Abstract
Despite increasing mental health provider supply shortages, research on capacity planning and management in the field of outpatient community mental healthcare is limited. There is an immediate need for strategies to plan and manage the capacity of existing mental healthcare providers to ensure a balance between demand and resources. To address this need, research on capacity planning and management in healthcare and mental healthcare settings is reviewed. Next, the Capacity-to-Serve Model is introduced and defined as a data-driven process for quantifying and reporting real-time standardized estimates of mental health provider availability based on qualifications, monitoring of outcome targets, and use of the Capacity-to-Serve Ratio and Realizing Capacity Measure. Finally, implications for using the model as an innovative solution for capacity management to meet demand in mental health are addressed. A case example is provided to demonstrate the application of the model. Ultimately, the Capacity-to-Serve Model can standardize capacity reporting of existing provider organizations and networks, both small and large, to support increased access to and supply of mental health services.
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References
American Medical Association. (2023). CPT (Current Procedural Terminology). https://www.ama-assn.org/amaone/cpt-current-procedural-terminology
Anesi, G. L., Liu, V. X., Gabler, N. B., Delgado, M. K., Kohn, R., Weissman, G. E., Bayes, B., Escobar, G. J., & Halpern, S. D. (2018). Associations of intensive care unit capacity strain with disposition and outcomes of patients with sepsis presenting to the emergency department. Annals of the American Thoracic Society, 15(11), 1328–1335. https://doi.org/10.1513/AnnalsATS.201804-241OC
Bouchery, E. (2018). Examining substance use disorder treatment demand and provider capacity in a changing health care system: Final report, Office of the Assistant Secretary for Planning and Evaluation. https://aspe.hhs.gov/reports/examining-substance-use-disorder-treatment-demand-provider-capacity-changing-health-care-system-1#main-content
Bouchery, E. (2021). Mental health treatment need and treatment system capacity issue brief. Office of the Assistant Secretary for Planning and Evaluation. https://aspe.hhs.gov/reports/mental-health-treatment-need-treatment-system-capacity-issue-brief
Burdett, R., & Kozan, E. (2016). A multi-criteria approach for hospital capacity analysis. European Journal of Operational Research, 255(2), 505–521. https://doi.org/10.1016/j.ejor.2016.05.041
Cameron, P. A., & Campbell, D. A. (2003). Access block: Problems and progress. The Medical Journal of Australia, 178(3), 99–100. https://doi.org/10.5694/j.1326-5377.2003.tb05091.x
Carey, M. R., Sheth, H., & Braithwaite, R. S. (2005). A prospective study of reasons for prolonged hospitalizations on a general medicine teaching service. Journal of General Internal Medicine, 20(2), 108–115. https://doi.org/10.1111/j.1525-1497.2005.40269.x
Chopra, V., Toner, E., Waldhorn, R., & Washer, L. (2020). How should U.S. hospitals prepare for Coronavirus Disease 2019 (COVID-19)? Annals of Internal Medicine, 172(9), 621–622. https://doi.org/10.7326/M20-0907
Cochran, J. K., & Roche, K. A. (2008). A queuing-based decision support methodology to estimate hospital inpatient bed demand. Journal of the Operational Research Society, 59(11), 1471–1482. https://doi.org/10.1057/palgrave.jors.2602499
Consolidated Appropriations Act, Public Law 116–260. (2021) https://www.govinfo.gov/app/details/PLAW-116publ260
Czeisler, M. E., Lane, R. I., Petrosky, E., Wiley, J. F., Christensen, A., Njai, R., Weaver, M. D., Robbins, R., Facer-Childs, E. R., Barger, L. K., Czeisler, C. A., Howard, M. E., & Rajaratnam, S. M. W. (2020). Mental health, substance use, and suicidal ideation during the COVID-19 pandemic - United States, June 24–30, 2020. Morbidity and Mortality Weekly Report, 69(32):1049–1057. https://doi.org/10.15585/mmwr.mm6932a1
Devapriya, P., Strömblad, C. T. B., Bailey, M. D., Frazier, S., Bulger, J., Kemberling, S. T., & Wood, K. E. (2015). StratBAM: A discrete-event simulation model to support strategic hospital bed capacity decisions. Journal of Medical Systems, 39(10), 130. https://doi.org/10.1007/s10916-015-0325-0
Eriksson, C. O., Stoner, R. C., Eden, K. B., Newgard, C. D., & Guise, J. M. (2017). The association between hospital capacity strain and inpatient outcomes in highly developed countries: A systematic review. Journal of General Internal Medicine, 32(6), 686–696. https://doi.org/10.1007/s11606-016-3936-3
Fatovich, D. M., Nagree, Y., & Sprivulis, P. (2005). Access block causes emergency department overcrowding and ambulance diversion in Perth, Western Australia. Emergency Medicine Journal, 22(5), 351–354. https://emj.bmj.com/content/22/5/351
Freedman, S., Lin, H., & Prince, J. (2018). Information technology and patient health: Analyzing outcomes, populations and mechanisms. American Journal of Health Economics, 4(1), 51–79. https://doi.org/10.1162/ajhe_a_00093
Halpern, S. D. (2011). ICU capacity strain and the quality and allocation of critical care. Current Opinion in Critical Care, 17(6), 648–657. https://doi.org/10.1097/MCC.0b013e32834c7a53
Kate, S., Richard, L., Bevan, H., & Steyn, R. S. (2004). Reducing waiting times in the NHS: Is lack of capacity the problem? Clinician in Management, 12(3), 105–111.
Kohn, R., Harhay, M. O., Weissman, G. E., Anesi, G. L., Bayes, B., Greysen, S. R., Ratcliffe, S. J., Halpern, S. D., & Kerlin, M. P. (2019). Ward capacity strain: A novel predictor of delays in intensive care unit survivor throughput. Annals of the American Thoracic Society, 16(3), 387–390. https://doi.org/10.1513/AnnalsATS.201809-621RL
Kumar, K., & Shastri, L. (2018). How advanced analytics can improve hospital capacity management. https://www.infosys.com/industries/healthcare/whitepapers/Documents/hospital-capacity-management.pdf
North Carolina Department of Health & Human Services. (n.d.). COVID-19 and behavioral health. Raleigh, NC. https://www.ncdhhs.gov/divisions/mental-health-developmental-disabilities-and-substance-abuse/covid-19-and-behavioral-health
O’Brien, D., Harvey, K., Howse, J., Reardon, T., & Creswell, C. (2016). Barriers to managing child and adolescent mental health problems: A systematic review of primary care practitioners’ perceptions. The British Journal of General Practice, 66(651), 693–707. https://doi.org/10.3399/bjgp16X687061
Ravaghi, H., Alidoost, S., Mannion, R., & Belorgeot, V. D. (2020). Models and methods for determining the optimal number of beds in hospitals and regions: A systematic scoping review. BMC Health Services Research, 20(1), 186. https://doi.org/10.1186/s12913-020-5023-z
Reinert, M., Fritze, D., & Nguyen, T. (2021). The state of mental health in America 2022. Alexandria, VA: Mental Health America. Retried from https://mhanational.org/sites/default/files/2022 State of Mental Health in America.pdf
Sanders, H., & Guth, M. (2023). A look at strategies to address behavioral health workforce shortages: Findings from a survey of state Medicaid programs. Kaiser Family Foundation. https://www.kff.org/medicaid/issue-brief/a-look-atstrategies-to-address-behavioral-health-workforce-shortages-findings-from-a-survey-of-state-medicaid-programs/
Saunders, H., Guth, M., & Eckart, G. (2023). A look at strategies to address behavioral health workforce shortages: Findings from a survey of state Medicaid programs. https://www.kff.org/medicaid/issue-brief/a-look-at-strategies-to-address-behavioral-health-workforce-shortages-findings-from-a-survey-of-state-medicaid-programs/
Terwiesch, C., Diwas, K. C., & Kahn, J. M. (2011). Working with capacity limitations: Operations management in critical care. Critical Care, 15(4), 308. https://doi.org/10.1186/cc10217
U.S. Department of Health and Human Services, Health Resources and Services Administration, Bureau of Health Workforce, National Center for Health Workforce Analysis (2016). National projections of supply and demand for selected behavioral health practitioners: 2013–2025 https://bhw.hrsa.gov/sites/default/files/bureau-health-workforce/data-research/behavioral-health-2013-2025.pdf
U.S. Department of Health & Human Services (2021). New HHS study shows 63-fold increase in Medicare telehealth utilization during the pandemic. Washington, DC. https://www.hhs.gov/about/news/2021/12/03/new-hhs-study-shows-63-fold-increase-in-medicare-telehealth-utilization-during-pandemic.html
U.S. Department of Health and Human Services. (2023). COVID-19 public health emergency. https://www.hhs.gov/coronavirus/covid-19-public-health-emergency/index.html
Utley, M., & Peters, M. (2012). Bring on the geeks: The case for improved modelling of capacity requirements. Archives of Disease in Childhood, 97(11), 933–934. https://doi.org/10.1136/archdischild-2012-302411
Wagner, J., Gabler, N. B., Ratcliffe, S. J., Brown, S. E., Strom, B. L., & Halpern, S. D. (2013). Outcomes among patients discharged from busy intensive care units. Annals of Internal Medicine, 159(7), 447–55. https://doi.org/10.7326/0003-4819-159-7-201310010-00004
Weissman, G. E., Gabler, N. B., Brown, S. E., & Halpern, S. D. (2015). Intensive care unit capacity strain and adherence to prophylaxis guidelines. Journal of Critical Care, 30(6), 1303–1309. https://doi.org/10.1016/j.jcrc.2015.08.015
Zeitz, K., & Watson, D. (2018). Principles of capacity management, applied in the mental health context. Australian Health Review, 42(4), 438–444. https://doi.org/10.1071/AH17007
Zhu, J. M., Myers, R., McConnell, K. J., Levander, X., & Lin, S. C. (2022). Trends in outpatient mental health service use before and during the COVID-19 pandemic. Health Affairs, 41(4), 573–580. https://doi.org/10.1377/hlthaff.2021.01297
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Richardson, S., Joe, S. The Capacity-to-Serve Model as a Data-Driven Process for Provider Capacity Management in Outpatient Community Mental Health. Community Ment Health J 60, 851–858 (2024). https://doi.org/10.1007/s10597-024-01251-0
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DOI: https://doi.org/10.1007/s10597-024-01251-0