Many healthcare organizations are struggling to juggle the ACA's mandates of improving patient outcomes, while reducing costs. With a significant segment of US patient populations suffering with acute physical and mental health conditions, this task is nearly unattainable for most health systems. To better manage patients with multiple complex conditions and at the same time reduce costs, numerous health systems have developed and implemented integrated behavioral health programs throughout their organizations. Specifically, the collaborative care model (COCM) which has the most evidence for effectively treating patients with comorbid depression and medical conditions.
Collaborative care is the systematic coordination of primary and behavioral health care. It typically involves the integration of mental health, substance use, and primary care services into various clinical, operational, and financial procedures that emphasize patient-centered and population-based health (Delaney et al., 2017). Studies have revealed that patients who received collaborative care interventions have shown improved outcomes and twelve percent lower overall healthcare costs over a four-year period (Loveland, 2016).
COCM adds care managers (often licensed behavioral health providers) and psychiatric consultants to primary care teams. Care managers provide continuous supporting contact with patients including behavioral activation, follow up and feedback regarding patient progress to primary care teams. Care managers facilitate the engagement of patients in their care through self-management support (Holst et al., 2018).
The collaborative care model also magnifies the reach of psychiatric providers by reducing direct patient services. Instead, psychiatric providers function as caseload consultants providing curbside consultations to primary care providers for patients with behavioral health conditions. Psychiatric consults provide case load reviews with care managers where they review medical team panels. During case load reviews the consultant provides treatment recommendations for the care managers to bring back to the medical teams (Dohl, 2017).
Given the nation's current shortage of behavioral health providers, psychiatric mental health (PMH) nurses can fill the gap as care managers if licensed behavioral health providers are unavailable. PMH nurse's diverse education in medicine and behavioral health make them an ideal fit for integrated services, particularly models grounded in care management and wellness approaches. PMH RN skills in assessment, physical health monitoring, pharmacology, and disease management allow them to seamlessly transition to care management roles in the collaborative care model (Delaney et al., 2017).
Behavioral health provider shortages are particularly apparent among psychiatrists whose numbers continue to decline each year. Many health systems have turned to Advance practice PMH nurse practitioners to fill the positions once held by psychiatrists. PMH nurse practitioners are suited provide psychiatric consultation services. Their scope of practice which includes diagnosis and treatment of an array of mental and physical health conditions, including pharmacotherapy, psychotherapy, monitoring comorbid conditions, and screening for emerging mental and psychical issues. Their skill set is a natural fit for integrated models for complex populations and is recognized as best practice for underserved communities (Delaney et al., 2017).
An organization's ability to maximize health information technology (HIT) in patient care is important step in obtaining a competitive advantage. When it comes to population management it is hard to find an HIT tool more effective than patient registries. Patient registry capability is an essential piece of collaborative care. It helps with the management of a complete patient population. Successful registry utilization supports workflows via reminders for preemptive outreach and follow up for patients who are not responding to care. Registries flag patients whose symptoms have not improved and might benefit from different treatment methods (Bauer et al., 2018).
Registries have multiple functions and add-on capabilities. For optimum population management it is highly recommended that risk stratification levels are added to your existing patient registries. Risk stratification segments patients into separate groups of similar complexity and care needs. It allows providers to identify the right level of care for distinct subgroups by assigning risk levels (high, medium, and low). At the individual level it helps with planning, developing, and implementing an individualized care plan. Patient populations risk stratification allows for care models to be personalized to the needs of patients within specific subgroups. Segmenting populations according to risk level allows health systems to target resources more effectively and at a lower cost (Risk-stratification-action-guide-mar-2019, 2019).
Sanford Health System has developed an innovative risk stratification system worthy emulating. They built a risk stratification system with the aim of identifying patients who would benefit from care management, improving health outcomes, reducing waste, and decreasing unnecessary utilization. Sanford pulled data from patient registries, payer contracts, CMS utilization data, and medical team huddle sheets. From this data they developed an algorithm that produces an adjusted risk stratification score (Swenson, 2019).
Their algorithm is an automated system with a defined criterion that allows it to assign an adjusted risk score ranging from one (low) to seventeen (high complexity). The criteria are based on hospital and ER encounters over the past year, office visit no shows, lab values, screening tools, diagnosis, age, tobacco use, and BMI. Care teams can also modify patients adjusted risk stratification score based on social needs, utilization, health literacy, activation, and behavioral/medical needs. The score allows Sanford to design interventions focus resources on patient populations based on their adjusted risk score (Swenson, 2019).
Healthcare infrastructure disparities are evident in the limited amount of quality medical and mental health resources in many underserved communities. Social determinants of health such as inadequate public transportation, substandard housing, and unhealthy environments have significant effects on the general health of underserved populations (Sommers et al., 2017).
Exasperating the societal troubles faced by underserved communities are the disappearance of agencies that acted as safety nets for their most vulnerable populations. This is especially true with the nation's community mental health centers (MHC). Numerous MHCs are in jeopardy because they rarely receive federal grants or enhanced reimbursement rates to counteract significant levels of uncompensated care. Lack of federal support and subpar reimbursement rates places them in a susceptible position and adds to workforce shortages due to their inability to pay providers and support staff competitive wages (Loveland, 2016).
Collaborative care has the capacity to monitor and track complex patient populations through measurement-based treatment to target, that monitors patient outcomes with standardized measures and modifies treatment when patients are not improving (Bauer et al., 2018). However, many health systems have not realized a return on their investment in collaborative care. In 2015, Medicare started offering care coordination reimbursement codes. Yet, only saw a five percent uptake on these billing codes due to system barriers. Unfortunately, too many health systems must provide direct patient encounters to remain viable. Countless collaborative care programs may be short lived unless insurers recognize care coordination as a reimbursable service (Williams et al., 2019).
Electronic health record systems (EHR) are an essential part of most health systems efforts track patient outcomes and provide population-based care. Effective use of EHRs facilitate teamwork, consultation, task delegation through instant messaging, care management, and population specific data gathering. Nevertheless, many systems lack the capability to support care management and population-based care due to the unavailability of shared care plans and patient registries (Cifuentes et al., 2015).
With the demise of MHCs across the country, federally qualified health centers (FQHC) which highlight integrated models of care have become the de facto gateways to medical and behavioral health services for underserved communities (Jones & Ku, 2015). FQHCs have been the recipient of government funding from both parties because of their ability to provide multiple services within one location. However, FQHCs are unable to fill the void of MHCs for patients with complex mental and physical health conditions. Specifically, MHC intensive services such as PACT (program for assertive community treatment) which offers multi-disciplinary, self-contained clinical team approach delivering long-term intensive care and provides all mental health services in community settings to Medicaid participants (dphhs, 2017).
The expansion of telehealth services is a possible solution to address complex community health problems. Especially, with the accessibility of smart phone technology to most Americans. Telehealth technology has proven to increase access, improve outcomes, and reduce costs. It is estimated that healthcare costs could be reduced by almost 36 billion dollars per year through the efficient use of telehealth services (Kruse et al., 2016).
A significant barrier for widespread implementation of collaborative care programs is that innovation on the ground outpaces healthcare policy (Miller, 2015). Many states are still using fee for service reimbursement methods which prevents the adoption of strategies demonstrated by countless peer reviewed studies of COCM and impacts the sustainability of existing collaborative care models. Fee for service payment models lack incentives for improving quality of care (Vlaanderen et al., 2018). Collaborative care will only be achievable when value-based payment models are universally available to health systems (Nielsen & Levkovich, 2019). Until then most health systems will continue to work against itself while taxpayers and our most susceptible populations pay the price.
Baucher, H. (2019). Rationing of health care in the united states: An inevitable consequence of increasing health care costs. JAMA, 321, 751-752. Link
Bauer, A. M., Hodsdon, S., Bechtel, J. M., & Fortney, J. C. (2018). Applying the principles for digital development: Case study of a smartphone app to support collaborative care for rural patients with posttraumatic stress disorder or bipolar disorder. Journal of Medical Internet Research, 20(6), e10048. Link
Cifuentes, M., Davis, M., Fernald, D., Gunn, R., Dickenson, P., & Cohen, D. (2015). Electronic health record challenges, workarounds, and solutions observed in practices integrating behavioral health and primary care. Journal of the American Board of Family Medicine, 28, 63-72. Link
Delaney, K. R., Naegle, M. A., Valentine, N. M., Antai-Otong, D., Groh, C. J., & Brennaman, L. (2017). The effective use of psychiatric mental health nurses in integrated care: Policy implications for increasing quality and access to care. The Journal of Behavioral Health Services & Research. Link
dphhs. (2017). Program for assertive community treatment (pact). MTDPHHS. Link
Edwards, E. (2017). Assessing changes to medicaid managed care regulations: Facilitating integration of physical and behavioral health care. Link
Holst, A., Ginter, A., Björkelund, C., Hange, D., Petersson, E.-L., Svenningsson, I., Westman, J., André, M., Wikberg, C., Wallin, L., Möller, C., & Svensson, M. (2018). Cost-effectiveness of a care manager collaborative care programme for patients with depression in primary care: Economic evaluation of a pragmatic randomised controlled study. BMJ Open, 8(11), e024741. Link
Johnson, S. M. (2004). The practice of emotionally focused couple therapy. Routledge. Link
Jones, E. B., & Ku, L. (2015). Sharing a playbook: Integrated care in community health centers in the united states. American Journal of Public Health, 105, 2028-2034. Link
Kruse, C., Bouffard, S., Dougherty, M., & Parro, J. (2016). Telemedicine use in rural native american communities in the era of the aca: A systematic literature review. Journal of Medical Systems, 40(6). Link
Loveland, K. (2016). Integrated behavioral health in montana: A baseline assessment of benefits, challenges, and opportunities. Link
Miller, B. F. (2015). When frontline practice innovations are ahead of the health policy community: The example of behavioral health and primary care integration. Journal of the American Board of Family Medicine, 28, 98-101. Link
Nielsen, M., & Levkovich, N. (2019). Promoting health payment reform literacy: Does integrated care save money?. Family, Systems, & Health, 37, 74-83. Link
Risk-stratification-action-guide-mar-2019. (2019). National Association of Community Health Centers. Link
Sommers, B. D., McMurtry, C. L., Blendon, R. J., Benson, J. M., & Sayde, J. M. (2017). Beyond health insurance: Remaining disparities in US health care in the post-ACA era. The Millbank Quarterly, 95, 43-69. Link
Swenson, J. (2019, September 18). Risky business: One health care systems model of risk stratification. Minnesota Department of Health. Link
Vlaanderen, F. P., Tanke, M. A., Bloem, B. R., Faber, M. J., Eijkenaar, F., Schut, F. T., & Jeurissen, P. T. (2018). Design and effects of outcome-based payment models in healthcare: A systematic review. The European Journal of Health Economics, 20(2), 217-232. Link
Williams, M. D., Asiedu, G. B., Finnie, D., Neely, C., Egginton, J., Finney Rutten, L. J., &
Jacobson, R. M. (2019). Sustainable care coordination: A qualitative study of primary care provider,
administrator, and insurer perspectives. BMC Health Services Research, 19(1).
Link
Zurovac, J., Peterson, G. G., Stewart, K. A., Kranker, K., Wells, K., Gilman, B., Day, T., Hoag, S., & Moreno, L. (2019). Effects of a behavioral health and chronic illness care intervention on patient outcomes in primary care practices in the dakotas. Journal of Health Care for the Poor and Underserved, 30, 702-720. Link