Abstract
Background
Racial, ethnic, and geographical health disparities have been widely documented in the United States. However, little attention has been directed towards disparities associated with integrated behavioral health and primary care services.
Methods
Access to behavioral health professionals among primary care physicians was examined using multinomial logistic regression analyses with 2010 National Plan and Provider Enumeration System, American Medical Association Physician Masterfile, and American Community Survey data.
Results
Primary care providers practicing in neighborhoods with higher percentages of African Americans and Hispanics were less likely to have geographically proximate behavioral health professionals. Primary care providers in rural areas were less likely to have geographically proximate behavioral health professionals.
Conclusion
Neighborhood-level factors are associated with access to nearby behavioral health and primary care. Additional behavioral health professionals are needed in racial/ ethnic minority neighborhoods and rural areas to provide access to behavioral health services, and to progress toward more integrated primary care.
Keywords: Racial disparities; behavioral health; primary care; colocation; rural health disparities, health policy
The identified unmet need for mental health and substance use services, hereafter referred to as behavioral health, increases every year in the United States, with 7.2 million individuals experiencing unmet mental health need in 2010, up from 4.3 million in 1997.1 A high proportion of individuals diagnosed with a behavioral health diagnosis do not receive any treatment, and those who do receive it primarily do so in general medical settings.2 Compared with the general population, persons of racial and ethnic minority groups, the uninsured, those living in low-income or rural areas and other underserved segments of the population experience even greater unmet need for behavioral health services.1–7 Many of the leading distal causes of mortality in the United States8—including tobacco use, poor diet, physical inactivity, and alcohol consumption—can benefit from behavioral health expertise.9
Individuals experiencing multiple chronic conditions are also less likely than others to have access to behavioral health services,3 despite the evidence that individuals with these chronic health conditions coupled with behavioral health comorbidities usually have poorer health outcomes and higher cost than those with chronic health conditions alone.10,11 To address the compounding effect of behavioral health and physical health comorbidities, an increasing body of evidence supports the strategy of integrating behavioral health providers into primary care settings, the first and only place of contact for many people with behavioral health conditions.9,10,12–16
Nearly 25% of behavioral health services are provided by primary care providers rather than behavioral health professionals (including anxiety and mood disorders),2 but primary care providers may often provide suboptimal behavioral health care.17,18 In response, mental health professionals such as psychologists, family therapists, psychiatrics, social workers, and licensed professional counselors have been integrated into many primary care settings and neighborhoods to address the multifaceted health needs of primary care patients in collaboration with primary care providers.
Integrated behavioral health and primary care includes the provision of collaborative, team-based behavioral health and primary care services in the same setting.9 Evidence suggests that the provision of integrated care can provide a multitude of benefits for patients and practitioners alike. The delivery of integrated care services has been associated with improved clinical outcomes,19,20 and improved patient21 and provider satisfaction.22,23 Although some level of collaboration can be achieved without physically co-locating behavioral health professionals in the same clinic as primary care professionals, fully integrated care models that achieve routine collaboration and team-based care begin with colocation of services. Primary care providers with geographic proximity (e.g., in the same neighborhood or within walking distance) to behavioral health services may be seen as a starting point for neighborhood-level integration of care. Neighborhood definitions have been extensively discussed in the literature,24,25 yet, to the authors’ knowledge, no widely-accepted definitive methodology exists to define neighborhoods most accurately.
Several studies that examine the general provision of medical services and those targeted towards behavioral health services have described the influence of geography and neighborhood-level factors on health.26–30 In fact, models of health care utilization have included geographic factors since the 1960s.31,32 A patient’s geographic location is not only associated with access to and utilization of services,30,33,34 but also with outcomes of care.35
However, despite the multitude of documented health disparities associated with unmet need for behavioral health services1–7 and the growing body of evidence supporting integrated primary care,19–23 little is known about disparities in access to integrated care. This study aims to help fill that gap by examining neighborhood demographic, housing, and socioeconomic conditions associated with presence of geographically proximate behavioral health professionals among medical primary care services.
Methods
Publicly available National Provider Identifier (NPI) data (2010) from the National Plan and Provider Enumeration System (NPPES) were used to identify physicians and behavioral health providers who bill third party payers for medical or behavioral health services.36 These data were merged with the 2010 American Medical Association (AMA) Physician Masterfile (2010)37 to identify physicians providing direct patient care in the United States. Primary care providers included individuals with specialties listed as family medicine, general practice, general internal medicine or pediatrics. Behavioral health providers included psychiatrists, psychologists, social workers, marriage and family therapists, and mental health counselors. Provider addresses were geocoded using Esri’s ArcGIS software38 matching to a NAVTEQ address database,39 to identify providers in close geographic proximity or in shared space. Primary care providers located within approximately one kilometer of a behavioral health provider were considered to have access to geographically-proximate behavioral health services.40 These data were merged with the American Community Survey (ACS) (2010, 5-year estimates),41 an annual nationally-representative survey administered by the United States Census Bureau,42 to incorporate population, housing, and other neighborhood level variables. ZIP Code Tabulation Areas (ZCTA) were used to merge primary care provider and ACS data.
A clustered multinomial logistic regression model (n=197,838 providers) was utilized to evaluate neighborhood-level factors associated with non-access to behavioral health among primary care providers (outcome variable). Sub-analyses were performed to examine specific factors associated with access to geographically-proximate care in primary care provider neighborhoods with a high percentage of minority populations and rural/ urban areas. Independent variables of interest include geography (rural versus urban) and percentage of minorities living in primary care provider site neighborhoods. Rurality is defined by non-metro counties using Rural-Urban Continuum (RUC) codes that indicate that the location is “more than 60 minutes or greater road travel to the closest edge of an Urbanized Area and more than 30 minutes or greater road travel to the closest edge of a large Urbanized Cluster of 10k population or greater.”43[p. 1] Minority neighborhoods are defined by percentage of African American and Hispanic individuals residing in a given ZCTA.
Results
Basic provider and provider neighborhood demographic characteristics appear in Table 1.
Table 1.
Average | Standard Deviation |
||
---|---|---|---|
Primary Care Provider Measures | |||
Geographic Proximitya |
Percentage located within 1 km of behavioral health professional |
145,438 (73.5%) |
|
Clinic Size | Primary Care Clinicians at clinic site | 20.59 | 47.46 |
Locationa | Northeast | 35,633 (18.0%) |
|
Midwest | 46,745 (23.6%) |
||
South | 68,0667 (34.4%) |
||
West | 47,393 (24.0%) |
||
Neighborhood Characteristics | |||
Ruralitya | Rural location | 27,757 (14.0%) |
|
Race and Ethnicity | Percentage African American | 12.93 | 18.03 |
Percentage Other Race | 8.15 | 9.23 | |
Percentage Hispanic | 14.80 | 18.53 | |
Socioeconomic Factors |
Percentage primary language other than English |
20.25 | 19.98 |
Percentage married | 48.65 | 11.55 | |
Percentage uninsured | 12.50 | 6.55 | |
Percentage over 25 years old with only high school education or GED equivalent |
23.83 | 9.39 | |
Percentage disabled | 12.10 | 4.75 | |
Percentage renter occupied housing | 40.21 | 19.21 | |
Percentage primary utilizing public transportation |
6.11 | 11.93 | |
Median household income (USD) | 55,811.92 | 23,466.01 |
Statistics are presented as a count and percentage for categorical variables
General results
For every 10% increase in the African American population within a neighborhood (compared with White), primary care physicians were 6.5% more likely to not have geographically-proximate behavioral health services (p<.001). For every 10% increase in the neighborhood Hispanic population (compared with non-Hispanic), primary care physicians were 8.5% more likely not to have geographically-proximate behavioral health services (p=.001).
Primary care physicians located in rural areas were 20.1% more likely not to have geographically-proximate behavioral health services, compared with urban-located physicians (p<.001).
For every 10% increase in the neighborhood uninsured population (compared with insured), primary care physicians were 14.6% more likely to not have geographically-proximate behavioral health services (p=.002).
General multinomial logistic regression results are found in Table 2.
Table 2.
Odds Ratio |
p-value | 95% Confidence Interval |
||
---|---|---|---|---|
Percentage African Americana | 1.065 | .000 | 1.041 | 1.090 |
Percentage Other Racea | 1.027 | .170 | 0.988 | 1.068 |
Percentage Hispanica | 1.085 | .001 | 1.035 | 1.138 |
Percentage Uninsureda | 1.146 | .002 | 1.052 | 1.249 |
Rural Location | 1.201 | .000 | 1.102 | 1.308 |
Number of Primary Care Physicians | 0.940 | .000 | 0.932 | 0.949 |
Percentage Primary Language non-Englisha | 0.864 | .000 | 0.819 | 0.912 |
Percentage Marrieda | 1.430 | .000 | 1.348 | 1.517 |
Percentage (over age 25) with only High School Education or GED Equivalenta |
1.338 | .000 | 1.270 | 1.409 |
Percentage any Disabilitya | 0.669 | .000 | 0.604 | 0.740 |
Percentage Renter Occupied Housinga | 0.786 | .000 | 0.757 | 0.817 |
Median Household Income | 1.000 | .000 | 1.000 | 1.000 |
Constant | 0.385 | .001 | 0.221 | 0.668 |
Unit of change equals 10%
Neighborhoods with greater than 25% minority population
Among providers located in communities with greater than a 25% African American population or a 25% Hispanic population (n=62,639), rural health communities were 45.8% more likely to not have geographically-proximate behavioral health services (p<.001). Additionally, for every 10% increase in the neighborhood uninsured populations (compared with the insured) primary care physicians were 29.9% more likely to not have geographically-proximate behavioral health services (p<.001).
Multinomial logistic regression results for neighborhoods with greater than 25% minority populations are found in Table 3.
Table 3.
Odds Ratio |
p-value | 95% Confidence Interval |
||
---|---|---|---|---|
Percentage African Americana | 1.098 | .004 | 1.030 | 1.170 |
Percentage Other Racea | 1.086 | .000 | 1.041 | 1.132 |
Percentage Hispanica | 1.147 | .000 | 1.068 | 1.231 |
Percentage Uninsureda | 1.299 | .000 | 1.127 | 1.497 |
Rural Location | 1.458 | .000 | 1.213 | 1.753 |
Primary Care Physicians on Site | 0.941 | .000 | 0.929 | 0.953 |
Percentage Primary Language non-Englisha | 0.815 | .000 | 0.752 | 0.884 |
Percentage Marrieda | 1.373 | .000 | 1.228 | 1.535 |
Percentage (over age 25) with only High School Education or GED Equivalenta |
1.270 | .000 | 1.126 | 1.432 |
Percentage any Disabilitya | 0.654 | .000 | 0.539 | 0.793 |
Percentage Renter Occupied Housinga | 0.749 | .000 | 0.704 | 0.797 |
Median Household Income | 1.000 | .000 | 1.000 | 1.000 |
Constant | 0.548 | .270 | 0.189 | 1.594 |
Unit of change equals 10%
Rural health communities
Among providers located in rural communities (n=27,759), for every 10% increase in the African American populations (compared with Whites) primary care physicians were 8.9% more likely to not have geographically-proximate behavioral health services (p=.001). In rural communities, insurance status was not significantly associated with geographically-proximate behavioral health services.
Multinomial logistic regression results for physicians located in rural communities are found in Table 4.
Table 4.
Odds Ratio |
p-value | 95% Confidence Interval |
||
---|---|---|---|---|
Percentage African Americana | 1.089 | .001 | 1.037 | 1.144 |
Percentage Other Racea | 0.874 | .000 | 0.822 | 0.928 |
Percentage Hispanica | 1.036 | .474 | 0.940 | 1.142 |
Percentage Uninsureda | 1.025 | .769 | 0.870 | 1.208 |
Primary Care Physicians on Site | 0.916 | .000 | 0.897 | 0.935 |
Percentage Primary Language non-Englisha | 1.023 | .709 | 0.908 | 1.152 |
Percentage Marrieda | 1.188 | .004 | 1.057 | 1.337 |
Percentage (over age 25) with only High School Education or GED Equivalenta |
1.296 | .000 | 1.171 | 1.434 |
Percentage any Disabilitya | 0.869 | .092 | 0.737 | 1.023 |
Percentage Renter Occupied Housinga | 0.746 | .000 | 0.681 | 0.817 |
Median Household Income | 1.000 | .023 | 1.000 | 1.000 |
Constant | 1.151 | .800 | 0.387 | 3.420 |
Unit of change equals 10%
Urban communities
Among providers located in urban communities (n=170,079), for every 10% increase in the African American populations (compared with Whites) primary care physicians were 5.8% more likely to not have geographically-proximate behavioral health services (p<.001). For every 10% increase in the neighborhood Hispanic population (compared with non-Hispanic), primary care physicians were 8.7% more likely to not have geographically-proximate behavioral health services (p=.002). Additionally, for every 10% increase in the neighborhood uninsured populations (compared with the insured) primary care physicians were 19.7% more likely to not have geographically-proximate behavioral health services (p<.001).
Multinomial logistic regression results for physicians located in urban communities are found in Table 5.
Table 5.
Odds Ratio |
p-value | 95% Confidence Interval |
||
---|---|---|---|---|
Percentage African Americana | 1.058 | .000 | 1.030 | 1.086 |
Percentage Other Racea | 1.081 | .002 | 1.030 | 1.134 |
Percentage Hispanica | 1.087 | .002 | 1.032 | 1.146 |
Percentage Uninsureda | 1.197 | .001 | 1.081 | 1.326 |
Primary Care Physicians on Site | 0.944 | .000 | 0.934 | 0.953 |
Percentage Primary Language non-Englisha | 0.832 | .000 | 0.783 | 0.884 |
Percentage Marrieda | 1.465 | .000 | 1.369 | 1.569 |
Percentage (over age 25) with only High School Education or GED Equivalenta |
1.368 | .000 | 1.287 | 1.455 |
Percentage any Disabilitya | 0.593 | .000 | 0.519 | 0.678 |
Percentage Renter Occupied Housinga | 0.791 | .000 | 0.757 | 0.826 |
Median Household Income | 1.000 | .000 | 1.000 | 1.000 |
Constant | 0.358 | .002 | 0.188 | 0.682 |
Unit of change equals 10%
Discussion
A broad range of disparities are associated with access to behavioral health services, including racial, ethnic, and geographical disparities.1–7 This national study focuses on neighborhood-level access to geographically-proximate behavioral health and primary care services.
Our findings suggest that primary care providers who practice in rural areas and/or communities with increased African American and Hispanic populations (compared with White) have fewer community resources to refer patients to behavioral health professionals. These findings are consistent with previous research on disparities in access to mental health services.29,33,44 When comparing rural and urban communities, neighborhood-level insurance status is only significantly associated with access to behavioral health professionals in urban settings. Therefore, primary care physicians located in urban communities with high percentages of minority and uninsured populations experience the greatest unmet need for geographically-proximate behavioral health professionals. These findings provide a neighborhood-level focus to target policy to reduce these disparities and to improve the health of underserved communities. To improve patient access to behavioral health services, behavioral health professionals must practice in these communities and/or primary care providers need the individual capacity to provide behavioral health services.
Research suggests several approaches to improving health care workforce capacity in underserved communities, though evidence supporting certain strategies is limited. Strong evidence suggests that individuals with rural origins and/or rural health career intent are associated with a future choice to practice in rural settings.45 Therefore educational programs may want to target recruitment and admission from these populations. Training programs or satellite campuses located in rural areas may also improve the rural health workforce. Inconsistent evidence suggests that health professionals of racial and ethnic minority backgrounds may be more likely to provide care in communities with large proportions of racial and ethnic minority populations.45–48 Continued research in this area is needed with special attention to behavioral health professionals.49
State and national policies also have potential to simultaneously improve the behavioral health workforce and the access to behavioral health services in primary care. For instance, loan forgiveness programs and scholarships targeted toward providers practicing in underserved communities could improve the primary care and behavioral health workforce in underserved areas.50 National Health Service Corps scholarships and loan repayment programs51 in addition to Minority Fellowship Programs funded through the Substance Abuse and Mental Health Services Administration52 explicitly place primary care and behavioral health professionals in underserved health professional shortage areas. Payment reform policies could support the provision of integrated primary care clinics that provide collaborative, team-based, same-day primary care services and behavioral health services in shared clinical space.51,53–55 Health care safety-net organizations and delivery systems such as federally qualified health centers (FQHCs) and accountable care organizations (ACOs) are encouraged to locate in such communities to reduce disparities faced in these communities. These types of practices and organizations have been found to pursue integrated services when there is high patient demand and access to behavioral health services in the community is scarce.56 However, primary care safety-net organizations such as federally-qualified community health centers have reported barriers to providing various behavioral health services, especially for their uninsured clients.57
Our findings also offer insight into neighborhood-level barriers to the achievement of optimal comprehensive health outcomes, including behavioral health. Despite the inability to directly examine patient level health outcomes in the present study, research suggests that people living in disadvantaged neighborhoods are more likely to experience poor health outcomes, including behavioral health.58–62 Availability and proximity of care in one’s own neighborhood can reduce travel distance, which has been shown to be an important factor associated with visit attendance.63,64 Future research could examine how access to neighborhood primary care and behavioral health services may or may not be associated with health and wellness outcomes.
Further research is needed to disentangle the continuum of geographically-proximate care, co-located care, and integrated services from the process and outcomes65 of care in each of these settings. It is well understood that mere physical proximity among providers is not sufficient for collaboration and team-based care, but may be one of the many starting points for integrated behavioral health and primary care efforts. Future research and classification efforts may provide further understanding into the factors that are necessary and/or sufficient for achieving fully integrated care in all community settings.
Limitations
This study includes a nationally representative sample of primary care providers and leverages the ability to geocode primary care provider location with respect to the geocoded locations of behavioral health professionals. However, several limitations should be considered when interpreting study results. First, the independent variable indicating geographically-proximate care only indicates if a behavioral health provider is located within approximately one kilometer radius of the primary care provider and does not indicate whether working relationships between the providers have been established. Despite the physical proximity of behavioral health and primary care providers, nothing is known about the actual collaborative nature of these professionals, or even if they are aware of each other’s presence in the community. This study assumes that if a behavioral health provider is located close to a primary care provider, the primary care provider will have improved opportunity to refer patients and increased probability that patients will follow-up with these referrals. This is not likely the true scenario faced by primary care providers, but due to data limitations this is the best measure of access to behavioral health and primary care services in this dataset.
Contextual variables of neighborhood-level factors were linked at the ZIP Code Tabulation Area (ZCTA) level, which is a conglomeration of adjacent ZIP codes based on census tract ZIP code commonality. The confines of these areas were designed under influence of U.S. census blocks, but do not perfectly follow census units. As a result, some of the ZCTAs cover strangely defined space and may not correspond to a true neighborhood designation of the primary care provider. Despite the modifiable areal unit problem, ZCTAs were the most appropriate, and available, units of measurement.66
The empirical unit of analysis for these findings is the practicing primary care provider. To identify practicing providers, both the NPPES file and AAMC Physician master file was used. However, it is possible that physicians that retired between data collection rounds may be included in the dataset. While this perspective provides useful insight into access to referral and potential for collaboration with geographically proximate behavioral health providers, it fails to account for patient-level factors (such as insurance status and access to transportation) integral to access to care. For instance, literature suggests that neighborhood-level factors such as a large percentage of minority populations or limited social cohesion (e.g., getting along with neighbors, depending on neighbors for emergencies) are associated with limited access to primary care services.67–69 These challenges are exacerbated by workforce training factors such as the shortage of medical graduates practicing in underserved areas such as medically underserved areas and provider shortage areas and the inadequate supply of primary care practitioners.70 In our study, neighborhoods lacking primary care providers were not evaluated. Therefore, given these documented disparities described above, our results likely underestimate the neighborhood level disparities associated with access to primary care and behavioral health services from the patient perspective.
Finally, neighborhood-level variables may or may not represent the true likelihood that patients can attend a clinic location in their neighborhood of residence. For example, physicians may only accept a few uninsured patients per year, despite being located in a neighborhood consisting of many uninsured individuals.
Conclusion
The present study examines access to neighborhood-level behavioral health and primary care services. Physicians practicing in neighborhoods with high percentages of African Americans, high percentages of Hispanic populations and in rural areas are more likely to not have access to geographically-proximate behavioral health professionals. This research is consistent with prior studies demonstrating increased unmet need for mental health services in such communities, and provides additional insight into access to integrated services. Findings suggest that targeted health policies and resources are required to encourage the provision of behavioral health services in underserved communities. Ideally, these services should be provided in fully integrated primary care clinics that include behavioral health to help defragment health care and address the multi-faceted needs of the nation’s population.
Contributor Information
Lynn M. VanderWielen, Eugene S. Farley, Jr. Health Policy Center and an Assistant Professor at the University of Colorado School of Medicine, Department of Family Medicine.
Emma C. Gilchrist, Eugene S. Farley, Jr. Health Policy Center, University of Colorado School of Medicine, Department of Family Medicine.
Molly A. Nowels, Eugene S. Farley, Jr. Health Policy Center, University of Colorado School of Medicine, Department of Family Medicine and Biostatistics Graduate Student in the Colorado School of Public Health, Department of Biostatistics and Informatics.
Stephen M. Petterson, Robert Graham Center, Washington, DC.
George Rust, Family Medicine and Community Health / Preventive Medicine at the Morehouse School of Medicine, where he also serves as Co-Director of the National Center for Primary Care.
Benjamin F. Miller, Eugene S. Farley, Jr. Health Policy Center and an Assistant Professor at the University of Colorado School of Medicine, Department of Family Medicine.
References
- 1.Roll JM, Kennedy J, Tran M, et al. Disparities in unmet need for mental health services in the United States, 1997–2010. Psychiatr Serv. 2013 Jan;64(1):80–82. doi: 10.1176/appi.ps.201200071. http://dx.doi.org/10.1176/appi.ps.201200071 PMid:23280460. [DOI] [PubMed] [Google Scholar]
- 2.Wang PS, Lane M, Olfson M, et al. Twelve-month use of mental health services in the United States: results from the National Comorbidity Survey Replication. Arch Gen Psychiatry. 2005 Jun;62(6):629–640. doi: 10.1001/archpsyc.62.6.629. http://dx.doi.org/10.1001/archpsyc.62.6.629 PMid:15939840. [DOI] [PubMed] [Google Scholar]
- 3.Bartels SJ, Coakley EH, Zubritsky C, et al. Improving access to geriatric mental health services: a randomized trial comparing treatment engagement with integrated versus enhanced referral care for depression, anxiety, and at-risk alcohol use. Am J Psychiatry. 2004 Aug;161(8):1455–1462. doi: 10.1176/appi.ajp.161.8.1455. http://dx.doi.org/10.1176/appi.ajp.161.8.1455 PMid:15285973. [DOI] [PubMed] [Google Scholar]
- 4.Wells K, Klap R, Koike A, et al. Ethnic disparities in unmet need for alcoholism, drug abuse, and mental health care. Am J Psychiatry. 2001 Dec;158(12):2027–2032. doi: 10.1176/appi.ajp.158.12.2027. http://dx.doi.org/10.1176/appi.ajp.158.12.2027 PMid:11729020. [DOI] [PubMed] [Google Scholar]
- 5.Chow JC-C, Jaffee K, Snowden L. Racial/ethnic disparities in the use of mental health services in poverty areas. Am J Public Health. 2003 May;93(5):792–797. doi: 10.2105/ajph.93.5.792. http://dx.doi.org/10.2105/AJPH.93.5.792 PMid:12721146 PMCid:PMC1447841. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Lasser KE, Himmelstein DU, Woolhandler S. Access to care, health status, and health disparities in the United States and Canada: results of a cross-national population-based survey. Am J Public Health. 2006 Jul;96(7):1300–1307. doi: 10.2105/AJPH.2004.059402. Epub 2006 May 30. http://dx.doi.org/10.2105/AJPH.2004.059402 PMid:16735628 PMCid:PMC1483879. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.American Psychological Association. A portrait of success and challenges—a progress report: 1997– 2005. Washington, DC: American Psychological Association; 2008. Available at: http://www.apa.org/pi/oema/resources/success-challenge.pdf. [Google Scholar]
- 8.Mokdad AH, Marks JS, Stroup DF, et al. Actual causes of death in the United States, 2000. JAMA. 2004 Mar 10;291(10):1238–1245. doi: 10.1001/jama.291.10.1238. http://dx.doi.org/10.1001/jama.291.10.1238 PMid:15010446. [DOI] [PubMed] [Google Scholar]
- 9.Peek CJ The National Integration Academy Council. Lexicon for behavioral health and primary care integration: concepts and definitions developed by expert consensus. Rockville, MD: Agency for Health care Research and Policy; 2013. [Google Scholar]
- 10.Naylor C, Parsonage M, McDaid D, et al. Long-term conditions and mental health: the cost of co-morbidities. London: The King’s Fund; 2012. Available at: http://www.kingsfund.org.uk/publications/long-term-conditions-and-mental-health. [Google Scholar]
- 11.Melek S, Norris D. Chronic conditions and comorbid psychological disorders. Seattle, WA: Milliman; 2008. PMCid:PMC2690686. [Google Scholar]
- 12.World Health Organization. Geneva, Switzerland: World Health Organization; 2008. Integrating mental health into primary care: a global perspective. Available at: http://www.who.int/mental_health/resources/mentalhealth_PHC_2008.pdf. [Google Scholar]
- 13.World Health Organization. Geneva, Switzerland: World Health Organization; 2001. The world health report 2001—mental health: new understanding, new hope. Available at: http://www.who.int/whr/2001/en/ [Google Scholar]
- 14.deGruy F. Mental health care in the primary care setting. In: Donaldson MS, Yordy KD, Lohr KN, et al., editors. Primary care: America’s health in a new era. Washington, DC: Institute of Medicine; 1996. [Google Scholar]
- 15.Talen MR, Valeras AB. Integrated behavioral health in primary care: evaluating the evidence, identifying the essentials. New York, NY: Springer Science & Business; 2013. http://dx.doi.org/10.1007/978-1-4614-6889-9 PMid:24261267. [Google Scholar]
- 16.Katon W, Unutzer J. Collaborative care models for depression: time to move from evidence to practice. Arch Intern Med. 2006 Nov 27;166(21):2304–2306. doi: 10.1001/archinte.166.21.2304. http://dx.doi.org/10.1001/archinte.166.21.2304 PMid:17130381. [DOI] [PubMed] [Google Scholar]
- 17.Wells KB, Schoenbaum M, Unutzer J, et al. Quality of care for depressed primary care patients under managed care. Arch Fam Med. 1999 Nov-Dec;8:529–536. doi: 10.1001/archfami.8.6.529. http://dx.doi.org/10.1001/archfami.8.6.529 PMid:10575393. [DOI] [PubMed] [Google Scholar]
- 18.Wells KB. Caring for depression. Cambridge, MA: Harvard University Press; 1996. [Google Scholar]
- 19.Unutzer J, Katon W, Callahan CM, et al. Collaborative care management of late-life depression in the primary care setting: a randomized controlled trial. JAMA. 2002 Dec 1;288(22):2836–2845. doi: 10.1001/jama.288.22.2836. http://dx.doi.org/10.1001/jama.288.22.2836 PMid:12472325. [DOI] [PubMed] [Google Scholar]
- 20.Gilbody S, Bower P, Fletcher J, et al. Collaborative care for depression: a cumulative meta-analysis and review of longer-term outcomes. Arch Intern Med. 2006 Nov;166(21):2314–2321. doi: 10.1001/archinte.166.21.2314. http://dx.doi.org/10.1001/archinte.166.21.2314 PMid:17130383. [DOI] [PubMed] [Google Scholar]
- 21.Price D, Beck A, Nimmer C, et al. The treatment of anxiety disorders in a primary care HMO setting. Psychiatr Q. 2000 Spring;71(1):31–45. doi: 10.1023/a:1004662600803. http://dx.doi.org/10.1023/A:1004662600803 PMid:10736815. [DOI] [PubMed] [Google Scholar]
- 22.Williams J, Shore SE, Foy JM. Co-location of mental health professionals in primary care settings: three North Carolina models. Clin Pediatr (Phila) 2006 Jul;45(6):537–543. doi: 10.1177/0009922806290608. http://dx.doi.org/10.1177/0009922806290608 PMid:16893859. [DOI] [PubMed] [Google Scholar]
- 23.Blount A. Integrated primary care: organizing the evidence. Families, Systems, & Health. 2003 Summer;21(2):121–134. http://dx.doi.org/10.1037/1091-7527.21.2.121. [Google Scholar]
- 24.Grubesic TH, Matisziw TC. On the use of ZIP codes and ZIP code tabulation areas (ZCTAs) for the spatial analysis of epidemiological data. Int J Health Geogr. 2006 Dec 13;5:58. doi: 10.1186/1476-072X-5-58. http://dx.doi.org/10.1186/1476-072X-5-58 PMid:17166283 PMCid:PMC1762013. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Matthews SA. The salience of neighborhood: some lessons from sociology. Am J Prev Med. 2008 Mar;34(3):257–259. doi: 10.1016/j.amepre.2007.12.001. http://dx.doi.org/10.1016/j.amepre.2007.12.001 PMid:18312814. [DOI] [PubMed] [Google Scholar]
- 26.Kim G, Aguado Loi CX, Chiriboga DA, et al. Limited English proficiency as a barrier to mental health service use: A study of Latino and Asian immigrants with psychiatric disorders. J Psychiatr Res. 2011 Jan;45(1):104–110. doi: 10.1016/j.jpsychires.2010.04.031. Epub 2010 May 26. http://dx.doi.org/10.1016/j.jpsychires.2010.04.031 PMid:20537658. [DOI] [PubMed] [Google Scholar]
- 27.Kim G, Jang Y, Chiriboga DA, et al. Factors associated with mental health service use in Latino and Asian immigrant elders. Aging Ment Health. 2010 Jul;14(5):535–542. doi: 10.1080/13607860903311758. http://dx.doi.org/10.1080/13607860903311758 PMid:20496182. [DOI] [PubMed] [Google Scholar]
- 28.Semrad TJ, Tancredi DJ, Baldwin LM, et al. Geographic variation of racial/ethnic disparities in colorectal cancer testing among Medicare enrollees. Cancer. 2011 Apr 15;117(8):1755–1763. doi: 10.1002/cncr.25668. Epub 2011 Jan 10. http://dx.doi.org/10.1002/cncr.25668 PMid:21472723. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Cummings JR, Wen H, Ko M, et al. Race/ethnicity and geographic access to Medicaid substance use disorder treatment facilities in the United States. JAMA Psychiatry. 2014 Feb;71(2):190–196. doi: 10.1001/jamapsychiatry.2013.3575. http://dx.doi.org/10.1001/jamapsychiatry.2013.3575 PMid:24369387 PMCid:PMC4039494. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Guerrero EG, Kao D. Racial/ethnic minority and low-income hotspots and their geographic proximity to integrated care providers. Subst Abuse Treat Prev Policy. 2013 Sep 23;8:34. doi: 10.1186/1747-597X-8-34. http://dx.doi.org/10.1186/1747-597X-8-34 PMid:24059252 PMCid:PMC3848872. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Andersen R. A behavioral model of families’ use of health services. J Human Resources. 1972 Winter;7(1):125–127. http://dx.doi.org/10.2307/145064. [Google Scholar]
- 32.Andersen RM. Revisiting the behavioral model and access to medical care: does it matter? J Health Soc Behav. 1995 Mar;36(1):1–10. http://dx.doi.org/10.2307/2137284 PMid:7738325. [PubMed] [Google Scholar]
- 33.Dinwiddie GY, Gaskin DJ, Chan KS, et al. Residential segregation, geographic proximity and type of services used: Evidence for racial/ethnic disparities in mental health. Soc Sci Med. 2013 Mar;80:67–75. doi: 10.1016/j.socscimed.2012.11.024. Epub 2012 Dec 11. http://dx.doi.org/10.1016/j.socscimed.2012.11.024 PMid:23312305 PMCid:PMC4119020. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Kim G, Parton JM, DeCoster J, et al. Regional variation of racial disparities in mental health service use among older adults. Gerontologist. 2013 Aug;53(4):618–626. doi: 10.1093/geront/gns107. Epub 2012 Aug 2. http://dx.doi.org/10.1093/geront/gns107 PMid:22859437 PMCid:PMC3709841. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Graves BA. Integrative literature review: a review of literature related to geographical information systems, health care access, and health outcomes. Perspect Health Inf Manag. 2008;5:11. Epub 2008 Jul. PMid:18698429 PMCid:PMC2500173. [PMC free article] [PubMed] [Google Scholar]
- 36.National Plan and Provider Enumeration System. National provider identifier. Fargo, ND: 2010. [Google Scholar]
- 37.American Medical Association. Physician masterfile. Chicago, IL: American Medical Association; 2010. Available at: http://www.ama-assn.org/ama/pub/about-ama/physician-data-resources/physician-masterfile.page? [Google Scholar]
- 38.Environmental Systems Resource Institute. ArcGIS Desktop: Release 10. Redlands, CA: Environmental Systems Resource Institute; 2014. [Google Scholar]
- 39.Environmental Systems Resource Institute. NAVTEQ 2012 street map premium release 2. Redlands, CA: Environmental Systems Resource Institute; 2012. [Google Scholar]
- 40.Miller BF, Petterson S, Levey SMB, et al. Primary care, behavioral health, provider colocation, and rurality. J Am Board Fam Med. 2014 May-Jun;27(3):367–374. doi: 10.3122/jabfm.2014.03.130260. http://dx.doi.org/10.3122/jabfm.2014.03.130260 PMid:24808115. [DOI] [PubMed] [Google Scholar]
- 41.United Stated Census Bureau. American Community Survey: 2010 Data Release. Washington, DC: United Stated Census Bureau; 2011. [Google Scholar]
- 42.United States Census Bureau. American Community Survey information guide. Washington, DC: United States Census Bureau; 2013. Available at: http://www.census.gov/acs/www/Downloads/ACS_Information_Guide.pdf. [Google Scholar]
- 43.WWAMI Rural Health Research Center. RUCA data: travel distance and time, remote, isolated, and frontier. Seattle, WA: WWAMI Rural Health Research Center; 2014. Available at: http://depts.washington.edu/uwruca/ruca-travel-dist.php. [Google Scholar]
- 44.Hart JT. The inverse care law. Lancet. 1971 Feb 27;1(7696):405–412. doi: 10.1016/s0140-6736(71)92410-x. http://dx.doi.org/10.1016/S0140-6736(71)92410-X. [DOI] [PubMed] [Google Scholar]
- 45.Wilson N, Couper I, De Vries E, et al. A critical review of interventions to redress the inequitable distribution of health care professionals to rural and remote areas. Rural Remote Health. 2009 Apr-Jun;9(2):1060. Epub 2009 Jun 12. PMid:19530891. [PubMed] [Google Scholar]
- 46.Betancourt JR, Green AR, Carrillo JE, et al. Defining cultural competence: a practical framework for addressing racial/ethnic disparities in health and health care. Public Health Rep. 2003 Jul-Aug;118(4):293–2302. doi: 10.1016/S0033-3549(04)50253-4. http://dx.doi.org/10.1093/phr/118.4.293 http://dx.doi.org/10.1016/S0033-3549(04)50253-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Cohen JJ, Gabriel BA, Terrell C. The case for diversity in the health care workforce. Health Aff (Millwood) 2002 Sep-Oct;21(5):90–102. doi: 10.1377/hlthaff.21.5.90. http://dx.doi.org/10.1377/hlthaff.21.5.90. [DOI] [PubMed] [Google Scholar]
- 48.Brach C, Fraserirector I. Can cultural competency reduce racial and ethnic health disparities? A review and conceptual model. Med Care Res Rev. 2000;57(Suppl 1):181–217. doi: 10.1177/1077558700057001S09. http://dx.doi.org/10.1177/107755800773743655 http://dx.doi.org/10.1177/1077558700574009 PMid:11092163. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Bird DC, Dempsey P, Hartley D. Addressing mental health workforce needs in underserved rural areas: accomplishments and challenges. Portland, ME: Maine Rural Health Research Center, Edmund S. Muskie School of Public Services, University of Southern Maine; 2001. Available at: https://muskie.usm.maine.edu/Publications/rural/wp23.pdf. [Google Scholar]
- 50.Geletko KW, Brooks RG, Hunt A, et al. State scholarship and loan forgiveness programs in the United States: forgotten driver of access to healthcare in underserved areas. Health. 2014 Aug;6(15):1994–2003. http://dx.doi.org/10.4236/health.2014.615234. [Google Scholar]
- 51.Miller BF, Petterson S, Burke BT, et al. Proximity of providers: Colocating behavioral health and primary care and the prospects for an integrated workforce. Am Psychol. 2014 May-Jun;69(4):443–451. doi: 10.1037/a0036093. http://dx.doi.org/10.1037/a0036093 PMid:24820692. [DOI] [PubMed] [Google Scholar]
- 52.Jones JM, Austin-Dailey AT. The Minority Fellowship Program: A 30-year legacy of training psychologists of color. Cultur Divers Ethnic Minor Psychol. 2009 Oct;15(4):388–399. doi: 10.1037/a0017558. http://dx.doi.org/10.1037/a0017558 PMid:19916673. [DOI] [PubMed] [Google Scholar]
- 53.Thomas KC, Ellis AR, Konrad TR, et al. North Carolina’s mental health workforce: unmet need, maldistribution, and no quick fixes. N C Med J. 2012 May-Jun;73(3):161–168. PMid:22779145. [PubMed] [Google Scholar]
- 54.Struijs JN, Baan CA. Integrating care through bundled payments—lessons from the Netherlands. N Engl J Med. 2011 Mar 17;364(11):990–991. doi: 10.1056/NEJMp1011849. http://dx.doi.org/10.1056/NEJMp1011849 PMid:21410368. [DOI] [PubMed] [Google Scholar]
- 55.Mechanic D. Seizing opportunities under the Affordable Care Act for transforming the mental and behavioral health system. Health Aff (Millwood) 2012 Feb;31(2):376–382. doi: 10.1377/hlthaff.2011.0623. http://dx.doi.org/10.1377/hlthaff.2011.0623 PMid:22323168. [DOI] [PubMed] [Google Scholar]
- 56.Lewis VA, Colla CH, Tierney K, et al. Few ACOs pursue innovative models that integrate care for mental illness and substance abuse with primary care. Health Aff (Millwood) 2014 Oct;33(10):1808–1816. doi: 10.1377/hlthaff.2014.0353. http://dx.doi.org/10.1377/hlthaff.2014.0353 PMid:25288427. [DOI] [PubMed] [Google Scholar]
- 57.Rust G, Daniels E, Satcher D, et al. Ability of community health centers to obtain mental health services for uninsured patients. JAMA. 2005 Feb 2;293(5):550–556. doi: 10.1001/jama.293.5.554-c. http://dx.doi.org/10.1001/jama.293.5.554-c PMid:15687308. [DOI] [PubMed] [Google Scholar]
- 58.Ross CE, Mirowsky J. Neighborhood disadvantage, disorder, and health. J Health Soc Behav. 2001 Sep;42(3):258–276. http://dx.doi.org/10.2307/3090214 PMid:11668773. [PubMed] [Google Scholar]
- 59.Aneshensel CS, Sucoff CA. The neighborhood context of adolescent mental health. J Health Soc Behav. 1996 Dec;37(4):293–310. http://dx.doi.org/10.2307/2137258 PMid:8997886. [PubMed] [Google Scholar]
- 60.De Jesus M, Puleo E, Shelton RC, et al. Associations between perceived social environment and neighborhood safety: Health implications. Health Place. 2010 Sep;16(5):1007–1013. doi: 10.1016/j.healthplace.2010.06.005. Epub 2010 Jun 20. http://dx.doi.org/10.1016/j.healthplace.2010.06.005 PMid:20598624 PMCid:PMC3229178. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 61.Mohnen SM, Groenewegen PP, Völker B, et al. Neighborhood social capital and individual health. Soc Sci Med. 2011 Mar;72(5):660–667. doi: 10.1016/j.socscimed.2010.12.004. Epub 2010 Dec 16. http://dx.doi.org/10.1016/j.socscimed.2010.12.004 PMid:21251743. [DOI] [PubMed] [Google Scholar]
- 62.Gary-Webb TL, Baptiste-Roberts K, Pham L, et al. Neighborhood socioeconomic status, depression, and health status in the Look AHEAD (Action for Health in Diabetes) study. BMC Public Health. 2011 May 19;11:349. doi: 10.1186/1471-2458-11-349. http://dx.doi.org/10.1186/1471-2458-11-349 PMid:22182286 PMCid:PMC3111582. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 63.Ballantyne M, Stevens B, Guttmann A, et al. Maternal and infant predictors of attendance at Neonatal Follow-Up programmes. Child Care Health Dev. 2014 Mar;40(2):250–258. doi: 10.1111/cch.12015. Epub 2013 Jan 7. http://dx.doi.org/10.1111/cch.12015 PMid:23294101. [DOI] [PubMed] [Google Scholar]
- 64.Harmon SL, Conaway M, Sinkin RA, et al. Factors associated with neonatal intensive care follow-up appointment compliance. Clinical Pediatr (Phila) 2013 May;52(5):389–396. doi: 10.1177/0009922813477237. Epub 2013 Feb 19. http://dx.doi.org/10.1177/0009922813477237 PMid:23426231. [DOI] [PubMed] [Google Scholar]
- 65.Donabedian A. Evaluating the quality of medical care. Milbank Q. 2005 Dec;83(4):691–729. doi: 10.1111/j.1468-0009.2005.00397.x. http://dx.doi.org/10.1111/j.1468-0009.2005.00397.x PMid:16279964 PMCid:PMC2690293. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66.Fotheringham AS, Wong DW. The modifiable areal unit problem in multivariate statistical analysis. Environment Planning A. 1991;23(7):1025–1044. http://dx.doi.org/10.1068/a231025. [Google Scholar]
- 67.Williams DR, Collins C. Racial residential segregation: a fundamental cause of racial disparities in health. Public health Rep. 2001 Sep-Oct;116(5):404–416. doi: 10.1093/phr/116.5.404. http://dx.doi.org/10.1093/phr/116.5.404 http://dx.doi.org/10.1016/S0033-3549(04)50068-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 68.Hardt NS, Muhamed S, Das R, et al. Neighborhood-level hot spot maps to inform delivery of primary care and allocation of social resources. Perm J. 2013 Winter;17(1):4–9. doi: 10.7812/TPP/12-090. http://dx.doi.org/10.7812/TPP/12-090 PMid:23596361 PMCid:PMC3627788. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 69.Ryvicker M, Gallo WT, Fahs MC. Environmental factors associated with primary care access among urban older adults. Soc Sci Med. 2012 Sep;75(5):914–921. doi: 10.1016/j.socscimed.2012.04.029. Epub 2012 May 23. http://dx.doi.org/10.1016/j.socscimed.2012.04.029 PMid:22682664 PMCid:PMC3383917. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 70.Chen C, Xierali I, Piwnica-Worms K, et al. The redistribution of graduate medical education positions in 2005 failed to boost primary care or rural training. Health Aff (Millwood) 2013 Jan;32(1):102–110. doi: 10.1377/hlthaff.2012.0032. http://dx.doi.org/10.1377/hlthaff.2012.0032 PMid:23297277. [DOI] [PubMed] [Google Scholar]