Evaluation of Data Quality Improvement Plans and Their Impact on Clinical and Administrative Decisions at Fmc Yenagoa

This study evaluated Data Quality Improvement Plans (DQIPs) and their impact on clinical and administrative decision making at the Federal Medical Centre, Yenagoa, Nigeria. It was motivated by persistent challenges in healthcare data quality, including inaccurate reporting, incomplete records, delayed submissions, and suboptimal use of health information for evidence-based decision making. A descriptive cross-sectional survey design was adopted. The population comprised 1,151 healthcare workers, including Health Information Management personnel, nurses, doctors, laboratory scientists, pharmacists, and administrative staff. A sample size of 297 was determined using Taro Yamane’s formula, and respondents were selected through stratified and simple random sampling techniques. Data were collected using a structured questionnaire, and reliability was established using Cronbach’s Alpha. Data were analyzed using descriptive statistics, including frequencies, percentages, means, and standard deviation. Out of 297 questionnaires distributed, 284 were validly returned, yielding a 95.6% response rate. Findings showed that DQIPs were implemented in the institution, including staff training (mean = 3.20), routine data quality assessments (mean = 3.16), standardized data collection tools (mean = 3.24), feedback mechanisms (mean = 3.13), and supportive supervision (mean = 3.18). Healthcare data quality was rated relatively high across accuracy, completeness, timeliness, consistency, and reliability (grand mean = 3.15). The study further revealed that DQIPs positively influenced clinical decision making (grand mean = 3.20), particularly in diagnosis, treatment planning, continuity of care, patient management, and reduction of medical errors. Similarly, administrative decision making was enhanced (grand mean = 3.19), especially in planning, budgeting, performance monitoring, policy implementation, and resource allocation. The study concludes that effective implementation of DQIPs improves healthcare data quality and strengthens evidence-based clinical and administrative decision making in tertiary healthcare settings. It recommends continuous staff training, regular data quality assessments, improved governance systems, strengthened digital infrastructure, and sustained institutional support for data quality initiatives.

Data Quality, Health Information Systems, Clinical Decision Making, Administrative Decision Making, Nigeria

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