Effectiveness of Laboratory Practices to Reduce Specimen Labeling Errors at the Time of Specimen Collection in Healthcare Settings: A Laboratory Medicine Best Practices (LMBP) Systematic Review

Abstract

Background

Specimen labeling errors have long plagued the laboratory industry, putting patients at risk of transfusion-related death, medication errors, misdiagnosis, and patient mismanagement. Many interventions have been implemented and deemed to be effective in reducing specimen error rates. The objective of this review was to identify and evaluate the effectiveness of laboratory practices and interventions to develop evidence-based recommendations for the best laboratory practices to reduce labeling errors.

Content

The standardized Laboratory Medicine Best Practices Initiative^TM A-6 methods were used to conduct this systematic review. Total evidence included 12 studies published from 1990 to September 2015. Combined data from 7 studies found that the interventions developed from improved communication and collaboration between the laboratory and clinical staff resulted in substantial decreases in specimen labeling errors [median relative percent change in labeling errors: −75.86; interquartile interval (IQI): −84.77, −58.00]. Further data from the subset of 4 studies showed a significant decrease in specimen labeling errors after the institution of the standardized specimen labeling protocols (median relative percent decrease in specimen labeling errors: −72.45; IQI: −83.25, −46.50).

Summary

Based on the evidence included in this review, interventions that enhance communication and collaboration between laboratory and healthcare professionals can decrease the number of specimen identification errors in healthcare settings. However, more research is needed to make any conclusion on the effectiveness of other evaluated practices in this review, including training and education of the specimen collection staff, audit and feedback of labeling errors, and implementation of new technology (other than barcoding).

IMPACT STATEMENT

The findings from this study are beneficial for patient health and safety, as patients are at risk of adverse events, such as transfusion-related death, medication errors, and misdiagnosis, resulting from patient or specimen misidentification. Although multiple corrective measures have been developed, specimen labeling errors continue to happen. Because of the potential adverse consequences associated with mislabeled specimens, every labeling error should be treated seriously. Based on the findings from this review, multifaceted and multidisciplinary approaches, including improved communication and collaboration between the laboratory and healthcare professionals, can significantly reduce the incidence of specimen labeling errors.

Specimen labeling errors have long plagued the laboratory industry, putting patients at risk of transfusion-related death, medication errors, misdiagnosis, and patient mismanagement. It has been estimated that >160000 adverse patient events occur each year in the US because of patient or specimen identification errors involving the laboratory (1). Eleven percent of all transfusion deaths occur as a result of the phlebotomist not properly identifying the patient or mislabeling a tube of blood (2). In general, specimen labeling errors account for 5.6% to 6.7% of all rejected samples (3, 4). A 2009 Q-Probes study found the rate of tube mislabeling of blood bank samples to be 1.12% (5).

The use of barcoding systems for specimen labeling and point-of-care test barcoding was recommended by the Laboratory Medicine Best Practices Initiative^TM (LMBP)⁷ Workgroup formed by the Centers for Disease Control and Prevention as a best practice in 2010 to reduce identification errors and improve the accuracy of patient specimen and laboratory testing identification in hospital settings (6, 7). However, data accumulated over the past 20 years indicate that the incidence of wrong-blood-in-tube errors remained unchanged even though barcode scanner usage increased from 8% to 38% during the same period (8).

A thorough literature review and establishment of best practices for the industry are necessary to protect patients from the risk of specimen labeling errors. The objective of this review is to identify and evaluate the effectiveness of existing interventions and practices to develop evidence-based recommendations for the best laboratory practices to reduce specimen labeling errors.

Description of Evaluated Practices

In this review, we evaluated the effectiveness of 4 laboratory practices to reduce the incidence of specimen labeling errors, whether blood or any other type of patient specimen (e.g., urine, cerebrospinal fluid, sputum), at the time of specimen collection:

• Improved communication and collaboration between laboratory and healthcare professionals: formation of multidisciplinary teams (MDTs)

• Education and training of healthcare staff responsible for specimen collection

• Audit and feedback of labeling errors: real-time event reporting

• Implementation of new technology.

Improved communication and collaboration between laboratory and healthcare professionals: formation of MDT

The MDT approach helps to improve communication and collaboration between the key stakeholders, including treating healthcare professionals (clinicians and nurses), pathologists, radiologists, and management, to reduce diagnostic errors related to patient misidentification caused by labeling errors (9). The MDT advocates for the development of standardized organizational policies and protocols that emphasize the importance of positive patient identification and are compatible with the values and needs of the medical facilities. For example, the organizational policies and protocols might include the following: requirement of unique patient identifiers on specimen labels, implementation of zero-tolerance policy, staff performance assessment, availability of adequate number of qualified personnel to perform specimen collection, reinforcement of specimen labeling at bedside, and delta checks.

Education and training of healthcare staff responsible for specimen collection

These interventions include education and training of laboratory staff (e.g., technicians/scientists, phlebotomists) and clinical staff (e.g., nurses) who are responsible for collection and labeling of patient specimens in clinical settings. Education and training sessions serve to maintain and increase the knowledge and skills of the staff involved in patient preparation, filling of test requisition forms, and collection and labeling of patient specimens.

Education and training can be conducted through different outreach methods, e.g., educational training modules; dissemination of information through seminars, bulletins, newsletter, courses, infographics, and technical briefs; training in phlebotomy practices; training in technology; and practical demonstrations during training sessions.

Audit and feedback of labeling errors: real-time event reporting

Auditing involves the collection of information about mislabeled specimens on a regular basis and provides feedback to the management and the involved staff with the aim to eliminate these errors or minimize the relative risk of errors. Previous studies have shown that regularly sharing trending data on mislabeled samples with patient care areas can improve phlebotomy practices and reduce specimen mislabeling (10, 11).

Methods

The standardized LMBP A-6 methods that were used to conduct LMBP systematic reviews have been described elsewhere (6). For this review, a systematic review team was formed and included the review coordinator, data abstractors, the Centers for Disease Control and Prevention liaison, and an advisory group called the expert panel team, comprising experts with varied professional experience (see Appendix A in the Data Supplement that accompanies the online version of this article at http://www.jalm.org/content/vol2/issue2 for the member list of the expert panel team for this review). The systematic review team worked under the oversight of the independent, unpaid, nonfederal LMBP Workgroup (see Appendix B in the online Data Supplement for the list of LMBP Workgroup members).

Ask (A-1): review question and analytic framework

Review question(s).

What practices are effective at reducing specimen labeling errors at the time of sample collection in all types of healthcare settings?

To address the applicability of the implementation of evaluated interventions to reduce specimen labeling errors, we also investigated whether the effectiveness of these practices varies according to the type of the setting or population (e.g., emergency, pediatric unit, inpatient, outpatient) and the type of organization (e.g., academic institution, private clinic).

The conceptual approach shown in Fig. 1 illustrates the causal relationship of the laboratory interventions to the relevant intermediate outcomes, e.g., reduction in specimen labeling errors and associated harm to patient health from a missed or delayed diagnosis, unnecessary blood draws, or wrong treatment, as well as improved patient satisfaction resulting from fewer treatment delays, shorter hospital stays, and lower related costs.

Analytical framework.

Fig. 1.

Ultimately, these interventions may lead to a decrease in overall morbidity and mortality and a decrease in healthcare costs at the organizational level.

The following PICO (population, intervention, comparison, outcomes) elements were considered for this review:

Population

• General patients attending all types of healthcare settings who require specimen collection for physician-ordered laboratory testing

Intervention

• The following practices to reduce patient misidentification caused by labeling errors were evaluated:

• Improved communication and collaboration between laboratory and healthcare professionals: formation of MDTs.

• Education and training of healthcare staff responsible for specimen collection.

• Audit and feedback of labeling errors: real-time event reporting.

• Implementation of new technology (other than barcoding): e.g., automatic identification and data capture systems, including radio frequency identification, biometrics (e.g., optical character recognition), magnetic stripes, smart cards, point-of-care label printers and scanners, and voice recognition.

• Comparison group: Group with no exposure to the intervention/practice of interest

Primary Outcomes of interest:

• Decrease in specimen labeling errors at the time of specimen collection

• Decrease in patient harm as a result of:

  • Misdiagnosis

  • Unnecessary blood draws

  • Wrong treatment

• Increase in patient satisfaction by decrease in:

  • Treatment delay

  • Hospital stay

  • Related cost

• Decreased specimen rejection rate

Long-term healthcare outcomes: decrease in related:

• Morbidity and mortality

• Overall healthcare costs

Inclusion and exclusion criteria for evidence to be included in this review

Inclusion criteria.

To be included in this review, the study had to:

• Evaluate the effectiveness of at least 1 of the interventions or practices of interest to reduce specimen labeling error.

• Report at least 1 of the outcomes of interest (listed above) after the intervention implementation.

• Be considered primary research in the form of a study, a dissertation, or a technical or government report.

• Be published in an English-language journal.

• Use a study design that compared outcomes of interest with and without the new practice implementation to reduce specimen mislabeling, e.g., preintervention and postintervention data and concurrent comparison data such as randomized control trials.

In addition, this review included labeling errors associated with all types of patient specimens collected from the patients for laboratory diagnostic testing (e.g., blood, urine, cerebrospinal fluid, sputum).

For analysis purposes, in this systematic review the following labeling error categories were lumped together as “specimen labeling errors”:

• Mislabeled or misidentified specimen: specimen label with patient identifiers from a wrong patient, mostly referred as wrong-blood-in-tube errors in the literature.

• Mismatched labels: patient information on the label does not match with the accompanying requisition form, or patient information on specimen label does not match with the patient's wristband.

• Incomplete, illegible, or unlabeled specimen label: a specimen with a label that lists only partial information of required unique patient identifiers; a specimen without a label or without any patient identifiers on the label; and, finally, specimen labels that had illegible patient identifiers that could not be read electronically or manually.

Exclusion criteria.

The studies on the effectiveness of barcoding practices for reducing patient specimen and laboratory testing identification errors were excluded from the “Implementation of New Technology” category, as these practices are already evaluated in 1 of the previous LMBP reviews (7).

Acquire (A-2): search for evidence

Published evidence was searched from 1990 to September 2015 using Medline OVID (R), Embase OVID, CINAHL EbscoHost, Cochrane Library Database, Dissertation Abstracts, and PubMed to identify studies relevant to evaluations of interventions to reduce specimen mislabeling (see Appendix C in the online Data Supplement for search details). In addition, the evidence retrieved from other informal sources, such as hand searches, including relevant references from all retrieved articles and additional studies identified by subject matter experts on the systematic review team were incorporated into the review. We also received relevant unpublished data from the researchers, laboratories, and institutions in the field through personal requests and the LMBP website, but none of the unpublished data qualified to be included in this review. A total of 10854 relevant records (both published and unpublished) were retrieved as a result of formal and informal literature searches (Fig. 2).

Review search flow diagram: specimen labeling factors.

Fig. 2.

Appraise (A-3): screening, data abstraction, and quality scoring of individual studies

Retrieved evidence was screened at different levels (e.g., title screening and abstract screening) to identify studies meeting the inclusion criteria. Using the standardized LMBP abstraction methods and abstraction form, 2 reviewers abstracted the data from each study that met the inclusion criteria. Any discrepancies among the reviewers were reconciled by consensus. Unresolved discordances between reviewers required at least 1 additional reviewer to abstract the study and serve as the tiebreaker. Based on the abstracted data, each study was rated using a 10-point scale for study quality as good (8–10 score), fair (5–7 score), or poor (≤4 score). Details for the LMBP quality scoring process can be found elsewhere (12). Studies with good and fair quality of execution were included in this review analysis. See Appendix D in the online Data Supplement for the evidence summary tables containing detailed information and quality ratings for each study.

Analyze (A-4): summarization of results and strength of the effect magnitude

Effect estimates for each practice were calculated as relative percentage point change where the studies reported the percent change in specimen labeling errors resulting from the intervention implementation. For each study, the effect estimates were calculated separately using the last available data point.

The following formula was used to calculate the relative percentage change in labeling errors:

$$\text{Postintervention}-\text{Preintervention}/\mathrm{Preintervention}\times 100$$

where Preintervention and Postintervention represent the percent of labeling errors before and after the intervention implementation, respectively.

The strength rating of effect size for each individual study was based on the range of percentage change in labeling errors resulting from the intervention. The reduction in labeling errors between 0% and ≤40% was considered a “minimal” magnitude of effect. Any decrease in labeling errors between >40% and ≤75% was considered of “moderate” magnitude, and any decrease in labeling errors >75% was considered a “substantial” magnitude of effect.

The LMBP criteria were used to draw conclusions on the overall strength of evidence on effectiveness, which is based on the total body of evidence by considering the number of studies included in the evidence, quality of available evidence, consistency of results, magnitude of effect estimates, and applicability considerations. More details about these criteria can be found elsewhere (6).

Results

From the broader search for evidence, a total of 10854 references were retrieved. After removing 167 duplicates, 10621 identified as not relevant to the topic after first- and second-level screening; therefore, 66 were considered for full text abstraction. After the full abstraction and quality scoring, 11 studies qualified for inclusion in the systematic review (Fig. 2). The majority of the studies were conducted in the US (13–22), as well as 1 in India (23) and 1 in Spain (24).

Practice 1: improved communication and collaboration between laboratory and healthcare professionals—formation of the MDT

Seven studies (13, 17–22) qualified for inclusion in the total body of evidence to investigate the effectiveness of interventions as a result of improved communication and collaboration between clinical staff and laboratory personnel. Three studies (20–22) were of “good” quality, and 4 studies (13, 17–19) were of “fair” quality. All identified interventions for this category comprised formation of MDTs including representatives from diverse disciplines, e.g., clinicians, nurses, laboratory personnel, and other healthcare professionals. The teams met on a regular basis to develop collaborative approaches, including development of standardized labeling policies (e.g., inclusion of specific patient identifiers on the specimen labels) and processes (e.g., printing labels at the same time of specimen collection, checking specimen label for any missing or incorrect information), according to the organizational needs that were acceptable and sustainable to staff. In the included studies, the interventions were targeted to the general population in 5 studies (17–20, 22), children and adults in 1 study (21), and newborns in 1 study (13). The total evidence was derived from varied types of healthcare settings, i.e., 3 studies (17–19) were conducted in multiple settings within a healthcare facility, such as inpatient, ambulatory, surgical services areas, emergency department, intensive care unit, and general care unit; 1 study (21) in an inpatient setting; 1 (22) in a surgical unit; 1 (20) in a dermatology unit; and 1 (13) in a pediatric department.

Four studies (17, 20–22) measured the effect of standardized specimen labeling policies developed as a result of a multidisciplinary approach that required inclusion of specific patient identifiers in specimen labeling (e.g., patient full legal name, date of birth, date and time of collection, initials of person collecting the specimen), and also the staff was educated about those standardized policies. In the other 3 studies (13, 18, 19), the MDT established processes including instructions for the staff to print specimen labels at the time of specimen labeling process and the use of 1 sheet for blood and other bodily fluid specimens from the same patient.

The overall combined data from the 7 studies (13, 17–22) found that the interventions developed as a result of improved communication and collaboration between the laboratory and clinical staff resulted in a substantial decrease in specimen labeling errors [median relative percent change in labeling errors: 75.86; interquartile interval (IQI): −84.77, −58.00] (Fig. 3). Results from 6 studies were statistically significant; however, we were unable to calculate the significance of results for 1 study because of the limited available evidence (19). The effect size strength was considered “substantial” from 4 studies (13, 17–22), “moderate” from 2 studies, and “minimal” for 1 study (Table 1). In addition, the results from the subanalyses performed for 4 studies (17, 20–22) showed a moderate decline in specimen labeling errors after the institution of the standardized specimen labeling policy, i.e., inclusion of unique patient identifiers on the specimen labeling (median relative percent decrease in specimen labeling errors: −72.45; IQI: −83.25, −46.50). The results from all these studies were statistically significant and consistently led to a reduction in specimen labeling errors (see Appendix E and Fig. 1 in the online Data Supplement).

Improved communication and collaboration between laboratory and healthcare professionals: formation of multidisciplinary teams.

Fig. 3.

Table 1.

Improved communication and collaboration between laboratory and healthcare professionals by formation of multidisciplinary team interventions: overall practices.

Studies (author/year published)	Study quality rating	Effect size rating
Zervakis, 2015	Good	Moderate
Seferian, 2014	Good	Substantial
Kim, 2013	Good	Minimal
Rees, 2012	Fair	Substantial
Shetterly, 2011	Fair	Moderate
O'Neil, 2009	Fair	Substantial
Foresberg, 1996	Fair	Substantial
Body of evidence ratings	1 Good/substantial
	1 Good/moderate
	1 Good/minimal
	1 Fair/moderate
	3 Fair/substantial
Consistency	Consistent
Overall strength	Moderate

Conclusions.

Applying the LMBP criteria, the overall strength of evidence from 7 studies (13, 17–22) is considered “sufficient” to recommend that the improved communication and collaboration between laboratory and healthcare professionals by forming MDTs is effective to decrease specimen identification errors (Table 1). Based on subgroup analysis (4 studies) (17, 20–22), there was sufficient evidence of “moderate” strength to recommend that the implementation of standardized policies, developed by MDTs that require specific patient identifiers on specimen labels, is effective in decreasing specimen labeling in healthcare settings (see Appendix E and Table 1 in the online Data Supplement).

Practice 2: education and training

Two studies (15, 23) were identified that evaluated the effectiveness of education and training interventions to decrease the specimen labeling errors. One study (23) was of good quality and 1 (15) was of fair quality. Results from 1 study (23) showed a substantial reduction in the number of patients with wrong identification resulting from labeling errors after introducing training and education sessions for medical, nursing, and laboratory staff as part of continuous medical education (relative percent change: −90.89; IQI: −97.86, −61.14). In another study (15), the specimen labeling errors decreased by 35% over 6 months after the implementation of in-service education of the nursing staff along with the provision of 24-h phlebotomy services (relative percent change: −35.77; IQI: −51.58, −14.80) (see Appendix E and Fig. 2 in the online Data Supplement). Findings from both studies were statistically significant.

Conclusions.

Both included studies showed a consistent decrease in specimen labeling errors. However, because of the small number of studies, according to the LMBP guidelines (6), evidence is considered insufficient to determine whether education and training interventions are effective to decrease specimen labeling errors (Table 2).

Table 2.

Body of evidence LMBP ratings for educational and training interventions.

Studies (author/year published)	Study quality rating	Effect size rating
Agarwal, 2012	Good	Substantial
Wagar, 2006	Fair	Minimal
Body of evidence ratings	1 Fair/moderate, 1 good
Consistency of results	Consistent
Overall strength	Insufficient

Practice 3: audit and feedback

Three studies (14, 15, 24) were included in the analyses to investigate the effectiveness of audit and feedback interventions. One study (24) was of good quality and 2 (14, 15) studies were of fair quality of execution. Two studies (14, 15) were conducted in the US and 1 study was conducted in Spain (24). The interventions in the included studies involved regular reporting or feedback of specimen mislabeling data from the laboratories to the management and the staff responsible for specimen collection and labeling. The combined results from 3 studies showed that after the intervention implementation there was a moderate decrease in labeling errors (median relative percent change in labeling errors: −58.0; IQI: 74.77, −30.08). Results from 2 studies (15, 24) were statistically significant, whereas 1 was not statistically significant (14) (see Appendix E and Fig. 3 in the online Data Supplement) (Fig. 3). The effect size from 2 studies (14, 15) was of moderate strength and from 1 study (24) was of minimal strength (Table 3).

Table 3.

Body of Evidence LMBP ratings for audit and feedback interventions.

Studies (author/year published)	Study quality rating	Effect size rating
Gonzalez, 2008	Good	Minimal
Quillen and Murphy, 2006	Fair	Moderate
Wagar, 2006	Fair	Moderate
Body of evidence ratings	2 Fair/moderate, 1 good/minimal
Consistency	Consistent
Overall strength	Insufficient

Conclusions.

Applying the LMBP criteria, the overall strength of evidence is considered insufficient because of the small number of included studies and weak effect size to draw any conclusions on the effectiveness of audit and feedback interventions at reducing errors related to specimen labeling in all types of clinical settings (Table 3).

Practice 4: implementation of new technology

No study qualified to be included in the analyses to evaluate the effectiveness this intervention category.

Discussion

Best practices recommendations

Based on the findings from the evidence presented, the interventions involving improved communication and collaboration between laboratory and healthcare professionals in the form of MDTs are recommended to decrease specimen identification errors (13, 17–22). In particular, the standardized policies and strategies developed by the MDT (e.g., use at least 2 identifiers to verify specimen and patient identity on the specimen label) were effective in reducing labeling errors (17, 20–22). The findings from this review showed that other evaluated practices, i.e., training and education of the specimen collection staff and audit and feedback of labeling errors, also led to a decrease in specimen labeling errors. However, because of the unavailability of sufficient data, no recommendations could be made in favor or against the effectiveness of those practices. In laboratory medicine, correct linking of the specimen to the patient from whom it was collected is identified as an essential and fundamental objective for improving patient health and safety, as it impacts on all aspects of patient care, including correct diagnosis and treatment. In 2013, the Joint Commission identified accurate specimen and patient identification as the first of the National Patient Safety Goals (25), which continues to be an accreditation requirement. The WHO considers accurate identification a priority area for improving patient safety and recommends continued staff education and training to ensure correct specimen and patient identification among all healthcare organizations (26). Various approaches have proved to be effective in decreasing the incidence of specimen labeling errors when implemented among different facilities within a healthcare system, such as education and training of the staff collecting patient specimens (24, 27, 28) and regular auditing of labeling errors (10, 29, 30). The findings from our review appear to be similar to a recent systematic review that addressed the errors related to the wrong blood in tube and investigated which interventions (single or multiple) were successful in reducing wrong-blood-in-tube errors. This review also found that interventions such as standardized labeling policies, staff education, weekly feedback, and electronic transfusion systems were likely to be more effective when implemented in combination vs when implemented individually (31).

Generally, healthcare organizations and facilities implement multiple practices at the same time and do not attempt to investigate the weighing of the effectiveness of individual practices in relation to the other. This approach makes it challenging for the stakeholders to investigate the effectiveness of individual practices that may be more or less effective according to their organizational needs. In this review, we were able to measure the effectiveness of 4 individual practices in reducing specimen labeling errors at the time of specimen collection.

Considerations for implementation

Factors such as limited knowledge and training of nonlaboratory staff (e.g., doctors and nurses) regarding specimen collection and labeling procedures compared with the laboratory staff (e.g., phlebotomists) may contribute to specimen labeling errors. Therefore, educational and training interventions targeted at nonlaboratory staff can play an important role in reducing specimen mislabeling (15, 21, 32). Other factors contributing to labeling errors are identified as lack of compliance by the staff to the specimen labeling standard operating procedures, often because of shortcuts and workarounds (33). Furthermore, turnover is a major issue with laboratory and nursing staff (34). To mitigate these barriers, annual competency checks of new and existing employees, incorporating training sessions into staff orientation, and routine professional development sessions may be more effective than 1-time training sessions. Finally, it is also suggested that patients' involvement can play an important role in improving their own identification (26). Therefore, interventions that encourage patient and family involvement to verify and confirm patient information should not be undervalued to reduce identification errors.

Economic evaluation

No eligible economic evaluations were identified for analysis of cost-effectiveness.

Potential problems

Some of the interventions to reduce specimen labeling errors may have unintended disadvantages. Interventions may result in increased cost of operations because of implementation and maintenance of staff education and training. There can be additional costs associated with acquiring technical solutions and staff training on the use of new technology. In addition, regular educational and training sessions may result in an increase in staff workload and time spent away from patients. Healthcare providers perceive that repeated verification of patient identity may compromise their relationship with patients.

Study limitations and future research needs

Because of the limited available evidence, no recommendations could be made for the effectiveness of 3 evaluated practices, i.e., interventions including education and training, audit and feedback, and implementation of new technology.

For this systematic review, the total body of evidence is driven from a before-and-after study design. Because of the uncontrolled nature of this design, there may have been unmeasured factors that changed between study periods that might account for or influence the study results. Future studies using stronger research designs (e.g., randomized control trials) would be valuable to clarify the effectiveness of interventions to reduce labeling errors at the time of specimen collection.

In this review, implementation of policies and strategies for specimen labeling, developed as a result of improved communication and collaboration between the laboratory, management, and clinical staff, remained effective for a longer period (up to 3 years). However, for other evaluated practices, i.e., staff education and audit and feedback interventions, the follow-up period to report the results varied from 6 months to 1 year (14, 15, 23, 24). Future research studies need to be conducted over a prolonged period to examine the sustainability of the effects of these interventions.

Significant discrepancies in error definitions, terminology, and error categorization strategies used in existing literature made it difficult to compare these studies. For example, the terms “laboratory identification error,” “specimen identification error,” “patient identification error,” “identification error,” “mislabeled specimen,” and “unlabeled specimen” have been used interchangeably for specimen labeling. Furthermore, the use of a variety of metrics and measures for result reporting, such as percent change, change in error rate, and error counts, made it challenging and difficult for synthesizing and summarizing findings from the total evidence. For future research, it is warranted to use standardize term(s), definition(s), and error detection methods and measures for result reporting in establishing future quality control studies to allow better analysis and better result interpretation.

We found a considerable amount of published and unpublished literature on this topic, but only a few studies qualified for inclusion in the analyses (Fig. 2). In the majority of studies, the interventions to reduce the labeling errors were implemented as a combination of multiple practices at the same time, e.g., staff training and education and development of labeling policies and processes. It was difficult to distinguish which specific component was attributable to the intervention effectiveness (e.g., do policy components or education components contribute more to intervention effectiveness; what are the central “active ingredients” in complex interventions?). Providing more descriptive information on how different “best practices” were implemented as an intervention to reduce errors might help organizations replicate successes. In addition, many published studies and unpublished data that we retrieved from the laboratories were mostly “trend data” that did not qualify for inclusion in the final analyses. Because of the lack of comparison data (e.g., preintervention baseline data), it was difficult to conduct intervention effectiveness analyses. Furthermore, some studies were missing information on other vital aspects, such as intervention description and the outcomes of interest for this review. Although clinical laboratories routinely perform quality improvement projects at an institutional level, it is hoped to that future quality improvement studies are designed in such a way that the data driven from these studies can be used to demonstrate intervention effectiveness.

Finally, research showed that the incidence of specimen labeling errors varies according to the type of healthcare setting. For example, the risk of these events is higher in emergency departments because of rapid patient turnover, more interruptions to the medical staff (33), and patients may arrive unexpectedly and be unconscious or with no identification, as compared with an in-patient setting where the patients are admitted in advance and may stay for days for their treatment (34). The findings from this review may not be generalizable across different types of healthcare settings because of limited data availability and will require further investigation to determine whether the recommended practices are equally effective in all types of settings (e.g., emergency departments, pediatrics).

In summary, humans tend to cause errors. Although multiple corrective measures have been developed that focus on human factor improvement, specimen labeling errors continue to happen. Because of the potential adverse consequences on patient safety associated with mislabeled laboratory specimens, every specimen labeling error should be treated seriously. Based on the findings from this review, multifaceted and multidisciplinary improvement approaches, such as improved communication and collaboration between laboratory and healthcare professionals to develop and implement stringent and standardized specimen labeling policies and procedures, can improve patient safety by significantly reducing the incidence of specimen labeling errors in healthcare settings.

7 Nonstandard abbreviations

 
• LMBP

  Laboratory Medicine Best Practices Initiative^TM

 
• MDT

  multidisciplinary team

 
• IQI

  interquartile interval.

Author Contributions:  All authors confirmed they have contributed to the intellectual content of this paper and have met the following 4 requirements: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; (c) final approval of the published article; and (d) agreement to be accountable for all aspects of the article thus ensuring that questions related to the accuracy or integrity of any part of the article are appropriately investigated and resolved.

Authors' Disclosures or Potential Conflicts of Interest:  Upon manuscript submission, all authors completed the author disclosure form.

Employment or Leadership: None declared.

Consultant or Advisory Role: None declared.

Stock Ownership: None declared. Honoraria: None declared.

Research Funding: This work is funded by the CDC under Contract No. 200-2013-F-57569, Delivery Order, “Laboratory Medicine Preparedness: Best Practices.”

Expert Testimony: None declared.

Patents: None declared.

Role of Sponsor: The funding organization played no role in the design of study, choice of enrolled patients, review and interpretation of data, or preparation or approval of manuscript.

Acknowledgments

The authors thank the LMBP Specimen labeling/ patient misidentification Expert Panel, LMBP Workgroup members, and Joanna Taliano, Reference Librarian (CDC).

Author notes

Disclaimer: The findings and conclusions of this article are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention.

Names and affiliations of the Laboratory Medicine Best Practices Workgroup (LMBP Workgroup) can be found at http://wwwn.cdc.gov/futurelabmedicine/default.aspx.