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Primary care in behavioral health settings

Adult Mental Health: Serious Mental Illness
Benefit-cost methods last updated December 2024.  Literature review updated May 2014.
This program was archived December 2024.
These studies evaluated co-location of primary care in behavioral health settings (mental health and substance abuse treatment centers). That is, the primary care provider was located at, or adjacent to, the behavioral health facility. Of 11 studies, six were conducted in Veterans' Administration health facilities; two were conducted at Kaiser Permanente addiction centers; and three were conducted at other community addiction treatment centers.
 
ALL
BENEFIT-COST
META-ANALYSIS
CITATIONS
For an overview of WSIPP's Benefit-Cost Model, please see this guide. The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2022).  The chance the benefits exceed the costs are derived from a Monte Carlo risk analysis. The details on this, as well as the economic discount rates and other relevant parameters are described in our 2023 Technical Documentation.
Benefit-Cost Summary Statistics Per Participant
Benefits to:
Taxpayers $175 Benefits minus costs $76
Participants ($100) Benefit to cost ratio $1.29
Others $100 Chance the program will produce
Indirect $160 benefits greater than the costs 50%
Total benefits $335
Net program cost ($260)
Benefits minus cost $76

^WSIPP’s benefit-cost model does not monetize this outcome.

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the program impacts measured in the research literature (for example, impacts on crime or educational attainment). Treatment N represents the total number of individuals or units in the treatment group across the included studies.

An effect size (ES) is a standard metric that summarizes the degree to which a program or policy affects a measured outcome. If the effect size is positive, the outcome increases. If the effect size is negative, the outcome decreases. See Estimating Program Effects Using Effect Sizes for additional information on how we estimate effect sizes.

The effect size may be adjusted from the unadjusted effect size estimated in the meta-analysis. Historically, WSIPP adjusted effect sizes to some programs based on the methodological characteristics of the study. For programs reviewed in 2024 or later, we do not make additional adjustments, and we use the unadjusted effect size whenever we run a benefit-cost analysis.

Research shows the magnitude of effects may change over time. For those effect sizes, we estimate outcome-based adjustments, which we apply between the first time ES is estimated and the second time ES is estimated. More details about these adjustments can be found in our 2023 Technical Documentation.

Meta-Analysis of Program Effects
Outcomes measured Treatment age No. of effect sizes Treatment N Effect sizes (ES) and standard errors (SE) used in the benefit-cost analysis Unadjusted effect size (random effects model)
First time ES is estimated Second time ES is estimated
ES SE Age ES SE Age ES p-value
Alcohol use disorder
Clinical diagnosis of alcohol use disorder or symptoms measured on a validated scale.  
 41 3 684 -0.001 0.124 41 0.000 0.186 44 -0.001 0.995
Illicit drug use disorder
Clinical diagnosis of illicit drug use disorder or symptoms measured on a validated scale. When possible, we exclude cannabis/marijuana use disorder from this outcome.
 41 2 643 -0.016 0.081 41 0.000 0.187 44 -0.016 0.845
Hospitalization
Hospital admission, for any reason.
 41 9 11301 -0.052 0.044 41 0.000 0.000 42 -0.052 0.235
Hospitalization (psychiatric)
Admission to a psychiatric ward or hospital.
 41 1 59 -0.068 0.293 41 0.000 0.000 42 -0.068 0.818
Emergency department visits
Whether someone visited the emergency department, or the number of times they visited the emergency department.
41 9 7320 -0.077 0.043 41 0.000 0.000 42 -0.077 0.073
Blood pressure^
Blood pressure in the typical clinical range.
 41 2 1192 -0.151 0.067 41 n/a n/a n/a -0.151 0.023
Blood sugar (HbA1c)^
Measure of average blood sugar over 10-12 weeks.
 41 2 1072 0.164 0.104 41 n/a n/a n/a 0.164 0.117
Death
“All-cause mortality,” or the proportion of all deaths in a given population during a specified period of time, regardless of the cause.
41 2 98 -0.077 0.160 41 0.000 0.000 43 -0.077 0.632
Cholesterol^
Total cholesterol (low-density lipoprotein and high-density lipoprotein).
 41 2 1515 -0.013 0.121 41 n/a n/a n/a -0.013 0.915
Primary care visits^
Visit to a primary care physician for any reason.
 41 7 1361 0.235 0.157 41 n/a n/a n/a 0.235 0.136
Regular smoking
Smoking tobacco on a regular basis.
 41 1 453 0.116 0.194 41 0.000 0.000 42 0.116 0.548
Obesity
Obese based on clinical guidelines for adults (body mass index of 30 or higher) or children (body mass index at or above the 95th percentile for children of the same age and sex), as appropriate.
41 1 435 -0.002 0.194 41 0.000 0.086 43 -0.002 0.992
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1In addition to the outcomes measured in the meta-analysis table, WSIPP measures benefits and costs estimated from other outcomes associated with those reported in the evaluation literature. For example, empirical research demonstrates that high school graduation leads to reduced crime. These associated measures provide a more complete picture of the detailed costs and benefits of the program.

2“Others” includes benefits to people other than taxpayers and participants. Depending on the program, it could include reductions in crime victimization, the economic benefits from a more educated workforce, and the benefits from employer-paid health insurance.

3“Indirect benefits” includes estimates of the net changes in the value of a statistical life and net changes in the deadweight costs of taxation.
Detailed Monetary Benefit Estimates Per Participant
Affected outcome: Resulting benefits:1 Benefits accrue to:
Taxpayers Participants Others2 Indirect3 Total
Regular smoking Labor market earnings associated with smoking ($81) ($191) $0 $0 ($271)
Health care associated with smoking ($18) ($5) ($19) ($9) ($51)
Mortality associated with smoking $0 $0 $0 ($5) ($5)
Alcohol use disorder Property loss associated with alcohol abuse or dependence $0 $0 $0 $0 $0
Illicit drug use disorder Criminal justice system $0 $0 $0 $0 $0
Labor market earnings associated with illicit drug abuse or dependence $28 $66 $0 $0 $95
Mortality associated with illicit drugs $8 $19 $0 $185 $212
Hospitalization Health care associated with general hospitalization $47 $2 $46 $23 $118
Hospitalization (psychiatric) Health care associated with psychiatric hospitalization $167 $2 $38 $83 $290
Emergency department visits Health care associated with emergency department visits $24 $6 $35 $12 $77
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($130) ($130)
Totals $175 ($100) $100 $160 $335
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Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $217 2014 Present value of net program costs (in 2022 dollars) ($260)
Comparison costs $0 2014 Cost range (+ or -) 20%
According to Saxon et al., (2006), patients in the clinics co-located at Veterans' Administration centers had an average of 1.1 more primary care visits than the comparison group in 12 months. Samet, et al. (2003) found those in a community clinic used 1.0 more primary care visits than the comparison group. For this combination location, assume an average of 1.05 visits per patient. We estimate additional cost of the program by multiplying 1.05 visits by the Medicaid enhanced payment rate for the longest primary care visit. See http://www.hca.wa.gov/medicaid/pages/aca_rates.aspx. Saxon et al., (2006). Randomized trial of onsite versus referral primary medical care for veterans in addictions treatment. Medical Care, 44(4), 334-342. Samet et al., (2003). Linking alcohol- and drug-dependent adults to primary medical care: A randomized controlled trial of a multi-disciplinary health intervention in a detoxification unit. Addiction, 98(4), 509-516.
The figures shown are estimates of the costs to implement programs in Washington. The comparison group costs reflect either no treatment or treatment as usual, depending on how effect sizes were calculated in the meta-analysis. The cost range reported above reflects potential variation or uncertainty in the cost estimate; more detail can be found in our 2023 Technical Documentation.
Benefits Minus Costs
Benefits by Perspective
Taxpayer Benefits by Source of Value
Benefits Minus Costs Over Time (Cumulative Discounted Dollars)
The graph above illustrates the estimated cumulative net benefits per-participant for the first fifty years beyond the initial investment in the program. We present these cash flows in discounted dollars. If the dollars are negative (bars below $0 line), the cumulative benefits do not outweigh the cost of the program up to that point in time. The program breaks even when the dollars reach $0. At this point, the total benefits to participants, taxpayers, and others, are equal to the cost of the program. If the dollars are above $0, the benefits of the program exceed the initial investment.

Citations Used in the Meta-Analysis

Druss, B.G., Rohrbaugh, R.M., Levinson, C.M., & Rosenheck, R.A. (2001). Integrated medical care for patients with serious psychiatric illness: a randomized trial. Archives of General Psychiatry, 58(9), 861-8.

Friedmann, P.D., Hendrickson, J.C., Gerstein, D.R., Zhang, Z., & Stein, M.D. (2006). Do Mechanisms That Link Addiction Treatment Patients to Primary Care Influence Subsequent Utilization of Emergency and Hospital Care?. Medical Care, 44(1), 8-15.

Kilbourne, A.M., Pirraglia, P.A., Lai, Z., Bauer, M.S., Charns, M.P., Greenwald, D., . . . Yano, E.M. (2011). Quality of general medical care among patients with serious mental illness: does colocation of services matter?. Psychiatric Services, 62(8), 922-928.

Laine, C., Hauck, W.W., & Turner, B.J. (2005). Availability of Medical Care Services in Drug Treatment Clinics Associated with Lower Repeated Emergency Department Use. Medical Care, 43(10), 985-995.

Parthasarathy, S., Mertens, J., Moore, C., & Weisner, C. (2003). Utilization and Cost Impact of Integrating Substance Abuse Treatment and Primary Care. Medical Care, 41(3), 357-367.

Pirraglia, P.A., Kilbourne, A.M., Lai, Z., Friedmann, P.D., & O'Toole, T.P. (2011). Colocated general medical care and preventable hospital admissions for veterans with serious mental illness. Psychiatric Services, 62(5), 554-557.

Saxon, A.J., Malte, C.A., Sloan, K.L., Baer, J.S., Calsyn, D.A., Nichol, P., . . . Kivlahan, D.R. (2006). Randomized Trial of Onsite Versus Referral Primary Medical Care for Veterans in Addictions Treatment. Medical Care, 44(4), 334-342.

Scharf, D.M, Eberhart, N.K., Horvitz-Lennon, M., R. Beckman, Han, B., Lovejoy, S., Pincus, H.A., Burnam, M.A. (2013). Evaluation of the SAMHSA Primary and Behavioral ehalth Care Integration Program: Final report. Rand Corporation. http://aspe.hhs.gov/daltcp/reports/2013/PBHCIfr.shtml

Umbricht-Schneiter, A., Ginn, D.H., Pabst, K.M., & Bigelow, G.E. (1994). Providing medical care to methadone clinic patients: referral vs on-site care. American Journal of Public Health, 84(2), 207-210.

Weisner, C., Mertens, J., Parthasarathy, S., Moore, C., & Lu, Y. (2001). Integrating primary medical care with addiction treatment: A randomized controlled trial. JAMA : The Journal of the American Medical Association, 286(14), 1715-1723.

Willenbring, M.L., & Olson, D.H. (1999). A randomized trial of integrated outpatient treatment for medically ill alcoholic men. Archives of Internal Medicine, 159(16), 1946-1952.

Willenbring, M.L., Olson, D.H., & Bielinski, J. (1995). Integrated Outpatient Treatment for Medically Ill Alcoholic Men: Results from a Quasi-Experimental Study. Journal of Studies on Alcohol, 56(3), 337.