Emergency Department Dataset Research Articles

Overcoming challenges of establishing a hospital-based out-of-hospital cardiac arrest registry: accuracy of case identification using administrative data and clinical registries

IntroductionComprehensive identification of out-of-hospital cardiac arrest (OHCA) cases for inclusion in registries remains challenging due to the inherent diversity of OHCA aetiology, presentation, and management. The Northern Adelaide Local Health Network (NALHN) OHCA registry identifies OHCAs presenting to NALHN hospitals using existing data sources to monitor in-hospital treatment and survival. This study aimed to investigate the accuracy of hospital-based data sources for identifying OHCA cases treated at hospital. MethodsRetrospective analysis of all OHCAs aged >18 years included in the NALHN OHCA registry between 2011–16. Registry cases are identified from an emergency medical service (EMS) OHCA registry, Emergency Department (ED) and ICD-10 coding datasets, and key-word searches of two in-hospital clinical registries. Sensitivity and positive predictive values (PPV) of each hospital-based data source were analysed with respect to (a) the number of cases expected to be identified by that source, (b) total OHCA. Non-OHCAs yielded by each source were explored and a sub-analysis of ICD-10 codes was performed. ResultsBetween 2011–16, the four hospital-based sources yielded 992 cases, of which 383 were confirmed as OHCA. The ED coding dataset was the most accurate with a sensitivity and PPV of 78%. The ICD-10 coding dataset had good sensitivity but low PPV (33%). The ED coding dataset, combined with the two in-hospital clinical registries, identified 93% of OHCAs. ConclusionsNo single dataset identified all OHCAs presenting to NALHN hospitals. Combined hospital-based data sources provide a valid method of identifying OHCAs treated at hospital that may be adapted to augment EMS-based data.

Tracking Violent Crime with Ambulance Data: How Much Crime Goes Uncounted?

Research QuestionWhat proportion of ambulance records documenting injuries caused by criminal violence is included in police records for violent crimes occurring in the same area at the same dates and times as incidents found in ambulance records?DataWe analysed subsets of three datasets during matched time periods: West Midlands Ambulance Service records of all 36,639 incidents of violent injuries from January 2012 to March 2017; 132,317 West Midlands Police records of violent crimes from January 2012 to December 2015; and 9083 records of treatment of violent injuries as recorded in hospital Emergency Department (ED) records covering September 2013 to March 2016.MethodsWe compared all incidents in the ambulance dataset and ED data to corresponding locations and times in incidents recorded in police datasets.FindingsApproximately 90% of cases in the ambulance dataset did not have a corresponding case in the police dataset. The proportion was even lower in the Emergency Department dataset, where less than 5% of cases were successfully matched to a police record. These data suggest that adding the medical data to the police data could add 15 to 20% more violent offences to the totals recorded by the police.ConclusionsTracking identified ambulance data can add substantial numbers of serious violent crimes, over and above those reported to the police. These added cases can increase the targeting of police and public health resources to prevent harm against victims, at places, and by offenders at highest risk of serious violence.

Antibiotic utilization for adult acute respiratory tract infections in United States Emergency Departments.

Antibiotic stewardship programs have been a major focus in recent years to curtail antibiotic resistance. The purpose of this study was to evaluate antibiotic utilization for acute respiratory tract infections (ARTI) in the Emergency Department (ED) setting. A retrospective analysis of adult ARTI visits to EDs utilizing 2011-2017 National Hospital Ambulatory Medical Care Survey- Emergency Department (NHAMCS-ED) datasets was conducted. Included were all visits of adults (≥18 years) diagnosed with ARTI. Antibiotics were determined based upon NHAMCS-ED use of the Multum Lexicon Drug Database coding system. All significance tests were two-sided, P-value <0.05 for significance. A total of 4632 unweighted ED visits, which represented more than 28 million US ED visits from 2011 to 2017, with 57.2% receiving a prescription for antibiotics. Antibiotic prescriptions for ARTI significantly declined from 65.8% in 2011 to 54.3% in 2017 (P = 0.046). Among all visits, patients were more likely to receive an antibiotic if they were over age 45 (33.0% vs 27.6%, P = 0.005), male (36.7% vs. 32.3%, P = 0.039), and presenting in a non-MSA ED (21.4% vs. 14.5%, P = 0.002). No association was found between antibiotic prescription and race (P = 0.076) insurance (P = 0.488), CBC (P = 0.148), x-ray (P = 0.278), and blood cultures (P = 0.182). We found a significant reduction in the utilization of antibiotics among adult ARTI visits to U.S. EDs from 2011 to 2017. This is an improvement from previous studies which showed no change, suggesting that antimicrobial stewardship efforts may be impacting overall antibiotic use and should continue to be practiced.

SIM-PFED: A Simulation-Based Decision Making Model of Patient Flow for Improving Patient Throughput Time in Emergency Department

Healthcare sectors face multiple threats, and the hospital emergency department (ED) is one of the most crucial hospital areas. ED plays a key role in promoting hospitals' goals of enhancing service efficiency. ED is a complex system due to the stochastic behavior of patient arrivals, the unpredictability of the care required by patients, and the department's complex nature. Simulations are effective tools for analyzing and optimizing complex ED operations. Although existing ED simulation models have substantially improved ED performance in terms of ensuring patient satisfaction and effective treatment services, many deficiencies continue to exist in addressing the key challenge in ED, namely, long patient throughput time. The patient throughput time issue is affected by causative factors, such as waiting time, length of stay, and decision-making. This research aims to develop a new simulation model of patient flow for ED (SIM-PFED) to address the reported key challenge of the patient throughput time. SIM-PFED introduces a new process for patient flow in ED on the basis of the newly proposed operational patient flow by combining discrete event simulation and agent-based simulation and applying a multi-attribute decision-making method, namely, the technique for order preference by similarity to the ideal solution. Experiments were performed on three actual hospital ED datasets to assess the effectiveness of SIM-PFED. Experimental results revealed the superiority of SIM-PFED over other alternative models in reducing patient throughput time in ED by consuming less patient waiting time and having a shorter length of stay. The findings also demonstrated the effectiveness of SIM-PFED in helping ED decision-makers select the best scenarios to be implemented in ED for ensuring minimal throughput time while being cost effective.

A Quantification of the Impact of Awaiting Results of a Urinalysis upon Emergency Department Length of Stay.

Despite the popular conception that ordering a urinalysis causes a significant increase in emergency department (ED) length of stay (LOS), there is little research on its actual impact. This study investigated the quantitative impact of obtaining the results of a urinalysis, compared with the quantitative impact of obtaining the results of any laboratory testing of blood ("blood testing"), upon ED LOS in the National Hospital Ambulatory Medical Care Survey-Emergency Department (NHAMCS-ED) dataset. The NHAMCS-ED dataset was queried from 2006-2015, comparing LOS in visits where urinalysis was ordered, blood testing was ordered, both were ordered, or neither. There were 1,232,279,000 ED visits with LOS data found in the study period. Urinalysis was performed in 24.2% of visits, blood testing in 36.7%, both in 18.2%, and none in 57.4%. Median LOS was 153min. No blood or urine testing had a median LOS of 109, urinalysis only 161min, blood testing only 221min, and both, 250min. Urinalysis does increase LOS, but blood testing increases it more, with additive effects when both are ordered.

Outcomes in Vaso-Occlusive Crisis Treatment in the Emergency Department Vs. Acute Care Observation Center

I NTRODUCTION: Acute painful vaso-occlusive crises (VOC) are the leading cause of emergency department (ED) encounters and hospital admissions for those with sickle cell disease (SCD). For SCD patients, the goal of the sickle cell acute care observation unit (ACOU) at University of Illinois Health (UIH) is to improve patient outcomes by providing immediate care for an uncomplicated VOC. At our urban hospital which cares for more than 500 adult SCD patients, a considerable portion of SCD patients, despite having access to the ACOU, continue to present to the ED for treatment of an uncomplicated VOC. In order to help improve our current system, this study investigated outcomes in SCD patients who receive care for an uncomplicated VOC in the ACOU versus the ED at UIH. METHODS: By querying the electronic medical record, a retrospective study was conducted to analyze outcomes of encounters from the ACOU and ED at UIH between October 2019 and December 2019, specifically including SCD patients ≥18 years old who received morphine for treatment of an uncomplicated VOC. Encounters for complicated VOCs such as acute chest syndrome and stroke were excluded. Endpoints collected include time to first dose of morphine, total milligrams (mg) of IV morphine equivalents given, number of total morphine doses, admission rates, subsequent hospital length of stay, and 30-day inpatient admission rates. Time to the first dose (log transformed) and total dose in mg were analyzed by linear mixed effects models. The number of doses and hospitalization days were analyzed by negative binomial mixed effects model. Admissions and 30-day admissions were analyzed by logistic mixed effects models. These models adjusted for age, gender, and severe Hb genotype (HbSS or HbS beta0-thalassemia) and treated patient identity as random effect. P values were obtained from Wald- test. RESULTS: The ACOU data set contains 394 patient encounters for 79 patients with a median age of 33 years (interquartile range [IQR], 28-40), 71% female, and 73% with severe sickle genotypes. The ED data set contains 391 patient encounters for 128 patients with a median age of 30 years (IQR, 26-41), 53% female, and 74% with severe sickle genotypes. In the ACOU, the median time to first dose of morphine was 49 minutes (IQR, 39-60) compared to 107 minutes (IQR, 71-194) in the ED. The time to first dose was significantly longer in the ED compared to the ACOU (eβ=2.5, p &amp;lt;2×10-16). There was no significant difference in the total number of morphine doses received nor the total mg of morphine received between the two locations. Admission rate from ACOU was 6.6% compared to 53% from ED (OR=0.019, p=2x10-16). Of those admitted, the median number of hospitalization days from the ACOU was 4 days (IQR, 2.3-5.8) and 4 days (IQR, 2.0-6.5) from the ED. There was no significant difference in hospitalization days (p=0.6). The 30-day admission rate was 55% from the ACOU compared to 58% from the ED. 30-day admission rate however had strong intra-patient correlation (i.e., a patient was likely re-admitted multiple times): 44% of patients from the ACOU had admissions within 30 days of their ACOU visit compared to 32% from the ED. Controlling for the intra-patient correlation, ACOU visits had a higher 30-day admission rate than ED visit (OR=2.8, p=0.0015). DISCUSSION: SCD patients treated for an uncomplicated VOC at the sickle ACOU at UIH had a significantly shorter time to initial dose of IV pain medication. The wait time in the ED before first dose of IV pain medication received was more than double than those treated in the ACOU. Patients treated for an uncomplicated VOC in ACOU and ED had similar hospitalization days without a statistically significant difference. The 30-day admission rate to the inpatient setting was comparable for those treated in the ED versus the ACOU. However, given that only 6.6% of patients from the ACOU were admitted during the study period, this suggests that most patients who use both the ED and ACOU tend to be subsequently admitted from the ED. SCD patients may be presenting to the ED for treatment of VOC if capacity in the ACOU is exceeded or are presenting outside of hours of operation (currently 2 shifts Monday through Saturday). Therefore, improving access to our ACOU by increasing capacity and hours of operation may subsequently also lead to a decrease in time to first dose of medication and decrease in the overall 30-day admission rate. Disclosures Gordeuk: Imara: Research Funding; CSL Behring: Consultancy, Research Funding; Global Blood Therapeutics: Consultancy, Research Funding; Novartis: Consultancy; Ironwood: Research Funding.

Healthcare cost associations of patients who use illicit drugs in Florida: a retrospective analysis

BackgroundIllicit drug use increases visits to the hospital. Research is limited on the costs of these healthcare visits by illicit drug.MethodsFlorida’s Agency for Health Care Administration’s emergency department and inpatient datasets from 2016 to 2018 were analyzed. Adults who used an illicit drug were included in the study population resulting in 709,658 observations. Cost-to-charge ratios were used to estimate healthcare costs. Linear regression analyzed associations of illicit drugs with total healthcare cost.ResultsTotal healthcare costs are estimated at $6.4 billion over the 3 year period. Medicare paid for the most patient care ($2.16 billion) with Medicaid and commercial insurance each estimated at $1.36 billion. Cocaine (9.25%) and multiple drug use (6.12%) increased the costs of an ED visit compared to a patient with cannabis SUD. Opioids (23.40%) and inhalants use (16.30%) increased the costs of inpatient compared to cannabis SUD.ConclusionHealthcare costs are high of patients with illicit drug SUD and poisoning, over half of which are paid for with tax payer dollars and to an unknown degree hospital write-offs. Injuries and illness of patients using cocaine and multiple drugs are associated with more expensive ED patient care and opioids and inhalants are associated with more expensive inpatient care.

Applying FAIR Principles to Improve Data Searchability of Emergency Department Datasets: A Case Study for HCUP-SEDD.

There is a recognized need to improve how scholarly data are managed and accessed. The scientific community has proposed the findable, accessible, interoperable, and reusable (FAIR) data principles to address this issue. The objective of this case study was to develop a system for improving the FAIRness of Healthcare Cost and Utilization Project's State Emergency Department Databases (HCUP's SEDD) within the context of data catalog availability. A search tool, EDCat (Emergency Department Catalog), was designed to improve the "FAIRness" of electronic health databases and tested on datasets from HCUP-SEDD. ElasticSearch was used as a database for EDCat's search engine. Datasets were curated and defined. Searchable data dictionary-related elements and unified medical language system (UMLS) concepts were included in the curated metadata. Functionality to standardize search terms using UMLS concepts was added to the user interface. The EDCat system improved the overall FAIRness of HCUP-SEDD by improving the findability of individual datasets and increasing the efficacy of searches for specific data elements and data types. The databases considered for this case study were limited in number as few data distributors make the data dictionaries of datasets available. The publication of data dictionaries should be encouraged through the FAIR principles, and further efforts should be made to improve the specificity and measurability of the FAIR principles. In this case study, the distribution of datasets from HCUP-SEDD was made more FAIR through the development of a search tool, EDCat. EDCat will be evaluated and developed further to include datasets from other sources.

Homelessness and health needs in Wales

Background Public Health Wales developed its long-term strategy with the purpose of ‘Working to Achieve a Healthier Future for Wales’. This study is motivated by one of the strategic priorities, ‘Influencing the wider determinants of health’ with an emphasis on homelessness prevention.&#x0D; Main AimTo understand health needs of homeless health service users from routinely collected health data in Wales. To quantify the corresponding differences from general population.&#x0D; MethodsScoping work has completed collaborating with academic researchers, third sectors, clinical professionals, Office for National Statistics, and housing stats of Welsh Government. To construct study cohort, we will perform linkage exercise among Annual District Death Extract, Emergency Department Data Set, Outpatient Dataset for Wales, Patient Episode Database for Wales, Substance Misuse Data Set and Welsh Longitudinal General Practice dataset (from 2007 to 2018) stored in Secure Anonymised Information Linkage (SAIL) Databank. Study cohort includes all patients with an indication (i.e. clinical codes) of homelessness in their registration information and/or health records. We propose to adapt propensity score matching to construct matched case and control groups. This method will assign each homeless individual to individual without homeless flag with same or similar propensity score. We will then proceed to test for the significance of the homelessness and each health and wellbeing indicators (i.e. physical health, mental wellbeing and substance misuse) in the presence of confounders, and estimate the effects of homelessness on these indicators.&#x0D; ResultsThis study will demonstrate how linked data provide a more comprehensive review of the health needs of a vulnerable population, the homeless groups in Wales, and be able to explore changes over time.&#x0D; ConclusionThe relationship between homelessness and health issues is bi-directional. Findings from this study will have implications for health, housing, social, and homelessness policy at both local and national level; as well as contributing to the ability to providing tailored health services to targeted homeless populations groups.

The Influence of Non-Clinical Patient Factors on Clinical Decision Making: Uncovering the Impact on Mental Health

BackgroundUnderstanding how non-clinical patient factors (NCpF) such as gender, educational level and socioeconomic status impact clinical decisions regarding one’s mental health is important for appropriate and equitable care.&#x0D; Main AimThis research aims to i) investigate the feasibility of using administrative health data to investigate clinical decision making in mental health; ii) understand the impact of NCpF on mental health-related diagnosis, treatment, and referral decisions.&#x0D; Methods/ApproachThree waves of the Welsh Health Survey, containing a five-item Mental Health Inventory (Short- Form SF36), and NCpF information were used to create our interest cohort.&#x0D; The records with a low SF36, a ‘gold standard’ identifier of common mental health conditions, were then linked to the healthcare records datasets (Primary Care GP Dataset, Patient Episode Database for Wales, Emergency Department Dataset, Outpatient Referral Dataset, Annual District Death Extract) securely stored on the Secure Anonymised Information Linkage Databank.&#x0D; ResultsWe will present the methodological challenges and benefits of using administrative data the study of decision making in mental health.&#x0D; The differences in NCpF between those with a low SF36 and a mental health diagnosis, symptoms and treatment as well as those with a similar SF36 score but no diagnosis, symptoms or treatment recorded will be presented and discussed.&#x0D; ConclusionAdministrative data can provide a unique opportunity to investigate issues related with clinical decision-making in mental health and improve health equity. Having a better understanding of the influence of NCpF on mental health decisions is necessary to prevent inequity in mental health care.

Fragmentation of Care for Young Adults with Sickle Cell Disease in California

Background: Sickle Cell Disease (SCD) predominantly affects people of African ancestry, causing significant morbidity and mortality. In high-income countries children, who are more likely to receive comprehensive care than adults, have better health care outcomes. Young adults (YA) are in a period of transition from pediatric to adult models of care and the effect of receiving care at multiple medical facilities (fragmentation) during this time on outcomes has not been well-described. In this study we sought to examine fragmentation of care for YA SCD patients and the association of fragmentation on mortality. Methods: Using a previously published definition, longitudinal records from the California Patient Discharge, Emergency Department, and Ambulatory Surgery datasets were used to identify SCD patients from 1991-2016. SCD patients were placed into three different age cohorts: children (10-17), YA (18-25) and adults (26-33). Each patient required the full 7 year follow up time in each age category; patients could be in multiple age cohorts. Patients with no inpatient admissions were excluded. The number of inpatient admissions during each age group period was used as a measure of disease severity (&lt;10, 10-19, 20-29, ≥30). SCD specialty care centers (SCD SC) were determined using all SCD inpatient admissions; facilities in the top 5% based on number of unique SCD patients seen were considered SCD SC. Patients were classified as always, sometimes and never seen at SCD SC facilities in each age group. We classified care fragmentation by the number of facilities an individual received inpatient care (1, 2, 3-4 or ≥5 unique facilities) during their time in each age group. Descriptive statistics were used to describe patients' characteristics by age group. Multivariable Poisson regression was used to identify risk factors associated with fragmented care. Multivariable Cox regression was used to determine the impact of fragmented care, disease severity and care at SCD SC on all-cause mortality, conditional on surviving to 26 years of age for the YA group. Results We identified a cohort of 6,977 unique SCD patients: 1,019 children, 1,122 YAs and 1,015 adults. The YA cohort consisted of predominately African Americans (91.3%) with 43.9% male and 56.1% female. Forty-two % YAs had Medi-Cal followed by 26.7% with private insurance as first reported health insurance. Forty-four % (494) had &lt;10, 20.1% (226) had 10-19, 11.1% (125) had 20-29 and 24.7% (277) had ≥30 inpatient admissions while in the YA age period. Twenty-two % (248) YAs were seen at 1, 25.8% (290) were seen at 2, 30.2% (339) were seen at 3-4, and 21.8% (245) were seen at &gt; 5 inpatient facilities. YAs and older adults were seen at a similar number of facilities while children were seen at less (Figure 1). In multivariable regression models among YAs, those with private insurance (vs. Medi-Cal) were at lower risk of fragmentation (Incident Rate Ratio (IRR)=0.85, CI 0.78-0.93, p=0.0002), while those without insurance were at a higher risk (IRR 1.45, CI 1.22-1.72, p&lt;0.0001). Patients with more admissions (vs. &lt;10) were at higher risk of fragmentation (IRR for 10-19 =1.42, CI 1.29-1.57; IRR for 20-29 1.49, CI 1.33-1.67, IRR for &gt;30 admissions 2.13, CI 1.98-2.43 p&lt;0.0001). Patients who were sometimes admitted to an SCD SC (IRR=2.19, CI 1.98-2.43, p&lt;0.0001) or never (IRR=1.15, CI 1.15-1.46, p&lt;0.0001) were at increased risk of fragmented care compared to those who were always admitted to an SCD SC. In the multivariable mortality model, YAs with increasing number of admissions, regardless of location, were at increased risk of death (10-19 HR 2.36, CI 1.13-4.91 p=0.022; 20-29 HR 4.25, CI 2.03-8.92, p=0.0001; &gt; 30 admissions HR 7.79, CI 4.09-14.83, p&lt;0.0001). Fragmentation of care and always or sometimes being admitted to an SCD SC were not associated with mortality. Conclusion Most young adult SCD patients (78%) received inpatient care at &gt;1 facility. Of all age groups, children were most likely to be seen at only 1 facility, suggesting that fragmentation of care begins in early adulthood. Young adults without insurance, patients with more frequent admissions and those who did not always receive care at an SCD SC were at higher risk for fragmented care. Young adults with more frequent admissions were also at an increased risk of mortality. The effect of specialty centers and more consistent location of care on health-related outcomes for patients with SCD requires further study. Disclosures Wun: Janssen: Other: Steering committee; Pfizer: Other: Steering committee.

Patient, hospital and regional characteristics associated with undertriage of injured children in California (2005–2015): a retrospective cohort study

Background/objectiveTrauma centers save lives, but they are scarce and concentrated in urban settings. The population of severely injured children in California who do not receive trauma center care (undertriage) is...

Violent crime and socioeconomic deprivation in shaping asthma-related pollution susceptibility: a case-crossover design

BackgroundThe objective of this study was to quantify and compare the relative influence of community violent crime and socioeconomic deprivation in modifying associations between ozone and emergency department (ED) visits...

Can Statewide Emergency Department, Hospital Discharge, and Violent Death Reporting System Data Be Used to Monitor Burden of Firearm-Related Injury and Death in Rhode Island?

National data on the epidemiology of firearm injuries and circumstances of firearm deaths are difficult to obtain and often are nonreliable. Since firearm injury and death rates and causes can vary substantially between states, it is critical to consider state-specific data sources. In this study, we illustrate how states can systematically examine demographic characteristics, firearm information, type of wound, toxicology tests, precipitating circumstances, and costs to provide a comprehensive picture of firearm injuries and deaths using data sets from a single state with relatively low rates of firearm injury and death. Cross-sectional study. Firearm-related injury data for the period 2005-2014 were obtained from the Rhode Island emergency department and hospital discharge data sets; death data for the same period were obtained from the Rhode Island Violent Death Reporting System. Descriptive statistics were used. Healthcare Cost and Utilization Project cost-to-charge ratios were used to convert total hospital charges to costs. Most firearm-related emergency department visits (55.8%) and hospital discharges (79.2%) in Rhode Island were from assaults; however, most firearm-related deaths were suicides (60.1%). The annual cost of firearm-related hospitalizations was more than $830 000. Most decedents who died because of firearms tested positive for illicit substances. Nearly a quarter (23.5%) of firearm-related homicides were due to a conflict between the decedent and suspect. More than half (59%) of firearm suicide decedents were reported to have had current mental or physical problems prior to death. Understanding the state-specific magnitude and patterns (who, where, factors, etc) of firearm injury and death may help inform local injury prevention efforts. States with similar data sets may want to adopt our analyses. Surveillance of firearm-related injury and death is essential. Dissemination of surveillance findings to key stakeholders is critical in improving firearm injury prevention. States that are not part of the National Violent Death Reporting System (NVDRS) could work with their other data sources to obtain a better picture of violent injuries and deaths to make the best use of resources.

Wildfire smoke and risk of out-of-hospital cardiac arrests using a spatially derived exposure metric for 2015-2017 California wildfires

Wildfire smoke and risk of out-of-hospital cardiac arrests using a spatially derived exposure metric for 2015-2017 California wildfires

Incidence of Bleeding in Patients with Sickle Cell Disease: A Population Based Study

Background:Bleeding in patients with sickle cell disease (SCD) occurs at a number of sites, often with significant morbidity and mortality. The increased risk of hemorrhagic stroke, hematuria, and vitreous hemorrhage in SCD patients is well known. However, the overall cumulative incidence of both major and clinically relevant, non-major bleeding events in SCD patients has not been well-described. Therefore, we determined the cumulative incidence of and risk factors for bleeding amongst patients with SCD. We also determined the association between bleeding and overall mortality.Methods:We utilized the California Patient Discharge Dataset (PDD) and Emergency Department (ED) Dataset to identify patients with SCD between 1991-2014. We then used specific ICD-9 CM codes to identify the first admission (PDD or ED) for bleeding events: intracranial hemorrhage (ICH), gastrointestinal (GI) bleeding, hemophthalmos, gross hematuria, and “other” bleeding (including hemopericardium, pulmonary bleed, and hemarthrosis). The cumulative incidence of bleeding was adjusted for the competing risk of death using age as the time scale and stratified by disease severity (severe disease was defined as requiring an average of ≥ 3 hospitalizations or ED visits per year). Cox proportional hazards regression models were used to determine factors associated with bleeding (all, ICH and GI) and the association of bleeding with mortality. Models included age, race, SCD related complications (ischemic stroke, venous thromboembolism [VTE], osteonecrosis of the femoral head [ONFH], renal failure, and liver failure) and disease severity. Complications and bleeding were included as time-dependent covariates.Results:Of the 6,423 SCD patients identified, 15.9% had an index bleeding event. Of these, 65.6% were GI bleeding, 14.2% were ICH, 7.1% were hemophthalmos, 4.3% were gross hematuria, and 8.8% were other types of bleeding. The top six diagnoses of GI bleeding were GI hemorrhage not otherwise specified, melena, hematemesis, rectal and anal hemorrhage, chronic gastric ulcer with hemorrhage, and Mallory-Weiss syndrome. Figure 1 shows the cumulative incidence of bleeding overall and by bleeding type. The incidence of all bleeding was 15.5% (95% confidence interval (CI) 14.4 - 16.6) at age 40 years and 33.6% (CI 31.5 - 35.8%) at age 60. The incidence of bleeding was higher among SCD patients with severe disease. For example, the cumulative incidence of GI bleeding at age 40 was 15.8% (CI 14.2-17.4%) among severe SCD patients compared to 4.8% (CI 3.9-5.8%) for those with less severe disease. In multivariable models, a higher risk of all bleeding was associated with severe SCD, VTE within 180 days prior to bleeding event, ONFH, ischemic stroke, renal failure and liver failure (Table 1). In multivariable models by bleeding type, there was a strong association between VTE and ischemic stroke with risk of ICH. In addition, ONFH was positively associated with risk of GI bleed. Bleeding was associated with a two-fold increased risk of death (hazard ratio =2.28; CI 1.97-2.64), adjusted for other SCD related complications. Bleeding had a similar negative effect on mortality as other complications.Conclusion:The findings from our study indicate that SCD patients have a high cumulative incidence of bleeding. While the increased incidence of intracranial, urological, and retinal bleeding has been previously described and are confirmed here, we present the novel finding that SCD patients also have a high incidence of GI bleeding, the majority of which are from an upper GI source. The association of hemorrhagic stroke with a history of ischemic stroke is also confirmed. The association of bleeding with VTE is likely due, at least in part, to anticoagulation. Further studies on the causes and risk factors for GI bleeding in patients with SCD are warranted, and possibilities include gastritis from increased use of non-steroidal anti-inflammatory drugs (hence the association of ONFH with GI bleeding) and stress ulcerations from frequent hospitalizations. Such data could inform preventive strategies. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

A Regional Collaboration of Health (ARCH): Using health survey and linked routine data to understand wellbeing

IntroductionMonitoring social wellbeing and its relationship to health service utilisation by means of appropriate measurement tools can potentially provide a complementary view for influencing service development. Aspects of wellbeing have been collected in the Welsh Health Survey (WHS) while routine health data captures health service utilisation.&#x0D; Objectives and ApproachWHS was used to link self-reported wellbeing to health outcomes, prior to linking to routinely collected data. Initially, a measure for personal wellbeing was developed using the four personal wellbeing questions defined by The Office of National Statistics (ONS), included in national surveys from 2011 onward. We conducted regression analysis to identify potential predictors of personal wellbeing scores our model included self-reported lifestyle behaviour, self-reported health, education, work, household and general demographics. Links to primary care, hospital and emergency department datasets are being developed to provide insight into the relationship between wellbeing, multi-morbidity and health service utilisation.&#x0D; ResultsFour wellbeing questions had similar scoring patterns across age groups which is different to most health indicators that tend to show a marked health decline with increasing age. There is a difference between mean wellbeing score for males and females. Our finding showed that self-reported of ‘excellent’ or ‘very good’ general health has the largest positive effect on wellbeing while positive viewpoint on self-health has the second largest effect on our model. In addition, being retired from a paid job, eating at least one or 5+ portion of fruit and vegetables and giving up smoking have positive impact on population wellbeing. In contrast, not being able to work, intermediate household occupancy, consuming alcohol in last 12-months, having long-standing illness, showed a negative impact on wellbeing.&#x0D; Conclusion/ImplicationsThis project established robust methodology on utilizing survey and routine health data for monitoring and evaluation purposes. We also evaluated the linkability of survey data The latest release of National Survey for Wales (NSW) will cover a combination of self-reported health measures and aims for a higher linkage consent rate.

Harmonising data from different sources to conduct research using linked survey and routine datasets

IntroductionHarmonization of different data sources from various electronic health records across systems enhances the potential scope and granularity of data available to health data research, providing more opportunities for research by improving the generalizability and effective sample size of a range of outcome metrics.&#x0D; Objectives and ApproachThis study describes data harmonisation for a UK longitudinal birth cohort, the Millennium Cohort Study (MCS) which was linked to routine inpatient and emergency department, and, where available, general practice and child health records for 1838 Welsh and 1431 Scottish consenting MCS participants. Datasets requiring harmonisation were: from Wales, Patient Episode Dataset for Wales (PEDW) and Emergency Department Data Set (EDDS) data and from Scotland, Scottish Medical Record 01 (SMR01) and Accident and Emergency dataset (A&amp;E2). Heterogeneous variables were created by transforming variable names, concepts, codes to improve scope for analysis.&#x0D; ResultsA harmonized dataset of 2166 participants and 5747 hospital admissions were derived of cohort members who had at least 1 hospital inpatient or A&amp;E event before their 14th birthday. Harmonisation included: dealing with date granularity by generating random dates of birth; standardising periods of data collection; identifying inconsistencies and then mapping and bridging differences in definitions of periods of care and levels of diagnostic and operational coding across countries and datasets.&#x0D; Conclusion/ImplicationsHeterogeneous variables from different data sources were pooled and converted into standardised data for research, extending existing harmonisation work, including curation of a population based anonymously linkable longitudinal cohort. [AA1] These methods are reproducible and can be utilised by other researchers and projects applying to use these routine data sources.

A Regional Collaboration of Health (ARCH): Using health survey and linked routine data to understand wellbeing.

BackgroundMonitoring social wellbeing and its relationship to health service utilisation by means of appropriate measurement tools can provide a complementary view towards service development. Welsh Health Survey (WHS) collects aspects of wellbeing while routine health data captures details around health service utilisation.&#x0D; ObjectiveThe aim of this project was to evaluate the linkage ability of routine health data with survey data and establish a methodology for utilizing survey data as a measure for self-reported health outcomes.&#x0D; MethodWe used WHS data from UK data archive to link self-reported wellbeing to health outcomes, a measure for personal wellbeing was developed using the personal wellbeing questions defined by Office of National Statistics (ONS), included in national surveys from 2011 onward. WHS was then linked to routine health data using SAIL Databank. We conducted regression analysis to identify potential predictors of personal wellbeing by linking primary care, hospital and emergency department datasets, to develop and provide insight into the relationship between wellbeing, multi-morbidity and health service utilisation.&#x0D; FindingsWellbeing questions had similar scoring patterns across age groups which is different to most health indicators that tend to show a marked health decline with increasing age. Our findings showed that self-reported of ‘excellent’ or ‘very good’general health has the largest positive effect on wellbeing while positive viewpoint on self-health has the second largest effect.&#x0D; ConclusionsCombining and harmonising data from multiple sources and linking them to information from a longitudinal cohort create useful resources for population health research. These methods are reproducible and can be utilised by other researchersand projects.

Integrating electronic health records from different sources across the UK: lessons from a record linkage study

BackgroundHarmonisation of different data sources from various electronic health records (EHRs) across systems enhances the potential scope and granularity of data available to health data research.&#x0D; ObjectiveTo describe data harmonisation of routine electronic healthcare records in Wales and Scotland linked to a UK longitudinal birth cohort, the Millennium Cohort Study (MCS).&#x0D; MethodsComparable secondary care data was linked, with parental consent, to MCS information for 1838 and 1431 children participating in MCS and residing in Wales and Scotland, by assigning, respectively, unique Anonymised Linkage Fields to personbased records in the privacy protecting Secure Anonymised Information Linkage (SAIL) databank at Swansea University, and by the National Health Service (NHS) Information Standards Division. Survey and non-response weights were created to account for the clustered sample, sample attrition and consent to linkage. Heterogeneous variables from the Patient Episode Dataset for Wales, Emergency Department Data Set for Wales, Scottish Medical Record 01 and Accident and Emergency dataset for Scotland were harmonised enabling data to be pooled and standardised for research.&#x0D; FindingsOverall linkage to harmonised health care data was achieved for 98.9% (99.9% for Wales and 97.6% for Scotland) of consented MCS participants. 66% of children experienced at least one hospital admission (total 5747 hospital admissions) up totheir 14th birthday, while 60% attended A&amp;E departments at least once (total 5221 attendances) between their 9th and 14th birthday. We managed date granularity by generating random dates of birth, standardising periods of data collection,identifying inconsistencies and then mapping and bridging differences in definitions of periods of care across countries and datasets.&#x0D; ConclusionsCombining and harmonising data from multiple sources and linking them to information from a longitudinal cohort create useful resources for population health research. These methods are reproducible and can be utilised by other researchersand projects.