Impact of Behavioral Health Homes on Cost and Utilization Outcomes
Abstract
Objective:
This study evaluated the impact of two behavioral health home (BHH) approaches, provider-supported care and self-directed care, on health care utilization and cost outcomes among adult Medicaid recipients with serious mental illness.
Methods:
Eleven community mental health provider sites were randomly assigned to one of the BHH approaches, which each site implemented over a 2-year period. In both approaches, staff were trained in wellness coaching to support patients’ progress toward general health and wellness goals. Provider-supported sites employed a full-time on-site registered nurse, who provided consultation to patients and wellness coaches. Each approach had a consistently enrolled treatment group (combined N=859) with a matched comparison cohort that was identified for analysis. Approaches were compared with each other and with baseline, and differences between each approach and its comparison cohort were examined by using analysis of covariance to determine impact on total health care cost, prescription costs, and use and cost of general medical and behavioral health services.
Results:
Relative to its comparison cohort, each approach achieved significant reductions in total cost (15% for provider-supported care and 26% for self-directed care) and increases in use of outpatient general medical services (43% for provider-supported care and 29% for self-directed care). Compared with self-directed care, provider-supported care resulted in approximately 28% lower use of general medical inpatient services and 26% lower related costs.
Conclusions:
BHH approaches in community mental health settings can produce health care savings and decrease use of inpatient health care.
HIGHLIGHTS
•
Little is known about the impact of behavioral health homes (BHHs) on total use of services and related costs among adults with serious mental illness.
•
Two BHH approaches were compared with one another and with a matched comparison cohort over a baseline year and 2-year implementation period.
•
BHHs resulted in a significant reduction in total cost of care and use of general medical inpatient services as well as an increase in use of outpatient general medical services, demonstrating that health homes in community mental health settings can improve outcomes and produce health care savings.
Individuals with serious mental illness are more likely than persons in the general population to experience negative health outcomes (1–3). The annual economic, indirect cost of serious mental illness in the United States due to loss of productivity and earnings is estimated to be $193 billion (4). The integration of general medical health and wellness in behavioral health treatment settings has been shown to decrease health care disparities for individuals with serious mental illness (5–7); however, little is known about whether integrated care reduces cost to payers or health care utilization in this population.
A recent literature review identified 11 studies conducted between 2000 and 2018 assessing the impact of behavioral health homes (BHHs) (8). Four of these studies assessed cost-related outcomes and yielded mixed findings; however only two were peer reviewed (9, 10). Both of these studies provided important information, but their applicability and generalizability were limited. The randomized controlled trial by Druss et al. (9), an important seminal study, found no significant difference in total cost of care between those receiving integrated care in the offices of community mental health providers and a control group. The applicability of the findings to current policy is limited because the study was published nearly 20 years ago, was based on findings from two U.S. Department of Veteran’s Affairs (VA) clinics, and used VA cost accounting data with a small number of patients (N=120) over the course of a single year. Similarly, Krupski and colleagues (10) did not find a significant decrease in per member per month (PMPM) cost in their study of an approach implemented in mental health safety net clinics with a larger patient sample (N=762). This study included cost data only from two clinics and an affiliated medical center, and the matched comparison cohort had significantly lower behavioral health acuity. Several studies that evaluated health care utilization, including emergency department use, inpatient stays, and receipt of outpatient general medical care, resulted in heterogeneous findings (5, 6, 9–11).
Community Care Behavioral Health Organization (Community Care), a nonprofit behavioral managed care organization that is a subsidiary of UPMC, implemented two BHH approaches, provider-supported care and self-directed care, in behavioral health provider sites (“providers”) across Pennsylvania as part of a comparative effectiveness study funded by the Patient-Centered Outcomes Research Institute (PCORI contract #271). At the completion of the parent study, we conducted a subsequent analysis with the study population and a matched comparison cohort to examine the impact of the interventions on cost and health care utilization and to understand how our findings compare with current evidence.
Methods
Study Setting
Participating community mental health provider sites were within Community Care’s provider network and were chosen on the basis of their rural and suburban locations. Providers could not have previously participated in the implementation of a BHH approach and had to provide case management services. Eleven providers across Pennsylvania were randomly assigned to either provider-supported care (N=5) or self-directed care (N=6). Each provider implemented its assigned BHH approach over a 2-year period (6).
Study Interventions
Figure 1 provides an overview of the common and unique components of each BHH approach. In both approaches, provider staff, namely case managers and peer specialists, were trained in wellness coaching to support patients with identification of and progress toward general health and wellness goals. Interventions were implemented within the context of a culture of wellness in which sites were encouraged to support healthy lifestyles, disease prevention, health education and promotion, and coordination with primary care providers (6). Neither approach required on-site primary care service delivery.
Provider-supported sites employed a full-time on-site registered nurse (i.e., wellness nurse) who provided consultation to patients and wellness coaches. Nurses educated provider staff about common medical conditions and assisted wellness coaches in the development of patient wellness plans. In addition, wellness nurses supported patient access to and utilization of outpatient primary and specialty care (6).
Self-directed sites provided tools and resources to patients to support the adoption of healthy habits and management of chronic conditions. Tools included education about common chronic medical conditions and trackers to support positive sleep hygiene, smoking cessation, improved nutrition, and weight management. Patients could access information via a secure online portal or in a paper toolkit format (6).
Patient Sample
Eligible participants were Medicaid recipients receiving services at participating provider sites, age 21 or older, with a diagnosis of serious mental illness based on the Commonwealth of Pennsylvania’s definition (i.e., major depression, bipolar disorder, and schizophrenia or schizoaffective disorder) (12). The parent study enrolled 1,229 participants—713 across provider-supported sites and 516 across self-directed sites. We obtained informed consent from all individuals participating in the parent study. The study was reviewed and approved by the University of Pittsburgh Institutional Review Board (6).
For this analysis, we identified 859 individuals from our study sample (522 from provider-supported sites and 337 from self-directed sites) who were Medicaid eligible at some point in each of the 3 analysis years and who received case management services consistently from the same provider. Those not meeting these criteria dropped from Medicaid eligibility for 1 or more study years, switched the provider from which they were receiving case management services during the study period, or both. Those not included in the study for these reasons were slightly older and had modestly higher PMPM costs. A comparable pattern was found for members not in the sample in the larger population receiving services from other nonparticipating providers who lost Medicaid eligibility or switched providers. Of individuals receiving case management services, those who remained eligible for Medicaid and received services consistently from the same provider were slightly younger and had lower PMPM spending, compared with those who lost eligibility or switched providers over the 2-year study period.
Group composition of the provider-supported approach was as follows: total, 522; males, 213; females, 309, mean age, 45.1 (comparison cohort: total, 522; males, 213; females, 309; mean age, 43.2). Group composition of the self-directed approach was as follows: total, 337; males, 111; females, 226; mean age, 43.6 (comparison cohort: total, 337; males, 112; females, 225; mean age, 42.0).
We used historical claims data to identify comparison cohorts of individuals with characteristics similar to those of participants in the parent study, including serious mental illness diagnosis and receipt of case management services. The matched cohorts were identified from Community Care’s members in the same Medicaid program who were not receiving services at provider sites participating in the parent study. We matched with replacement using an iterative algorithm that considered serious mental illness diagnoses, total PMPM costs, continuity of Medicaid enrollment, age, gender, and PMPMs for the service categories included in this analysis. Although the Medicaid enrollment data included a race-ethnicity indicator, the completeness and accuracy of this information were of uncertain reliability; thus, we did not include it in our evaluation. Both cohorts were matched by using data only from the study’s baseline year (2013). Assessment of the comparison cohort’s health risk profiles relative to those of the two treatment groups with use of the Chronic Illness and Disability Payment System (13) determined that the comorbidity burden and acuity of the treatment and control groups were highly similar.
Data and Measures
We analyzed Medicaid total cost of care, including behavioral health, general medical, and pharmacy claims encounter data from calendar years 2013–2015 for the intervention and comparison cohorts. The claims cost to payers as the cost outcome measure is a significant advance over prior studies. Preimplementation occurred in calendar year 2013 (baseline), and 2014 (year 1) and 2015 (year 2) served as implementation measurement years.
Outcomes included service utilization rates (annual average of the monthly percentage of members utilizing services) and PMPM costs, with both measures calculated for behavioral health, general medical health, and combined spending; medical inpatient and behavioral health; emergency department use; prescription drugs; and total case management services. General medical claims did not contain payment amounts; thus, costs were calculated by applying a publicly available standardized pricing algorithm calibrated against Pennsylvania Medicaid unit costs. This algorithm was applied to general medical encounter data and behavioral health claims data for all the pre- and postimplementation periods. The National Quality Forum endorsed the algorithm’s integrity and validity in standardizing and measuring cost of care (14). Full payment information was available for a subset of the members whose claims costs allowed us to verify that there was no systematic bias introduced by the algorithm, which had the additional advantage of not being influenced by unrelated shifts in specific provider-contracted rates. Cost measures were not adjusted for inflation over the study years.
Statistical Methods
Three comparative analyses were conducted using Stata11 (15). First, in the primary analysis, changes in total claim spending were compared for each treatment arm (self-directed care and provider-supported care) to the comparison cohort matched to each approach’s subpopulation. Second, the impact of the approaches was confirmed and further illuminated by comparing each approach to its own baseline year. These two analyses estimated whether the BHH approaches had a statistically significant impact relative to an estimated counterfactual (i.e., comparison cohort and difference-in-difference for the first and second analyses, respectively). Third, to more clearly estimate and display the statistical significance of differences in impact between provider-supported and self-directed sites (i.e., which treatment arm worked “better”), the difference between these two arms was assessed directly for magnitude and statistical significance.
Analyses were conducted at the level of the individual service user. Dependent variables included annual average monthly utilization (i.e., percentage of members accessing service) and annual average PMPM expenditures, overall and for each service category analyzed. Average annual PMPM (i.e., total expenditure/total eligible member months) was calculated for service users in each of the 3 analysis years.
For most measures with service-specific categories, a majority of recipients reported no spending; thus, a two-part model for cost outcome variables was used to assess total costs and for each service use category. In the two-part model, the first stage predicted whether any cost would be incurred (and so included observations with both zero and nonzero cost), and the second stage predicted the level of cost given that cost had been incurred (and so included only observations with nonzero cost) (16). Logistic regression was used in the first model, and the second used generalized linear models with a gamma distribution and log link, which was a more suitable fit for handling skewness. The analysis controlled for age, gender, and baseline outcome values to guard against chance of imbalance between treatment arms. Difference-in-differences estimation by linear regression was used for comparisons to the baseline period within treatment arms.
Results were calculated and are presented in percentage change to clearly demonstrate the relative sizes of the various effects analyzed. Percentage change was calculated from the parameters of the statistical models. Using total cost in year 2 for provider-supported sites compared with their own historical baseline as an outcome example, the calculation for the percentage change was (year 2 PMPM–baseline year PMPM)/(baseline year PMPM).
Results
The narrative below provides an overview of each analysis, describing results significant at least at the level of p<0.05, and in most cases p<0.01. Table 1 presents summary results for each of the three analyses, including year-2 impacts, the arm-to-arm comparison, significance levels, and sample characteristics. (More detailed tables displaying absolute values and calculations of percentage changes for each of the three analyses are available in an online supplement .)
| Patients using service (% difference) | Per member per month cost (% difference) | |||||
|---|---|---|---|---|---|---|
| Service and approach | Year 2 vs. comparison cohort | Year 2 vs. baseline | Provider supported vs. self-directed | Year 2 vs. comparison cohort | Year 2 vs. baseline | Provider supported vs. self-directed |
| Total | ||||||
| Provider supported | nab | nab | nab | –15* | –12** | –9 |
| Self-directed | nab | nab | nab | –26* | –8* | |
| General medical services | ||||||
| Provider supported | 43** | 16** | 5 | –2 | 9 | –9 |
| Self-directed | 29** | 9** | –22* | –9 | ||
| Behavioral health services | ||||||
| Provider supported | 14** | –11** | –5 | –28** | –25** | –12 |
| Self-directed | 15** | –5** | –29 | –10** | ||
| Prescription medications | ||||||
| Provider supported | –30** | –13** | –8 | –5 | 27** | 22 |
| Self-directed | –26** | –8** | –23** | 1 | ||
| All inpatient services | ||||||
| Provider supported | –36** | –32** | –23* | –23** | –3 | –22 |
| Self-directed | –34** | –28** | –44* | –26 | ||
| Medical inpatient services | ||||||
| Provider supported | 33 | –32** | –28** | 13 | –12 | –26* |
| Self-directed | 19 | –32** | –7 | –18 | ||
| Behavioral health inpatient services | ||||||
| Provider supported | –41** | –33 | –12 | –49** | –25 | –25 |
| Self-directed | –29 | –40** | –74c | –42 | ||
| Emergency department services | ||||||
| Provider supported | nad | –6 | –13 | nad | –1 | –19 |
| Self-directed | nad | –14** | nad | –7 | ||
| All case management services | ||||||
| Provider supported | 8 | –19** | –14 | –17* | –25** | –33** |
| Self-directed | 23 | –4** | 26 | 15** | ||
a
Values are percentage changes in the average monthly utilization rate or per member per month cost estimates.
b
Not applicable because all continuously enrolled members used some service in all periods.
c
p=.054.
d
Not applicable because the matched cohort was not comparable to intervention groups for the emergency department analysis.
*
p<.05, **p<.01.
Each BHH Approach Versus Comparison Cohort
Provider-supported care.
The first and primary analysis compared each approach with its own comparison cohort over the same 2-year period. Relative to the comparison cohort, the provider-supported cohort incurred a 15% decrease in overall PMPM cost and a 28% reduction in behavioral health PMPM cost at the end of year 2. In addition, it incurred a 36% reduction in use of inpatient services and a 23% reduction in total inpatient cost, which was likely driven by the 41% reduction in use of inpatient behavioral health services and 49% reduction in associated behavioral health spending. Provider-supported care was also correlated with a reduced percentage of prescription drug use (30%) and lower total case management spending (17%). At the same time, significant increases were noted in access to general medical and behavioral health services (43% and 14%, respectively), with no significant change in general medical spending and a reduction in behavioral health spending of 28%.
Self-directed care.
The self-directed cohort experienced a significant 26% decrease in total PMPM costs and a 22% reduction in general medical cost at the end of year 2, while increasing use of general medical services by 29% and behavioral health services by 15%. Self-directed care was associated with significant reductions in overall inpatient service use (34%) and cost (44%) as well as reductions in prescription drug use (26%) and cost (23%). Although downward trends were observed for inpatient behavioral health costs, this finding was not statistically significant.
Each BHH Approach Versus Baseline
Given the large increases in utilization of general medical services and the large reductions in cost in the primary results discussed above, it is helpful to analyze how each measure shifted relative to the year prior to BHH. The findings indicate that by year 2 many cost measures showed a large absolute drop relative to baseline. In the treatment arms, costs for many categories fell below baseline levels by year 2, whereas in the comparison cohorts discussed in the previous section, costs grew marginally at year 2. Therefore, the cost difference between the treatment arms and the comparison cohort was larger in absolute value than the cost difference between the treatment arms and baseline, which, by definition, had zero growth.
Provider-supported care.
Participants in the provider-supported approach had a statistically significant 12% reduction in overall PMPM spending postimplementation, compared with baseline, primarily driven by a significant reduction in behavioral health spending of 25%. We observed a 16% increase in overall use of general medical services. At the same time, a significant 32% reduction was seen in total inpatient utilization (behavioral and general medical), as well as medical inpatient utilization. Percentage of members with prescription drug use decreased significantly by 13%, but the PMPM spending on prescription drugs increased by 27%, suggesting a shift in the mix of medications. A significant downward trend was shown in total case management use (19%) and cost (25%).
Self-directed care.
The self-directed cohort also experienced a significant decrease in overall PMPM spending (8%), overall inpatient utilization (28%), medical inpatient utilization (32%), and inpatient behavioral health utilization (40%). We also observed significant reductions in prescription drug use (8%) and higher general medical services utilization (9%). In contrast to provider-supported care, self-directed care corresponded with reduced emergency department use (14%) and an increase (15%) in total case management cost.
Provider-Supported Versus Self-Directed Approaches
In the first two analyses, each arm was compared with its own comparator (comparison cohort in the first analysis and baseline year in the second analysis). In the third analysis, we observed modest differences in the impact of the provider-supported and self-directed approaches. Because the inclusion of a wellness nurse increased the cost of implementing the provider-supported approach, we conducted a direct comparison of the trial arms to provide an explicit test of the statistical significance of any differences in impact between the two arms observed in the analyses described above.
Relative to self-directed care, provider-supported care had regression parameters suggesting a more pronounced impact for most measures. Most measures were not statistically significant, with a few exceptions, including lower overall inpatient utilization (23%) and use of medical inpatient services (28%) and lower incurred cost for medical inpatient utilization (26%) and total case management (33%).
Again, because each intervention displayed significant changes in cost and utilization outcomes relative to both its own baseline period and to its matched comparison cohort (i.e., both interventions shifted utilization and costs in a similar manner), findings for our comparison of provider-supported to self-directed approaches tended to be less statistically significant.
Discussion
Existing literature underscores the value of health homes in supporting health care systems as they continue to work toward achieving the “triple aim” of improved care quality, cost, and patient outcomes (9, 17). To date, the potential of BHHs to reduce costs has not been conclusively supported (8).
Both provider-supported care and self-directed care resulted in a higher proportion of members utilizing general medical services, compared with those receiving services in nonintervention sites. Higher rates observed for the provider-supported approach may be driven by the contributions of the on-site wellness nurse, who focused on direct collaboration and communication with general medical providers around management of patients’ chronic diseases. This may have led to timely and consistent use of general medical care by patients. Nonetheless, the observed increase in use of general medical services for those receiving services at self-directed sites suggests that in cases where resources may not be available for on-site nursing staff, providers can still play a role in enhancing important care linkages. Provider-supported and self-directed approaches provide two BHH options of variable intensity to help facilitate coordinated, holistic care.
The implementation of patient-centered medical homes has resulted in successes in enhancing the spectrum and coordination of services available to members in primary care settings and improving patient outcomes (18–20). In the context of mixed findings in the literature (5, 9–11, 21, 22), our study provides further evidence that medical homes may be advantageous for individuals with complex conditions who are receiving care at community mental health provider sites. In addition to highlighting the need for expansion of the medical home approaches in behavioral health treatment settings, our findings highlight the importance of implementing and evaluating similar efforts to address outcomes for individuals with other chronic illnesses who have primary clinical connections to a specialty setting rather than with their primary care physician.
This study adds to the literature by showing that a BHH approach with modest changes in staffing that does not require the addition of on-site primary care provision can make efficient use of resources by reducing the total cost of care to payers. These improvements were large and statistically significant. Furthermore, outcomes were measured over a 2-year period, allowing the program to take root and develop its potential for impact, which is an additional contribution to current knowledge regarding this important public policy issue.
This study had some notable limitations. Because randomization occurred at the provider level, there may have been differences in providers or in implementation regions for which we could not control; however, safeguards related to statistical methods and control variables should have reduced any such effects. In addition, the available population for the comparison cohort came from more urban geographic areas, in contrast to the more rural and suburban locations of the study sites. One result of this limitation in available comparison data was that we were not able to match emergency department utilization for the intervention versus comparison cohorts in the first analysis. However, the similarity in magnitude and significance of the results of the matched cohort comparison analysis with the approach-versus-baseline results suggests that this limitation did not have a large effect.
Conclusions
Our analysis of two BHH approaches revealed a significant reduction in total cost of care to payers, a reduction in use of general inpatient services, and an increase in use of outpatient general medical services. Our prior research assessing the implementation of provider-supported and self-directed approaches demonstrated improved patient outcomes (6). This study showed that implementation of health homes in community mental health provider settings may also produce health care savings and more efficient health care utilization. Similar approaches may be advantageous for individuals with other complex chronic conditions.
Supplementary Material
File (appi.ps.201900141.ds001.pdf)
- View/Download
- 158.30 KB
References
1.
Colton CW, Manderscheid RW: Congruencies in increased mortality rates, years of potential life lost, and causes of death among public mental health clients in eight states. Prev Chronic Dis 2006; 3:A42
2.
Daumit GL, Anthony CB, Ford DE, et al: Pattern of mortality in a sample of Maryland residents with severe mental illness. Psychiatry Res 2010; 176:242–245
3.
Olfson M, Gerhard T, Huang C, et al: Premature mortality among adults with schizophrenia in the United States. JAMA Psychiatry 2015; 72:1172–1181
4.
Kessler RC, Heeringa S, Lakoma MD, et al: Individual and societal effects of mental disorders on earnings in the United States: results from the National Comorbidity Survey Replication. Am J Psychiatry 2008; 165:703–711
5.
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 2017; 174:246–255
6.
Schuster JM, Nikolajski C, Kogan JN, et al: A payer-guided approach to widespread diffusion of behavioral health homes in real-world settings. Health Aff 2018; 37:248–256
7.
Waters HC, Furukawa MF, Jorissen SL: Evaluating the impact of integrated care on service utilization in serious mental illness. Community Ment Health J 2018; 54:1101–1108
8.
Murphy KA, Daumit GL, Stone E, et al: Physical health outcomes and implementation of behavioural health homes: a comprehensive review. Int Rev Psychiatry 2018; 30:224–241
9.
Druss BG, Rohrbaugh RM, Levinson CM, et al: Integrated medical care for patients with serious psychiatric illness: a randomized trial. Arch Gen Psychiatry 2001; 58:861–868
10.
Krupski A, West II, Scharf DM, et al: Integrating primary care into community mental health centers: impact on utilization and costs of health care. Psychiatr Serv 2016; 67:1233–1239
11.
Missouri Community Mental Health Center Healthcare Homes Progress Report 2017. Jefferson City, Missouri Department of Mental Health, 2017. https://dmh.mo.gov/media/pdf/missouri-community-mental-health-center-healthcare-homes-progress-report-2017. Accessed Oct 29, 2019
12.
Mental Illness Coverage, Pa. 40 PS Insurance §764g
13.
Chronic Illness and Disability Payment System. San Diego, University of California San Diego. http://cdps.ucsd.edu. Accessed Oct 29, 2019
14.
Total Care Relative Resource Value (TCRRV). Bloomington, MN, Health Partners, Sept 2017. https://www.healthpartners.com/ucm/groups/public/@hp/@public/documents/documents/cntrb_039627.pdf. Accessed Oct 29, 2019
15.
Stata Statistical Software, Release 11. College Station, TX, StataCorp LP, 2009
16.
Belotti F, Deb P, Manning WG, et al: Twopm: two-part models. Stata J 2015; 15:3–20
17.
Nielsen M, Olayiwola JN, Grundy P, et al: The Patient-Centered Medical Home's Impact on Cost and Quality: An Annual Update of the Evidence: 2012–2013. Washington, DC, Patient-Centered Primary Care Collaborative, Jan 2014. https://www.milbank.org/publications/the-patient-centered-medical-homes-impact-on-cost-quality-an-annual-update-of-the-evidence-2012-2013. Accessed Oct 29, 2019
18.
Friedberg MW, Rosenthal MB, Werner RM, et al: Effects of a medical home and shared savings intervention on quality and utilization of care. JAMA Intern Med 2015; 175:1362–1368
19.
Grumbach K, Bodenheimer T, Grundy P: The Outcomes of Implementing Patient-Centered Medical Home Interventions: A Review of the Evidence on Quality, Access and Costs From Recent Prospective Evaluation Studies. Washington, DC, Patient-Centered Primary Care Collaborative, 2009. https://pcmh.ahrq.gov/sites/default/files/attachments/The%20Outcomes%20of%20Implementing%20Patient-Centered%20Medical%20Home%20Interventions.pdf. Accessed Oct 29, 2019
20.
Nielsen M, Buelt L, Patel K, et al: The Patient-Centered Medical Home's Impact on Cost and Quality: Annual Review of Evidence 2014–2015. Washington, DC, Patient-Centered Primary Care Collaborative, Feb 2016. https://www.milbank.org/wp-content/uploads/2016/02/PCPCC_2016_Report.pdf. Accessed Oct 29, 2019
21.
Gilmer TP, Henwood BF, Goode M, et al: Implementation of integrated health homes and health outcomes for persons with serious mental illness in Los Angeles County. Psychiatr Serv 2016; 67:1062–1067
22.
Romaire MA, Keyes V, Parish WJ, et al: Impact of medical homes on expenditures and utilization for beneficiaries with behavioral health conditions. Psychiatr Serv 2018; 69:871–878
Information & Authors
Information
Published In
History
Received: 15 March 2019
Revision received: 9 December 2019
Revision received: 4 February 2020
Accepted: 5 March 2020
Published online: 28 April 2020
Published in print: August 01, 2020
Keywords
Authors
Competing Interests
The authors report no financial relationships with commercial interests.
Metrics & Citations
Metrics
Citations
Export Citations
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.
For more information or tips please see 'Downloading to a citation manager' in the Help menu.
View Options
View options
PDF/EPUB
View PDF/EPUBLogin options
Already a subscriber? Access your subscription through your login credentials or your institution for full access to this article.
Personal login Institutional Login Open Athens loginNot a subscriber?
PsychiatryOnline subscription options offer access to the DSM-5-TR® library, books, journals, CME, and patient resources. This all-in-one virtual library provides psychiatrists and mental health professionals with key resources for diagnosis, treatment, research, and professional development.
Need more help? PsychiatryOnline Customer Service may be reached by emailing [email protected] or by calling 800-368-5777 (in the U.S.) or 703-907-7322 (outside the U.S.).