When Should ED Physicians Use an HIE? Predicting Presence of Patient Data in an HIE.

OBJECTIVES: Health information exchanges (HIEs) make possible the construction of databases to characterize patients as multisystem users (MSUs), those visiting emergency departments (EDs) of more than one hospital system within a region during a 1-year period. HIE data can inform an algorithm highlighting patients for whom information is more likely to be present in the HIE, leading to a higher yield HIE experience for ED clinicians and incentivizing their adoption of HIE. Our objective was to describe patient characteristics that determine which ED patients are likely to be MSUs and therefore have information in an HIE, thereby improving the efficacy of HIE use and increasing ED clinician perception of HIE benefit. METHODS: Data were extracted from a regional HIE involving four hospital systems (11 EDs) in the Charleston, South Carolina area. We used univariate and multivariable regression analyses to develop a predictive model for MSU status. RESULTS: Factors associated with MSUs included younger age groups, dual-payer insurance status, living in counties that are more rural, and one of at least six specific diagnoses: mental disorders; symptoms, signs, and ill-defined conditions; complications of pregnancy, childbirth, and puerperium; diseases of the musculoskeletal system; injury and poisoning; and diseases of the blood and blood-forming organs. For patients with multiple ED visits during 1 year, 43.8% of MSUs had ≥4 visits, compared with 18.0% of non-MSUs (P < 0.0001). CONCLUSIONS: This predictive model accurately identified patients cared for at multiple hospital systems and can be used to increase the likelihood that time spent logging on to the HIE will be a value-added effort for emergency physicians.

A Comprehensive View of Frequent Emergency Department Users Based on Data from a Regional HIE.

OBJECTIVES: A small but significant number of patients make frequent emergency department (ED) visits to multiple EDs within a region. We have a unique health information exchange (HIE) that includes every ED encounter in all hospital systems in our region. Using our HIE we were able to characterize all frequent ED users in our region, regardless of hospital visited or payer class. The objective of our study was to use data from an HIE to characterize patients in a region who are frequent ED users (FEDUs). METHODS: We constructed a database from a cohort of adult patients (18 years old or older) with information in a regional HIE for a 1-year period beginning in April 2012. Patients were defined as FEDUs (those who made four or more visits during the study period) and non-FEDUs (those who made fewer than four ED visits during the study period). Predictor variables included age, race, sex, payer class, county of residence, and International Classification of Diseases, Ninth Revision codes. Bivariate (χ(2)) and multivariate (logistic regression) analyses were performed to determine associations between predictor variables and the outcome of being a FEDU. RESULTS: The database contained 127,672 patients, 12,293 (9.6%) of whom were FEDUs. Logistic regression showed the following patient characteristics to be significantly associated with the outcome of being a FEDU: age 35 to 44 years; African American race; Medicaid, Medicare, and dual-pay payer class; and International Classification of Diseases, Ninth Revision codes 630 to 679 (complications of pregnancy, childbirth, and puerperium), 780 to 799 (ill-defined conditions), 280 to 289 (diseases of the blood), 290-319 (mental disorders), 680 to 709 (diseases of the skin and subcutaneous tissue), 710 to 739 (musculoskeletal and connective tissue disease), 460 to 519 (respiratory disease), and 520 to 579 (digestive disease). No significant differences were noted between men and women. CONCLUSIONS: Data from an HIE can be used to describe all of the patients within a region who are FEDUs, regardless of the hospital system they visited. This information can be used to focus care coordination efforts and link appropriate patients to a medical home. Future studies can be designed to learn the reasons why patients become FEDUs, and interventions can be developed to address deficiencies in health care that result in frequent ED visits.

Observational study and estimate of cost savings from use of a health information exchange in an academic emergency department.

BACKGROUND: Federal initiatives to improve health care information sharing have led to the development of a new type of regional electronic medical record known as a health information exchange (HIE). OBJECTIVE: Our aim was to investigate the ability of an HIE to decrease health services use for emergency department (ED) patients. METHODS: We performed an observational, prospective study using a voluntary, anonymous survey among clinicians at an urban academic ED. All ED clinicians were eligible to participate. Survey items addressed clinician perception of whether information from the HIE avoided the use of hospital resources, improved quality of care, and reduced length of stay (LOS). Cost savings were estimated by multiplying the number of services the clinicians completing our survey reported they avoided through use of the HIE by the costs of those services at our facility. The study was approved by the Institutional Review Board at the study site. RESULTS: The study was conducted between August and December of 2011. There were 18,529 patient encounters during the study period and 60 clinicians at the study site who were eligible to participate. The clinicians consulted the HIE for 5.39% of these encounters (998 patients). Surveys were completed by the clinicians caring for 13.8% (n = 138) of these patients. Of the completed surveys, 76% (105 surveys) referenced patients for whom the HIE was found to contain information on the patient under care by the clinician participant. These 105 patients formed the sample on which our analysis was based. Within this sample of patients, the following studies were reported to have been avoided by the clinicians participating in our survey: values are percent of patients for whom a study was reported to have been avoided (actual number of studies avoided): laboratory/microbiology: 30.5% (32 studies); radiologic studies: 47.6% (50 studies); consultations: 19% (20 consultations); and admissions: 11.4% (12 admissions). Calculated cost savings based on these estimates were as follows: laboratory/microbiology: $462.85; radiologic studies: $160,893.00; consultations: $3,990.00; and admissions: $118,131.84. Total savings: $283,477. Clinicians participating in the study reported improved quality of care for 86.7% of their patients, as well as a mean time savings of 120.8 minutes. CONCLUSIONS: According to clinician estimates, use of an HIE in this urban academic ED resulted in reduced use of hospital resources, noteworthy cost savings, decreased LOS, and improved quality of care. Limitations included the observational nature of the study, selection bias, the Hawthorne effect, and cost estimates being from a single institution. Allowance was not made for additional services used because of information obtained from the HIE.