Implementation factors affecting the large-scale deployment of digital health and well-being technologies : a qualitative study of the initial phases of the ‘Living-It-Up’programme

Little is known about the factors which facilitate or impede the large-scale deployment of health and well-being consumer technologies. The Living-It-Up project is a large-scale digital intervention led by NHS 24, aiming to transform health and well-being services delivery throughout Scotland. We conducted a qualitative study of the factors affecting the implementation and deployment of the Living-It-Up services. We collected a range of data during the initial phase of deployment, including semi-structured interviews (N = 6); participant observation sessions (N = 5) and meetings with key stakeholders (N = 3). We used the Normalisation Process Theory as an explanatory framework to interpret the social processes at play during the initial phases of deployment.Initial findings illustrate that it is clear - and perhaps not surprising - that the size and diversity of the Living-It-Up consortium made implementation processes more complex within a 'multi-stakeholder' environment. To overcome these barriers, there is a need to clearly define roles, tasks and responsibilities among the consortium partners. Furthermore, varying levels of expectations and requirements, as well as diverse cultures and ways of working, must be effectively managed. Factors which facilitated implementation included extensive stakeholder engagement, such as co-design activities, which can contribute to an increased 'buy-in' from users in the long term. An important lesson from the Living-It-Up initiative is that attempting to co-design innovative digital services, but at the same time, recruiting large numbers of users is likely to generate conflicting implementation priorities which hinder - or at least substantially slow down - the effective rollout of services at scale.The deployment of Living-It-Up services is ongoing, but our results to date suggest that - in order to be successful - the roll-out of digital health and well-being technologies at scale requires a delicate and pragmatic trade-off between co-design activities, the development of innovative services and the efforts allocated to widespread marketing and recruitment initiatives

Evaluation of a Chromogenic Medium for the Detection of ESBL with Comparison to Double Disk Synergy Test

Background: Extended Spectrum Beta Lactamase (ESBL) producing bacterial strains are the major causes of nosocomial and community-acquired infections worldwide. The aim of the study was to evaluate the effectiveness of Brilliance ESBL Agar (BEA) (a chromogenic culture medium) for the detection of ESBL in comparison with Double Disc Synergy Test (DDST) and confirm results from both methods by Single-plex Polymerase Chain Reaction (PCR) as gold standard. Materials and Methods: A total of 75 clinical isolates of Escherichia coli were screened for ESBL production using BEA & DDST from various clinical specimens. The antibiotic susceptibility testing was done by the Kirby-Bauer disc diffusion method using Cefotaxime (30 µg) and Ceftazidime (30 µg) discs on Mueller Hinton agar. ESBL producing strains were detected phenotypically by DDST and BEA at 24 h and 48 h, respectively. Isolates screened by both methods were confirmed using PCR for the detection of blaSHV, blaTEM, blaCTX-M genes. Results: The prevalence of ESBL was 61%. The sensitivity and specificity of DDST at 24 h and 48hours incubation time was 91.3% and 89.5%, respectively. BEA showed an increase in sensitivity and specificity at 48 h with 97.8% and 98.0%, respectively. All ESBL producing strains detected by phenotypic tests were also found harboring ESBL genes (blaSHV, blaTEM, blaCTX-M) by PCR. Conclusion: The use of BEA in the screening of ESBL production was found to give much better results than DDST and can be used where PCR cannot be performed

Antifungal susceptibility and test for cure of candida species among vulvovaginal candidiasis patients in a secondary care hospital, Nigeria

Background: Antimicrobial resistance among Candida species is an intense public health concern. The aim of the study was to determine the antifungal susceptibility pattern and test for cure of Candida species among women of child bearing age who visited the General Hospital Onitsha, Nigeria with symptoms suggestive of Vulvovaginal Candidiasis (VVC).Materials and Methods: Eight hundred and seventy six female patients participated in the study of which high vaginal swabs were collected and evaluated mycological by standard microbiological methods: microscopic examination and culture using sabouraud dextrose agar (SDA). Susceptibility of isolates to 4 antifungal agents was tested using agar dilution method. Clinicomycological evaluation was also performed among the patients.Result: Higher minimum inhibitory concentration (MIC) to azole antifungals was observed predominantly among non-albicans Candida species increasingly involved in VVC. The rate of mycological resolution was higher than symptomatic relief at 2 weeks after treatment with antifungal drug.Conclusion: Efficacious treatment of VVC requires an adequate knowledge of the causative agents and more importantly the antimicrobial to which they exhibit high susceptibility.Keywords: Vulvovaginal Candidiasis, Clinico- mycology, Antimicrobial resistance, Candida speciesSusceptibilite antifonique et test pour la cure d'especes de candida entre les patients de candidases vulvovaginales dans un hopital de soins secondaires, NigeriaContexte: La résistance aux antimicrobiens chez les espèces de Candida est un problème de santé publique intense. L'objectif de l'étude était de déterminer le schéma de susceptibilité aux antifongiques et le test de guérison des espèces de Candida parmi les femmes en âge de procréer qui ont visité l'hôpital général de Onitsha, au Nigeria, avec des symptômes suggérant une candidose vulvovaginale (VVC).Matériaux et méthodes: huit cent soixante-seize six patientes ont participé à l'étude des prélèvements vaginaux élevés collectés et évalués par mycologie par méthodes microbiologiques standard: examen microscopique et culture à l'aide de la gélose sabouraud dextrose (SDA). La susceptibilité des isolats à 4 agents antifongiques a été testée en utilisant une méthode de dilution en agar. Une évaluation clinico-mycologique a également été réalisée chez les patients.Résultat: une concentration minimale minimale d'inhibition (MIC) en anatoxines azoliques a été observée principalement chez les espèces non-albicans Candida de plus en plus impliquées dans VVC. Le taux de résolution mycologique était plus élevé que le soulagement symptomatique à 2 semaines après le traitement par un médicament antifongique.Conclusion: Un traitement efficace de la VVC nécessite une connaissance adéquate des agents causaux et, plus important encore, des antimicrobiens auxquels ils présentent une forte susceptibilité.Mots-clés: Candidiase Vulvovaginale, Clinico-mycologie, Résistance Antimicrobienne, Espèces Candid

Natural language processing for mimicking clinical trial recruitment in critical care: a semi-automated simulation based on the LeoPARDS trial

Clinical trials often fail to recruit an adequate number of appropriate patients. Identifying eligible trial participants is resource-intensive when relying on manual review of clinical notes, particularly in critical care settings where the time window is short. Automated review of electronic health records (EHR) may help, but much of the information is in free text rather than a computable form. We applied natural language processing (NLP) to free text EHR data using the CogStack platform to simulate recruitment into the LeoPARDS study, a clinical trial aiming to reduce organ dysfunction in septic shock. We applied an algorithm to identify eligible patients using a moving 1-hour time window, and compared patients identified by our approach with those actually screened and recruited for the trial, for the time period that data were available. We manually reviewed records of a random sample of patients identified by the algorithm but not screened in the original trial. Our method identified 376 patients, including 34 patients with EHR data available who were actually recruited to LeoPARDS in our centre. The sensitivity of CogStack for identifying patients screened was 90% (95% CI 85%, 93%). Of the 203 patients identified by both manual screening and CogStack, the index date matched in 95 (47%) and CogStack was earlier in 94 (47%). In conclusion, analysis of EHR data using NLP could effectively replicate recruitment in a critical care trial, and identify some eligible patients at an earlier stage, potentially improving trial recruitment if implemented in real time

Modulation of the immune response to Mycobacterium tuberculosis during malaria/M. tuberculosis co-infection

Tuberculosis (TB) causes significant morbidity and mortality on a global scale. The African region has 24% of the world's TB cases. TB overlaps with other infectious diseases such as malaria and HIV, which are also highly prevalent in the African region. TB is a leading cause of death among HIV-positive patients and co-infection with HIV and TB has been described as a syndemic. In view of the overlapping epidemiology of these diseases, it is important to understand the dynamics of the immune response to TB in the context of co-infection. We investigated the cytokine response to purified protein derivative (PPD) in peripheral blood mononuclear cells from TB patients co-infected with HIV or malaria and compared it to that of malaria- and HIV-free TB patients. A total of 231 subjects were recruited for this study and classified into six groups; untreated TB-positive, TB positive subjects on TB drugs, TB- and HIV-positive, TB- and malaria-positive, latent TB and apparently healthy control subjects. Our results demonstrate maintenance of interferon (IFN)-γ production in HIV and malaria co-infected TB patients in spite of lower CD4 counts in the HIV-infected cohort. Malaria co-infection caused an increase in the production of the T helper type 2 (Th2)-associated cytokine interleukin (IL)-4 and the anti-inflammatory cytokine IL-10 in PPD-stimulated cultures. These results suggest that malaria co-infection diverts immune response against M. tuberculosis towards a Th-2/anti-inflammatory response which might have important consequences for disease progression

Modulation of the immune response to Mycobacterium tuberculosis during malaria/M. tuberculosis co-infection

Tuberculosis (TB) causes significant morbidity and mortality on a global scale. The African region has 24% of the world's TB cases. TB overlaps with other infectious diseases such as malaria and HIV, which are also highly prevalent in the African region. TB is a leading cause of death among HIV-positive patients and co-infection with HIV and TB has been described as a syndemic. In view of the overlapping epidemiology of these diseases, it is important to understand the dynamics of the immune response to TB in the context of co-infection. We investigated the cytokine response to purified protein derivative (PPD) in peripheral blood mononuclear cells from TB patients co-infected with HIV or malaria and compared it to that of malaria- and HIV-free TB patients. A total of 231 subjects were recruited for this study and classified into six groups; untreated TB-positive, TB positive subjects on TB drugs, TB- and HIV-positive, TB- and malaria-positive, latent TB and apparently healthy control subjects. Our results demonstrate maintenance of interferon (IFN)-γ production in HIV and malaria co-infected TB patients in spite of lower CD4 counts in the HIV-infected cohort. Malaria co-infection caused an increase in the production of the T helper type 2 (Th2)-associated cytokine interleukin (IL)-4 and the anti-inflammatory cytokine IL-10 in PPD-stimulated cultures. These results suggest that malaria co-infection diverts immune response against M. tuberculosis towards a Th-2/anti-inflammatory response which might have important consequences for disease progression

Integration of cardiovascular risk assessment with COVID-19 using artificial intelligence

Artificial Intelligence (AI), in general, refers to the machines (or computers) that mimic "cognitive" functions that we associate with our mind, such as "learning" and "solving problem". New biomarkers derived from medical imaging are being discovered and are then fused with non-imaging biomarkers (such as office, laboratory, physiological, genetic, epidemiological, and clinical-based biomarkers) in a big data framework, to develop AI systems. These systems can support risk prediction and monitoring. This perspective narrative shows the powerful methods of AI for tracking cardiovascular risks. We conclude that AI could potentially become an integral part of the COVID-19 disease management system. Countries, large and small, should join hands with the WHO in building biobanks for scientists around the world to build AI-based platforms for tracking the cardiovascular risk assessment during COVID-19 times and long-term follow-up of the survivors

Readiness for Delivering Digital Health at Scale: Lessons From a Longitudinal Qualitative Evaluation of a National Digital Health Innovation Program in the United Kingdom

Background: Digital health has the potential to support care delivery for chronic illness. Despite positive evidence from localized implementations, new technologies have proven slow to become accepted, integrated, and routinized at scale.Objective: The aim of our study was to examine barriers and facilitators to implementation of digital health at scale through the evaluation of a £37m national digital health program: ‟Delivering Assisted Living Lifestyles at Scale” (dallas) from 2012-2015.Methods: The study was a longitudinal qualitative, multi-stakeholder, implementation study. The methods included interviews (n=125) with key implementers, focus groups with consumers and patients (n=7), project meetings (n=12), field work or observation in the communities (n=16), health professional survey responses (n=48), and cross program documentary evidence on implementation (n=215). We used a sociological theory called normalization process theory (NPT) and a longitudinal (3 years) qualitative framework analysis approach. This work did not study a single intervention or population. Instead, we evaluated the processes (of designing and delivering digital health), and our outcomes were the identified barriers and facilitators to delivering and mainstreaming services and products within the mixed sector digital health ecosystem.Results: We identified three main levels of issues influencing readiness for digital health: macro (market, infrastructure, policy), meso (organizational), and micro (professional or public). Factors hindering implementation included: lack of information technology (IT) infrastructure, uncertainty around information governance, lack of incentives to prioritize interoperability, lack of precedence on accountability within the commercial sector, and a market perceived as difficult to navigate. Factors enabling implementation were: clinical endorsement, champions who promoted digital health, and public and professional willingness.Conclusions: Although there is receptiveness to digital health, barriers to mainstreaming remain. Our findings suggest greater investment in national and local infrastructure, implementation of guidelines for the safe and transparent use and assessment of digital health, incentivization of interoperability, and investment in upskilling of professionals and the public would help support the normalization of digital health. These findings will enable researchers, health care practitioners, and policy makers to understand the current landscape and the actions required in order to prepare the market and accelerate uptake, and use of digital health and wellness services in context and at scale