Rural primary care (RPC) clinics may face unique barriers to implementing the Collaborative Care Model (CoCM). We used mixed methods to explore RPC staff and practice facilitator (PF) perspectives on CoCM implementation. PFs reported on barriers and facilitators experienced after each monthly meeting with clinics (n = 459 surveys across 23 clinics). Data were analyzed descriptively and informed qualitative interviews with a purposive sample (n = 11) of clinic staff and PFs. Interviews were analyzed using Rapid Assessment Process and triangulated with quantitative data. The most prominent barriers experienced were: (1) the COVID-19 pandemic, (2) limited availability of site staff to participate in implementation activities, and (3) hiring of new CoCM staff. Qualitative data further characterized the ways these barriers uniquely influenced RPC settings and promising implementation strategies. RPC settings face unique challenges to CoCM implementation, but several promising implementation strategies – when tailored to RPC contexts - may help.

Background: Suicide is a leading cause of death in adolescents and adults in the US. Follow-up support delivered when patients return home after an emergency department (ED) or primary care encounter can significantly reduce suicidal ideation and attempts. Two follow-up models to augment usual care including the Safety Planning Intervention have high efficacy: Instrumental Support Calls (ISC) and Caring Contacts (CC) two-way text messages, but they have never been compared to assess which works best. This protocol for the Suicide Prevention Among Recipients of Care (SPARC) Trial aims to determine which model is most effective for adolescents and adults with suicide risk. Methods: The SPARC Trial is a pragmatic randomized controlled trial comparing the effectiveness of ISC versus CC. The sample includes 720 adolescents (12-17 years) and 790 adults (18+ years) who screen positive for suicide risk during an ED or primary care encounter. All participants receive usual care and are randomized 1:1 to ISC or CC. The state suicide hotline delivers both follow-up interventions. The trial is single-masked, with participants unaware of the alternative treatment, and is stratified by adolescents/adults. The primary outcome is suicidal ideation and behavior, measured using the Columbia Suicide Severity Rating Scale (C-SSRS) screener at 6 months. Secondary outcomes include C-SSRS at 12 months, and loneliness, return to crisis care for suicidality, and utilization of outpatient mental health services at 6 and 12 months. Discussion: Directly comparing ISC and CC will determine which follow-up intervention is most effective for suicide prevention in adolescents and adults.

Background Depressive disorders are among the most prevalent mental health conditions; however, significant barriers to treatment access persist. This study examined differences in depression outcomes between younger and older adults in a large-scale implementation demonstration of the collaborative care model (CoCM). Methods Secondary data analysis of a longitudinal, observational implementation demonstration at eight primary care clinics across low-resourced rural or frontier areas of the Western United States. Seven of these clinics were federally qualified health centers. The sample consisted of 3722 younger (18-64 years) and older (65+ years) adult primary care patients diagnosed with unipolar depression. All participants received depression treatment via CoCM, which enhances usual primary care and makes efficient use of specialists by using a behavioral healthcare manager and a psychiatric consultant to support primary care providers. Clinics were followed for up to 27 months. Patients were followed until they completed treatment or dropped out. The Patient Health Questionnaire (PHQ-9) assessed depressive symptoms at baseline (enrollment) and at most follow-up contacts. The primary treatment outcome was a change between a patient's first and last recorded PHQ-9 scores. Results Across both age groups, there was an average overall reduction of 6.9 points on the PHQ-9. Older adults demonstrated a greater decrease in depression scores of 2.06 points (95% CI -2.98 to -1.14, p < 0.001) on the PHQ-9 compared with younger adults. Estimates were robust when adjusting for gender, race, and clinic. Conclusions CoCM resulted in meaningful improvement in depressive symptoms across age groups.

Objective: The Patient Health Questionnaire-9 (PHQ-9) is commonly used to assess depression symptoms, but its associated treatment success criteria (i.e., metrics) are inconsistently defined. The authors aimed to analyze the impact of metric choice on outcomes and discuss implications for clinical practice and research. Methods: Analyses included three overlapping and nonexclusive time cohorts of adult patients with depression treated in 33 organizations between 2008 and 2018. Average depression improvement rates were calculated according to eight metrics. Organization-level rank orders defined by these metrics were calculated and correlated. Results: The 12-month cohort had higher rates of metrics indicating treatment success than did the 3- and 6-month cohorts; the degree of improvement varied by metric, although all organization-level rank orders were highly correlated. Conclusions: Different PHQ-9 treatment metrics are associated with disparate improvement rates. Organization-level rankings defined by different metrics are highly correlated. Consistency of metric use may be more important than specific metric choice.

Back to table of contents Previous article Next article Psychiatry & Integrated CareFull AccessCollaborative Care Fits COVID-19 WorkflowsAnna Ratzliff, M.D., Ph.D., Diane Powers, M.A., M.B.A., Sara Barker, M.P.H.Anna Ratzliff, M.D., Ph.D., Diane Powers, M.A., M.B.A., Sara Barker, M.P.H.Published Online:25 Jun 2020https://doi.org/10.1176/appi.pn.2020.7a32During the COVID-19 public health emergency, health care organizations are quickly learning to adapt, demonstrating how the five key principles of the Collaborative Care Model (CoCM) can fit their new workflows and facilitate ongoing delivery of behavioral health services to patients served in primary care and other medical settings.Patient-Centered Team CareTelehealth, especially via the telephone, has always been a recommended component of CoCM since the original development and testing of the model in the 1990s. Even before recent widespread use of telehealth necessitated by COVID-19, telephone or telehealth contact was often welcomed by patients because it is more convenient and can facilitate more frequent check-ins. Building warm connections is an area where health care organizations are getting creative in response to COVID-19. Some clinics have the behavioral health care manager "sit in" on primary care telehealth appointments where behavioral health is the presenting problem so an immediate connection can be made.Population-Based CareOne adaptation some clinics are using is to examine electronic health record (EHR) data to identify patients with a recent prescription for a psychotropic medication or a new behavioral health diagnosis and have the behavioral health care manager reach out to them by phone for a quick follow-up to determine whether they need care management. Some clinics are using EHR data to identify patients with an existing behavioral health diagnosis seen in the past week for follow-up. Another patient identification strategy involves the behavioral health care manager reviewing the primary care provider's'(PCP) daily or weekly schedule to identify patients with a behavioral health diagnosis who are not engaged in CoCM. During a virtual huddle or messaging between the PCP and behavioral health care manager, they can discuss a virtual warm connection or follow-up visit for these patients.Measurement-Based Treatment to TargetAn aspect of CoCM that needs little, if any, adaptation for COVID-19 workflows is caseload review between the behavioral health care manager and psychiatric consultant and follow-up treatment recommendations to the PCP. While some clinics use face-to-face caseload consultation when both providers are on-site, many CoCM programs have always had this consultation occur via phone with both providers using a registry they can access in real-time to facilitate identification of patients who are not improving as expected. Psychiatric consultants transmit their treatment recommendations to PCPs via the EHR, which does not require adaptation.Evidence-Based TreatmentsBehavioral health care managers help primary care providers optimize pharmacotherapy through the addition of psychotherapeutic interventions like behavioral activation and through proactive follow-up to support medications. When psychotherapy is a component of the treatment plan, use of telehealth is likely the most significant adaptation in response to COVID-19. While this has always been an option, it was previously not often practiced, in part because of limitations on billing for telehealth delivery. The Centers for Medicare and Medicaid Services (CMS) CoCM billing codes have permitted telehealth delivery of services since the codes were released in 2017. In addition, during the COVID-19 public health emergency, many payers, including CMS, have greatly expanded the ability to bill for psychotherapy delivered via telehealth. This is important because many health care organizations use a combination of psychotherapy and CoCM billing codes to fund their care delivery.Accountable CareCoCM leverages scarce behavioral health resources, especially psychiatrists, to inform treatment of a larger population receiving behavioral health care in medical settings than a provider can treat directly. This expands access at a time when more people are expected to need behavioral health services. Research shows the behavioral health care manager does not have to be on-site to provide effective care. CoCM is compatible with telehealth, whether by telephone or videoconferencing, and supports frequent contact with patients.Clinics wishing to adapt CoCM for COVID-19 requirements should use a quality-improvement approach to making changes, either those outlined here or others. They can test the effectiveness of changes to determine which work best for their organization and make adjustments accordingly. ■Anna Ratzliff, M.D., Ph.D., is a professor and co-director of the AIMS Center, director of the Integrated Care Training Program, and director of the Psychiatry Residency Program. Diane Powers, M.A., M.B.A., is co-director of the AIMS Center. Sara Barker, M.P.H., is assistant director for implementation at the AIMS Center. ISSUES NewArchived

Randomized controlled trials have demonstrated that the collaborative care model for depression in primary care is more effective than usual care, but little is known about the effectiveness of this approach in real-world settings. We used patient-reported outcome data from 11,303 patients receiving collaborative care for depression in 135 primary care clinics to examine variations in depression outcomes. The average treatment response across this large sample of clinics was substantially lower than response rates reported in randomized controlled trials, and substantial outcome variation was observed. Patient factors such as initial depression severity, clinic factors such as the number of years of collaborative care practice, and the degree of implementation support received were associated with depression outcomes at follow-up. Our findings suggest that the level of implementation support could be an important influence on the effectiveness of collaborative care model programs.

Introduction The gap between depression treatment needs and the available mental health workforce is particularly large in rural areas. Collaborative care (CoCM) is an evidence-based approach that leverages limited mental health specialists for maximum population effect. This study evaluates depression treatment outcomes, clinical processes of care, and primary care provider experiences for CoCM implementation in 8 rural clinics treating low-income patients. Method We used CoCM registry data to analyze depression response and remission then used logistic regression to model variance in depression outcomes. Primary care providers reported their experiences with this practice change 18 months following program launch. Results Participating clinics enrolled 5,187 adult patients, approximately 15% of the adult patient population. Mean PHQ-9 depression score was 16.1 at baseline and 10.9 at last individual measurement, a statistically and clinically significant improvement (SD6.7; 95% CI [4.9, 5.3]). Suicidal ideation also reduced significantly. Multivariate logistic regression predicted the probability of depression response and remission after controlling for several demographic attributes and processes of care, showing a significant amount of variance in outcomes could be explained by clinic, length of time in treatment, and age. Primary care providers reported positive experiences overall. Discussion Three quarters of participating primary care clinics, adapting CoCM for limited resource settings, exceeded depression response outcomes reported in a controlled research trial and mirrored results of large-scale quality improvement implementations. Future research should examine quality improvement strategies to address clinic-level variation and sustain improvements in clinical outcomes achieved. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Tools to monitor implementation progress could facilitate scale-up of effective treatments. Most treatment for depression, a common and disabling condition, is provided in primary care settings. Collaborative Care Management (CoCM) is an evidence-based model for treating common mental health conditions, including depression, in this setting; yet, it is not widely implemented. The Stages of Implementation Completion (SIC) was adapted for CoCM and piloted in eight rural primary care clinics serving adults challenged by low-income status. The CoCM-SIC accurately assessed implementation effectiveness and detected site variations in performance, suggesting key implementation activities to aid future scale-ups of CoCM for diverse populations.

Background The purpose of this study was to identify the effects of Collaborative Care on rural Native American and Alaska Native (AI/AN) patients. Methods Collaborative Care was implemented in three AI/AN serving clinics. Clinic staff participated in training and coaching designed to facilitate practice change. We followed clinics for 2 years to observe improvements in depression treatment and to examine treatment outcomes for enrolled patients. Collaborative Care elements included universal screening for depression, evidence-based treatment to target, use of behavioral health care managers to deliver the intervention, use of psychiatric consultants to provide caseload consultation, and quality improvement tracking to improve and maintain outcomes. We used t-tests to evaluate the main effects of Collaborative Care and used multiple linear regression to better understand the predictors of success. We also collected qualitative data from members of the Collaborative Care clinical team about their experience. Results The clinics participated in training and practice coaching to implement Collaborative Care for depressed patients. Depression response (50% or greater reduction in depression symptoms as measured by the PHQ-9) and remission (PHQ-9 score less than 5) rates were equivalent in AI/AN patients as compared with White patients in the same clinics. Significant predictors of positive treatment outcome include only one depression treatment episodes during the study and more follow-up visits per patient. Clinicians were overall positive about their experience and the effect on patient care in their clinic. Conclusions This project showed that it is possible to deliver Collaborative Care to AI/AN patients via primary care settings in rural areas.

Lactation consultants working with mothers and babies in different settings-whether hospital, clinic, home or support group-may find themselves not understanding the challenges and dissimilarities that are part of a distinctive lactation setting. In an effort to even the playing field, allowing for a bird's-eye view of inpatient and outpatient work life issues, this is an article designed to hone in on the variances that confront LC's depending upon where they interface with the breastfeeding dyad.

Back to table of contents Previous article Next article Psychiatry & Integrated CareFull AccessSustaining Practice Change: How to Prevent Organizational RelapseDiane Powers, M.B.A., M.A.Diane PowersSearch for more papers by this author, M.B.A., M.A.Published Online:8 Aug 2019https://doi.org/10.1176/appi.pn.2019.8b35AbstractImplementation of a high-quality collaborative care program can be challenging but sustaining that program can be even more difficult. In this month’s column, Diane Powers, M.B.A., M.A., writes about lessons learned from developing a sustainment intervention as part of a collaborative care implementation in the rural West. —Jürgen Unützer, M.D., M.P.H.Over the past 15 years, the University of Washington AIMS Center has learned a lot about what it takes to implement a multicomponent health care innovation. One of the key lessons learned from efforts to implement the Collaborative Care Model (CoCM)—an approach that integrates behavioral health care and primary care—is that it can be more difficult to sustain practice change than to implement it.Sustaining innovative health care programs can be particularly challenging in rural areas, where there are fewer health care providers as well as technological limitations, such as a lack of high-speed internet.A few years ago, the AIMS Center provided CoCM training, practice coaching, and program evaluation for primary care clinics serving low-income individuals living in health care provider shortage areas and/or medically underserved areas of the rural West. Through conversations with employees at these clinics, several best practices for sustaining practice change emerged:Sustainment Starts Before ImplementationDevelop a clear vision and goals for the practice change. The first step in implementing a practice change is to develop a clear rationale for the practice change being implemented and clear, concrete goals. Engaging all stakeholders, including clinicians, support staff, clinic leadership, board of directors, and patients, in developing the vision and goals increases the likelihood of employee alignment with the practice change and strengthens shared accountability to patients and other stakeholders.The goals established during the planning stage are intended as a starting point that clinic leadership can use to measure progress toward achieving their behavioral health integration goals. These goals should evolve over time.Develop a business case for integrating behavioral health care. Financing is often the biggest barrier to sustainment. Available financing strategies include external start-up funding, Centers for Medicare and Medicaid Services billing codes, and support from commercial payers. Regardless of the funding sources, it is crucial that clinics develop a business case for integrating behavioral health care and primary care that is at least revenue neutral.“[T]he biggest [revenue] hurdle to overcome is that the care manager can’t bill, so they’re not an income-generating position,” explained an employee at one of the clinics participating in the CoCM program. “We can look at other programs in our organization that are generating revenue to help us out, but I would say [billing is] the biggest hurdle.”Sustainment Is a ProcessEstablish measurable treatment targets. Perhaps the most important component of CoCM is measurement-based treatment to target. This means measuring patient-level clinical outcomes and using this information to make proactive changes in treatment when patients are not improving. While we usually think of this in the context of individual patient care, it also applies to organizational sustainment. That is, the organization should measure aggregate clinical outcomes and evidence-based processes of care (for example, proportion of patients discussed with psychiatric consultant) and make program adjustments if organizational goals are not being met.Be prepared for staff turnover. One of the biggest threats to sustainment is staff turnover, especially in rural areas where workforce shortages are most acute. “You have a time when everything is running smoothly, and … then the medical team changes due to attrition and you have to start the process all over again,” said an employee at one of the clinics participating in the CoCM program.To address this issue, staff at this clinic built trainings on CoCM into the onboarding process for new medical providers in all three roles—care managers, primary care providers, and psychiatric consultants.Establish a process for continuous quality improvement. For practice change to become institutionalized, a continuous quality improvement process is necessary. This involves regularly reviewing process and outcome metrics, identifying areas for improvement, implementing interventions to make those improvements, and evaluating the outcomes.“It’s particularly useful to have … very clear standards, expectations, and trackable data. When [processes] aren’t working, there needs to be troubleshooting [to pinpoint the problem area],” said leaders at one of the clinics participating in the CoCM program. Continuous quality improvement has “forced examination of policies and procedures everywhere [from] clinical flow to human resources. It’s been a very useful driver of overall, organizational improvement.”Clinics implementing CoCM often assume that effective implementation seamlessly translates to effective sustainment. But preventing organizational relapse requires planning for sustainment during the implementation planning phase and ongoing review of processes and outcomes after implementation. ■More resources on the Collaborative Care Model, including how to implement the model and get paid for services, are posted here.Diane Powers, M.B.A., M.A., is co-director of the AIMS Center, dedicated to “advancing integrated mental health solutions,” at the University of Washington Department of Psychiatry & Behavioral Sciences. Jürgen Unützer, M.D., M.P.H., is a professor and chair of psychiatry and behavioral sciences at the University of Washington and founder of the AIMS Center. ISSUES NewArchived

Nipple shields have a long and somewhat controversial history. Nearly every published article in recent years reports positive breastfeeding outcomes for mother/baby dyads who used a nipple shield. Its use may be warranted if infants have sucking difficulties, or are having problems latching to flat or inverted nipples. In addition, they can be useful for mothers who dread breastfeeding because of nipple pain, are experiencing hyperlactation, or have histories of sexual abuse. It is time to recognize the possible uses for nipple shields that can help create favorable results for breastfeeding couplets.

Breast abscesses appear to be occurring more frequently in both our practices, perhaps because of the presence of "super bugs" in our evolving environment. Understanding how quickly breast pain can fulminate into an invasive abscess allows for healthcare providers (HCP) to be vigilant in follow-up with those women presenting with breast fullness, without pain or fever, when they have either recently been treated for mastitis or are currently taking antibiotics for mastitis.

OBJECTIVES:We evaluated a quality improvement program with a pay-for-performance (P4P) incentive in a population-focused, integrated care program for safety-net patients in 29 community health clinics.METHODS:We used a quasi-experimental design with 1673 depressed adults before and 6304 adults after the implementation of the P4P program. Survival analyses examined the time to improvement in depression before and after implementation of the P4P program, with adjustments for patient characteristics and clustering by health care organization.RESULTS:Program participants had high levels of depression, other psychiatric and substance abuse problems, and social adversity. After implementation of the P4P incentive program, participants were more likely to experience timely follow-up, and the time to depression improvement was significantly reduced. The hazard ratio for achieving treatment response was 1.73 (95% confidence interval=1.39, 2.14) after the P4P program implementation compared with pre-program implementation.CONCLUSIONS:Although this quasi-experiment cannot prove that the P4P initiative directly caused improved patient outcomes, our analyses strongly suggest that when key quality indicators are tracked and a substantial portion of payment is tied to such quality indicators, the effectiveness of care for safety-net populations can be substantially improved.

This study evaluated a mail and telephone intervention to improve breast health behaviors while maintaining quality of life. Women recruited from the general public were randomized to a stepped-intensity intervention consisting of mailings, telephone calls, and counseling (if requested or appropriate given a woman's genetic risk for breast cancer) or to a delayed treatment control group. Outcomes (mammography screening and quality of life) were measured at baseline in a telephone survey and again at a 12-month follow-up period. Women in the intervention group significantly increased screening mammography uptake by 12% and quality of life by 5.3 scale points compared to control participants. Changes in knowledge of breast cancer, genetic testing, and cancer worry all significantly predicted intervention changes. This successful intervention can help women make better breast health choices without causing increased worry.

OBJECTIVE To determine the long-term effects on total healthcare costs of the Improving Mood: Promoting Access to Collaborative Treatment (IMPACT) program for late-life depression compared with usual care. STUDY DESIGN Randomized controlled trial with enrollment from July 1999 through August 2001. The IMPACT trial, conducted in primary care practices in 8 delivery organizations across the United States, enrolled 1801 depressed primary care patients 60 years or older. Data are from the 2 IMPACT sites for which 4-year cost data were available. Trial enrollment across these 2 health maintenance organizations was 551 patients. METHODS Participants were randomly assigned to the IMPACT intervention (n = 279) or to usual primary care (n = 272). Intervention patients had access to a depression care manager who provided education, behavioral activation, support of antidepressant medication management prescribed by their regular primary care provider, and problem-solving treatment in primary care for up to 12 months. Care managers were supervised by a psychiatrist and a primary care provider. The main outcome measures were healthcare costs during 4 years. RESULTS IMPACT participants had lower mean total healthcare costs ($29 422; 95% confidence interval, $26 479-$32 365) than usual care patients ($32 785; 95% confidence interval, $27 648-$37 921) during 4 years. Results of a bootstrap analysis suggested an 87% probability that the IMPACT program was associated with lower healthcare costs than usual care. CONCLUSION Compared with usual primary care, the IMPACT program is associated with a high probability of lower total healthcare costs during a 4-year period.