Population-based implementation of behavioral health detection and treatment into primary care: early data from New York state.

BACKGROUND: The Collaborative Care Model is a well-established, evidence-based approach to treating depression and other common behavioral health conditions in primary care settings. Despite a robust evidence base, real world implementation of Collaborative Care has been limited and very slow. The goal of this analysis is to better describe and understand the progression of implementation in the largest state-led Collaborative Care program in the nation-the New York State Collaborative Care Medicaid Program. Data are presented using the RE-AIM model, examining the proportion of clinics in each of the model's five steps from 2014 to 2019. METHODS: We used the RE-AIM model to shape our data presentation, focusing on the proportion of clinics moving into each of the five steps of this model over the years of implementation. Data sources included: a New York State Office of Mental Health clinic tracking database, billing applications, quarterly reports, and Medicaid claims. RESULTS: A total of 84% of clinics with which OMH had an initial contact [n = 611clinics (377 FQHCs and 234 non-FQHCs)] received some form of training and technical assistance. Of those, 51% went on to complete a billing application, 41% reported quarterly data at least once, and 20% were able to successfully bill Medicaid. Of clinics that reported data prior to the first quarter of 2019, 79% (n = 130) maintained Collaborative Care for 1 year or more. The receipt of any training and technical assistance was significantly associated with our implementation indices: (completed billing application, data reporting, billing Medicaid, and maintaining Collaborative Care). The average percent of patient improvement for depression and anxiety across 155 clinics that had at least one quarter of data was 44.81%. Training and technical assistance source (Office of Mental Health, another source, or both) and intensity (high/low) were significantly related to implementation indices and were observed in FQHC versus non-FQHC samples. CONCLUSIONS: Offering Collaborative Care training and technical assistance, particularly high intensity training and technical assistance, increases the likelihood of implementation. Other state-wide organizations might consider the provision of training and technical assistance when assisting clinics to implement Collaborative Care.

Pharmacogenomics Implementation Training Improves Self-Efficacy and Competency to Drive Adoption in Clinical Practice.

Background: Administration of pharmacogenomics (PGx) testing in clinical practice has been suboptimal, presumably due to lack of PGx education. Here, we aim to evaluate the standpoint of PGx testing among a diverse group of healthcare professionals (HCPs) through conducting surveys before and after training. Materials and Methods: Training modules were designed to cover three key learning objectives and deployed in five sections. A pre- and post-training survey questionnaire was used to evaluate participants' self-assessments on employing PGx in clinical practice. Results and Conclusion: Out of all enrollments, 102 survey responses were collected. Overall, respondents agree on the benefits of PGx testing, but have inadequate self-efficacy and competency in utilizing PGx data. Our results show that a 90 min long training significantly improves these, and could lead to greater anticipation of PGx adoption.

Efficacy of a training programme to support the application of the guideline evidence-based health information: study protocol of a randomised controlled trial.

BACKGROUND: The evidence-based guideline entitled guideline evidence-based health information emerged from the German Network for Evidence-based Medicine (DNEbM) and was published in February 2017. The guideline addresses providers of health information and its goal is to improve the quality of health information. In addition, we explored the competences of providers of health information and developed a training programme. The aim of this study is to evaluate the efficacy of a training programme addressing providers of health information to support the application of the guideline evidence-based health information. We expected the intervention to improve the quality of health information in comparison to the provision of the guideline on its own. METHODS/DESIGN: The trial uses a superiority randomised control group design with 10 months' follow-up. Twenty-six providers of health information (groups with up to ten members) will be enrolled to compare the intervention (guideline and training programme) with usual care (a publicly available guideline). The 5-day training programme comprises an evidence-based medicine training module and a module to prepare the application of the guideline. The primary outcome parameter is the quality of the health information. Quality is operationalised as the extent of adherence to the guideline's recommendations. Each provider will prepare a single health information item informing a health-related decision on a topic freely chosen before randomisation. The quality of this information will be rated using the Mapping Health Information Quality (MAPPinfo) Checklist. An accompanying process evaluation will then be conducted. DISCUSSION: The study results should show whether the efficacy of the intervention justifies implementation of the training programme to enhance health information developers' competences in evidence-based medicine and to ensure high-quality evidence-based health information (EBHI) in the long term. TRIAL REGISTRATION: ISRCTN registry, ID: ISRCTN96941060. Registered on 7 March 2019.