Capture and Documentation of Coded Data on Adverse Drug Reactions: An Overview

Paul, Lindsay; Robinson, Kerin

doi:10.1177/183335831204100304

Cited by 10 publications

(9 citation statements)

References 84 publications

(101 reference statements)

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“…A review of the available literature indicates that different coding systems are used for documenting DA information in EHRs, including International Classification of Diseases (ICD) [ 44 , 51 ], Systematized Nomenclature of Medicine, Clinical Terms (SNOMED CT) [ 49 ], RxNorm, and National Drug File-Reference Terminology (NDF-RT) [ 50 ]. Sometimes mapped coding schemes are used to add functionality.…”

Section: Resultsmentioning

confidence: 99%

Clinical Decision Support Systems for Drug Allergy Checking: Systematic Review

Légat¹,

Laere²,

Nyssen³

et al. 2018

J Med Internet Res

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BackgroundWorldwide, the burden of allergies—in particular, drug allergies—is growing. In the process of prescribing, dispensing, or administering a drug, a medication error may occur and can have adverse consequences; for example, a drug may be given to a patient with a documented allergy to that particular drug. Computerized physician order entry (CPOE) systems with built-in clinical decision support systems (CDSS) have the potential to prevent such medication errors and adverse events.ObjectiveThe aim of this review is to provide a comprehensive overview regarding all aspects of CDSS for drug allergy, including documenting, coding, rule bases, alerts and alert fatigue, and outcome evaluation.MethodsThe Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed as much as possible and searches were conducted in 5 databases using CPOE, CDSS, alerts, and allergic or allergy as keywords. Bias could not be evaluated according to PRISMA guidelines due to the heterogeneity of study types included in the review.ResultsOf the 3160 articles considered, 60 met the inclusion criteria. A further 9 articles were added based on expert opinion, resulting in a total of 69 articles. An interrater agreement of 90.9% with a reliability Κ=.787 (95% CI 0.686-0.888) was reached. Large heterogeneity across study objectives, study designs, study populations, and reported results was found. Several key findings were identified. Evidence of the usefulness of clinical decision support for drug allergies has been documented. Nevertheless, there are some important problems associated with their use. Accurate and structured documenting of information on drug allergies in electronic health records (EHRs) is difficult, as it is often not clear to healthcare providers how and where to document drug allergies. Besides the underreporting of drug allergies, outdated or inaccurate drug allergy information in EHRs poses an important problem. Research on the use of coding terminologies for documenting drug allergies is sparse. There is no generally accepted standard terminology for structured documentation of allergy information. The final key finding is the consistently reported low specificity of drug allergy alerts. Current systems have high alert override rates of up to 90%, leading to alert fatigue. Important challenges remain for increasing the specificity of drug allergy alerts. We found only one study specifically reporting outcomes related to CDSS for drug allergies. It showed that adverse drug events resulting from overridden drug allergy alerts do not occur frequently.ConclusionsAccurate and comprehensive recording of drug allergies is required for good use of CDSS for drug allergy screening. We found considerable variation in the way drug allergy are recorded in EHRs. It remains difficult to reduce drug allergy alert overload while maintaining patient safety as the highest priority. Future research should focus on improving alert specificity, thereby reducing override rates and alert fatigue. Als...

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Section: Resultsmentioning

confidence: 99%

Clinical Decision Support Systems for Drug Allergy Checking: Systematic Review

Légat¹,

Laere²,

Nyssen³

et al. 2018

J Med Internet Res

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“…Evidence from several reports suggests ADRs are underestimated in HES data. 12 14 48 Suggested reasons for under-estimation include under-recognition, under-recording and the limited scope of the relevant ICD-10 codes. 14 Variation in coding practice by hospital/trust is also possible, but as our sample size was large, this is unlikely to be an important confounder.…”

Section: Discussionmentioning

confidence: 99%

Are primary care factors associated with hospital episodes for adverse drug reactions? A national observational study

et al. 2015

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ObjectiveIdentification of primary care factors associated with hospital admissions for adverse drug reactions (ADRs).Design and settingCross-sectional analysis of 2010–2012 data from all National Health Service hospitals and 7664 of 8358 general practices in England.MethodWe identified all hospital episodes with an International Classification of Diseases (ICD) 10 code indicative of an ADR, in the 2010–2012 English Hospital Episode Statistics (HES) admissions database. These episodes were linked to contemporary data describing the associated general practice, including general practitioner (GP) and patient demographics, an estimate of overall patient population morbidity, measures of primary care supply, and Quality and Outcomes Framework (QOF) quality scores. Poisson regression models were used to examine associations between primary care factors and ADR-related episode rates.Results212 813 ADR-related HES episodes were identified. Rates of episodes were relatively high among the very young, older and female subgroups. In fully adjusted models, the following primary care factors were associated with increased likelihood of episode: higher deprivation scores (population attributable fraction (PAF)=0.084, 95% CI 0.067 to 0.100) and relatively poor glycated haemoglobin (HbA1c) control among patients with diabetes (PAF=0.372; 0.218 to 0.496). The following were associated with reduced episode likelihood: lower GP supply (PAF=−0.016; −0.026 to −0.005), a lower proportion of GPs with UK qualifications (PAF=−0.035; −0.058 to −0.012), lower total QOF achievement rates (PAF=−0.021; −0.042 to 0.000) and relatively poor blood pressure control among patients with diabetes (PAF=−0.144; −0.280 to −0.022).ConclusionsVarious aspects of primary care are associated with ADR-related hospital episodes, including achievement of particular QOF indicators. Further investigation with individual level data would help develop understanding of the associations identified. Interventions in primary care could help reduce the ADR burden. ADRs are candidates for primary care sensitive conditions.

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“…A number of research papers published in the Health Information Management Journal (HIMJ)have explored the quality of health data in this context. For example, Paul and Robinson (2012) highlighted such concerns in their discussion of the impact of poor documentation of drug allergy in the patient's medical record, the under-reporting of adverse drug reactions and incomplete coding. Another study examined mortality data, an essential element for health service planning, where poor quality of cause of death coding was attributed in part to documentation errors in death certificates (Haghighi et al2013).…”

Section: Joanne Callenmentioning

confidence: 99%

What is the Impact of Electronic Health Records on the Quality of Health Data?

Callen

2014

HIM J

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Capture and Documentation of Coded Data on Adverse Drug Reactions: An Overview

Cited by 10 publications

References 84 publications

Clinical Decision Support Systems for Drug Allergy Checking: Systematic Review

Clinical Decision Support Systems for Drug Allergy Checking: Systematic Review

Are primary care factors associated with hospital episodes for adverse drug reactions? A national observational study

What is the Impact of Electronic Health Records on the Quality of Health Data?

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