Blood Bank Specimen Mislabeling: A College of American Pathologists Q-Probes Study of 41 333 Blood Bank Specimens in 30 Institutions.
To reduce the risk of error, American Association of Blood Banks standards require that patient blood sample tubes have affixed to them labels bearing at least 2 unique patient identifiers and the dates on which specimens were collected. (4) Further, several studies have demonstrated that bar coding patient specimens reduces specimen misidentification. (5-9)
Since 1989, the College of American Pathologists Q-Probes studies have determined a broad range of performance benchmarks in anatomic pathology and laboratory medicine. (10-12) Participants in these studies, representing the entire spectrum of practice settings worldwide, have been able to compare their performances with those of their peers, and to share among their peers laboratory practices associated with superior performance.
A previous Q-Probes study of 122 blood bank laboratories performed in 2007 determined normative rates of mislabeled specimens submitted to blood banks and the rates of instances in which specimen tubes contained blood belonging to another patient (so-called wrong blood in tube [WBIT]), and examined laboratory and hospital practices that the study designers thought might influence those rates. (13)
In this Q-Probes study, we again reassessed the normative rates of mislabeled blood bank specimens and WBIT to determine whether or not this rate has diminished, and again examined practices, in particular the use of bar coding, that we thought might contribute to diminished rates.
Laboratories enrolled in the College of American Pathologists Q-Probes program for the first quarter of 2015 participated in this study. The study was conducted and the data were handled in a manner similar to that described previously. (4)
Upon their enrollments into the Q-Probes program, participants from each institution submitted certain demographic information including their institutions' geographic locations, community classifications (urban, suburban, rural), teaching status, residency program status, number of occupied beds, and both hospital and laboratory accreditation status.
The study instructions requested participants to tally both retrospectively during the previous 12 months and prospectively during the next 30 days the number of inpatient and outpatient specimens submitted for ABO typing and the number of those specimens that fulfilled their institution's definitions of being mislabeled. Our outcome measurement was the number of mislabeled specimens per 1000 specimens submitted for ABO typing.
For those patients whose ABO blood types were archived in blood bank files, we asked participants to tally the number of patients for whom the current specimen's blood type result differed from that in their records, so-called WBIT. We excluded from the study all specimens submitted from patients who had known ABO discrepancies (eg, history of bone marrow transplantation, stem cell transplants, cord blood transfusions, etc).
We evaluated the effects of various practice characteristics on the rates of misidentification by asking participants to complete detailed questionnaires (see Table 1).
Statistical analysis was performed to determine which demographic and practice characteristics were significantly associated with the performance indicators--ABO mislabeled specimen rate (per 1000 specimens) and WBIT rate (per 1000 specimens). Because of the skewed distributions, the performance indicators were log transformed.
To detect associations between the performance indicators and the discrete-valued demographic/practice variables, we used for univariate analyses both Kruskal-Wallis and Wilcoxon rank sum tests, and for linear regression analysis continuous independent variable testing. We then included variables with significant associations (P < .10) in a forward-selection multivariate regression model. We used a significance level of .05 for this final model.
We evaluated differences between the 2007 and 2015 performance indicator distributions with the Kruskal-Wallis test. All analyses were performed with SAS 9.3 (SAS Institute, Cary, North Carolina).
A total of 30 institutions submitted data for this study, the demographic characteristics of which are shown in Table 2. Most laboratories (19 of 30; 63.3%) were associated with voluntary, nonprofit, nongovernmental hospitals comprising 300 or fewer beds. Slightly more than two-thirds (21 of 30; 70%) of these hospitals were located in urban locations and the remaining third (9 of 30; 30%) were located in rural locations.
Participants recorded data on 41 333 blood specimens submitted for ABO typing. They identified 306 mislabeled specimens, yielding an aggregate rate of 7.4 mislabeled specimens per 1000 specimens submitted. Archived laboratory records included ABO types for 23 234 of these specimens, 10 of which were identified as having WBIT, yielding an aggregate WBIT rate of 0.43/1000 specimens.
Table 3 shows the percentile distributions of mislabeled blood bank specimens among the 30 participating institutions, and of WBIT specimens in the 29 institutions that provided WBIT data. The top-performing quartile recorded no mislabeled or WBIT specimens. Half the laboratories received slightly more than 4 mislabeled specimens per 1000 and no WBIT specimens. The bottom-performing 10% of laboratories received more than 18 mislabeled and almost 2 WBIT specimens for every 1000 blood bank specimens health care workers submitted to them.
Twenty-one of the 30 participating laboratories (70%) required and 9 (30%) did not require that specimens be labeled with the patients' birth dates. The median rate of mislabeled specimens among those laboratories requiring birth date labeling was 1.52 per 1000 specimens, compared with 12.61 per 1000 specimens for those that did not (P = .02).
Twenty-nine participants provided information as to whether their institutions used bar code readers to identify patients by their armband at the time of specimen collection. Eleven of 29 (37.9%) did and 18 of 29 (62.1%) did not use bar code readers for this purpose. The specimen mislabeling and WBIT rates were not associated with the use of bar codes or with any of the other practice variables we investigated.
In this study, we recorded both aggregate and institutional rates of ABO blood specimen mislabeling and instances of WBIT. The aggregate mislabeling rate for 41 333 blood bank specimens examined in 30 participating institutions was 7.4 mislabeled specimens (306) per 1000 specimens submitted. This rate is slightly lower than the rate of 11.2 per 1000 (1258 specimens) tallied in the 2007 study in which 122 institutions examined 112 112 specimens. The rate of WBIT was 0.43 per 1000 specimens (10 of 23 234) and is essentially identical to the WBIT rate of 0.38 per 1000 specimens (23 of 61 305) determined in the 2007 study.
The institutional mislabeling rates provide another perspective. Whereas at least a quarter of participants reported no instances of blood bank specimen mislabeling, at least 75% of participants reported institutional performance that was no better, and if anything a bit worse, than what participants reported in the 2007 study. (7)
That institutional performance has not budged may be an accurate assessment of the state of blood bank specimen mislabeling. However, other conclusions must be considered. The results may reflect a statistical consequence of the small sample size of this repeat study. Also, the data may reflect bias inherent in the population of institutions choosing to participate in this Q-Probes study. We do not know how many institutions enrolled in this study precisely because they were having trouble with specimen mislabeling, which, if there were many, might have skewed the results. The anonymity of participation in the Q-Probes studies did not allow us to compare the performance of individual laboratories that may have participated in both this and the 2007 study. Regardless, this Q-Probes study reveals that not all transfusionists routinely adhere to their institutions' labeling requirements.
In addition to having the ability to compare their performance with that of their peers, participants in the Q-Probes Program seek to discover practices that may improve their performance. In this study, the practice of requiring that all specimens include patients' birth dates was associated with lower specimen mislabeling rates. None of the other practice variables we tested, including the use of bar coding, were associated with lower mislabeling rates.
Slightly less than 38% (11 of 29) of the participants in this study used bar coding to identify patients, almost a 5-fold increase over the 8% (10 of 123) of the 2007 Q-Probes study participants that claimed to be using bar codes. (7) Yet the use of bar coding to identify patients by their armbands at the time of specimen collection was not associated with lower mislabeling rates. Other multi-institutional Q-Probes studies have also failed to correlate the use of bar coding with lower specimen mislabeling rates. (14-16) Why is it that single-institutional studies were able to correlate bar coding with lower rates of mislabeling and multi-institutional studies could not? We believe it is logical to assume that the experimental conditions can be more tightly controlled in studies performed in single institutions than they can be in multi-institutional studies. We have no way of knowing whether better-performing institutions that do not bar code specimens compensated by using other practices about which we did not inquire, or whether poorer-performing institutions that did bar-code specimens harbored operational flaws about which we also did not inquire.
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(2.) Quillen K, Murphy K. Quality improvement to decrease specimen mislabeling in transfusion medicine. Arch Pathol Lab Med. 2006;130(8):1196-1198.
(3.) US Food and Drug Administration. Fatalities Reported to FDA Following Blood Collection and Transfusion: Annual Summary for Fiscal Year 2008: 2008 Food and Drug Administration: Transfusion/Donation Fatalities. Silver Spring, MD. http://www.fda.gov/downloads/BiologicsBloodVaccines/SafetyAvailability/BloodSafety/UCM113904.pdf. Accessed August 15, 2016.
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(9.) Nichols JH, Bartholomew C, Brunton M, et al. Reducing medical errors through barcoding at the point of care. Clin Leadersh Manag Rev. 2004;18(6): 328-334.
(10.) Howanitz PJ. Quality assurance measurements in departments of pathology and laboratory medicine. Arch Pathol Lab Med. 1990;114(11):1131-1135.
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(13.) Grimm E, Friedberg RC, Wilkinson DS, AuBuchon JP, Souers RJ, Lehman CM. Blood bank safety practices: mislabeled samples and wrong blood in tube--a Q-Probes analysis of 122 clinical laboratories. Arch Pathol Lab Med. 2010; 134(8):1108-1115.
(14.) Nakhleh RE, Idowu MO, Souers RF, Meier FA, Bekeris LG. Mislabeling of cases, specimens, blocks, and slides: a College of American Pathologists study of 136 institutions. Arch Pathol Lab Med. 2011;135(8):969-974.
(15.) Wagar EA, Stankovic AK, Raab S, Nakhleh, Walsch MK. Specimen labeling errors: a Q-Probes analysis of 147 clinical laboratories. Arch Pathol Lab Med. 2008;132(10):1617-1622.
(16.) Valenstein PN, Raab SS, Walsh MK. Identification errors involving clinical laboratories: a College of American Pathologists Q-Probes study of patient and specimen identification errors at 120 institutions. Arch Pathol Lab Med. 2006; 130(8):1106-1113. David A. Novis, MD; Paul F. Lindholm, MD; Glenn Ramsey, MD; Kirsten W. Alcorn, MD; Rhona J. Souers, MS; Barbara Blond, MBA.
Accepted for publication July 20, 2016.
From Novis Consulting, LLC, Portsmouth, New Hampshire (Dr Novis); the Hemostasis/Coagulation Laboratory and Blood Bank and Transfusion Medicine (Dr Lindholm) and the Department of Pathology (Dr Ramsey), Feinberg School of Medicine, Northwestern University, Chicago, Illinois; Bloodworks Northwest, Seattle, Washington (Dr Alcorn); and the Department of Biostatistics, College of American Pathologists, Northfield, Illinois (Mss Souers and Blond).
The authors have no relevant financial interest in the products or companies described in this article.
Reprints: David A Novis, MD, Novis Consulting, LLC, 213 South St, Portsmouth, NH 03801 (email: email@example.com).
Table 1. Laboratory Practices Relating to Blood Bank Specimens No. % Does your hospital have a written policy with explicit criteria for acceptance/rejection of blood bank specimens? Yes 30 100.0 No 0 0.0 If you have a written policy does the policy permit exceptions to the standard acceptance/rejection criteria under specific circumstances or with permission of the laboratory medical director? Yes 18 60.0 No 12 40.0 Do nonlaboratory personnel collect and label blood bank specimens? Yes 26 86.7 No 4 13.3 Approximately what percentage of your blood bank specimens are collected and labeled by nonlaboratory personnel? Less than 10 7 26.9 10-50 9 34.6 51-90 6 23.1 Greater than 90 4 15.4 If nonlaboratory personnel collect and label blood bank specimens, is there a hospital-approved SOP governing specimen labeling and submission? Yes 25 96.2 No 1 3.8 If nonlaboratory personnel collect and label blood bank specimens, do they receive specific training on specimen labeling? Yes 24 92.3 No 2 7.7 If there is a hospital-approved SOP governing specimen labeling, are on-site audits conducted to assure compliance with the policy? (a) Yes 16 61.5 No 6 23.1 Does your institution have a specific policy prohibiting the practice of producing and saving labels for specimen labeling at a future specimen collection? Yes 16 53.3 No 14 46.7 In circumstances where a patient armband is required to be used for patient identification, does your institution have a specific policy requiring an armband to be present on the patient before specimen collection can proceed? (This measure excluded special circumstances where exceptions to the policy are permitted, for example, patients in the burn unit or newborn intensive care patients.) Yes 29 100.0 No 0 0.0 Does your institution use a separate, blood bank-specific armband or patient identifier for inpatients? Yes 13 43.3 No 17 56.7 Does your institution allow clinicians to remove armbands during an inpatient admission (eg, for surgery)? Yes 11 39.3 No 17 60.7 Does your institution have a specific policy addressing replacement of armbands that have been removed? Yes 20 71.4 No 8 28.6 Does your institution limit who can apply a patient armband (eg, only admitting personnel, only nursing personnel)? Yes 18 62.1 No 11 37.9 Does your institution allow patient name changes during one admission (eg, spelling changes, trauma designation changed to actual name)? Yes 29 96.7 No 1 3.3 Do you require submission of a new specimen for ABO typing when a patient's name is changed/updated during an admission? Yes 17 56.7 No 13 43.3 Do you require 2 ABO typings on patients with no historical ABO type before issuing non-group O RBCs outside of an emergency situation? Yes 27 90.0 No 3 10.0 If you require 2 typings, do you require ABO typing on 2 different specimens? Yes 18 66.7 No 9 33.3 Do you store and retrieve historical ABO types in a laboratory or hospital computer? Yes 28 93.3 No 2 6.7 Does your computer contain historical blood types performed by other hospitals affiliated with yours? Yes 7 24.1 No 22 75.9 Are you served by a centralized transfusion service that may use historical blood types from specimens that were collected at other facilities? Yes 4 13.3 No 26 86.7 Do you use a bar code reader to identify patients by their armband at the time of specimen collection? Yes 11 37.9 No 18 62.1 Does your institution require an armband for outpatient transfusions? Yes 28 93.3 No 2 6.7 When a specimen does not meet the requirements for specimen labeling information, is the specimen automatically discarded? Yes 18 60.0 No 12 40.0 When a specimen does not meet the requirements for specimen labeling information, does your institution permit the specimen label to be corrected? Yes 3 25.0 No 9 75.0 Does your institution require a photo ID to register a patient? Yes 22 73.3 No 8 26.7 In the last 12 months, how many times has your laboratory identified a patient who was registered with an incorrect medical record number (or other unique identifier) because the patient intentionally used another person's identifying information when registering for an encounter at your institution (eg, presented with another person's identification card)? 0 23 92.0 1 1 4.0 3 1 4.0 Abbreviation: RBC, red blood cell;SOP, standard operating procedure. (a) Four institutions responded "not applicable." Table 2. Institution Demographics No. % Institution type (N = 30) Voluntary, nonprofit hospital 19 63.3 Nongovernmental, university hospital 4 13.3 System/integrated delivery network 3 10.0 County hospital 1 3.3 Proprietary hospital 1 3.3 Public health, nonhospital 1 3.3 Other, governmental, federal 1 3.3 Occupied bed size (N = 29) 0-150 11 37.9 151-300 8 27.6 301-450 3 10.3 451-600 4 13.8 >600 3 10.3 Institution location (N = 30) City 12 40.0 Suburban 9 30.0 Rural 9 30.0 Government affiliation (N = 30) Nongovernmental 27 90.0 Governmental, federal 2 6.7 Governmental, nonfederal 1 3.3 Table 3. Performance Indicator (Outcome Metric) Distributions All Institutions Percentiles Study No. of Performance Indicator Year Participants 10th 25th ABO mislabeled specimen rate 2015 30 0.00 0.00 (per 1000 specimens) (a) 2007 122 0.00 0.00 WBIT rate 2015 29 0.00 0.00 (per 1000 specimens) (b) 2007 120 0.00 0.00 Distributions All Institutions Percentiles Study Performance Indicator Year Median 75th 90th ABO mislabeled specimen rate 2015 4.04 12.43 18.19 (per 1000 specimens) (a) 2007 2.90 11.60 18.00 WBIT rate 2015 0.00 .23 1.82 (per 1000 specimens) (b) 2007 0.00 0.00 .80 Abbreviation: WBIT, wrong blood in tube. (a) Kruskal-Wallis test; P = .94. (b) Kruskal-Wallis test; P = .10.
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|Title Annotation:||CAP Laboratory Improvement Programs|
|Author:||Novis, David A.; Lindholm, Paul F.; Ramsey, Glenn; Alcorn, Kirsten W.; Souers, Rhona J.; Blond, Barb|
|Publication:||Archives of Pathology & Laboratory Medicine|
|Date:||Feb 1, 2017|
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