• Humans
• Machine Learning
• Blood Cell Count/methods
• Child

• audit
• blood sample
• electronic labelling systems
• mislabelling
• rejection
• wrong blood in tube

• Humans
• United Kingdom
• Blood Transfusion
• Medical Errors
• Product Labeling
• Female
• Male
• Medical Audit

• autoverification rules
• blood transfusion safety
• laboratory quality
• transfusion compatibility testing

• Humans
• Blood Grouping and Crossmatching/standards
• Blood Grouping and Crossmatching/methods
• Retrospective Studies
• Blood Transfusion/standards
• Blood Group Antigens
• Female

• quality assurance, health care
• quality control
• safety

• Humans
• Pilot Projects
• Medical Errors/statistics & numerical data
• Specimen Handling/methods
• Blood Cell Count
• Diagnostic Errors

• intensive care
• knowledge
• nurses
• transfusion

• Neonate
• Platelets
• Premature
• Red blood cells
• Transfusion

• Infant, Newborn
• Humans
• Blood Banking
• ABO Blood-Group System
• Blood Transfusion
• Blood Group Incompatibility
• Hemolysis

• administration
• regulatory and QA
• transfusion service operations

• Humans
• United States
• Medical Errors/prevention & control
• Blood Transfusion
• Blood Banks
• Blood Grouping and Crossmatching
• Blood Specimen Collection/methods
• ABO Blood-Group System

• Humans
• Retrospective Studies
• Medical Errors
• Laboratories, Hospital
• Machine Learning
• Blood Cell Count

• barcode
• patient safety
• positive patient identification
• transfusion quality

• Pregnancy
• Humans
• Female
• Child
• Hospitals, Pediatric
• Tertiary Healthcare
• Blood Transfusion
• Patients
• Specimen Handling

• Electronic patient identification
• Specimen rejection
• Wrong blood in tube (WBIT)

• artificial intelligence
• artificial neural network
• machine learning
• mislabelled samples
• wrong blood in tube

The second blood group determination or group check sample is a process of verifying the ABO group with a second blood sample prior to transfusion. It has been used to detect errors related to wrong blood in tube (WBIT) events and reduce the risk of ABO‐incompatible transfusions. To prevent the clinical team from collecting the group check sample at the same time as the first sample, a tan top tube only available from the blood bank was introduced for second blood group determinations if drawn within 24 h of the first group and screen.

This is a retrospective study analyzing data from 2005 to 2020 before and after the implementation of the blood bank supplied tan top tube for group check. The number of WBIT events, transfusion delays, and health care costs were determined.

The number of WBIT events remained unchanged throughout the time period. No delays in transfusion or procedure were reported due to the tan top tube group check. There was no increase in group O transfusions over time. In comparison to using an ethylenediaminetetraacetic acid (EDTA) tube, the tan top tube was estimated to add an extra yearly cost of $790.79 Canadian dollars.

Second blood group determination using the blood bank supplied tan top tube did not increase the number of WBIT events detected but ensured an independent sample draw. A minimal incremental cost of implementing the tan top tube was noted with no delay in transfusions or procedures.

• blood transfusion
• laboratory safety
• patient safety
• patient testing and transfusion medicine clinical practices

• decision support
• electronic medical records
• patient identification
• transfusion

• blood transfusion
• patient safety
• pretransfusion testing
• specimen collection

• artificial intelligence
• artificial neural network
• decision support
• machine learning
• mislabeled samples
• wrong blood in tube

• Acute transfusion reactions
• Adverse blood reactions
• Blood safety
• Complications of blood transfusion
• Delayed transfusion reactions
• Transfusion-transmitted infections

• blood transfusion
• patient safety
• pretransfusion testing
• specimen collection

• FMEA
• King Hussein Cancer Center
• Nursing
• Specialized Cancer Center
• and Sampling Process

• Blood Specimen Collection/nursing
• Cancer Care Facilities
• Healthcare Failure Mode and Effect Analysis
• Humans
• Jordan
• Medical Errors/prevention & control
• Safety Management
• Selection Bias

• CAR T
• centralization
• decentralization
• discrete event simulation
• manufacturing
• supply chain

• bedside
• electronic identification system
• nurse
• pre-transfusion check
• questionnaire survey

• Medical education & training
• blood bank & transfusion medicine
• haematology
• health services administration & management
• quality in health care

Large-scale and long-term studies are not sufficient to determine the efficiency that IT solutions can bring to transfusion safety.

This quality-improvement report describes our continuous efforts to implement and upgrade a bar code–based transfusion management (BCTM) system since 2011 and examines its effectiveness and sustainability in reducing blood transfusion errors, in a 3000-bed tertiary hospital, where more than 60,000 prescriptions of blood transfusion are covered by 2500 nurses each year.

The BCTM system uses barcodes for patient identification, onsite labeling, and blood product verification, through wireless connection to the hospital information systems. Plan-Do-Study-Act (PDSA) cycles were used to improve the process. Process maps before and after implementation of the BCTM system in 2011 were drawn to highlight the changes. The numbers of incorrect labeling or wrong blood in tube incidents that occurred quarterly were plotted on a run chart to monitor the quality changes of each intervention introduced. The annual occurrences of error events from 2011 to 2017 were compared with the mean occurrence of 2008-2010 to determine whether implementation of the BCTM system could effectively reduce the number of errors in 2016 and whether this reduction could persist in 2017.

The error rate decreased from 0.03% in 2008-2010 to 0.002% in 2016 (P<.001) and 0.001% in 2017 (P<.001) after implementation of the BTCM system. Only one incorrect labeling incident was noted among the 68,324 samples for blood typing, and no incorrect transfusions occurred among 67,423 transfusion orders in 2017.

This report demonstrates that continuous efforts to upgrade the existing process is critical to reduce errors in transfusion therapy, with support from information technology.

• barcode technology
• blood transfusion safety
• quality improvement

• Blood Group Incompatibility/complications
• Blood Group Incompatibility/diagnosis
• Blood Group Incompatibility/immunology
• Diagnosis, Differential
• Hemolysis
• History, 17th Century
• History, 20th Century
• Humans
• Transfusion Reaction/diagnosis
• Transfusion Reaction/history
• Transfusion Reaction/physiopathology
• Transfusion Reaction/therapy

• adverse reaction
• biovigilance
• blood transfusion
• haemovigilance
• human factors

• cost of transfusion
• thalassaemia
• time-driven activity-based costing

To describe the development and implementation of a person-centered endoscopy safety checklist and to evaluate the effects of a “checklist intervention”.

The checklist, based on previously published safety checklists, was developed and locally adapted, taking patient safety aspects into consideration and using a person-centered approach. This novel checklist was introduced to the staff of an endoscopy unit at a Stockholm University Hospital during half-day seminars and team training sessions. Structured observations of the endoscopy team’s performance were conducted before and after the introduction of the checklist. In addition, questionnaires focusing on patient participation, collaboration climate, and patient safety issues were collected from patients and staff.

A person-centered safety checklist was developed and introduced by a multi-professional group in the endoscopy unit. A statistically significant increase in accurate patient identity verification by the physicians was noted (from 0% at baseline to 87% after 10 mo, P < 0.001), and remained high among nurses (93% at baseline vs 96% after 10 mo, P = nonsignificant). Observations indicated that the professional staff made frequent attempts to use the checklist, but compliance was suboptimal: All items in the observed nurse-led “summaries” were included in 56% of these interactions, and physicians participated by directly facing the patient in 50% of the interactions. On the questionnaires administered to the staff, items regarding collaboration and the importance of patient participation were rated more highly after the introduction of the checklist, but this did not result in statistical significance (P = 0.07/P = 0.08). The patients rated almost all items as very high both before and after the introduction of the checklist; hence, no statistical difference was noted.

The intervention led to increased patient identity verification by physicians - a patient safety improvement. Clear evidence of enhanced person-centeredness or team work was not found.

• Checklist
• Communication
• Endoscopy
• Observation
• Patient-centered care
• Person-centered care
• Patient safety
• Teamwork

• Adult
• Checklist
• Endoscopy, Gastrointestinal/adverse effects
• Endoscopy, Gastrointestinal/methods
• Endoscopy, Gastrointestinal/standards
• Female
• Gastroenterologists/organization & administration
• Gastroenterologists/psychology
• Gastrointestinal Diseases/diagnosis
• Gastrointestinal Diseases/therapy
• Health Plan Implementation
• Humans
• Male
• Patient Care Team/organization & administration
• Patient Participation
• Patient Safety
• Physician-Patient Relations
• Postoperative Complications/etiology
• Postoperative Complications/prevention & control
• Quality Improvement
• Surveys and Questionnaires
• Sweden
• Work Performance
• Young Adult

• Administration safety
• Confusion
• Critical incidents
• Error
• Error reporting
• Hemotherapy
• Right patient
• Right tube
• Transfusion safety

• Clinical Laboratory Techniques/standards
• Diagnostic Errors
• Humans
• Laboratories/standards

• Barcode
• Blood transfusion
• Electronic order
• Medical errors/prevention and control
• Wrong blood in tube

• Blood Banking/methods
• Blood Group Incompatibility/prevention & control
• Blood Grouping and Crossmatching/methods
• Electronic Data Processing/methods
• Humans
• Medical Errors/prevention & control

Accurate patient identification and specimen labeling at the time of collection are crucial steps in the prevention of medical errors, thereby improving patient safety.

All patient specimen identification errors that occurred in the outpatient department (OPD), emergency department (ED), and inpatient department (IPD) of a 3,800-bed academic medical center in Taiwan were documented and analyzed retrospectively from 2005 to 2014. To reduce such errors, the following series of strategies were implemented: a restrictive specimen acceptance policy for the ED and IPD in 2006; a computer-assisted barcode positive patient identification system for the ED and IPD in 2007 and 2010, and automated sample labeling combined with electronic identification systems introduced to the OPD in 2009.

Of the 2000345 specimens collected in 2005, 1023 (0.0511%) were identified as having patient identification errors, compared with 58 errors (0.0015%) among 3761238 specimens collected in 2014, after serial interventions; this represents a 97% relative reduction. The total number (rate) of institutional identification errors contributed from the ED, IPD, and OPD over a 10-year period were 423 (0.1058%), 556 (0.0587%), and 44 (0.0067%) errors before the interventions, and 3 (0.0007%), 52 (0.0045%) and 3 (0.0001%) after interventions, representing relative 99%, 92% and 98% reductions, respectively.

Accurate patient identification is a challenge of patient safety in different health settings. The data collected in our study indicate that a restrictive specimen acceptance policy, computer-generated positive identification systems, and interdisciplinary cooperation can significantly reduce patient identification errors.

• Blood group incompatibility
• Blood transfusion
• Medical errors
• Patient participation
• Patient safety