Literature Collection

BACKGROUND: Although collaborative care (CoCM) is an evidence-based and widely adopted model, reimbursement challenges have limited implementation efforts nationwide. In recent years, Medicare and other payers have activated CoCM-specific codes with the primary aim of facilitating financial sustainability. OBJECTIVE: To investigate and describe the experiences of early adopters and explorers of Medicare's CoCM codes. DESIGN AND PARTICIPANTS: Fifteen interviews were conducted between October 2017 and May 2018 with 25 respondents representing 12 health care organizations and 2 payers. Respondents included dually boarded medicine/psychiatry physicians, psychiatrists, primary care physicians (PCPs), psychologists, a registered nurse, administrative staff, and billing staff. APPROACH: A semi-structured interview guide was used to address health care organization characteristics, CoCM services, patient consent, CoCM operational components, and CoCM billing processes. All interviews were recorded, transcribed, coded, and analyzed using a content analysis approach conducted jointly by the research team. KEY RESULTS: Successful billing required buy-in from key, interdisciplinary stakeholders. In planning for CoCM billing implementation, several organizations hired licensed clinical social workers (LICSWs) as behavioral health care managers to maximize billing flexibility. Respondents reported a number of consent-related difficulties, but these were not primary barriers. Workflow changes required for billing the CoCM codes (e.g., tracking cumulative treatment minutes, once-monthly code entry) were described as arduous, but also stimulated creative solutions. Since CoCM codes incorporate the work of the psychiatric consultant into one payment to primary care, organizations employed strategies such as inter-departmental ledger transfers. When challenges arose from variations in the local payer mix, some organizations billed CoCM codes exclusively, while others elected to use a mixture of CoCM and traditional fee-for-service (FFS) codes. For most organizations, it was important to demonstrate financial sustainability from the CoCM codes. CONCLUSIONS: With deliberate planning, persistence, and widespread organizational buy-in, successful utilization of newly available FFS CoCM billing codes is achievable.

BACKGROUND: Despite the risk of negative sequelae from opioid use disorder (OUD) and clinical guidelines for the use of effective medication treatment for OUD (M-OUD), many Veterans Health Administration (VHA) providers and facilities lag in providing M-OUD. An intensive external facilitation intervention may enhance uptake in low-adopting VHA facilities by engaging stakeholders from multiple clinical settings within a facility (e.g., mental health, primary care, pain specialty clinic, substance use disorder clinics). Our study identified pre-intervention determinants of implementation through qualitative interviews, described strategies employed during the first 6 months of intensive external facilitation, and explored patterns of implementation determinants in relation to early outcomes. METHODS: Guided by the integrated-Promoting Action on Research Implementation in Health Services (i-PARIHS) framework, we interviewed stakeholders at low-adopting VHA facilities prior to external facilitation, employed a rapid qualitative analytic process, presented findings during facility visits, and collaboratively created facilitation action plans to achieve goals set by the facilities that would increase M-OUD uptake. The primary outcome was the Substance Use Disorder (SUD)-16, which is a VHA facility-level performance metric consisting of the percent of patients receiving M-OUD among those with an OUD diagnosis. We examined the relationship between pre-implementation factors and 6-month SUD-16 outcomes. RESULTS: Across eight VHA facilities, we interviewed 68 participants. Implementation determinants included barriers and facilitators across innovation, context, and recipients constructs of i-PARIHS. Each facility selected goals based on the qualitative results. At 6 months, two facilities achieved most goals and two facilities demonstrated progress. The SUD-16 from baseline to 6 months significantly improved in two facilities (8.4% increase (95 % confidence interval [CI] 4.4-12.4) and 9.9% increase (95% CI 3.6-16.2), respectively). Six-month implementation outcomes showed that the extent to which M-OUD aligns with existing clinical practices and values was a primary factor at all facilities, with six of eight facilities perceiving it as both a barrier and facilitator. External health system barriers were most challenging for facilities with the smallest change in SUD-16. CONCLUSIONS: Early impacts of a multi-faceted implementation approach demonstrated a strong signal for positively impacting M-OUD prescribing in low-adopting VHA facilities. This signal indicates that external facilitation can influence adoption of M-OUD at the facility level in the early implementation phase. These short-term wins experienced by stakeholders may encourage continued adoption and long-term sustainability M-OUD.

Few primary care patients are screened for substance use. As part of a phased feasibility study examining the implementation of electronic health record-integrated screening with the Tobacco, Alcohol, and Prescription Medication Screening (TAPS) Tool and clinical decision support (CDS) in rural primary care clinics, focus groups were conducted to identify early indicators of success and challenges to screening implementation. Method: Focus groups (n = 6) were conducted with medical assistants (MAs: n = 3: 19 participants) and primary care providers (PCPs: n = 3: 13 participants) approximately one month following screening implementation in three Federally Qualified Health Centers in Maine. Rapid analysis and matrix analysis using Proctor's Taxonomy of Implementation Outcomes were used to explore implementation outcomes. Results: There was consensus that screening is being used, but use of the CDS was lower, in part due to limited positive screens. Fidelity was high among MAs, though discomfort with the CDS surfaced among PCPs, impacting adoption and fidelity. The TAPS Tool's content, credibility and ease of workflow integration were favorably assessed. Challenges include screening solely at annual visits and self-administered screening for certain patients. Conclusions: Results reveal indicators of implementation success and strategies to address challenges to screening for substance use in primary care.

Background: Few primary care patients are screened for substance use. As part of a phased feasibility study examining the implementation of electronic health record-integrated screening with the Tobacco, Alcohol, and Prescription Medication Screening (TAPS) Tool and clinical decision support (CDS) in rural primary care clinics, focus groups were conducted to identify early indicators of success and challenges to screening implementation. Method: Focus groups (n = 6) were conducted with medical assistants (MAs: n = 3: 19 participants) and primary care providers (PCPs: n = 3: 13 participants) approximately one month following screening implementation in three Federally Qualified Health Centers in Maine. Rapid analysis and matrix analysis using Proctor's Taxonomy of Implementation Outcomes were used to explore implementation outcomes. Results: There was consensus that screening is being used, but use of the CDS was lower, in part due to limited positive screens. Fidelity was high among MAs, though discomfort with the CDS surfaced among PCPs, impacting adoption and fidelity. The TAPS Tool's content, credibility and ease of workflow integration were favorably assessed. Challenges include screening solely at annual visits and self-administered screening for certain patients. Conclusions: Results reveal indicators of implementation success and strategies to address challenges to screening for substance use in primary care.