Evidence map›Paper›PMID 39991418›Full record

ArticleCureus2025

Descriptive Analysis of Inpatient Pharmacist Interventions at a Tertiary Care Military Hospital in Eastern Province, Saudi Arabia.

Saleh H Almutairi, Wafa K Alanazi, Rahayef N Alotaibi, Manar H Alonayzan

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Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Saleh H AlmutairiDepartment of Hospital Material and Management, King Fahd Military Medical Complex, Dhahran, SAU.
Wafa K AlanaziDepartment of Pharmaceutical Services, King Fahd Military Medical Complex, Dhahran, SAU.
Rahayef N AlotaibiDepartment of Pharmacy Practice, King Faisal University, Al Ahsa, SAU.
Manar H AlonayzanDepartment of Pharmacy Practice, King Faisal University, Al Ahsa, SAU.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background  Medication errors can be categorized into five main categories: prescribing, compounding, dispensing, distribution, and administration. Prescribing errors, including wrong indication, dose, frequency, and route of administration, are the most prevalent preventable medication errors. Over the past decades, pharmacists' role in minimizing such errors has grown with the development of pharmaceutical care. Thus, emphasizing pharmacists' interventions regarding prescribed medications is essential. Aims  This study evaluated the frequency and types of medication errors addressed by in-patient pharmacists, as well as the acceptance of these interventions by physicians at King Fahd Military Medical Complex (KFMMC) in Dhahran, Saudi Arabia. Methods This is a retrospective study that analyzed data on inpatient pharmacists' interventions at KFMMC. All inpatient prescriptions from January to December 2022 were involved in the study. Primary data collected from the inpatient pharmacy system include pharmacist intervention type, doctor's action, ward, dosage, medication classification, and whether it falls under high-alert medication. Data was tabulated in Excel (Microsoft, Redmond, WA, USA) and analyzed using SPSS version 27 (IBM Corp., Armonk, NY, USA). Results A total of 9594 pharmacy interventions were analyzed. Approximately 1300 (13.6%) of the pharmacist interventions were approved by the physicians. The rate of clinical intervention was 563 (5.9%). More than half of the interventions were from the specialty ward (N=5261; 55.1%). The intervention rate for intravenous dosage was 4837 (50.4%), and 2028 (21.1%) of the medication was considered high alert. The top three most common medication interventions were related to nutrition and blood (N=2268; 23.6%), followed by antimicrobial medications (N=2243; 23.4%) and gastrointestinal medications (N=1731; 18%). Moreover, most of the clinical interventions were related to antimicrobial medicines. No significant relationships were observed between the medication classes and the doctor's action (p=0.087).  Conclusion This study highlights the critical role of pharmacist intervention in reducing medication errors. Nutrition and blood medications were most prescribed due to the critical conditions of hospitalized patients, while antimicrobial prescriptions required pharmacist input to optimize therapy and address drug resistance. Pharmacist intervention detected significant errors such as wrong dose, duplication, and frequency, improving patient outcomes and collaboration with physicians, ultimately enhancing healthcare quality at KFMMC. Future research should analyze outpatient pharmacist interventions and strategies for addressing pending interventions.

Indexed as

inpatient pharmacyinpatient unitsmedications errorspharmacist interventionssaudi arabia

Identifiers

PMID39991418
PMCPMC11847578

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.