National data about mortality in people with ID provides a basis for public health interventions. Linked data using GP records to identify people with ID could provide comprehensive population-based monitoring in England, unbiased by the circumstances of illnesses or death; to date information governance constraints have prevented this. However, GPs in England currently identify only around 0.5% of the population as having ID, suggesting that individuals with mild, non-syndromic ID are largely missed. Notably common causes of death suggest control of cardiovascular risk factors, epilepsy and dysphagia, management of thrombotic risks and colorectal screening are important areas for health promotion initiatives.
BackgroundThere is currently limited evidence regarding the extent Real World Evidence (RWE) has directly impacted the health and social care systems. The aim of this review is to identify national guidelines or guidances published in England from 2000 onwards which have referenced studies using the governmental primary care data provider the Clinical Practice Research Datalink (CPRD).MethodsThe methodology recommended by Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was followed. Four databases were searched and documents of interest were identified through a search algorithm containing keywords relevant to CPRD. A search diary was maintained with the inclusion/exclusion decisions which were performed by two independent reviewers.ResultsTwenty-five guidance documents were included in the final review (following screening and assessment for eligibility), referencing 43 different CPRD/GPRD studies, all published since 2007. The documents covered 12 disease areas, with the majority (N =7) relevant to diseases of the Central Nervous system (CNS). The 43 studies provided evidence of disease epidemiology, incidence/prevalence, pharmacoepidemiology, pharmacovigilance and health utilisation.ConclusionsA slow uptake of RWE in clinical and therapeutic guidelines (as provided by UK governmental structures) was noticed. However, there seems to be an increasing trend in the use of healthcare system data to inform clinical practice, especially as the real world validity of clinical trials is being questioned. In order to accommodate this increasing demand and meet the paradigm shift expected, organisations need to work together to enable or improve data access, undertake translational and relevant research and establish sources of reliable evidence.
Our figures are likely to be an underestimate as GP identification of people with ID is known to be far from complete. However, they indicate that the number of people with ID in acute hospital settings is likely to be substantially more than a recent survey of English health services indicated they were aware of. The study is intended to help guide expectations for acute hospitals seeking to audit the completeness of their identification of people with ID and to indicate their likely distribution between clinical specialties.
Background Hospital admissions for preventable reasons [ambulatory care sensitive (ACS) conditions] can indicate gaps in access to or quality of primary care. This paper seeks to document the numbers and causes of these admissions in England for people with intellectual disabilities (ID) compared with those without.Methods Observational cohort study of number and duration of emergency admitted patient episodes for ACS conditions, overall and by cause, using the Clinical Practice Research Datalink GOLD primary care database and the linked Hospital Episode Statistics Admitted Patient Care dataset. Results The study covered 5.2% of the population of England from April 2010 to March 2014 giving a total population base of 59 280 person-years for people with ID and 11 103 910 for people without identified ID. The rate of emergency admissions for ACS conditions for people with ID was 77.5 per 1000 person-years. As a crude comparison, this was 3.0 times the rate for those without ID, but standardising for the distinct demography of this group, the number of episodes was 4.8 times that expected if they had the same age-specific and sex-specific rates. Stay durations for these episodes were longer for both young-age and working-age people with ID. Overall people with ID used 399.8 beddays per 1000 person-years. As a crude comparison, this is 2.8 times the figure for people without ID. Standardising for their age and sex profile, it is 5.4 times the number expected if they had the same age-specific and sex-specific rates. For patients with ID, 16.6% (one in six) of all admitted patient episodes and 24.3% (one in four) of in-patient care days for people with ID were for ACS conditions. Corresponding figures for those without ID were 8.3% (one in 12) and 14.4% (one in seven). The difference in rates between those with and without ID was most marked in people of working age. The three most common causes of emergency episodes for ACS conditions in people with ID were convulsions and epilepsy, influenza pneumonia and aspiration pneumonitis. Influenza pneumonia was also a common cause for people without ID. Episodes for convulsions and epilepsy and aspiration pneumonitis were specifically associated with people with ID. Conclusions Rates of hospital admissions for ACS conditions provide an important indicator of health literacy, basic self-care (or support by carers) and the accessibility of primary care. High rates are seen for some conditions specifically associated with premature death in people with ID. Local monitoring of
Purpose UK primary care provides a rich data source for research. The impact of proposed data collection restrictions is unknown. This study aimed to assess the impact of restricting the scope of electronic health record (EHR) data collection on the ability to conduct research. The study estimated the consequences of restricted data collection on published Clinical Practice Research Datalink studies from high impact journals or referenced in clinical guidelines. Methods A structured form was used to systematically analyse the extent to which individual studies would have been possible using a database with data collection restrictions in place: (1) retrospective collection of specified diseases only; (2) retrospective collection restricted to a 6‐ or 12‐year period; (3) prospective and retrospective collection restricted to non‐sensitive data. Outcomes were categorised as unfeasible (not reproducible without major bias); compromised (feasible with design modification); or unaffected. Results Overall, 91% studies were compromised with all restrictions in place; 56% studies were unfeasible even with design modification. With restrictions on diseases alone, 74% studies were compromised; 51% were unfeasible. Restricting collection to 6/12 years had a major impact, with 67 and 22% of studies compromised, respectively. Restricting collection of sensitive data had a lesser but marked impact with 10% studies compromised. Conclusion EHR data collection restrictions can profoundly reduce the capacity for public health research that underpins evidence‐based medicine and clinical guidance. National initiatives seeking to collect EHRs should consider the implications of restricting data collection on the ability to address vital public health questions.
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