How to include anonymised routine data in emergency care research

A workshop on development and use of anonymised datasets using ambulance and other health service data

Assessing the excess health service utilisation and direct medical costs of injuries.

This study was undertaken with the aim to develop improved measures of health service utilisation (HSU) and direct medical costs following an index injury, utilising large scale datasets linked via anonymous patient identifiers.A cohort of anonymous injury patients resident in Swansea and attending an emergency department (ED) or admitted to hospital between 01/04/2005 and 31/03/2007 were identified and tracked as they progressed through various treatment stages following their index injury, incorporating ED attendances, inpatient stay and outpatient contacts. To determine the extent of the subsequent HSU and direct medical costs associated with the index injury a unique model was developed whereby the numbers, lengths and treatment costs of health service contacts observed amongst the cohort of injured individuals during the follow-up period were compared with the equivalent figures expected in the absence of an injury.On average each index injury was found to lead to an excess of 0.12 (95% Cl 0.11, 0.13) ED attendances, 0.07 (95% Cl 0.06, 0.08) inpatient admissions, 1.00 (95% Cl 0.78, 1.23) inpatient bed days and 0.55 (95% Cl 0.52, 0.58) outpatient contacts being estimated over the follow-up period. Moreover, every index injury resulted in mean excess ED, inpatient and outpatient treatment costs of £12.05 (95% Cl £11.05, £13.05), £492.43 (95% Cl £415.66, £569.21) and £73.30 (95% Cl £68.44, £78.17), respectively, equating to a combined figure of £577.79 (95% Cl £500.32, £655.26). Across the entire injured cohort this amounts to an overall excess direct medical cost total of £17.6 million being incurred, with the equivalent figure for the whole of Wales potentially being as high as £306.4 million.Together with signifying the magnitude of the HSU and direct medical costs resulting from injury, this study has introduced and implemented improved methods for estimating these outcome measures based on the use of anonymous patient record linkage

Impact of an Inpatient Geriatric Consultative Service on Outcomes for Cognitively Impaired Patients

Background Impact of geriatric consultative services (GCS) on hospital readmission and mortality outcomes for cognitively impaired (CI) patients is not known. Objective Evaluate impact of GCS on hospital readmission and mortality among CI inpatients. Design Secondary data-analysis of a prospective trial of a computerized decision support system between July 1, 2006, and May 30, 2008. Setting Study conducted at XXXXX hospital, a 340-bed, public hospital with over 2,300 yearly admissions of 65 or older. Patients 415 inpatients aged 65 and older with CI were enrolled from July 2006 to March 2008. Measurements 30 day and one year mortality and hospital readmission following the index admission. Cox’s proportional hazard models were used to determine the association between receiving GCS, re-admission or mortality while adjusting for demographics, discharge destination, delirium, Charlson Comorbidity Index, and prior hospitalizations. The propensity score method was used to adjust for the non-random assignment of GCS. Results Patients receiving GCS were older (79; 8.1 SD vs 76; 7.8 SD; p<.001 with higher incidence of delirium (49% vs. 29%; p<.001)). No significant differences were found between the groups for hospital readmission (Hazard Ratio (HR)=1.19; 95% CI = 0.89, 1.59) and mortality at 12 months of index admission (HR=.91 ; 95% CI = 0.59, 1.40). However, a significant increase in readmissions was observed for the GCS group (HR=1.75; 95% CI = 1.06–2.88) at 30 days post-discharge. Conclusion One year post-discharge outcomes of CI patients that received GCS were not different from patients who did not receive the service. New models of care are needed to improve post-discharge readmission and mortality among hospitalized patients with CI

Obesity in pregnancy: a retrospective prevalence-based study on health service utilisation and costs on the NHS.

Objective: To estimate the direct healthcare cost of being overweight or obese throughout pregnancy to the National Health Service in Wales. Design: Retrospective prevalence-based study. Setting: Combined linked anonymised electronic datasets gathered on a cohort of women enrolled on the Growing Up in Wales: Environments for Healthy Living (EHL) study. Women were categorised into two groups: normal body mass index (BMI; n=260) and overweight/obese (BMI>25; n=224). Participants: 484 singleton pregnancies with available health service records and an antenatal BMI. Primary outcome measure: Total health service utilisation (comprising all general practitioner visits and prescribed medications, inpatient admissions and outpatient visits) and direct healthcare costs for providing these services in the year 2011–2012. Costs are calculated as cost of mother (no infant costs are included) and are related to health service usage throughout pregnancy and 2 months following delivery. Results: There was a strong association between healthcare usage cost and BMI ( p<0.001). Adjusting for maternal age, parity, ethnicity and comorbidity, mean total costs were 23% higher among overweight women (rate ratios (RR) 1.23, 95% CI 1.230 to 1.233) and 37% higher among obese women (RR 1.39, 95% CI 1.38 to 1.39) compared with women with normal weight. Adjusting for smoking, consumption of alcohol, or the presence of any comorbidities did not materially affect the results. The total mean cost estimates were £3546.3 for normal weight, £4244.4 for overweight and £4717.64 for obese women. Conclusions: Increased health service usage and healthcare costs during pregnancy are associated with increasing maternal BMI; this was apparent across all health services considered within this study. Interventions costing less than £1171.34 per person could be cost-effective if they reduce healthcare usage among obese pregnant women to levels equivalent to that of normal weight women

Supporting women, girls and people who menstruate to participate in physical activity – Rapid evidence summary

Abstract Insufficient physical activity is a leading risk factor for non-communicable diseases and has a negative effect on mental health and quality of life. Women, girls and people who menstruate living in Wales are less likely to engage in regular physical activity than boys and men. The aim of this rapid evidence summary is to identify research focusing on physical activity participation (including exercise and sport) of women, girls and people who menstruate in relation to the menstrual cycle, to inform the Welsh Government Period Proud Action Plan. Results 42 reports were identified, including overviews of reviews, systematic reviews, a scoping review, organisational reports, and primary studies. The secondary research evidence was published between 2008 and 2024 with the most recent searches being conducted in September 2023. The primary studies were published between 2020 and 2022. The organisational reports were published between 2018 and 2024. Research Implications and Evidence Gaps There is a need for interventions that could support physical activity participation (including exercise or sport) of women, girls and people who menstruate in relation to the menstrual cycle. These interventions need to consider and address barriers that women, girls and people who menstruate face in relation to their menstrual cycle, and robust evaluations are required to determine effectiveness

Population based absolute and relative survival to 1 year of people with diabetes following a myocardial infarction: A cohort study using hospital admissions data

<p>Abstract</p> <p>Background</p> <p>People with diabetes who experience an acute myocardial infarction (AMI) have a higher risk of death and recurrence of AMI. This study was commissioned by the Department for Transport to develop survival tables for people with diabetes following an AMI in order to inform vehicle licensing.</p> <p>Methods</p> <p>A cohort study using data obtained from national hospital admission datasets for England and Wales was carried out selecting all patients attending hospital with an MI for 2003-2006 (inclusion criteria: aged 30+ years, hospital admission for MI (defined using ICD 10 code I21-I22). STATA was used to create survival tables and factors associated with survival were examined using Cox regression.</p> <p>Results</p> <p>Of 157,142 people with an MI in England and Wales between 2003-2006, the relative risk of death or recurrence of MI for those with diabetes (n = 30,407) in the first 90 days was 1.3 (95%CI: 1.26-1.33) crude rates and 1.16 (95%CI: 1.1-1.2) when controlling for age, gender, heart failure and surgery for MI) compared with those without diabetes (n = 129,960). At 91-365 days post AMI the risk was 1.7 (95% CI 1.6-1.8) crude and 1.50 (95%CI: 1.4-1.6) adjusted. The relative risk of death or re-infarction was higher at younger ages for those with diabetes and directly after the AMI (Relative risk; RR: 62.1 for those with diabetes and 28.2 for those without diabetes aged 40-49 [compared with population risk]).</p> <p>Conclusions</p> <p>This is the first study to provide population based tables of age stratified risk of re-infarction or death for people with diabetes compared with those without diabetes. These tables can be used for giving advice to patients, developing a baseline to compare intervention studies or developing license or health insurance guidelines.</p

HERALD (Health Economics using Routine Anonymised Linked Data)

&lt;b&gt;Background&lt;/b&gt; Health economic analysis traditionally relies on patient derived questionnaire data, routine datasets, and outcomes data from experimental randomised control trials and other clinical studies, which are generally used as stand-alone datasets. Herein, we outline the potential implications of linking these datasets to give one single joined up data-resource for health economic analysis.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Method&lt;/b&gt; The linkage of individual level data from questionnaires with routinely-captured health care data allows the entire patient journey to be mapped both retrospectively and prospectively. We illustrate this with examples from an Ankylosing Spondylitis (AS) cohort by linking patient reported study dataset with the routinely collected general practitioner (GP) data, inpatient (IP) and outpatient (OP) datasets, and Accident and Emergency department data in Wales. The linked data system allows: (1) retrospective and prospective tracking of patient pathways through multiple healthcare facilities; (2) validation and clarification of patient-reported recall data, complementing the questionnaire/routine data information; (3) obtaining objective measure of the costs of chronic conditions for a longer time horizon, and during the pre-diagnosis period; (4) assessment of health service usage, referral histories, prescribed drugs and co-morbidities; and (5) profiling and stratification of patients relating to disease manifestation, lifestyles, co-morbidities, and associated costs.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Results&lt;/b&gt; Using the GP data system we tracked about 183 AS patients retrospectively and prospectively from the date of questionnaire completion to gather the following information: (a) number of GP events; (b) presence of a GP 'drug' read codes; and (c) the presence of a GP 'diagnostic' read codes. We tracked 236 and 296 AS patients through the OP and IP data systems respectively to count the number of OP visits; and IP admissions and duration. The results are presented under several patient stratification schemes based on disease severity, functions, age, sex, and the onset of disease symptoms.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Conclusion&lt;/b&gt; The linked data system offers unique opportunities for enhanced longitudinal health economic analysis not possible through the use of traditional isolated datasets. Additionally, this data linkage provides important information to improve diagnostic and referral pathways, and thus helps maximise clinical efficiency and efficiency in the use of resources

Indicate separate contributions of long-lived and short-lived greenhouse gases in emission targets

European Union funding: 821205, 821003, 820829. Wellcome Trust: 205212/Z/16/