Assessment of point-of-care testing accuracy in primary healthcare clinics

Thesis Abstract

Point-of-care testing (POCT) has become an integral component of primary healthcare delivery, offering rapid diagnostic results that facilitate timely clinical decision-making. Despite its widespread adoption, concerns persist regarding the accuracy, reliability, and overall quality of POCT in resource-limited primary healthcare settings. This study aims to systematically assess the diagnostic accuracy of commonly used POCT devices in primary healthcare clinics. Specifically, it evaluates the sensitivity, specificity, positive predictive value, and negative predictive value of glucose meters, hemoglobin analyzers, and rapid diagnostic tests (RDTs) for infectious diseases, comparing these results against standardized laboratory reference methods. The research adopts a cross-sectional analytic design, targeting a population of 500 patients attending primary healthcare clinics in a metropolitan setting with diverse demographic profiles. The study employs a stratified random sampling technique to ensure representation across different age groups, genders, and clinical conditions. Data collection involves the concurrent use of POCT devices and gold-standard laboratory assays—such as automated hematology analyzers, spectrophotometry, and PCR-based methods—performed on venous blood samples. Data accuracy is evaluated through Bland-Altman analyses, receiver operating characteristic (ROC) curve analysis, and contingency table-based measures (sensitivity, specificity, predictive values). Additionally, the study investigates factors influencing POCT accuracy, including operator training, environmental conditions, and device maintenance, through multivariate logistic regression models. The study hypothesizes that the accuracy of POCT devices varies significantly depending on device type, operator skill, and environmental conditions, with certain devices demonstrating correlation coefficients exceeding 0.90 when compared with standard laboratory results. It is expected that glucose meters and hemoglobin analyzers will demonstrate high sensitivity (>90%) and specificity (>85%), whereas some RDTs may exhibit lower predictive values, especially in low-prevalence settings. The findings are anticipated to reveal critical discrepancies in POCT performance that could impact clinical decision-making and patient outcomes, underscoring the necessity for targeted quality control measures and operator training programs. This research makes a significant contribution to knowledge by providing empirical evidence on the diagnostic accuracy of POCT devices in primary healthcare environments, bridging existing gaps in literature related to resource-constrained settings. It also offers a framework for quality assurance and performance monitoring that can be adapted across diverse primary care contexts. The study's insights support health policymakers, laboratory managers, and clinicians in making informed decisions regarding POCT deployment, training, and quality assurance protocols, thereby enhancing diagnostic reliability and patient safety. The primary conclusion emphasizes that while POCT offers substantial benefits in terms of rapidity and convenience, its diagnostic accuracy varies considerably among device types and operational conditions. Consequently, regular validation against laboratory standards, reinforced training, and environmental controls are recommended to optimize POCT performance. Future research should focus on longitudinal assessments of POCT quality in real-world settings, the development of standardized validation protocols, and the integration of digital quality management systems to ensure sustained accuracy. Overall, the findings advocate for a balanced approach that recognizes POCT as a valuable adjunct to traditional laboratory diagnostics, provided rigorous quality assurances are maintained.