Medical Home Effects on Enrollees With Mental and Physical Illness

Medical home enrollment had mixed effects on acute care use and a large effect on outpatient care use. Effects on expenditures varied by mental illness.

ABSTRACTObjectives: To assess the effect of medical home enrollment on acute care use and healthcare spending among Medicaid beneficiaries with mental and physical illness.

Study Design: Retrospective cohort analysis of administrative data.

Methods: We used 2007-2010 Medicaid claims and state psychiatric hospital data from a sample of 83,819 individuals diagnosed with schizophrenia or depression and at least 1 comorbid physical condition. We performed fixed-effects regression analysis at the person-month level to examine the effect of medical home enrollment on the probabilities of emergency department (ED) use, inpatient admission, and outpatient care use and on amount of Medicaid spending.

Results: Medical home enrollment had no effect on ED use in either cohort and was associated with a lower probability of inpatient admission in the depression cohort (P <.05). Medical home enrollees in both cohorts experienced an increase in the probability of having any outpatient visits (P <.05). Medical home enrollment was associated with an increase in mean monthly spending among those with schizophrenia ($65.8; P <.05) and a decrease among those with depression (—$66.4; P <.05).

Conclusions: Among Medicaid beneficiaries with comorbid mental and physical illness, medical home enrollment appears to increase outpatient healthcare use and has mixed effects on acute care use. For individuals in this population who previously had no engagement with the healthcare system, use of the medical home model may represent an investment in providing improved access to needed outpatient services with cost savings potential for beneficiaries with depression.

Am J Manag Care. 2020;26(5):218-223. https://doi.org/10.37765/ajmc.2020.43153Takeaway Points

  • This study extends existing work examining medical home effects on utilization and spending among people with mental illness by analyzing administrative data on individuals with mental and physical illnesses.
  • Compared with nonenrollees, medical home enrollees with schizophrenia or depression had similar probability of emergency department use, but those with depression had lower probability of inpatient admission.
  • Medical home enrollees had a greater probability of outpatient visits. Use of the medical home model among individuals with mental and physical illness may lead to greater access to outpatient services. Among individuals with depression, associated cost increases may be offset by lower inpatient utilization.

Individuals with comorbid physical and mental illnesses tend to have higher rates of emergency department (ED) utilization and hospital admission, as well as greater overall healthcare expenditures, compared with individuals who have chronic illness without comorbid mental illness.1-4 Greater use of costly acute care (ie, ED utilization and inpatient admissions) among those with mental illness and comorbid physical conditions may result from their decreased likelihood of receiving primary care services. Individuals with severe mental illness have low rates of primary care use and report experiencing a number of barriers to accessing primary care, including lack of transportation, difficulty scheduling appointments in a timely manner, and perceived provider bias.5-7

Reflecting these barriers and diminished access to primary care, those with mental illness have been shown to receive preventive services, including screening services, at lower rates than individuals without mental illness.5,8 Without access to screening services, individuals with mental illness may experience delayed detection of previously undiagnosed chronic conditions and other serious illness (eg, cancer). While undetected, these comorbid chronic conditions are likely to remain untreated and serious illness will continue to progress, presenting later in a more advanced stage.9 Even when comorbid physical illness is diagnosed and treated, care for such conditions among those with serious mental illness is often poorly coordinated across primary care and specialty providers.10-12 For individuals with chronic conditions, greater fragmentation of care is associated with increased total expenditures.13

For individuals with serious mental illness, the behavioral health home model, in which behavioral health organizations connect patients to needed medical care and take responsibility for coordinating and managing care, has been shown to improve chronic condition management and reduce acute care utilization and costs.14-16 For those with multiple chronic conditions, including mental illness, the primary care—based medical home model, which tasks primary care providers with responsibility for care coordination and management, also has the potential to increase primary care access and improve chronic condition management.17,18 However, for the subpopulation of individuals with both mental and physical chronic conditions, little is known about the effect of the primary care—based medical home model.

Features of the medical home model that may benefit individuals with multiple chronic conditions and mental illness include reimbursement for care coordination, use of a team-based treatment approach, and same-day appointments with expanded hours of operation.19 Existing research on the medical home model suggests that it can effectively increase primary care access and reduce ED and inpatient utilization among individuals with mental illness.20-22 Evidence on the effect of medical home enrollment on expenditures is mixed.23-25 Among those with mental illness, any reductions in acute care use may be offset by increases in utilization of primary and specialty care services.21

The purpose of the present study is to explore the relationship between medical home enrollment and acute care use and total expenditures among those with comorbid mental and physical illness using the experience of North Carolina’s Medicaid medical home program. Established in 1998, the Community Care of North Carolina (CCNC) program uses a model in which participating primary care providers across the state of North Carolina receive a per-member per-month (PMPM) fee, in the amount of $2.50 during the study time period, to serve as a medical home for Medicaid beneficiaries.26 Primary care practices in the CCNC program joined together to form regional networks intended to collaboratively improve care coordination and quality of care for Medicaid beneficiaries using data-driven decision making.26 All North Carolina Medicaid beneficiaries were given the opportunity to enroll voluntarily in the CCNC program upon Medicaid enrollment or by switching to a medical home practice, and participating primary care providers received a PMPM fee for Medicaid beneficiaries who chose to enroll.

Using linked Medicaid claims and administrative data from the state psychiatric hospitals for Medicaid beneficiaries who enrolled in a CCNC medical home and comparable beneficiaries who chose not to enroll, we examined the effect of enrollment on ED use and inpatient admissions, as well as on total expenditures, among individuals with comorbid mental and physical illness. We anticipated that medical home enrollees would have improved primary care access, in turn reducing enrollees’ acute care utilization by improving management of their chronic conditions. Any reductions in acute care utilization could lead to lower total expenditures but might be offset by greater use of primary care and other outpatient services. Additionally, improved chronic disease management could involve greater utilization of specialty medical care. The net effect of medical home enrollment on total expenditures would therefore depend on whether or not any increases in use of primary care and specialty services were offset by reductions in acute care utilization.

METHODS

We conducted the study using data from the North Carolina Integrated Data for Researchers data set, which integrates multiple sources of information on the service utilization of individuals with severe mental illness in North Carolina.27 For the purposes of the present study, we restricted the sample to include only Medicaid beneficiaries who were 18 years and older. Because of the focus on Medicaid expenditures, months in which an individual was not enrolled in Medicaid were excluded. We excluded individuals who were dually eligible for Medicare because payment data on Medicare-covered services such as prescription drugs were not available. We restricted the sample to individuals who met the following criteria: (1) at least 1 inpatient or at least 2 outpatient claims with diagnoses of schizophrenia during the entire study period, or at least 1 inpatient or at least 2 outpatient claims with diagnoses of major depressive disorder during the study period, and (2) 1 or more inpatient or outpatient claims with a diagnosis of hypertension, hyperlipidemia, seizure disorder, chronic obstructive pulmonary disease (COPD), diabetes, or asthma during the study period. Study data included claims from July 1, 2007, to June 30, 2010.

We used a fixed-effects ordinary least squares (OLS) regression approach to assess the effect of medical home enrollment on our outcomes of interest, with the person-month as the unit of analysis and fixed effects at the person level. Our models were identified by changes in individuals’ medical home status over the study period, which occurred for more than half (57%) of our sample. This approach allowed us to control for any observable and unobservable individual-level characteristics that do not vary over time, including medical profile and family health history, which should reduce any bias from nonrandom selection into medical homes. Our key independent variable was a dichotomous indicator for medical home enrollment. As our dependent variables, we used dichotomous indicators of whether there were any ED visits, any Medicaid-paid or state psychiatric facility inpatient stays, and any Medicaid-paid outpatient visits in the month, as well as a continuous measure of total Medicaid expenditures in the month. We also examined the use of any Medicaid-paid inpatient care without inclusion of state psychiatric facility inpatient stays and found virtually identical results to those with the broader measure of inpatient use (results not reported). We constructed the total expenditures measure by summing Medicaid payments for inpatient, outpatient, and ED services; this measure excludes expenditures on certain types of services such as pharmaceuticals and laboratory tests, which were not available for this study. Our measure of total expenditures also does not include either state-only expenditures on psychiatric hospitals or the $2.50 PMPM fee that medical home providers received for enrolled beneficiaries.

For all dependent variables, we used OLS models with standard errors clustered at the individual level to account for correlation of the error term within an individual. For the total expenditures dependent variable, we performed a sensitivity analysis in which we used generalized estimating equation (GEE) models with a log link, gamma distribution, and exchangeable correlation structure to account for the right-skewed distribution of expenditures. In the GEE models, we included demographic characteristics, number of comorbid chronic conditions, and indicators for comorbid chronic conditions because these models cannot accommodate individual fixed effects. We compared the fit of the OLS and GEE spending models using the root mean squared error (RMSE), preferring the model with the lower RMSE. We anticipated that the effect of medical home enrollment on our outcomes of interest would differ for individuals with schizophrenia and individuals with depression, due to the differing clinical needs and access to care of each population. To account for these expected differences, we stratified all models by type of mental illness; individuals diagnosed with both schizophrenia and depression were included in the schizophrenia cohort.

RESULTS

Our sample included a total of 83,819 individuals with schizophrenia and/or depression, contributing 1,960,671 person-months; 60,638 individuals in the sample were ever enrolled in a medical home during the study period. Compared with those who were never enrolled in a medical home during the study period, medical home enrollees were more likely to be black, were less likely to be Latino or male, and tended to be younger (Table 1). The prevalence of depression was higher in the medical home enrollee cohort than in the nonenrollee cohort (91.7% vs 86.0%; P <.05), whereas a slightly greater percentage of those never enrolled in a medical home had schizophrenia (21.0% vs 15.8%; P <.05). The prevalence of diabetes, hypertension, and COPD was slightly higher among nonenrollees, whereas medical home enrollees exhibited a higher prevalence of asthma. The proportions of individuals with hyperlipidemia and seizure disorder were similar between the 2 groups.

As shown in Table 2, medical home enrollee and nonenrollee person-months among those with schizophrenia did not significantly differ with respect to unadjusted mean monthly expenditures. However, among those with depression, medical home enrollee person-months had lower unadjusted mean monthly expenditures ($395.3 vs $427.4; P <.05). The unadjusted proportions of person-months with any ED visits and Medicaid-paid or state psychiatric facility inpatient visits were slightly lower among medical home enrollees with schizophrenia and among those with depression. State psychiatric facility use was a very small fraction of overall inpatient hospital use, as expected among a population covered by Medicaid. State psychiatric facility inpatient visits represented a low percentage of inpatient stays: 14.7% for the schizophrenia cohort and 1.6% for the depression cohort (results not shown). The unadjusted percentage of person-months with any outpatient visits was higher among medical home enrollees in both diagnosis cohorts.

Among person-months from adults with schizophrenia, medical home enrollment had no significant effect on ED use in the month, controlling for time-invariant individual characteristics (Table 3). We also observed no significant effect of medical home enrollment on the probability of ED use among person-months from adults with depression. In the cohort with schizophrenia, medical home enrollment had no effect on the probability of having any Medicaid-paid inpatient admissions or state psychiatric facility inpatient admissions in the month. In the cohort with depression, medical home enrollment was associated with a decrease of 1.2 percentage points in the probability of having any Medicaid-paid or state psychiatric facility inpatient admissions in the month (P <.05). Relative to the proportion of nonenrollee person-months with any Medicaid-paid or state psychiatric facility inpatient admissions among the depression cohort (0.06), this average marginal effect represents a relative decrease of 19.8% in the probability of such inpatient admissions.

We found that medical home enrollment was associated with an increase of 8.7 percentage points in the probability of having any outpatient visits in the month among the schizophrenia cohort (P <.05). This average marginal effect represents a 15.1% increase in the probability of outpatient visits, relative to the comparison group mean of 0.58. In the cohort with depression, medical home enrollment was associated with an increase of 14.0 percentage points in the probability of having any outpatient visits in the month (P <.05). This average marginal effect represents a 26.4% increase in the probability of outpatient visits, relative to the comparison group mean of 0.53.

We found that among the cohort with schizophrenia, being in a medical home was associated with an overall increase of $65.8 in expected total Medicaid expenditures in the month (P <.05). This average marginal effect is equivalent to a 12.4% increase in spending, relative to the comparison group mean ($532.5). Among the cohort with depression, medical home enrollment was associated with a decrease of $66.4 in expected total Medicaid expenditures in the month (P <.05), a 13.3% decrease from the comparison group mean ($497.4). In the GEE models, we obtained results that were similar in direction of effect, average marginal effect magnitude, and statistical significance (results available upon request). However, because the GEE models had a higher RMSE than the OLS models with individual fixed effects, indicating a poorer fit, we selected the OLS fixed-effect models.

DISCUSSION

In this study, we found that medical home enrollment had minimal effects on acute care use. We observed no effect on the probability of ED use among adults with schizophrenia and adults with depression. In comparison, prior studies found that medical home enrollment was associated with small decreases in ED use among North Carolina Medicaid beneficiaries with schizophrenia and North Carolina Medicaid beneficiaries with depression, although their samples were not restricted to individuals with comorbid physical illness.20,21 The fact that we observed no effect on ED use may reflect the greater clinical complexity that medical home providers face in caring for patients with both severe mental illness and at least 1 chronic physical condition, which could make it more difficult to mitigate the need for emergency care.

Our finding of no medical home enrollment effect on Medicaid-paid or state psychiatric facility inpatient admissions among those with schizophrenia may similarly reflect this clinical complexity. Other work evaluating the effectiveness of the medical home model in reducing acute care use has also found little to no effect on such outcomes. For example, in a study of clinics serving Medicaid beneficiaries in Louisiana, Cole and colleagues found that inpatient admissions and ED use did not differ between clinics recognized as patient-centered medical homes that served a high proportion of individuals with chronic illness and a comparison group of similar non—medical home clinics.24 In contrast to this prior work, however, we found evidence of a substantial decrease in inpatient admissions among individuals with depression, suggesting that medical home enrollment may have unique benefits for this population.

Our study also provides evidence of greater engagement in outpatient care among Medicaid beneficiaries with comorbid mental and physical illness enrolled in a medical home. This pattern of higher likelihood of outpatient care use may reflect both better primary care access and increased referrals to specialty care by medical home providers, and it is consistent with prior work showing increased primary care and specialty mental health service use among medical home enrollees diagnosed with schizophrenia and comorbid chronic conditions compared with nonenrollees.28

Likely due to increased outpatient care use that was not offset by decreased inpatient admissions, we observed that medical home enrollees with schizophrenia experienced an increase in the amount of Medicaid expenditures. By comparison, medical home enrollment was associated with decreased Medicaid spending among individuals with depression. For those with depression, savings from lower inpatient care use thus appear to have dominated increased spending due to greater use of outpatient care. This finding is consistent with a prior evaluation of the CCNC program that found lower rates of hospitalization and lower spending among enrollees with chronic conditions.25

Limitations

Findings from this study need to be interpreted in light of a number of important limitations. First, results may be subject to selection bias due to the voluntary enrollment process of the medical home program under study. Our use of a fixed-effects regression approach accounts for any bias from time-invariant characteristics that could affect an individual’s enrollment into a medical home, but this approach does not address bias from characteristics that are time-variant, many of which are unobservable in claims data. This could include enrollment in a medical home during periods of acute symptoms, for example. An ad hoc analysis comparing ED spending in the 3 months pre- and post initial medical home enrollment found no difference in ED spending ($135 vs $133), potentially indicating no strong evidence of enrollment at a higher level of utilization, but other time-varying differences cannot be ruled out. An additional limitation is that our measure of total Medicaid expenditures does not capture all spending on health services used by our population of interest. For example, it does not capture expenses on state psychiatric hospitalizations, which are not covered by Medicaid for nonelderly adults. Although we were able to observe whether use of state psychiatric facilities occurred, we did not observe the costs associated with these visits. Our total Medicaid expenditures measure also does not include any spending on pharmaceuticals and laboratory services and thus does not give a complete picture of Medicaid-funded services. Finally, we were unable to account for the clustering of observations within medical home providers because we did not have access to provider identifiers.

CONCLUSIONS

Our nonexperimental study provides evidence that use of the medical home model among Medicaid beneficiaries with comorbid mental and physical illness may decrease inpatient admissions for adults with major depression, but not for adults with schizophrenia, and that it does not appear to reduce ED use. Consistent with prior research, we found that medical home enrollment for this population may increase the likelihood of contact with the healthcare system through greater probability of outpatient service use, resulting in greater Medicaid spending among service users with schizophrenia. This increase in Medicaid spending may represent an investment in addressing unmet need for outpatient services and, for those with depression, appears to be offset by cost savings from lower inpatient utilization. Future research is needed to determine whether the services received by medical home enrollees with comorbid mental and physical illness lead to meaningful improvements in clinical status.Author Affiliations: Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill (LRG, MED), Chapel Hill, NC; College of Pharmacy, University of Minnesota (JFF), Minneapolis, MN; NORC at the University of Chicago (KES), Boston, MA; RTI International (CB), Research Triangle Park, NC; Department of Social Work, North Carolina State University (ARE), Raleigh, NC; Community Care of North Carolina, Inc (CTJ), Raleigh, NC; Aledade, Inc (CAD), Bethesda, MD.

Source of Funding: Agency for Healthcare Research and Quality (grant No. R24 HS019659-01). This research was partially supported by a National Research Service Award Pre-Doctoral Traineeship from the Agency for Healthcare Research and Quality sponsored by The Cecil G. Sheps Center for Health Services Research, The University of North Carolina at Chapel Hill, grant No. T32-HS000032.

Author Disclosures: Dr Jackson is employed by Community Care of North Carolina, which operates the medical home model evaluated in this article. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (LRG, MED, JFF, KES, CB, ARE, CAD); acquisition of data (MED, CTJ, CAD); analysis and interpretation of data (LRG, KES, CB, ARE, CTJ); drafting of the manuscript (LRG, JFF); critical revision of the manuscript for important intellectual content (LRG, MED, JFF, KES, CB, ARE, CTJ, CAD); statistical analysis (LRG); obtaining funding (MED, CAD); administrative, technical, or logistic support (MED, JFF, CAD); and supervision (MED).

Address Correspondence to: Lexie R. Grove, MSPH, Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Dr, Chapel Hill, NC 27599-7411. Email: lrgrove@live.unc.edu.REFERENCES

1. Pines JM, Buford K. Predictors of frequent emergency department utilization in southeastern Pennsylvania. J Asthma. 2006;43(3):219-223. doi: 10.1080/02770900600567015.

2. Egede LE. Major depression in individuals with chronic medical disorders: prevalence, correlates and association with health resource utilization, lost productivity and functional disability. Gen Hosp Psych. 2007;29(5):409-416. doi: 10.1016/j.genhosppsych.2007.06.002.

3. Yoon J, Yano EM, Altman L, et al. Reducing costs of acute care for ambulatory care-sensitive medical conditions: the central roles of comorbid mental illness. Med Care. 2012;50(8):705-713. doi: 10.1097/MLR.0b013e31824e3379.

4. Egede LE, Zheng D, Simpson K. Comorbid depression is associated with increased health care use and expenditures in individuals with diabetes. Diabetes Care. 2002;25(3):464-470. doi: 10.2337/diacare.25.3.464.

5. Salsberry PJ, Chipps E, Kennedy C. Use of general medical services among Medicaid patients with severe and persistent mental illness. Psychiatr Serv. 2005;56(4):458-462. doi: 10.1176/appi.ps.56.4.458.

6. Kaufman EA, McDonell MG, Cristofalo MA, Ries RK. Exploring barriers to primary care for patients with severe mental illness: frontline patient and provider accounts. Issues Ment Health Nurs. 2012;33(3):172-180. doi: 10.3109/01612840.2011.638415.

7. Mojtabai R, Cullen B, Everett A, et al. Reasons for not seeking general medical care among individuals with serious mental illness. Psychiatr Serv. 2014;65(6):818-821. doi: 10.1176/appi.ps.201300348.

8. Carney CP, Jones LE. The influence of type and severity of mental illness on receipt of screening mammography. J Gen Intern Med. 2006;21(10):1097-1104. doi: 10.1111/j.1525-1497.2006.00565.x.

9. Nasrallah HA, Meyer JM, Goff DC, et al. Low rates of treatment for hypertension, dyslipidemia and diabetes in schizophrenia: data from the CATIE schizophrenia trial sample at baseline. Schizophr Res. 2006;86(1-3):15-22. doi: 10.1016/j.schres.2006.06.026.

10. Institute of Medicine. Improving the Quality of Health Care for Mental and Substance-Use Conditions: Quality Chasm Series. Washington, DC: National Academies Press; 2006.

11. Horvitz-Lennon M, Kilbourne AM, Pincus HA. From silos to bridges: meeting the general health care needs of adults with severe mental illnesses. Health Aff (Millwood). 2006;25(3):659-669. doi: 10.1377/hlthaff.25.3.659.

12. Morden NE, Mistler LA, Weeks WB, Bartels SJ. Health care for patients with serious mental illness: family medicine’s role. J Am Board Fam Med. 2009;22(2):187-195. doi: 10.3122/jabfm.2009.02.080059.

13. Frandsen BR, Joynt KE, Rebitzer JB, Jha AK. Care fragmentation, quality, and costs among chronically ill patients. Am J Manag Care. 2015;21(5):355-362.

14. Tepper MC, Cohen AM, Progovac AM, et al. Mind the gap: developing an integrated behavioral health home to address health disparities in serious mental illness. Psychiatr Serv. 2017;68(12):1217-1224. doi: 10.1176/appi.ps.201700063.

15. Parks J. Behavioral health homes. In: Raney LE, ed. Integrated Care: Working at the Interface of Primary Care and Behavioral Health. Washington, DC: American Psychiatric Publishing; 2015:193-216.

16. Druss BG, von Esenwein SA, Glick GE, et al. Randomized trial of an integrated behavioral health home: the health outcomes management and evaluation (HOME) study. Am J Psychiatry. 2016;174(3):246-255. doi: 10.1176/appi.ajp.2016.16050507.

17. Parekh AK, Goodman RA, Gordon C, Koh HK; HHS Interagency Workgroup on Multiple Chronic Conditions. Managing multiple chronic conditions: a strategic framework for improving health outcomes and quality of life. Public Health Rep. 2011;126(4):460-471. doi: 10.1177/003335491112600403.

18. Croghan TW, Brown JD. Integrating mental health treatment into the patient centered medical home. Agency for Healthcare Research and Quality website. pcmh.ahrq.gov/sites/default/files/attachments/Integrating%20Mental%20Health%20and%20Substance%20Use%20Treatment%20in%20the%20PCMH.pdf. Published June 2010. Accessed April 18, 2019.

19. Rosenthal TC. The medical home: growing evidence to support a new approach to primary care. J Am Board Fam Med. 2008;21(5):427-440. doi: 10.3122/jabfm.2008.05.070287.

20. Domino ME, Wells R, Morrissey JP. Serving persons with severe mental illness in primary care—based medical homes. Psychiatr Serv. 2015;66(5):477-483. doi: 10.1176/appi.ps.201300546.

21. Domino ME, Kilany M, Wells R, Morrissey JP. Through the looking glass: estimating effects of medical homes for people with severe mental illness. Health Serv Res. 2017;52(5):1858-1880. doi: 10.1111/1475-6773.12585.

22. Adaji A, Melin GJ, Campbell RL, Lohse CM, Westphal JJ, Katzelnick DJ. Patient-centered medical home membership is associated with decreased hospital admissions for emergency department behavioral health patients. Popul Health Manag. 2018;21(3):172-179. doi: 10.1089/pop.2016.0189.

23. Xin H, Kilgore ML, Menachemi N, Sen B. The relationships between access to and use of a patient-centered medical home and healthcare utilization and costs: a cohort study using Medical Expenditure Panel Survey data from 2007 to 2010. Health Serv Manage Res. 2014;27(3-4):70-81. doi: 10.1177/0951484815602503.

24. Cole ES, Campbell C, Diana ML, Webber L, Culbertson R. Patient-centered medical homes in Louisiana had minimal impact on Medicaid population’s use of acute care and costs. Health Aff (Millwood). 2015;34(1):87-94. doi: 10.1377/hlthaff.2014.0582.

25. Fillmore H, DuBard CA, Ritter GA, Jackson CT. Health care savings with the patient-centered medical home: Community Care of North Carolina’s experience. Popul Health Manag. 2013;17(3):141-148. doi: 10.1089/pop.2013.0055.

26. DuBard CA, Cockerham J. Community Care of North Carolina and the medical home approach to chronic kidney disease. N C Med J. 2008;69(3):229-232.

27. DuBard CA. North Carolina Integrated Data for Researchers (NCIDR): merged behavioral health data from four publicly-funded sources in North Carolina, July 2007-June 2011. Inter-university Consortium for Political and Social Research website. icpsr.umich.edu/icpsrweb/AHRQMCC/studies/34542/version/1. Published March 11, 2013. Accessed April 18, 2019.

28. Grove LR, Olesiuk WJ, Ellis AR, et al. Evaluating the potential for primary care to serve as a mental health home for people with schizophrenia. Gen Hosp Psychiatry. 2017;47:14-19. doi: 10.1016/j.genhosppsych.2017.03.002.