DOI: 10.6084/m9.figshare.19184312
title: Data set for sssessment of conformity to prescription writing guidelines and medication errors among paediatric patients in three Hospitals in Freetown, Sierra Leone - medication spss.sav data set

description: <b>Study setting</b> We conducted this study in the paediatrics departments of the Ola During Children's Hospital (ODCH), Rokupa Government Hospital (RGH), and the King Harman Maternity and Children Hospital (KHMCH) located in Freetown, the Capital city of Sierra Leone. Ola During Children's hospital is a tertiary teaching hospital and the leading paediatric referral hospital in Sierra Leone. Rokupa Government and KHMCH are secondary hospitals that provide comprehensive emergency obstetric and newborn care inpatient and outpatient paediatric and maternity services.<br>Study design and duration This study was conducted between April 2021 to July 2021 and had two phases. Phase 1 was a descriptive cross-sectional retrospective study of paediatrics prescriptions from the respective pharmacy departments from May 1 to May 31, 2021. In phase 2, we conducted a point prevalence descriptive inpatient chart review that lasted for one week to assess MEs and pDDIs among the paediatric patient population.<br><b>Study population</b><br>This data set is the SPSS file with both variable and data view. It contains the variables that were analysed for the two phases of the study namely: For phase 1 of the study, the population included paediatric prescriptions that came to the respective pharmacy departments in May 2021. Phase 2 included inpatients &lt;16 years irrespective of their working diagnosis and gender and whose parents or guardians consented to participate in the study.Data collection procedure and tool For phase 1 of the study, the data collection tool was adapted from the Sierra Leone Pharmacy and Drugs Act 2001, the World Health Organization (WHO) guidelines for prescription writing, and a previous study [12, 32, 33]. Seventeen essential elements were selected for this study and compiled into a single data collection tool. We manually extracted all data through a review of prescriptions accessed from the pharmacies.<b> </b>The data collection tool for phase 2 was adapted from the WHO guide on reporting and learning systems for medication errors, American Society of Health System Pharmacists (ASHP) guidelines for preventing medication errors in hospitals, and previous studies [3, 4, 18, 34]. Data collection tools were piloted, and feedback was used to develop the final versions used in the study.<b> </b>The treatment charts were reviewed, and the following were extracted and entered into the data collection tool: wrong patient, wrong dose, wrong route, wrong medicine, wrong dosage form, wrong time of administration, contraindication including allergy, wrong duration, dose omitted or delay, wrong frequency, wrong indication, unnecessary medicine, and therapeutic duplication. In addition, nurses were accompanied during the medicine administration rounds and patients and caretakers were interviewed to gather information when necessary.<b> </b> Ethical consideration Clearance to conduct the study was obtained from the Research, Innovation and Publication Review Committee of the Faculty of Pharmaceutical Sciences, College of Medicine and Allied Health Sciences, University of Sierra Leone. The management of the hospitals permitted the study to be done in their facilities. Written informed consent was obtained from parents/caregivers after explaining the purpose and procedures of the study. Parents gave consent before data was collected, and they were not coerced to participate in the study. Patient information was coded and kept confidential. Data analyses The researchers evaluated the completion of the essential elements for each prescription, such as the use of the generic names, recommended abbreviations, and prescription legibility. We determined the accuracy score out of 34 total points. Each element was assessed, scoring 0, 1 or 2 for 'not completed', 'partially completed', or 'fully completed', respectively. Legibility was scored subjectively according to the prescription quality index (PQI) as 0, 1, or 2 for 'illegible', 'barely legible' or 'legible', respectively, by two or more persons [35]. The global accuracy score (GAS) for each prescription was determined by calculating the total percentage achieved out of 34 possible points for the 17 prescription elements considered. The GAS was then classified into one of four scores: 100%, 80% – 99%, 40% – 79%, and less than 40%. The desired prescription-writing accuracy score, or gold standard, is 100%. The definition and severity categorisation of the National Coordinating Council of Medication Error Reporting and Prevention (NCCMERP) was used [5]. Potential drug-drug interactions (pDDIs) were assessed by the Drug.com interaction checker and classified into no interaction, minor, moderate, and major [36]. The data obtained was cleaned and coded and then entered into Statistical Package for Social Sciences (SPSS) version 20 (IBM Statistics, Armonk, NY, USA) for analysis. Descriptive statistics were applied, and results were presented as frequency, percentages, mean, and standard deviation. Inferential statistics, including the Kruskal Wallis, Mann-Whitney U and Pearson correlation, were employed, and a p-value of &lt; 0.05 was considered statistically significant.