51 research outputs found

    Shaping the future of our training

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    Peer reviewedPublisher PD

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

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    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./

    Predicting discharge to institutional long-term care after stroke: a systematic review & meta-analysis

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    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

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

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    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

    Identifying care-home residents in routine healthcare datasets:a diagnostic test accuracy study of five methods

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    Background: there is no established method to identify care-home residents in routine healthcare datasets. Methods matching patient’s addresses to known care-home addresses have been proposed in the UK, but few have been formally evaluated. Study design: prospective diagnostic test accuracy study. Methods: four independent samples of 5,000 addresses from Community Health Index (CHI) population registers were sampled for two NHS Scotland Health Boards on 1 April 2017, with one sample of adults aged ≥65 years and one of all residents. To derive the reference standard, all 20,000 addresses were manually adjudicated as ‘care-home address’ or not. The performance of five methods (NHS Scotland assigned CHI Institution Flag, exact address matching, postcode matching, Phonics and Markov) was evaluated compared to the reference standard. Results: the CHI Institution Flag had a high PPV 97–99% in all four test sets, but poorer sensitivity 55–89%. Exact address matching failed in every case. Postcode matching had higher sensitivity than the CHI flag 78–90%, but worse PPV 77–85%. Area under the receiver operating curve values for Phonics and Markov scores were 0.86–0.95 and 0.93–0.98, respectively. Phonics score with cut-off ≥13 had PPV 92–97% with sensitivity 72–87%. Markov PPVs were 90–95% with sensitivity 69–90% with cut-off ≥29.6. Conclusions: more complex address matching methods greatly improve identification compared to the existing NHS Scotland flag or postcode matching, although no method achieved both sensitivity and positive predictive value > 95%. Choice of method and cut-offs will be determined by the specific needs of researchers and practitioners

    Development of a UK core dataset for geriatric medicine research: a position statement and results from a Delphi consensus process

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    BACKGROUND: There is lack of standardisation in assessment tools used in geriatric medicine research, which makes pooling of data and cross-study comparisons difficult. METHODS: We conducted a modified Delphi process to establish measures to be included within core and extended datasets for geriatric medicine research in the United Kingdom (UK). This included three complete questionnaire rounds, and one consensus meeting. Participants were selected from attendance at the NIHR Newcastle Biomedical Research Centre meeting, May 2019, and academic geriatric medicine e-mailing lists. Literature review was used to develop the initial questionnaire, with all responses then included in the second questionnaire. The third questionnaire used refined options from the second questionnaire with response ranking. RESULTS: Ninety-eight responses were obtained across all questionnaire rounds (Initial: 19, Second: 21, Third: 58) from experienced and early career researchers in geriatric medicine. The initial questionnaire included 18 questions with short text responses, including one question for responders to suggest additional items. Twenty-six questions were included in the second questionnaire, with 108 within category options. The third questionnaire included three ranking, seven final agreement, and four binary option questions. Results were discussed at the consensus meeting. In our position statement, the final consensus dataset includes six core domains: demographics (age, gender, ethnicity, socioeconomic status), specified morbidities, functional ability (Barthel and/or Nottingham Extended Activities of Daily Living), Clinical Frailty Scale (CFS), cognition, and patient-reported outcome measures (dependent on research question). We also propose how additional variables should be measured within an extended dataset. CONCLUSIONS: Our core and extended datasets represent current consensus opinion of academic geriatric medicine clinicians across the UK. We consider the development and further use of these datasets will strengthen collaboration between researchers and academic institutions

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

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    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

    New Horizons in the use of routine data for ageing research

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    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
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