Risk models and scores for type 2 diabetes: Systematic review

This article is published under a Creative Commons Attribution Non Commercial (CC BY-NC 3.0) licence that allows reuse subject only to the use being non-commercial and to the article being fully attributed (http://creativecommons.org/licenses/by-nc/3.0).Objective - To evaluate current risk models and scores for type 2 diabetes and inform selection and implementation of these in practice. Design - Systematic review using standard (quantitative) and realist (mainly qualitative) methodology. Inclusion - criteria Papers in any language describing the development or external validation, or both, of models and scores to predict the risk of an adult developing type 2 diabetes. Data sources - Medline, PreMedline, Embase, and Cochrane databases were searched. Included studies were citation tracked in Google Scholar to identify follow-on studies of usability or impact. Data extraction - Data were extracted on statistical properties of models, details of internal or external validation, and use of risk scores beyond the studies that developed them. Quantitative data were tabulated to compare model components and statistical properties. Qualitative data were analysed thematically to identify mechanisms by which use of the risk model or score might improve patient outcomes. Results - 8864 titles were scanned, 115 full text papers considered, and 43 papers included in the final sample. These described the prospective development or validation, or both, of 145 risk prediction models and scores, 94 of which were studied in detail here. They had been tested on 6.88 million participants followed for up to 28 years. Heterogeneity of primary studies precluded meta-analysis. Some but not all risk models or scores had robust statistical properties (for example, good discrimination and calibration) and had been externally validated on a different population. Genetic markers added nothing to models over clinical and sociodemographic factors. Most authors described their score as “simple” or “easily implemented,” although few were specific about the intended users and under what circumstances. Ten mechanisms were identified by which measuring diabetes risk might improve outcomes. Follow-on studies that applied a risk score as part of an intervention aimed at reducing actual risk in people were sparse. Conclusion - Much work has been done to develop diabetes risk models and scores, but most are rarely used because they require tests not routinely available or they were developed without a specific user or clear use in mind. Encouragingly, recent research has begun to tackle usability and the impact of diabetes risk scores. Two promising areas for further research are interventions that prompt lay people to check their own diabetes risk and use of risk scores on population datasets to identify high risk “hotspots” for targeted public health interventions.Tower Hamlets, Newham, and City and Hackney primary care trusts and National Institute of Health Research

What does it take to make integrated care work? A ‘cookbook’ for large-scale deployment of coordinated care and telehealth

The Advancing Care Coordination & Telehealth Deployment (ACT) Programme is the first to explore the organisational and structural processes needed to successfully implement care coordination and telehealth (CC&TH) services on a large scale. A number of insights and conclusions were identified by the ACT programme. These will prove useful and valuable in supporting the large-scale deployment of CC&TH. Targeted at populations of chronic patients and elderly people, these insights and conclusions are a useful benchmark for implementing and exchanging best practices across the EU. Examples are: Perceptions between managers, frontline staff and patients do not always match; Organisational structure does influence the views and experiences of patients: a dedicated contact person is considered both important and helpful; Successful patient adherence happens when staff are engaged; There is a willingness by patients to participate in healthcare programmes; Patients overestimate their level of knowledge and adherence behaviour; The responsibility for adherence must be shared between patients and health care providers; Awareness of the adherence concept is an important factor for adherence promotion; The ability to track the use of resources is a useful feature of a stratification strategy, however, current regional case finding tools are difficult to benchmark and evaluate; Data availability and homogeneity are the biggest challenges when evaluating the performance of the programmes

Cross-Modal Health State Estimation

Individuals create and consume more diverse data about themselves today than any time in history. Sources of this data include wearable devices, images, social media, geospatial information and more. A tremendous opportunity rests within cross-modal data analysis that leverages existing domain knowledge methods to understand and guide human health. Especially in chronic diseases, current medical practice uses a combination of sparse hospital based biological metrics (blood tests, expensive imaging, etc.) to understand the evolving health status of an individual. Future health systems must integrate data created at the individual level to better understand health status perpetually, especially in a cybernetic framework. In this work we fuse multiple user created and open source data streams along with established biomedical domain knowledge to give two types of quantitative state estimates of cardiovascular health. First, we use wearable devices to calculate cardiorespiratory fitness (CRF), a known quantitative leading predictor of heart disease which is not routinely collected in clinical settings. Second, we estimate inherent genetic traits, living environmental risks, circadian rhythm, and biological metrics from a diverse dataset. Our experimental results on 24 subjects demonstrate how multi-modal data can provide personalized health insight. Understanding the dynamic nature of health status will pave the way for better health based recommendation engines, better clinical decision making and positive lifestyle changes.Comment: Accepted to ACM Multimedia 2018 Conference - Brave New Ideas, Seoul, Korea, ACM ISBN 978-1-4503-5665-7/18/1

Chronic Disease Risk Prediction Models and their Impacts on Behavioural and Health Outcomes: A Systematic Review and Meta-analysis

Risk prediction models are tools that predict an individual’s risk of developing a health outcome. They were developed to influence patient management by guiding preventive interventions, with the goal of reducing the incidence of new diseases. Studies examining their impacts are uncommon, and no consensus regarding their effects has been reached. This systematic review sought to determine the impact of risk prediction models for chronic diseases on physician behaviour, patient behaviour, and patient health outcomes. Twenty-two studies were found to be eligible for review. The results demonstrated that: 1) physician behaviour may be positively influenced, though a statistically significant result was not found; 2) alterations in patient behaviour were inconclusive; and 3) some aspects of patient health outcomes were significantly improved, such as changes in blood pressure, but these results may be clinically insignificant. The evidence indicates some effects may exist, though future studies are required to confirm this effect

Overweight and Obesity and the Demand for Primary Physician Care

The standard economic model for the demand for health care predicts that unhealthy behaviour such as being overweight or obese should increase the demand for medical care, particularly as clinical studies link obesity to a number of serious diseases. In this paper, we investigate whether overweight or obese individuals demand more medical care than normal weight individuals by estimating a finite mixture model which splits the population into frequent and non-frequent users of primary physician (GP) services according to the individual's latent health status. Based on a sample of wage-earners aged 25-60 years drawn from the National Health Interview (NHI) survey 2000 and merged to Danish register data, we compare differences in the impact of being overweight and obese relative to being normal weight on the demand for primary physician care. Estimated bodyweight effects vary across latent classes and show that being obese or overweight does not increase the demand for primary physician care among infrequent users but does so among frequent users.overweight, obesity, demand for primary physician care

On the road to personalised and precision geomedicine: medical geology and a renewed call for interdisciplinarity

Our health depends on where we currently live, as well as on where we have lived in the past and for how long in each place. An individual’s place history is particularly relevant in conditions with long latency between exposures and clinical manifestations, as is the case in many types of cancer and chronic conditions. A patient’s geographic history should routinely be considered by physicians when diagnosing and treating individual patients. It can provide useful contextual environmental information (and the corresponding health risks) about the patient, and should thus form an essential part of every electronic patient/health record. Medical geology investigations, in their attempt to document the complex relationships between the environment and human health, typically involve a multitude of disciplines and expertise. Arguably, the spatial component is the one factor that ties in all these disciplines together in medical geology studies. In a general sense, epidemiology, statistical genetics, geoscience, geomedical engineering and public and environmental health informatics tend to study data in terms of populations, whereas medicine (including personalised and precision geomedicine, and lifestyle medicine), genetics, genomics, toxicology and biomedical/health informatics more likely work on individuals or some individual mechanism describing disease. This article introduces with examples the core concepts of medical geology and geomedicine. The ultimate goals of prediction, prevention and personalised treatment in the case of geology-dependent disease can only be realised through an intensive multiple-disciplinary approach, where the various relevant disciplines collaborate together and complement each other in additive (multidisciplinary), interactive (interdisciplinary) and holistic (transdisciplinary and cross-disciplinary) manners

Shared decision-making about cardiovascular disease medication in older people: A qualitative study of patient experiences in general practice

Objectives To explore older people's perspectives and experiences with shared decision-making (SDM) about medication for cardiovascular disease (CVD) prevention. Design, setting and participants Semi-structured interviews with 30 general practice patients aged 75 years and older in New South Wales, Australia, who had elevated CVD risk factors (blood pressure, cholesterol) or had received CVD-related lifestyle advice. Data were analysed by multiple researchers using Framework analysis. Results Twenty eight participants out of 30 were on CVD prevention medication, half with established CVD. We outlined patient experiences using the four steps of the SDM process, identifying key barriers and challenges: Step 1. Choice awareness: taking medication for CVD prevention was generally not recognised as a decision requiring patient input; Step 2. Discuss benefits/harms options: CVD prevention poorly understood with emphasis on benefits; Step 3. Explore preferences: goals, values and preferences (eg, length of life vs quality of life, reducing disease burden vs risk reduction) varied widely but generally not discussed with the general practitioner; Step 4. Making the decision: overall preference for directive approach, but some patients wanted more active involvement. Themes were similar across primary and secondary CVD prevention, different levels of self-reported health and people on and off medication. Conclusions Results demonstrate how older participants vary widely in their health goals and preferences for treatment outcomes, suggesting that CVD prevention decisions are preference sensitive. Combined with the fact that the vast majority of participants were taking medications, and few understood the aims and potential benefits and harms of CVD prevention, it seems that older patients are not always making an informed decision. Our findings highlight potentially modifiable barriers to greater participation of older people in SDM about CVD prevention medication and prevention in general

Javanese Muslim with Diabetes in YOGYAKARTA Managing the Daily Self-Care Activity

Self-care, capability in performing certain activity in maintaining well-being in daily life, was regarded important especially among people with long-term condition such as diabetes. Locus of control and self-efficacy are among the self-agency factors that might influence how people engage with daily self-care activity in diabetes management. While, Javanese and Islamic values and norms are other parts of structure that support the effort. This study aimed to seek further into the experiences and perceptions among the Javanese Muslim on how they managed to do self-care in diabetes management. The study was done utilizing a mixed method approach with the usage of the Summary of Diabetes Self-care Activity (SDSCA) questionnaire to measure the level of self-care and followed by further interview to dig deeper into the perception and experiences and what are the opportunity or obstacle in performing daily self-care. A convenient sample of 100 participants has filled the questionnaires, with further 24 interviews. The study identified the moderate self-care practices as a separate notion, instead of an integrated and comprehensive concept amid the unavailability of a structured education program. Five themes were generated from the interviews, those are: education and knowledge, being in or out of control, Javanese way – sensitivity and surrender, peace of mind and role of Allah or God, and poor access to health care