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

Study setting

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.
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.
Study population
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 <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.
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. 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.

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 < 0.05 was considered
statistically significant.