Jason S Shapiro

Icahn School of Medicine at Mount Sinai, Borough of Manhattan, New York, United States

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Publications (47)101.7 Total impact

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    ABSTRACT: Homeless patients experience poor health outcomes and consume a disproportionate amount of health care resources compared with domiciled patients. There is increasing interest in the federal government in providing care coordination for homeless patients, which will require a systematic way of identifying these individuals. We analyzed address data from Healthix, a New York City-based health information exchange, to identify patterns that could indicate homelessness. Patients were categorized as likely to be homeless if they registered with the address of a hospital, homeless shelter, place of worship, or an address containing a keyword synonymous with "homelessness." We identified 78 460 out of 7 854 927 Healthix patients (1%) as likely to have been homeless over the study period of September 30, 2008 to July 19, 2013. We found that registration practices for these patients varied widely across sites. The use of health information exchange data enabled us to identify a large number of patients likely to be homeless and to observe the wide variation in registration practices for homeless patients within and across sites. Consideration of these results may suggest a way to improve the quality of record matching for homeless patients. Validation of these results is necessary to confirm the homeless status of identified individuals. Ultimately, creating a standardized and structured field to record a patient's housing status may be a preferable approach. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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    ABSTRACT: Objectives“Hospital crossover” occurs when people visit multiple hospitals for care, which may cause gaps in electronic health records. Although crossover is common among people with epilepsy, the effect on subsequent use of health services is unknown. Understanding this effect will help prioritize health care delivery innovations targeted for this population.Methods We collected de-identified information from a health information exchange network describing 7,836 people with epilepsy who visited any of seven hospitals in New York, NY from 2009–2012. Data included demographics, comorbidities, and 2 years of visit information from ambulatory, inpatient, emergency department (ED), and radiology settings. We performed two complementary retrospective cohort analyses, in order to (1) illustrate the effect on a carefully selected subgroup, and (2) confirm the effect across the study population. First, we performed a matched cohort analysis on 410 pairs of individuals with and without hospital crossover in the baseline year. Second, we performed a propensity score odds weighted ordinal logistic regression analysis to estimate the effect across all 7,836 individuals. The outcomes were the use of six health services in the follow-up year.ResultsIn the matched pair analysis, baseline hospital crossover increased the odds of more visits in the ED (odds ratio 1.42, 95% confidence interval [CI] 1.05–1.95) and radiology settings (1.7, 1.22–2.38). The regression analysis confirmed the ED and radiology findings, and also suggested that crossover led to more inpatient admissions (1.35, 1.11–1.63), head CTs (1.44, 1.04–2), and brain MRIs (2.32, 1.59–3.37).SignificanceBaseline hospital crossover is an independent marker for subsequent increased health service use in multiple settings among people with epilepsy. Health care delivery innovations targeted for people with epilepsy who engage in hospital crossover should prioritize (1) sharing radiology images and reports (to reduce unnecessary radiology use, particularly head CTs), and (2) improving coordination of care (to reduce unnecessary ED and inpatient use).
    Epilepsia 01/2015; DOI:10.1111/epi.12882 · 4.58 Impact Factor
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    ABSTRACT: Hospital closures are becoming increasingly common in the United States. Patients who received care at the closing hospitals must travel to different, often farther hospitals for care, and nearby remaining hospitals may have difficulty coping with a sudden influx of patients. Our objectives are to analyze the dispersion patterns of patients from a closing hospital and to correlate that with distance from the closing hospital for three specific visit types: emergency, inpatient, and ambulatory. In this study, we used data from a health information exchange to track patients from Saint Vincent's Medical Center, a hospital in New York City that closed in 2010, to determine where they received emergency, inpatient, and ambulatory care following the closure. We found that patients went to the next nearest hospital for their emergency and inpatient care, but ambulatory encounters did not correlate with distance. It is likely that patients followed their ambulatory providers as they transitioned to another hospital system. Additional work should be done to determine predictors of impact on nearby hospitals when another hospital in the community closes in order to better prepare for patient dispersion.
    Applied Clinical Informatics 01/2015; 6(1):185-99. DOI:10.4338/ACI-2014-10-RA-0090 · 0.39 Impact Factor
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    ABSTRACT: For over 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 (EDs) 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 QA reviews of patients who return to the ED within 72 hours.
    American Journal of Emergency Medicine 08/2014; DOI:10.1016/j.ajem.2014.08.005 · 1.15 Impact Factor
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    ABSTRACT: Objective 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. Methods We used a cross-sectional study design to examine the bivariate and multivariable association of demographics, comorbidity, and health service utilization variables with hospital crossover, among people with epilepsy. We identified 8,074 people with epilepsy from the International Classification of Diseases, Ninth Revision (ICD-9) codes, obtained from an HIE that linked seven hospitals in Manhattan, New York. We defined hospital crossover as care from more than one hospital in any setting (inpatient, outpatient, emergency, or radiology) over 2 years. ResultsOf 8,074 people with epilepsy, 1,770 (22%) engaged in hospital crossover over 2 years. Crossover was associated with younger age (children compared with adults, adjusted odds ratio [OR] 1.4, 95% confidence interval [CI] 1.2–1.7), living near the hospitals (Manhattan vs. other boroughs of New York City, adjusted OR 1.6, 95% CI 1.4–1.8), more visits in the emergency, radiology, inpatient, and outpatient settings (p < 0.001 for each), and more head computerized tomography (CT) scans (p < 0.01). The diagnosis of “encephalopathy” was consistently associated with crossover in bivariate and multivariable analyses (adjusted OR 2.66, 95% CI 2.14–3.29), whereas the relationship between other comorbidities and crossover was less clear. SignificanceHospital crossover is common among people with epilepsy, particularly among children, frequent users of medical services, and people living near the study hospitals. HIE should focus on these populations. Further research should investigate why hospital crossover occurs, how it affects care, and how HIE can most effectively mitigate the resultant fragmentation of medical records.A PowerPoint slide summarizing this article is available for download in the Supporting Information section here.
    Epilepsia 02/2014; 55(5). DOI:10.1111/epi.12552 · 4.58 Impact Factor
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    William Fleischman, Tina Lowry, Jason Shapiro
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    ABSTRACT: Introduction/Objectives: Health Information Exchange (HIE) efforts face challenges with data quality and performance, and this becomes especially problematic when data is leveraged for uses beyond primary clinical use. We describe a secondary data infrastructure focusing on patient-encounter, nonclinical data that was built on top of a functioning HIE platform to support novel secondary data uses and prevent potentially negative impacts these uses might have otherwise had on HIE system performance. Background: HIE efforts have generally formed for the primary clinical use of individual clinical providers searching for data on individual patients under their care, but many secondary uses have been proposed and are being piloted to support care management, quality improvement, and public health. Description of the HIE and Base Infrastructure: This infrastructure review describes a module built into the Healthix HIE. Healthix, based in the New York metropolitan region, comprises 107 participating organizations with 29,946 acute-care beds in 383 facilities, and includes more than 9.2 million unique patients. The primary infrastructure is based on the InterSystems proprietary Caché data model distributed across servers in multiple locations, and uses a master patient index to link individual patients’ records across multiple sites. We built a parallel platform, the “visit data warehouse,” of patient encounter data (demographics, date, time, and type of visit) using a relational database model to allow accessibility using standard database tools and flexibility for developing secondary data use cases. These four secondary use cases include the following: (1) tracking encounter-based metrics in a newly established geriatric emergency department (ED), (2) creating a dashboard to provide a visual display as well as a tabular output of near-real-time de-identified encounter data from the data warehouse, (3) tracking frequent ED users as part of a regional-approach to case management intervention, and (4) improving an existing quality improvement program that analyzes patients with return visits to EDs within 72 hours of discharge. Results/Lessons Learned: Setting up a separate, near-real-time, encounters-based relational database to complement an HIE built on a hierarchical database is feasible, and may be necessary to support many secondary uses of HIE data. As of November 2014, the visit-data warehouse (VDW) built by Healthix is undergoing technical validation testing and updates on an hourly basis. We had to address data integrity issues with both nonstandard and missing HL7 messages because of varied HL7 implementation across the HIE. Also, given our HIEs federated structure, some sites expressed concerns regarding data centralization for the VDW. An established and stable HIE governance structure was critical in overcoming this initial reluctance. Conclusions: As secondary use of HIE data becomes more prevalent, it may be increasingly necessary to build separate infrastructure to support secondary use without compromising performance. More research is needed to determine optimal ways of building such infrastructure and validating its use for secondary purposes.
    01/2014; 2(1):Article 19. DOI:10.13063/2327-9214.1099
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    ABSTRACT: In a health care system where patients often have numerous providers and multiple chronic medical conditions, interoperability of health information technology (HIT) is of paramount importance. Regional health information organizations (RHIO) often provide a health information exchange (HIE) as a solution, which gives stakeholders access to clinical data that they otherwise would not otherwise have. A secondary use of preexisting HIE infrastructure is clinical event notification (CEN) services, which send automated notifications to stakeholders. This paper describes the development and implementation of a CEN service enabled by a RHIO in the New York metropolitan area to improve care coordination for patients enrolled in a geriatric emergency department care coordination program. This operational CEN system incorporates several innovations that to our knowledge have not been implemented previously. They include the near real-time notifications and the delivery of notifications via multiple pathways: electronic health record (EHR) "in-baskets," email, text message to internet protocol-based "zone" phones, and automated encounter entry into the EHR. Based on these alerts the geriatric care coordination team contacts the facility where the patient is being seen and offers additional information or assistance with disposition planning with the goal of decreasing potentially avoidable admissions and duplicate testing. During the nearly one-year study period, the CEN program enrolled 5722 patients and sent 497 unique notifications regarding 206 patients. Of these notifications, 219 (44%) were for emergency department (ED) visits; 121 (55%) of those notifications were received during normal business hours when the care coordination team was available to contact the ED where the patient was receiving care. Hospital admissions resulted from 45% of ED visits 17.8% of these admissions lasted 48 hours or less, suggesting some might potentially be avoidable. This study demonstrates the potential of CEN systems to improve care coordination by notifying providers of the occurrence of specific events. Although it could not directly be demonstrated here, we believe that widespread use of CEN systems have potential to reduce potentially avoidable admissions and duplicate testing, likely leading to decreased costs.
    01/2014; 2(3):1095. DOI:10.13063/2327-9214.1095
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    ABSTRACT: We hypothesized that using communitywide data from a health information exchange (HIE) could improve the ability to identify frequent emergency department (ED) users-those with four or more ED visits in thirty days-by allowing ED use to be measured across unaffiliated hospitals. When we analyzed HIE-wide data instead of site-specific data, we identified 20.3 percent more frequent ED users (5,756 versus 4,785) and 16.0 percent more visits by them to the ED (53,031 versus 45,771). Additionally, we found that 28.8 percent of frequent ED users visited multiple EDs during the twelve-month study period, versus 3.0 percent of all ED users. All three differences were significant ($$p ). An improved ability to identify frequent ED users allows better targeting of case management and other services that can improve frequent ED users' health and reduce their use of costly emergency medical services.
    Health Affairs 12/2013; 32(12):2193-8. DOI:10.1377/hlthaff.2013.0167 · 4.64 Impact Factor
  • Annals of Emergency Medicine 10/2013; 62(4):S94. DOI:10.1016/j.annemergmed.2013.07.082 · 4.33 Impact Factor
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    ABSTRACT: The Health Information Technology for Economic and Clinical Health Act of 2009 and the Centers for Medicare & Medicaid Services "meaningful use" incentive programs, in tandem with the boundless additional requirements for detailed reporting of quality metrics, have galvanized hospital efforts to implement hospital-based electronic health records. As such, emergency department information systems (EDISs) are an important and unique component of most hospitals' electronic health records. System functionality varies greatly and affects physician decisionmaking, clinician workflow, communication, and, ultimately, the overall quality of care and patient safety. This article is a joint effort by members of the Quality Improvement and Patient Safety Section and the Informatics Section of the American College of Emergency Physicians. The aim of this effort is to examine the benefits and potential threats to quality and patient safety that could result from the choice of a particular EDIS, its implementation and optimization, and the hospital's or physician group's approach to continuous improvement of the EDIS. Specifically, we explored the following areas of potential EDIS safety concerns: communication failure, wrong order-wrong patient errors, poor data display, and alert fatigue. Case studies are presented that illustrate the potential harm that could befall patients from an inferior EDIS product or suboptimal execution of such a product in the clinical environment. The authors have developed 7 recommendations to improve patient safety with respect to the deployment of EDISs. These include ensuring that emergency providers actively participate in selection of the EDIS product, in the design of processes related to EDIS implementation and optimization, and in the monitoring of the system's ongoing success or failure. Our recommendations apply to emergency departments using any type of EDIS: custom-developed systems, best-of-breed vendor systems, or enterprise systems.
    Annals of emergency medicine 06/2013; 62(4). DOI:10.1016/j.annemergmed.2013.05.019 · 4.33 Impact Factor
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    ABSTRACT: 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.
    BMJ quality & safety 01/2013; 22(3). DOI:10.1136/bmjqs-2012-001419 · 3.28 Impact Factor
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    ABSTRACT: For people with epilepsy, the potential value of health information exchange (HIE) is unknown. We reviewed two years of clinical encounters for 8055 people with epilepsy from seven Manhattan hospitals. We created network graphs illustrating crossover among these hospitals for multiple encounter types, and calculated a novel metric of care fragmentation: "encounters at risk for missing clinical data." Given two hospitals, a median of 109 [range 46 - 588] patients with epilepsy had visited both. Due to this crossover, recent, relevant clinical data may be missing at the time of care frequently (44.8% of ED encounters, 34.5% inpatient, 24.9% outpatient, and 23.2% radiology). Though a smaller percentage of outpatient encounters were at risk for missing data than ED encounters, the absolute number of outpatient encounters at risk was three times higher (14,579 vs. 5041). People with epilepsy may benefit from HIE. Future HIE initiatives should prioritize outpatient access.
    AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium 01/2013; 2013:527-36.
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    ABSTRACT: We evaluated the performance of LOINC® and RadLex standard terminologies for covering CT test names from three sites in a health information exchange (HIE) with the eventual goal of building an HIE-based clinical decision support system to alert providers of prior duplicate CTs. Given the goal, the most important parameter to assess was coverage for high frequency exams that were most likely to be repeated. We showed that both LOINC® and RadLex provided sufficient coverage for our use case through calculations of (a) high coverage of 90% and 94%, respectively for the subset of CTs accounting for 99% of exams performed and (b) high concept token coverage (total percentage of exams performed that map to terminologies) of 92% and 95%, respectively. With trends toward greater interoperability, this work may provide a framework for those wishing to map radiology site codes to a standard nomenclature for purposes of tracking resource utilization.
    AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium 01/2013; 2013:94-102.
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    ABSTRACT: 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 RHIO's planning as it looks to add new participant organizations in the surrounding geographical area.
    Journal of the American Medical Informatics Association 10/2012; 20(e1). DOI:10.1136/amiajnl-2012-001217 · 3.93 Impact Factor
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    ABSTRACT: The aim of this study was to understand home healthcare nurses' current experiences in obtaining outside clinical information at the point of care and the type of clinical information they most desire in their patients' health information exchange profile. A Web-based survey was deployed to home health workers in New York to learn about their experiences retrieving outside clinical data prior to having access to health information exchange, preferred data elements and sources in their patients' health information exchange profiles, and how availability of outside clinical data may affect emergency department referrals. Of the 2383 participants, 566 responded for a 23.8% overall response rate, and 469 of these respondents were RNs. Most RNs, 96.7%, agreed that easier and quicker access to outside information would benefit delivery of care, and 72.6% said the number of emergency department referrals would decrease. When asked about pre-health information exchange access to patient data, 96.3% said it was problematic. Inpatient discharge summaries were chosen most often by the RNs as a top five desired data element 81.5% of the time. Obtaining outside clinical information has been a challenge without health information exchange, but improved access to this information may lead to improved care. Further study is required to assess experiences with the use of health information exchange.
    Computers, informatics, nursing: CIN 05/2012; 30(9):503-9. DOI:10.1097/NXN.0b013e3182573a91 · 0.81 Impact Factor
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    ABSTRACT: Background The trend towards hospitalist medicine can lead to disjointed patient care. Outpatient clinicians may be unaware of patients' encounters with a disparate healthcare system. Electronic notifications to outpatient clinicians of patients' emergency department (ED) visits and inpatient admissions and discharges using health information exchange can inform outpatient clinicians of patients' hospital-based events. Objective Assess outpatient clinicians' impressions of a new, secure messaging-based, patient event notification system. Methods Twenty outpatient clinicians receiving notifications of hospital-based events were recruited and 14 agreed to participate. Using a semi-structured interview, clinicians were asked about their use of notifications and the impact on their practices. Results Nine of 14 interviewed clinicians (64%) thought that without notifications, they would have heard about fewer than 10% of ED visits before the patient's next visit. Nine clinicians (64%) thought that without notifications, they would have heard about fewer than 25% of inpatient admissions and discharges before the patient's next visit. Six clinicians (43%) reported that they call the inpatient team more often because of notifications. Eight users (57%) thought that notifications improved patient safety by increasing their awareness of the patients' clinical events and their medication changes. Key themes identified were the importance of workflow integration and a desire for more clinical information in notifications. Conclusions The notification system is perceived by clinicians to be of value. These findings should instigate further message-oriented use of health information exchange and point to refinements that can lead to even greater benefits.
    Informatics in primary care 01/2012; 20(4):249-55. DOI:10.14236/jhi.v20i4.14
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    ABSTRACT: Notifying ambulatory providers when their patients visit the hospital is a simple concept but potentially a powerful tool for improving care coordination. A health information exchange (HIE) can provide automatic notifications to its members by building services on top of their existing infrastructure. NYCLIX, Inc., a functioning HIE in New York City, has developed a system that detects hospital admissions, discharges and emergency department visits and notifies their providers. The system has been in use since November 2010. Out of 63,305 patients enrolled 6,913 (11%) had one or more events in the study period and on average there were 238 events per day. While event notifications have a clinical value, their use also involves non-clinical care coordination; new workflows should be designed to incorporate a broader care team in their use. This paper describes the user requirements for the notification system, system design, current status, lessons learned and future directions.
    AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium 01/2012; 2012:635-42.
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    ABSTRACT: The financial effects of electronic health records (EHRs) and health information exchange (HIE) are largely unknown, despite unprecedented federal incentives for their use. We sought to understand which components of EHRs and HIE are most likely to drive financial savings in the ambulatory, inpatient, and emergency department settings. Framework development and a national expert panel. We searched the literature to identify functionalities enabled by EHRs and HIE across the 3 healthcare settings. We rated each of 233 functionality-setting combinations on their likelihood of having a positive financial effect. We validated the top-scoring functionalities with a panel of 28 national experts, and we compared the high-scoring functionalities with Stage 1 meaningful use criteria. We identified 54 high-scoring functionality- setting combinations, 27 for EHRs and 27 for HIE. Examples of high-scoring functionalities included providing alerts for expensive medications, providing alerts for redundant lab orders, sending and receiving imaging reports, and enabling structured medication reconciliation. Of the 54 high-scoring functionalities, 25 (46%) are represented in Stage 1 meaningful use. Many of the functionalities not yet represented in meaningful use correspond with functionalities that focus directly on healthcare utilization and costs rather than on healthcare quality per se. This work can inform the development and selection of future meaningful use measures; inform implementation efforts, as clinicians and hospitals choose from among a "menu" of measures for meaningful use; and inform evaluation efforts, as investigators seek to measure the actual financial impact of EHRs and HIE.
    The American journal of managed care 01/2012; 18(8):438-45. · 2.17 Impact Factor

Publication Stats

257 Citations
101.70 Total Impact Points


  • 2004–2015
    • Icahn School of Medicine at Mount Sinai
      • Department of Emergency Medicine
      Borough of Manhattan, New York, United States
  • 2013
    • Mount Sinai Medical Center
      • Department of Emergency Medicine
      New York, New York, United States
  • 2010
    • Georgia Health Sciences University
      • Medical College of Georgia
      Augusta, Georgia, United States
  • 2005–2009
    • Columbia University
      • Department of Biomedical Informatics
      New York City, New York, United States