Susan Malveau

Evaluating the Use of Existing Data Sources, Probabilistic Linkage, and Multiple Imputation to Build Population-based Injury Databases Across Phases of Trauma Care

OBJECTIVES The objective was to evaluate the process of using existing data sources, probabilistic linkage, and multiple imputation to create large population-based injury databases matched to outcomes. METHODS This was a retrospective cohort study of injured children and adults transported by 94 emergency medical systems (EMS) agencies to 122 hospitals in seven regions of the western United States over a 36-month period (2006 to 2008). All injured patients evaluated by EMS personnel within specific geographic catchment areas were included, regardless of field disposition or outcome. The authors performed probabilistic linkage of EMS records to four hospital and postdischarge data sources (emergency department [ED] data, patient discharge data, trauma registries, and vital statistics files) and then handled missing values using multiple imputation. The authors compare and evaluate matched records, match rates (proportion of matches among eligible patients), and injury outcomes within and across sites. RESULTS There were 381,719 injured patients evaluated by EMS personnel in the seven regions. Among transported patients, match rates ranged from 14.9% to 87.5% and were directly affected by the availability of hospital data sources and proportion of missing values for key linkage variables. For vital statistics records (1-year mortality), estimated match rates ranged from 88.0% to 98.7%. Use of multiple imputation (compared to complete case analysis) reduced bias for injury outcomes, although sample size, percentage missing, type of variable, and combined-site versus single-site imputation models all affected the resulting estimates and variance. CONCLUSIONS This project demonstrates the feasibility and describes the process of constructing population-based injury databases across multiple phases of care using existing data sources and commonly available analytic methods. Attention to key linkage variables and decisions for handling missing values can be used to increase match rates between data sources, minimize bias, and preserve sampling design.

Emergency Department Visits for Nontraumatic Dental Problems: A Mixed-Methods Study

OBJECTIVES We documented emergency department (ED) visits for nontraumatic dental problems and identified strategies to reduce ED dental visits. METHODS We used mixed methods to analyze claims in 2010 from a purposive sample of 25 Oregon hospitals and Oregons All Payer All Claims data set and interviewed 51 ED dental visitors and stakeholders from 6 communities. RESULTS Dental visits accounted for 2.5% of ED visits and represented the second-most-common discharge diagnosis in adults aged 20 to 39 years, were associated with being uninsured (odds ratio [OR] = 5.2 [reference: commercial insurance]; 95% confidence interval [CI] = 4.8, 5.5) or having Medicaid insurance (OR = 4.0; 95% CI = 3.7, 4.2), resulted in opioid (56%) and antibiotic (56%) prescriptions, and generated

Developing a Statewide Emergency Medical Services Database Linked to Hospital Outcomes: A Feasibility Study

402 (95% CI = 

Automatic prediction of trauma registry procedure codes from emergency room dictations.

396,

Minimizing Attrition for Multisite Emergency Care Research

408) in hospital costs per visit. Interviews revealed health system, community, provider, and patient contributors to ED dental visits. Potential solutions provided by interviewees included Medicaid benefit expansion, care coordination, water fluoridation, and patient education. CONCLUSIONS Emergency department dental visits are a significant and costly public health problem for vulnerable individuals. Future efforts should focus on implementing multilevel interventions to reduce ED dental visits.

Reliability of clinical assessments in older adults with syncope or near syncope

Abstract Background. Statewide emergency medical services (EMS) data linked to outcomes are critical for promoting high-quality emergency care; however, many states do not have such a resource. Objective. To demonstrate the feasibility of creating such a statewide database using a one-month pilot sample. Methods. This was a prospective cohort study of all EMS patient encounters throughout Oregon during May 2008. Eighty-three National EMS Information System (NEMSIS) variables were obtained from EMS agencies via electronic or paper charts. We reformatted raw data, mapped NEMSIS fields, entered hard-copy records, and uploaded data files to a statewide electronic medical records platform. Records from transport and nontransport (first-responder) agencies caring for the same patients were matched using probabilistic linkage, then linked to three statewide outcome databases (Oregon Hospital Discharge Database [OHDD], Oregon Trauma Registry [OTR], and Oregon Department of Transportation [ODOT] Crash File) using similar methodology. We estimated population-adjusted case ascertainment by county and used descriptive statistics to characterize the process. Results. During the one-month period, we collected 27,474 EMS records in 36 (100%) counties from 106 (77%) licensed transport agencies and 10 nontransport agencies, representing 20,673 persons. There were 3,302 admission record matches, 285 trauma registry matches, and 392 crash record matches. Overall, 3,979 hospital outcomes were matched to EMS records for 80 (75%) transport and six (60%) first-responder agencies. Median per-agency match rates were 16.3% for OHDD (interquartile range [IQR] 8.3–22.2%, range 0–56.5%), 0.9% for OTR (IQR 0–2.5%, range 0–60.0%), and 1.6% for ODOT (IQR 0–3.5%, range 0–23.1%). Conclusion. Developing a statewide EMS database linked to hospital outcomes is feasible. The processes used in this study and match rate estimates may provide a template for other states to follow, enhancing opportunities for outcomes-based EMS research and EMS quality assurance efforts.

ECG Predictors of Cardiac Arrhythmias in Older Adults With Syncope

Current natural language processing techniques for recognition of concepts in the electronic medical record have been insufficient to allow their broad use for coding information automatically. We have undertaken a preliminary investigation into the use of machine learning methods to recognize procedure codes from emergency room dictations for a trauma registry. Our preliminary results indicate moderate success, and we believe future enhancements with additional learning techniques and selected natural language processing approaches will be fruitful.

Outcomes of Patients with Syncope and Suspected Dementia.

Loss to follow-up of enrolled patients (a.k.a. attrition) is a major threat to study validity and power. Minimizing attrition can be challenging even under ideal research conditions, including the presence of adequate funding, experienced study personnel, and a refined research infrastructure. Emergency care research is shifting toward enrollment through multisite networks, but there have been limited descriptions of approaches to minimize attrition for these multicenter emergency care studies. This concept paper describes a stepwise approach to minimize attrition, using a case example of a multisite emergency department prospective cohort of over 3,000 patients that has achieved a 30-day direct phone follow-up attrition rate of <3%. The seven areas of approach to minimize attrition in this study focused on patient selection, baseline contact data collection, patient incentives, patient tracking, central phone banks, local enrollment site assistance, and continuous performance monitoring. Appropriate study design, including consideration of these methods to reduce attrition, will be time well spent and may improve study validity.

Out-of-Hospital Research in the Era of Electronic Health Records

OBJECTIVES Clinical prediction models for risk stratification of older adults with syncope or near syncope may improve resource utilization and management. Predictors considered for inclusion into such models must be reliable. Our primary objective was to evaluate the inter-rater agreement of historical, physical examination, and electrocardiogram (ECG) findings in older adults undergoing emergency department (ED) evaluation for syncope or near syncope. Our secondary objective was to assess the level of agreement between clinicians on the patients overall risk for death or serious cardiac outcomes. METHODS We conducted a cross-sectional study at 11 EDs in adults 60 years of age or older who presented with unexplained syncope or near syncope. We excluded patients with a presumptive cause of syncope (e.g., seizure) or if they were unable or unwilling to follow-up. Evaluations of the patients past medical history and current medication use were completed by treating provider and trained research associate pairs. Evaluations of the patients physical examination and ECG interpretation were completed by attending/resident, attending/advanced practice provider, or attending/attending pairs. All evaluations were blinded to the responses from the other rater. We calculated the percent agreement and kappa statistic for binary variables. Inter-rater agreement was considered acceptable if the kappa statistic was 0.6 or higher. RESULTS We obtained paired observations from 255 patients; mean (±SD) age was 73 (±9) years, 137 (54%) were male, and 204 (80%) were admitted to the hospital. Acceptable agreement was achieved in 18 of the 21 (86%) past medical history and current medication findings, none of the 10 physical examination variables, and three of the 13 (23%) ECG interpretation variables. There was moderate agreement (Spearman correlation coefficient, r = 0.40) between clinicians on the patients probability of 30-day death or serious cardiac outcome, although as the probability increased, there was less agreement. CONCLUSIONS Acceptable agreement between raters was more commonly achieved with historical rather than physical examination or ECG interpretation variables. Clinicians had moderate agreement in assessing the patients overall risk for a serious outcome at 30 days. Future development of clinical prediction models in older adults with syncope should account for variability of assessments between raters and consider the use of objective clinical variables.

Stroke Prophylaxis After a New Emergency Department Diagnosis of Atrial Fibrillation

Study objective: Cardiac arrhythmia is a life‐threatening condition in older adults who present to the emergency department (ED) with syncope. Previous work suggests the initial ED ECG can predict arrhythmia risk; however, specific ECG predictors have been variably specified. Our objective is to identify specific ECG abnormalities predictive of 30‐day serious cardiac arrhythmias in older adults presenting to the ED with syncope. Methods: We conducted a prospective, observational study at 11 EDs in adults aged 60 years or older who presented with syncope or near syncope. We excluded patients with a serious cardiac arrhythmia diagnosed during the ED evaluation from the primary analysis. The outcome was occurrence of 30‐day serous cardiac arrhythmia. The exposure variables were predefined ECG abnormalities. Independent predictors were identified through multivariate logistic regression. The sensitivities and specificities of any predefined ECG abnormality and any ECG abnormality identified on adjusted analysis to predict 30‐day serious cardiac arrhythmia were also calculated. Results: After exclusion of 197 patients (5.5%; 95% confidence interval [CI] 4.7% to 6.2%) with serious cardiac arrhythmias in the ED, the study cohort included 3,416 patients. Of these, 104 patients (3.0%; 95% CI 2.5% to 3.7%) had a serious cardiac arrhythmia within 30 days from the index ED visit (median time to diagnosis 2 days [interquartile range 1 to 5 days]). The presence of nonsinus rhythm, multiple premature ventricular conductions, short PR interval, first‐degree atrioventricular block, complete left bundle branch block, and Q wave/T wave/ST‐segment abnormalities consistent with acute or chronic ischemia on the initial ED ECG increased the risk for a 30‐day serious cardiac arrhythmia. This combination of ECG abnormalities had a similar sensitivity in predicting 30‐day serious cardiac arrhythmia compared with any ECG abnormality (76.9% [95% CI 67.6% to 84.6%] versus 77.9% [95% CI 68.7% to 85.4%]) and was more specific (55.1% [95% CI 53.4% to 56.8%] versus 46.6% [95% CI 44.9% to 48.3%]). Conclusion: In older ED adults with syncope, approximately 3% receive a diagnosis of a serious cardiac arrhythmia not recognized on initial ED evaluation. The presence of specific abnormalities on the initial ED ECG increased the risk for 30‐day serious cardiac arrhythmias.