Impact of Predictive Text Clinical Decision Support on Imaging Order Entry in the Emergency Department

PURPOSE

Imaging clinical decision support (CDS) is designed to assist providers in selecting appropriate imaging studies and is now federally required. The aim of this study was to understand the effect of CDS on decisions and workflows in the emergency department (ED).

METHODS

The authors' institution's order entry platform serves up structured indications for imaging orders. Imaging orders are scored by CDS on the basis of appropriate use criteria (AUC). CDS triggers alerts for imaging orders with low AUC scores. Because free text alone cannot be scored by CDS, an artificial intelligence predictive text (AIPT) module was implemented to guide the selection of structured indications when free-text indications are entered. A total of 17,355 imaging orders in the ED over 6 months were retrospectively analyzed.

RESULTS

CDS alerts for low AUC scores were triggered for 3% of all imaging study orders (522 of 17,355). Providers spent an average of 24 seconds interacting with alerts. In 18 of 522 imaging orders with alerts, alternative studies were ordered. After AIPT implementation, the percentage of unscored studies significantly decreased from 81% to 45% (P < .001).

CONCLUSIONS

In a quaternary academic ED, CDS alerts triggered by low AUC scores caused minimal increase in time spent on imaging order entry but had a relatively marginal impact on imaging study selection. AIPT implementation increased the number of scored studies and could potentially enhance CDS effects. CDS implementation enables the collection of novel data regarding which imaging studies receive low AUC scores. Future work could include exploring alternative models of CDS implementation to maximize its impact.

Emergency Department Management of Suicidal Ideation: Challenges, Misperceptions, and Hope

Behavioral crises continue to escalate across the United States. Our country has one of the highest suicide rates amongst developed nations. More than 45,000 U.S. citizens are dying annually now from suicide. Many with suicidal ideation seek care in Emergency Departments in hospital systems under resourced to handle this growing public health crisis. Evidenced-based screening, risk stratification, and treatment continues to evolve and is not standardized. Improved suicide education needs to be more broadly applied across healthcare and society. Missouri as a state is making concentrated efforts to improve resources and care for those with suicidal ideation. Many challenges need to be overcome and time will tell if new statewide initiatives will reduce Missouri's high rate of suicide.

Bridges to Care and Recovery: Addressing Behavioral Health and Mental Health Needs Through the Faith Community

The Bridges to Care and Recovery program supports the behavioral health assessment, treatment, and recovery of individuals through partnerships with the African-American faith community. Church members receive mental health training and skill building, so they can serve as personal mental health educators and advocates. A Community Connector provides guidance and referral to behavioral health services, including access to free counseling. The program reduces the perceived stigma of mental illness and strengthens partnerships between behavioral health service providers and the African-American community.

Impact of order set design on urine culturing practices at an academic medical centre emergency department

BACKGROUND

Urinalysis and urine culture are commonly ordered tests in the emergency department (ED). We evaluated the impact of removal of order sets from the 'frequently ordered test' in the computerised physician order entry system (CPOE) on urine testing practices.

METHODS

We conducted a before (1 September to 20 October 2015) and after (21 October to 30 November 2015) study of ED patients. The intervention consisted of retaining 'urinalysis with reflex to microscopy' as the only urine test in a highly accessible list of frequently ordered tests in the CPOE system. All other urine tests required use of additional order screens via additional mouse clicks. The frequency of urine testing before and after the intervention was compared, adjusting for temporal trends.

RESULTS

During the study period, 6499 (28.2%) of 22 948 ED patients had ≥1 urine test ordered. Urine testing rates for all ED patients decreased in the post intervention period for urinalysis (291.5 pre intervention vs 278.4 per 1000 ED visits post intervention, P=0.03), urine microscopy (196.5vs179.5, P=0.001) and urine culture (54.3vs29.7, P<0.001). When adjusted for temporal trends, the daily culture rate per 1000 ED visits decreased by 46.6% (-46.6%, 95% CI -66.2% to -15.6%), but urinalysis (0.4%, 95% CI -30.1 to 44.4%), microscopy (-6.5%, 95% CI -36.0% to 36.6%) and catheterised urine culture rates (17.9%, 95% CI -16.9 to 67.4) were unchanged.

CONCLUSIONS

A simple intervention of retaining only 'urinalysis with reflex to microscopy' and removing all other urine tests from the 'frequently ordered' window of the ED electronic order set decreased urine cultures ordered by 46.6% after accounting for temporal trends. Given the injudicious use of antimicrobial therapy for asymptomatic bacteriuria, findings from our study suggest that proper design of electronic order sets plays a vital role in reducing excessive ordering of urine cultures.

An emergency department patient flow model based on queueing theory principles

OBJECTIVES

The objective was to derive and validate a novel queuing theory-based model that predicts the effect of various patient crowding scenarios on patient left without being seen (LWBS) rates.

METHODS

Retrospective data were collected from all patient presentations to triage at an urban, academic, adult-only emergency department (ED) with 87,705 visits in calendar year 2008. Data from specific time windows during the day were divided into derivation and validation sets based on odd or even days. Patient records with incomplete time data were excluded. With an established call center queueing model, input variables were modified to adapt this model to the ED setting, while satisfying the underlying assumptions of queueing theory. The primary aim was the derivation and validation of an ED flow model. Chi-square and Student's t-tests were used for model derivation and validation. The secondary aim was estimating the effect of varying ED patient arrival and boarding scenarios on LWBS rates using this model.

RESULTS

The assumption of stationarity of the model was validated for three time periods (peak arrival rate = 10:00 a.m. to 12:00 p.m.; a moderate arrival rate = 8:00 a.m. to 10:00 a.m.; and lowest arrival rate = 4:00 a.m. to 6:00 a.m.) and for different days of the week and month. Between 10:00 a.m. and 12:00 p.m., defined as the primary study period representing peak arrivals, 3.9% (n = 4,038) of patients LWBS. Using the derived model, the predicted LWBS rate was 4%. LWBS rates increased as the rate of ED patient arrivals, treatment times, and ED boarding times increased. A 10% increase in hourly ED patient arrivals from the observed average arrival rate increased the predicted LWBS rate to 10.8%; a 10% decrease in hourly ED patient arrivals from the observed average arrival rate predicted a 1.6% LWBS rate. A 30-minute decrease in treatment time from the observed average treatment time predicted a 1.4% LWBS. A 1% increase in patient arrivals has the same effect on LWBS rates as a 1% increase in treatment time. Reducing boarding times by 10% is expected to reduce LWBS rates by approximately 0.8%.

CONCLUSIONS

This novel queuing theory-based model predicts the effect of patient arrivals, treatment time, and ED boarding on the rate of patients who LWBS at one institution. More studies are needed to validate this model across other institutions.

Emergency severity index triage system correlation with emergency department evaluation and management billing codes and total professional charges

OBJECTIVES

All services provided by physicians to patients during an emergency department (ED) visit, including procedures and "cognitive work," are described by common procedural terminology (CPT) codes that are translated by coders into total professional (physician) charges for the visit. These charges do not include the technical (facility) charges. The objectives of this study were to characterize associations between Emergency Severity Index (ESI) acuity level, ED Evaluation and Management (E&M) billing codes 99281-99285 and 99291, and total ED provider charges (sum of total procedure and E&M professional charges). Secondary objectives were to identify factors that might affect these associations and to evaluate the performance of ESI and identified variables to predict E&M code and average total professional charges.

METHODS

The authors reviewed 276,824 patient records for calendar year 2007, of which 193,952 adult ED visits from three different ED types (community, university-based academic, and non-university-based academic) met inclusion criteria. Correlations between 1) ESI level and E&M billing code per visit by institution and 2) ESI and total professional charges were analyzed using Spearman rank correlation. Linear regression analysis was performed to identify variables that significantly affected these correlations.

RESULTS

ESI level and E&M codes were moderately correlated (Spearman r = 0.51). ESI levels corresponded proportionately to higher E&M codes. ESI 1, 2, and 3 most frequently corresponded with E&M level 5 (50, 62, and 45%, respectively), and ESI 4 and 5 most frequently corresponded with E&M level 3 (56 and 67%, respectively). Only age by decade significantly affected the association between ESI level and E&M billing code. The mean total professional charge for all patient encounters was $421 (SD ± $204) with increasing mean charges per patient by increasing ESI acuity. Race and E&M code significantly affected the relationship between ESI level and total ED professional charges per patient (adjusted r(2) = 0.66).

CONCLUSIONS

A moderate, nonlinear correlation exists between ESI acuity levels and ED E&M billing codes. Increasing age affects this correlation. Race and E&M code affect the correlation between ESI level and total professional charges. As such, basic triage data can be used to estimate E&M code and total professional charges. Future studies are needed to validate these findings across other institutional settings.