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The associated morbidity and mortality from COVID-19 and the public health response to prevent the spread of the virus has repeatedly demonstrated the significant impact of social determinants of health (SDoH) and social inequities on health outcomes. Social prescriptions are interventions aimed at tackling SDoH. In 2019, NHS-England committed to support the use of social prescribing across England. NHS-England commissioned the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) sentinel network to monitor the distribution of social prescribing services within English primary care and, within that, monitor the impact of the COVID-19 pandemic response on SDoH. To track incidence of people presenting to primary care with SDoH-related issues, we implemented an ontological approach to curate SDoH indicators in computerised medical records (CMR) using the Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT). These indicators were then extracted from the RCGP-RSC sentinel network database to present weekly incidence rates per 10,000 people to assess the impact of the pandemic on these SDoH. Pre- versus peri-pandemic, we observed an increase in the recording of several of our SDoH indicators;namely issues related to homelessness, unemployment, mental health, harmful substance use and financial difficulties. As far as we are aware, this is the first time that routinely collected primary care CMR data has been utilised for the monitoring and surveillance of SDoH and demonstrates the feasibility of this approach for future surveillance. © 2022, Springer Nature Switzerland AG.
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Background: Internet of Things (IoT) innovations such as wearables and sensors promise improved health outcomes and service efficiencies. Yet, most applications remain experimental with little routine use in health and care settings. We sought to examine the multiple interacting influences on IoT implementation, spread and scale-up, including the role of regional innovation ‘ecosystems' and the impact of the COVID-19 context. Methods: Qualitative study involving 20 participants with clinical, entrepreneurial and broader innovation experience in 18 in-depth interviews, focusing primarily on heart monitoring and assistive technology applications. Data analysis was informed by the NASSS (non-adoption, abandonment, scale-up, spread, sustainability) framework. Results: Interviewees discussed multiple tensions and trade-offs, including lack of organisational capacity for routine IoT use, limited ability to receive and interpret data, complex procurement and governance processes, and risk of health disparities and inequalities without system support and funding. Although the pandemic highlighted opportunities for IoT use, it was unclear whether these would be sustained, with framings of innovation as ‘disruption' coming at odds with immediate needs in healthcare settings. Even in an ‘ecosystem' with strong presence of academic and research institutions, support was viewed as limited, with impressions of siloed working, conflicting agendas, fragmentation and lack of collaboration opportunities. Conclusions: IoT development, implementation and roll-out require support from multiple ecosystem actors to be able to articulate a value proposition beyond experimental or small-scale applications. In contexts where clinical, academic and commercial worlds collide, sustained effort is needed to align needs, priorities and motives, and to strengthen potential for good value IoT innovation. © The Author(s) 2023.
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Mental health conditions are a significant contributor to morbidity and mortality and cost an estimated £1.6 trillion per year globally. The COVID-19 pandemic and its associated lockdowns have contributed to increases in common mental health problems (CMHP) like depression. Bodies in the UK recommend the use of non-medical interventions like social prescriptions to support individuals suffering from CMHP. In 2019, NHS-England committed to support the use of social prescribing across England. Despite this commitment, the proportion of eligible individuals with a CMHP that actually receive a social prescription remains unknown. To overcome this knowledge gap, a novel ontological approach was used to estimate the proportion of individuals with a CMHP that received a social prescription, disaggregated by different attributes (region, ethnicity, socio-economic status, sex, age) across a four-year period from 2017–2020. We discovered two general trends. First, there was a 1.4-fold increase in the presentation of individuals, across all attributes, to primary care with a CMHP across the four-year period analysed. There was also marked variation in the presentation to primary care with a CMHP based on different attributes (2020 variation figures - regions: 2.8-fold;ethnicity: 1.8-fold;socio-economic status: 1.4-fold;sex: 1.7-fold;age: 3.9-fold). Second, despite an increase in the use of social prescribing for mental health, there was still substantial underuse of it across all attributes in England (the highest percentage seen across all attributes in 2020 was 14%). The general trends revealed through our analyses provide valuable insights that can help to inform both policy and practice to address variation, health inequalities as well as to proactively design and implement appropriate services. © 2022, Springer Nature Switzerland AG.
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As the (Covid-19) pandemic spreads, the creativity of the scientific community is thriving while trying to control the situation. They are trying to treat patients viably and work with the almost exhausted medical equipment and staff, while growing new, successful antibodies. Successful screening of SARS-CoV-2 empowers fast and proficient determination of COVID-19 and can relieve the weight on medical care frameworks. Numerous forecast models are being created to comprehend and prognosticate the spread of the pandemic and to stay away from the following wave. But in the coming time, we can be sure that the models would experience the ill effects of a few issues, security being one of them. All the models need to be built in such a way that the investigation task gets successfully conducted without compromising the privacy and security of the patients. To take care of this, we propose a blockchain framework for sharing patients' personal data or medical reports. A blockchain will take care of the integrity part, but we still need to worry about confidentiality. Therefore, combining a genetic approach with a blockchain seemed like a good idea. A twofold hybrid methodology is proposed in this paper to tackle the issue of confidentiality. The outcomes displayed high entropy accomplishment for the utilized dataset. The sensitivity of the plaintext and ciphertext is also checked and compared with existing approaches which thus demonstrates the security of the proposed approach in the given setting.
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Context: COVID-19 outbreak has had a huge impact on health-care facilities, and challenges of health-care providers would compromise their physical and mental well-being during this epidemic. Aims: This study aimed to find out stress, anxiety, insomnia, and depression among the health-care workers during COVID-19 outbreak. Settings and Design: This was a 3-month, cross-sectional, observational, single-center study of health-care workers of designated COVID-19 hospital. Subjects and Methods: Study objectives were explained to health-care workers, and written consent was obtained. Participants were approached in their department as per their convenience and requested to fill the pro forma. Depression, Anxiety, and Stress Scale-21 and Insomnia Severity Index were used to detect psychological issues in the form of stress, anxiety, insomnia, and depression. Statistical Analysis: Descriptive statistics and Chi-square test were used for analysis of variables in the study. Results: Overall 27.41% and 29.18% of the health-care workers reported stress and anxiety symptoms, respectively, while 18.78% reported clinically significant insomnia and depression. Among them, being female, married, elderly, presence of medical illness, frontline workers, frequently watching COVID news, and excessive fear of COVID emerged as statistically significant variables associated with stress, anxiety, insomnia, and depression. Conclusions: Health-care workers experienced many mental health issues while performing duties during COVID-19 outbreak. Such issues are alarming and need to be addressed with appropriate health-care policy.
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Aims: Study aimed to find out the prevalence and risk factors of depression among the health care workers during COVID-19 outbreak. Methods and Material: This was a four month, cross-sectional, observational, single center study of heath care workers of a notified COVID-19 hospital. Study objectives were explained to health care workers, and written consent was obtained. Patient health questionnaire-9 (PHQ-9), DSM-5 criterion of major depressive disorder and Structured Clinical Interview for DSM-5 were used to diagnose the depression. Descriptive statistics, chi-square test, and Binary logistic regression were used for analysis of variables Results: Overall 18.78% health workers reported major depressive disorder. Nearly three fourth of the old age participants had moderate to severe depression. 20.69% of married subjects had major depression. Medical health workers reported more depression. One third of the front line workers had major depression. 51% of the participants with medical co-morbidities reported major depression as compared to only 12% in those without any medical co-morbidity.33% of subjects watching COVID-19 news very frequently in a day had major depression Discussion: The prevalence of depression ranges from 9 to 35% in various studies. Among them living in joint family, married, elderly, presence of medical illness, frontline work, frequently watching COVID-19 news, excessive fear of COVID-19, and medical health worker emerged as statistically significant variables associated with major depression Conclusions: The prevalence of depression is high among health care workers while performing duties during COVID-19 outbreak. Early diagnosis and treatment of depression would be crucial during this difficult time. © 2021 Polish Psychiatric Association. All rights reserved.
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Objectives: In this Covid-19 pandemic, onco-hematological patients are at higher risk of severe infection because of both their immunosuppressive state caused by malignancy and treatments and their recurrent hospital accesses. At our cancer centre (IRST), following national authorities and scientific societies recommendations, we set up a model for reduction of risk of Covid-19 positive accesses through sequential actions on patients, caregivers and workers. In this work we give an estimate of reduction of risk of Covid-19 positive accesses. Methods: Covid-19 positive accesses baseline Absolute Risk (AR, ratio between the number of infected subjects accesses and the total number of accesses) for patients, caregivers and workers was estimated in the period from March, 11 to March, 31. Five risk reduction actions were implemented: (1) all procedures judged as deferrable by physicians have been postponed, (2) by-phone triage and (3) on-site triage have been activated to avoid accesses of suspected cases patients and caregivers. For workers (4) special leaves and (5) smartwork were encouraged. For each of these actions we estimated Absolute Risk Reduction (ARR) and Relative Risk Reduction (RRR). Results: In the analysis period we estimated 50 Covid-19 positive accesses: 14 for patients, 7 for caregivers, 29 for workers (AR 0.129%, 0.087%, 0.316% respectively). We measured 9 avoided accesses for patients (ARR: 0.084%, RRR: 65.4%), 5 for caregivers (ARR: 0.061%, RRR: 69.5%), 17 for workers (ARR: 0.184, RRR: 58.0%);for a total of 31 accesses potentially avoided thanks to the 5 actions. Conclusions: During the pandemic IRST never stopped providing care to the patients, the implemented actions allowed a risk reduction that can be an example of how to face this pandemia maintaining both continuity of care and safety for patients and staff in a context of frailty such as a cancer centre.