Impact of Interfacing Near Point of Care Clinical Chemistry and Hematology Analyzers at Urgent Care Clinics at an Academic Health System.

BACKGROUND: Point-of-care (POC) testing equipment is commonly utilized in outpatient clinics. Our institution recently interfaced POC chemistry and hematology devices at two outpatient clinics via middleware software to the central electronic health record (EHR), facilitating a comparison of manual transcription versus automatic reporting via interface. This allowed for estimation of serious/obvious error rates and manual time savings. Additional goals were to develop autoverification rules and analyze broad trends of results in response to common clinician complaints on the POC testing. MATERIAL AND METHODS: Data were obtained from two satellite clinic sites providing both primary and urgent care within an academic health system. Interface of devices was accomplished via Instrument Manager middleware software and occurred approximately halfway through the 38 month retrospective timeframe. Laboratory results for three testing POC chemistry and hematology panels were extracted with EHR tools. RESULTS: Nearly 100,000 lab values were analyzed and revealed that the rate of laboratory values outside reference range was essentially unchanged before and after interface of POC testing devices (2.0-2.1%). Serious/obvious errors, while rare overall, declined significantly, with none recorded after the interface with autoverified results and only three related to manual edits of results that failed autoverification. Fewer duplicated test results were identified after the interface, most notably with the hematology testing. Anion gap values of less than zero were observed more frequently in POC device tests when compared to central laboratory tests and are attributed to a higher proportion of Cl values greater than 110 mEq/L and CO2 values greater than 30 mEq/L with POC results. Time savings of eliminating manual data entry were calculated to be 21.6 employee hours per month. CONCLUSIONS: In a switch from manual entry to automatic interface for POC chemistry and hematology, the most notable changes were reduction of serious/obvious errors and duplicate results. Significant time employee time savings highlight an additional benefit of instrument interfacing. Lastly, a difference between POC and central laboratory instruments is a higher rate of high Cl and CO2 values relative to the central laboratory.

Impact of add-on laboratory testing at an academic medical center: a five year retrospective study.

BACKGROUND: Clinical laboratories frequently receive orders to perform additional tests on existing specimens ('add-ons'). Previous studies have examined add-on ordering patterns over short periods of time. The objective of this study was to analyze add-on ordering patterns over an extended time period. We also analyzed the impact of a robotic specimen archival/retrieval system on add-on testing procedure and manual effort. METHODS: In this retrospective study at an academic medical center, electronic health records from were searched to obtain all add-on orders that were placed in the time period of May 2, 2009 to December 31, 2014. RESULTS: During the time period of retrospective study, 880,359 add-on tests were ordered on 96,244 different patients. Add-on testing comprised 3.3 % of total test volumes. There were 443,411 unique ordering instances, leading to an average of 1.99 add-on tests per instance. Some patients had multiple episodes of add-on test orders at different points in time, leading to an average of 9.15 add-on tests per patient. The majority of add-on orders were for chemistry tests (78.8 % of total add-ons) with the next most frequent being hematology and coagulation tests (11.2 % of total add-ons). Inpatient orders accounted for 66.8 % of total add-on orders, while the emergency department and outpatient clinics had 14.8 % and 18.4 % of total add-on orders, respectively. The majority of add-ons were placed within 8 hours (87.3 %) and nearly all by 24 hours (96.8 %). Nearly 100 % of add-on orders within the emergency department were placed within 8 hours. The introduction of a robotic specimen archival/retrieval unit saved an average of 2.75 minutes of laboratory staff manual time per unique add-on order. This translates to 24.1 hours/day less manual effort in dealing with add-on orders. CONCLUSION: Our study reflects the previous literature in showing that add-on orders significantly impact the workload of the clinical laboratory. The majority of add-on orders are clinical chemistry tests, and most add-on orders occur within 24 hours of original specimen collection. Robotic specimen archival/retrieval units can reduce manual effort in the clinical laboratory associated with add-on orders.

Autoverification in a core clinical chemistry laboratory at an academic medical center.

BACKGROUND: Autoverification is a process of using computer-based rules to verify clinical laboratory test results without manual intervention. To date, there is little published data on the use of autoverification over the course of years in a clinical laboratory. We describe the evolution and application of autoverification in an academic medical center clinical chemistry core laboratory. SUBJECTS AND METHODS: At the institution of the study, autoverification developed from rudimentary rules in the laboratory information system (LIS) to extensive and sophisticated rules mostly in middleware software. Rules incorporated decisions based on instrument error flags, interference indices, analytical measurement ranges (AMRs), delta checks, dilution protocols, results suggestive of compromised or contaminated specimens, and 'absurd' (physiologically improbable) values. RESULTS: The autoverification rate for tests performed in the core clinical chemistry laboratory has increased over the course of 13 years from 40% to the current overall rate of 99.5%. A high percentage of critical values now autoverify. The highest rates of autoverification occurred with the most frequently ordered tests such as the basic metabolic panel (sodium, potassium, chloride, carbon dioxide, creatinine, blood urea nitrogen, calcium, glucose; 99.6%), albumin (99.8%), and alanine aminotransferase (99.7%). The lowest rates of autoverification occurred with some therapeutic drug levels (gentamicin, lithium, and methotrexate) and with serum free light chains (kappa/lambda), mostly due to need for offline dilution and manual filing of results. Rules also caught very rare occurrences such as plasma albumin exceeding total protein (usually indicative of an error such as short sample or bubble that evaded detection) and marked discrepancy between total bilirubin and the spectrophotometric icteric index (usually due to interference of the bilirubin assay by immunoglobulin (Ig) M monoclonal gammopathy). CONCLUSIONS: Our results suggest that a high rate of autoverification is possible with modern clinical chemistry analyzers. The ability to autoverify a high percentage of results increases productivity and allows clinical laboratory staff to focus attention on the small number of specimens and results that require manual review and investigation.