Jason S. Shapiro

Using Health Information Exchange to Improve Public Health

Public health relies on data reported by health care partners, and information technology makes such reporting easier than ever. However, data are often structured according to a variety of different terminologies and formats, making data interfaces complex and costly. As one strategy to address these challenges, health information organizations (HIOs) have been established to allow secure, integrated sharing of clinical information among numerous stakeholders, including clinical partners and public health, through health information exchange (HIE). We give detailed descriptions of 11 typical cases in which HIOs can be used for public health purposes. We believe that HIOs, and HIE in general, can improve the efficiency and quality of public health reporting, facilitate public health investigation, improve emergency response, and enable public health to communicate information to the clinical community.

Matching identifiers in electronic health records: implications for duplicate records and patient safety

Objective To quantify the percentage of records with matching identifiers as an indicator for duplicate or potentially duplicate patient records in electronic health records in five different healthcare organisations, describe the patient safety issues that may arise, and present solutions for managing duplicate records or records with matching identifiers. Methods For each institution, we retrieved deidentified counts of records with an exact match of patient first and last names and dates of birth and determined the number of patient records existing for the top 250 most frequently occurring first and last name pairs. We also identified methods for managing duplicate records or records with matching identifiers, reporting the adoption rate of each across institutions. Results The occurrence of matching first and last name in two or more individuals ranged from 16.49% to 40.66% of records; inclusion of date of birth reduced the rates to range from 0.16% to 15.47%. The number of records existing for the most frequently occurring name at each site ranged from 41 to 2552. Institutions varied widely in the methods they implemented for preventing, detecting and removing duplicate records, and mitigating resulting errors. Conclusions The percentage of records having matching patient identifiers is high in several organisations, indicating that the rate of duplicate records or records may also be high. Further efforts are necessary to improve management of duplicate records or records with matching identifiers and minimise the risk for patient harm.

Clinical Information System and Process Redesign Improves Emergency Department Efficiency

BACKGROUND Fueled by a decade-long increase in emergency department (ED) visits with a concomitant decrease in hospital bed capacity and the number of hospital EDs, ED crowding has reached crisis proportions. Robust information systems and process redesign are two strategies to improve the safety and quality of emergency care. At the ED at the Mount Sinai Medical Center, an urban, tertiary care academic medical center in New York City, elements of departmental work flow were redesigned to streamline patient throughput before implementation of a fully integrated emergency department information system (EDIS) with patient tracking, computerized charting and order entry, and direct access to patient historical data from the hospital data repository. Pre- and postintervention data were analyzed to examine the impact on (ED) efficiency. RESULTS The length of stay for all patients (arrival to time patient left ED) decreased by 1.94 hours, from 6.69 (n = 508) pre-intervention to 4.75 (n = 691) postintervention (p < .001); doctor-to-disposition time (first doctor-patient contact to disposition decision) decreased by 1.90 hours, from 3.64 (n = 508) to 1.74 (n = 691; p < .001); door-to-doctor time (triage to first doctor-patient contact) decreased by 0.54 hours, from 1.22 (n = 508) to 0.68 (n = 691; p < .001). X-ray turnaround time (TAT) decreased by 0.18 hours from 0.92 (n = 60) to 0.74 (n = 108; p = .179); computerized tomography (CT) scan TAT decreased by 1.56 hours, from 3.89 (n = 40) to 2.33 (n = 29; p < .001), lab TAT decreased by 0.59 hours, from 2.03 (n = 121) to 1.44 (n = 271; p = .006). CONCLUSIONS Increasing the clinical information available at the bedside and improving departmental work flow through EDIS implementation and process redesign led to decreased patient throughput times and improved ED efficiency.

Iterative Evaluation of the Health Level 7—Logical Observation Identifiers Names and Codes Clinical Document Ontology for Representing Clinical Document Names: A Case Report

The authors summarize their experience in iteratively testing the adequacy of three versions of the Health Level Seven (HL7) Logical Observation Identifiers Names and Codes (LOINC) Clinical Document Ontology (CDO) to represent document names at Columbia University Medical Center. The percentage of documents fully represented increased from 23.4% (Version 1) to 98.5% (Version 3). The proportion of unique representations increased from 7.9% (Analysis 1) to 39.4% (Analysis 4); the proportion reflects the level of specificity in the document names as well as the completeness and level of granularity of the CDO. The authors shared the findings of each analysis with the Clinical LOINC committee and participated in the decision-making regarding changes to the CDO on the basis of those analyses and those conducted by the Department of Veterans Affairs. The authors encourage other institutions to actively engage in testing healthcare standards and participating in standards development activities to increase the likelihood that the evolving standards will meet institutional needs.

People with epilepsy who use multiple hospitals; prevalence and associated factors assessed via a health information exchange.

Hospital crossover occurs when people seek care at multiple hospitals, creating information gaps for physicians at the time of care. Health information exchange (HIE) is technology that fills these gaps, by allowing otherwise unaffiliated physicians to share electronic medical information. However, the potential value of HIE is understudied, particularly for chronic neurologic conditions like epilepsy. We describe the prevalence and associated factors of hospital crossover among people with epilepsy, in order to understand the epidemiology of who may benefit from HIE.

Delphi Consensus on the Feasibility of Translating the ACEP Clinical Policies Into Computerized Clinical Decision Support

Clinical practice guidelines are developed to reduce variations in clinical practice, with the goal of improving health care quality and cost. However, evidence-based practice guidelines face barriers to dissemination, implementation, usability, integration into practice, and use. The American College of Emergency Physicians (ACEP) clinical policies have been shown to be safe and effective and are even cited by other specialties. In spite of the benefits of the ACEP clinical policies, implementation of these clinical practice guidelines into physician practice continues to be a challenge. Translation of the ACEP clinical policies into real-time computerized clinical decision support systems could help address these barriers and improve clinician decision making at the point of care. The investigators convened an emergency medicine informatics expert panel and used a Delphi consensus process to assess the feasibility of translating the current ACEP clinical policies into clinical decision support content. This resulting consensus document will serve to identify limitations to implementation of the existing ACEP Clinical Policies so that future clinical practice guideline development will consider implementation into clinical decision support at all stages of guideline development.

Predicting frequent ED use by people with epilepsy with health information exchange data.

Objectives: To describe (1) the predictability of frequent emergency department (ED) use (a marker of inadequate disease control and/or poor access to care), and (2) the demographics, comorbidities, and use of health services of frequent ED users, among people with epilepsy. Methods: We obtained demographics, comorbidities, and 2 years of encounter data for 8,041 people with epilepsy from a health information exchange in New York City. Using a retrospective cohort design, we explored bivariate relationships between baseline characteristics (year 1) and subsequent frequent ED use (year 2). We then built, evaluated, and compared predictive models to identify frequent ED users (≥4 visits year 2), using multiple techniques (logistic regression, lasso, elastic net, CART [classification and regression trees], Random Forests, AdaBoost, support vector machines). We selected a final model based on performance and simplicity. Results: People with epilepsy who, in year 1, were adults (rather than children or seniors), male, Manhattan residents, frequent users of health services, users of multiple health systems, or had medical, neurologic, or psychiatric comorbidities, were more likely to frequently use the ED in year 2. Predictive techniques identified frequent ED visitors with good positive predictive value (approximately 70%) but poor sensitivity (approximately 20%). A simple strategy, selecting individuals with 11+ ED visits in year 1, performed as well as more sophisticated models. Conclusions: People with epilepsy with 11+ ED visits in a year are at highest risk of continued frequent ED use and may benefit from targeted intervention to avoid preventable ED visits. Future work should focus on improving the sensitivity of predictions.

A conceptual framework for improved analyses of 72-hour return cases

For more than 25 years, emergency medicine researchers have examined 72-hour return visits as a marker for high-risk patient visits and as a surrogate measure for quality of care. Individual emergency departments frequently use 72-hour returns as a screening tool to identify deficits in care, although comprehensive departmental reviews of this nature may consume considerable resources. We discuss the lack of published data supporting the use of 72-hour return frequency as an overall performance measure and examine why this is not a valid use, describe a conceptual framework for reviewing 72-hour return cases as a screening tool, and call for future studies to test various models for conducting such quality assurance reviews of patients who return to the emergency department within 72 hours.

Electronic Collaboration: Using Technology to Solve Old Problems of Quality Care

The participants of the Electronic Collaboration working group of the 2010 Academic Emergency Medicine consensus conference developed recommendations and research questions for improving regional quality of care through the use of electronic collaboration. A writing group devised a working draft prior to the meeting and presented this to the breakout session at the consensus conference for input and approval. The recommendations include: 1) patient health information should be available electronically across the entire health care delivery system from the 9-1-1 call to the emergency department (ED) visit through hospitalization and outpatient care, 2) relevant patient health information should be shared electronically across the entire health care delivery system, 3) Web-based collaborative technologies should be employed to facilitate patient transfer and timely access to specialists, 4) personal health record adoption should be considered as a way to improve patient health, and 5) any comprehensive reform of regionalization in emergency care must include telemedicine. The workgroup emphasized the need for funding increases so that research in this new and exciting area can expand.

Geographical distribution of patients visiting a health information exchange in New York City.

Objective For a health information exchange (HIE) organization to succeed in any given region, it is important to understand the optimal catchment area for the patient population it is serving. The objective of this analysis was to understand the geographical distribution of the patients being served by one HIE organization in New York City (NYC). Materials and Methods Patient demographic data were obtained from the New York Clinical Information Exchange (NYCLIX), a regional health information organization (RHIO) representing most of the major medical centers in the borough of Manhattan in NYC. Patients’ home address zip codes were used to create a research dataset with aggregate counts of patients by US county and international standards organization country. Times Square was designated as the geographical center point of the RHIO for distance calculations. Results Most patients (87.7%) live within a 30 mile radius from Times Square and there was a precipitous drop off of patients visiting RHIO-affiliated facilities at distances greater than 100 miles. 43.6% of patients visiting NYCLIX facilities were from the other NYC boroughs rather than from Manhattan itself (31.9%). Discussion Most patients who seek care at members of NYCLIX live within a well-defined area and a clear decrease in patients visiting NYCLIX sites with distance was identified. Understanding the geographical distribution of patients visiting the large medical centers in the RHIO can inform the RHIOs planning as it looks to add new participant organizations in the surrounding geographical area.