Specimen Labeling Errors: A Retrospective Study

Citation

Martin, H., Metcalfe, S. & Whichello, R. (June 2015). Specimen labeling errors: A retrospective study. Online Journal of Nursing Informatics (OJNI), 19 (2), Available at http://www.himss.org/ojni

Abstract

Aim: Specimen labeling errors are a serious problem in healthcare facilities. The effects from specimen labeling errors can be devastating and could lead to misguided treatment or death. This retrospective study analyzes the effects of two interventions - one-on-one specimen collection education and removal of an electronic option that allowed registered nurses to bypass the barcode safety function.

Methods: The average number of specimens collected by registered nurses and the number of specimen labeling errors by registered nurses in the two adult intensive-care units in the six months before and the six months after the interventions were obtained via two instruments at the researched facility.

Results: The total error rate before the interventions was 1.31 per 1,000 specimens or 0.131%. The total error rate after the interventions was 0.139 per 1,000 specimens or 0.014%. Together, the two interventions, one-on-one education and removal of an electronic option that allowed registered nurses to bypass the barcode safety function, resulted in a 90% error reduction post- implementation.

Discussion: Several limitations were noted with the setting, sample and data collection, but overall, the study proved that reducing specimen labeling errors is possible. Through one-on-one education and removal of an electronic option that allowed registered nurses to bypass the barcode safety function, the researched facility led to a significant reduction in specimen labeling errors.

Background and Rationale for Study

The Institute of Medicine (IOM) report To Err is Human noted that laboratory medicine was a source of concern for adverse events and patient safety (Kohn, Corrigan, & Donaldson, 2000). The Joint Commission (TJC) also acknowledged specimen identification errors and released two National Patient Safety Goals in 2014 to address the issue. The first goal called for healthcare providers to use two patient-specific identifiers, such as name and date of birth, to ensure each patient received the correct medication or treatment. The second goal was to make sure the correct patient gets the correct blood when they get a transfusion (The Joint Commission, 2014).

Patient specimen and laboratory testing identification errors comprise the majority of laboratory errors. The reported error rates vary due to incidents of underreported or undetected errors. However, each error should be taken seriously due to the potential severity of the adverse effects a patient could experience if a specimen labeling error occurred (Snyder, et al., 2012). Laboratory tests help direct and determine how healthcare providers are going to treat and diagnose; therefore, labeling a specimen correctly is crucial to providing safe care and essential to ensuring the right patient receives appropriate treatment (Strobel, 2013). Even though identification errors related to specimen collection have been deemed preventable, this zero deficit mentality may be unachievable with the amount of human interaction that still remains in the collection process (Plebani, Sciacovelli, Aita, Padoan, & Chiozza, 2013). Due to the potentially catastrophic consequences of mislabeled specimens, laboratories should aim for zero deficits, but consider human imperfection in any policy or intervention. Due to the ineffective and inefficient care that results from a mislabeled specimen, it should be the expectation to aim for zero deficits while remembering that human imperfection still exists (Snyder, et al., 2012).

Increases in specimen labeling errors were noticed at the researched institution, an 800- bed, Level 2 trauma center in the southeastern United States. Three types of specimen labeling errors were identified and categorized: patient-specific labels in the bag not attached to the specimen, unlabeled specimens with no labels in the bag and mislabeled specimens with the wrong patient identification on the specimen.

The first and second error types are discovered once the specimen reaches the laboratory and the specimen management technicians check the specimen into the laboratory.

Specimens labeled with the wrong patient identification could be identified by a nurse who realizes that the collection was on the wrong patient; a specimen management technician who notices the specimens sent to the lab do not match orders for that patient, and/or the quality controls on the laboratory machines identifying differences from past labs on that patient. The most alarming possibility is that the specimen may not be identified as mislabeled and go undetected.

By tracking errors closely over the past several years, two common areas of process failure were recognized within the bedside specimen collection process at the researched institution, in addition to other facilities. The first process failure identified is the human factor of ensuring the collector follows the designed process (Lippi, et al., 2009). The second process failure is an option within the electronic system that allows the collector to completely bypass the barcode scanning function of the specimen label.

After the research institution identified a lack of process consistency by the nurses collecting specimens, nurses were required to re-train, one-on-one, in specimen collection. In January 2013, every nurse in adult intensive-care unit A (ICU A) was retrained, one-on-one, by a select group of educators at the study institution, who received additional training on the specimen collection and labeling process. The nurses in adult intensive-care unit B (ICU B) were never re-trained with the one-on-one education. However, in March 2013, a preference within the specimen collection software application that allowed bypassing of the barcode safety function in the electronic collection process was changed. This forced the nurse to scan the patient-specific label, produced by the bedside printers, to show the specimen as signed and collected. This paper will discuss the impact of the intervention(s) on specimen labeling errors in the two adult intensive-care units.

Literature Review

A review of the literature found that specimen-labeling errors are not isolated to one facility, but are common in clinical laboratories (Green, 2013; Romero, Cobos, Gomez, & Munoz, 2012; Snyder S., et al, 2012). Several accrediting and medical governing bodies have identified specimen labeling errors as a problem, such as the Institute of Medicine that released the report To Err is Human that addressed errors in laboratory medicine (Kohn, Corrigan, & Donaldson, 2000), and The Joint Commission (TJC), who released several National Patient Safety Goals about performing positive patient identification when completing actions such as medication administration and collecting specimens (TJC, 2014).

Specimen labeling errors are serious and can be devastating to a patient's treatment plan or life. The errors can delay, impede and/or misdirect treatment options (deRin, 2010) due to the actuality that 60 to 70 per cent of treatment options are determined by laboratory results (Green, 2013). The errors are damaging to the healthcare industry, resulting in an increased cost to the facility and the laboratory department, increased length of stay, decreased confidence in the healthcare system, and damaging to the reputation of the facility.

When reviewing deeper into the literature about specimen collection, the laboratory test process is divided into three phases: pre-analytical, analytical, and post-analytical. The pre-analytical phase contains the steps from when the healthcare provider enters or places the order until the specimen reaches the laboratory. The analytical phase is the actual analysis or testing of the specimen and the last phase, post-analytical, consists of reporting and interpretation of results (Green, 2013). A literature review of the laboratory test process by Green (2013) revealed that the majority of laboratory errors occur in the pre-analytical phase, which is the phase involved in this retrospective study.

According to multiple studies, errors in the pre-analytical phase are more prevalent than the other two phases (Bhat, Tiwari, Chavan, & Kelkar, 2012; Green, 2013; Kaushik & Green, 2014). A review by Green (2013) found that pre-analytical errors may account for up to 75 per cent of the total laboratory errors. The pre-analytical phase is complex, possibly making it more prone to error. The phase is also fragmented; the first part of the phase is performed outside of the laboratory while the second part is performed inside the laboratory. Another variable in the pre-analytical phase is the mixture of non-laboratory staff and/or laboratory staff that handle the specimen between time of order and time of delivery to the laboratory (Green, 2013). It is important to remember that within the pre-analytical phase there are multiple steps where human unreliability must be considered, some of which are: ensuring the healthcare provider ordered the correct test on the correct patient, ensuring the collector obtains the correct specimen from the correct patient under the correct conditions, and then ensuring the collector correctly identifies and labels the specimen before sending it to the laboratory to be processed. A lapse in any part of the specimen collection process can cause an error, but the steps that involve human interaction are more at risk for error (Snyder, et al., 2012).

The review by Green (2013) found incorrect patient identification to be one of four frequent causes of pre-analytical errors. An error in patient identification or the blood component, according to Green, caused 40 to 50 per cent of transfusion morbidities. This type of error, patient identification, is particularly troubling because of the potential for misdiagnosis, additional laboratory testing and/or treating a patient for the wrong medical condition (Green, 2013; Snyder S., et al., 2012).

A study by Dunn and Moga (2010) examined 227 root-cause analysis reports from the Veterans Health Administration. Of the 227 reports, 182 of those were patient misidentification errors that occurred during one of the three specimen collection phases. Of the 182 misidentification reports, 132 events were in the pre-analytical phase. Wrong wristband applied to the patient, specimen mislabeling during collection and failure of two patient identifiers used were a few of the reasons for errors.

Kaushik and Green (2014) further dissected the specimen collection process and broke down the pre-analytical phase, identified common error types, identified common reasons the error occurred, as well as best practices to help reduce errors in this phase. The parts within the pre-analytical phase are: before, during and after specimen collection. Patient identification and specimen labeling errors were two of the identified error types in the before and after specimen collection phases of the pre-analytical phase. The most common causes of these error types were missing patient identifiers and labeling the specimen away from the bedside. Best practices identified to help prevent these errors were: barcoded wristbands, use of at least two patient identifiers, using biometric information and labeling the specimen container immediately after specimen collection.

Review of the literature found that specimen labeling errors are prevalent and known in clinical laboratories. Specimen labeling errors have been identified as dangerous and affect the quality of care provided to patients; therefore, identification standards and goals have been put in place to help address the issue. The literature also identified that specimen errors occur most often in the pre-analytical phase (Kaushik & Green, 2014). This phase contains three steps: before, during, and after specimen collection. This phase is also unique in that it does not take place solely within the laboratory and also involves laboratory and non-laboratory personnel.

Due to the well-known fact that in any process, including specimen labeling, the presence of a human element increases the risk of error, extra safety steps must be implemented. Therefore, barcoding of specimens has been implemented and deemed the best practice for specimen labeling as it helps reduce specimen labeling errors. Unfortunately, this safety feature has not totally eliminated specimen labeling errors (Snyder, et al., 2012). Barcode scanners are used to confirm patient identity, through barcoded wristbands, against electronically entered orders. The use of stationary printers at the patient bedside produce patient-specific barcode specimen labels through interfaces with a handheld device, the electronic health record (EHR) and computerized physician order entry (CPOE). Patient-specific labels specify the laboratory orders needed, the correct container type and special handling instructions. Once the specimen is collected and labeled the handheld device is used to scan the patient-specific barcode specimen label to confirm it matches the patient identity and the patient's orders. The electronic barcode scanning process is completed by electronically signing the specimen, showing it as collected in the electronic medical record (Brown, Smith, & Sherfy, 2011).

Nurses are often involved in specimen collections, however, the bulk of the literature around specimen labeling errors does not identify who collected the specimen, laboratory staff, nursing staff or others. One nursing article noted that 37 per cent of nurses who responded to their survey said that prevention of specimen management errors were a high priority for action (Steelman & Graling, 2013). The pre-analytical phase is the only phase that nursing would be directly involved in, yet the literature provided limited information on nursing involvement or the prevalence of errors committed by nursing staff within this phase.

Methodology

Design

This project is a retrospective study that compares the total number of nurse collected specimen labeling errors in each adult intensive-care unit before and after the one-on-one education and/or the removal of the preference that allowed the collector to bypass the barcode safety function. The purpose of comparing the number of specimen labeling errors before and after the intervention(s) was to help identify if the intervention(s) helped to reduce the amount of specimen labeling errors in each adult intensive care unit. The results of this study help determine which, if any, intervention or combination of interventions was most successful and help nursing administration decide which intervention is the most successful method of lowering specimen labeling errors and should be adopted.

Setting

Retrospective specimen labeling error data from two adult intensive-care units within an 800-bed Level 2 trauma center in the southeast before and after the identified intervention(s) were studied. Specimen labeling errors from July 2012 through December 2012 were obtained and analyzed as the pre-intervention data. Specimen labeling errors from April 2013 through September 2013 were obtained and analyzed as the post-intervention data. Adult intensive-care unit A has 12 patient rooms that serve a variety of adult medical and surgical intensive care patients. On average, intensive-care unit A has eight registered nurses per shift with an average of two certified nursing assistants per shift. Adult intensive care unit B has 10 patient rooms that serve patients post cardiac and thoracic surgeries. On average, intensive care unit B has eight nurses and two certified nursing assistants per shift. The two interventions occurred mid-January and mid-March, therefore, specimens from the months of January 2013 through March 2013 were not considered for this study.

Sample

The retrospective study sample is specimen labeling errors on specimens that were collected by registered nurses in two adult intensive care units. The specimens collected by nurses were not limited and varied from blood, urine, sputum stool samples or other types of specimens. The specimen labeling errors were discovered in various ways by the laboratory staff. Once discovered, they were reported through a facility-wide occurrence reporting electronic database and then transcribed into a database specific to specimen labeling errors that is maintained by the laboratory quality coordinator. The specimen labeling error may be transcribed incorrectly into either database or the specimen labeling error may never be identified by the nurse collecting the specimen or the laboratory staff.

Protection of Human Subjects

The requested data, specimen labeling errors from July 2012 through December 2012 and April 2013 through September 2013, was obtained and analyzed. No patient or nurse identity was needed for this study, only whether the collection was performed by a registered nurse. The number of specimens performed in the two adult intensive care units from July 2012 through December 2012 and April 2013 through September 2013 was also requested to calculate the average number of specimens collected in those units by registered nurses. All data was de-identified by the laboratory quality coordinator, and data was maintained on a password protected laptop computer that was only accessed by this researcher for the purposes of this study.

After a presentation to the Nursing Research Council about the proposed retrospective study at the study institution, approval to continue with the study and apply for Internal Review Board approval was granted. Expedited review forms were completed and submitted to the Internal Review Board at the study institution first, then to the University. After extensive review, Internal Review Board exemption was granted at the study institution on October 13, 2014, then, Internal Review Board exemption was submitted at the University and granted on November 24, 2014.

Instruments

The first instrument used for data collection was an electronic reporting system that integrates with the electronic medical record. This reporting system was used to pull the total number of specimens collected in each adult intensive care unit for the six months before and six months after the interventions to find the average number of specimens collected by nurses. This report is titled Positive Patient Identification Dashboard Metric which pulls information on every specimen collected in each adult intensive care unit used for this study.

The second instrument is an internal database maintained by the laboratory quality coordinator. This instrument contains details from all of the specimen labeling errors at the study institution since 2010. The database contains the following: event report number, date and time of error, facility unit where collection occurred, collector name, patient name affected by the error, patient medical record number, details of the error, and who was notified of the error. Only the year of collection, month of collection, collection unit and collector position was obtained for this study.

Data Collection/Field Procedures

Data from the first instrument, the electronic reporting system that integrates with the electronic medical record, was used by the laboratory quality coordinator to obtain the total number of specimens collected in each adult intensive care unit used for this study, for the months of July 2012 through December 2012 and April 2013 through September 2013. Within the spreadsheet sent by the laboratory quality coordinator, the researcher sorted by collector type, since only specimens collected by nurses were needed for this study. Each registered nurse is under a specified position in the electronic charting system, depending on where they work. Only positions that had registered nurses were chosen, therefore, all other positions were eliminated. Specimens collected by other individuals data was discarded. De-identified data was then used to calculate the average number of specimens collected by nurses in the two adult intensive-care units for the date ranges identified for this study.

The second instrument, the internal database, was used to obtain the number of specimen labeling errors caused by nurses in each of the two adult intensive-care units identified for this study. The database was sorted by the unit where the specimen was collected, only the errors for the two adult intensive-care units was needed for the study. Only the year of collection, month of collection, collection unit and collector position was obtained from this database for this study. This database contains the name and position of the collector with the error, thus identities had to be removed for this study. Once the de-identified data was obtained the researcher only looked at the errors committed by nurses: the rest of the data were discarded.

Data Analysis

After being granted Internal Review Board exemption from both the study institution and the university, de-identified data were obtained from the laboratory quality coordinator. The number of specimens collected by nurses per month was analyzed, averaged and compared between the two adult intensive care units. This helped to determine if the average number of specimens are similar in each adult intensive care unit and also allowed for the rate of error to be calculated per unit. Then, the number of specimen labeling errors in each adult intensive care unit was analyzed before and after the interventions. Once obtained, data was analyzed to see which intervention(s), if either, had an impact on the number of specimen labeling errors. A Fisher's exact test was also used to look for statistical significance.

Results

De-identified data were obtained, via the instruments described in previous sections, for the two adult intensive care units from July 2012 through December 2012, before the two interventions occurred. A total of 11 specimen labeling errors occurred in the two adult intensive-care units between July 2012 and December 2012. One of the events was discarded from the total due to the collector position not being available in the database. Therefore, the total number of specimen labeling errors by registered nurses, used for this study, before the two interventions was 10 (see table 1).

View Table 1

In further breakdown, seven of the specimen labeling events occurred in adult intensive care unit A: two errors in July 2012, one error in August 2012, three errors in October 2012 and one in December 2012. Three of the 10 errors occurred in adult ICU B (see table 1). Two of those errors occurred in July 2012 and one error occurred in November 2012 (see table 2).

View Table 2

A total of 4,416 specimens were collected by registered nurses in adult ICU A in the six months prior to the interventions, July 2012 through December 2012. Having seven errors before the interventions, the error rate for adult ICU A was 1.585 per 1,000 specimens or 0.158 per cent. A total of 3,194 specimens were collected by registered nurses in adult ICU B in the six months prior to the intervention, July 2012 through December 2012. Adult ICU B had three errors before the interventions, giving them an error rate of 0.939 per 1,000 specimens or 0.094 per cent. Together the total equaled 7,610 specimens collected in the six months prior to the interventions for the two adult intensive-care units. The total error rate in the six months before the interventions was 1.31 per 1,000 specimens or 0.131 per cent.

Data were obtained via the instruments described in previous sections, for the two adult intensive care units from April 2013 through September 2013, after the one-on-one education in adult ICU A and the removal of the electronic option in both units occurred. One error between the two adult intensive-care units occurred in the six months studied after the intervention(s) were implemented. This error happened in adult ICU A in June 2013 (see table 2).

A total of 4,076 specimens were collected by registered nurses in adult ICU A in the six months after the interventions, April 2013 through September 2013. Only one error occurred after the interventions, in adult ICU A, giving them an error rate of 0.245 per 1,000 specimens or 0.025 per cent. A total of 3,122 specimens were collected by registered nurses in adult ICU B in the six months after the intervention, April 2013 through September 2013. Adult ICU B had zero errors after the intervention. Together the total equaled 7,198 specimens collected in the six months after the interventions for the two adult intensive care units. The total error rate in the six months after the interventions was 0.139 per 1,000 specimens or 0.014 per cent.

Major Findings

Both adult intensive care units collected a similar amount of specimens in the six months before and the six months after the interventions. On average adult ICU A collected about 200 more specimens a month than adult ICU B. In total, ten specimen labeling errors occurred out of 7,610 specimens before the interventions in the two adult intensive care units, a rate of 1.31 per 1,000 specimens. A total of one specimen labeling error occurred, after the one-on-one education in adult ICU A and the removal of the electronic option that allowed bypassing of the barcode safety function in both adult intensive care units, equaling a rate of 0.139 per 1,000 specimens.

Adult ICU A went from seven errors before the two interventions, one-on-one education plus removal of the electronic option that allowed nurses to bypass the barcode safety function, to one error after the interventions, an 85.7% decrease. Adult ICU B went from three errors before the intervention to zero errors after removal of the electronic option that allowed nurses to bypass the barcode safety function alone, a 100% decrease. A Fisher's Exact test was completed comparing pre and post intervention errors, summing across adult ICU A and adult ICU B. There were 10 errors out of 7,610 specimens before the interventions, a 0.13 per cent error rate. There was one error out of 7,198 specimens after the interventions, a 0.01 per cent error rate. The Fisher's exact test p-value was 0.01, indicating statistical significance in the difference of total errors before and after the interventions. The total results of the two adult intensive care units combined revealed that the two interventions together led to a 90 per cent decrease in errors.

Overall, after reviewing the specimen labeling errors before and after the intervention(s), it was noted that the number of specimen labeling errors by registered nurses dropped from 10 errors in the six months before the intervention(s) to one error in the six months after the intervention(s). This marks a 90 per cent decrease in specimen labeling errors after the one-on-one education and removal of the electronic option to bypass barcoding.

Discussion

Findings

The findings from this study confirms that specimen labeling errors within healthcare facilities is an issue that threatens patient safety and quality of care. Although the error rates of 1.31 per 1,000 specimens before the interventions and 0.139 per 1,000 specimens after the interventions is small, these errors could have devastating effects on patient care. Human fallibility is a major factor that needs to be diminished as much as possible or, if possible, eliminated altogether. Through one-on-one education and eliminating an option of bypassing the electronic barcoding system, the specimen labeling process can be improved and lead to a significant reduction of errors.

Implications for Practice

Facilities that experience specimen labeling errors should first assess the nursing population on their knowledge and comfort of the collection process and their knowledge of the downstream effects on specimen labeling errors. If educational deficiencies are found, an education plan that stresses the importance of correct labeling, as well as the steps involved in the specimen collection process should be developed and implemented. Healthcare facilities should also meticulously examine the electronic process to ensure there are no workarounds that easily allow nurses to bypass the electronic barcoding system.

Limitations

Several limitations are identified within the setting, sample and data collection process. The first limitation, related to the setting, is that the study takes place at one facility and only within two of the adult intensive care units at that facility. Within the setting of the two adult intensive-care units, patient acuity, census levels and staffing ratios were not studied, but may have an impact on the number of specimen labeling errors for the months of data collection.

Several limitations exist within the sample. Only specimens collected by nurses and labeling errors by nurses in the two adult intensive-care units were accepted for this retrospective study, which limited the amount of data in the study. The study did not analyze if the errors were by the same registered nurse or the amount of experience the registered nurse had with specimen collection at this facility. Also, the study did not analyze the type of specimen labeling error.

Two main limitations are noted in the collection process. Due to the possibility of human fallibility during data entry to the internal laboratory database, data collection points have the potential to be a limitation. Human fallibility of the laboratory quality coordinator during data collection is also a possibility and therefore also a limitation.

Future Research

Studies that examine only specimen labeling errors by nurses is very limited. Most studies include phlebotomy collections as well as collections performed by nurses. Further research related to specimen labeling errors by registered nurses is needed. A larger and longer study of specimen labeling errors by registered nurses is needed to further verify the issue as well as examine potential causes and potential solutions.

Although total elimination of specimen labeling errors may be unachievable due to human fallibility in the specimen collection process, healthcare facilities should always aim for zero errors in processes that pose a potential risk to patient safety. This study proves that two interventions, one-on-one education and meticulous assessment of the collection process to identify and eliminate an electronic option that allows bypassing of the barcode safety function, can help get a healthcare facility closer to the goal of zero specimen labeling errors.

Conclusion

Specimen labeling errors are a serious threat to the safety and quality of care patients receive in healthcare facilities. Educating registered nurses on the potential effects of specimen labeling errors as well as critiquing electronic processes to ensure no bypass methods allow nurses to skip barcoding are both interventions that this study shows are effective. By implementing these two interventions healthcare facilities can ensure nurses are informed and that the best practice of specimen barcoding is being followed which will hopefully reduce specimen labeling occurrences in other facilities.

References

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Author Bios

Heather Martin, MS(N), RN

Heather Martin MS(N), RN is currently employed at Mission Hospital, part of the Mission Health system, as a Registered Nurse in the Staffing Pool. For the past two and a half years, she has focused on barcode medication administration and electronic positive patient identification for specimen collection, as well as other various safety and quality projects. She also serves on the Nursing Quality Council, Nursing Practice Council and has served as the co-chair of the Nursing Informatics Council since 2011.

Sharon Elizabeth Metcalfe, EdD, MSN, RN

Sharon Elizabeth Metcalfe is currently an Associate Professor of Nursing at Western Carolina University in Asheville, North Carolina. For over 8 years, Sharon has been an Associate Professor of Nursing and has had previous academic appointments as a Dean of Nursing for a private and community college. Additionally, she has been an educational grants researcher and has focused on grant funding for partnerships with colleges and medical facilities. Sharon is currently serving on the Board of the North Carolina Nursing Association Foundation from 2010 to the present. Sharon has focused her nursing research agenda on global leadership development for nurses and on mentoring transformational nurse leaders to meet the needs of the future. She additionally has been serving as the Program Director of the NN-CAT Program (Nursing Network-Careers and Technology Program) which is a national program that provides scholarships, stipends, and personal mentors to underrepresented ethnic minority students for guidance for applying to the baccalaureate of nursing education program at Western Carolina University, USA.

Ramona Craft Whichello MN, RN, NEA-BC

Ramona Craft Whichello MN, RN, NEA-BC is currently employed at Western Carolina University as an Associate Professor. She serves as the Director for the RN to BSN, Master of Science ­ Nursing Leadership, and Master of Science ­ Nurse Educator programs. Ms. Whichello is currently enrolled in the Doctor of Nursing Practice program at East Tennessee State University with a focus on Executive Leadership.

Acknowledgement: The primary author would like to extend a special thank you to Kristy Stewart, MS(N), RN, ONC, Sheri Denslow and Vallire Hooper PhD, RN, CPAN, FAAN. The primary author truly appreciated all the guidance and support you both provided.