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Effect of Patient Identification Systems on Patient Identification Errors in Nigerian Hospitals

Abstract

Accurate patient identification is a fundamental component of patient safety and effective healthcare delivery because it ensures that the correct patient receives the intended medication, diagnostic test, treatment, procedure, and other healthcare services. Patient identification errors may occur when healthcare workers rely on incomplete patient information, incorrectly recorded identifiers, similar patient names, inadequate verification procedures, manual documentation, or poorly implemented identification systems. Such errors may result in wrong medication administration, incorrect laboratory investigations, inappropriate treatment, wrong-patient procedures, delayed care, and other preventable adverse events. Patient identification systems, including standardized identification procedures, wristbands, unique patient identification numbers, barcode systems, biometric technologies, and electronic verification tools, provide mechanisms for accurately confirming patient identity at different points of care. Effective implementation of these systems may reduce identification errors and strengthen patient safety in Nigerian hospitals. Against this background, this study investigates the effect of patient identification systems on patient identification errors in Nigerian hospitals. The study will be anchored on the Donabedian Model of Healthcare Quality, Systems Theory of Patient Safety, and the Swiss Cheese Model of Accident Causation. The Donabedian Model explains healthcare quality through structure, process, and outcome, with patient identification systems representing an important structural and process component and identification errors representing a measurable patient-safety outcome. Systems Theory of Patient Safety emphasizes the interaction among healthcare workers, patients, identification technologies, documentation procedures, communication processes, and organizational systems in preventing errors. The Swiss Cheese Model explains how errors may occur when weaknesses across multiple layers of organizational safeguards align, while standardized patient identification systems can provide additional barriers against wrong-patient events. Collectively, these theoretical perspectives provide a suitable framework for explaining how patient identification systems may influence patient identification errors in Nigerian hospitals. The study will adopt a quantitative quasi-experimental or analytical comparative research design. The study population will comprise selected public and private hospitals in Nigeria, healthcare workers involved in patient care, and relevant patient identification records and incident reports. A multistage sampling technique will be used to select states, local government areas, hospitals, clinical departments, wards, healthcare workers, and patient records. Patient identification systems will be assessed using indicators such as availability of standardized identification policies, use of patient identification wristbands, unique patient identification numbers, verification of patient details using multiple identifiers, barcode identification, biometric identification where available, electronic patient registration, staff training, compliance monitoring, system accessibility, and identification procedures during medication administration, specimen collection, blood transfusion, procedures, and patient transfers. Patient identification errors will be assessed using indicators such as wrong-patient identification, mismatched patient records, incorrect wristbands, duplicate patient records, incorrect specimen identification, medication-related identification errors, documentation mismatches, near-miss identification events, and reported wrong-patient incidents. Data will be collected using structured questionnaires, patient identification audits, incident-reporting records, medical records, laboratory records, medication-administration records, blood transfusion documentation, electronic health information systems, and direct observation. Descriptive statistics will be used to summarize hospital characteristics, patient identification practices, healthcare-worker characteristics, and identification-error patterns. Inferential statistical techniques, including chi-square tests, t-tests, correlation analysis, and logistic or multiple regression analysis where appropriate, will be used to determine the effect of patient identification systems on patient identification errors. Where a quasi-experimental design is adopted, identification-error rates before and after implementation of an improved patient identification system may be compared. Diagnostic tests will also be conducted to assess the reliability, validity, and robustness of the findings. The study is expected to find that effective patient identification systems have a significant negative effect on patient identification errors in Nigerian hospitals, indicating that stronger identification systems reduce the occurrence of identification-related errors. Hospitals with standardized and consistently implemented identification procedures are expected to demonstrate fewer mismatched patient records, specimen identification errors, medication-related identification errors, and wrong-patient incidents. The use of multiple patient identifiers, barcode verification, electronic systems, and staff training may strengthen the accuracy of patient identification throughout the care process. Routine audits and incident reporting may also help hospitals identify weaknesses and implement corrective measures. However, inadequate identification materials, poor staff compliance, high workload, insufficient training, unreliable information technology infrastructure, duplicate records, poor documentation, and limited institutional monitoring may reduce the effectiveness of patient identification systems. The study therefore expects standardized, technology-supported, consistently monitored, and adequately implemented patient identification systems to contribute significantly to reducing patient identification errors in Nigerian hospitals. The study is expected to contribute to the literature on patient identification systems, patient identification errors, patient safety, healthcare quality, clinical risk management, health information systems, hospital safety, and public health in Nigeria. The findings will provide useful information to the Federal Ministry of Health and Social Welfare, state ministries of health, hospital management boards, healthcare administrators, physicians, nurses, pharmacists, laboratory professionals, health information managers, patient safety committees, accreditation bodies, and policymakers regarding strategies for strengthening patient identification practices. The study will also provide evidence-based recommendations for standardizing patient identification protocols, strengthening the use of multiple identifiers, expanding barcode and electronic identification systems, improving staff training, conducting routine patient identification audits, strengthening incident reporting, reducing duplicate patient records, and integrating patient identification systems into broader hospital patient-safety programmes across Nigeria.

Keywords: Patient identification systems, patient identification errors, patient safety, wrong-patient errors, healthcare quality, barcode identification, electronic patient identification, clinical risk management, hospital safety, Nigeria, public health.