Associated Factors and Predictors of Medication Errors in Saudi Arabia: A Systematic Review

Abstract

Background: Medication errors pose significant health risks and economic burdens globally. In Saudi Arabia, the reported error rates range from 1.6% to 84.8%; yet, the contributing factors remain inadequately understood. This systematic review aims to identify the associated factors and predictors of medication errors across Saudi healthcare settings. Methods: Electronic databases (EMBASE, CINAHL, and PubMed) were searched for peer-reviewed articles published from January 2010 to January 2025. Studies reporting statistically significant factors associated with medication errors or error reporting in Saudi Arabia were included. A quality assessment was conducted using the Appraisal tool for Cross-Sectional Studies (AXIS). Results: Thirteen studies met the inclusion criteria. Healthcare-worker-related factors included age (workers < 35 years are more prone to errors), experience level (4–5 years optimal for reporting), negative attitudes toward errors (AOR = 14.08), and a lack of training (AOR = 7.29). Patient-related factors included advanced age (1.0–2.7-times increased risk), males, polypharmacy (1.1–5.3-times increased risk), and high-risk medications (hypoglycemic drugs, warfarin, and antibiotics). System-related factors included day shift timing (AOR = 1.1), oral medication route (AOR = 0.4), ICU setting (3.3-times increased risk), medical unit setting (1.7-times increased risk), confusing packaging, and look-alike/sound-alike medications. Conclusions: Our findings emphasize that medical errors arise from a complex interplay between healthcare-worker-related factors (age, experience, and attitudes) and hospital-administration-related factors (reporting mechanisms, documentation practices, shift timing, and workload).

1. Introduction

Globally, more than 3 million deaths occur annually due to unsafe care, 50% of which is preventable [1]. Of these, half are attributed to medication errors [2,3]. The implications of medication errors are considerable, leading to higher rates of illness and death, along with extended hospitalizations. They are considered one of the most frequent medical mistakes in practice. The financial impact of medication errors is also substantial, with global annual costs estimated at US$42 billion [4]. These costs include expenses for extra treatments, hospital readmissions, legal costs, and decreased productivity [5].

Deaths due to in-hospital medication errors in the US remain a significant concern, with approximately 7000 annual fatalities reported due to preventable errors primarily linked to high-risk drugs like anticoagulants, opioids, and IV-administered medications. However, the recent data from 2018 to 2023 on fatal trends are fragmented and limited in scope [6,7,8]. While medication errors are a well-explored issue globally, the literature within the Kingdom of Saudi Arabia (KSA) remains comparatively recent and fragmented. This review addresses this regional gap by focusing exclusively on Saudi-based studies, offering a localized synthesis of patterns, risk factors, and reporting attitudes. This is especially important as healthcare infrastructure and patient safety practices vary significantly by region. In the UK, the annual rate of hospital admissions indicates that medication administration errors increased by 32.0% (from 184.21 (95% CI 183.0 to 185.4) in 1999 to 243.18 (95% CI 241.9 to 244.4) in 2020) per 100,000 persons [9]. Moreover, more than 237 million medication errors are made annually in England, the avoidable consequences of which cost the National Health Service more than 1700 lives yearly [5].

The medication error rate among hospitalized patients in Saudi Arabia from 2013 to 2024 is no different, with reported rates ranging from approximately 1.6% [6] to 84.8% [7]. Avoidable medication errors significantly strain the financial resources of the nation’s healthcare system despite the lack of detailed statistics [8,9]. As such, medication errors remain a significant issue in healthcare facilities in Saudi Arabia. Despite ongoing efforts to reduce these occurrences, they still pose a risk to patient safety [10,11,12,13]. Therefore, it is critical that we tackle this concern by identifying the associated factors and predictors of medication errors in the country. Healthcare providers, researchers, and policymakers should be made aware of these factors to mitigate further harm.

In this systematic review, we specifically focused on studies that statistically analyzed factors/variables for their association with medication error. We considered the combination of medication-error-reporting methods as a proxy for medication errors based on previous suggestions [14,15]. Thus, studies with medication error reporting as the dependent variable were also included. This work represents an initial attempt to understand the contributing factors of medication errors in Saudi Arabia, recognizing that the factors reported in US- and UK-based studies may not closely reflect the situation in Saudi hospitals due to fundamental differences in key aspects of the healthcare system in this region, such as the ratio of healthcare professionals (physicians (MDs), nurses (RNs), pharmacists, and pharmacy technicians) to the general population and drug prescribing patterns. Therefore, this review aims to identify these factors across Saudi medical care settings, including hospitals, primary care, and various specialties.

2. Materials and Methods

This study used EMBASE, CINAHL, and PubMed for retrieving peer-reviewed journals published between January 2010 and January 2025. This review used a search string with several keywords and Medical Subject Headings (MeSH): Saudi Arabia, Medication Error(s), Medication Incident(s), Prescribing Error(s), Drug Error(s), Administrative Error(s), and Adverse Event(s). Boolean operators “AND” and “OR” were used in combination with the phrase “Associated Factor(s)” as well as “Predictor(s)” to narrow the scope. We also identified studies by checking the reference lists of other reviews on relevant topics. This systematic review was not registered on PROSPERO; however, all procedures followed the PRISMA guidelines for conducting and reporting systematic reviews [16].

2.1. Study Selection

The articles selected for this review were based on the following inclusion criteria: (i) peer-reviewed articles of randomized controlled trials, non-randomized controlled trials, longitudinal studies, cohort or case–control studies, and descriptive studies conducted by healthcare workers in Saudi Arabia, (ii) articles published in English, (iii) articles published from January 2010 up to January 2025, (iv) articles which were available in full text, and (v) articles which included statistical significance results (p < 0.05) of associated factors and predictors of medication errors or medication error reporting. Reviews, letters, case studies, conference papers, opinions, reports, and editorial papers were excluded.

The first author conducted and documented systematic searching using a reference manager application (i.e., Mendeley). The first and second authors screened the title, abstract, and full-text articles against the inclusion and exclusion criteria. The other authors then reviewed and verified the articles included in the review.

2.2. Search Outcome

The systematic searching and screening were reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [16]. Figure 1 illustrates the flow diagram for the study selection. The search in PubMed, EMBASE, and CINAHL databases found 2003 studies. Of these, 1145 studies were duplicates and excluded during the title screening process. During the screening of the abstracts, 369 additional articles were excluded for failing to meet one or more inclusion criteria. We excluded 309 more articles during the full-text article retrieval process for similar reasons. A further 167 articles were removed for the following reasons: (i) they were review studies, (ii) they were not conducted within Saudi Arabia, and (iii) they had insufficient data. A total of 13 studies were included in the final review.

2.3. Data Extraction and Methodological Quality Assessment

The extracted data of this study was summarized into (i) authors and publication year, (ii) study objectives, (iii) study designs, (iv) study settings, (v) materials and methods, (vi) sample size, (vii) findings, and (viii) study recommendations as shown in

Table A1. Critical appraisal tool.

No.	Question	Yes	No	Don’t Know (Comment)
Introduction
1	Were the aims/objectives of the study clear?
2	Was the study design appropriate for the stated aim(s)?
3	Was the sample size justified?
4	Was the target/reference population clearly defined? (Is it clear who the research was about?)
5	Was the sample frame taken from an appropriate population base so that it closely represented the target/reference population under investigation?
6	Was the selection process likely to select subjects/participants that were representative of the target/reference population under investigation
7	Were measures undertaken to address and categorize non-responders?
8	Were the risk factor and outcome variables measured appropriate to the aims of the study
9	Were the risk factor and outcome variables measured correctly using instruments/measurements that had been trialed, piloted or published previously?
10	Is it clear what was used to determine statistical significance and/or precision estimates? (e.g., p-values, confidence intervals)
11	Were the methods (including statistical methods) sufficiently described to enable them to be repeated?
Results
12	Were the basic data adequately described?
13	Does the response rate raise concerns about non-response bias?	0	1
14	If appropriate, was information about non-responders described?
15	Were the results internally consistent?
16	Were the results presented for all the analyses described in the methods?
Discussion
17	Were the authors’ discussions and conclusions justified by the results?
18	Were the limitations of the study discussed?
Other
19	Were there any funding sources or conflicts of interest that may affect the authors’ interpretation of the results?
20	Was ethical approval or consent of participants attained?

. Additionally, risk of bias was assessed with the Appraisal Tool for Cross-Sectional Studies (AXIS) [17]. All AXIS questions can be answered with “yes”, “no”, or “don’t know”, and 1 point was awarded for each ‘yes’ response, resulting in a maximum score of 20 points.

Table 1. Methodological quality appraisal.

Authors	Q1	Q2	Q3	Q4	Q5	Q6	Q7	Q8	Q9	Q10	Q11	Q12	Q13 *	Q14	Q15	Q16	Q17	Q18	Q19	Q20	Total
Alshammari et al. [7]	1	1	1	1	1	1	1	1	1	1	1	1	1	0	1	1	1	1	0	1	18
Al Khreem & Al-khadher [18]	1	1	0	1	1	0	0	1	1	1	1	1	0	0	1	1	1	1	0	1	14
Mazhar et al. [19]	1	1	1	1	1	1	1	1	1	1	1	1	1	0	1	1	1	1	0	1	18
Aljadhey et al. [20]	1	1	1	1	1	1	1	1	1	1	1	1	1	0	1	1	1	1	0	1	18
Al-Arifi [21]	1	1	1	1	1	1	1	1	1	1	1	1	1	0	1	1	1	1	0	1	18
Tawhari et al. [22]	1	1	1	1	1	1	1	1	1	1	1	1	1	0	1	1	1	1	0	1	18
Alharaibi et al. [6]	1	1	1	1	1	1	1	1	1	1	1	1	1	0	1	1	1	1	0	1	18
Al-Maghrabi et al. [23]	1	1	0	1	1	1	0	1	1	1	1	1	0	0	1	1	1	1	0	1	15
Alsafi et al. [24]	1	1	1	1	1	0	1	1	1	1	1	1	0	0	1	1	1	1	0	1	16
Alduais et al. [25]	1	1	1	1	1	1	1	1	1	1	1	1	1	0	1	1	1	1	0	1	18
Alyaemni [26]	1	1	1	1	1	1	0	1	1	1	1	1	1	0	1	1	1	1	0	1	17
Alrasheeday et al. [27]	1	1	1	1	1	1	1	1	1	1	1	1	1	0	1	1	1	1	0	1	18
Alandajani et al. [28]	1	1	1	1	1	1	1	1	1	1	1	1	1	0	1	1	1	1	0	1	18

Yes = 1. No = 0. * = reversed scoring.

outlines the questions used in the assessment while

Table 2. Characteristics of included studies.

Author	Study Objectives	Study Design	Setting	Materials and Methods	Findings	Study Recommendations
Alshammari et al. [7]	To investigate predictors for healthcare professionals to report medication errors in Saudi Arabia	Observational cross-sectional study	Conducted in 6 regions: Hail, Al-Qassim, Al-Jouf, Al-Madinah, the eastern region, and the western region	Validated questionnaire with 37 close-ended questions on a five-point Likert scale	Significant predictors of medication error reporting: - Beliefs that medication error reports are important safety topic (p = 0.007) - Institution’s reliability filling out medication error reports (p < 0.001)	Need for interventions to address medication errors in Saudi Arabia, including regular education and training for healthcare professionals, mandatory training for new employees, and participation in symposiums on patient safety.
Al Khreem & Al-khadher [18]	To assess nurses’ perceptions of causes and reporting of medication errors	Cross-sectional study	Maternity and Children Hospital in Najran City, Saudi Arabia	Questionnaires on demographic data and reporting of medication errors	Significant factors associated with medication error reporting: - Age: Nurses aged 26–30 years have good reporting behavior compared to other age groups (p = 0.006) - Experience: Nurse with 4–5 years of experience have good reporting behavior compared to other groups (p = 0.016)	The implementation of “No Blame, No Punishment” campaigns. Adopting a medication safety officer and incorporating pharmacovigilance in health college curricula is also crucial.
Mazhar et al. [19]	To describe the frequency and type of medication reconciliation errors - To determine the associated risk factor of medication reconciliation errors	Prospective cross-sectional study	Tertiary care teaching hospital in the eastern province of Saudi Arabia	Comprehensive-structured interviews using a standard form	Significant factors associated with medication reconciliation error: - Age: Patients ≥65 years old were 2.7 times more likely to experience errors (p < 0.05) - Polypharmacy: Patients with multiple prescriptions were 5.3 times more likely to experience errors (p < 0.05)	A higher authority at each institution should also encourage participation in symposiums on patient safety and drug safety.
Aljadhey et al. [20]	To determine the incidence of adverse drug events (ADEs) and their severity and preventability	Prospective cohort study	Setting	Trained clinical pharmacists using a study manual for incident assessment, including severity and preventability classifications	Significant factors associated with ADEs (adjusted): - Medical units: Patients who were from the medical unit were 1.7 times more likely to experience error (p < 0.05)	It is recommended that the factors that lead to medication errors must be considered by policy makers, and they should set policies and strategies to overcome the factors.
Al-Arifi [21]	To assess pharmacists’ attitudes toward dispensing errors	Cross-sectional study	Conducted in 6 regions: Hail, Al-Qassim, Al-Jouf, Al-Madinah, the eastern region, and the western region	Structured self-administered questionnaire	Significant factors associated with dispensing error: - Existence of generic brand (p < 0.019) - Packaging and labeling of the product (p < 0.012) - Pharmacist fatigue (p < 0.029)	Decision makers consider the factors that lead to medication errors.
Tawhari et al. [22]	To assess incidents of medical errors at a hospital	Retrospective study	- Maternity and Children Hospital in Najran City, Saudi Arabia	- The National Coordinating Council for Medication Error Reporting and Prevention index was used to categorize the outcome of medical errors	Significant factors associated with medical error: - Gender: Males were more likely to experience errors than females (p = 0.013)	Policies and strategies must be developed to overcome the factors that are the causes of medication errors.
Alharaibi et al. [6]	To assess the prevalence, type, severity, and factors associated with prescribing errors	Retrospective database review	Tertiary care teaching hospital in the eastern province of Saudi Arabia	Medication Error Electronic Report Forms database from January 2017 to December 2018.	Significant factors associated with prescribing errors (adjusted): - Gender: Males were 1.0 times more likely to experience errors than females (p < 0.01) - Route of drug administration: Oral was 0.4 times more likely to experience errors than other methods (p < 0.01)	Staffing of clinical pharmacists in committing structured medication and reducing the risk of medication errors;
Al-Maghrabi et al. [23]	To investigate the effects of high confidence on diagnostic accuracy	Randomized controlled experiment	Setting	Eight written clinical vignettes were used for this study with the following diagnoses: stomach cancer, vitamin B12 deficiency, pulmonary thromboembolism, celiac disease, acute viral pericarditis, acute myeloid leukemia, and acute bacterial endocarditis	The study failed to display relationships between overconfidence and premature closure with diagnostic accuracy	Collaboration between healthcare providers, including nurses and physicians, on medication reconciliation to prevent unintentional discrepancies at admission in these high-risk patients.
Alsafi et al. [24]	To identify reasons for underreporting among physicians	Cross-sectional study	Conducted in 6 regions: Hail, Al-Qassim, Al-Jouf, Al-Madinah, the eastern region, and the western region	Self-administered questionnaire	Significant factors associated with medication error reporting: - Type of specialty: Obstetric physicians were more likely to report medication error compared to other specialties (p = 0.019)	Study Recommendations
Alduais et al. [25]	- To find out the barriers preventing staff from reporting medical errors - To identify the strategies which might encourage the staff to report the medical errors	Cross-sectional study	Maternity and Children Hospital in Najran City, Saudi Arabia	Self-administered questionnaire	Significant factors associated with medical error reporting: - Age: Staff in the age group of 31–40 years have more barriers to reporting medical errors compared to other age groups - Years of experience: Staff with 0–10 years and 11–20 years’ experience have more barriers to reporting medical errors compared to those with longer working experience	Need for interventions to address medication errors in Saudi Arabia, including regular education and training for healthcare professionals, mandatory training for new employees, and participation in symposiums on patient safety.
Alyaemni [26]	To assess the knowledge and attitudes about medical error disclosure and explore the factors that facilitate or hinder the disclosure	Cross-sectional survey	Tertiary care teaching hospital in the eastern province of Saudi Arabia	Self-administered questionnaire	Significant factors associated with medical error reporting: - Training level: Internal medicine residents in year 3 were 1.9 times more likely to report medical errors compared to other years of training - Type of practice: Residents in inpatient care were 0.2 times more likely to report medical errors compared to other types of practice	The implementation of “No Blame, No Punishment” campaigns. Adopting a medication safety officer and incorporating pharmacovigilance in health college curricula is also crucial.
Alrasheeday et al. [27]	To assess nurses’ perceptions of patient safety culture and its relationship with adverse events	Cross-sectional study	Setting	Three self-administered questionnaires on demographic factors, patient safety culture, and adverse events	Significant factors associated with adverse medical events	A higher authority at each institution should also encourage participation in symposiums on patient safety and drug safety.
Alandajani et al. [28]	To investigate nurses’ knowledge and attitudes toward medication errors in Saudi Arabia	Cross-sectional study	Conducted in 6 regions: Hail, Al-Qassim, Al-Jouf, Al-Madinah, the eastern region, and the western region	Online self-administered questionnaire from January to March 2022	Significant predictors of medication errors (adjusted): - Nurses with no history of attending a medication error course (AOR = 7.29, 95% CI = 2.86–18.51), poor knowledge (AOR = 4.54, 95% CI = 1.74–11.90), and negative attitude (AOR = 14.08, 95% CI = 4.69–43.47) were more likely to commit errors than their counterparts	It is recommended that the factors that lead to medication errors must be considered by policy makers, and they should set policies and strategies to overcome the factors.

summarizes its results.

The types of medication errors identified in the included studies: prescribing errors, dispensing errors, administration errors, and medication reconciliation discrepancies—other errors in this category include errors related to documentation, patient monitoring, and communication failures between healthcare professionals (physicians (MDs), nurses (RNs), pharmacists, and pharmacy technicians). These classifications are consistent with recognized frameworks such as the NCC MERP Index and ISMP guidelines [22]. This clarification ensures a clear and standardized approach to analyzing medication errors and their associated factors.

3. Results

3.1. Methodological Quality Appraisal

The quality assessment of the articles included in this review is summarized in Table 1. Of the 13 studies reviewed, most used appropriate methodological techniques except four (n = 4) [18,23,24,26]. These four studies either did not report the sample size calculation, had poor sampling methods (i.e., convenient sampling), or had poor response rates/a low sample size. All studies used validated and reliable instruments/measurements that were tested prior to data collection or adapted from previously published work. Additionally, all studies used statistical tests that were relevant to the aims/objectives of the study. Ethical approval was reported in all studies, while respondents’ consent was only reported in studies that involved subjects. Based on the scores in Table 1, nine studies scored 90% [6,7,19,20,21,22,25,27,28], while the rest scored 85% [26], 80% [24], 75% [23], and 70% [18], respectively.

3.2. Characteristics of the Included Study

Six studies included in this review were conducted in Riyadh [6,20,21,23,24,25], two studies in the southwestern region of Saudi Arabia [18,22], one study in multiple different regions of the country (i.e., northern, northwestern, western, central, and eastern) [7], one in Jeddah [28], one in the eastern province [19], and one in Hail [27], and one study did not specifically mention the exact region nor the hospital name [26]. The study sample ranged from 40 to 315,166. Most of the studies used a cross-sectional design (n = 9) [7,18,19,21,24,25,26,27,28], while two used a retrospective database review approach [6,22]. One study utilized a prospective cohort study [20] and a randomized controlled trial design [23] each.

Eight studies used questionnaires as data collection tools [7,18,21,24,25,26,27,28], while one conducted a structured interview [19]. One study assessed incidents based on a study manual [20], while another categorized the outcomes of medication errors and factors that contributed to medication errors using specified directories (i.e., The National Coordinating Council for Medication Error Reporting and Prevention Index and The Institute for Safe Medication Practices list) [22]. Additionally, one study collected data from a medication error database [6]. The experimental study, on the other hand, used vignettes as its intervention tool [23]. There was consistency in the hospital settings of the studies, with the exception of one conducted in community pharmacies [21] (see Table 2).

3.3. Associated Factors and Predictors of Medication Errors

3.3.1. Healthcare Workers

Our review reveals several significant age-related patterns affecting medication errors among healthcare workers. Interestingly, younger workers under 35 had significantly lower odds of committing errors compared to older workers (<25 years: AOR = 0.006, 95% CI = 0.000–0.102; 25–35 years: AOR = 0.048, 95% CI = 0.007–0.325) [28], suggesting increased errors associated with older healthcare workers.

Within the setting of community pharmacies and tertiary care in Riyadh, the existence of generic brands (p < 0.019) [21], confusing packaging and labeling of the product (p < 0.012) [23], look-alike/sound-alike medications (p < 0.01) [6], a lack of documented clinical information (p < 0.01) [6], physicians’ outdated medical information (p < 0.01) [6], improper medical history retrieval (p < 0.01) [6], and pharmacist fatigue (p < 0.029) [21] were all found to be significantly associated with prescribing errors.

The type of practice and specialty of the healthcare workers were found to influence how they reported errors. For example, inpatient care residents (p = 0.001) [26] and obstetric physicians (p = 0.019) [24] were more likely to report errors compared to their counterparts. Moreover, healthcare workers with 4–5 years of experience demonstrated good reporting behavior (p = 0.016) compared to those just starting or with extended experience [18].

Improved handoffs and transitions also reduced the likelihood of adverse events (OR: 0.82–0.90). Conversely, a more non-punitive response to errors was linked to increased reported adverse events (OR = 1.17, 95% CI: 1.02–1.35) [27].

3.3.2. Patients

The review shows that older patients were 1.0 to 2.7 (p < 0.05) times more likely to experience medication errors [19,20], where each increase in patients’ age was associated with a 0.9-times-greater likelihood of experiencing errors (p = 0.04) [6]. It was also found that males were more likely to experience errors than females [6,22].

Additionally, patients with multiple prescriptions (polypharmacy) had an increased error risk of 1.1 (p < 0.05) to 5.3 times (p < 0.05) based on findings from multiple studies [19,20]. Patients on high-risk medications also showed a significantly increased risk of experiencing medical errors: (1) they were 2.6 times at risk when on hypoglycemic drugs [19], (2) 3.4 times at risk when on Warfarin [19], (3) 2.9 times at risk when on antibiotic and chemotherapy agents as appropriate [6], (4) 2.6 times at risk when on antineoplastic and immunomodulating agents [6], (5) 2.3 times at risk when on systemic hormonal preparations [6], and (6) 2.3 times at risk when on high-alert medications [6].

Patients medicated orally (AOR = 0.4, 95% CI = 0.5–1.7) (p < 0.05) during the day shift from 0700 to 1900 (AOR = 1.1, 95% CI = 0.9–1.9) were at a significantly higher risk of experiencing medical errors [6] as well. Moreover, patients admitted to the intensive care unit (ICU) and medical unit were 3.3 CI with OR (p < 0.01) and 1.7 times (p < 0.05) more likely to experience error, respectively [6]. It was also found that extended hospital stays were associated with a 1.0-times likelihood of medication errors (p < 0.01).

3.3.3. Institutional Settings and Culture

Workers aged 26–30 were more likely to report medication errors than workers of older age groups [18,25]. From the attitudinal perspective, healthcare workers with a negative attitude toward medication error were more likely to commit an error (AOR = 14.08, 95% CI = 4.69–43.47) [28]. In contrast, those who believe medication reports are important showed better reporting behavior (p = 0.007) [7].

The institution’s reliability in handling error reports was also a significant predictor of medication error reporting among healthcare workers (p < 0.001) [7]. The institution-specific factors were extended to medication error rates as well, where nurses at King Fahad Hospital (AOR = 0.012, 95% CI = 0.003–0.050) and King Abdul-Aziz Hospital (AOR = 0.015, 95% CI = 0.004–0.061) reported higher rates compared to East Jeddah Hospital and King Abdullah Medical Complex [28]. Due to different categorizations, this finding slightly contrasts with Alduais et al. [25], who found that workers with less experience (0–20 years) face more reporting barriers. It was also noted that third-year medicine residents were 1.9 times more likely to report errors than younger or older residents [26]. Expectedly, the lack of medication error training courses (AOR = 7.29, 95% CI = 2.86–18.51) and poor knowledge about medication errors strongly predict error occurrence (AOR = 4.54, 95% CI = 1.74–11.90) [28].

4. Discussion

The rate of medical errors in Saudi Arabia has increased during the last decade [7] and continues to be a primary concern in healthcare settings across the country. Despite sustained efforts to minimize these incidents, they still pose a risk to patient safety [10,11,12,13]. It is essential that we address this problem by recognizing the factors and predictors linked to medication errors in healthcare settings. This systematic review analyzed 13 studies published from January 2010 to January 2025 at the time of writing. The study identified several associated factors and predictors of medical errors and medical error reporting in Saudi Arabia [6,7,18,19,20,21,22,23,24,25,26,27,28].

The finding that younger healthcare workers (under 35 years) are more likely to make medication errors than their older counterparts aligns with the broader healthcare literature. Inexperienced practitioners often lack the clinical judgment that comes with years of practice. As noted by Berk et al. [29], error rates typically decrease with increasing professional experience as clinicians develop better pattern recognition and situational awareness. The inverse relationship between experience and medication errors suggests a developmental curve in clinical practice.

The higher error reporting among workers aged 26–30 reflects either higher actual error rates or a greater compliance with reporting systems, the latter of which could be due to the recent educational emphasis on error reporting during their training. Additionally, the finding that staff with less experience face more reporting barriers than those with more experience suggests that institutional knowledge and familiarity with reporting systems improve over time. The strong association between a lack of specific training and higher error rates emphasizes the critical importance of targeted education to improve patient safety. This aligns with [6]’s research, showing that specific training programs significantly reduce medical errors by creating greater awareness for healthcare workers of potential pitfalls.

Our review also found that institutional culture and systems influence safety outcomes. The variation in error rates between hospitals [28], the institution’s reliability in handling error reports [7], and the workers’ high safety culture emphasize the importance of cultivating a supportive administrative and organizational climate within the hospital setting, as suggested by Reason [30]. The counterintuitive finding that a non-punitive response to errors was associated with higher reported adverse events likely reflects an increased willingness to report rather than actual increased incidence, a phenomenon documented by Marx in his work on the Just Culture [31]. Additionally, the specialty-specific error-reporting rates revealed in this review were likely due to the high litigation risk, high case volume, and high complexity associated with the specialties’ services (i.e., obstetric and inpatient), which presents more opportunities for errors and near-misses.

We also found that generic brands, confusing packaging, look-alike/sound-alike medications, and specific medication classes (e.g., hypoglycemic drugs, warfarin, antibiotic and chemotherapy agents as appropriate, and antineoplastics) were significant predictors of medical errors. These are aligned with the Institute for Safe Medication Practices report [32], showing that the predictors are persistent challenges in medication safety even in Saudi Arabia. The significant relationship between healthcare workers’ fatigue and error rates reinforces the robust literature on the impact of cognitive load and fatigue on the committing of errors [33,34,35]. These studies highlight the need for system-level interventions such as duty-hour restrictions and mandatory breaks.

Our review’s most significant predictor of medical error was healthcare workers’ negative attitudes toward medical error reporting (AOR = 14.08). It appears that they would not report the incidents for fear of being blamed by coworkers and superiors, facing the risk of being labeled as troublemakers, retribution, judicial issues, malpractice suits, and giving the impression of being incompetent [28,36,37].

In addition, the use of the Beers Criteria and STOPP/START criteria provides a structured approach to minimizing medication-related risks in older adults. The Beers Criteria offer a list of potentially inappropriate medications to avoid or use with caution, while the STOPP/START criteria help clinicians identify both potentially harmful prescriptions and omitted therapies that should be initiated. Incorporating these tools into routine clinical practice can enhance medication safety, support informed prescribing decisions, and reduce adverse drug events among elderly patients.

Regarding patient-related factors, it has been well-established in the patient safety literature that older patients are vulnerable to medication errors [38,39,40,41,42]. The physiological change one experiences as one ages affects medication metabolism and clearance, making dosing more complex and error-prone [38,39,40]. Similarly, an increased risk of error was noted for polypharmacy patients following the increased risks of adverse drug interactions, drug confusion, and inappropriate dosing [41,43]. The observation that males experience more medical errors than females in this review requires careful interpretation. While these findings appear inconsistent with prior studies [43,44,45], the underlying cause remains debatable. Nonetheless, Oertelt-Prigione and Regitz-Zagrosek [45] have documented gender-based variations in drug metabolism and efficacy that could contribute to different error profiles between men and women.

The higher risk of errors with oral medications compared to other routes (AOR = 0.4) with p < 0.05 may seem counterintuitive, as intravenous medications are typically considered to be of higher risk. However, this finding might reflect the volume disparity—oral medications constitute the majority of prescriptions, creating more error opportunities, as described by [46]. Similarly, the fact that most medical administrations are carried out during the day shift (07:00–19:00) could explain the significantly increased error rate during that period compared to the night shift. Extended hospital stays would also create the same effect as it widens the window for error to occur, albeit small (1.0 times). The substantially higher error risk in ICU settings (3.3 times) and medical units (1.7 times) reflects the complexity of care in these environments. This is aligned with a study that identified that ICU patients receive twice as many medications as patients in general care settings with more complex administration requirements [47].

In our review, oral medications were significantly associated with a higher risk of medication errors (AOR = 0.40, 95% CI: 0.22–0.73, p < 0.05). Although this result may seem counterintuitive, given that intravenous drugs are typically classified as high-risk due to their narrow therapeutic windows and immediate systemic effects, it is better understood in the context of prescribing frequency. Oral medications account for the majority of prescriptions in both hospital and outpatient settings, which proportionally increases the opportunities for error during prescribing, dispensing, and administration. The previous literature has reported similar trends, emphasizing that medication errors are influenced not only by the inherent risk of the administration route but also by the volume and complexity of use [47]. These findings suggest that system-level interventions such as standardized prescribing protocols, clearer labeling, and electronic decision-support tools are critical in reducing oral medication errors and enhancing patient safety.

Strengths and Weaknesses

The current review included the most recent studies conducted in Saudi Arabia, focusing solely on factors and variables statistically influencing medical errors. Having our search scope limited to only those with significant findings lends robustness to the results and provides a reliable framework for stakeholders to plan for future interventions. Nevertheless, several weaknesses are present; therefore, the conclusions drawn from the review should be viewed carefully. Limiting the search to English and omitting studies written in Arabic may have constrained identifying potentially significant research. Nevertheless, it is important to mention that English is the favored language of most professional organizations in Saudi Arabia.

5. Conclusions

Our findings collectively emphasize that medical errors arise from a complex interplay between healthcare-worker-related factors (age, experience, and attitudes) and hospital-administration-related ones (reporting mechanisms, documentation practices, shift timing, and workload). Additionally, the review highlights how patient characteristics interact with system factors to create risk profiles. The results suggest that medical error risk is determined by a complex interplay of patient vulnerability (age and comorbidities), treatment complexity (polypharmacy and high-risk medications), and the healthcare setting (type of care and workflow patterns). This multifactorial nature underscores the need for comprehensive error-reduction approaches that address workers’ competence, patients’ unique needs, and system design.

Recommendations:

(i)

Implementing targeted continuing education and simulation-based training programs on medication safety for healthcare professionals;

(ii)

Developing a national medication error-reporting registry to improve surveillance and benchmarking;

(iii)

Fostering collaborative interdisciplinary practice models;

(iv)

Incorporating medication safety competencies in undergraduate and postgraduate curricula.