Using A Pharmacy-Based Intervention To Improve Antipsychotic Adherence Among Patients With Serious Mental Illness

Background: Similar to patients with other chronic disorders, patients with serious mental illness (SMI) are often poorly adherent with prescribed medications. Objective: We conducted a randomized controlled trial examining the effectiveness of a pharmacy-based intervention (Meds-Help) in increasing antipsychotic medication adherence among Department of Veterans Affairs (VA) patients with SMI. We also examined the impact of Meds-Help on psychiatric symptoms, quality of life, and satisfaction with care. Methods: We enrolled 118 patients from 4 VA facilities with schizophrenia, schizoaffective, or bipolar disorder who were on long-term antipsychotics but had antipsychotic medication possession ratios (MPRs) Results: Prior to enrollment, Meds-Help and UC patients had mean antipsychotic MPRs of 0.54 and 0.55, respectively. At 6 months, mean MPRs were 0.91 for Meds-Help and 0.64 for UC patients; at 12 months, they were 0.86 for Meds-Help and 0.62 for UC patients. In multivariate analyses adjusting for patient factors, Meds-Help patients had significantly higher MPRs at 6 and 12 months (P \u3c .0001). There were no significant differences between groups in PANSS, QWB, or CSQ-8 scores, but power to detect small effects was limited. Conclusions: Congruent with prior studies of patients with other disorders, a practical pharmacy-based intervention increased antipsychotic adherence among patients with SMI. However, SMI patients may require additional care management components to improve outcomes

Development and investigation of a decision support system to facilitate shared decision making in community mental health

Background. Electronic decision support systems (EDSS) using a shared decision making framework may be a new technology to facilitate service planning in public sector mental health care. The case management context is a ripe testing ground for such technology, given the quality of life decisions involved in case management. Honoring consumer preferences for services has been associated with improvements in outcomes in decades of studies. Methods. Three studies were conducted from one single cluster-randomized experiment. An analysis of the usability of the EDSS was conducted using electronic questionnaires and the automated recording of user interaction with the systems (N=40 dyads). The primary experiment examined the effect of the EDSS on case managers‘ and clients‘ satisfaction with the care planning process, and on client recall of their care plans three days later (n=80 dyads). OLS regression with adjustment for intra-worker clustering was used to test for differences in satisfaction scores (on a five point scale) and knowledge. A qualitative investigation was embedded in the larger study to better understand how shared decision making works in this clinical context (N=16 dyads). Results. This set of studies has demonstrated that consumers can build their own care plans, and edit them with their case managers. The experimental results indicated that case managers in the experimental group were significantly more satisfied with the EDSS process than in the control group (mean score=4.0 (SD .54) versus 3.3 (SD .53)). There were no differences between the client EDSS and control groups regarding satisfaction, but the EDSS participants were significantly more knowledgeable about the contents of their care plans 3 days later (mean proportion of plan goals recalled=75% (SD=28%) versus 57% (SD=32%)). The qualitative study indicated that the differences between the two groups were that the dyads in the EDSS group had more frequent (worker-led) discussions of areas of disagreement, role definition, and negotiation of decisions. Case managers also reported learning more about their clients using the process. Conclusions and Implications. The amplification of client preferences using the EDSS was clearly present. Further research is needed to understand if this insight transfers to action longitudinally

COVID-19 Impact on Diagnostic Innovations: Emerging Trends and Implications

Diagnostic testing remains the backbone of the coronavirus disease 2019 (COVID-19) response, supporting containment efforts to mitigate the outbreak. The severity of this crisis and increasing capacity issues associated with polymerase chain reaction (PCR)-based testing, accelerated the development of diagnostic solutions to meet demands for mass testing. The National Institute for Health Research (NIHR) Innovation Observatory is the national horizon scanning organization in England. Since March, the Innovation Observatory has applied advanced horizon scanning methodologies and tools to compile a diagnostic landscape, based upon data captured for molecular (MDx) and immunological (IDx) based diagnostics (commercialized/in development), for the diagnosis of SARS-CoV-2. In total we identified and tracked 1608 diagnostics, produced by 1045 developers across 54 countries. Our dataset shows the speed and scale in which diagnostics were produced and provides insights into key periods of development and shifts in trends between MDx and IDx solutions as the pandemic progressed. Stakeholders worldwide required timely and detailed intelligence to respond to major challenges, including testing capacity and regulatory issues. Our intelligence assisted UK stakeholders with assessing priorities and mitigation options throughout the pandemic. Here we present the global evolution of diagnostic innovations devised to meet changing needs, their regulation and trends across geographical regions, providing invaluable insights into the complexity of the COVID-19 phenomena