Patient identification is considered as an important initial part of the care process in health institutions, as well as an essential safety resource and, if correctly performed and used, it assists in the prevention of errors and serious harm to patients.1,2 Failures in patient identification have been recognized as the root cause of many problems. Moreover, misidentification can seriously affect the provision of health services, hence, additional efforts should be concentrated on reducing this significant source of preventable medical errors.3 The Joint Commission on Accreditation of Healthcare Organisations (JCAHO)4 has listed improved patient identity accuracy as the first of its national patient safety objectives, introduced in 2003, to ensure patient safety, quality of services and accreditation of the health unit.
Patient identification can be defined as "first a reliable identification of the individual as the person for whom the service or treatment is intended; second to match the service or treatment to that individual”.5 (p.1) Identification errors may also be classified into three major categories: i) incorrect patient identification, ii) incorrect body part identification and iii) use of biological materials from the wrong patient. The first category consists of possible incompatibility of name, identification documents, number and social security codes, the second relates to therapeutic interventions in the wrong place (for instance surgical procedures), while the third question covers the analysis of pathological specimens and other biological fluids from the wrong patients.3 This systematic review will focus on the first category: the incorrect patient identification.
There have been several pieces of research that have evidenced the occurrence of patient identification errors. A multicenter study conducted in 712 hospitals in the United States examined 2,463,727 identification wristbands and 67,289 (2.7%) errors were identified, of which, 49.5% due to the absence of ID bands.6 The same study was also duplicated in 204 small hospitals, where 451,436 identification wristbands were examined and 28,800 (5.7%) had errors. Again, the most common (64.4%) were related to the absence of wristbands.7 The National Patient Safety Agency8 in the United Kingdom documented, between June 2006 and August 2008, 1309 incidents related to errors in patient identification, with the vast majority (97%) occurring in hospitals. In Australia, between 2004 and 2008, 487 incidents in various health services were related to patient identification.9 In a Brazilian hospital, 385 patients were analyzed, and of these, 11.9% had errors in identification wristbands and 4.2% did not present any type of identification.10 In the same country, another study evaluated 800 patients and identified that the conformity of the identification wristbands in the obstetric clinic was 58.5% and 22.3% in the obstetric surgical center.2
The Emergency Care Research Institute11 (ECRI) conducted extensive research between 2013 and 2016 at 181 health organizations, in various countries, and examined 7613 cases of misidentification. The events included near misses as well as adverse events. A report supported by the Joint Commission12 (JC) listed a total of 409 sentinel events of patient identification out of 3326 incidents looked over the years 2014-2017 (12.3%).
In the light of this evidence, there is an apparent need for interventions, involving both the multidisciplinary team and the patients themselves, to reduce patient identification errors. Several initiatives and strategies have been created that aim to ensure that each patient is correctly identified, and all their data are checked before any intervention, to promote safer care and facilitate the process of decision-making in health.
The College of American Pathologists Q-Tracks study showed that error rates on patient ID bracelets decreased as these indicators were continuously monitored and audited over a two-year period. This same study identified error rates as high as 18.8% in adult health setting.13 Additionally, research findings suggest educational initiatives with the health workforce and improvements in the identification process, in a hospital, can ensure the accuracy of patient identification wristbands.14 This study reported initial error rates of 8.2%, which were reduced to zero and maintained for 15 months after the measures were implemented.14 Hain et al. 15 have demonstrated that a multidisciplinary approach to quality improvement and maintenance can effectively reduce rates of patient identification errors.
The World Health Organisation16 (WHO) suggests a number of strategies that should be considered in all health organizations to ensure correct identification of patients, such as, emphasizing the responsibility of health professionals to verify the identity of patients before care or treatment is performed. It encourages the use of at least two identifiers (e.g. name, date of birth) to verify the patient's identity after admission or transfer to another hospital or other care facility and prior to the delivery of care. The document also suggests the standardization of patient identification methods within the same health organization as well as the implementation of technological resources. It advises that clear protocols should be introduced for the identification of homonymous patients. It encourages the patient participation in all stages of the identification process. Training on procedures to correctly verify a patient's identity should be introduced along with guidance for the workforce about the importance and relevance or correct identification.16
More recent studies also address similar patient identification interventions. The use of two or more identifiers for medical or therapeutic interventions; use of appropriate and reliable identifiers; education and training of health personnel regarding the proper implementation and maintenance of the patient identification process; and encouraging the investment of technological resources to increase the safety in the identification process are all recommended.3,17 Furthermore, researchers advice standardization of the patient identification process, fostering a safety culture between the multidisciplinary team and patients in order to ensure correct patient identification, effective implementation and monitoring of patient identification protocols.18,19
A preliminary search of literature was conducted in February 2018 and included the JBI Database of Systematic Reviews and Implementation Reports, Cochrane Database of Systematic Reviews, MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL) and International Prospective Registers of Systematic Review (PROSPERO). Some reviews have been identified, that focus on the use of technology such as barcode and Radio Frequency Identification Technology (RFID)-based patient tracking systems to improve patient safety and efficiency.20,21 Others address the active participation of the patient in reducing errors.22,23 However, none of these reviews focus on the effectiveness of the various interventions considered by the WHO16 in reducing patient identification errors and they only compile evidence on the effectiveness of one- or two-point interventions. Thus, this review proposes to broaden the theme, considering all possible strategies evaluated in the studies as to their effectiveness in reducing or preventing errors in identifying the patient, both in the adult and in the pediatric hospital setting.
The review will consider studies that include children and adults of any age, race, ethnicity or gender who have been admitted to inpatient hospital services for any health or disease condition.
This review will consider studies that evaluate the use of strategies to reduce patient identification errors, such as educational programs and use of technology. These interventions are based on the WHO16 report, and are as follows: use, at least, two identifiers to verify patient's identity; implementation of technological resources and tools; education of frontline staff regarding correct identification band; and partnering with families and patients through education.
This review will consider studies that compare the interventions to alternative or different interventions or the absence of interventions.
This review will consider studies that include the following outcomes: reported patient identification errors rates as measured by the number of patient identification incidents during a hospital stay and causes of patient identification errors in the hospital setting.
Types of studies
This review will consider both experimental and quasi-experimental study designs including randomized controlled trials, non-randomized controlled trials, before and after studies and interrupted time-series studies. In addition, analytical observational studies including prospective and retrospective cohort studies, case-control studies and analytical cross-sectional studies will be considered for inclusion. This review will also consider descriptive observational study designs including case series, individual case reports and descriptive cross-sectional studies for inclusion. Studies published in English, Portuguese and Spanish languages will be considered for inclusion in this review. In addition, all studies published at any time will be considered for inclusion in this review.
This systematic review will be conducted in accordance with the Joanna Briggs Institute (JBI) methodology for systematic reviews of effectiveness evidence.24 This review is registered on PROSPERO with registration number CRD42018085236.
The search strategy aims to find both published and unpublished studies. An initial limited search of MEDLINE and CINAHL has been undertaken followed by analysis of the text words contained in the title and abstract, and of the index terms used to describe articles. This informed the development of a search strategy which will be tailored for each information source. A full search strategy for MEDLINE using keywords is detailed in Appendix I. The reference list of all studies selected for critical appraisal will be screened for additional studies.
The databases to be searched will include: MEDLINE via PubMed, CINAHL, Embase, Scopus and Latin American and Caribbean Health Sciences Literature (LILACS).
The trial registers to be searched will include: Cochrane Central Trials Register of Controlled Trials
The search for unpublished studies will include: ProQuest Dissertation and Theses, Google Scholar, MedNar, NHS Improvement, Dart-e, System for Information on Grey Literature in Europe (Open Grey), and Banco de Teses-CAPES.
Following the search, all identified citations will be collated and uploaded into EndNote™ online (Clarivate Analytics, PA, USA) and duplicates removed. Titles and abstracts will then be screened by two independent reviewers for assessment against the inclusion criteria for the review. Studies that may meet the inclusion criteria will be retrieved in full and their details imported into Joanna Briggs Institute System for the Unified Management, Assessment and Review of Information (JBI SUMARI) (Joanna Briggs Institute, Adelaide, Australia). The full text of selected studies will be retrieved and assessed in detail against the inclusion criteria. Full text studies that do not meet the inclusion criteria will be excluded and reasons for exclusion will be provided in an appendix in the final systematic review report. Included studies will undergo a process of critical appraisal. The results of the search will be reported in full in the final report and presented in a PRISMA flow diagram.25 Any disagreements that arise between the reviewers will be resolved through discussion or with a third reviewer.
Assessment of methodological quality
Selected studies will be critically appraised by two independent reviewers at the study level for methodological quality in the review using standardized critical appraisal instruments from JBI for the following study types: case control studies, case reports, case series, cohort studies, quasi-experimental studies, randomized controlled trials and analytical cross sectional studies.26 Any disagreements that arise will be resolved through discussion or with a third reviewer. Following critical appraisal, studies that do not meet a certain quality threshold will be excluded. The decision to exclude will be based on cut-off scores of less than 70% of the items assessed for all JBI critical appraisal tools included in this study. This represents the following amount of “yes” answers from the JBI critical appraisal checklist for each type of study: less than six out of nine for quasi-experimental studies; less than nine out of 13 for randomized controlled trials; less than eight out of 11 for cohort studies; less than seven out of 10 for case control studies; less than seven out of 10 for case series; less than five out of eight for case reports; and less than five out of eight for analytical cross sectional studies.
Data will be extracted from papers included in the review using the standardized data extraction tool available in JBI SUMARI by two independent reviewers.26 The data extracted will include specific details about the interventions, populations, study methods and outcomes of significance to the review question and specific objectives. Any disagreements that arise between the reviewers will be resolved through discussion or with a third reviewer. Authors of papers will be contacted to request missing or additional data where required.
Papers will, where possible be pooled in statistical meta-analysis using JBI SUMARI.26 Effect sizes will be expressed as either odds ratios (for dichotomous data) and weighted (or standardized) mean differences (for continuous data) and their 95% confidence intervals will be calculated for analysis. Heterogeneity will be assessed statistically using the standard chi-squared and I squared tests. The choice of model (random or fixed effects) and method for meta-analysis will be based on the guidance by Tufanaru et al. 27
Subgroup analyses will be conducted where there is sufficient data to investigate for effectiveness, age group (children, adolescents and adults) and types of intervention. Sensitivity analyses will be conducted to test decisions made regarding to the effectiveness of interventions. Where statistical pooling is not possible the findings will be presented in narrative form including tables and figures to aid in data presentation where appropriate.
A funnel plot will be generated to assess publication bias if there are 10 or more studies included in a meta-analysis. Statistical tests for funnel plot asymmetry (Egger test, Begg test, Harbord test) will be performed where appropriate.
Assessing certainty in the findings
A Summary of Findings will be created using GRADEPro GDT software (McMaster University, ON, Canada). The Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach for grading the quality of evidence will be followed. The Summary of Findings will present the following information where appropriate: absolute risks for treatment and control, estimates of relative risk, and a ranking of the quality of the evidence based on study limitations (risk of bias), indirectness, inconsistency, imprecision and publication bias.28,29
The study will be fully funded by the first author, HAR.
This review will partially fulfil degree requirements for successful completion of the Doctor of Sciences at School of Nursing, University of São Paulo, Brazil, for: Helena Aparecida de Rezende, MSc, BSN.
MEDLINE search strategy (searched on March 6, 2018)
1. Bates DW, Larizgoitia I, Prasopa-Plaizier N, Jha AK. Global priorities for patient safety
2. Tase TH, Tronchin DMR. Patient identification systems
in obstetric units and wristband conformity. Acta Paul Enfermagem
2015; 28 4:374–380.
3. Lippi G, Mattiuzzi C, Bovo C, Favaloro EJ. Managing the patient identification crisis in healthcare and laboratory medicine. Clin Biochem
6. Renner SW, Howanitz PJ, Bachner P. Wristband identification error reporting in 712 hospitals. A College of America Pathologists’ Q-Probes Study of Quality Issues in Transfusion Practice. Arch Pathol Lab Med
1993; 117 6:573–577.
7. Renner SW, Dale JC. Wristband Identification Reporting Errors: Data Analysis and Critique. Q-Probes Study 95-07. 1995; Northfield, IL: College of American Pathologists, 17pp.
9. Thomas MJ, Schultz TJ, Hannaford N, Runciman WB. Mapping the limits of safety reporting systems in health care - what lessons can we actually learn? Med J Aust
2011; 194 12:635–639.
10. Hoffmeister LV, Moura GMSS. Use of identification wristbands
among patients receiving inpatient treatment in a teaching hospital
. Rev Lat Am Enfermagem
2015; 23 1:36–43.
13. Howanitz PJ, Renner SW, Walsh MK. Continuos wristband monitoring over 2 years decreases identification errors: a College of American Pathologists Q-Tracks Study. Arch Pathol Lab Med
2002; 126 7:809–815.
14. Greenly MA. Helping Hippocrates: a cross-functional approach to patient identification. Jt Comm J Qual Patient Saf
2006; 32 8:463–469.
15. Hain PD, Jokers B, Rush M, Clayton J, Throop P, Hoagg S, et al. An intervention to decrease patient identification band errors in a children's hospital
. Qual Saf Health Care
2010; 19 3:244–247.
18. Tase TH, Lourenção DCA, Bianchini SM, Tronchin SM. Patient identification in healthcare organizations: an emerging debate. Rev Gaúcha Enferm
2013; 34 2:196–200.
19. Tase TH, Quadrado ERS, Tronchin DMR. Avaliação do risco de erro de identificação de mulheres numa maternidade pública. Rev Bras Enferm
2018; 71 1:120–125.
20. Dobson I, Doan Q, Hung G. A systematic review of patient tracking system for use in the paediatric department. J Emerg Med
2013; 44 1:242–248.
21. Khammarnia M, Kassani A, Eslahi M. The Efficacy of Patients’ Wristband Bar-code on Prevention of Medical Errors: A Meta-Analysis Study. Appl Clin Inform
2015; 6 4:716–727.
22. Doherty C, Stavropoulou C. Patients’ willingness and ability to participate actively in the reduction of clinical errors: a systematic literature review. Soc Sci Med
2012; 75 2:257–263.
23. Schwappach DL. Review: engaging patients as vigilant partners in safety: a systematic review. Med Care Res Rev
2010; 67 2:119–148.
24. Tufanaru C, Munn Z, Aromataris E, Campbell J, Hoop L. Aromataris E, Munn Z. Chapter 3: Systematic reviews of effectiveness. The Joanna Briggs Institute, Joanna Briggs Institute Reviewer's Manual [Internet]
. Adelaide (AU): 2017.
25. Moher D, Liberati A, Tetzlaff J, Altman DG. The PRISMA Group. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med
2009; 6 6:e1000097.
27. Tufanaru C, Munn Z, Stephenson M, Aromataris E. Fixed or random effects meta-analysis? Common methodological issues in systematic reviews of effectiveness. Int J Evid Based Healthc
2015; 13 3:196–207.
28. Guyatt G, Oxman AD, Aki EA, Kina R, Vist G, Brozek J. GRADE guidelines: 1. Introduction - GRADE evidence profiles and summary of findings tables. J Clin Epidemiol
2011; 64 4:383–394.
29. Schünemman H, Brozek J, Guyatt G, Oxman A. Handbook for grading the quality of evidence and the strength of recommendations using GRADE approach [Internet]. Canada: GRADE Working Group; 2013.