New horizons in the role of digital data in the healthcare of older people.

There are national and global moves to improve effective digital data design and application in healthcare. This New Horizons commentary describes the role of digital data in healthcare of the ageing population. We outline how health and social care professionals can engage in the proactive design of digital systems that appropriately serve people as they age, carers and the workforce that supports them. KEY POINTS: Healthcare improvements have resulted in increased population longevity and hence multimorbidity. Shared care records to improve communication and information continuity across care settings hold potential for older people. Data structure and coding are key considerations. A workforce with expertise in caring for older people with relevant knowledge and skills in digital healthcare is important.

Engagement in research during specialist geriatric medicine training: results of a national trainee survey.

INTRODUCTION: Meaningful ageing research across the UK is dependent on a network of engaged geriatricians. The research in geriatric specialty training (RGST) survey aimed to establish current research opportunities available to geriatric medicine specialty trainees in the UK. METHODS: The RGST survey was disseminated to UK higher specialist trainees in geriatric medicine in 2019 via the Geriatric Medicine Research Collaborative network. RESULTS: Among the 36.9% (192/521) of respondents, 44% (83/188) reported previous research involvement and 7% (n=8) held a PhD or MD. Of the respondents with no research experience to date, 59.0% (n=49) reported a desire to undertake a period of research. One-third (31%) of geriatric registrars surveyed felt that they had gained sufficient research experience during their training. Perceived encouragement and support to undertake research was low (30.7%). Enablers and barriers to research engagement were identified. CONCLUSION: Research opportunity and engagement in geriatric medicine training is lacking. This could jeopardise the future workforce of research-active geriatricians in the UK and limit patient access to emerging research and innovation. Interventions to promote research engagement among geriatric medicine trainees are needed to facilitate integration of research into routine clinical practice to improve the health and care of older people.

Effect of Angiotensin System Inhibitors on Physical Performance in Older People - A Systematic Review and Meta-Analysis.

OBJECTIVE: Preclinical and observational data suggest that angiotensin converting enzyme inhibitors (ACEi) and angiotensin receptor blockers (ARBs) may be able to improve physical performance in older people via direct and indirect effects on skeletal muscle. We aimed to summarize current evidence from randomised controlled trials in this area. DESIGN: Systematic review and meta-analysis. SETTING AND PARTICIPANTS: Randomized controlled trials enrolling older people, comparing ACEi or ARB to placebo, usual care or another antihypertensive agent, with outcome data on measures of physical performance. METHODS: We searched multiple electronic databases without language restriction between inception and the end of February 2020. Trials were excluded if the mean age of participants was <65 years or treatment was targeting specific diseases known to affect muscle function (for example heart failure). Data were sought on measures of endurance and strength. Standardized mean difference (SMD) treatment effects were calculated using random-effects models with RevMan software. RESULTS: Eight trials (952 participants) were included. Six trials tested ACEi, 2 trials tested ARBs. The mean age of participants ranged from 66 to 79 years, and the duration of treatment ranged from 2 months to 1 year. Trials recruited healthy older people and people with functional impairment; no trials specifically targeted older people with sarcopenia. Risk of bias for all trials was low to moderate. No significant effect was seen on endurance outcomes [6 trials, SMD 0.04 (95% CI -0.22 to 0.29); P = .77; I2 = 53%], strength outcomes [6 trials, SMD -0.02 (95% CI -0.18 to 0.14), P = .83, I2 = 21%] or the short physical performance battery [3 trials, SMD -0.04 (95% CI -0.19 to 0.11), P = .60, I2 = 0%]. No evidence of publication bias was evident on inspection of funnel plots. CONCLUSIONS AND IMPLICATIONS: Existing evidence does not support the use of ACE inhibitors or angiotensin receptor blockers as a single intervention to improve physical performance in older people.

Prevalence and geographical variation of dementia in New Zealand from 2012 to 2015: Brief report utilising routinely collected data within the Integrated Data Infrastructure.

OBJECTIVES: There are no national dementia epidemiological studies using New Zealand (NZ) data. NZ routinely collects health-care data within the Integrated Data Infrastructure (IDI). The study objectives were to 1) investigate late-onset dementia estimates using the IDI between 2012-2015 and compare these with 2) published estimates, and 3) variations between North and South Islands and ethnicity. METHODS: A population-based, retrospective cohort design was applied to routinely collected de-identified health/administrative IDI data. Dementia was defined by ICD-10-AM dementia codes or anti-dementia drugs. RESULTS: Approximately 2% of those aged ≥60 years had dementia, lower than published estimates. Dementia was higher in North Island; in 80- to 89-year-olds; among the Maori population when age-standardised, and 9% of all dementia cases had >1 dementia sub-type. CONCLUSIONS: To our knowledge, this is the first study ascertaining dementia estimates using NZ's whole-of-population IDI data. Estimates were lower than existing NZ estimates, for several reasons. Further work is required, including expanding IDI data sets, to develop future estimates that better reflect NZ's diverse population.

New Horizons in the use of routine data for ageing research.

The past three decades have seen a steady increase in the availability of routinely collected health and social care data and the processing power to analyse it. These developments represent a major opportunity for ageing research, especially with the integration of different datasets across traditional boundaries of health and social care, for prognostic research and novel evaluations of interventions with representative populations of older people. However, there are considerable challenges in using routine data at the level of coding, data analysis and in the application of findings to everyday care. New Horizons in applying routine data to investigate novel questions in ageing research require a collaborative approach between clinicians, data scientists, biostatisticians, epidemiologists and trial methodologists. This requires building capacity for the next generation of research leaders in this important area. There is a need to develop consensus code lists and standardised, validated algorithms for common conditions and outcomes that are relevant for older people to maximise the potential of routine data research in this group. Lastly, we must help drive the application of routine data to improve the care of older people, through the development of novel methods for evaluation of interventions using routine data infrastructure. We believe that harnessing routine data can help address knowledge gaps for older people living with multiple conditions and frailty, and design interventions and pathways of care to address the complex health issues we face in caring for older people.

Investigating the Relationship Between Type 2 Diabetes and Dementia Using Electronic Medical Records in the GoDARTS Bioresource.

OBJECTIVE: To investigate the impact of type 2 diabetes on incidence of major dementia subtypes, Alzheimer and vascular dementia, using electronic medical records (EMR) in the GoDARTS bioresource. RESEARCH DESIGN AND METHODS: GoDARTS (Genetics of Diabetes Audit and Research in Tayside Scotland) comprises a large case-control study of type 2 diabetes with longitudinal follow-up in EMR. Dementia case subjects after recruitment were passively identified in the EMR, and using a combination of case note review, an Alzheimer-specific weighted genetic risk score (wGRS), and APOE4 genotype, we validated major dementia subtypes. We undertook a retrospective matched cohort study to determine the risk of type 2 diabetes status for incident dementia accounting for competing risk of death. RESULTS: Type 2 diabetes status was associated with a significant risk of any dementia (cause-specific hazard ratio [csHR] 1.46, 95% CI 1.31-1.64), which was attenuated, but still significant, when competing risk of death was accounted for (subdistribution [sd]HR 1.26, 95% CI 1.13-1.41). The accuracy of EMR-defined cases of Alzheimer or vascular dementia was high-positive predictive value (PPV) 86.4% and PPV 72.8%, respectively-and wGRS significantly predicted Alzheimer dementia (HR 1.23, 95% CI 1.12-1.34) but not vascular dementia (HR 1.02, 95% CI 0.91-1.15). Conversely, type 2 diabetes was strongly associated with vascular dementia (csHR 2.47, 95% C 1.92-3.18) but not Alzheimer dementia, particularly after competing risk of death was accounted for (sdHR 1.02, 95% CI 0.87-1.18). CONCLUSIONS: Our study indicates that type 2 diabetes is associated with an increased risk of vascular dementia but not with an increased risk of Alzheimer dementia and highlights the potential value of bioresources linked to EMR to study dementia.

Predicting Discharge to Institutional Long-Term Care After Stroke: A Systematic Review and Metaanalysis.

BACKGROUND/OBJECTIVES: Stroke is a leading cause of disability worldwide, and a significant proportion of stroke survivors require long-term institutional care. Understanding who cannot be discharged home is important for health and social care planning. Our aim was to establish predictive factors for discharge to institutional care after hospitalization for stroke. DESIGN: We registered and conducted a systematic review and meta-analysis (PROSPERO: CRD42015023497) of observational studies. We searched MEDLINE, EMBASE, and CINAHL Plus to February 2017. Quantitative synthesis was performed where data allowed. SETTING: Acute and rehabilitation hospitals. PARTICIPANTS: Adults hospitalized for stroke who were newly admitted directly to long-term institutional care at the time of hospital discharge. MEASUREMENTS: Factors associated with new institutionalization. RESULTS: From 10,420 records, we included 18 studies (n = 32,139 participants). The studies were heterogeneous and conducted in Europe, North America, and East Asia. Eight studies were at high risk of selection bias. The proportion of those surviving to discharge who were newly discharged to long-term care varied from 7% to 39% (median 17%, interquartile range 12%), and the model of care received in the long-term care setting was not defined. Older age and greater stroke severity had a consistently positive association with the need for long-term care admission. Individuals who had a severe stroke were 26 times as likely to be admitted to long-term care than those who had a minor stroke. Individuals aged 65 and older had a risk of stroke that was three times as great as that of younger individuals. Potentially modifiable factors were rarely examined. CONCLUSION: Age and stroke severity are important predictors of institutional long-term care admission directly from the hospital after an acute stroke. Potentially modifiable factors should be the target of future research. Stroke outcome studies should report discharge destination, defining the model of care provided in the long-term care setting.

Predicting discharge to institutional long-term care following acute hospitalisation: a systematic review and meta-analysis.

Background: moving into long-term institutional care is a significant life event for any individual. Predictors of institutional care admission from community-dwellers and people with dementia have been described, but those from the acute hospital setting have not been systematically reviewed. Our aim was to establish predictive factors for discharge to institutional care following acute hospitalisation. Methods: we registered and conducted a systematic review (PROSPERO: CRD42015023497). We searched MEDLINE; EMBASE and CINAHL Plus in September 2015. We included observational studies of patients admitted directly to long-term institutional care following acute hospitalisation where factors associated with institutionalisation were reported. Results: from 9,176 records, we included 23 studies (n = 354,985 participants). Studies were heterogeneous, with the proportions discharged to a care home 3-77% (median 15%). Eleven studies (n = 12,642), of moderate to low quality, were included in the quantitative synthesis. The need for institutional long-term care was associated with age (pooled odds ratio (OR) 1.02, 95% confidence intervals (CI): 1.00-1.04), female sex (pooled OR 1.41, 95% CI: 1.03-1.92), dementia (pooled OR 2.14, 95% CI: 1.24-3.70) and functional dependency (pooled OR 2.06, 95% CI: 1.58-2.69). Conclusions: discharge to long-term institutional care following acute hospitalisation is common, but current data do not allow prediction of who will make this transition. Potentially important predictors evaluated in community cohorts have not been examined in hospitalised cohorts. Understanding these predictors could help identify individuals at risk early in their admission, and support them in this transition or potentially intervene to reduce their risk.

Training tomorrow's doctors.

The ability of our NHS to deliver world-class compassionate care is dependent on the quality of training and education of our staff. We know that the path of moving from novice to expert is far from linear. Instead, it is a complex journey that is domain specific with multiple variations reflecting the individuality of our learners. Within this complex journey, there is a need to train the doctors of tomorrow to be humanistic, competent, patient-centred, resilient beings who will thrive in a challenging environment, striving to advance medicine. We discuss two models of curricula, the longitudinal integrated programmes and the internal medicine curriculum, which are proposed to address the healthcare needs of the UK population. In this article, we look at the opportunities that exist, the future potentials for medical education, and the challenges to overcome as we endeavour to create the best education models for physicians in the 21st century.