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 Table of Contents  
Year : 2023  |  Volume : 11  |  Issue : 1  |  Page : 26-35

Identification and characterization of preventable adverse drug events in family medicine clinics from central Saudi Arabia

1 Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
2 Department of Family Medicine and Polyclinic, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
3 Executive Department of Organization Development, First Health Cluster, Ministry of Health, Riyadh, Saudi Arabia

Date of Submission06-Mar-2022
Date of Decision25-Aug-2022
Date of Acceptance21-Nov-2022
Date of Web Publication09-Jan-2023

Correspondence Address:
Ghadah A Assiri
Department of Clinical Pharmacy, College of Pharmacy, King Saud University, P.O. Box 2454, Riyadh, 11451
Saudi Arabia
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/sjmms.sjmms_124_22

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Background: Medication errors can result in adverse drug events (ADEs) and cause considerable patient harm. Limited data are available from Saudi Arabia and the Middle East regarding the prevalence of preventable adverse drug events (pADEs) in primary care settings.
Objectives: To estimate the period prevalence of pADEs and assess the medication error severity in primary care setting in Saudi Arabia.
Methods: This retrospective study is a continuation of a previous study where 117 of 2000 adult patients managed at the Family Medicine clinics of King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia, were identified to have had least one medication error in the past 15 months. The electronic health records of these 117 patients were analyzed for a 3-month post-medication error period to explore the presence of pADE. Medication errors were categorized according to the National Coordinating Council for Medication Error Reporting and Prevention index (NCC MERP) and the occurrence of pADE was assessed using the NCC MERP scheme.
Results: Of the included 117 patients, 9 (7.7% [95% confidence interval (CI): 2.79–12.59]) experienced pADE (Category E), while 108 (92.3% [95% CI: 87.97–98.35]) did not (Category C). All patients who experienced pADE were using over-the-counter medications and were on polypharmacy. Outcomes 2a and 2b (asthma and β-blocker) accounted for two and four cases, respectively, while Outcomes 6 (warfarin and international normalized ratio), 7 (lithium and lithium level), 16 (new oral anti-coagulant or warfarin and antiplatelet), and 17 (acetylsalicylic acid [aspirin] and antiplatelet) each accounted for one case.
Conclusions: This study provides the period prevalence of patients with pADEs from Family Medicine clinics at a major tertiary hospital of Saudi Arabia, and highlights the need for a multicenter study of clinically important medication errors at the prescribing and monitoring stages for the development of quality improvement programs.

Keywords: Adult, adverse drug event, electronic health records, adverse drug reaction reporting systems, primary health care, medication errors, preventable

How to cite this article:
Assiri GA, Bin Shihah AS, Alkhalifah MK, Alshehri AS, Alkhenizan AH. Identification and characterization of preventable adverse drug events in family medicine clinics from central Saudi Arabia. Saudi J Med Med Sci 2023;11:26-35

How to cite this URL:
Assiri GA, Bin Shihah AS, Alkhalifah MK, Alshehri AS, Alkhenizan AH. Identification and characterization of preventable adverse drug events in family medicine clinics from central Saudi Arabia. Saudi J Med Med Sci [serial online] 2023 [cited 2023 Mar 26];11:26-35. Available from: https://www.sjmms.net/text.asp?2023/11/1/26/367379

  Introduction Top

Adverse drug events (ADE), defined as an "injury resulting from medical intervention related to a drug,"[1] can often be predictable and dose dependent. On the other hand, preventable ADEs (pADEs), which are "an injury that is the result of an error at any stage in the medication use" and are also known as error-related adverse event/medication error-associated harm, are a significant concern, as they can lead to hospitalization, emergency department visits, prolongation in the length of hospital stay, and incurrence of additional healthcare costs.[1],[2],[3],[4],[5]

According to the World Health Organization (WHO), medication errors are a leading cause of preventable harm to patients worldwide, and its associated costs are estimated at US$42 billion annually.[6] In the United States alone, 1.5 million pADEs are reported each year.[7] In other studies, the rate of pADEs have been found to be 12% and 11% in hospitalized and outpatient/ambulatory care patients, respectively.[8],[9] The differences in the rate of pADEs across published studies is likely due to variations in definition, population, and preventability criteria.[10]

In Saudi Arabia, a multicenter cohort study found that the incidence of ADEs in hospital settings was 6.6%.[11] However, to the best of the authors knowledge, limited data are available in Saudi Arabia and the Middle East regarding the prevalence and outcomes of pADEs in primary care, even though the bulk of drug use occurs in these settings: one study analyzed the prescribing errors in primary care, while the others only investigated drug-related problems that lead to hospitalization.[12],[13]

In our previous study, where the period prevalence of clinically important medication errors at the prescribing and monitoring stages was investigated among adults managed at the Family Medicine clinics at King Faisal Specialist Hospital and Research Center (KFSHRC), Riyadh, Saudi Arabia, the overall period prevalence of patients with at least one medication error in the past 15 months was 5.85% (95% CI 4.8–6.9);[14] the prescribing and monitoring stages used the definition by the pharmacist-led information technology intervention for medication errors (PINCER) trial.[15],[16],[17] Those findings showed that clinically important medication errors are not only common but also have the potential to harm patients,[14] thereby highlighting the need to extend the research, which would be in line with the WHO's Global Patient Safety Challenge.[6],[18] Accordingly, a continuation of the previous study was conducted with the aim of estimating the period prevalence of pADE and assessing medication error preventability and severity at the Family Medicine clinics in KFSHRC.

  Methods Top

The manuscript follows the Strengthening the Reporting of Observational studies in Epidemiology (STROBE) checklist. The study was approved by the institutional Office of Research Affairs.

Study design, setting, and participants

This retrospective study included all the 117 adult (≥18 years) patients who were found to have at least one medication error in the past 15 months in our previous study. The settings and the inclusion/exclusion criteria have been explained previously. In brief, the patients were included irrespective of their nationality and if they had been registered with the Family Medicine clinics in KFSHRC for at least 15 months before data extraction and had a record of at least one prescribed or over-the-counter (OTC) medication.[14]

For the current study, the electronic health records (EHRs) of all the included patients were analyzed for a 3-month period after the occurrence of a medication error to explore the presence of pADE. Patients were excluded if they had not returned for follow-up during this 3-month post-medication error period.


To examine for medication errors that might have resulted in patient harm, the following variables were considered:[19]

  1. The occurrence of preventable harm (binary outcome):

    1. Absence of pADE: National Coordinating Council for Medication Error Reporting and Prevention (NCC MERP) categories A–D
    2. Presence of pADE: harm caused by the use of a drug as a result of an error or medication related harm due to error.[19] NCC MERP categories E–I

  2. Medication error severity:

    Assessment tool: The NCC MERP scheme was used [Figure 1].[19]
Figure 1: The National Coordinating Council for Medication Error Reporting and Prevention (NCC MERP) Scheme.[19] ©2021 National Coordinating Council for Medication Error Reporting and Prevention

Click here to view

Data collection tool and process

A paper-based data collection form was used [Appendix 1]. The information from the paper-based data collection tool was transferred to a Microsoft Excel spreadsheet for analysis. No identifying information was recorded on the paper data collection forms. Data collection took 3 months (April–June 2021). The EHRs of the 117 included patients were reviewed by a primary reviewer (medical resident). Records of patients suspected of having ADE were recorded and classified according to severity. To ensure reliability and to minimize the risk of information bias,[20] data extraction for all patient records was independently undertaken by a secondary reviewer (medical resident). In addition, the occurrence of pADE was assessed through the NCC MERP scheme and the interrater agreement was assessed according to the British Medical Journal Best Practice.[19],[21] The data extraction was double-checked by the primary reviewer, and if the primary and secondary reviewers disagreed, a third reviewer was consulted (physician).

An inventory of medical record numbers and each record's code number were used in this study. The Excel datasheet was checked for errors in data entry, outliers, and missing data.

Statistical analysis

Microsoft Excel was used to manage and process data together with STATA version 14.1 (Stata Corp., College Station, Texas, USA). Descriptive statistics in terms of frequency counts and Chi-square were performed to describe the demographic characteristics. The period prevalence of patients who had at least one pADE was calculated as "the number of patients experiencing at least one pADE (numerator)/the total number of patients with medication error in the study population (denominator) (117)."[22]

To assess the agreement between the two independent data extractors, the Kappa coefficient was calculated, with values <0.40 indicating poor-to-fair agreement, 0.41–0.60 moderate agreement, 0.61–0.80 substantial agreement, and 0.81–1.00 an almost perfect agreement.[23],[24]

  Results Top

All the 117 patients returned to the clinics for follow-up during the 3-month post-medication error period, and thus were included in the analysis. The agreement between the two independent data reviewers and extractors was almost perfect (Kappa 0.82) [Appendix 2].

Proportion of pADE and their demographic characteristics

Of the 117 included patients, 9 patients (7.7% [95% CI 2.79–12.59]) experienced pADE (i. e., error with harm; Category E) and 108 (92.3% [95% CI 87.97–98.35]) did not (i.e., error with no harm; Category C) [Table 1].
Table 1: Outcome measures and preventable adverse drug events[15],[16],[17]

Click here to view

Of the nine patients who experienced pADE, 66.67% were aged between 18–64 years, and approximately half of the patients were Saudi males. All these patients were using OTC medications and were on polypharmacy (i.e., five or more concurrent medications).

Of the patients who did not experience pADE, 75.93% were aged ≥65 years, and more than half of the patients were Saudi females. Most patients were using OTC medications (93.5%) and were on polypharmacy (88.9%) [Table 2].
Table 2: Demographic characteristics of patients with and without preventable adverse drug events among the study sample

Click here to view


The cases of adverse effects associated with medication errors are detailed in [Table 1]. The 10 pADE cases in the nine patients were related to the following outcomes: Outcomes 2a (n = 2) and 2b (n = 4): asthma and β-blocker; Outcome 6 (n = 1): warfarin and international normalized ratio (INR); Outcome 7 (n = 1): lithium and lithium level; Outcome 16 (n = 1): new oral anti-coagulant (NOAC) or warfarin and antiplatelet; and Outcome 17 (n = 1): acetylsalicylic acid (aspirin) and antiplatelet.

  Discussion Top

Most patients with medication errors in the current study did not experience harm. In our previous study, we had identified medications that required monitoring or were prescribed to patients with at least one medication error were aspirin and other nonsteroidal anti-inflammatory drug (NSAID), anticoagulant (warfarin), antiplatelet, antipsychotic, antimanic agent (lithium), beta (β)-blocker, and NOAC, as these medications put patients at risk of harm from possible (a) gastrointestinal (GI) bleeding, (b) asthma attack, (c) serious bleeding associated with high INR, or thromboembolic events associated with low INR, (d) lithium toxicity, (e) heart failure, or (f) stroke.[14],[15]

Of the included 117 patients, 9 had pADE (7.7% [95% (CI) 2.79–12.59]), which was higher than that reported from four primary care practice-based research networks in the United States (3.4%).[25] Although both studies used the NCC MERP scheme as an assessment tool for pADE, the variability between the findings could be attributed to the differences in study participants and setting.[25] A systematic review that assessed the types of safety incidents recorded in primary care settings found that medication incidents was one of the broader category in which the bulk on incidents were recorded.[26] From Saudi Arabia, a prospective cohort study that assessed ADEs in three public and private hospitals in Riyadh found the rate of pADEs to be 6.6% (85 pADEs from 1286 medication errors), which is similar to our result.[11] However, that study assessed all incidents of ADEs without specifying the outcome, medication, or stage.[11]

Patients with asthma and on β-blockers faced the highest risk of prescription errors.[14] As a result of prescription-error-related adverse events, the most common pADE was asthma attacks in patients with a history of asthma who had been prescribed a β-blocker. In a population-based nested case–control study using the United Kingdom Clinical Practice Research Datalink, administration of oral nonselective β-blockers for patients with asthma and cardiovascular disease was associated with a significantly increased risk of asthma exacerbations when prescribed chronically at high doses.[27] Although (cardioselective) β1-blockers, e.g., metoprolol and atenolol, are safer than nonselective β-blockers, they still should be used with caution in patients with asthma, particularly those with severe asthma.[28]

In a study that interviewed pharmacists in different community pharmacies in central Saudi Arabia, 60% reported that β-blocker is a widely prescribed drug for the treatment of asthma.[29] Given this popularity of β-blocker prescription for asthmatic patients clinically, when treating asthmatic patients with β-blockers, physicians must assess benefits and risks.[30] A recent review suggests that if there is a clinical indication for using β-blockers, highly selective β1-blockers, e.g., bisoprolol, at a lower effective dose is likely to minimize the risk of problematic nonselective β-blocker bronchospasm.[31]

In the current study, two patients developed GI bleeding after they had been prescribed warfarin or aspirin with an anti-platelet drug (clopidogrel) without the co-prescription of an ulcer-healing drug. Guidelines from both Europe and North America recommend ulcer-healing drug, i.e., proton pump inhibitor, for patients taking the combined anticoagulant–antiplatelet therapy.[32] In a cross-sectional study of 423 patients who attended the cardiac center in the Western region of Saudi Arabia, 83% of patients took only aspirin, 9% took only clopidogrel, and 8% took dual therapy of aspirin and clopidogrel.[33] Of the patients who underwent dual therapy, approximately 47% (n = 16) experienced GI side effects. Among patients on any antiplatelet agent, 33.3% were not using ulcer-healing drugs as prophylactic therapy for GI side effects.[33]

In terms of monitoring error-related ADEs, it was found that one patient developed serious bleeding associated with high INR after receiving warfarin for at least 3 months without INR monitoring. Patients on warfarin require careful monitoring of INR; there is an increased risk of clotting if the INR is below the target range. In contrast, there is an increased risk of bleeding if the INR is above the target range.[34] Previous studies in Saudi Arabia related to warfarin monitoring in outpatient clinics dealt with patients' knowledge of warfarin therapy[35] and their adherence to warfarin therapy.[36] The actual proportion of warfarin monitoring error was unknown because patients were excluded from the study if they did not have four consecutive INR readings every 4 weeks on average.[36] Moreover, in our study, one patient presented to the emergency room with self-harm after receiving lithium for at least 3 months and not having lithium levels monitored within the previous 3 months. Unmonitored lithium levels expose patients to risk of subtherapeutic levels or lithium toxicity.[37] In a previous study, in a university hospital clinic in the Eastern Province of Saudi Arabia, lithium was prescribed to 54 patients (22.3%) as a mood stabilizer with a total of 187 therapeutic drug monitoring (TDM) ordered.[38] The average number of lithium TDM per patient during the study period was 3.07 (range 1–21). The actual proportion of lithium monitoring error was unknown because patients were excluded if there was no documentation of TDM value.[38]

In previous studies in primary care and ambulatory or outpatient settings, pADE was frequently associated with similar medication groups, i.e., beta-blockers[8] and anticoagulants/antiplatelets.[39],[40]

Study strengths and limitations

Our study had several strengths. First, to ensure the reliability and accuracy of error-related adverse event occurrence and to decrease selection bias, the records of all patients with at least one medication error were reviewed by two medical residents independently. Second, we followed up with the patients for three months retrospectively. Third, the NCC MERP scheme, which has gained widespread acceptance in medication safety,[19] was used to standardize the assessment procedure for error-related adverse events in addition to BMJ Open Best Practices.[21]

Our study is not without limitations. First, the prevalence of ADE (in the population of 2000 patients) was not calculated because this study aimed to investigate the occurrence of harm in patients with at least one medication error or pADE (117 patients). Second, the results cannot be generalized, as the study was conducted in a single center. Third, the retrospective assessments of categorization and severity were limited by the information available in the electronic record and without knowing the patient's perspective. Information and documentation biases may have affected how reviewers perceive the severity of an event. Finally, we could not determine if being on polypharmacy or OTC medications increased the risk of pADE because all patients with pADE were using OTC medications and were on polypharmacy.


The implementation of the following recommendations will have the potential to reduce the number of medication errors and, in turn, pADE in the future: (a) educating, training, and updating physicians and pharmacists, especially regarding the most common medications that put the patient at risk of harm;[41] (b) placing a system wherein primary care managers ensure that the clinical pharmacists or medication safety officers routinely review new medication orders and implement ongoing medication monitoring activities that focus on optimizing medication selection and use; (c) conducting a multicenter study of the clinically important medication errors in different primary care settings in Saudi Arabia and then a quality improvement programs;[19] and (d) taking advantage of a computerized prescription process by integrating software to detect medication errors outcomes during prescription entry.[42],[43] Future research can explore the root causes of pADEs and interventions to improve the same.[44]

  Conclusions Top

This study found that 7.7% of the medication errors were pADEs of Category E. These findings highlight the need for a multicenter study of the clinically important medication errors, findings of which may help develop quality improvement programs that target errors in prescribing and monitoring, especially for patients using medications that put them at risk of harm.

Ethical considerations

Ethical approval and a waiver of informed consent were obtained from the Clinical Research Committee and the research ethics committee of the institution's Office of Research Affairs, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia (Project number: 2171 060; date of approval: May 17, 2018).

Data availability statement

The datasets generated and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.

Peer review

This article was peer-reviewed by three independent and anonymous reviewers.


The authors would like to thank Dr. Mansour A. Mahmoud, College of Pharmacy, Taibah University, Al-Madinah Al-Munawarah, Saudi Arabia, for his scientific assistance.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.


kap is the interrater agreement for two unique raters,

freq is frequency,

pop is the number assessed by both raters,

tab is to show the table of assessment, and

AS is Abdulelah bin Shihah (AS) (rater 1), MA is Mohammed Alkhalifah (rater 2).

The agreement between the two independent data extractors in the cohort study was almost-perfect agreement (Kappa 0.82). All discrepancies were resolved.

  References Top

Bates DW. Frequency, consequences and prevention of adverse drug events. J Qual Clin Pract 1999;19:13-7.  Back to cited text no. 1
Weber RJ. Medication Safety Principles and Practices. In: DiPiro JT, Yee GC, Posey L, Haines ST, Nolin TD, Ellingrod V. eds. Pharmacotherapy: A Pathophysiologic Approach, 11th ed. New York: McGraw Hill; 2020. Available from: https://accesspharmacy.mhmedical.com/content.aspx?bookid=2577&sectionid=219306468 [Last accessed November 29, 2022].  Back to cited text no. 2
Morimoto T, Gandhi TK, Seger AC, Hsieh TC, Bates DW. Adverse drug events and medication errors: Detection and classification methods. Qual Saf Health Care 2004;13:306-14.  Back to cited text no. 3
Amelung S, Meid AD, Nafe M, Thalheimer M, Hoppe-Tichy T, Haefeli WE, et al. Association of preventable adverse drug events with inpatients' length of stay – A propensity-matched cohort study. Int J Clin Pract 2017;71:e12990.  Back to cited text no. 4
Iwasaki H, Sakuma M, Ida H, Morimoto T. The burden of preventable adverse drug events on hospital stay and healthcare costs in Japanese pediatric inpatients: The JADE Study. Clin Med Insights Pediatr 2021;15:1179556521995833.  Back to cited text no. 5
Donaldson LJ, Kelley ET, Dhingra-Kumar N, Kieny MP, Sheikh A. Medication without harm: WHO's third global patient safety challenge. Lancet 2017;389:1680-1.  Back to cited text no. 6
Institute of Medicine; Board on Health Care Services; Committee on Identifying and Preventing Medication Errors; Aspden P, Wolcott J, Bootman JL, Cronenwett LR, editors. Preventing Medication Errors. Washington, D.C.: National Academies Press; 2007.  Back to cited text no. 7
Gandhi TK, Seger AC, Overhage JM, Murray MD, Hope C, Fiskio J, et al. Outpatient adverse drug events identified by screening electronic health records. J Patient Saf 2010;6:91-6.  Back to cited text no. 8
Gandhi TK, Weingart SN, Borus J, Seger AC, Peterson J, Burdick E, et al. Adverse drug events in ambulatory care. N Engl J Med 2003;348:1556-64.  Back to cited text no. 9
Hutton B, Kanji S, McDonald E, Yazdi F, Wolfe D, Thavorn K, et al. Incidence, causes, and consequences of preventable adverse drug events: Protocol for an overview of reviews. Syst Rev 2016;5:209.  Back to cited text no. 10
Aljadhey H, Mahmoud MA, Ahmed Y, Sultana R, Zouein S, Alshanawani S, et al. Incidence of adverse drug events in public and private hospitals in Riyadh, Saudi Arabia: The (ADESA) prospective cohort study. BMJ Open 2016;6:e010831.  Back to cited text no. 11
Al-Arifi M, Abu-Hashem H, Al-Meziny M, Said R, Aljadhey H. Emergency department visits and admissions due to drug related problems at Riyadh military hospital (RMH), Saudi Arabia. Saudi Pharm J 2014;22:17-25.  Back to cited text no. 12
Al Hamid A, Aslanpour Z, Aljadhey H, Ghaleb M. Hospitalisation resulting from medicine-related problems in adult patients with cardiovascular diseases and diabetes in the United Kingdom and Saudi Arabia. Int J Environ Res Public Health 2016;13:479.  Back to cited text no. 13
Assiri GA, Alkhenizan AH, Al-Khani SA, Grant LM, Sheikh A. Investigating the epidemiology of medication errors in adults in community care settings. A retrospective cohort study in central Saudi Arabia. Saudi Med J 2019;40:158-67.  Back to cited text no. 14
Avery AJ, Rodgers S, Cantrill JA, Armstrong S, Cresswell K, Eden M, et al. A pharmacist-led information technology intervention for medication errors (PINCER): A multicentre, cluster randomised, controlled trial and cost-effectiveness analysis. Lancet 2012;379:1310-9.  Back to cited text no. 15
Revised PINCER Query Library Evidence-Based Summaries; 2015. Available from: https://www.nottingham.ac.uk/primis/documents/audit-docs/evidence-based-summaries-for-health-foundation -pincer-12-07-2018.pdf. [Last accessed on 2020 Nov 11].  Back to cited text no. 16
Spencer R, Bell B, Avery AJ, Gookey G, Campbell SM, Royal College of General Practitioners. Identification of an updated set of prescribing-safety indicators for GPs. Br J Gen Pract 2014;64:e181-90.  Back to cited text no. 17
Sheikh A, Dhingra-Kumar N, Kelley E, Kieny MP, Donaldson LJ. The third global patient safety challenge: Tackling medication-related harm. Bull World Health Organ 2017;95:546-A.  Back to cited text no. 18
National Coordinating Council for Medication Error and Reporting and Prevention; 2001. Available from: https://www.nccmerp.org/types-medication-errors. [Last accessed on 2020 Dec 08].  Back to cited text no. 19
Pannucci CJ, Wilkins EG. Identifying and avoiding bias in research. Plast Reconstr Surg 2010;126:619-25.  Back to cited text no. 20
BMJ Best Practice; 2022. Available from: https://bestpractice.bmj.com/info/. [Last accessed on 2022 Nov 01].  Back to cited text no. 21
Taché SV, Sönnichsen A, Ashcroft DM. Prevalence of adverse drug events in ambulatory care: A systematic review. Ann Pharmacother 2011;45:977-89.  Back to cited text no. 22
Porta M. Kappa Index. In: A Dictionary of Epidemiology. 6th ed. New York (NY): Oxford University Press; 2014.  Back to cited text no. 23
Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977;33:159-74.  Back to cited text no. 24
Hickner J, Zafar A, Kuo GM, Fagnan LJ, Forjuoh SN, Knox LM, et al. Field test results of a new ambulatory care Medication Error and Adverse Drug Event Reporting System-MEADERS. Ann Fam Med 2010;8:517-25.  Back to cited text no. 25
Panesar SS, deSilva D, Carson-Stevens A, Cresswell KM, Salvilla SA, Slight SP, et al. How safe is primary care? A systematic review. BMJ Qual Saf 2016;25:544-53.  Back to cited text no. 26
Morales DR, Lipworth BJ, Donnan PT, Jackson C, Guthrie B. Respiratory effect of beta-blockers in people with asthma and cardiovascular disease: Population-based nested case control study. BMC Med 2017;15:18.  Back to cited text no. 27
Finks SW, Rumbak MJ, Self TH. Treating hypertension in chronic obstructive pulmonary disease. N Engl J Med 2020;382:353-63.  Back to cited text no. 28
Alotaibi HS, Shivanandappa TB, Nagarethinam S. Contribution of community pharmacists in educating the asthma patients. Saudi Pharm J 2016;24:685-8.  Back to cited text no. 29
Global Initiative for Asthma. Global Strategy for Asthma Management and Prevention; 2021. Available from: https://ginasthma.org/gina-reports/. [Last accessed on 2021 Dec 01].  Back to cited text no. 30
Bennett M, Chang CL, Tatley M, Savage R, Hancox RJ. The safety of cardioselective β1-blockers in asthma: Literature review and search of global pharmacovigilance safety reports. ERJ Open Res 2021;7:00801-2020.  Back to cited text no. 31
Barnes GD. Combining antiplatelet and anticoagulant therapy in cardiovascular disease. Hematology Am Soc Hematol Educ Program 2020;2020:642-8.  Back to cited text no. 32
Bebars A, Alhazmi A, Aldajan M, Alhujeri N, Alhaidari R. Gastrointestinal side effects of antiplatelet drugs (Aspirin and Clopidogrel) in Medina, Saudi Arabia. Int J Med Dev Ctries 2021;5:210-6.  Back to cited text no. 33
McRae HL, Militello L, Refaai MA. Updates in anticoagulation therapy monitoring. Biomedicines 2021;9:262.  Back to cited text no. 34
Wajid A, Al-Arifi MN, Al-Fadly SO, Almana F, Babelghaith S. Evaluation of patients' knowledge on warfarin therapy from outpatient anticoagulant clinic in a teaching hospital. A cross-sectional study from central Saudi Arabia. Lat Am J Pharm 2019;38:163-8.  Back to cited text no. 35
Mayet AY. Patient adherence to warfarin therapy and its impact on anticoagulation control. Saudi Pharm J 2016;24:29-34.  Back to cited text no. 36
Oxley A. Guidelines for the Management of Lithium in Acute and Primary Care Settings-Safer Lithium Therapy. NHS; 2019. Available from: https://www.lmsg.nhs.uk/guidelines/health-community/patient-safety/safer-lithium-therapy/. [Last accessed on 2021 Dec 01].  Back to cited text no. 37
Abu-Qurain H, Almashhad F, Lucca JM, Abumadini MS. A retrospective study on therapeutic drug monitoring of mood stabilizers in real-life clinical scenario. J Pharm Bioallied Sci 2020;12:351-5.  Back to cited text no. 38
Obreli-Neto PR, Nobili A, de Oliveira Baldoni A, Guidoni CM, de Lyra Júnior DP, Pilger D, et al. Adverse drug reactions caused by drug-drug interactions in elderly outpatients: A prospective cohort study. Eur J Clin Pharmacol 2012;68:1667-76.  Back to cited text no. 39
Field TS, Mazor KM, Briesacher B, Debellis KR, Gurwitz JH. Adverse drug events resulting from patient errors in older adults. J Am Geriatr Soc 2007;55:271-6.  Back to cited text no. 40
Harris Y, Hu DJ, Lee C, Mistry M, York A, Johnson TK. Advancing medication safety: Establishing a national action plan for adverse drug event prevention. Jt Comm J Qual Patient Saf 2015;41:351-60.  Back to cited text no. 41
Rodgers S. New PINCER Query Library tool to support safer prescribing. Prescriber 2013;24:11-4.  Back to cited text no. 42
Improving prescribing and medicine use. J Health Serv Res Policy 2016;21:272-8.  Back to cited text no. 43
de Lemos J, Loewen P, Nagle C, McKenzie R, You YD, Dabu A, et al. Preventable adverse drug events causing hospitalisation: Identifying root causes and developing a surveillance and learning system at an urban community hospital, a cross-sectional observational study. BMJ Open Qual 2021;10:e001161.  Back to cited text no. 44


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  [Table 1], [Table 2]


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