Bibliographic Information - Author (s) - Yr Published/Submitted - Publication - Author Affiliations - Funding	Study - Design - Facility/Setting - Time Period - Population/Sample - Comparator - Study bias	Practice - Description - Duration - Training - Staff/Other Resources - Cost	Outcome Measures - Description (s) - Recording method	Results/Findings - Type of Findings - Findings/Effect Size - Stat. Significance/Test(s) - Results/Conclusion Bias
Lyndon B Johnson General Hospital (Heng J) - 2009 - LMBP Unpublished Submission - Lyndon B Johnson General Hospital Core Laboratory, Houston, TX - Funding: Self-financed	- Design: Before-after - Facility: Lyndon B Johnson hospital, Houston, TX, >300 bed teaching hospital.; > 1,000,000 lab tests annually Study Setting: Laboratory department and all nursing units except ER, ICU, NICU and Outpatient; Lab collects 8,500 specimens/ mo.; 280/day - Time Period: 1/1/2009 – 8/31/2009 Pre: 1/2009 – 4/2009 (4 mos.) Post: 6/2009 – 8/2009 (3 mos.) - Sample: Inpatient blood samples by venipuncture Pre: 41,815 Post: 24,789 - Comparator: Phlebotomists use of a printed draw list and pre-printed specimen label to enter collection information (date/time & ID of patient) - Study bias: Phlebotomists only - low initial/baseline rates	- Description Barcoding system used by laboratory department only; laboratory phlebotomists print labels from wireless handheld printer and label specimen tubes by the patients’ bedside; in use 24/7. No mention of CPOE. - Duration: 6/1/2009– 10/1/2009; ongoing - Training: Staff training takes 3 hours to learn equipment use - Staff: 20 phlebotomists, IT facility staff for installs and training - Cost: Cost related to training phlebotomists: $14.20 * 3 hours * 20 FTEs =$852. Cost of Collection Manager (hardware, installation, support, and training) = $1 million for district (2 hospitals; 650 and 330 beds respectively). (US$ 2009)	- Description: Patient specimen identification (PSID) error rate: Number of mislabeled specimens/total number of specimens - Recording Methods: Incident reports Pre: review of occurrence log based on manual forms Post: online application	- Pretest-Posttest Findings/Effect Size: PSID error rate Pre: 0.012%, (5 / 41, 815) Post: 0.00% (0 / 24,789) Absolute decrease: 0.01% Relative decrease 100.0%; OR = 6.50 (CI: 0.36 117.61) Stat. Significance/Test(s): Proportion successful/ significance not reported Results/conclusion bias: None reported
Quality Rating: 8 (Good) (10 point maximum) Effect Size Magnitude Rating: Moderate (Relevance: Direct)	Study (3 pts maximum): 2; Potential study bias –Sample selection using phlebotomists only with low initial error rates.	Practice (2 pts maximum): 2	Outcome measures (2 pts maximum): 2	Results/findings (3 pts maximum): 2;- Sample sufficiency: Small number of errors reported yields unstable effect size estimate
Univ. of Minnesota Medical Center Fairview (Senn C and Bormann P) - 2009 - LMBP Unpublished Submission - Univ. of Minnesota Medical Center Fairview, Acute Care Laboratory - Funding: Self-financed	- Design: Before-After - Facility/ Setting: UMN Fairview, Minneapolis, MN; >300 bed academic medical center; > 1,000,000 tests/yr. - Study Setting: Clinical lab, EDs, Adult ICUs, Pediatric PCUs - Time Period: Multiple study arms/start dates in various units: Clinical lab: 6/2006–8/2009; Univ. campus ED 7/2006– 8/2009; select PCUs-pilot only: 11/2006–2/2007; Riverside and behavioral ED: 2/2007 –8/2009; Adult ICUs: 2/2008–8/2009. - Sample: 100% of specimen containers; numbers and dates not reported. Total volume: 39,300 / month. - Comparator: No details reported for practice - Study bias: Time period and sample selection methods may introduce bias affecting results	- Description: Barcoding system for patient ID using hand-held PC to verify specimen labels match wristband prior to labeling specimen tubes at the bedside. No mention of CPOE. - Duration: 3 years; ongoing (staggered implementation as indicated in under Study Period). - Training: ~30 min. for users - Staff: Lab in collaboration with nursing and IT staff to implement; 0.5 FTE maintaining, auditing, problem- solving, validation, etc. - Cost: Start-Up: Design & programming cost: $600,000; hardware : ~ $425,000 Post Start-Up: ~$425,000 for new installations; ~$300,000 for replacement hardware	- Description: Patient specimen Identification (PSID) error rate: Number of mislabeled specimens, wrong specimen in tube (WSIT) and unlabeled specimens per 10,000 collections - Recording Methods: Pre-implementation: manual error reporting system Post-implementation: electronic reporting system (electronic event tracking logs, and compared to “cancel comments” in lab computer system). Compliance (scan rate) based on monthly 1-day audits of each unit where barcoding implemented.	- Pretest-Posttest - Findings/Effect Size PSID error rate Units Without Barcoding system: 12.1 errors/10,000 collections. Units with Barcoding system: 0.4 errors/10,000 collections OR = N/A - Stat. Significance/Test(s): None reported Results/conclusion biases: Sample sizes and specific dates not reported. Results not specified by medical unit (i.e., with/without barcoding system vs. those not reported), and different recording methods used for measuring outcomes of practices.
Quality Rating: 5 (Poor: Results/Findings rating = 0) (10 point maximum) Effect Size Magnitude Rating: N/A (Relevance: Less Direct)	Study (3 pts maximum): 1; - Potential study bias: Study sample and selection methods may introduce a study bias substantially affecting results - Sample not adequately described and sample selection may be biased (when practice used “compliantly”)	Practice (2 pts maximum): 2	Outcome measures (2 pts maximum): 2	Results/findings (3 pts maximum): 0; - Sample sufficiency: Measurement period, # tests and errors not reported (−2) - Appropriateness of statistical analysis: Insufficient data to allow/verify calculation of effect size (−1) and different recording method used for two practices (−2)
Univ. of Washington (Schmidt R) - 2009 - LMBP Unpublished Submission - Univ. of Washington, Pathology Laboratory, Seattle, WA - Funding: Self-financed	- Design: Before-after - Facility: Univ. of Washington, Seattle, WA;,>300 bed academic medical center; > 1,000,000 lab tests annually -Study Setting: Anatomic pathology lab gross room. - Time Period: 12/1/2007 – 8/2009 Pre: 12/2007 11/2008 (1 yr.) Post: 12/2008– 8/2009 (9 mos.) - Sample: Primary cassettes/blocks derived from patient specimens (outpatient biopsies and inpatient surgical) Pre: 85,213 Post: 50,016 - Comparator: Not described - Study bias: None noted for error rate measure.	-Barcoding system to identify and track all specimens from accessioning to gross station, and just-in-time, single piece workflow system for cassette/block labeling, with specimen barcode read at grossing station and user specifies number of cassettes to produce and then computer prints 2D barcoded cassettes requiring custom software and commercial cassette printers. - Duration: 9 months (12/1/08– 8/2009), ongoing -Training: End User Training for permanent gross room personnel and rotating pathology residents - Staff: Gross room pathologists, path. assistants and residents - Cost: Software custom~$200,000; 4 cassette printers @ $20,000 each = $80,000; Hardware: PCs, barcode readers, label printers, mounting arms = $8,000 (US$ 2008)	- Description: (1) Primary cassette/ block labeling error rate: # mislabeled specimen cassettes (includes duplicate number, wrong specimen, wrong case, wrong patient) / total pathology specimen cassettes (2) Personnel Savings – estimate of labor hours saved due to practice - Recording Methods: (1) Pre: Estimated from incident reports supplemented by management and user survey Post: Counted directly and documented via incident reports. (2) Survey of gross room personnel – estimates of time saved due to barcoding system	- Pretest-Posttest - Findings/Effect Size: (1) Cassette/block labeling error rate Pre: 1.16% (988 / 85,213 ) Post: 0.008% (4 / 50,016) Absolute decrease: 1.2% Relative decrease 99.3%; ➢ OR = 147 (CI: 55 – 391) (2) Post-practice: saved 0.75–1.0 FTE gross room personnel (less material handling, less error resolution efforts), not reported over what time period. - Stat. Significance/Test(s): Proportion successful; no statistical analysis/significance reported - Results/conclusion bias: personnel savings based on user recall (no point deduction as bias is for non-effectiveness measure)
Quality Rating: 7 (Fair) (10 point maximum) Effect Size Magnitude Rating: Substantial (Relevance: Direct)	Study (3 pts maximum): 2; - Study Setting: Sufficiently distinctive that results may not be generalizable to other settings /specimens – Anat. path. gross room process- derived specimen cassettes	Practice (2 pts maximum): 2	Outcome measures (2 pts maximum): 2	Results/findings (3 pts maximum): 1; - Appropriateness of statistical analysis: Different recording methods used during for pre and post periods for measuring and comparing errors (−2)
Unpublished Study A – Barcoding System - 2009 - LMBP Unpublished Submission - Large academic medical center, Southern California, USA - Funding: Self-financed	- Design: Before-after - Facility: Academic medical center in Western U.S.; >300 beds; > 1,000,000 lab tests/yr. - Setting: Inpatient non-ICU units where blood collected by clinical lab phlebotomy team - Time Period: 1/1/06 – 7/31/2009: Pre: 1–12/2006 (1 year); Post: 1/2007–7/2009) - Sample: All phlebotomist inpatient blood specimens (sample size not reported); approx. 33% of 29,000/mo. collected by clinical phlebotomy team (units: neurology, med./ surg., transplant, OB/GYN, oncology, neuropsych, emergency, pediatric, newborn and NICU) Estimated sample: 9,570/mo. (=.0.33 x 29,000); 114,840/year - Comparator: Status quo (no barcode labeling system)	- Description: Barcoding system with phlebotomists using patient bedside barcode specimen labeling with wireless handheld device and attached mini-barcode label printer. The device can access the patient test orders in real time, collect orders, and print test labels at the patient bedside. CPOE not mentioned. - Duration: 11/06–7/09, ongoing -Training: 3 trainers provided directly from system vendor and 2 FTEs from clinical laboratory IT; no time-related information - Staff: Clinical lab team: 1 FTE phlebotomy supervisor; 20 FTEs for 24/7 blood draws - Cost: Start-up software: $30,000; hardware: $72,000; Annual maintenance: $32,000 (US$ 2006)	- Description: Annual # of patient specimen Identification (PSID) errors Note: error rate estimated from data provided by submitter as described under “Sample” - Recording Methods: Event reporting system and occurrence management reports/ log	- Pretest-Posttest - Findings/Effect Size: PSID Error Rate (calculated using above PSID errors using estimated sample size of 114,840/ yr.): Pre: 12/114,840 = 0.010% Post: 1/114,840 = 0.0008% Absolute decrease: 0.01% Relative decrease 92.0% ➢ OR = 12.00 (CI: 1.56 92.3) Total (annual) PSID errors reported Pre (2006): 12 errors Post: 2007: 1 error 2008: 0 errors; 2009: 0 errors (through 7/09). - Stat. Significance/ Test(s): None reported Results/conclusion bias: None noted.
Quality Rating: 6 (Fair) (10 point maximum) Effect Size Magnitude Rating: Substantial (Relevance: Direct)	Study (3 pts maximum): 1; Potential study bias: (1) Phlebotomists only (no information non-phlebotomist) (−1); (2) barcoded specimens from 11–12/2006 in Pre period (−1)	Practice (2 pts maximum): 2;	Outcome measures (2 pts maximum): 1; - Recording method: May not accurately capture all instances of the outcome	Results/findings (3 pts maximum): 2; - Sample sufficiency: Small number of errors reported yields unstable effect size estimate