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 RHIO's planning as it looks to add new participant organizations in the surrounding geographical area.

Perceptions of health information exchange in home healthcare.

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.

Acute coronary syndrome cohort definition: troponin versus ICD-9-CM codes.

AIM: To determine the accuracy of troponin laboratory results versus International Classification of Diseases clinical modification codes (ICD-9-CM) in identifying acute coronary syndrome (ACS) rule-out (R/O) patients who present to emergency departments (EDs). MATERIALS & METHODS: Retrospective data analysis and chart review (to establish gold standard) were conducted on ED patients. Data retrieved from a clinical data warehouse were reviewed to identify patients with two or more troponins within 24 h of ED registration and ICD-9-CM codes consistent with ACS R/O. RESULTS: Of 329 charts reviewed, 17 were determined to be ACS R/O. A total of 31 out of 329 (9.42%, 95% CI: 6.26­12.58%) had two or more troponins with a sensitivity of 100% (95% CI: 77.08­100%) and specificity of 95.51% (95% CI: 92.42­97.43%). A total of 32 out of 329 patients (9.73%, 95% CI: 6.53­12.93%) had R/O ICD-9-CM codes with a sensitivity of 76.47% (95% CI: 49.76­83.00%) and specificity of 93.91% (95% CI: 90.50­96.19%). All 17 gold-standard ACS R/O patients were identified using troponins while ICD-9-CM identified 13 out of 17. CONCLUSION: Clinical data (two troponins) availability is timelier and compares well with billing data (ICD-9-CM codes) in ACS R/O patient identification. Clinical data use may be generalized to identify other disease specific cohorts for clinical research.

Preparing for the evaluation of health information exchange.

To prepare for the evaluation of a health information exchange (HIE) project in New York City, we collected pre-implementation data regarding aspects of care that might be affected by the HIE initiative. The first application of the HIE will be to provide data to emergency physicians; therefore, we focused on measures relevant to emergency care. These data allowed us to better understand the characteristics of our patient population and perform sample size calculations for certain outcome measures.