HealthCare Partners: Building on a Foundation of Global Risk Management to Achieve Accountable Care

Describes the progress of a medical group and independent practice association in forming an accountable care organization by working with insurers as part of the Brookings-Dartmouth ACO Pilot Program. Lists lessons learned and elements of success

Machine Learning and Integrative Analysis of Biomedical Big Data.

Recent developments in high-throughput technologies have accelerated the accumulation of massive amounts of omics data from multiple sources: genome, epigenome, transcriptome, proteome, metabolome, etc. Traditionally, data from each source (e.g., genome) is analyzed in isolation using statistical and machine learning (ML) methods. Integrative analysis of multi-omics and clinical data is key to new biomedical discoveries and advancements in precision medicine. However, data integration poses new computational challenges as well as exacerbates the ones associated with single-omics studies. Specialized computational approaches are required to effectively and efficiently perform integrative analysis of biomedical data acquired from diverse modalities. In this review, we discuss state-of-the-art ML-based approaches for tackling five specific computational challenges associated with integrative analysis: curse of dimensionality, data heterogeneity, missing data, class imbalance and scalability issues

Chromosomal radiosensitivity of human immunodeficiency virus positive/negative cervical cancer patients in South Africa

Cervical cancer is the second most common cancer amongst South African women and is the leading cause of cancer-associated mortality in this region. Several international studies on radiation-induced DNA damage in lymphocytes of cervical cancer patients have remained inconclusive. Despite the high incidence of cervical cancer in South Africa, and the extensive use of radiotherapy to treat it, the chromosomal radiosensitivity of South African cervical cancer patients has not been studied to date. Since a high number of these patients are human immunodeficiency virus (HIV)-positive, the effect of HIV infection on chromosomal radiosensitivity was also investigated. Blood samples from 35 cervical cancer patients (20 HIV-negative and 15 HIV-positive) and 20 healthy controls were exposed to X-rays at doses of 6 MV of 2 and 4 Gy in vitro. Chromosomal radiosensitivity was assessed using the micronucleus (MN) assay. MN scores were obtained using the Metafer 4 platform, an automated microscopic system. Three scoring methods of the MNScore module of Metafer were applied and compared. Cervical cancer patients had higher MN values than healthy controls, with HIV-positive patients having the highest MN values. Differences between groups were significant when using a scoring method that corrects for false positive and false negative MN. The present study suggested increased chromosomal radiosensitivity in HIV-positive South African cervical cancer patients

Healthy ageing in Europe: prioritizing interventions to improve health literacy

Background: Health literacy (HL) is low for 40-50% of the population in developed nations, and is strongly linked to many undesirable health outcomes. Older adults are particularly at risk. The Intervention Research on Health Literacy in Ageing populations project systematically created a large inventory of HL interventions targeting adults age 50+, to support practical production of policy and practice guidelines for promoting health literacy in European populations. Methods: We comprehensively surveyed international scientific literature, grey literature and other sources (published 2003+) for implemented HL interventions that involved older adults. Studies were screened for eligibility criteria and further selected for aspects important in European public health policy, including priority diseases, risk factors and vulnerable target groups. Interventions were prioritised using a multiple criteria tool to select final interventions that also featured strong evidence of efficacy and a broad range of strategies. Results: From nearly 7000 written summaries, 1097 met inclusion criteria, of which 233 were chosen for scoring and ranking. Of these, 7 had the highest multi-criteria scores. Eight more articles were selected based on rounded criteria including a high multi-criteria score as well as elements of innovation. Final selections were 18 articles describing 15 programmes, which feature strong evidence of efficacy among important diseases or risk factors and vulnerable groups, or that had success with elements of innovation were identified. Most programmes tried to increase skills in communication, self-management and understanding healthcare or lifestyle choices. Conclusions: These programmes have multiple positive attributes which could be used as guidance for developing innovative intervention programmes to trial on European older adults. They provide evidence of efficacy in addressing high priority diseases and risk factors

AutoDiscern: Rating the Quality of Online Health Information with Hierarchical Encoder Attention-based Neural Networks

Patients increasingly turn to search engines and online content before, or in place of, talking with a health professional. Low quality health information, which is common on the internet, presents risks to the patient in the form of misinformation and a possibly poorer relationship with their physician. To address this, the DISCERN criteria (developed at University of Oxford) are used to evaluate the quality of online health information. However, patients are unlikely to take the time to apply these criteria to the health websites they visit. We built an automated implementation of the DISCERN instrument (Brief version) using machine learning models. We compared the performance of a traditional model (Random Forest) with that of a hierarchical encoder attention-based neural network (HEA) model using two language embeddings, BERT and BioBERT. The HEA BERT and BioBERT models achieved average F1-macro scores across all criteria of 0.75 and 0.74, respectively, outperforming the Random Forest model (average F1-macro = 0.69). Overall, the neural network based models achieved 81% and 86% average accuracy at 100% and 80% coverage, respectively, compared to 94% manual rating accuracy. The attention mechanism implemented in the HEA architectures not only provided 'model explainability' by identifying reasonable supporting sentences for the documents fulfilling the Brief DISCERN criteria, but also boosted F1 performance by 0.05 compared to the same architecture without an attention mechanism. Our research suggests that it is feasible to automate online health information quality assessment, which is an important step towards empowering patients to become informed partners in the healthcare process

East Midlands Research into Ageing Network (EMRAN) Discussion Paper Series

Academic geriatric medicine in Leicester . There has never been a better time to consider joining us. We have recently appointed a Professor in Geriatric Medicine, alongside Tom Robinson in stroke and Victoria Haunton, who has just joined as a Senior Lecturer in Geriatric Medicine. We have fantastic opportunities to support students in their academic pursuits through a well-established intercalated BSc programme, and routes on through such as ACF posts, and a successful track-record in delivering higher degrees leading to ACL post. We collaborate strongly with Health Sciences, including academic primary care. See below for more detail on our existing academic set-up. Leicester Academy for the Study of Ageing We are also collaborating on a grander scale, through a joint academic venture focusing on ageing, the ‘Leicester Academy for the Study of Ageing’ (LASA), which involves the local health service providers (acute and community), De Montfort University; University of Leicester; Leicester City Council; Leicestershire County Council and Leicester Age UK. Professors Jayne Brown and Simon Conroy jointly Chair LASA and have recently been joined by two further Chairs, Professors Kay de Vries and Bertha Ochieng. Karen Harrison Dening has also recently been appointed an Honorary Chair. LASA aims to improve outcomes for older people and those that care for them that takes a person-centred, whole system perspective. Our research will take a global perspective, but will seek to maximise benefits for the people of Leicester, Leicestershire and Rutland, including building capacity. We are undertaking applied, translational, interdisciplinary research, focused on older people, which will deliver research outcomes that address domains from: physical/medical; functional ability, cognitive/psychological; social or environmental factors. LASA also seeks to support commissioners and providers alike for advice on how to improve care for older people, whether by research, education or service delivery. Examples of recent research projects include: ‘Local History Café’ project specifically undertaking an evaluation on loneliness and social isolation; ‘Better Visits’ project focused on improving visiting for family members of people with dementia resident in care homes; and a study on health issues for older LGBT people in Leicester. Clinical Geriatric Medicine in Leicester We have developed a service which recognises the complexity of managing frail older people at the interface (acute care, emergency care and links with community services). There are presently 17 consultant geriatricians supported by existing multidisciplinary teams, including the largest complement of Advance Nurse Practitioners in the country. Together we deliver Comprehensive Geriatric Assessment to frail older people with urgent care needs in acute and community settings. The acute and emergency frailty units – Leicester Royal Infirmary This development aims at delivering Comprehensive Geriatric Assessment to frail older people in the acute setting. Patients are screened for frailty in the Emergency Department and then undergo a multidisciplinary assessment including a consultant geriatrician, before being triaged to the most appropriate setting. This might include admission to in-patient care in the acute or community setting, intermediate care (residential or home based), or occasionally other specialist care (e.g. cardiorespiratory). Our new emergency department is the county’s first frail friendly build and includes fantastic facilities aimed at promoting early recovering and reducing the risk of hospital associated harms. There is also a daily liaison service jointly run with the psychogeriatricians (FOPAL); we have been examining geriatric outreach to oncology and surgery as part of an NIHR funded study. We are home to the Acute Frailty Network, and those interested in service developments at the national scale would be welcome to get involved. Orthogeriatrics There are now dedicated hip fracture wards and joint care with anaesthetists, orthopaedic surgeons and geriatricians. There are also consultants in metabolic bone disease that run clinics. Community work Community work will consist of reviewing patients in clinic who have been triaged to return to the community setting following an acute assessment described above. Additionally, primary care colleagues refer to outpatients for sub-acute reviews. You will work closely with local GPs with support from consultants to deliver post-acute, subacute, intermediate and rehabilitation care services. Stroke Medicine 24/7 thrombolysis and TIA services. The latter is considered one of the best in the UK and along with the high standard of vascular surgery locally means one of the best performances regarding carotid intervention

Development of a Web Platform for Surgical Oncologists in Portugal

In an age of enormous access to clinical data and rapid technological development, ensuring that physicians have computational tools to navigate a sea of information and improve health outcomes is vital. A major advance in medical practice is the incorporation of Clinical Decision Support Systems (CDSSs) to assist and support the healthcare team in clinical decision making, thus improving the quality of decisions and overall patient care, while minimizing costs. Postsurgical complications of cancer surgery are hard to predict, although there are several traditional risk scores available. However, there is an urgent need to improve perioperative risk assessment to reduce the growing postoperative burden in the Portuguese population. Understanding the individual risks of performing surgical procedures is essential to customizing preparatory, intervention, and aftercare protocols to minimize post-surgical complications. This knowledge is essential in oncology, given the nature of the interventions, the fragile profile of patients with comorbidities and drug exposure, and the possible recurrence of cancer. This thesis aims to develop an user-friendly web platform to support the collaboration and manage clinical data among oncologists at the Portuguese Institute of Oncology, Porto. The work integrates both a database to register/store the clinical data of cancer patients in a structured format, visualization tools and computational methods to calculate a specific risk score of postoperative outcomes for the Portuguese population. The platform named IPOscore will not only to manage the clinic data but also offer a predictive healthcare system, as an valuable instrument for the oncologists.Numa época de grande acesso a dados e rápido desenvolvimento tecnológico, garantir que os médicos tenham as ferramentas de apoio à decisão clínica para se deslocar em um mar de informação para encontrar o que é mais relevante para as necessidades dos pacientes é vital para otimizar os resultados de saúde. Um grande avanço na prática médica é a incorporação de Sistemas de Apoio à Decisão Clínica (CDSSs) para auxiliar e apoiar a equipe de saúde na tomada de decisão clínica, melhorando assim a qualidade das decisões e o atendimento geral ao paciente, minimizando custos. As complicações pós-operatórias da cirurgia do cancro ainda são difíceis de prever, embora existam muitos scores de risco destinados a fazer tais previsões. Compreender os riscos individuais de realizar procedimentos cirúrgicos é essencial para personalizar os protocolos preparatórios, de intervenção e pós-atendimento para minimizar as complicações pós-cirúrgicas. Esse conhecimento é fundamental em oncologia, dada a natureza das intervenções, o perfil frágil dos pacientes com comorbidades e exposição a drogas e a possível recorrência do cancro. Este trabalho propõe a construção duma plataformaweb de fácil utilização para apoiar a colaboração e dispor uma gestão de dados clínicos entre oncologistas. O trabalho integra uma base de dados para registrar / armazenar os dados clínicos, fisiológicos e biopatológicos de pacientes com cancro num formato estruturado e métodos computacionais para calcular um grau de risco específico de complicações pós-operatórias para a população portuguesa. A plataforma denominada IPOscore servirá para a gestão de dados clinicos, mas também oferecerá um sistema preditivo e preventivo, como uma ferramenta de apoio à decisão médica no contexto clínico diário