Impact of Point-of-Ccare Testing on Workflow Efficiency in Rural Hospitals

Thesis Abstract

Point-of-care testing (POCT) has the potential to transform workflow efficiency in rural hospital laboratories by reducing turnaround times, consolidating pre-analytical processes, and enabling rapid clinical decision-making. This study addresses the persistent challenges of delayed test reporting, fragmented specimen handling, and resource constraints that undermine diagnostic timeliness in rural settings. The principal aim is to quantify the impact of POCT implementation on laboratory and clinical workflow efficiency, defined by turnaround time (TAT) reductions, specimen-to-result intervals, staff workload, and patient throughput, while assessing the ripple effects on clinical decision-making accuracy and patient length of stay. Specific objectives include (i) measuring changes in TAT for core chemistry, hematology, and infectious disease panels pre- and post-POCT integration; (ii) evaluating changes in workflow indicators such as sample transport time, specimen rejection rates, and queue lengths in phlebotomy and central laboratory units; (iii) assessing staff workload and perceived efficiency using validated workload scales; (iv) examining clinical impact indicators, including time to antibiotic administration in sepsis and time to treatment initiation in acute myocardial infarction; and (v) exploring barriers and facilitators to POCT adoption through qualitative insights from laboratory and clinical staff. The study adopts a mixed-methods design underpinned by the Technology Acceptance Model and the Donabedian framework for quality of care, allowing triangulation between quantitative workflow metrics and qualitative perceptions of utility and feasibility. The population comprises rural hospital laboratories and associated clinical units within a regional health system. A multi-stage sampling approach selects 12 rural hospitals stratified by bed size and catchment population. Quantitative data will be collected over 12 months pre- and 12 months post-POCT implementation, with a target sample of 2,400 POCT test records per panel and corresponding centralized laboratory records. Instrumentation includes an electronic data extraction protocol from Laboratory Information Management Systems (LIMS), time-stamped workflow logs, and a validated workload questionnaire administered to 60 laboratory technicians and 40 clinicians. Qualitative data will be captured through semi-structured interviews with 20 laboratory managers and 20 senior clinicians, complemented by 8 focus groups with frontline staff. Validity and reliability procedures encompass pilot testing of data extraction scripts, inter-rater reliability checks for time-motion coding, and Cronbach’s alpha assessments for questionnaire scales. Data analysis will utilize descriptive statistics to profile baseline workflow metrics and inferential analyses to quantify POCT effects. Paired t-tests and repeated-measures ANOVA will compare pre- and post-POCT TATs across panels, while multivariate linear regression will model predictors of reduced TAT and improved throughput, controlling for hospital size, staffing levels, and seasonal demand. Time-to-event analyses (Cox proportional hazards models) will examine time to clinical decision and treatment initiation. For qualitative data, thematic analysis will be conducted using a six-step approach, aided by NVivo, to identify themes related to implementation feasibility, perceived reliability, and workflow integration. Mixed-methods integration will follow a convergent design, juxtaposing quantitative outcomes with qualitative themes to interpret discrepancies and synergy. Expected findings include statistically significant reductions in TATs for POCT-performed panels, shorter specimen transport times, lower specimen rejection rates, and improved staff-perceived efficiency without compromising analytical accuracy. It is anticipated that clinical turnaround metrics—such as time to antibiotic administration in suspected sepsis and time to reperfusion therapy in myocardial events—will improve commensurately. The study will contribute to knowledge by providing robust, context-specific evidence on how POCT reshapes rural laboratory workstreams, informs policy on resource allocation, and clarifies the balance between decentralization of testing and quality assurance. Conclusions are expected to underscore the necessity of integrated training, standardized POCT governance, and ongoing performance monitoring. Recommendations will address scalable implementation strategies, including tiered POCT deployment, data interoperability enhancements, and targeted change-management interventions to sustain workflow gains in rural hospitals.