The Impact of an Electronic Ordering System on Blood Bank Specimen Rejection Rates

Forest, Sylvain; Shirazi, Maryam; Wu-Gall, Charlotte; Stotler, Brie A.

doi:10.1093/ajcp/aqw204

Cited by 7 publications

(4 citation statements)

References 11 publications

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“…Previous studies have focused on evaluating the numbers of mislabeled specimens before and after implementation of an electronic system. [15][16][17] Our approach analyses the use of barcode scanning several years after implementation, to assess real-world performance in a pediatric and maternity tertiary care center.…”

Section: Discussionmentioning

confidence: 99%

Patient and specimen identification in a tertiary care pediatric hospital: Barcodes do not scan themselves

et al. 2023

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Background Despite the safety improvements linked to the use of barcodes for patient and specimen identification, patient misidentification remains a leading cause of transfusion‐associated reactions including fatalities. A wealth of evidence supports the use of barcodes in general, but there is less published evidence of real‐world barcode compliance. This project investigates barcode scanning compliance for patient and specimen identification at a tertiary care pediatric/maternity hospital. Study Design and Methods Transfusion laboratory specimen collection noncompliance events between January 1, 2019, and December 31, 2019 were retrieved from the hospital laboratory information system. Data were analyzed including stratification of collections by collector role and collection event. A survey of blood collectors was conducted. Results Collection compliance for 6285 blood typing specimens was evaluated. Full barcode scanning identification of both patient and specimen was utilized in only 33.6% of total collections. The remaining two thirds of collections were overridden by the blood collector: no barcode scanning occurred in 31.3%, while the specimen accession label was scanned but not the patient armband in 32.3% of total collections. There were significant differences between phlebotomists and nurses, with more phlebotomists performing the full scanning and specimen scanning only, while more nurses obtained specimens without patient or specimen scanning (p < .001). Blood collectors identified hardware challenges and training gaps as key contributors to barcode noncompliance. Discussion Our study highlights an instance of poor barcode scanning compliance for patient and specimen identification. We formulated improvement strategies and launched a quality improvement project to address factors influencing noncompliance.

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Section: Discussionmentioning

confidence: 99%

Patient and specimen identification in a tertiary care pediatric hospital: Barcodes do not scan themselves

et al. 2023

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“…EHRs support multiple healthcare functions, including creation and storage of patient notes, managing electronic prescriptions and patient-facing web portals 3. Widening access to EHRs is also driving greater adoption of computerised provider order entry (CPOE) systems, which are used by healthcare workers (HCWs) to submit diverse electronic requests, ranging from laboratory investigations,4–14 to imaging studies and radiological examinations,15–22 to health education videos,3 to drugs and medications 1 2 23–25. The proportion of hospitals using CPOE is not known 5.…”

Section: Introductionmentioning

confidence: 99%

Impact of computerised provider order entry on the quality and quantity of clinical information included with investigation requests: an interrupted time series analysis

et al. 2023

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IntroductionRelevant clinical information is vital to inform the analytical and interpretative phases of most investigations. The aim of this study is to evaluate the impact of implementation of computerised provider order entry (CPOE), featuring order-specific electronic order entry forms (eOEFs), on the quality and quantity of clinical information included with investigation requests.MethodsThe CPOE module of a commercially available electronic health record (Cerner Millennium) was implemented at a large, tertiary care centre. The laboratory information management system was interrogated to collect data on specimens sent for microbiological culture 1 year before implementation of CPOE (2018), immediately post implementation (2019) and 6 months post implementation (2020). An interrupted time series analysis was performed, using text mining, to evaluate the quality and quantity of free-text clinical information.ResultsIn total, 39 919 specimens were collected from 16 458 patients. eOEFs were used to place 10 071 out of 13 735 orders in 2019 (73.3%), and 9155 out of 12 229 orders in 2020 (74.9%). No clinical details were included with 653 out of 39 919 specimens (1.6%), of which 22 (3.4%) were ordered using eOEFs. The median character count increased from 14 in 2018, to 41 in 2019, and 38 in 2020. An anti-infective agent was specified in 581 out of 13 955 requests (4.2%) in 2018; 5545 out of 13 735 requests (40.4%) in 2019; and 5215 out of 12 229 requests (42.6%) in 2020. Ciprofloxacin or piperacillin-tazobactam (Tazocin) were mentioned in the clinical details included with 421 out of 15 335 urine culture requests (2.7%), of which 406 (96.3%) were ordered using eOEFs. Subsequent detection of in vitro non-susceptibility led to a change in anti-infective therapy for five patients.ConclusionsImplementation of CPOE, featuring order-specific eOEFs, significantly and sustainably improves the quality and quantity of clinical information included with investigation requests, resulting in changes to patient management that would not otherwise have occurred.

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“…Many factors may lead to blood sampling errors. These factors include incorrect sample or patient identification, wrong sample labeling, inadequate training and education, lack of process standardization, inappropriate equipment and suppliers, lack of proper patient engagement, limited technological solutions, and staff overload and interruptions (De la Salle, 2019;Forest et al, 2017;Frietsch et al, 2017;Kaufman et al, 2018;World Health Organization, 2010).…”

Section: Introductionmentioning

confidence: 99%

Using Failure Mode and Effects Analysis in Improving Nursing Blood Sampling at an International Specialized Cancer Center

Haroun

Ruzzieh

Hussien

et al. 2021

Asian Pac J Cancer Prev

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Background:The process of blood sampling is considered one of the primary and most common nursing invasive procedures carried out daily. Any failure at any point could have a severe negative impact on patient outcomes. Purpose: This project aimed to assess and improve the nursing blood sampling process in a specialized cancer center using failure mode and effect analysis (FMEA). Methods: An observational analytical design of the nursing blood sampling process using FMEA was conducted in King Hussein Cancer Center in Amman, Jordan. Seven steps were conducted, including a review of the blood sampling process, brainstorming potential failures, listing potential effects of each failure mode, assigning a severity rating for each potential effect, assigning a frequency/occurrence rating for each failure mode, assigning a detection rating scale for each failure mode, and calculating the Risk Priority Number (RPN) for each effect. Results: Eight (out of 28) main critical failure modes with more than 200 RPN were identified in the blood sampling process. Accordingly, five themes were developed to guide the corrective actions. These themes included: process and responsibility modifications, resource and information technology utilization, patients and family engagement, safety culture, and education and training after implementation of the corrective actions. This resulted in a 58 % reduction in the RPN of major failure modes. Conclusion: Many factors lead to blood sampling errors. A critical focus should be conducted on the preparation phase due to the possible errors that may occur. Proper identification of patients and blood sample tests are the keys to a significant decrease in blood sampling errors.

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The Impact of an Electronic Ordering System on Blood Bank Specimen Rejection Rates

Abstract: Our data demonstrate that implementation of an electronic ordering system significantly decreased the rate of blood sample rejection.

Cited by 7 publications

References 11 publications

Patient and specimen identification in a tertiary care pediatric hospital: Barcodes do not scan themselves

Patient and specimen identification in a tertiary care pediatric hospital: Barcodes do not scan themselves

Impact of computerised provider order entry on the quality and quantity of clinical information included with investigation requests: an interrupted time series analysis

Using Failure Mode and Effects Analysis in Improving Nursing Blood Sampling at an International Specialized Cancer Center

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