Transfusion Error Surveillance System (TESS): 2012-2016 Report

Foreword

The Centre for Communicable Diseases and Infection Control (CCDIC) of the Public Health Agency of Canada (PHAC) is pleased to present the Transfusion Error Surveillance System (TESS), 2012-2016 Report. This report presents transfusion error surveillance data submitted between 2012 and 2016 by participating Canadian sentinel hospitals.

The TESS is a voluntary surveillance system established by PHAC to capture non-nominal data on errors occurring at any point in the transfusion chain, including those detected before or after the transfusion of blood components and fractionated plasma products to the patient and those that may or may not have resulted in adverse transfusion reactions. The overall objective is to identify potential areas for improvement in the transfusion chain and ultimately, improve transfusion processes and patient safety in Canada.

CCDIC, in partnership with participating provinces and territories, is responsible for the collection, management, and analysis of data, and the production of reports to support evidence-based public health decisions.

Acknowledgment

The development of the Transfusion Error Surveillance System (TESS) would not have been possible without the collaborative support and continued commitment of the many transfusion safety officers, medical laboratory technologists, and other healthcare professionals in hospitals and Blood Transfusion Services. Their dedication to reducing errors and increasing patient safety has led to the collection and analysis of 2012-2016 TESS data.

Abbreviations

AHTR
Acute Haemolytic Transfusion Reaction
DC
Distributor Codes
DHTR
Delayed Haemolytic Transfusion Reaction
FNHTR
Febrile Non-Haemolytic Transfusion Reaction
IM
Inventory Management
IVIG
Intravenous Immunoglobulin
MS
Miscellaneous
PC
Product Check-in
PR
Product Request
PS
Product Selection
RP
Request for Pick-up
SC
Sample Collection
SH
Sample Handling
SOP
Standard Operating Procedure
SR
Sample Receipt
ST
Sample Testing
TACO
Transfusion Associated Circulatory Overload
TESS
Transfusion Error Surveillance System
UI
Unit Issue
UM
Unit Manipulation
US
Unit Storage
UT
Unit Transfusion

Executive Summary

The Transfusion Error Surveillance System (TESS) was initiated by the Public Health Agency of Canada (PHAC) in 2005, in conjunction with 11 hospitals, to monitor errors occurring in the transfusion chain. Currently, 15 hospitals in 4 Canadian provinces and territories (P/Ts) participate in the surveillance as sentinel sites and report all errors to PHAC on a quarterly basis.

Overall, a total number of 50,925 errors were reported from 2012 to 2016. The most frequent errors reported were related to sample collection (SC) (n=17,485; 34.3%), unit transfusion (UT) (n=7,040; 13.8%), and sample handling (SH) (n=5,721; 11.2%). The majority (n=48,256; 94.8%) of all errors did not reach the patient (near-miss events).

Of the 2,669 errors that reached the patient (actual events), approximately 97.5% (n=2,602) caused no harm at the time of reporting. Two point five percent (n=67) caused some harm to the patient (recipient), which were errors related to product request (PR) (n=49), UT (n=15), and product selection (PS) (n=2), and sample testing (ST, n=1). These four types of errors were linked to 45 cases of transfusion-associated circulatory overload (TACO), 11 cases of febrile non-haemolytic reactions, 3 cases of minor allergic reactions, 2 cases of acute haemolytic reaction, 2 cases of delayed serologic reaction, 1 cases of incorrect dose administered, 1 case of IVIG headache, and 1 case of ABO incompatibility. Of the 2,669 errors that reached the patient, 29.7% (n=791) were related to the request for blood product pick-up (RP), 20.6% (n=548) to PR, and 19.2% (n=513) to UT. From 2012 to 2016, there was a decreasing trend in the annual rates of SC, SH, and ST errors that reached the patient.

The TESS data demonstrate that blood transfusions are safe in participating Canadian hospitals, as only 0.1% (n=67) of all errors reported to the TESS resulted in harm. No cases resulted in death. The TESS data also highlight potential areas for improvement. For example, most errors that escaped detection occurred during PR and UT processes. Thus, more system and process innovations, knowledge translations, attention, and awareness are required during these two processes to improve the safe delivery of blood to Canadians.

Data collected through the TESS can help facilitate the identification and evaluation of preventive measures designed to improve the transfusion process and patient safety.

Introduction

Blood transfusion is a very safe and effective treatment when performed according to hospital policies and procedures. Transfusion safety depends on a complex multistep process, beginning with the decision to order an appropriate blood component or fractionated plasma product. The process is then followed by sample collection, labeling, transportation, handling, storing, pre-transfusion testing, issuing and the transfusion of blood components and fractionated plasma products to the patient. Due to robust precautionary measures, the risk of an adverse reaction following transfusion is very low in developed countries, including Canada. However, errors may occur at each step of the multistep transfusion process and these errors can cause administrative delays in the transfusion procedure, product wastage, sample re-collection, unnecessary transfusions, adverse transfusion reactions, and deathFootnote 1. These errors have the potential to negatively impact patient safety and to increase costs of the healthcare system. Therefore, mitigating the risk of errors is a fundamental step in improving patient safety.

In 2005, the Transfusion Error Surveillance System (TESS) was initiated by the Public Health Agency of Canada (PHAC) as a sentinel pilot surveillance system with 11 hospitalsFootnote 2Footnote 3. The objective was to monitor the incidence and trends of errors that can occur at any step in the transfusion chain. Currently, 15 hospitals across four provinces (Québec, British Columbia, Ontario, and Nova Scotia) participate in the TESS. The TESS data serve as a complement to data collected through the Transfusion Transmitted Injuries Surveillance System (TTISS), which monitors the incidence of adverse reactions following blood transfusion in CanadaFootnote 4. In addition, numerous other non-sentinel hospitals submit data to TESS for their own use of the data; their non-sentinel data are not reported here.

Participating hospitals provide anonymous data on a quarterly basis using a secure electronic web-based server maintained by the PHAC. In addition to data on errors, participating hospitals provide the number of blood components or fractionated plasma products received, requested, prepared, and issued, and the number of samples received and tests performed, which are used as denominator for calculating error rates. This allows for comparing error rates between sites and hospital locations/wards as well as across similar hospital sizes or transfusion practices.

The TESS allows hospitals to identify the points along the transfusion chain where errors most commonly occur, including those that are detected prior to the blood transfusion. Corrective action can be taken to minimize errors in those areas and prevent adverse reactions. Following the implementation of intervention measures, future TESS data may be used to evaluate the effectiveness of such measures. Findings may also provide comparable benchmarks for other hospitals in Canada and for international comparisons.

Methods

Details on the TESS’s methods, including definitions, data collection, classification, categorization data management, data quality control, and analysis of errors, have already been described in previous reportsFootnote 2Footnote 3.

Definition of error:

Errors reported through the TESS are defined as unexpected and unplanned deviations from standard operating procedures or applicable laws and regulations, usually attributable to a human or system problem that could:

Errors are classified as near-miss events or actual events:

Error type and error coding:

Errors captured through TESS are also categorized according to their occurrence point in the transfusion chain. Figure 1 illustrates this multistep transfusion process where each type of error can occur. For instance, all errors described with distributor codes (DC) are errors that occur at the distributor/supplier level of blood components or fractionated plasma products, whereas unit transfusion (UT) errors occur at the time of transfusion in clinical settings. There are errors that occur only in the transfusion service or clinical settings (e.g., medical/surgical wards, operating rooms, emergency rooms, out-patient clinics and procedures [Out-patient clinics], intensive care units, and obstetrics). The transfusion service errors were divided into nine process types according to the point in the transfusion process, and clinical setting errors were divided into five types. Table 1 provides a summary of blood suppliers, transfusion services, and clinical settings.

A set of predefined standardized alpha-numeric codes that are used to classify each type of errors are described in detail in the TESS User’s manual. Table 2 presents general error codes where the letters in the codes indicate the type of error. Errors are further sub-categorized into numeric values to differentiate specific errors within each type. A complete listing of the error codes is provided in Appendix 1.

To ensure the consistency of error coding across participating sites in the TESS, PHAC organises monthly error coding meetings to discuss complex cases for which error coding may be difficult. Baseline training for error coding is also offered to new sites prior to participating in the TESS.

Figure 1. Multistep transfusion process and type of errors that may occur at each step, TESS 2012-2016
Figure 1. Text version below.
Figure 1 - Text description

The transfusion chain starts with blood suppliers (including Canadian Blood Services, Héma-Québec, and hospitals that may serve as suppliers to others) that supply blood products to transfusion services which manage the inventory in hospitals. Requests for products to transfusion services are initiated/placed from various hospital wards by doctors' prescriptions. Upon receipt of these requests, transfusion services determine what blood type is required and prepare the product as per the prescription, then issued it to the requesting ward for infusion. At each level of the processing of the request, specific transfusion errors may occur. Errors related to distributor codes (DC) at the supplier level, those related to: product check-in (PC), inventory management (IM), unit storage (US), sample receipt (SR), sample testing (ST), product selection (PS), as well as unit manipulation (UM) and issue (UI) can only occur at the transfusion services level (laboratory setting); while those related to: product request (PR), sample collection (SC), sample handling (SH), request for pick-up (RP), and unit transfusion (UT) would happen only at the clinical setting (ward) level.

Table 1. Summary of error codes that occur at blood suppliers, transfusion services or clinical settings
Point in the Transfusion Process Error Code Type of Error
Blood Suppliers DC Distributor codesFootnote *
Transfusion Services DC Distributor codes
PC Product check-in
IM Inventory management
US Unit storage
SR Sample receipt
ST Sample testing
PS Production selection
UM Unit manipulation
UI Unit issue
MS Miscellaneous
Clinical Settings PR Product request
SC Sample collection
SH Sample handling
RP Request for pick-up
UT Unit transfusion
MS Miscellaneous
Footnote *

Distributor code errors can also occur at blood supplier levels [including Canadian Blood Services (CBS) or Héma-Québec]. Distributor code errors can be divided into two parts according to their occurrence locations (e.g. blood suppliers and transfusion Services). Only partial data on DC errors were captured at blood supplier levels. For the calculation of the rate of DC errors at blood supplier levels, the denominator used was the total units of product received because of the non-availability of the total units of product distributed by blood suppliers.

Return to footnote * referrer

Table 2. General error codes and corresponding denominator, TESS 2012-2016
Error Code Type of Error Description Corresponding Denominator
DC Distributor codes
  • Errors occurring at the supplier level (including blood manufacturers, and blood suppliers)
Units of product received
PC Product check-in
  • Errors that relate to putting products into inventory from the blood centre, another site/campus or return from the clinical setting.
US Unit storage
  • Errors related to storage of blood products/components within transfusion services
IM Inventory management
  • Errors related to inventory management
PR Product request
  • Errors related to placing an order/request for a product
Units of product requested
SC Sample collection
  • Errors that relate to collecting or labelling specimen tubes
Samples received
SH Sample handling
  • Events related to test ordering, sample collection and transportation that do not involve the sample itself.
    • Errors related to managing requisition
    • Sample transport errors, etc.
SR Sample receipt
  • Errors related to receipt of samples in the transfusion service
ST Sample testing
  • Testing errors
Tests performed
PS Product selection
  • Production selection errors
Units of product prepared
UM Unit manipulation
  • Processing errors (e.g., pooling, irradiation)
RP Request for pick-up
  • Errors related to picking up blood products/ components for transfusion
Units of product issued
UI Unit issued
  • Events occurring during the issue of blood or blood product for transfusion.
    • Wrong product issued,
    • Product issued to wrong patient, etc.
UT Unit transfusion
  • Events occurring outside of transfusion services involving the storage, selection and administration of a blood or blood product.
    • Wrong product administered,
    • Product administered to wrong patient, etc.
MS Miscellaneous
  • Errors not related to any of those listed above (e.g., incomplete/ incorrect patient registration)
N/A

Potential severity of transfusion error:

The potential severity is a measure of the potential harm that the error may cause to the patient if it is not detected. High severity level is assigned to errors that have the potential to cause serious injury (including death), whereas low and medium severity levels are assigned to errors with the potential to cause no or minor/transient injury, respectively. The national TESS working group defined errors of high-potential severity, listed in Table 3.

Table 3. Pre-defined high (potential) severity of errors, TESS 2012-2016
Type of Error Description Error Code
Product request
  • Order for wrong patient
PR 01

Sample collection

  • Sample labelled with wrong patient identification
SC 01
  • Not labelled
SC 02
  • Wrong patient collected (not from intended patient)
SC 03
  • Label incomplete/illegible for key patient identifiers (e.g., name, identification, birthdate)
SC 07
  • Armband incorrect/not available
SC 10
Sample handling
  • Paperwork and sample ID do not match
SH 02
Sample receipt
  • Sample accepted in error
SR 01

Sample testing

  • Sample labelled with incorrect accession label
ST 05
  • Sample/test tubes mixed up/mislabelled
ST 09
Request for pick-up
  • Request for pick-up on wrong patient
RP 01

Unit issue

  • Product issued to wrong patient
UI 04
  • LIS warning overridden (in error or outside standard operating procedure (SOP))
UI 06
  • Wrong type/dose of product issued to right patient
UI 19

Unit transfusion

  • Administered product to wrong patient
UT 01
  • Administered wrong type/dose of product to patient
UT 02
Miscellaneous
  • Patient registration incomplete/incorrect
MS 03

Data collection:

Hospital sizes were classified as the following: small transfusion volume, less than 2,000 units of red blood cells (RBCs) transfused per year; medium transfusion volume, 2,000 to 10,000 units of RBCs per year; and large transfusion volume, more than 10,000 units of RBCs per year. Data on errors were reported by 17 participating hospitals from four Canadian P/Ts in 2012. In 2014, three hospitals dropped out of the system. In 2015, a large transfusion volume hospital was reclassified as a medium transfusion volume hospital, and in 2016, a small transfusion volume hospital joined the surveillance system. As a result, from 2012 to 2016, the overall number of participating hospitals changed from 17 to 15: the number of large transfusion volume hospitals decreased from four to two, and both medium transfusion volumes and small transfusion volumes remained unchanged at five and eight, respectively.

Errors are detected using various methods, including ongoing systematic quality control (chart audit, record review, and real-time prospective transfusion audit), scheduled quality assurance, supervisory reports, and reporting by other authorized individuals. The reporting process begins with the individuals who discover the event, whether or not they are involved in the transfusion. Once an error is detected at a hospital, non-nominal data regarding the error are then collected by the site. The corresponding error type and code, as well as other pieces of information such as the date, time, and location of the error, the point in the transfusion chain at which the error occurred, the point in the transfusion chain at which the error was detected, the potential severity of the error, and its consequences to the patient, are captured using a reporting form. The data are validated and consolidated into a master file by the P/T coordinator. The data elements required for the TESS are then extracted and exported to PHAC as per the data sharing agreement between the P/T and PHAC. Data exports occur every 3 months. A user’s manual for the TESS web application was developed to assist P/T with the data transfer.

Data analysis:

Data were submitted to PHAC either through the TESS electronic warehouse, web-based database, or by Microsoft Excel files. All raw data were retained in compliance with the Directive for the collection, use and dissemination of information relating to public health (PHAC. 2013 [unpublished document]). Microsoft Excel 2010 and SAS Enterprise Guide (SAS EG) v5.1 software were used for dataset combination, data cleaning, and analysis. Before the analysis and report preparation, all data were reviewed for errors, inconsistencies, and completeness. Follow-up validation was done with the reporting jurisdictions to resolve any concerns or data quality issues.

In this report, the term “rate” refers to the number of errors occurring in each year per 100,000 units of products received, requested, prepared, or issued, or per 100,000 samples received or tests performed,depending on the error type. Table 4 summarizes the number of units of blood components and fractionated plasma products received, requested, prepared, and issued before transfusion.

Table 4. Total units of blood components and fractionated plasma products received/requested /prepared/issued before transfusion for the hospitals participating in TESS 2012-2016
Denominator Data 2012 2013 2014 2015 2016 Total
Total number of samples received 144,586 132,391 104,850 98,494 110,580 590,901
Total number of tests performed 301,088 271,578 218,707 195,920 219,203 1,206,496
Total units of products received 202,618 189,354 154,229 144,669 156,657 847,527
a. Blood components 110,202 98,536 77,978 70,955 76,423 434,094
b. Fractionated plasma products 92,416 90,818 76,251 73,714 80,245 413,444
Total units of products requested 211,414 198,946 158,695 140,496 167,277 876,828
a. Blood components 119,362 107,419 82,743 74,796 85,367 469,687
b. Fractionated plasma products 92,052 91,527 75,952 65,700 81,910 407,141
Total units of products prepared 225,684 213,881 171,548 151,794 178,607 941,514
a. Blood components 130,866 120,924 94,553 87,587 96,980 530,910
b. Fractionated plasma products 94,818 92,957 76,995 73,329 81,710 419,809
Total units of products issued 210,290 198,046 158,034 140,008 166,714 873,092
a. Blood components 118,287 106,613 82,126 77,149 84,927 469,102
b. Fractionated plasma products 92,003 91,433 75,908 71,652 81,787 412,783

No statistical procedures were used for comparative analyses, nor were any statistical techniques applied to account for missing data. Data in tables with small cell sizes (n≤5) were not suppressed, since disclosure was not deemed to pose any risk of identifying individual cases. Errors were counted by the date of error occurrence.

Results

The results are organized into four sections:

  1. Overview of errors
  2. Errors that did not reach the patient (near-miss events)
  3. Errors that reached the patient (actual events)
  4. Potential severity of errors

Section 1. Overall errors, TESS 2012-2016

Figure 2. Error flowchart, overall counts for 2012-2016
Figure 2. Text version below.

From 2012 to 2016, a total of 50,925 errors were reported (Figure 2). Approximately 94.8% (n=48,256) of all errors were near-miss events while only 5.2% (n=2,669) were actual events. Of all 50,925 error events, 0.1% (n=67) resulted in harm. Of the 48,256 near-miss events, approximately 98.3% (n=47,453) were detected by a planned discovery and 1.7% (n=803) by an unplanned discovery. Based on its potential severity, these 50,925 errors are classified into three categories: high (n=7,057; 13.9%), medium (n=3,052; 6.0%), or low (n=40,816; 80.1%).

a) Errors reported by hospitals of various transfusion volumes

Table 5. Summary report of errors by hospitals of various transfusion volumes, TESS 2012-2016
Hospital Type 2012 2013 2014 2015 2016 Total
NFootnote * Freq. % N Freq. % N Freq. % N Freq. % N Freq. % Freq. %
Small (<2,000 RBC units/year) 8 356 2.9 8 459 4.0 7 302 3.5 7 274 3.1 8 482 5.0 1,873 3.7
Medium (2,000 - 10,000 RBC units/year) 5 1,821 15.0 5 1,539 13.3 4 1,527 17.5 5 2,879 32.4 5 2,859 29.8 10,625 20.9
Large (>10,000 RBC units/year) 4 9,969 82.1 4 9,567 82.7 3 6,916 79.1 2 5,722 64.5 2 6,253 65.2 38,427 75.5
Total 17 12,146 100 17 11,565 100 14 8,745 100 14 8,875 100 15 9,594 100 50,925 100
Footnote *

Number of participating hospitals.

Return to footnote * referrer

Table 5 summarizes the counts of errors by year and hospitals of various transfusion volumes. Of the 50,925 errors reported by participating hospitals between 2012 and 2016, hospitals of large transfusion volumes accounted for over 75% (n=38,427) and medium and small transfusion volumes accounted for 20.9% (n=10,625) and 3.7% (n=1,873), respectively.

b) Summary report of errors by type and hospital of various transfusion volumes

Table 6. Summary report of counts and rate of errors by hospitals of various transfusion volumes, TESS 2012 – 2016
Type of Error Small (<2,000 RBC units/year) Medium (2,000 - 10,000 RBC units/year) Large (>10,000 RBC units/year) Total
Freq. % Rate per 100,000 Freq. % Rate per 100,000 Freq. % Rate per 100,000 Freq. % Rate per 100,000
SC 243 13.0 665.3 2,735 25.7 1,510.3 14,507 37.8 3,886.2 17,485 34.3 2,959.0
SH 192 10.3 525.7 1,068 10.1 589.8 4,461 11.6 1,195.0 5,721 11.2 968.2
SR 173 9.2 473.7 166 1.6 91.7 1,492 3.9 399.7 1,831 3.6 309.9
ST 110 5.9 339.8 796 7.5 198.8 1,681 4.4 217.2 2,587 5.1 214.4
DC 49 2.6 165.3 689 6.5 235.3 616 1.6 117.3 1,354 2.7 159.8
IM 24 1.3 80.9 131 1.2 44.7 345 0.9 65.7 500 1.0 59.0
PC 49 2.6 165.3 397 3.7 135.6 635 1.7 120.9 1,081 2.1 127.5
US 673 35.9 2,270.0 97 0.9 33.1 2,770 7.2 527.5 3,540 7.0 417.7
PR 56 3.0 223.4 832 7.8 269.8 1,782 4.6 327.9 2,670 5.2 304.5
PS 3 0.2 20.7 58 0.5 17.5 72 0.2 12.1 133 0.3 14.1
UM 35 1.9 241.9 181 1.7 54.6 509 1.3 85.4 725 1.4 77.0
RP 20 1.1 92.0 539 5.1 174.8 1,148 3.0 211.5 1,707 3.4 195.5
UI 39 2.1 179.3 488 4.6 158.2 2,284 5.9 420.7 2,811 5.5 322.0
UT 173 9.2 795.5 2,046 19.3 663.4 4,821 12.5 888.0 7,040 13.8 806.3
MSFootnote * 34 1.8 NA 402 3.8 NA 1,304 3.4 NA 1,740 3.4 NA
Total 1,873 100 NA 10,625 100 NA 38,427 100 NA 50,925 100 NA
Footnote *

Rate of MS errors could not be calculated because the appropriate denominator data were not available.

Return to footnote * referrer

Overall, the three most common errors were related to SC (34.3%, n=17,458), UT (13.8%, n=7,040), and SH (11.2%, n=5,721) (Table 6). The corresponding rates for SC, SH and UT were 2,959, 968.2, and 806.3 per 100,000; however, this number varied depending on the hospital’s transfusion volume. Among small transfusion volume hospitals, the three most commonly reported errors were US (35.9%), SC (13%), and SH (10.3%) and among large transfusion volume hospitals, these were SC (37.8%), UT (12.5%), and SH (11.6%). From 2012 to 2016, the annual rate of US errors in hospitals with small transfusion volumes was more than four times higher compared to that in hospitals with large transfusion volumes. The rate of SC errors was more than five times higher in hospitals with large transfusion volumes compared to hospitals with small transfusion volumes.

c) Errors by type and year

Table 7. Summary report of errors by type and year, TESS 2012-2016
Type of Error 2012 2013 2014 2015 2016
Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000
SC 4,191 2,898.6 3,998 3,019.8 3,173 3,026.2 3,095 3,142.3 3,028 2,817.5
SH 1,122 776.0 1,354 1,022.7 1,044 995.7 886 899.5 1,315 1,223.6
SR 444 307.1 428 323.3 390 372.0 272 276.2 296 275.4
ST 634 210.6 538 198.1 512 234.1 557 284.3 347 158.3
DC 440 217.2 323 170.6 183 118.7 239 165.2 169 107.9
IM 115 56.8 86 45.4 81 52.5 94 65.0 124 79.2
PC 281 138.7 228 120.4 174 112.8 214 147.9 184 117.5
US 772 381.0 917 484.3 602 390.3 773 534.3 476 303.8
PR 759 359.0 562 282.5 565 356.0 357 239.1 427 255.3
PS 40 17.7 29 13.6 22 12.8 20 12.4 22 12.3
UM 207 91.7 143 66.9 123 71.7 132 82.0 120 67.2
RP 365 173.6 486 245.4 316 200.0 276 185.5 264 158.4
UI 583 277.2 662 334.3 551 348.7 396 266.1 619 371.3
UT 1,928 916.8 1,467 740.7 672 425.2 1,197 804.4 1,776 1,065.3
MSFootnote * 265 NA 344 NA 337 NA 367 NA 427 NA
Total 12,146 NA 11,565 NA 8,745 NA 8,875 NA 9,594 NA
Footnote *

Rate of MS errors could not be calculated because the appropriate denominator data were not available.

Return to footnote * referrer

In Table 7, the annual rates of errors for SC, SH, SR, and ST remained relatively stable from 2012 to 2016. An overall upward trend in UI errors was observed from 277.2 per 100,000 in 2012 to 371.3 per 100,000 in 2016.

d) Three most frequent events that were attributable to each type of error

Table 8. Counts, proportions and rates of the three most frequent events that were associated with each type of error, TESS 2012 – 2016
Description Error Code Freq. Percent Rate per 100,000
Sample collection errors
Sample collected unnecessarily SC 08 8,847 50.6 1,497.2
Sample haemolysed SC 06 3,181 18.2 538.3
Label incomplete/illegible for non-key patient identifiers SC 12 2,070 11.8 350.3
Sample handling errors
No phlebotomist / witness identification SH 05 2,452 42.9 415.0
Patient information (other than ID) missing / incorrect on requisition SH 07 1,258 22.0 212.9
Sample arrives without requisition SH 01 424 7.4 71.8
Sample receive errors
Sample incorrectly accessioned (test / product) SR 04 765 41.8 129.5
Historical review incorrect / not done SR 02 472 25.8 79.9
Demographic review / entry incorrect / not done SR 03 386 21.1 65.3
Sample testing errors
Data entry incorrect ST 06 983 38.0 81.5
Data entry incomplete / not done ST 04 644 24.9 53.4
Final check not done / incorrect ST 20 204 7.9 16.9
Distributor code errors
Packaging DC 04 682 50.4 80.5
Transport DC 05 202 14.9 23.8
Order incompletely / incorrectly filled DC 08 184 13.6 21.7
Inventory management errors
Product status not / incorrectly updated in computer-internal only (available / discard) IM 02 338 67.6 39.9
Product ordered incorrectly / not submitted to supplier IM 04 91 18.2 10.7
Inventory audit not done / incorrect IM 01 37 7.4 4.4
Product check-in errors
Data entry incomplete / not performed/incorrect PC 01 951 88.0 112.2
Inappropriate return to inventory PC 05 44 4.1 5.2
Unit confirmation not done / incorrect PC 06 35 3.2 4.1
Unit storage errors
Inappropriate monitoring of storage device US 03 3233 91.3 381.5
Expired product in stock US 02 145 4.1 17.1
Unit storage error of unspecified nature US 99 93 2.6 11.0
Product / test request errors
Inappropriate order of a blood product PR 06 944 35.4 107.7
Order not done / incorrect / incomplete PR 04 502 18.8 57.3
Order incorrectly entered (online order entry) PR 02 244 9.1 27.8
Product selection errors
Incorrect type / product / unit / dose selected PS 01 104 78.2 11.0
Special needs not checked PS 07 19 14.3 2.0
Product selection errors of unspecified nature PS 99 7 5.3 0.7
Unit manipulation errors
Data entry incomplete / incorrect UM 01 223 30.8 23.7
Special processing not done / incorrectly done UM 09 200 27.6 21.2
Unit Manipulation errors of unspecified nature UM 99 131 18.1 13.9
Request for pick-up errors
Request for pick-up incomplete RP 06 506 29.6 58.0
Request for pick-up of unspecified nature RP 99 361 21.2 41.3
Request for pick-up on wrong patient RP 01 266 15.6 30.5
Unit issue errors
Receipt verification not done (pneumatic tube issue) UI 21 1,735 61.7 198.7
Data entry incomplete / incorrect UI 01 609 21.7 69.8
Not checking/incorrect checking of unit and/or patient information) UI 09 147 5.2 16.8
Unit transfusion errors
Incorrect storage of product on floor UT 04 1,763 25.0 201.9
Documentation not returned UT 24 1,572 22.3 180.0
Documentation not complete / incorrect UT 23 1,371 19.5 157.0

In Table 8, the DC errors were largely attributable to packaging (50.3%, n=682), transport (14.9%, n=202), and order incompletely or incorrectly filled (13.6%, n=184). The three most frequent SC errors were sample collected unnecessarily (50.6%, n=8,847), sample haemolysed (18.2%, n=3,181), and label incomplete/illegible for non-key patient identifiers (11.8%, n=2,070), for which the corresponding rates were 1,497.2, 538.3, and 350.3 per 100,000. The three most frequent SH errors included no phlebotomist/witness identification (42.9%, n=2,452), patient information missing/incorrect on requisition (22.0%, n=1,258), and sample arrives without requisition (7.4%, n=424).

The relative effectiveness of each clinical setting or transfusion service in the transfusion chain was assessed by comparing the proportion of errors originating from and detected by each setting/unit/service (Table 9). Of the 50,775 errors, approximately 68.5% (n=34,775) and 28.9% (n=14,681) occurred in clinical settings and in the transfusion service, respectively. The highest proportions of errors that occurred in clinical settings were medical/surgical wards (19.8%, n=10,043) and emergency rooms (16.3%, n=8,298). Of the 34,775 errors that occurred in clinical settings, approximately 94.2% (n=32,773) were detected by the transfusion service and 5.6% (n=1,947) by clinical settings. Of the 14,691 errors that occurred in the transfusion service, 97.3% (n=14,277) were discovered by the transfusion service and only 2.7% (n=395) by clinical settings.

e) Localisation of errors

Table 9. Errors by locations of error occurrence and error discovery
Location of error discoveryFootnote *

Location of Error Occurrence

Emergency rooms,
Freq. (%)Footnote **
Intensive care units,
Freq. (%)
Medical/ surgical wards,
Freq. (%)
Obstetrics,
Freq. (%)
Operating rooms,
Freq. (%)
Out-patient clinics,
Freq. (%)
Laboratory services,
Freq. (%)
Supplier/ Service provider,
Freq. (%)
Transfusion services,
Freq. (%)
Blood supplier,
Freq. (%)
Total,
Freq. (%)
Emergency rooms 220 (2.7) 1 (0.0) 1 (0.0) 0 (0.0) 0 2 (0.0) 0 (0.0) 3 (1.0) 28 (0.2) 5 (0.6) 260 (0.5)
Intensive care units 4 (0.0) 569 (10.8) 4 (0.0) 1 (0.0) 5 (0.2) 3 (0.1) 1 (0.5) 4 (1.3) 76 (0.5) 8 (1.0) 675 (1.3)
Medical/ surgical wards 24 (0.3) 4 (0.1) 460 (4.6) 0 (0.0) 0 (0.0) 5 (0.1) 0 (0.0) 6 (2.0) 74 (0.5) 14 (1.7) 587 (1.2)
Obstetrics 0 (0.0) 1 (0.0) 0 (0.0) 28 (1.4) 1 (0.0) 0 (0.1) 0 (0.0) 0 (0.0) 8 (0.1) 0 (0.0) 38 (0.1)
Operating rooms 4 (0.0) 1 (0.0) 8 (0.1) 0 (0.0) 322 (9.7) 10 (0.2) 1 (0.5) 7 (2.3) 62 (0.4) 6 (0.7) 421 (0.8)
Out-patient clinics 5 (0.1) 1 (0.0) 2 (0.0) 0 (0.0) 0 (0.0) 261 (4.5) 3 (1.6) 7 (2.3) 120 (0.8) 3 (0.4) 402 (0.8)
Lab services 9 (0.1) 5 (0.1) 13 (0.1) 0 (0.0) 7 (0.2) 7 (0.1) 8 (4.3) 1 (0.3) 2 (0.0) 0 (0.0) 53 (0.1)
Blood supplier 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 2 (1.1) 2 (0.7) 27 (0.2) 10 (1.2) 41 (0.1)
Supplier/ Service provider 3(0.0) 2 (0.0) 4 (0.0) 0 (0.0) 3 (0.1) 1 (0.0) 0 (0.0) 3 (1.0) 7 (0.0) 0 (0.0) 23 (0.0)
Transfusion services 8,029 (96.8) 4,695 (88.9) 9,551 (95.1) 1,989 (98.5) 2,975 (89.8) 5,534 (95.0) 172 (92.0) 268 (89.0) 14,277 (97.2) 785 (94.5) 48,275 (95.1)
Total 8,298 (100) 5,279 (100) 10,043 (100) 2,019 (100) 3,313 (100) 5,823 (100) 187 (100) 268 (100) 14,681 (100) 831 (100) 50,775 (100)
Footnote *

Information on the location of error discovery was not available for 150 cases.

Return to footnote * referrer

Footnote **

Due to rounding, percentages may not always appear to add up to 100%.

Return to footnote ** referrer

Table 10. Counts and rate of errors that occurred in clinical settings by location of error occurrence, TESS 2012–2016Footnote *
Type of Error

Location of Error

Emergency rooms Intensive care units Medical/surgical wards Obstetrics Operating rooms Out-patient clinics
Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000
SC 5,013 4,450.7 1,629 5,516.2 4,863 4,357.1 1,117 2,573.0 911 5066.2 2,259 1,073.9
SH 1,173 1,041.4 731 2,475.4 1,323 1,185.4 427 983.6 305 1696.1 1,327 630.8
PR 442 710.5 513 392.1 755 476.8 268 3,760.9 188 149.0 273 87.1
RP 288 467.2 501 383.6 555 353.8 88 1,248.9 89 70.5 114 36.5
UT 527 854.8 1,295 991.5 776 494.7 86 1,220.6 1,262 999.9 1,136 363.4
Footnote *

Both the frequency and the rate reported by three hospitals for the period of 2012-2013 were excluded from the analysis because appropriate denominator data were not available.

Return to footnote * referrer

In Table 10, the two locations with the highest rates of SC errors were intensive care units and operating rooms, with 5,516.2 and 5,066.2 per 100,000, respectively. SH errors also had the highest rates in intensive care units and operating rooms. Obstetrics had the highest rates of PR, UT, and RP errors.

f) Errors that did not reach (near-miss events) and reached the patient (actual events) by type

Table 11. Counts, percentages, and rates of errors that did not reach and reached the patient by type, TESS 2012-2016
Type of Error Actual Events Near-Miss Events
Freq. % Rate per 100,000 Freq. % Rate per 100,000
SC 44 0.3 7.4 17,441 99.7 2,951.6
SH 126 2.2 21.3 5,595 97.8 946.9
SR 102 5.6 17.3 1,728 94.4 292.4
ST 100 3.9 8.3 2,488 96.1 206.2
DC 69 5.1 8.1 1,285 94.9 151.6
IM 34 6.8 4.0 466 93.2 55.0
PC 20 1.9 2.4 1,061 98.1 125.2
US 2 0.1 0.2 3,538 99.9 417.4
PR 548 20.5 62.5 2,122 79.5 242.0
PS 45 33.8 4.8 88 66.2 9.3
UM 57 7.9 6.1 668 92.1 70.9
RP 791 46.3 90.6 916 53.7 104.9
UI 144 5.1 16.5 2,667 94.9 305.5
UT 513 7.3 58.8 6,527 92.7 747.6
MSFootnote * 74 4.3 NA 1,666 95.7 NA
Total 2,669 5.2 NA 48,256 94.8 NA
Footnote *

Rate of MS errors could not be calculated because the appropriate denominator data were not available.

Return to footnote * referrer

The three highest percentages of actual events were RP (46.3%), PS (33.8%), and PR (20.5%) errors with corresponding cumulative rates of 90.6, 4.8, and 62.5 per 100,000, respectively. The three highest percentages of near-miss events were US (99.9%), SC (99.7%), and PC (98.1%) errors, with corresponding cumulative rates of 417.4, 2,951.6, and 125.2 per 100,000, respectively (Table 11).

g) Errors by type and potential severity

Table 12. Counts and proportions of errors by type and potential severity, TESS 2012–2016
Type of Error High Potential Severity Medium Potential Severity Low Potential Severity
Freq. % Rate per 100,000 Freq. % Rate per 100,000 Freq. % Rate per 100,000
SC 2,840 16.2 480.6 129 0.7 21.8 14,516 83.0 2,456.6
SH 1,724 30.1 291.8 247 4.3 41.8 3,750 65.5 634.6
SR 184 10.1 31.1 222 12.1 37.6 1,424 77.8 241.0
ST 166 6.4 13.8 456 17.6 37.8 1,966 76.0 163.0
DC 149 11.0 17.6 82 6.1 9.7 1,123 82.9 132.5
IM 6 1.2 0.7 43 8.6 5.1 451 90.2 53.2
PC 11 1.0 1.3 48 4.4 5.7 1,022 94.5 120.6
US 7 0.2 0.8 19 0.5 2.2 3,514 99.3 414.6
PR 988 37.0 112.7 755 28.3 86.1 927 34.7 105.7
PS 21 15.8 2.2 61 45.9 6.5 51 38.3 5.4
UM 33 4.6 3.5 98 13.5 10.4 594 81.9 63.1
RP 306 17.9 35.0 123 7.2 14.1 1,278 74.9 146.4
UI 168 6.0 19.2 133 4.7 15.2 2,510 89.3 287.5
UT 178 2.5 20.4 514 7.3 58.9 6,348 90.2 727.1
MSFootnote * 276 15.9 NA 122 7.0 NA 1,342 77.1 NA
Total 7,057 13.9 NA 3,052 6.0 NA 40,816 80.1 NA
Footnote *

Rate of MS errors could not be calculated because the appropriate denominator data were not available.

Return to footnote * referrer

Of all the 50,925 errors reported between 2012 and 2016, 7,057 (13.9%) were considered to be high-potential severity/risk, 3,052 (6%) medium-potential severity, and 40,816 (80.1%) low-potential severity. The percentages of high-severity cases varied across different types of errors. A large percentage of high-potential severity errors were related to PR (37%), SH (30.1%), RP (17.9%), and SC (16.2%) (Table 12).

h) Errors by type and occurrence time

Table 13. Counts and percentage of errors by 4 hour range for the event occurrence timeFootnote *Footnote **Footnote ***
Type of Error

Time of Day

00:00 - 04:00 04:00 - 08:00 08:00 - 12:00 12:00 - 16:00 16:00 - 20:00 20:00 - 24:00
Freq. % Freq. % Freq. % Freq. % Freq. % Freq. %
SC 1,132 6.5 2,098 12.0 5,010 28.7 4,094 23.4 2,741 15.7 2,409 13.8
SH 352 6.2 585 10.2 1,642 28.7 1,579 27.6 890 15.6 673 11.8
SR 145 7.9 138 7.5 458 25.0 600 32.8 321 17.5 168 9.2
ST 150 5.8 260 10.0 620 24.0 784 30.3 461 17.8 313 12.1
DC 82 6.1 79 5.8 515 38.0 353 26.1 200 14.8 125 9.2
IM 94 18.8 52 10.4 134 26.8 117 23.4 51 10.2 52 10.4
PC 22 2.0 40 3.7 476 44.0 360 33.3 112 10.4 71 6.6
US 574 16.2 425 12.0 1,074 30.3 702 19.8 352 9.9 413 11.7
PR 281 10.5 336 12.6 773 29.0 666 24.9 377 14.1 237 8.9
PS 7 5.3 8 6.0 31 23.3 42 31.6 27 20.3 18 13.5
UM 59 8.1 67 9.2 192 26.5 220 30.3 115 15.9 72 9.9
RP 137 8.0 128 7.5 429 25.1 450 26.4 336 19.7 227 13.3
UI 157 5.6 188 6.7 966 34.4 850 30.2 412 14.7 238 8.5
UT 403 5.7 602 8.6 2,640 37.5 1,642 23.3 949 13.5 804 11.4
MS 149 8.6 211 12.1 434 24.9 601 34.5 139 8.0 206 11.8
Total 3,744 7.4 5,217 10.2 15,394 30.2 13,060 25.6 7,483 14.7 6,026 11.8
Footnote *

Information on the event occurrence time was not available for one case.

Return to footnote * referrer

Footnote **

Rate could not be calculated because the appropriate denominator data were not available.

Return to footnote ** referrer

Footnote ***

The limitation of just counting the number of errors is that it does not allow people to make fair comparisons of the frequency of errors occurred in different time periods, since they do not take into account the corresponding denominator (ie, transfusion volumes). When measuring frequency, proportions and rates are very helpful for comparing groups, because they relate the number of errors to transfusion volumes in which these errors occur.

Return to footnote *** referrer

The majority of events (55.8%) occurred from 8:00 AM to 4:00 PM. A large number of IM and US errors occurred from 0:00 AM to 4:00 AM (Table 13).

Section 2. Errors that did not reach the patient (near-miss events)

Table 14. Counts and annual rates of errors that did not reach the patient by type and year, TESS 2012-2016
Type of Error 2012 2013 2014 2015 2016
Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000
SC 4,175 2,887.6 3,991 3,014.6 3,161 3,014.8 3,090 3,137.2 3,024 2,734.7
SH 1,071 740.7 1,324 1,000.1 1,018 970.9 876 889.4 1,306 1,181.0
SR 418 289.1 407 307.4 373 355.7 252 255.9 278 251.4
ST 598 198.6 517 190.4 494 225.9 541 276.1 338 154.2
DC 424 209.3 302 159.5 172 111.5 224 154.8 163 104.0
IM 108 53.3 82 43.3 77 49.9 91 62.9 108 68.9
PC 278 137.2 226 119.4 172 111.5 205 141.7 180 114.9
US 770 380.0 917 484.3 602 390.3 773 534.3 476 303.8
PR 630 298.0 433 217.6 437 275.4 276 196.4 346 206.8
PS 26 11.5 16 7.5 17 9.9 15 9.9 14 7.8
UM 195 86.4 128 59.8 111 64.7 122 80.4 112 62.7
RP 224 106.5 239 120.7 162 102.5 152 108.6 139 83.4
UI 558 265.3 622 314.1 536 339.2 362 258.6 589 353.3
UT 1,867 887.8 1,410 712.0 608 384.7 969 692.1 1,673 1,003.5
MSFootnote * 248 NA 331 NA 320 NA 355 NA 412 NA
Total 11,590 NA 10,945 NA 8,260 NA 8,303 NA 9,158 NA
Footnote *

Rate of MS errors could not be calculated because the appropriate denominator data were not available.

Return to footnote * referrer

A downward trend in the annual rate per 100,000 of DC errors that did not reach the patient was observed from 209.3 in 2012 to 104 in 2016. Annual rates of SC, SH, SR, and ST errors that did not reach the patient remained relatively stable (Table 14).

Table 15. Counts and rates of near-miss events that were detected through a planned discovery by type and year, TESS 2012-2016
Type of Error 2012 2013 2014 2015 2016
Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000
SC 4,152 2,871.6 3,978 3,004.7 3,147 3,001.4 3,077 3,124.0 3,018 2,729.2
SH 1,063 735.2 1,317 994.8 1,012 965.2 869 882.3 1,302 1,177.4
SR 408 282.2 389 293.8 367 350.0 242 245.7 274 247.8
ST 560 186.0 484 178.2 466 213.1 514 262.4 330 150.5
DC 417 205.8 296 156.3 168 108.9 223 154.1 159 101.5
IM 102 50.3 76 40.1 74 48.0 88 60.8 108 68.9
PC 269 132.8 222 117.2 167 108.3 203 140.3 178 113.6
US 764 377.1 916 483.8 600 389.0 773 534.3 476 303.8
PR 606 286.6 415 208.6 425 267.8 254 180.8 335 200.3
PS 23 10.2 13 6.1 11 6.4 13 8.6 12 6.7
UM 190 84.2 123 57.5 107 62.4 121 79.7 110 61.6
RP 215 102.2 231 116.6 157 99.3 145 103.6 135 81.0
UI 541 257.3 611 308.5 530 335.4 351 250.7 583 349.7
UT 1,825 867.8 1,375 694.3 566 358.2 930 664.2 1,646 987.3
MSFootnote * 232 NA 312 NA 308 NA 350 NA 404 NA
Total 11,367 NA 10,758 NA 8,105 NA 8,153 NA 9,070 NA
Footnote *

Rate of MS errors could not be calculated because the appropriate denominator data were not available.

Return to footnote * referrer

Of the 48,256 near-miss events, discovery was planned for 47,453 errors (98.3%), and discovery was unplanned for 803 (1.7%). There was a downward trend in the annual rate of DC errors that did not reach the patient and that were detected through a planned discovery, from 205.8 to 101.5 per 100,000 between 2012 and 2016 (Table 15).

Table 16. Counts and rates of errors that did not reach the patient that were detected through an unplanned discovery by type and year, TESS 2012-2016
Type of Error 2012 2013 2014 2015 2016
Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000
SC 23 15.9 13 9.8 14 13.4 13 13.2 6 5.4
SH 8 5.5 7 5.3 6 5.7 7 7.1 4 3.6
SR 10 6.9 18 13.6 6 5.7 10 10.2 4 3.6
ST 38 12.6 33 12.2 28 12.8 27 13.8 8 3.6
DC 7 3.5 6 3.2 4 2.6 1 0.7 4 2.6
IM 6 3.0 6 3.2 3 1.9 3 2.1 0 0.0
PC 9 4.4 4 2.1 5 3.2 2 1.4 2 1.3
US 6 3.0 1 0.5 2 1.3 0 0.0 0 0.0
PR 24 11.4 18 9.0 12 7.6 22 15.7 11 6.6
PS 3 1.3 3 1.4 6 3.5 2 1.3 2 1.1
UM 5 2.2 5 2.3 4 2.3 1 0.7 2 1.1
RP 9 4.3 8 4.0 5 3.2 7 5.0 4 2.4
UI 17 8.1 11 5.6 6 3.8 11 7.9 6 3.6
UT 42 20.0 35 17.7 42 26.6 39 27.9 27 16.2
MSFootnote * 16 NA 19 NA 12 NA 5 NA 8 NA
Total 223 NA 187 NA 155 NA 150 NA 88 NA
Footnote *

Rate of MS errors could not be calculated because the appropriate denominator data were not available.

Return to footnote * referrer

A downward trend in the annual rates of PC and SC errors that did not reach the patient and that were detected through an unplanned discovery was observed between 2012 and 2016 (Table 16).

Table 17. Counts and rates of errors that did not reach the patients by type and hospital of various transfusion volumes, TESS 2012-2016
Type of Error Small (<2,000 RBC units/year) Medium (2,000 - 10,000 RBC units/year) Large (>10,000 RBC units/year)
Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000
SC 243 665.3 2,705 1,493.8 14,493 3,882.5
SH 185 506.5 1,054 582.0 4,356 1,166.9
SR 170 465.5 136 75.1 1,422 380.9
ST 108 333.6 739 184.6 1,641 212.1
DC 43 145.0 642 219.3 600 114.3
IM 20 67.5 120 41.0 326 62.1
PC 46 155.2 383 130.8 632 120.4
US 673 2,270.0 96 32.8 2,769 527.3
PR 46 183.5 760 246.5 1,316 242.2
PS 3 20.7 42 12.7 43 7.2
UM 35 241.9 161 48.6 472 79.2
RP 10 46.0 459 148.8 447 82.3
UI 36 165.5 405 131.3 2,226 410.0
UT 158 726.5 1,821 590.4 4,548 837.7
MSFootnote * 33 NA 352 NA 1,281 NA
Total 1,809 NA 9,875 NA 36,572 NA
Footnote *

Rate of MS errors could not be calculated because the appropriate denominator data were not available.

Return to footnote * referrer

The rates of SC and SH errors were higher in hospitals of large transfusion volumes than those of small transfusion volumes. However, the rate of US errors was four times higher in hospitals of small transfusion volumes than those of large transfusion volumes (Table 17).

Section 3. Errors that reached the patient (actual events)

Table 18. Counts and rates of errors that reached the patient by type and year, TESS 2012-2016
Type of Error 2012 2013 2014 2015 2016
Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000
SC 16 11.1 7 5.3 12 11.4 5 5.1 4 3.6
SH 51 35.3 30 22.7 26 24.8 10 10.2 9 8.1
SR 26 18.0 21 15.9 17 16.2 20 20.3 18 16.3
ST 36 12.0 21 7.7 18 8.2 16 8.2 9 4.1
DC 16 7.9 21 11.1 11 7.1 15 10.4 6 3.8
IM 7 3.5 4 2.1 4 2.6 3 2.1 16 10.2
PC 3 1.5 2 1.1 2 1.3 9 6.2 4 2.6
US 2 1.0 0 0.0 0 0.0 0 0.0 0 0.0
PR 129 61.0 129 64.8 128 80.7 81 57.7 81 48.4
PS 14 6.2 13 6.1 5 2.9 5 3.3 8 4.5
UM 12 5.3 15 7.0 12 7.0 10 6.6 8 4.5
RP 141 67.1 247 124.7 154 97.4 124 88.6 125 75.0
UI 25 11.9 40 20.2 15 9.5 34 24.3 30 18.0
UT 61 29.0 57 28.8 64 40.5 228 162.8 103 61.8
MSFootnote * 17 NA 13 NA 17 NA 12 NA 15 NA
Total 556 NA 620 NA 485 NA 572 NA 436 NA
Footnote *

Rate of MS errors could not be calculated because the appropriate denominator data were not available.

Return to footnote * referrer

The counts and annual rates of errors that reached the patient are presented in Table 18. The annual rates of SC errors that reached the patient diminished over twofold from 11.1 to 3.6 per 100,000 from 2012 to 2016. There was a downward trend in the annual rates of SH errors that reached the patient, from 35.3 to 8.1 per 100,000 between 2012 and 2016. The annual rates of ST errors that reached the patient decreased over three times from 12 to 4.1 per 100,000 from 2012 to 2016.

As presented in Table 19, the cumulative rate of PR errors that reached the patient was more than two times higher in hospitals with large transfusion volumes than those with small transfusion volumes. The cumulative rate of DC errors that reached the patient was more than seven times higher in hospitals with small transfusion volumes than those with large transfusion volumes.

Table 19. Counts and rates of errors that reached the patient (actual events) by type and hospital transfusion volumes, TESS 2012-2016
Type of Error Small (<2,000 RBC units/year) Medium (2,000 - 10,000 RBC units/year) Large (>10,000 RBC units/year)
Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000
SC 0 0.0 30 16.6 14 3.8
SH 7 19.2 14 7.7 105 28.1
SR 3 8.2 30 16.6 70 18.8
ST 2 6.2 57 14.2 40 5.2
DC 6 20.2 47 16.1 16 3.0
IM 4 13.5 11 3.8 19 3.6
PC 3 10.1 14 4.8 3 0.6
US 0 0.0 1 0.3 1 0.2
PR 10 39.9 72 23.4 466 85.8
PS 0 0.0 16 4.8 29 4.9
UM 0 0.0 20 6.0 37 6.2
RP 10 46.0 80 25.9 701 129.1
UI 3 13.8 83 26.9 58 10.7
UT 15 69.0 225 72.9 273 50.3
MSFootnote * 1 NA 50 NA 23 NA
Total 64 NA 750 NA 1,855 NA
Footnote *

Rate of MS errors could not be calculated because the appropriate denominator data were not available.

Return to footnote * referrer

Table 20. Counts and proportion of outcomes of errors that reached the patient by type, TESS 2012–2016
Type of Error Procedure Delayed Cancelled Transfusion Delayed Adverse Reaction Product Transfused-No Reaction Incorrect Dose Administered Lost Traceability Total %
Freq. % Freq. % Freq. % Freq. % Freq. % Freq. %
SC 1 2.3 37 84.1 0 0.0 6 13.6 0 0.0 0 0.0 44 100
SH 3 2.4 103 81.7 0 0.0 20 15.9 0 0.0 0 0.0 126 100
SR 2 2.0 42 41.2 0 0.0 57 55.9 1 1.0 0 0.0 102 100
ST 6 6.0 56 56.0 1 1.0 37 37.0 0 0.0 0 0.0 100 100
DC 1 1.4 62 89.9 0 0.0 5 7.2 1 1.4 0 0.0 69 100
IM 0 0.0 13 38.2 0 0.0 3 8.8 0 0.0 18 52.9 34 100
PC 0 0.0 20 100.0 0 0.0 0 0.0 0 0.0 0 0.0 20 100
US 0 0.0 1 50.0 0 0.0 1 50.0 0 0.0 0 0.0 2 100
PR 9 1.6 380 69.3 49 8.9 101 18.4 9 1.6 0 0.0 548 100
PS 0 0.0 20 44.4 1 2.2 22 48.9 2 4.4 0 0.0 45 100
UM 2 3.5 35 61.4 0 0.0 15 26.3 4 7.0 1 1.8 57 100
RP 2 0.3 785 99.2 0 0.0 2 0.3 2 0.3 0 0.0 791 100
UI 0 0.0 72 50.0 0 0.0 60 41.7 6 4.2 6 4.2 144 100
UT 1 0.2 61 11.9 15 2.9 140 27.3 25 4.9 271 52.8 513 100
MS 4 5.4 62 83.8 0 0.0 6 8.1 2 2.7 0 0.0 74 100
Total 31 1.2 1,749 65.5 66 2.5 475 17.8 52 1.9 296 11.1 2,669 100

Of the 2,669 errors that reached the patient, 2.5% (n=66) resulted in adverse reaction; 65.5% (n=1,749) were attributable to transfusion delay; 17.8% (n=475) of errors that did not result in an adverse reaction were discovered after the product had been transfused; and 11.1% (n=296) were associated with lost traceability (Table 20).

Table 21. Counts of cases with harm caused by errors, TESS 2012-2016
Event definition Event code ABO incompati-bility TACO OtherFootnote * Acute haemolytic transfusion reaction Delayed haemolytic transfusion reaction Febrile non-haemolytic reaction IVIG Headache Minor allergic reaction Incorrect dose administered Total (%)
Order not done / incorrect / incomplete PR 04 0 7 0 0 0 0 0 0 0 7 (10.4)
Inappropriate order of a blood product PR 06 0 9 0 0 1 9 0 2 0 21 (31.3)
Product request error of unspecified nature PR 99 0 21 0 0 0 0 0 0 0 21 (31.3)
Incorrect type / product / unit / dose selected PS 01 0 0 0 1 0 0 0 0 1 2 (3.0)
Sample testing error of unspecified nature ST 99 0 0 0 0 1 0 0 0 0 1 (1.5)
Administered product to wrong patient UT 01 1 0 1 0 0 0 0 0 0 2 (3.0)
Administered wrong type / dose of product to patient UT 02 0 0 0 1 0 0 0 0 0 1 (1.5)
Appropriate monitoring of patient not done UT 11 0 2 0 0 0 0 0 0 0 2 (3.0)
Guidelines for infusion time not followed UT 25 0 6 0 0 0 0 0 1 0 7 (10.4)
Transfusion reaction protocol not followed UT 26 0 0 0 0 0 2 1 0 0 3 (4.5)
Total (%)   1 (1.5) 45 (67.2) 1 (1.5) 2 (3.0) 2 (3.0) 11 (16.4) 1 (1.5) 3 (4.5) 1 (1.5) 67 (100)
Footnote *

Unspecified adverse reaction

Return to footnote * referrer

Approximately 2.5% (n=67) of the errors that reached the patient resulted in harm (Table 21). The most common cases of harm were TACO (45 cases, 67.2%), febrile non-haemolytic reactions (FNHR) (11 cases, 16.4%), minor allergic reactions (3 cases, 4.5%), acute haemolytic transfusion reaction (AHTR) (2 cases, 3%), and delayed haemolytic transfusion reaction (DHTR) (2 cases, 3%). Errors that led to TACO were related to PR [product order not done or incorrect (PR 04), inappropriate order of a blood product (PR 06), other unspecified PR error (PR 99)], and UT [not following guidelines for infusion time (UT 25) and appropriate monitoring of patient not done (UT 11)]. Those that resulted in febrile non-haemolytic and minor allergic reactions were due to PR [inappropriate order of blood product (PR 06)] and UT [not following transfusion reaction protocol (UT 26) and not following guidelines for infusion time (UT 25)]. Other harmful events that resulted from errors included a case of ABO incompatibility due to administered wrong type / dose of product to patient (UT 01) and a case of IVIG-related headache caused by not following transfusion reaction protocol (UT 26).

Those two cases of AHTR occurred in the year 2012 and 2015, respectively. The first case was related to the incorrect product selected. Two units of group O incompatible apheresis plasma were selected and transferred to an urgent patient of unknown blood group. Laboratory work was initiated, however, the test results were not available prior to transfusion due to the urgency of the situation. As per follow-up laboratory tests, the patient was group B positive and showed evidence of hemolysis after the transfusion, which resolved within a few days of the event. The second case was an issue regarding an administered wrong dose to patient combined with a computerized provider order entry (CPOE) error. The physician ordered more IVIG than required, which caused a 4th dose of IVIG to a Group A patient and resulted in severe hemolysis after the administration. No further information on the patient was provided.

Section 4. Potential severity of errors

Table 22. Counts and rates of errors of high-potential severity by type and year, TESS 2012–2016
Type of Error 2012 2013 2014 2015 2016
Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000
SC 500 345.8 613 463.0 617 588.5 587 596.0 523 473.0
SH 324 224.1 386 291.6 393 374.8 317 321.8 304 274.9
SR 44 30.4 38 28.7 41 39.1 28 28.4 33 29.8
ST 50 16.6 41 15.1 26 11.9 28 14.3 21 9.6
DC 37 18.3 36 19.0 18 11.7 39 27.0 19 12.1
IM 1 0.5 1 0.5 1 0.6 0 0.0 3 1.9
PC 1 0.5 5 2.6 1 0.6 4 2.8 0 0.0
US 1 0.5 1 0.5 4 2.6 0 0.0 1 0.6
PR 233 110.2 203 102.0 188 118.5 162 115.3 202 120.8
PS 7 3.1 3 1.4 6 3.5 3 2.0 2 1.1
UM 11 4.9 10 4.7 2 1.2 7 4.6 3 1.7
RP 67 31.9 83 41.9 59 37.3 43 30.7 54 32.4
UI 38 18.1 46 23.2 23 14.6 33 23.6 28 16.8
UT 17 8.1 42 21.2 36 22.8 35 25.0 48 28.8
MSFootnote * 61 NA 62 NA 94 NA 29 NA 30 NA
Total (%) 1,392 (19.7) NA 1,570 (22.2) NA 1,509 (21.4) NA 1,315 (18.6) NA 1,271 (18.0) NA
Footnote *

Rate of MS errors could not be calculated because the appropriate denominator data were not available.

Return to footnote * referrer

High-potential severity UT errors increased threefold from 8.1 to 28.8 per 100,000 from 2012 to 2016. Downward trends in the annual rates of ST errors were observed from 16.6 to 9.6 per 100,000 from 2012 to 2016. Both high-potential severity SC and SH were relatively stable over time (Table 22).

Table 23. Counts and rates of high-potential severity that occurred in clinical settings by location of occurrence, TESS 2012–2016Footnote *
Type of Error

Location of Error

Emergency rooms Intensive care units Medical/surgical wards Obstetrics Operating rooms Out-patient clinics
Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000
SC 647 574.4 383 1,296.9 763 683.6 370 852.3 143 795.2 478 227.2
SH 461 409.3 186 629.8 415 371.8 122 281.0 111 617.3 383 182.1
PR 192 308.6 251 191.8 376 237.5 27 378.9 42 33.3 95 30.3
RP 51 82.7 100 76.6 79 50.4 8 113.5 23 18.2 13 4.2
UT 23 37.3 28 21.4 49 31.2 2 28.4 45 35.7 22 7.0
Footnote *

Both the frequency and the rate reported by three hospitals for the period 2012-2013 were excluded from the analysis because appropriate denominator data were not available.

Return to footnote * referrer

High-potential severity SC errors occurred most frequently in intensive care units (1,296.9 per 100,000). The two locations with the highest rate of high-potential severity SH errors were intensive care units and operating rooms, with 629.3 and 617.3 per 100,000, respectively. High-potential severity PR and RP errors occurred most frequently in obstetrics with rates of 378.9 and 113.5 per 100,000, respectively. The two locations with the highest rate of high-potential severity UT errors were the emergency rooms and operating rooms, with 37.3 and 35.7 per 100,000, respectively (Table 24).

Table 24. Counts and rates of errors of medium-potential severity by type and year, TESS 2012–2016
Type of Error 2012 2013 2014 2015 2016
Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000
SC 41 28.4 33 24.9 31 29.6 14 14.2 10 9.0
SH 52 36.0 80 60.4 47 44.8 32 32.5 36 32.6
SR 58 40.1 59 44.6 48 45.8 33 33.5 25 22.6
ST 127 42.2 116 42.7 90 41.2 79 40.3 43 19.6
DC 17 8.4 21 11.1 13 8.4 14 9.7 17 10.9
IM 10 4.9 8 4.2 11 7.1 9 6.2 5 3.2
PC 11 5.4 12 6.3 8 5.2 9 6.2 8 5.1
US 9 4.4 4 2.1 2 1.3 1 0.7 3 1.9
PR 275 130.1 144 72.4 190 119.7 81 57.7 65 38.9
PS 19 8.4 16 7.5 6 3.5 10 6.6 10 5.6
UM 29 12.8 28 13.1 21 12.2 11 7.2 9 5.0
RP 37 17.6 36 18.2 18 11.4 20 14.3 12 7.2
UI 36 17.1 32 16.2 26 16.5 21 15.0 18 10.8
UT 153 72.8 207 104.5 55 34.8 58 41.4 41 24.6
MSFootnote * 19 NA 37 NA 30 NA 14 NA 22 NA
Total 893 NA 833 NA 596 NA 406 NA 324 NA
Footnote *

Rate of MS errors could not be calculated because the appropriate denominator data were not available.

Return to footnote * referrer

The total reported errors of medium-potential severity decreased from 2012 to 2016, with the highest frequency of errors (n=893) reported in 2012 and the lowest frequency of errors (n=324) reported in 2016. Downward trends in the annual rates of ST, UM, and UI errors of medium-potential severity were also observed. The annual rates of DC and PC errors of medium-potential severity remained relatively stable. The rates of SR, ST, UI, and RP remained stable up until 2015 and then decreased in 2016. Of the 3,052 errors reported from 2012-2016, a high frequency of medium-potential severity errors were related to PR, UT, and ST. Overall, PR had the highest annual error rate in 2012 and 2014-2016, whereas UT errors had the highest annual rate in 2013.

Table 25. Counts and rates of errors of low-potential severity by type and year, TESS 2012–2016
Type of Error 2012 2013 2014 2015 2016
Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000 Freq. Rate per 100,000
SC 3,650 2,524.4 3,352 2,531.9 2,525 2,408.2 2,494 2,532.1 2,495 2,256.3
SH 746 516.0 888 670.7 604 576.1 537 545.2 975 881.7
SR 343 237.2 331 250.0 301 287.1 211 214.2 238 215.2
ST 456 151.5 381 140.3 396 181.1 450 229.7 283 129.1
DC 386 190.5 266 140.5 152 98.6 186 128.6 133 84.9
IM 104 51.3 77 40.7 69 44.7 85 58.8 116 74.0
PC 269 132.8 211 111.4 165 107.0 201 138.9 176 112.3
US 762 376.1 912 481.6 596 386.4 772 533.6 472 301.3
PR 251 118.7 215 108.1 187 117.8 114 81.1 160 95.6
PS 14 6.2 10 4.7 10 5.8 7 4.6 10 5.6
UM 167 74.0 105 49.1 100 58.3 114 75.1 108 60.5
RP 261 124.1 367 185.3 239 151.2 213 152.1 198 118.8
UI 509 242.0 584 294.9 502 317.7 342 244.3 573 343.7
UT 1,758 836.0 1,218 615.0 581 367.6 1,104 788.5 1,687 1,011.9
MSFootnote * 185 NA 245 NA 213 NA 324 NA 375 NA
Total 9,861 NA 9,162 NA 6,640 NA 7,154 NA 7,999 NA
Footnote *

Rate of MS errors could not be calculated because the appropriate denominator data were not available.

Return to footnote * referrer

Of the 40,816 low-potential severity errors that were reported from 2012 to 2016, the highest frequency of total errors was reported in 2012 (n=9,861) and the lowest frequency of total errors was reported in 2014 (n=6,640). The error rates for SC, SR, ST, PC, PR, PS, UM, and UI remained relatively stable from 2012 to 2016. Overall, SC errors had the highest low-potential severity error rate and PS errors had the lowest error rate in each year throughout the five-year period. Overall, the highest rate was SC errors in 2012, with 2,524.4 per 100,000 and the lowest rate was PS errors in 2015, with 4.6 per 100,000.

Table 26. Counts and proportions of errors by potential severity and hospitals of transfusion volumes, TESS 2012-2016
Potential Severity Small (<2,000 RBC units/year) Medium (2,000 - 10,000 RBC units/year) Large (>10,000 RBC units/year)
Freq. % Freq. % Freq. %
High 125 6.7 2,139 20.1 4,793 12.5
Medium 69 3.7 892 8.4 2,091 5.4
Low 1,679 89.6 7,594 71.5 31,543 82.1
Total 1,873 100 10,625 100 38,427 100

There was a variation in the percentage of reported high-potential severity errors between the hospital sites. The percentage of high-potential severity errors was higher in hospitals of large and medium transfusion volumes than in those of small transfusion volumes (Table 26).

Discussion

The near-misses are not truly indicative of organizational weakness; instead, they may demonstrate that predetermined plans and corrective actions are performed before transfusion. The planned discovery of near-misses can help evaluate current detection and intervention procedures for identifying and mitigating events. Additionally, reporting the unplanned discovery of near-misses can help to identify where mechanisms to detect errors before transfusion may be lacking. As actual events indicate a weakness in the blood transfusion system, appropriate measures may be taken to prevent the continuation of such events. Data presented in this report will help identify critical points in the transfusion chain to develop preventative measures for future improvement.

Although near-misses are discovered and corrected before the transfusion, they are still defined as errors in TESS. These events can still have consequences on the healthcare system and can indirectly impact patients. For example, among the 17,485 SC errors reported by participating hospitals, over 68% of cases were haemolysed samples or were associated with samples that were collected unnecessarily. In addition, intensive care units and operating rooms were identified as clinical areas where SC errors occurred commonly. These errors often resulted in delays in the issuing of blood (due to time needed to correct events before blood product issue), non-productive workload, iatrogenic anemia for infants (due to additional blood loss for samples that cannot be tested), and delayed procedures that were waiting for redrawing sample.

The TESS provides valuable information on errors regardless of their level of severity. The data can be used to identify issues that risk the patient’s safety (e.g., an incident with or without an adverse reaction) and quality issues such as deviations from standard operating procedures (SOPs).

Annual rates of SC errors that indicate to have the potential to cause an ABO-incompatible transfusion remained relatively high and stable from 2012-2016. Despite such a high rate of SC errors, the transfusion service team and clinical health care workers were able to detect the majority of SC errors according to the SOP before an incompatible transfusion could occur because more than 95% of these SC errors were detected by a planned recovery mechanism. Furthermore, there is a decreasing trend in the rate of SC errors that reached the patient from 2012-2016. These results demonstrate that the TESS working group has shown that it is possible to improve some error tracking within clinical and transfusion areas even when there are safety SOPs in place. Future work will target interventions to increase timely error tracking in the clinical settings, particularly those related to sample collection and transfusion documentation. Further analysis is required to understand trends in errors and the impact of intervention measures, with the aim of improving transfusion process, patient safety, and mitigating error-related healthcare costs.

Data Limitations

The trends observed from 2012 to 2016 should be interpreted with caution since the composition of hospitals participating in TESS changed over time and for some errors, the corresponding rates are based on low numbers which are more prone to fluctuation over time. Furthermore, the true incidence of bedside transfusion errors in TESS may be underestimated because surveillance data rely on reporting of clinically relevant events or on indirect methods. Improved error detection capabilities, data cleaning and validation, shortened reporting delay, and changes in reporting practices at the jurisdictional level can contribute to changes in observed trends. Once the data for the summary report has been validated, adjustments made to individual P/T data will be updated in that year's national data. As a result of comparing dynamic databases, small discrepancies between PHAC and provincial or territorial numbers are expected.

Summary

Overall, SC, UT, and SH errors remain the most frequent errors. Transfusion services, medical/surgical wards, and emergency rooms are the locations where most errors occur. Although the total number of errors recorded remains substantially high (n=50,925), only 5.2% (n=2,669) of errors reached the patient, demonstrating that near-misses are much more frequent than actual events. Among the 2,669 actual events that reached the patient, only 2.5% (n=67) resulted in harm to the patient. As clinical settings were less effective in reporting errors, it may be appropriate to audit, review, and update the current transfusion error reporting procedures in these settings. Particular attention may be given to procedures targeting errors related to PR, RP, and UT, as these errors collectively represented the majority of the errors that reached the patient. Enhancing error reporting in both transfusion services and clinical settings will help identify problematic areas for improving transfusion safety. Continued participation in error identification and report efforts through the TESS is a key piece of the ongoing efforts to improve the safety of transfusions in Canada.

References

Footnote 1

Bolton-Maggs PH and Cohen H. Serious Hazards of Transfusion (SHOT) haemovigilance and progress is improving transfusion safety. Br J Haematol 2013;163:303-314.

Return to footnote 1 referrer

Footnote 2

Centre for Communicable Diseases and Infection Control. Transfusion Error Surveillance System (TESS)—2008-2011 Summary Results. Centre for Communicable Diseases and Infection Control: Public Health Agency of Canada; 2014.

Return to footnote 2 referrer

Footnote 3

Centre for Communicable Diseases and Infection Control. Transfusion Error Surveillance System (TESS)—2012-2013 Report. Centre for Communicable Diseases and Infection Control: Public Health Agency of Canada; 2015.

Return to footnote 3 referrer

Footnote 4

Centre for Communicable Diseases and Infection Control. Transfusion Transmitted Injury Surveillance System (TTISS), Summary Results for 2011-2015. Centre for Communicable Diseases and Infection Control: Public Health Agency of Canada; 2019.

Return to footnote 4 referrer

Appendix

Appendix 1. Types of errors and corresponding descriptions

Error Code Description of Event
Errors related to Distributor Codes (DC)
DC 00 Not specified
DC 01 Collection issues
DC 02 Processing/Testing issues
DC 03 Labelling incorrect
DC 04 Incorrect packaging of product for transport
DC 05 Transport delayed / sent to wrong location
DC 06 Look-back / Trace-back issues
DC 07 Recall process not / incorrectly followed
DC 08 Order incompletely / incorrectly filled
DC 99 Other
Errors related to Product Check-in (PC)
PC 00 Not specified
PC 01 Data entry incomplete/not performed/incorrect
PC 05 Inappropriate return to inventory
PC 06 Unit confirmation not done / incorrect
PC 07 Administrative check not done / incorrect
PC 99 Other
Errors related to Inventory Management (IM)
IM 00 Not specified
IM 01 Inventory audit not done / incorrect
IM 02 Product status not / incorrectly updated in computer-internal only (available / discard)
IM 03 Supplier recall / look back / trace back not addressed appropriately
IM 04 Product ordered incorrectly / not submitted to supplier
IM 99 Other
Errors related to Unit Storage (US)
US 00 Not specified
US 01 Incorrect storage of product in transfusion service
US 02 Expired product in stock
US 03 Inappropriate monitoring of storage device
US 04 Unit stored on incorrect shelf (Group / Autologous / Reserved)
US 99 Other
Errors related to Product Request (PR)
PR 00 Not specified
PR 01 Order for wrong patient
PR 02 Order incorrectly entered (online order entry)
PR 03 Special needs not indicated (e.g. auto, CMV negative)
PR 04 Order not done / incorrect / incomplete
PR 06 Inappropriate order of a blood product (includes duplicate orders)
PR 07 Wrong product ordered (type)
PR 99 Other
Errors related to Sample Collection (SC)
SC 00 Not specified
SC 01 Sample labelled with wrong patient identification
SC 02 Not Labelled
SC 03 Wrong patient collected (not from intended patient)
SC 04 Collected in wrong tube type
SC 05 Sample NSQ (Non-sufficient quantity)
SC 06 Sample haemolysed
SC 07 Label incomplete /illegible for key patient identifiers (name, identification, birthdate)
SC 08 Sample collected unnecessarily
SC 09 Requisition arrives without samples
SC 10 Armband incorrect / not available
SC 12 Label incomplete / illegible for non-key patient identifiers
SC 99 Other
Errors related to Sample Handling (SH)
SH 00 Not specified
SH 01 Sample arrives without requisition
SH 02 Paperwork and sample ID do not match
SH 03 Patient ID incomplete/illegible on requisition
SH 04 No patient ID on requisition
SH 05 No phlebotomist / witness identification
SH 06 Sample arrives with incorrect type of requisition
SH 07 Patient information (other than ID) missing / incorrect on requisition
SH 10 Sample transport issues
SH 11 Incorrect test ordered / requested
SH 12 Test not ordered / requested
SH 99 Other
Errors related to Sample Receipt (SR)
SR 00 Not specified
SR 01 Sample accepted in error
SR 02 Historical review incomplete or inadequate / not done
SR 03 Demographic review / entry incorrect / not done
SR 04 Sample incorrectly accessioned (test / product)
SR 99 Other
Errors related to Sample Testing (ST)
ST 00 Not specified
ST 02 Appropriate sample check(s) not done / incorrect
ST 03 Computer warning overridden
ST 04 Data entry incomplete / not done
ST 05 Sample labelled with incorrect accession label
ST 06 Data entry incorrect
ST 09 Sample / test tubes mixed up / mislabelled
ST 12 Testing not done (ordered / confirmatory)
ST 13 Incorrect testing method chosen
ST 14 Testing performed incorrectly (did not follow SOP)
ST 15 Test result misinterpreted
ST 16 Inappropriate reagents used for testing
ST 19 Additional testing not performed
ST 20 Final check not done / incorrect
ST 21 Administrative check not done / incorrect (after the fact, record review, audit)
ST 22 Sample storage incorrect / inappropriate
ST 98 Quality control related (only to be used as 2nd event code)
ST 99 Other
Errors related to Request for Pick-up (RP)
RP 00 Not specified
RP 01 Request for pick-up on wrong patient
RP 02 Incorrect type / dose of product requested for pick-up
RP 03 Product requested prior to obtaining consent
RP 04 Product requested for pick-up, patient not ready / unavailable
RP 05 Product requested for pick-up IV not ready
RP 06 Request for pick-up incomplete (no Pt. Id, MRN / or product indicated)
RP 10 Product transport issues (internal)
RP 99 Other
Errors related to Product Selection (PS)
PS 00 Not specified
PS 01 Incorrect type / product / unit / dose selected
PS 07 Special needs not checked
PS 09 Special needs misinterpreted
PS 99 Other
Errors related to Unit Manipulation (UM)
UM 00 Not specified
UM 01 Data entry incomplete / incorrect
UM 04 Final check not done / incorrect
UM 05 Labelling incorrect
UM 09 Special processing not done / incorrectly done
UM 10 Administrative check not done / incorrect
UM 99 Other
Errors related to Unit Issue (UI)
UI 00 Not specified
UI 01 Data entry incomplete / incorrect
UI 04 Product issued to wrong patient
UI 06 LIS warning overridden (in error or outside SOP)
UI 09 Not checking/incorrect checking of unit and/or patient information)
UI 11 Product delivered to the incorrect location by the Transfusion Service (physical delivery)
UI 19 Wrong type / dose of product issued to right patient
UI 21 Receipt verification not done (pneumatic tube issue)
UI 22 Issue approval not obtained / documented
UI 99 Other
Errors related to Unit Transfusion (UT)
UT 00 Not specified
UT 01 Administered product to wrong patient
UT 02 Administered wrong type / dose of product to patient
UT 04 Incorrect storage of product on floor
UT 05 Bedside check not done / incorrect (unit / patient info)
UT 06 Administered product with incompatible IV fluid
UT 08 Wrong unit / product chosen from satellite refrigerator
UT 11 Appropriate monitoring of patient not done
UT 12 Floor/clinic did not check for existing units in their area
UT 13 Labelling incorrect
UT 22 Order / consent check not done / incorrect
UT 23 Documentation not complete / incorrect
UT 24 Documentation not returned
UT 25 Guidelines for product infusion not followed
UT 26 Transfusion reaction protocol not followed
UT 27 Monitoring of satellite fridge not done / incorrect
UT 28 Inappropriate preparation of product
UT 29 Product storage tracking incorrect / not done
UT 99 Other
Miscellaneous Errors (MS)
MS 00 Not specified
MS 03 Patient registration incomplete / incorrect
MS 04 Equipment / computer failure
MS 05 Equipment QC not done / documented
MS 06 Reagent/material event
MS 07 Patient incurred event
MS 99 Other

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