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What is the epidemiology of medication errors, error-related adverse events and risk factors for errors in adults managed in community care contexts? A systematic review of the international literature
  1. Ghadah Asaad Assiri1,2,3,
  2. Nada Atef Shebl4,
  3. Mansour Adam Mahmoud5,
  4. Nouf Aloudah2,
  5. Elizabeth Grant6,
  6. Hisham Aljadhey7,
  7. Aziz Sheikh8
  1. 1 Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, UK
  2. 2 Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
  3. 3 Department of Paediatrics, Faculty of Medicine, King Saud University, Riyadh, Saudi Arabia
  4. 4 Department of Pharmacy, Pharmacology and Postgraduate Medicine, School of Life and Medical Sciences, University of Hertfordshire, Hertfordshire, UK
  5. 5 College of Pharmacy, Clinical Pharmacy Department, Taibah University, Madinah, Al Madinah, Saudi Arabia
  6. 6 The Global Health Academy, Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, UK
  7. 7 Saudi Food and Drug Authority, Riyadh, Saudi Arabia
  8. 8 Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK
  1. Correspondence to Ghadah Asaad Assiri; s1373565{at}


Objective To investigate the epidemiology of medication errors and error-related adverse events in adults in primary care, ambulatory care and patients’ homes.

Design Systematic review.

Data source Six international databases were searched for publications between 1 January 2006 and 31 December 2015.

Data extraction and analysis Two researchers independently extracted data from eligible studies and assessed the quality of these using established instruments. Synthesis of data was informed by an appreciation of the medicines’ management process and the conceptual framework from the International Classification for Patient Safety.

Results 60 studies met the inclusion criteria, of which 53 studies focused on medication errors, 3 on error-related adverse events and 4 on risk factors only. The prevalence of prescribing errors was reported in 46 studies: prevalence estimates ranged widely from 2% to 94%. Inappropriate prescribing was the most common type of error reported. Only one study reported the prevalence of monitoring errors, finding that incomplete therapeutic/safety laboratory-test monitoring occurred in 73% of patients. The incidence of preventable adverse drug events (ADEs) was estimated as 15/1000 person-years, the prevalence of drug–drug interaction-related adverse drug reactions as 7% and the prevalence of preventable ADE as 0.4%. A number of patient, healthcare professional and medication-related risk factors were identified, including the number of medications used by the patient, increased patient age, the number of comorbidities, use of anticoagulants, cases where more than one physician was involved in patients’ care and care being provided by family physicians/general practitioners.

Conclusion A very wide variation in the medication error and error-related adverse events rates is reported in the studies, this reflecting heterogeneity in the populations studied, study designs employed and outcomes evaluated. This review has identified important limitations and discrepancies in the methodologies used and gaps in the literature on the epidemiology and outcomes of medication errors in community settings.

  • medication errors
  • adverse drug events
  • error-related adverse drug events
  • prevalence
  • incidence
  • risk factor

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Strengths and limitations of this study

  • This is the first systematic review on the epidemiology of medication errors and medication-associated harm in community settings. The use of the International Classification for Patient Safety conceptual framework helped with framing and organising the findings from this systematic review.

  • A rigorous and transparent process has been employed, which included no language restrictions in undertaking searches, independent screening of titles, abstracts and full-text papers, independent data extraction, and critical appraisal of included studies by two reviewers.

  • Outcomes have been reported in a variety of ways using different tools and methodology, which made it difficult to undertake any quantitative pooled summary of the results.

  • Despite the comprehensiveness of the searches, we found no data regarding errors during medication dispensing and administration. This might be due to the lack of ‘dispensing error’ and ‘administration error’ terms in our search strategy, although ‘medication therapy management’ was included as a more overarching search term.

  • There is at present no agreed, consistently applied set of confounders that should be taken into account when trying to make causal inferences.


Patient safety is a public concern in healthcare systems across the world.1 Medication errors and error-related adverse drug events (ADEs) are common and are responsible for considerable patient harm.1 More specifically, ADEs can lead to morbidity, hospitalisation, increased healthcare costs and, in some cases, death.1 It has been estimated that 5%–6% of all hospitalisations are drug-related,2 3 with one estimate suggesting that ADEs causing hospital admission in the UK occur in around 10% of inpatients; approximately half of these ADEs are believed to be preventable.4 The cost of medication errors worldwide has been estimated as US$42 billion/year.5

Since the release of To Err is Human: Building a Safer Health System by the Institute of Medicine (now the National Academy of Medicine),6 which focused on acute care settings, most patient safety research has been conducted in hospital settings.7 8 Given that international and national policy drivers are for patients to be increasingly managed in primary, ambulatory and home settings in order to realise the goals of more accessible, patient-centred and efficient healthcare,9 there is an increased sense of urgency to further focus attention on community care contexts, particularly in relation to medication safety. With an ageing population, particularly in economically developed countries, as well as the use of polypharmacy, there is a need to empower patients, particularly those with chronic diseases, to self-care safely.

The aim of this systematic review was to investigate the epidemiology of medication errors, error-related adverse events and risk factors for errors in adults managed in community care contexts (ie, primary care, ambulatory and home settings). Box 1 provides definitions of the key terms employed in this review.

Box 1

Key definitions

  • Adverse drug event (ADE): Bates et al 84 define ADE as ‘an injury resulting from medical intervention related to a drug’. 84 Some ADEs are caused by underlying medication errors and therefore they are preventable.

  • Medication error: The National Coordinating Council for Medication Error Reporting and Prevention defines a medication error as ‘any preventable event that may cause or lead to inappropriate medication use or patient harm, while the medication is in the control of the health care professional, patient, or consumer. Such events may be related to professional practice, health care products, procedures, and systems, including prescribing; order communication; product labelling, packaging, and nomenclature; compounding; dispensing; distribution; administration; education; monitoring; and use’. 85 Medication errors can result from any step of the medication-use process: selection and procurement, storage, ordering and transcribing, preparing and dispensing, administration, or monitoring.1

  • Non-prescription drugs: Medicines that can be sold legally without a drug prescription.

  • Over-the-counter (OTC) drug: The Food and Drug Administration defines OTC drugs as ‘drugs that have been found to be safe and appropriate for use without the supervision of a health care professional such as a physician, and they can be purchased by consumers without a prescription’.86

  • Prescription drug: Drugs that cannot be sold legally without a prescription.


Protocol and reporting

The study protocol was developed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, and was registered in PROSPERO.10 11 The detailed systematic review protocol has also been published.12

Eligibility criteria/study selection

Studies conducted in adults (≥18 years) who were looked after in the community and living in their own or family homes without home healthcare or nursing home were eligible for inclusion in this review. The studied patients could have been self-managing, receiving care in primary care or ambulatory care settings, or any combination of the above. Studies were included if they were population-based, cross-sectional or cohort studies, which were suitable to estimate the incidence and prevalence of medication errors or ADEs. These study designs and case–control studies were considered eligible to study risk factors for the development of error-related ADEs. Studies with prescribed and/or over-the-counter (OTC) medications as the exposure of interest were eligible.

Paediatric studies (<18 years) and studies on patients receiving care in hospital at home settings (ie, continuous medical and/or nursing care provided to patients in their own homes), in nursing homes, as hospitalised inpatients or in emergency departments (ED) were excluded. Randomised controlled trials were excluded since these could not be used to reliably assess the incidence and/or prevalence of the outcomes of interest. Existing reviews were also excluded since the focus was on the primary literature. Incompletely reported studies, for example, in the form of abstracts, were not eligible for inclusion. Studies on illegal substance abuse, herbal products and those focusing on particular medications were also excluded.

No restriction on the language of publication was employed.

Data sources and search strategy

Search terms were developed based on the systematic review protocol.12 The search terms and detailed search strategies are presented in online supplementary appendix 1. In summary, these involved identifying search terms (and their synonyms) in relation to medication safety, community care settings and study design, and combining these concepts with the Boolean operator AND to identify studies that intersected all three search concepts of interest. Examples of the search terms used included the following: for the outcome: medication safety, medication error, preventable adverse drug event and patient error; for the setting: ambulatory care, outpatient, self-care, primary healthcare and general practice; and for the study design: cohort study, cross sectional study and observational study. Six biomedical databases were searched, including the Cumulative Index to Nursing and Allied Health Literature, EMBASE, Eastern Mediterranean Regional Office of the WHO, MEDLINE, PsycINFO and Web of Science, between 1 January 2006 and 31 December 2015. Google Scholar was searched for additional studies. An international panel of experts was also contacted to identify unpublished work and research in progress (online supplementary appendix 1). The reference list of all included studies was further reviewed for additional possible eligible studies.

Supplementary file 1

The databases were searched by GAA. The title and abstracts were then independently screened for eligible studies according to the above detailed selection criteria by GAA and a second reviewer, NAS. The corresponding authors of the eligible articles were contacted if additional information was needed. Disagreements were resolved by discussion between the reviewers or by arbitration by a third reviewer, AS, if a decision could not be reached. Full-text articles were retrieved from selected studies and reviewed according to the selection criteria. Each copy of the selected studies was retrieved and the reason for excluding other studies was clearly noted.

Data extraction and risk of bias assessment

Data were independently extracted and recorded onto a customised data extraction sheet by two reviewers (GAA and NAS, or GAA and MAM). Discrepancies were resolved by discussion or by arbitration by an additional reviewer (AS), if necessary.

Key information, such as study design, study type (retrospective, prospective), population of interest, exposure of interest, outcomes of interest and main findings, was extracted.

The risk of bias assessment was independently carried out on each study by two reviewers (GAA and NAS, or GAA and NA) using the Critical Appraisal Skills Programme (CASP) quality assessment tool for cohort and case–control studies,13 and cross-sectional studies were assessed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for descriptive studies.14 Any disagreements were resolved by consensus or by arbitration by a third reviewer (AS) if a decision could not be reached. Each study was given an overall grading as being at high, medium or low risk of bias.

Data synthesis

Data were summarised in detailed data tables, which included information on the incidence, prevalence, relative risk and ORs, together with 95% CIs, for each study (where available). A descriptive and narrative synthesis of the extracted data was undertaken.

The following is the definition of incidence rate used in this review: ‘the number of patients with one or more [medication error or preventable ADE] (numerator) divided by the total number of patients at risk per time unit (denominator)’. 15 The following is the definition of prevalence rate used in the data extraction: ‘the number of patients experiencing one or more [medication error or preventable ADE] (numerator) divided by the total number of patients in the study population (denominator)’. 16 The prevalence rate per population was either reported and extracted directly from the included study or calculated from data provided in the study.

We worked with the definitions of medication errors and error-related ADEs employed in individual studies. These errors may have occurred anywhere in the medicines’ management process.1 Medication errors were described according to (1) the stage in the medicines’ management process when the error occurred, that is, prescribing, dispensing, administration and monitoring1; and (2) the type of error that occurred in each stage according to the conceptual framework for the International Classification for Patient Safety (ICPS) definitions (box 2).17

Box 2

Classification of definitions used in this systematic review

  • Administration error: ‘Any discrepancy between how the medication is given to the patient and the administration directions from the physician or hospital guidelines’.1

  • Prescribing error: ‘Medication error occurring during the prescription of a medicine that is about writing the drug order or taking the therapeutic decision, appreciated by any non-intentional deviation from standard reference such as: the actual scientific knowledge, the appropriate practices usually recognized, the summary of the characteristics of the medicine product, or the mentions according to the regulations. A prescribing error notably can concern: the choice of the drug (according to the indications, the contraindications, the known allergies and patient characteristics, interactions whatever nature it is with the existing therapeutics, and the other factors), dose, concentration, drug regimen, pharmaceutical form, route of administration, duration of treatment, and instructions of use; but also the failure to prescribe a drug needed to treat an already diagnosed pathology, or to prevent the adverse effects of other drugs’.17

  • Inappropriate prescribing: ‘The use of medicines that introduce a significant risk of an adverse drug-related event where there is evidence for an equally or more effective but lower-risk alternative therapy available for treating the same condition. Inappropriate prescribing also includes the use of medicines at a higher frequency and for longer than clinically indicated, the use of multiple medicines that have recognized drug–drug interactions and drug–disease interactions, and importantly, the under-use of beneficial medicines that are clinically indicated but not prescribed for ageist or irrational reasons’.87

  • Monitoring error: ‘Failure to review a prescribed regimen for appropriateness and detection of problems, or failure to use appropriate clinical or laboratory data for adequate assessment of patient response to prescribed theory’.17

  • Dispensing error: ‘Deviation from the prescriber’s order, made by staff in the pharmacy when distributing medications to nursing units or to patients in an ambulatory pharmacy setting’.17

  • Other discrepancies:‘Any differences between the medication described by the patient and caregivers with the drugs listed by their general practitioners (GP) or between the medications listed in the discharge letter for the primary care physician with those in the patient discharge medication list’.31 32

Risk factors were categorised as patient, healthcare professional and medication-related risk factors.

Changes from the original protocol

The following changes were made from the plans described in the research protocol12: (1) due to the large quantity of studies found during the initial search and because of medications and practice changes over the years, only studies published in the last 10 years were included: 1 January 2006–31 December 2015; (2) only studies with the incidence or prevalence rate per number of patients were included; and (3) meta-analysis was not possible due to the heterogeneity of outcomes, methods and definitions.


A total of 13 033 potentially eligible studies were identified after removing duplicates, of which 59 studies met the inclusion criteria. One additional study was identified through hand-searching. Therefore, a total of 60 studies were included in the systematic review (figure 1).

Figure 1

PRISMA flow diagram (from Moher et al 88). CINAHL, Cumulative Index to Nursing and Allied Health Literature; EMRO, Eastern Mediterranean Regional Office; RCT, randomised controlled trial. *Articles may be duplicated between the excluded groups.

One study was available only in German and one in Spanish. Those two papers were retrieved and translated into English by native speakers.18 19

The key characteristics of all included studies are presented in table 1. The quality assessments of these studies are summarised in tables 2A and 2B.

Table 1

Systematic review data extraction table

Table 2A

Systematic review quality assessment: Joanna Briggs Institute Critical Appraisal Checklist for descriptive/case series and cross-sectional

Table 2B

Systematic review quality assessment: Critical Appraisal Skills Programme for cohort study

Nine studies were conducted in Asia, 4 in Australia, 32 in Europe, 8 in North America, 5 in South America and 2 were conducted across continents (one study covering two Australian countries, three European countries, one North American country and one South American country,20 and one study across two Australian countries, four European countries, one North American country and one South American country).21 Nineteen studies were conducted in primary healthcare or general practice contexts, 15 studies in home or community settings, 16 studies in ambulatory care or outpatient settings, 5 studies in community pharmacies and 2 studies in postdischarge settings, while 3 studies used secondary data analysis.

Eleven studies enrolled adults in all age groups (>18 years), three studies reported the mean age only,22–24 one enrolled those 55 years or older,25 five enrolled those aged 60 years or older,26–30 and the majority of studies (n=40 studies, 67%) enrolled patients 65 years or older. If the study included adult and paediatric data, only relevant adult data were extracted.

The quality of the cross-sectional or descriptive studies using the JBI Critical Appraisal Checklist was high for nine studies, moderate for ten studies and low for one study. The quality of the cohort studies using the CASP quality assessment tool was high for 37 studies and moderate for 3 studies.

Different methods of medication errors and error-related adverse events identification were used in the studies, including data review (electronic/paper-based medical record review, lab review, prescription review), database analysis, patient survey (face-to-face or telephone interview and survey or questionnaire), patient self-report and home visits.

Medication errors

Incidence and/or prevalence

We found no study reporting data on the incidence of medication errors. Estimates of community setting medication error prevalence were available from 53 studies.18–21 23 24 26 27 29–73

Self-reported medication errors

The period prevalence of self-reported medication errors was measured in four cross-sectional studies by Adams et al, Lu and Roughead, Sears et al 21 and Mira et al.20 21 72 73 In the first three studies, the period prevalence was reported as 2%, 6% and 6%, respectively,20 21 72 while in Mira et al’s study 75% of elderly patients with multiple comorbidities and polypharmacy (five or more drugs) reported having made at least one mistake with their medication (including errors related to dose, similar appearance of medications and lack of understanding of the physician’s instructions).73 In this study, in 5% of cases, errors due to drug confusion had very severe consequences, requiring a visit to the emergency services or hospital admission.73 That wide differences in prevalence were seen between the first three studies and the last may be due to population factors. Mira et al’s study population comprised older polymedicated patients with multiple comorbidities. This elderly group had a greater risk of error, while the first three studies had populations including any patient over 18 years.

Medication error according to medicines’ management process

Prescribing errors

The point or period prevalence of prescribing errors was reported in 46 studies. In these studies, prescribing errors included errors in drug indications, drug–disease interactions, drug–drug interactions (DDI) and dosing error, as well as inappropriate prescribing, which was the most common error reported.


Koper et al 23 found that, on average, 2.7 medications per patient were not indicated, with a total of 94% of patients having medications prescribed by the general practitioner (GP), but not mentioned in the indication of the UpToDate.23

Drug–disease interactions or contraindications

Drug–disease interactions were measured in one study by Mand et al 33 with a prevalence of 10%.33

Drug–drug interactions

The prevalence of DDIs was measured in 11 studies and ranged from 2% to 58%.23 24 26 27 30 34–39 This could in part have been due to the fact that different DDI screening tools were used, namely DDI compendia and ePocrates RX, Thomson Micromedex program, Pharmavista database, BotPlus program of the General Council of Pharmacists’ Official Colleges, British National Formulary 2010, Italian computerised interaction database, DrugDigest, Drugs, Micromedex and Medscape.

Inappropriate prescribing

  1. The prevalence of potentially inappropriate medication (PIM) was measured in 37 studies in the elderly age group only (≥65 years) and ranged from 5% to 94%.18 19 23 26 29 37 40–70 This extremely wide range of inappropriate prescribing prevalence estimates is likely to be, at least in part, due to the different detection tools used, namely Beers 2003, the 2006 Health Plan Employer Data and Information Set, improved prescribing in the elderly tool, Medication Appropriate Index, PRISCUS and Screening Tool of Older Person’s Prescriptions criteria. Johnell and Fastbom46 and Haider et al mentioned two other specific criteria.46 48

  2. The prevalence of potential prescribing omission (PPO) was measured in five studies for the elderly age group only (≥65 years), ranging from 23% to 57%.19 51 65 66 69 PPO was detected by the Screening Tool to Alert doctors to Right Treatment and Assessing Care of Vulnerable Elders.

Dosing errors

Koper et al 23 found that overdosing and/or underdosing was found in 44% of patients.23

Monitoring errors

Monitoring errors were measured in one study by Ramia and Zeenny,71 who found that 73% of patients had incomplete therapeutic/safety laboratory-test monitoring tests.71

Other errors: discrepancy

One study found that at least one discrepancy between the medication lists from the pharmacy, the GP or the patient was present in 86.7% of patients.31 In another study, almost half of the patients (47.6%; 95% CI 40.5 to 54.7) had one or more discrepancies in medication information at discharge.32

The reported point or period prevalence of medication errors in the community settings, including self-reported medication errors, prescribing errors (indication, drug–disease interaction, DDI, dosing error and inappropriate prescribing), monitoring error and discrepancies, had a very wide range from 2% to 94%. Figure 2 shows the medication errors prevalence estimates stratified according to the settings. The highest prevalence was in primary healthcare or general practice (94%).

Figure 2

Medication errors prevalence estimates according to settings.

Risk factors

Risk factors for medication errors were either related to patients, healthcare professionals and/or medications.

Patient-related risk factors

Patient-related risk factors for the development of medication errors were discussed in 33 studies.18 20 27 29–33 37 38 40–43 48 49 51–53 55 57 58 60 62 64–67 69 70 73–75

Seven risk factors related to patients were addressed in the included studies: polypharmacy, increased age, number of diseases or comorbidities, female, low level of education, hospital admission and middle family income (table 3).

Table 3

Medication errors patient-related risk factors

Several definitions of polypharmacy existed, ranging from prescription of at least three to six medications concurrently. Twenty-six studies showed a positive association between medication error and polypharmacy,18 27 29–33 37 38 40–42 49 51–53 55 57 58 64–67 69 70 74 of which 18 mentioned the estimated OR ranging from 1.06 to 11.45.18 27 29 30 32 33 37 38 40 42 49 52 57 64–67 69

Older age (≥75 years) was associated with medication errors in 13 studies,18 27 33 38 40 48 49 51 57 65–67 69 of which 10 mentioned the OR ranging from 1.02 to 4.03.18 27 33 38 40 49 57 66 67 69

Healthcare professional-related risk factors

Nine risk factors related to healthcare professionals for the development of medication errors were identified: more than one physician involved in their care, family medicine/GP specialty, age ≥51 years, male GP, frequent changes in prescription, not considering the prescription of other physicians, inconsistency in the information and outpatient clinic visits (see table 4).27 31 42 49 52 60 67 73 74

Table 4

Medication errors healthcare professional-related risk factors

Medication-related risk factors

Medication-related risk factors for the development of medication error were multiple medication storage locations used, expired medication present, discontinued medication repeats retained, hoarding of medications, therapeutic duplication,25 no medication administration routine, poor adherence and patients confused by generic and trade names.76 In one study by Johnell and Fastbom,46 multidose drug dispensing users (ie, medicines machine-packed into unit-dose bags for each time of administration) were more exposed to all indicators of potentially inappropriate drug.46

Receiving anticoagulant therapy (OR 2.38, 95% CI 2.15 to 2.64) was strongly associated in one study to potential drug–disease interactions.33

The use of OTC and/or prescribed drugs was a risk factor in two additional studies.29 43 The use of OTC medications was associated with PIM; the OR after adjusting for age, sex, education level, partnership, per capita income and occupation was 2.5 (95% CI 1.7 to 3.6) using Beers 2003 and 1.8 (95% CI 1.2 to 2.5) using Beers 2012.29

Error-related adverse events

Error-related adverse events or preventable ADEs were mentioned in six studies.22 28 29 31 32 77 The most frequently reported consequences were ED visits and hospitalisation.

Two methods for detecting ADE were applied: an ADE monitor (ie, using computerised programs composed of rules that identified incidents suggesting that an ADE might be present)22 and using trigger tools to detect ADEs.77

Incidence and/or prevalence

One study estimated preventable ADE incidence as 15/1000 person-years.22 ACE inhibitors and beta-blockers were the most common medications associated with preventable ADE.22 The estimate of the prevalence of preventable ADE was calculated from five studies as detailed below.28 29 31 32 77

All stages of medicines’ management process

Field et al found the prevalence of error caused by patients leading to an adverse event to be 0.38%, that is, less than 1% of the overall population experienced a medication-related adverse event. They found that the majority of patient errors-related adverse events (n=129) occurred in modifying the medication regimen (42%), administering the medication (32%) or not following clinical advice about medication use (22%).77 The medications associated with more than 10 preventable ADEs were anticoagulants/antiplatelets, cardiovascular drugs, diuretics, hypoglycaemics and non-opioid analgesics.77

Error-related adverse events according to medicines’ management process

Prescribing errors

Drug–drug interaction

Obreli-Neto et al 28 found that DDI-related adverse drug reaction (ADR) occurred in 7% of patients. Warfarin, digoxin, spironolactone and acetylsalicylic acid were the drugs most commonly associated with DDI-related ADRs.28

Potentially inappropriate medication

Forty-six per cent of participants reported complaints related to ADEs by interview; 95% of these were caused by prescribed medications.29

Use of inappropriate drugs was associated with an increased risk of nursing home admission, hospitalisation, more outpatient visit days, ED visits and having ADEs or ADRs.44 52 63 68

Other errors

Adverse events (undertreatment due to deletions, ADR due to additions and DDI) related to discrepancy between the medication lists from the patient, the GP or the pharmacy were identified in 24% of patients.31 Two discrepancies were categorised as having the potential to cause severe patient harm.32

Risk factors

Risk factors for the error-related adverse events were discussed in three studies only.28 31 77

Patient-related risk factors

Field et al found that the number of regularly scheduled medications (seven or more medications) (OR 3.3, 95% CI 1.5 to 7.0) and a Charlson Comorbidity Index (CCI) score of 5 or more (OR 15.0, 95% CI 6.5 to 34.5) were both associated with higher risk of patient error leading to preventable ADE.77 Obreli-Neto et al 28 found that an age of 80 years or more (OR 4.4, 95 % CI 3.0 to 6.1, p<0.01), a CCI of 4 or more (OR 1.3, 95% CI 1.1 to 1.8, p<0.01) and consumption of five or more medications (OR 2.7, 95% CI 1.9 to 3.1, p<0.01) were associated with the occurrence of DDI-related ADRs. In addition, Tulner et al 31 found that the number of medications was significantly positively correlated with medication discrepancy adverse patient events.

Medication-related risk factors

The use of medication with narrow therapeutic indices such as warfarin was associated with an increased risk of DDI-related ADRs (OR 1.7, 95% CI 1.1 to 1.9, p<0.01).28


Summary of main findings

We sought to critically review previous studies conducted in the community of the incidence/prevalence of medication errors and associated adverse events and to identify the main risk factors. We identified 60 studies carried out in various countries providing a comprehensive assessment of the available evidence on the epidemiology of medication errors and error-related ADEs in community settings.

No relevant studies on the incidence of medication errors in these settings were found. The reported point or period prevalence of medication errors in community settings had a very wide range (ie, 2%–94%). This wide range appears, at least in part, to be due to the inconsistency in the definitions of the medication errors used in the studies, differences in populations studied, methodologies employed for error detection and different outcome measures. More than half (37 studies) of the resulting studies were regarding the prescription of inappropriate drugs within the prescribing error stage in an elderly age group using different criteria. The comparison of those criteria is challenging due to the difference in medication use, consumption and availability of those medications to patients between countries. Further work is needed to review errors occurring at administration and dispensing stages of the medicines’ management process.

As for preventable ADEs, which may in some cases occur as a result of medication errors, only one study reported error-related adverse events incidence, measured as 15/1000 person-years.22 The prevalence of preventable ADE was further reported in five other studies and varied according to the medication error type that resulted in the adverse event.

The most common patient-related risk factors for both medication errors and preventable ADEs mentioned were the number of medications used by the patient and the increased age of patients.

Strengths and limitations

The main strength of this systematic review is that a rigorous and transparent process has been employed, which included no language restrictions, an independent screening of titles and abstracts, independent data extraction and critical appraisal of included studies by two reviewers. It is the first review undertaken within community settings. The use of the ICPS conceptual framework,17 which provides a comprehensive definition of each concept and type of error in the medicines’ management process, is a further strength.

However, several limitations need to be considered. First, despite the thorough process, no data were found regarding the dispensing error stage. This might be due to the lack of a ‘dispensing error’ key term in our search strategy, although ‘medication therapy management’ as a key term was included. However, 10 studies on dispensing errors were excluded because they failed to satisfy the inclusion criteria on one or more counts. Second, no data were found regarding the administration error stage. However, 14 studies on administration errors were also excluded for the same previous reason. Third, this systematic review had different outcomes reported in a variety of ways using different tools and methodology, which made combining results in one meta-analysis difficult. Lastly, the studies addressed risk factors adjusted for different confounders, which makes it difficult to generate comparable estimates and/or make causal inferences about whether the harm resulted from the medication error.

Comparison of the findings with previous studies

The definitional variation issue is supported by another two reviews.78 79 Other systematic reviews focusing on the safety of primary care contexts only have identified studies with vastly different prevalence estimates of the rates of medication errors. These reflect differences in definitions, sampling strategy and populations studied; none have investigated the risk factors for medication errors.80 81

Implications for research, policy and practice

There is a need for (1) improvement in the quality of research in this area—it is important that all researchers provide a standardised set of outcome measures of medication errors or internationally accepted terminology and definitions of key concepts; (2) training and monitoring of healthcare professionals with the involvement of medication safety pharmacists in the community; (3) empowering and educating the patients and the public, particularly those with chronic diseases and polypharmacy, to increase their knowledge of medication safety with a record of the current medication list for each patient; (4) patient use of tools and technology particularly for monitoring and follow-up; and (5) encourage the reporting of medication errors, administration errors and dispensing errors.82 This would strengthen the quality of research, improve the development of strategies to detect and prevent these errors, and provide a safer environment for the community to self-care safely.


We found a very wide variation in the medication error and error-related adverse events rate between studies, which, at least in part, reflects differences in their definitions, methodologies employed for error detection or clinical heterogeneity, that is, differences in populations studied and different outcome measures. Most of the studies were conducted on elderly populations in economically developed countries. There is therefore clearly a need to extend this work to low-income and middle-income countries, particularly give the WHO’s recent launch of a Global Medication Safety Challenge.82 83 Furthermore, most studies focused only on inappropriate prescribing with relatively little attention to other stages such as administration and dispensing. The most common patient and medication-related risk factors for both medication errors and preventable ADEs were the number of medications used by the patient, increased age and receiving anticoagulant therapy. The most common healthcare professional-related risk factor for medication error was when more than one practitioner was involved in the care of patients and care provision by family medicine and GP specialities.

This study has identified important limitations and discrepancies in the methodology used to study medication errors and error-related ADEs in community settings. These findings need to be considered in the context of designing future research related to medication safety. More research is needed in the areas of incidence of medication errors, administration error and dispensing errors and reporting. Researchers should use a more consistent set of definitions and outcomes in order to facilitate collation and synthesis of data.

Ethics and dissemination

The systematic review protocol was published in BMJ Open on 31 August 2016 and is registered with PROSPERO, an international prospective register of systematic reviews.11 12 It is reported using PRISMA. Trial registration number: CRD42016048126.


We are grateful to Marshall Dozier for her help with formulating the search strategy; Kathrin Cresswell and Andrea Fuentes Pacheco for non-English studies' translation; and the experts in the field for unpublished and in progress work and experts within the Farr Institute.


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View Abstract


  • Contributors GAA conceived the idea for this review, conducted the systematic literature search, study inclusion, data extraction and quality assessment. NAS participated in the study inclusion, data extraction and quality assessment. MAM participated in data extraction. NA participated in data extraction and quality assessment. GAA led the writing and drafting of the manuscript, and this was commented on critically by AS, EG, HA and NAS.

  • Funding The systematic review protocol is part of GAA’s PhD study at The University of Edinburgh. King Saud University, College of Pharmacy funded the scholarship. AS is supported by the Farr Institute. The project was financially supported through Prince Abdullah bin Khalid Celiac Disease Research Chair, Vice Deanship of Research Chairs, King Saud University and The University of Edinburgh.

  • Competing interests None declared.

  • Patient consent Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement All available data can be obtained by contacting the corresponding author.

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