Lessons Learned on Observed-to-Expected Analysis Using Spontaneous Reports During Mass Vaccination.

During the COVID-19 vaccination campaign, observed-to-expected analysis was used by the European Medicines Agency to contextualise data from spontaneous reports to generate real-time evidence on emerging safety concerns that may impact the benefit-risk profile of COVID-19 vaccines. Observed-to-expected analysis compares the number of cases spontaneously reported for an event of interest after vaccination ('observed') to the 'expected' number of cases anticipated to occur in the same number of individuals had they not been vaccinated. Observed-to-expected analysis is a robust methodology that relies on several assumptions that have been described in regulatory guidelines and scientific literature. The use of observed-to-expected analysis to support the safety monitoring of COVID-19 vaccines has provided valuable insights and lessons on its design and interpretability, which could prove to be beneficial in future analyses. When undertaking an observed-to-expected analysis within the context of safety monitoring, several aspects need attention. In particular, we emphasise the importance of stratified and harmonised data collection both for vaccine exposure and spontaneous reporting data, the need for alignment between coding dictionaries and the crucial role of accurate background incidence rates for adverse events of special interest. While these considerations and recommendations were determined in the context of the COVID-19 mass vaccination setting, they are generalisable in principle.

Hepatitis C community prevalence is over-estimated: a prospective, birth cohort study.

BACKGROUND: Hepatitis C virus infection is often asymptomatic, and many patients may be unaware they are infected. Community-based, birth cohort screening has been advocated to identify these patients. It has been estimated that 0.7-1% of individuals born between 1965 and 1985 in Ireland are infected. The cost-effectiveness of screening is critically dependent on the population prevalence. AIMS: The aim is to determine the community prevalence of hepatitis C virus infection in the birth cohort 1965-1985. METHODS: Residual serum samples from blood tests ordered by community general practitioners were anonymised and analysed for the presence of hepatitis C antibody ± antigen. Twelve large general hospitals throughout the country participated. RESULTS: A total of 14,320 samples were tested, 9347 of which were from the birth cohort 1965-1985. Seventy-two samples were positive for hepatitis C antibody of which 12 were positive for hepatitis C antigen (17%). The overall prevalence of hepatitis C antigen in the birth cohort was 0.09%. A higher prevalence (0.39%) was identified in males in two urban areas of Dublin. CONCLUSIONS: Hepatitis C virus seroprevalence was much lower than previously estimated. The proportion of antibody positive patients with hepatitis C antigen was also lower than expected suggesting the effects of treatment and/or high spontaneous viral clearance. Universal birth cohort screening is unlikely to be cost-effective. Targeted birth cohort screening in high prevalence areas could be considered.

Safety Monitoring of COVID-19 Vaccines: Perspective from the European Medicines Agency.

Prior to deployment of coronavirus disease 2019 (COVID-19) vaccines in the European Union in 2021, a high vaccine uptake leading to an unprecedented volume of safety data from spontaneous reports and real-world evidence, was anticipated. The European Medicines Agency (EMA) implemented specific activities to ensure enhanced monitoring of emerging vaccine safety information, including intensive monitoring of reports of adverse events of special interest and the use of observed-to-expected analyses. The EMA also commissioned several independent observational studies using a large network of electronic healthcare databases and primary data collection via mobile and web-based applications. This preparedness was key for two high-profile safety signals: thrombosis with thrombocytopenia syndrome (TTS), a new clinical entity associated with adenovirus-vectored vaccines, and myocarditis/pericarditis with messenger RNA vaccines. With no existing case definition nor background rates, the signal of TTS posed particular challenges. Nevertheless, it was rapidly identified, evaluated, contextualized and the risk minimized thanks to close surveillance and an efficient use of available evidence, clinical expertise and flexible regulatory tools. The two signals illustrated the complementarity between spontaneous and real-world data, the former enabling rapid risk identification and communication, the latter enabling further characterization. The COVID-19 pandemic has tremendously enhanced the development of tools and methods to harness the unprecedented volume of safety data generated for the vaccines. Areas for further improvement include the need for better and harmonized data collection across Member States (e.g., stratified vaccine exposure) to support signal evaluation in all population groups, risk contextualization, and safety communication.

Interventions to support the mental health and well-being of front-line healthcare workers in hospitals during pandemics: an evidence review and synthesis.

OBJECTIVE: Pandemics negatively impact healthcare workers' (HCW's) mental health and well-being causing additional feelings of anxiety, depression, moral distress and post-traumatic stress. A comprehensive review and evidence synthesis of HCW's mental health and well-being interventions through pandemics reporting mental health outcomes was conducted addressing two questions: (1) What mental health support interventions have been reported in recent pandemics, and have they been effective in improving the mental health and well-being of HCWs? (2) Have any mobile apps been designed and implemented to support HCWs' mental health and well-being during pandemics? DESIGN: A narrative evidence synthesis was conducted using Cochrane criteria for synthesising and presenting findings when systematic review and pooling data for statistical analysis are not suitable due to the heterogeneity of the studies. DATA SOURCES: Evidence summary resources, bibliographic databases, grey literature sources, clinical trial registries and protocol registries were searched. ELIGIBILITY CRITERIA: Subject heading terms and keywords covering three key concepts were searched: SARS-CoV-2 coronavirus (or similar infectious diseases) epidemics, health workforce and mental health support interventions. Searches were limited to English-language items published from 1 January 2000 to 14 June 2022. No publication-type limit was used. DATA EXTRACTION AND SYNTHESIS: Two authors determined eligibility and extracted data from identified manuscripts. Data was synthesised into tables and refined by coauthors. RESULTS: 2694 studies were identified and 27 papers were included. Interventions were directed at individuals and/or organisations and most were COVID-19 focused. Interventions had some positive impacts on HCW's mental health and well-being, but variable study quality, low sample sizes and lack of control conditions were limitations. Two mobile apps were identified with mixed outcomes. CONCLUSION: HCW interventions were rapidly designed and implemented with few comprehensively described or evaluated. Tailored interventions that respond to HCWs' needs using experience co-design for mental health and well-being are required with process and outcome evaluation.

Mental health symptoms in Australian general practitioners during the COVID-19 pandemic.

BACKGROUND: General practitioners (GPs) play a central role during the COVID-19 pandemic, and yet awareness of their mental health is limited. METHODS: A nationwide online survey of self-identified frontline healthcare workers was conducted between 27 August and 23 October 2020. Participants were recruited through health and professional organisations, colleges, universities, government contacts, and media. A subset of the findings on GPs and hospital medical staff (HMS) was used for this study. RESULTS: Of 9518 responses, there were 389 (4%) GPs and 1966 (21%) HMS. Compared with HMS, GPs received significantly less training on personal protective equipment usage or care for COVID-19 patients, and less support or communication within their workplace. GPs were significantly more concerned about household income, disease transmission to family and being blamed by colleagues if they became infected, all of which were associated with worse psychological outcomes. Significantly more GPs reported burnout, and experienced moderate-to-severe emotional exhaustion than HMS. Both groups used similar coping strategies, except fewer GPs than HMS used digital health applications or increased alcohol consumption. Less than 25% of either group sought professional help. CONCLUSIONS: GPs are vital in our healthcare systems, yet face unique workplace challenges and mental health stressors during the pandemic. Targeted workplace and psychological support is essential to protect wellbeing among the primary care workforce.

Rapid Design and Delivery of an Experience-Based Co-designed Mobile App to Support the Mental Health Needs of Health Care Workers Affected by the COVID-19 Pandemic: Impact Evaluation Protocol.

BACKGROUND: The COVID-19 pandemic has highlighted the importance of health care workers' mental health and well-being for the successful function of the health care system. Few targeted digital tools exist to support the mental health of hospital-based health care workers, and none of them appear to have been led and co-designed by health care workers. OBJECTIVE: RMHive is being led and developed by health care workers using experience-based co-design (EBCD) processes as a mobile app to support the mental health challenges posed by the COVID-19 pandemic to health care workers. We present a protocol for the impact evaluation for the rapid design and delivery of the RMHive mobile app. METHODS: The impact evaluation will adopt a mixed methods design. Qualitative data from photo interviews undertaken with up to 30 health care workers and semistructured interviews conducted with up to 30 governance stakeholders will be integrated with qualitative and quantitative user analytics data and user-generated demographic and mental health data entered into the app. Analyses will address three evaluation questions related to engagement with the mobile app, implementation and integration of the app, and the impact of the app on individual mental health outcomes. The design and development will be described using the Mobile Health Evidence Reporting and Assessment guidelines. Implementation of the app will be evaluated using normalization process theory to analyze qualitative data from interviews combined with text and video analysis from the semistructured interviews. Mental health impacts will be assessed using the total score of the 4-item Patient Health Questionnaire (PHQ4) and subscale scores for the 2-item Patient Health Questionnaire for depression and the 2-item Generalized Anxiety Scale for anxiety. The PHQ4 will be completed at baseline and at 14 and 28 days. RESULTS: The anticipated average use period of the app is 30 days. The rapid design will occur over four months using EBCD to collect qualitative data and develop app content. The impact evaluation will monitor outcome data for up to 12 weeks following hospital-wide release of the minimal viable product release. The study received funding and ethics approvals in June 2020. Outcome data is expected to be available in March 2021, and the impact evaluation is expected to be published mid-2021. CONCLUSIONS: The impact evaluation will examine the rapid design, development, and implementation of the RMHive app and its impact on mental health outcomes for health care workers. Findings from the impact evaluation will provide guidance for the integration of EBCD in rapid design and implementation processes. The evaluation will also inform future development and rollout of the app to support the mental health needs of hospital-based health care workers more widely. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/26168.

The Role of Relational Knowing in Advance Care Planning.

Medical decision making when a patient cannot participate is complicated by the question of whose voice should be heard. The most common answer to this question is that "autonomy" is paramount, and therefore it is the voice of the unwell person that should be given priority. Advance care planning processes and practices seek to capture this sentiment and to allow treatment preferences to be documented and decision makers to be nominated. Despite good intentions, advance care planning is often deficient because it is unable to facilitate a relational approach to decision making in cases when the patient's competence is reduced. In this article we present findings from a study of the ways in which older people and their significant others understand decision making in such circumstances. Critical to the participants' understanding was the emergent concept of "relational knowing," a concept that is poorly articulated in the advance care planning literature. Our findings suggest that the dominant understanding of decision making in conditions of impaired competence is incomplete and obscures much of what matters to people. We conclude that, having recognized a broader set of ethical concerns, it is necessary to develop a relational and narrative based approach that applies in appropriate settings.