerical data , Rural Health Services/statistics & numerical data , Urban Health Services/statistics & numerical data , Humans , Insurance Claim Review , Iowa , Primary Health Care/methodsABSTRACT
This brief updates Brief No. 2014-3 and explains changes in the Centers for Medicare & Medicaid Services (CMS) Accountable Care Organization (ACO) regulations issued in June 2015 pertaining to beneficiary assignment for Medicare Shared Savings Program ACOs. Overall, the regulatory changes are intended to (1) encourage ACOs to participate in two-sided risk contracts, (2) increase the likelihood that beneficiaries are assigned to the physician (and ACO) from whom they receive most of their primary care services, and (3) make it easier for Federally Qualified Health Centers (FQHCs) and Rural Health Clinics (RHCs) to participate in ACOs. Understanding ACO beneficiary assignment policies is critical for ACO in managing their panel of ACO providers and beneficiaries.