Barriers and opportunities for evidence-based health service planning: the example of developing a Decision Analytic Model to plan services for sexually transmitted infections in the UK

Decision Analytic Models (DAMs) are established means of evidence-synthesis to differentiate between health interventions. They have mainly been used to inform clinical decisions and health technology assessment at the national level, yet could also inform local health service planning. For this, a DAM must take into account the needs of the local population, but also the needs of those planning its services. Drawing on our experiences from stakeholder consultations, where we presented the potential utility of a DAM for planning local health services for sexually transmitted infections (STIs) in the UK, and the evidence it could use to inform decisions regarding different combinations of service provision, in terms of their costs, cost-effectiveness, and public health outcomes, we discuss the barriers perceived by stakeholders to the use of DAMs to inform service planning for local populations, including (1) a tension between individual and population perspectives; (2) reductionism; and (3) a lack of transparency regarding models, their assumptions, and the motivations of those generating models

Non-profit Health Care Services Marketing: Persuasive Messages Based on Multidimensional Concept Mapping and Direct Magnitude Estimation

Persuasive messages for marketing healthcare services in general and coordinated care in particular are more important now for providers, hospitals, and third-party payers than ever before. The combination of measurement based information with creativity may be among the most critical factors in reaching markets or expanding markets. The research presented here provides an approach to marketing coordinated care services which allows healthcare managers to plan persuasive messages given the market conditions they face. Using market respondents’ thinking about product attributes combined with distance measurement between pairs of product attributes, a conceptual marketing map is presented and applied to advertising, message copy, and delivery. The data reported here are representative of the potential caregivers for which the messages are intended. Results are described with implications for application to coordinated care services. Theory building and marketing practice are discussed in the light of findings and methodology

Artificial intelligence approaches to predicting and detecting cognitive decline in older adults: A conceptual review.

Preserving cognition and mental capacity is critical to aging with autonomy. Early detection of pathological cognitive decline facilitates the greatest impact of restorative or preventative treatments. Artificial Intelligence (AI) in healthcare is the use of computational algorithms that mimic human cognitive functions to analyze complex medical data. AI technologies like machine learning (ML) support the integration of biological, psychological, and social factors when approaching diagnosis, prognosis, and treatment of disease. This paper serves to acquaint clinicians and other stakeholders with the use, benefits, and limitations of AI for predicting, diagnosing, and classifying mild and major neurocognitive impairments, by providing a conceptual overview of this topic with emphasis on the features explored and AI techniques employed. We present studies that fell into six categories of features used for these purposes: (1) sociodemographics; (2) clinical and psychometric assessments; (3) neuroimaging and neurophysiology; (4) electronic health records and claims; (5) novel assessments (e.g., sensors for digital data); and (6) genomics/other omics. For each category we provide examples of AI approaches, including supervised and unsupervised ML, deep learning, and natural language processing. AI technology, still nascent in healthcare, has great potential to transform the way we diagnose and treat patients with neurocognitive disorders

Detecting clinically meaningful biomarkers with repeated measurements in an Electronic Health Record

Electronic health record (EHR) data are becoming an increasingly common data source for understanding clinical risk of acute events. While their longitudinal nature presents opportunities to observe changing risk over time, these analyses are complicated by the sparse and irregular measurements of many of the clinical metrics making typical statistical methods unsuitable for these data. In this paper, we present an analytic procedure to both sample from an EHR and analyze the data to detect clinically meaningful markers of acute myocardial infarction (MI). Using an EHR from a large national dialysis organization we abstracted the records of 64,318 individuals and identified 5,314 people that had an MI during the study period. We describe a nested case-control design to sample appropriate controls and an analytic approach using regression splines. Fitting a mixed-model with truncated power splines we perform a series of goodness-of-fit tests to determine whether any of 11 regularly collected laboratory markers are useful clinical predictors. We test the clinical utility of each marker using an independent test set. The results suggest that EHR data can be easily used to detect markers of clinically acute events. Special software or analytic tools are not needed, even with irregular EHR data.Comment: 23 pages, 3 figure

Exploring health-seeking behaviours among Nigerians in the UK: towards improved healthcare utilisation

The changing face of patient’s populations in the UK has resulted in notable increases in cultural diversity that impact on health care service provision, access and utilisation; with health services underutilisation, prevalent more among immigrants due to heavy reliance on cultural and religious cure methods. The aim of this thesis therefore, was to explore how Nigerians in the UK engage with the British health system. This objective was pursued by integrating immigration issues, with factors associated with decisions to seek medical help, including health beliefs, access, attitudes, cognitions, and socio-political and religious experiences (past and present) that impact upon health outcomes. A triangulation approach was employed, involving a critical review of measures, and four empirical studies consisting of qualitative and quantitative research methodologies. Results show that health-seeking behaviours among Nigerians were best accounted for by their religious and cultural beliefs, as typified by their health context before migration. Religion was not found as a barrier to medical help-seeking; the regression analysis revealed that belonging to the Christian religious group predicted increased medical help-seeking; although assimilation to the British culture was associated with reduced religious behaviours. However, the role of other religious groups regarding medical help-seeking remains unclear, and needs a more focused study. In addition, care providers mainly agreed on the benefits of integrating the spiritual methods into formal healthcare systems, bringing some challenges which were tentatively negotiated through the theory of transformative coping (TTC). Findings have implications for research, policies, and clinical practice, particularly when culture-sensitive and integrated health interventions are tailored to the needs of the diverse immigrant populations in the UK

The effect of age on referral to and use of specialist palliative care services in adult cancer patients: a systematic review

Objective: to investigate variations in the use of specialist palliative care (SPC) services for adult cancer patients, in relation to age.Design: systematic review of studies examining use of or referral to SPC services in adult cancer patients.Search strategy and selection criteria: six electronic databases (Medline, Embase, Web of Science, HMIC, SIGLE and AgeInfo) were searched for studies published between 1966 and March 2005, and references in the articles identified were also examined. Inclusion criteria were all studies which provided data on age in relation to use of or referral to SPC. Two reviewers independently selected studies, extracted data and assessed methodological quality according to defined criteria.Main outcome measures: use of or referral to SPC services, determined from all sources of report (patient, informal carer, health care professional, health care records).Results: 14 studies were identified. All reported a statistically significant lower use of SPC among older cancer patients (65 and above or older) at a univariate level [crude odds ratios ranged from 0.33 (0.15-0.72) to 0.82 (0.80-0.82)]. However, there were important methodological weaknesses in all of the studies identified; most crucially, studies failed to consider variations in use in relation to need for SPC.Conclusions: there is some evidence that older people are less likely to be referred to, or to use, SPC. These findings require confirmation in studies using prospectively collected data which control for patient's need for SPC