article · Tanzania Medical Journal
An evaluation across 44 hospitals in Dar es Salaam examined the adoption and functional design of electronic pharmacy information systems. Only about one third of the surveyed hospitals maintained systems that met recommended functional standards. While basic features such as managing patient data were present in nearly three quarters of the facilities, advanced tools to support clinical decision-making were entirely absent. Consequently, health workers reported zero use of decision support features like alerts for drug interactions or allergies. The practical utilisation of existing system functions was highest for patient records and medication administration, but remained low for prescribing and dispensing. Factors linked to higher system usage included working in private hospitals, receiving supportive supervision, possessing over a year of experience with the system, and having an on-site information and communications technology team of at least nine staff members.
Medication errors contribute significantly to hospitalisations globally. Electronic pharmacy systems can prevent these mistakes by alerting clinicians to dangerous drug interactions or incorrect dosages. Understanding that healthcare facilities currently lack these critical clinical decision tools highlights where technical upgrades and institutional support are needed to safeguard patient health.
The findings point to an immediate market opportunity for software developers and health informatics vendors to supply clinical decision support modules to hospital pharmacies. These applications are currently missing in the evaluated market despite existing baseline electronic systems. Adoption could be targeted at hospital administrators, supported by dedicated training and on-site technical support teams.
AI-generated from the published abstract. Always read the original work before citing.
Background The effective use of well-designed electronic Pharmacy Information Systems (ePIS) is critical in supporting clinical decision-making and detecting medication errors in hospital settings. These systems play a vital role in preventing medication errors, a significant factor contributing to patient safety. Globally, 6% of hospitalizations result from such errors. In this study, we aimed to assess the design, usage level and predictors of ePIS adoption in hospitals in Dar es Salaam, Tanzania. Methodology A cross-sectional survey was conducted from November 2019 to January 2020 across 44 (86%) eligible hospitals in Dar es Salaam to assess the proportion meeting recommended ePIS standards. Functionalities were categorized into four classes: patient data, prescription, clinical decision support (including alerts for drug interactions, allergies, dosages, indications, and side effects), and dispensing and administration. Additionally, the usage level of these functionalities among healthcare providers was evaluated using a self-reported questionnaire. Adjusted odds ratios (AOR) with 95% confidence intervals (CI) identified independent predictors of ePIS usage levels. Results About one-third of the assessed hospitals had ePIS with recommended functionalities. The most common were patient data (74%), followed by medication dispensing and administration (42.2%), and prescription (24.1%), with none supporting clinical decision-making. Utilization was high for patient data (64.9%), medication administration (47.2%), and prescription and dispensing (21.9%). No respondents used clinical decision support systems. High ePIS usage was associated with receiving supportive supervision (AOR=1.91 [1.18-3.15]), using ePIS for over a year (AOR=2.35 [1.39-4.00]), working in a private hospital (AOR=1.77 [1.06-2.97]), being male (AOR=1.65 [1.02-2.66]), being a nurse (AOR=2.04 [1.16-3.59]), and working in a hospital with an ICT staff size of nine or more (AOR=2.22 [1.33-3.69]) Conclusion Most adopted ePIS functionalities were not aimed at clinical decision-making, and their utilization is notably low. Adherence to established guidelines and regular monitoring of system and user performance are needed.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.4314/56hdjj57
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
