Early Childhood Vaccination Coverage and Patterns by Rural-Urban Commuting Area

INTRODUCTION

National surveillance efforts have reported rural-urban disparities in childhood vaccination coverage by metropolitan statistical area designations, measured at the county level. This study's objective was to quantify vaccination trends using more discrete measures of coverage and rurality than prior work.

METHODS

Serial, cross-sectional analyses of National Immunization Survey-Child restricted-use data collected in 2015-2021 for U.S. children born 2014-2018 were conducted. ZIP code of residence was merged with rural-urban commuting area codes. Vaccination coverage and patterns, including on-time receipt of recommended vaccines, were assessed using vaccinations recorded from birth through age 23 months. To determine whether trends differed by rurality, an interaction between birth year and RUCA was tested in multivariable regression models. Analyses were conducted in November 2023-January 2024.

RESULTS

In nationally representative analyses of N=59,361 children, 87.7%, 7.1%, and 5.3% lived in urban, large rural, or small town/rural areas, respectively. Among children born in 2018, coverage for the combined 7-vaccine series was 71.2% (95% CI=69.6%, 72.9%) in urban, 64.9% (95% CI=58.8%, 71.0%) in large rural, and 62.6% (95% CI=56.2%, 68.9%) in small town/rural areas. There was a positive trend in on-time vaccination in urban areas (adjusted prevalence ratio [aPR] for birth year=1.06; 95% CI=1.05, 1.08). While the trend did not significantly differ for large rural versus urban areas (interaction aPR=1.02; 95% CI=0.96, 1.08), there was less improvement in on-time vaccination in small town/rural areas (interaction aPR=0.93; 95% CI=0.88, 0.99).

CONCLUSIONS

Increased efforts are needed to eliminate disparities in routine and on-time vaccination for rural children.

Unmasking hidden disparities: a comparative observational study examining the impact of different rurality classifications for health research in Aotearoa New Zealand

OBJECTIVES

Examine the impact of two generic-urban-rural experimental profile (UREP) and urban accessibility (UA)-and one purposely built-geographic classification for health (GCH)-rurality classification systems on the identification of rural-urban health disparities in Aotearoa New Zealand (NZ).

DESIGN

A comparative observational study.

SETTING

NZ; the most recent 5 years of available data on mortality events (2013-2017), hospitalisations and non-admitted hospital patient events (both 2015-2019).

PARTICIPANTS

Numerator data included deaths (n=156 521), hospitalisations (n=13 020 042) and selected non-admitted patient events (n=44 596 471) for the total NZ population during the study period. Annual denominators, by 5-year age group, sex, ethnicity (Māori, non-Māori) and rurality, were estimated from Census 2013 and Census 2018.

PRIMARY AND SECONDARY OUTCOME MEASURES

Primary measures were the unadjusted rural incidence rates for 17 health outcome and service utilisation indicators, using each rurality classification. Secondary measures were the age-sex-adjusted rural and urban incidence rate ratios (IRRs) for the same indicators and rurality classifications.

RESULTS

Total population rural rates of all indicators examined were substantially higher using the GCH compared with the UREP, and for all except paediatric hospitalisations when the UA was applied. All-cause rural mortality rates using the GCH, UA and UREP were 82, 67 and 50 per 10 000 person-years, respectively. Rural-urban all-cause mortality IRRs were higher using the GCH (1.21, 95% CI 1.19 to 1.22), compared with the UA (0.92, 95% CI 0.91 to 0.94) and UREP (0.67, 95% CI 0.66 to 0.68). Age-sex-adjusted rural and urban IRRs were also higher using the GCH than the UREP for all outcomes, and higher than the UA for 13 of the 17 outcomes. A similar pattern was observed for Māori with higher rural rates for all outcomes using the GCH compared with the UREP, and 11 of the 17 outcomes using the UA. For Māori, rural-urban all-cause mortality IRRs for Māori were higher using the GCH (1.34, 95% CI 1.29 to 1.38), compared with the UA (1.23, 95% CI 1.19 to 1.27) and UREP (1.15, 95% CI 1.10 to 1.19).

CONCLUSIONS

Substantial variation in rural health outcome and service utilisation rates were identified with different classifications. Rural rates using the GCH are substantially higher than the UREP. Generic classifications substantially underestimated rural-urban mortality IRRs for the total and Māori populations.

Measuring rurality in health services research: a scoping review

PURPOSE

This study is a scoping review of the different methods used to measure rurality in the health services research (HSR) literature.

METHODS

We identified peer-reviewed empirical studies from 2010-2020 from seven leading HSR journals, including the Journal of Rural Health, that used any definition to measure rurality as a part of their analysis. From each study, we identified the geographic unit (e.g., county, zip code) and definition (e.g., Rural Urban Continuum Codes, Rural Urban Commuting Areas) used to classify categories of rurality. We analyzed whether geographic units and definitions used to classify rurality differed by focus area of studies, including costs, quality, and access to care. Lastly, we examined the number of rural categories used by authors to assess rural areas.

FINDINGS

In 103 included studies, five different geographic units and 11 definitions were used to measure rurality. The most common geographic units used to measure rurality were county (n = 59, 57%), which was used most frequently in studies examining cost (n = 12, 75%) and access (n = 33, 57.9%). Rural Urban Commuting Area codes were the most common definition used to measure rurality for studies examining access (n = 13, 22.8%) and quality (n = 10, 44%). The majority of included studies made rural versus urban comparisons (n = 82, 80%) as opposed to focusing on rural populations only (n = 21, 20%). Among studies that compared rural and urban populations, most studies used only one category to identify rural locations (n = 49 of 82 studies, 60%).

CONCLUSION

Geographic units and definitions to determine rurality were used inconsistently within and across studies with an HSR focus. This finding may affect how health disparities by rural location are determined and thus how resources and federal funds are allocated. Future research should focus on developing a standardized system to determine under what circumstances researchers should use different geographic units and methods to determine rurality by HSR focus area.

Mortality outcomes and inequities experienced by rural Māori in Aotearoa New Zealand

BACKGROUND

Previous research identified inequities in all-cause mortality between Māori and non-Māori populations. Unlike comparable jurisdictions, mortality rates in rural areas have not been shown to be higher than those in urban areas for either population. This paper uses contemporary mortality data to examine Māori and non-Māori mortality rates in rural and urban areas.

METHODS

A population-level observational study using deidentified routinely collected all-cause mortality, amenable mortality and census data. For each level of the Geographic Classification for Health (GCH), Māori and non-Māori age-sex standardised all-cause mortality and amenable mortality incident rates, Māori:Non-Māori standardised incident rate ratios and Māori rural:urban standardised incident rate ratios were calculated. Age and deprivation stratified rates and rate ratios were also calculated.

FINDINGS

Compared to non-Māori, Māori experience excess all-cause (SIRR 1.87 urban; 1.95 rural) and amenable mortality (SIRR 2.45 urban; 2.34 rural) and in all five levels of the GCH. Rural Māori experience greater all-cause (SIRR 1.07) and amenable (SIRR 1.13) mortality than their urban peers. Māori and non-Māori all-cause and amenable mortality rates increased as rurality increased.

INTERPRETATION

The excess Māori all-cause mortality across the rural: urban spectrum is consistent with existing literature documenting other Māori health inequities. A similar but more pronounced pattern of inequities is observed for amenable mortality that reflects ethnic differences in access to, and quality of, health care. The excess all-cause and amenable mortality experienced by rural Māori, compared to their urban counterparts, suggests that there are additional challenges associated with living rurally.

FUNDING

This work was funded by the Health Research Council of New Zealand (HRC19/488).

Evaluating policies to improve access to mental health services in rural areas

PURPOSE

The United States Department of Veterans Affairs (VA) has gradually implemented policies to increase access to mental health care outside of VA medical centers. Most notably, this included requirements to offer mental health services at VA-administered community-based clinics in 2008 and increased access to VA-paid care in the community beginning in 2014. Our objective was to understand how mental health service use patterns changed for rural VA patients during this time.

METHODS

We developed a longitudinal cohort of all rural patients who used VA services between 2002 and 2019 (N = 3,345,862). We examined individual, health care, and contextual predictors of mental health service use as well as modalities of mental health service use during policy-relevant time periods using descriptive statistics.

FINDINGS

Access to mental health services increased with each policy change. The annual percentage of rural VA patients accessing mental health services increased from 11.4% in the earliest years (2002-2004) to 19.8% in the latest years (2017-2019). The most rapid period of increase followed a requirement for availability of mental health services at VA-administered community clinics. Increasing access to VA-paid care in the community had less effect. By the end of the evaluation, gaps remained in the delivery of care to elderly patients over the age of 75.

CONCLUSIONS

Rural patients use mental health services when they become available. Access was the highest with a combination of changes to both delivery modalities and payment methods. Continued, and perhaps different efforts are required to address a persistent disparity for older patients.

The role of race in rural-urban suicide disparities

PURPOSE

To assess the role that race-ethnicity plays in modifying the observed rural-urban disparity in suicide among Veteran Health Administration (VHA) users.

METHODS

We performed a retrospective cohort study of 10,737,864 VHA users between 2003 and 2017, using cross-linked VHA medical records and National Death Index mortality data to assess longitudinal race-stratified rural-urban differences in age- and sex-adjusted annual suicide rates. We used Poisson regression and generated incident rate ratios (IRRs) to formally assess the impact of race on the rural-urban suicide disparity. Given evidence of effect modification, we performed additional race-stratified Poisson regression models.

FINDINGS

Rurality is significantly associated with a higher risk of suicide in models which do not control for race (IRR = 1.14, 95% CI: 1.10-1.17). However, when race is added to the model, rural residence is no longer significant (0.98, CI: 0.95-1.01). Stratified models demonstrate that rural residence is significantly associated with a higher suicide risk among Hispanic VHA users (1.41, CI: 1.11-1.79), but it is not substantially associated with suicide among White (0.97, CI: 0.94-1.00) and Black (1.03, CI: 0.86-1.23) VHA users. White VHA users have considerably higher suicide rates than Black and Hispanic VHA users, though the suicide rate among Hispanic VHA users, particularly those in rural settings, increased markedly over the period of observation.

CONCLUSIONS

Race significantly modifies the relationship between rural residence and suicide risk. Studies seeking to assess suicide disparity between rural and urban VHA user populations must include adjustment or stratification by race.

Influence of contextual factors on death by suicide in rural and urban settings

PURPOSE

To examine the association between contextual factors, represented by geographic and community health variables, and suicide among rural and urban Department of Veterans Affairs health care users (VA users).

METHODS

We performed a retrospective cohort study of 12,700,847 VA users between 2003 and 2017. We assigned contextual factors based on individuals' home address at the ZIP Code (area deprivation), county (sunlight exposure, altitude, and community health), and state level (firearm ownership), using publicly available data sources. We grouped contextual factors by quintiles or prespecified thresholds, depending on the nature of each variable. We obtained mortality data from the National Death Index. We measured the effect of living in a place with the highest versus lowest level of each contextual factor on odds of suicide using logistic regression, adjusting for individual compositional factors abstracted from VA electronic medical records data. We used random forest modeling to build prediction models for suicide based on contextual factors among rural and urban veterans.

FINDINGS

Almost all contextual factors we examined were significantly associated with suicide among rural and urban VA users, even after adjusting for individual compositional factors. However, no contextual variables were strong protective or risk factors (0.5<OR>2.0), and prediction models leveraging these contextual factors had poor accuracy among both rural (0.51, 95% CI: 0.48-0.54) and urban (0.53, 95% CI: 0.51-0.55) VA users.

CONCLUSIONS

A wide variety of contextual factors is significantly associated with suicide among rural and urban VA users. However, the factors we measured contributed very little to individual-level suicide risk.

Rural dwellers are less likely to survive cancer - An international review and meta-analysis

BACKGROUND

Existing research from several countries has suggested that rural-dwellers may have poorer cancer survival than urban-dwellers. However, to date, the global literature has not been systematically reviewed to determine whether a rural cancer survival disadvantage is a global phenomenon.

METHODS

Medline, CINAHL, and EMBASE were searched for studies comparing rural and urban cancer survival. At least two authors independently screened and selected studies. We included epidemiological studies comparing cancer survival between urban and rural residents (however defined) that also took socioeconomic status into account. A meta-analysis was conducted using 11 studies with binary rural:urban classifications to determine the magnitude and direction of the association between rurality and differences in cancer survival. The mechanisms for urban-rural cancer survival differences reported were narratively synthesised in all 39 studies.

FINDINGS

39 studies were included in this review. All were retrospective observational studies conducted in developed countries. Rural-dwellers were significantly more likely to die when they developed cancer compared to urban-dwellers (HR 1.05 (95% CI 1.02 - 1.07). Potential mechanisms were aggregated into an ecological model under the following themes: Patient Level Characteristics; Institutions; Community, Culture and Environment; Policy and Service Organization.

INTERPRETATION

Rural residents were 5% less likely to survive cancer. This effect was consistently observed across studies conducted in various geographical regions and using multiple definitions of rurality. High quality mixed-methods research is required to comprehensively evaluate the underlying factors. We have proposed an ecological model to provide a coherent framework for future explanatory research.

FUNDING

None.

Contribution of patient, physician, and environmental factors to demographic and health variation in colonoscopy follow-up for abnormal colorectal cancer screening test results

BACKGROUND

Patient, physician, and environmental factors were identified, and the authors examined the contribution of these factors to demographic and health variation in colonoscopy follow-up after a positive fecal occult blood test/fecal immunochemical test (FOBT/FIT) screening.

METHODS

In total, 76,243 FOBT/FIT-positive patients were identified from 120 Veterans Health Administration (VHA) facilities between August 16, 2009 and March 20, 2011 and were followed for 6 months. Patient demographic (race/ethnicity, sex, age, marital status) and health characteristics (comorbidities), physician characteristics (training level, whether primary care provider) and behaviors (inappropriate FOBT/FIT screening), and environmental factors (geographic access, facility type) were identified from VHA administrative records. Patient behaviors (refusal, private sector colonoscopy use) were estimated with statistical text mining conducted on clinic notes, and follow-up predictors and adjusted rates were estimated using hierarchical logistic regression.

RESULTS

Roughly 50% of individuals completed a colonoscopy at a VHA facility within 6 months. Age and comorbidity score were negatively associated with follow-up. Blacks were more likely to receive follow-up than whites. Environmental factors attenuated but did not fully account for these differences. Patient behaviors (refusal, private sector colonoscopy use) and physician behaviors (inappropriate screening) fully accounted for the small reverse race disparity and attenuated variation by age and comorbidity score. Patient behaviors (refusal and private sector colonoscopy use) contributed more to variation in follow-up rates than physician behaviors (inappropriate screening).

CONCLUSIONS

In the VHA, blacks are more likely to receive colonoscopy follow-up for positive FOBT/FIT results than whites, and follow-up rates markedly decline with advancing age and comorbidity burden. Patient and physician behaviors explain race variation in follow-up rates and contribute to variation by age and comorbidity burden. Cancer 2017;123:3502-12. Published 2017. This article is a US Government work and is in the public domain in the USA.

Comparing VA and Non-VA Quality of Care: A Systematic Review

BACKGROUND

The Veterans Affairs (VA) health care system aims to provide high-quality medical care to veterans in the USA, but the quality of VA care has recently drawn the concern of Congress. The objective of this study was to systematically review published evidence examining the quality of care provided at VA health care facilities compared to quality of care in other facilities and systems.

METHODS

Building on the search strategy and results of a prior systematic review, we searched MEDLINE (from January 1, 2005, to January 1, 2015) to identify relevant articles on the quality of care at VA facilities compared to non-VA facilities. Articles from the prior systematic review published from 2005 and onward were also included and re-abstracted. Studies were classified, analyzed, and summarized by the Institute of Medicine's quality dimensions.

RESULTS

Sixty-nine articles were identified (including 31 articles from the prior systematic review and 38 new articles) that address one or more Institute of Medicine quality dimensions: safety (34 articles), effectiveness (24 articles), efficiency (9 articles), patient-centeredness (5 articles), equity (4 articles), and timeliness (1 article). Studies of safety and effectiveness indicated generally better or equal performance, with some exceptions. Too few articles related to timeliness, equity, efficiency, and patient-centeredness were found from which to reliably draw conclusions about VA care related to these dimensions.

DISCUSSION

The VA often (but not always) performs better than or similarly to other systems of care with regard to the safety and effectiveness of care. Additional studies of quality of care in the VA are needed on all aspects of quality, but particularly with regard to timeliness, equity, efficiency, and patient-centeredness.

Screening and Follow-Up Monitoring for Substance Use in Primary Care: An Exploration of Rural-Urban Variations

BACKGROUND

Rates of substance use in rural areas are close to those of urban areas. While recent efforts have emphasized integrated care as a promising model for addressing workforce shortages in providing behavioral health services to those living in medically underserved regions, little is known on how substance use problems are addressed in rural primary care settings.

OBJECTIVE

To examine rural-urban variations in screening and monitoring primary care- based patients for substance use problems in a state-wide mental health integration program.

DESIGN

This was an observational study using patient registry.

SUBJECTS

The study included adult enrollees (n = 15,843) with a mental disorder from 133 participating community health clinics.

MAIN OUTCOMES

We measured whether a standardized substance use instrument was used to screen patients at treatment entry and to monitor symptoms at follow-up visits.

KEY RESULTS

While on average 73.6 % of patients were screened for substance use, follow-up on substance use problems after initial screening was low (41.4 %); clinics in small/isolated rural settings appeared to be the lowest (13.6 %). Patients who were treated for a mental disorder or substance abuse in the past and who showed greater psychiatric complexities were more likely to receive a screening, whereas patients of small, isolated rural clinics and those traveling longer distances to the care facility were least likely to receive follow-up monitoring for their substance use problems.

CONCLUSIONS

Despite the prevalent substance misuse among patients with mental disorders, opportunities to screen this high-risk population for substance use and provide a timely follow-up for those identified as at risk remained overlooked in both rural and urban areas. Rural residents continue to bear a disproportionate burden of substance use problems, with rural-urban disparities found to be most salient in providing the continuum of services for patients with substance use problems in primary care.

Dual use of VA and non-VA hospitals by Veterans with multiple hospitalizations

Background

Veterans who are hospitalized in both VA and non-VA hospitals within a short timespan may be at risk for fragmented or conflicting care. To determine the characteristics of these “dual users,” we analyzed administrative hospital discharge data for VA-enrolled veterans of any age in seven states, including any VA or non-VA hospitalizations they had in 2004–2007.

Method

For VA enrollees in Arizona, Iowa, Louisiana, Florida, South Carolina, Pennsylvania, or New York in 2007, we merged 2004–2007 discharge data for all VA hospitalizations and all non-VA hospitalizations listed in state health department or hospital association databases. For patients hospitalized in 2007, we compared those younger or older than 65 years who had one or multiple hospitalizations during the year, split into users of VA hospitals, non-VA hospitals, or both (“dual users”), on demographics, priority for VA care, travel times, principal diagnoses, co-morbidities, lengths of stay, and prior (2004–2006) hospitalizations, using chi-square analysis or ANOVA. Multiply hospitalized patients were compared with multinomial logistic regressions to predict non-VA and dual use. Payers for non-VA hospitalizations also were compared across groups.

Results

Of unique inpatients in 2007, 38 % of those 65 or older were hospitalized more than once during the year, as were 32 % of younger patients; 3 and 8 %, respectively, were dual users. Dual users averaged the most index-year (3.7) and prior (1.5) hospitalizations, split evenly between VA and non-VA. They also had higher rates of admission for circulatory diseases, symptoms/signs/ill-defined conditions, and injury and poisoning, and more admissions for multiple diagnostic categories; among younger patients they had the highest rate of mental disorders admissions. Higher income, non-rural residence, greater time to VA care, lower VA priority, prior non-VA hospitalization, no prior VA hospitalization, and several medical categories predicted greater non-VA use. Among younger patients, however, mental disorders predicted more dual use but less exclusively non-VA use. Dual users’ non-VA admissions were more likely than others’ to be covered by payers other than Medicare or commercial insurance.

Conclusions

Younger dual users require more medical and psychiatric treatment, and rely more on government funding sources. Effective care coordination for these inpatients might improve outcomes while reducing taxpayer burden.

Relationships between the importation, transmission, and nosocomial infections of methicillin-resistant Staphylococcus aureus: an observational study of 112 Veterans Affairs Medical Centers

BACKGROUND

The study of hospital methicillin-resistant Staphylococcus aureus (MRSA) epidemiology is complicated by its transmissibility. Our objective was to understand how MRSA importation and transmission influence MRSA nosocomial infections in Veterans Affairs Medical Centers (VAMCs).

METHODS

We performed hospital-level analyses of acute-care MRSA admission prevalence, acquisition rates, and incident nosocomial clinical culture (INCC) rates, each a surrogate measure of importation, transmission, and nosocomial infection, respectively. We studied 112 VAMCs from October 2007 through September 2010, after the start of a bundled intervention including active surveillance for MRSA. We analyzed data using generalized linear mixed models.

RESULTS

A total of 2.9 million surveillance tests were collected from 1.4 million patient admissions. Overall MRSA admission prevalence was 11.4%, acquisition was 5.2 per 1000 patient-days at risk, and INCC was 1.8 per 1000 patient-days at risk. A 10% increase in a hospital's average admission prevalence was associated with a 9.7% increase in its weekly acquisition rates (P < .001) and a 9.8% increase in its weekly INCC rates (P < .001). Significant decreases were observed in all 3 measures during the study period (P < .001). When INCC rates were stratified by nasal MRSA carriage at admission, a significant downward trend was observed only among those initially negative.

CONCLUSIONS

Measured associations between MRSA admission prevalence, acquisition rate, and INCC rate were consistent with the hypothesis that decreased acquisition led to decreased importation, which in turn further abated acquisition. The downward trend in INCC rate specifically among individuals with negative admission surveillance tests suggests that decreasing transmission contributed to lower rates of nosocomial MRSA infection.

Service utilization of veterans dually eligible for VA and Medicare fee-for-service: 1999-2004

OBJECTIVE

To examine care system choices for Veterans dually-eligible for VA and Medicare FFS following changes in VA eligibility policy, which expanded availability of VA health care services.

DATA SOURCES

VA and Medicare FFS enrollment and outpatient utilization databases in 1999 and 2004.

STUDY DESIGN

Multinomial logistic regression was used to examine odds of VA-only and Medicare-only utilization, relative to dual utilization, in 1999 and 2004. Observational cohort comprising a 5% random sample of dually-eligible Veterans: 73,721 in 1999 and 125,042 in 2004.

PRINCIPAL FINDINGS

From 1999 to 2004, persons with the highest HCC risk scores had decreasing odds of exclusive VA reliance (OR=0.26 in 1999 and 0.17 in 2004, p<0.05), but had increasing odds of exclusive Medicare reliance (OR=0.43 in 1999 and 0.56 in 2004, p<0.05).Persons in high VA priority groups had decreasing odds of exclusive VA reliance, as well as decreasing odds of exclusive Medicare reliance, indicating increasing odds of dual use. Newly eligible Veterans with the highest HCC risk scores had higher odds of dual system use, while newly eligible Black Veterans had lower odds of dual system use.

CONCLUSIONS

Veterans newly eligible for VA healthcare services, particularly those with the highest risk scores, had higher odds of dual system use compared to earlier eligibles. Providers should ensure coordination of care for Veterans who may be receiving care from multiple sources. Provisions of the Patient Protection and Affordable Care Act may help to ensure care coordination for persons receiving care from multiple systems.

Disparities in diabetes self-management and quality of care in rural versus urban veterans

BACKGROUND

There are distinct geographic differences in diabetes-related morbidity and mortality; however, data regarding self-management and clinical outcomes are limited. This study examined diabetes care among veterans residing in rural versus urban areas.

METHODS

A national data set was analyzed based on 10,570 veterans with type 2 diabetes. Residence was determined according to US census-based metropolitan statistical area. Primary outcomes were self-management behaviors (lifestyle and self-monitoring) and quality of care indicators (provider visits, laboratory monitoring and preventive measures). Multivariate analyses were done using STATA v10 to assess the independent effect of veteran residence on each outcome measure and to account for the complex survey design.

RESULTS

Among veterans with diabetes, 21.4% were rural residents. Compared to urban veterans, rural veterans had significantly lower education, less annual income and less received diabetes education (P = .002). The final regression model showed that daily foot self-check was the only self-management behavior significantly higher among rural veterans (odds ratio 1.36, 95% confidence interval 1.10-1.70). Provider-based quality of care was not significantly different between groups.

CONCLUSIONS

Diabetes self-foot care was significantly better among rural veterans than their urban counterparts, but quality of care was equivalent. This suggests that clinical diabetes care among veterans is uniform; however, greater efforts for patient education and support in diabetes self-management are needed to improve outcomes.

The effect of increased travel reimbursement rates on health care utilization in the VA

PURPOSE

The reimbursement rate that eligible veterans receive for travel to Department of Veterans Affairs (VA) facilities increased from 11 to 28.5 cents per mile on February 1, 2008. We examined the effect of this policy change on utilization of outpatient, inpatient, and pharmacy services, stratifying veterans based on distance from a VA facility.

METHODS

We compared health care utilization and costs on a sample of VA patients in the 10.5 months before the reimbursement rate increase and the 10.5 months after the reimbursement rate increase. Using a difference-in-difference technique, we ran multivariable logistic and count regressions for utilization and generalized linear models (GLM) for cost outcomes. Regressions were stratified based on urban and rural residence, as well as by distance thresholds.

FINDINGS

Our cohort contained 250,958 veterans, 76.7% (n = 192,559) of whom were eligible to receive a travel reimbursement. After the reimbursement rate increase, eligible veterans at all distances were 6.8% more likely to have an outpatient encounter and had 2.6% more outpatient encounters in the VA compared to those not eligible for the reimbursement (P< .001). Similar results were found for prescription fills at all distances, but inpatient encounters remained generally unaffected.

CONCLUSIONS

Our results suggest that this policy change was successful in increasing access to VA care for patients regardless of location of residence.

The impact of primary care dual-management on quality of care

BACKGROUND

Discontinuity is common in US healthcare. Patients access multiple systems of care and in the nation's largest integrated healthcare system, Veteran's Administration (VA) patients frequently use non-VA primary care providers. The impact of this "dual-management" on quality is unknown. The authors' objective was to identify dual-management and associations with markers of care quality for hypertension and associated conditions.

METHODS

Data was collected via surveys and chart reviews of primary care patients with hypertension from six VA clinics in Iowa and Minnesota. Clinical measures abstracted included the following: goal blood pressure (BP) and use of guideline-concordant therapy, low-density lipoprotein (LDL) cholesterol, hemoglobin A1C, and body mass index (BMI). Dual-management data was obtained through self-report.

RESULTS

Of 189 subjects (mean age = 66), 36% were dual-managed by non-VA providers. There was no difference in hypertension quality of care measures by dual-management status. A total of 51% were at BP goal and 58% were on guideline-concordant therapy. Dual-managed patients were more likely to use thiazide diuretics (43% vs 29%; P = .03) and angiotensin receptor blockers (13% vs 3%; P < .01), but less likely to use angiotensin-converting enzyme inhibitors (43% vs 61%; P = .02). There was no difference in LDL cholesterol (97.1 mg/dl vs 100.1 mg/dl; P = .55), hemoglobin A1C (7% vs 6%; P = .74), or BMI (29.8 vs 30.9; P = .40) for dual-managed versus VA managed patients, respectively.

CONCLUSIONS

Although dual-management may decrease continuity, VA/private sector dual-management did not impact quality of care, though some medication differences were observed. With the high prevalence of dual-management, future work should further address quality and evaluate redundancy of services.

Computing travel time when the exact address is unknown: a comparison of point and polygon ZIP code approximation methods

BACKGROUND

Travel time is an important metric of geographic access to health care. We compared strategies of estimating travel times when only subject ZIP code data were available.

RESULTS

Using simulated data from New Hampshire and Arizona, we estimated travel times to nearest cancer centers by using: 1) geometric centroid of ZIP code polygons as origins, 2) population centroids as origin, 3) service area rings around each cancer center, assigning subjects to rings by assuming they are evenly distributed within their ZIP code, 4) service area rings around each center, assuming the subjects follow the population distribution within the ZIP code. We used travel times based on street addresses as true values to validate estimates. Population-based methods have smaller errors than geometry-based methods. Within categories (geometry or population), centroid and service area methods have similar errors. Errors are smaller in urban areas than in rural areas.

CONCLUSION

Population-based methods are superior to the geometry-based methods, with the population centroid method appearing to be the best choice for estimating travel time. Estimates in rural areas are less reliable.