A blueprint for integrated mental health care: Commentary for "Costs of using evidence-based implementation strategies for behavioral health integration in a large primary care system".
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SUBMITTER: Chang TE
PROVIDER: S-EPMC7704473 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveTo describe the cost of using evidence-based implementation strategies for sustained behavioral health integration (BHI) involving population-based screening, assessment, and identification at 25 primary care sites of Kaiser Permanente Washington (2015-2018).Data sources/study settingProject records, surveys, Bureau of Labor Statistics compensation data.Study designLabor and nonlabor costs incurred by three implementation strategies: practice coaching, electronic health records clinical decision support, and performance feedback.Data collection/extraction methodsPersonnel time spent on these strategies was estimated for five broad roles: (a) project leaders and administrative support, (b) practice coaches, (c) clinical decision support programmers, (d) performance metric programmers, and (e) primary care local implementation team members.Principal findingImplementation involved 286 persons, 18 131 person-hours, costing $1 587 139 or $5 per primary care visit with screening or $38 per primary care visit identifying depression, suicidal thoughts and/or alcohol or substance use disorders, in a single year. The majority of person-hours was devoted to project leadership (35%) and practice coaches (34%), and 36% of costs were for the first three sites.ConclusionsWhen spread across patients screened in a single year, BHI implementation costs were well within the range for commonly used diagnostic assessments in primary care (eg, laboratory tests). This suggests that implementation costs alone should not be a substantial barrier to population-based BHI.
| S-EPMC7704468 | biostudies-literature
Project description:BackgroundIntegrating mental health services into primary care settings is complex and challenging. Although facilitation strategies have successfully supported implementation of primary care mental health integration and other complex innovations, we know little about the time required or its cost.ObjectiveTo examine the time and organizational cost of facilitating implementation of primary care mental health integration.DesignDescriptive analysis.ParticipantsOne expert external facilitator and two internal regional facilitators who helped healthcare system stakeholders, e.g., leaders, managers, clinicians, and non-clinical staff, implement primary care mental health integration at eight clinics.InterventionImplementation facilitation tailored to the needs and resources of the setting and its stakeholders.Main measuresWe documented facilitators' and stakeholders' time and types of activities using a structured spreadsheet collected from facilitators on a weekly basis. We obtained travel costs and salary information. We conducted descriptive analysis of time data and estimated organizational cost.Key resultsThe external facilitator devoted 263 h (0.09 FTE), including travel, across all 8 clinics over 28 months. Internal facilitator time varied across networks (1792 h versus 1169 h), as well as clinics. Stakeholder participation time was similar across networks (1280.6 versus 1363.4 person hours) but the number of stakeholders varied (133 versus 199 stakeholders). The organizational cost of providing implementation facilitation also varied across networks ($263,490 versus $258,127). Stakeholder participation accounted for 35% of the cost of facilitation activities in one network and 47% of the cost in the other.ConclusionsAlthough facilitation can improve implementation of primary care mental health integration, it requires substantial organizational investments that may vary by site and implementation effort. Furthermore, the cost of using an external expert to transfer facilitation skills and build capacity for implementation efforts appears to be minimal.
| S-EPMC7174254 | biostudies-literature
Project description:Guidelines recommend screening patients for unhealthy behaviors and mental health concerns. Health risk assessments can systematically identify patient needs and trigger care. This study seeks to evaluate whether primary care practices can routinely implement such assessments into routine care.As part of a cluster-randomized pragmatic trial, 9 diverse primary care practices implemented My Own Health Report (MOHR)-an electronic or paper-based health behavior and mental health assessment and feedback system paired with counseling and goal setting. We observed how practices integrated MOHR into their workflows, what additional practice staff time it required, and what percentage of patients completed a MOHR assessment (Reach).Most practices approached (60%) agreed to adopt MOHR. How they implemented MOHR depended on practice resources, informatics capacity, and patient characteristics. Three practices mailed patients invitations to complete MOHR on the Web, 1 called patients and completed MOHR over the telephone, 1 had patients complete MOHR on paper in the office, and 4 had staff help patients complete MOHR on the Web in the office. Overall, 3,591 patients were approached and 1,782 completed MOHR (Reach = 49.6%). Reach varied by implementation strategy with higher reach when MOHR was completed by staff than by patients (71.2% vs 30.2%, P <.001). No practices were able to sustain the complete MOHR assessment without adaptations after study completion. Fielding MOHR increased staff and clinician time an average of 28 minutes per visit.Primary care practices can implement health behavior and mental health assessments, but counseling patients effectively requires effort. Practices will need more support to implement and sustain assessments.
| S-EPMC4226773 | biostudies-literature
Project description:PurposeWe developed and implemented a new model of collaborative care that includes a triage and referral management system. We present initial implementation metrics using the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) framework.MethodsPrimary care clinicians in 8 practices referred patients with any unmet mental health needs to the Penn Integrated Care program. Assessments were conducted using validated measures. Patients were primarily triaged to collaborative care (26%) or specialty mental health care with active referral management (70%). We conducted 50 qualitative interviews to understand the implementation process and inform program refinement. Our primary outcomes were reach and implementation metrics, including referral and encounter rates derived from the electronic health record.ResultsIn 12 months, 6,124 unique patients were referred. Assessed patients reported symptoms consistent with a range of conditions from mild to moderate depression and anxiety to serious mental illnesses including psychosis and acute suicidal ideation. Among patients enrolled in collaborative care, treatment entailed a mean of 7.2 (SD 5.1) encounters over 78.1 (SD 51.3) days. Remission of symptoms was achieved by 32.6% of patients with depression and 39.5% of patients with anxiety. Stakeholders viewed the program favorably and had concrete suggestions to ensure sustainability.ConclusionsThe Penn Integrated Care program demonstrated broad reach. Implementation was consistent with collaborative care as delivered in seminal studies of the model. Our results provide insight into a model for launching and implementing collaborative care to meet the needs of a diverse group of patients with the full range of mental health conditions seen in primary care.
| S-EPMC7939709 | biostudies-literature
Project description:OBJECTIVE:Examine how behavioral health (BH) integration affects health care costs, emergency department (ED) visits, and inpatient admissions. DATA SOURCES/STUDY SETTING:Truven Health MarketScan Research Databases. STUDY DESIGN:Social network analysis identified "care communities" (providers sharing a high number of patients) and measured BH integration in terms of how connected, or central, BH providers were to other providers in their community. Multivariable generalized linear models adjusting for age, sex, number of prescriptions, and Charlson comorbidity score were used to estimate the relationship between the centrality of BH providers and health care utilization of BH patients. DATA COLLECTION/EXTRACTION METHODS:Used outpatient, inpatient, and pharmacy claims data from six Medicaid plans from 2011 to 2013 to identify study outcomes, comorbidities, providers, and health care encounters. PRINCIPAL FINDINGS:Behavioral health centrality ranged from 0 (no BH providers) to 0.49. Relative to communities at the median BH centrality (0.06), in 2012, BH patients in communities at the 75th percentile of BH centrality (0.31) had 0.2 fewer admissions, 2.1 fewer all-cause ED visits, and accrued $1,947 fewer costs, on average. CONCLUSIONS:Increased behavioral centrality was significantly associated with a reduced number of ED visits, less frequent inpatient admissions, and lower overall health care costs.
| S-EPMC6232391 | biostudies-literature
Project description: Not available
| S-EPMC6463846 | biostudies-literature
Project description:U.S. health care systems are tasked with alleviating the burden of mental health, but are frequently underprepared and lack workforce and resource capacity to deliver services to all in need. Digital mental health interventions (DMHIs) can increase access to evidence-based mental health care. However, DMHIs commonly do not fit into the day-to-day activities of the people who engage with them, resulting in a research-to-practice gap for DMHI implementation. For health care settings, differences between digital and traditional mental health services make alignment and integration challenging. Specialized attention is needed to improve the implementation of DMHIs in health care settings so that these services yield high uptake, engagement, and sustainment. The purpose of this article is to enhance efforts to integrate DMHIs in health care settings by proposing implementation strategies, selected and operationalized based on the discrete strategies established in the Expert Recommendations for Implementing Change project, that align to DMHI-specific barriers in these settings. Guidance is offered in how these strategies can be applied to DMHI implementation across four phases commonly distinguished in implementation science using the Exploration, Preparation, Implementation, Sustainment Framework. Next steps to advance research in this area and improve the research-to-practice gap for implementing DMHIs are recommended. Applying implementation strategies to DMHI implementation will enable psychologists to systematically evaluate this process, which can yield an enhanced understanding of the factors that facilitate implementation success and improve the translation of DMHIs from controlled trials to real-world settings. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
| S-EPMC7709140 | biostudies-literature
Project description:BACKGROUND:Despite their high prevalence and significant burden, mental disorders such as depression remain largely underdiagnosed and undertreated. OBJECTIVE:The aim of the Allillanchu Project was to design, develop, and test an intervention to promote early detection, opportune referral, and access to treatment of patients with mental disorders attending public primary health care (PHC) services in Lima, Peru. METHODS:The project had a multiphase design: formative study, development of intervention components, and implementation. The intervention combined three strategies: training of PHC providers (PHCPs), task shifting the detection and referral of mental disorders, and a mobile health (mHealth) component comprising a screening app followed by motivational and reminder short message service (SMS) to identify at-risk patients. The intervention was implemented by 22 PHCPs from five health centers, working in antenatal care, tuberculosis, chronic diseases, and HIV or AIDS services. RESULTS:Over a period of 9 weeks, from September 2015 to November 2015, 733 patients were screened by the 22 PHCPs during routine consultations, and 762 screening were completed in total. The chronic diseases (49.9%, 380/762) and antenatal care services (36.7%, 380/762) had the higher number of screenings. Time constraints and workload were the main barriers to implementing the screening, whereas the use of technology, training, and supervision of the PHCPs by the research team were identified as facilitators. Of the 733 patients, 21.7% (159/733) screened positively and were advised to seek specialized care. Out of the 159 patients with a positive screening result, 127 had a follow-up interview, 72.4% (92/127) reported seeking specialized care, and 55.1% (70/127) stated seeing a specialist. Both patients and PHCPs recognized the utility of the screening and identified some key challenges to its wider implementation. CONCLUSIONS:The use of a screening app supported by training and supervision is feasible and uncovers a high prevalence of unidentified psychological symptoms in primary care. To increase its sustainability and utility, this procedure can be incorporated into the routine practices of existing health care services, following tailoring to the resources and features of each service. The early detection of psychological symptoms by a PHCP within a regular consultation, followed by adequate advice and support, can lead to a significant percentage of patients accessing specialized care and reducing the treatment gap of mental disorders.
| S-EPMC5893885 | biostudies-other
Project description:Integration of behavioral and general medical care can improve outcomes for individuals with behavioral health conditions-serious mental illness (SMI) and substance use disorder (SUD). However, behavioral health care has historically been segregated from general medical care in many countries. We provide the first population-level evidence on the effects of Medicaid health homes (HH) on behavioral health care service use. Medicaid, a public insurance program in the United States, HHs were created under the 2010 Affordable Care Act to coordinate behavioral and general medical care for enrollees with behavioral health conditions. As of 2016, 16 states had adopted an HH for enrollees with SMI and/or SUD. We use data from the National Survey on Drug Use and Health over the period 2010 to 2016 coupled with a two-way fixed-effects model to estimate HH effects on behavioral health care utilization. We find that HH adoption increases service use among enrollees, although mental health care treatment findings are sensitive to specification. Further, enrollee self-reported health improves post-HH.
| S-EPMC7863583 | biostudies-literature
Project description:Lay abstractChildren with autism frequently experience co-occurring mental health needs. The "Access to Tailored Autism Integrated Care (ATTAIN)" model was co-created with caregivers, pediatric providers, and health care leaders to identify mental health needs and link to mental health care for autistic children. This article describes outcomes from a pilot study of Access to Tailored Autism Integrated Care with 36 pediatric primary care providers from seven clinics within three healthcare systems. Providers participated in an initial Access to Tailored Autism Integrated Care training and received ongoing online support over 4 months with autistic patients ages 4-16 years old. Survey and interview assessments measured provider perceptions of feasibility, acceptability, and intentions to continue using Access to Tailored Autism Integrated Care after the pilot. Providers reported that Access to Tailored Autism Integrated Care was feasible, acceptable, that the initial training was helpful in their implementation but that more specific and tailored implementation support was needed. Results show that Access to Tailored Autism Integrated Care is a promising model to support mental health screening and linkage for children with autism in primary care. Findings provide information on specific areas of the Access to Tailored Autism Integrated Care model that could be benefit from additional refinement to support more widespread use in primary care settings.
| S-EPMC9325918 | biostudies-literature