ICD-10 codes used to identify adverse drug events in administrative data: a systematic review

Hohl, Corinne M.; Karpov, Andrei; Reddekopp, Lisa; Stausberg, Jürgen

doi:10.1136/amiajnl-2013-002116

Cited by 125 publications

(164 citation statements)

References 58 publications

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“…Hence, any estimated ADR incidence rates based on administrative data alone should be interpreted with caution. Nevertheless, we applied the most recent systematic review of ADR-related ICD-10 codes 18 , and limited our analysis to high-probability or very high-probability ADR diagnosis only. The study findings demonstrate a modest increase in hospitalised ADR incidence using relevant diagnosis codes in addition to external cause codes for identifying ADR-related hospitalisations.…”

Section: Discussionmentioning

confidence: 99%

“…Results: Of 493 442 hospitalisations among 267 153 study participants during [2011][2012][2013]18.8% (n = 92 953) had hospital diagnosis codes that were potentially ADR related; 1.1% (n = 5305) had high/very highprobability ADR-related diagnosis codes (causality ratings: A1 and A2); and 2.0% (n = 10 039) had ADR-related external cause codes. Overall, 2.2% (n = 11 082) of cases were classified as including an ADR-based hospitalisation on either external cause codes or high/very high-probability ADR-related diagnosis codes.…”

Section: Methodsmentioning

confidence: 99%

“…We adopted causality rating categories A1, A2, B, C and D, based on the systematic review. 18 We created an additional 'other' category for ICD codes with causality ratings other than A-D 18 and the newly added codes that did not have validated causality ratings (Supplementary Table 1). We considered diagnosis codes of A1 or A2 causality ratings as having a very high or high probability of being ADR related.…”

Section: Adr-related Diagnosis Codesmentioning

confidence: 99%

See 2 more Smart Citations

Diagnosis-based and external cause-based criteria to identify adverse drug reactions in hospital ICD-coded data: application to an Australia population-based study

Du¹,

Pearson²,

Buckley³

et al. 2017

Public Health Res Pr

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Objectives: External cause International Classification of Diseases (ICD) codes are commonly used to ascertain adverse drug reactions (ADRs) related to hospitalisation. We quantified ascertainment of ADR-related hospitalisation using external cause codes and additional ICD-based hospital diagnosis codes. Methods:We reviewed the scientific literature to identify different ICD-based criteria for ADR-related hospitalisations, developed algorithms to capture ADRs based on candidate hospital ICD-10 diagnoses and external cause codes (Y40-Y59), and incorporated previously published causality ratings estimating the probability that a specific diagnosis was ADR related. We applied the algorithms to the NSW Admitted Patient Data Collection records of 45 and Up Study participants (2011)(2012)(2013).Results: Of 493 442 hospitalisations among 267 153 study participants during [2011][2012][2013]18.8% (n = 92 953) had hospital diagnosis codes that were potentially ADR related; 1.1% (n = 5305) had high/very highprobability ADR-related diagnosis codes (causality ratings: A1 and A2); and 2.0% (n = 10 039) had ADR-related external cause codes. Overall, 2.2% (n = 11 082) of cases were classified as including an ADR-based hospitalisation on either external cause codes or high/very high-probability ADR-related diagnosis codes. Hence, adding high/very high-probability ADR-related hospitalisation codes to standard external cause codes alone (Y40-Y59) increased the number of hospitalisations classified as having an ADR-related diagnosis by 10.4%. Only 6.7% of cases with high-probability ADR-related mental symptoms were captured by external cause codes.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Adr-related Diagnosis Codesmentioning

confidence: 99%

See 1 more Smart Citation

Diagnosis-based and external cause-based criteria to identify adverse drug reactions in hospital ICD-coded data: application to an Australia population-based study

Du¹,

Pearson²,

Buckley³

et al. 2017

Public Health Res Pr

View full text Add to dashboard Cite

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“…However, we cannot rule out some degree of inaccuracy in reporting to the registers as physicians might misdiagnose ADE with unspecific clinical presentations, especially among older individuals [33][34][35].…”

Section: Discussionmentioning

confidence: 99%

175 Injurious falls and subsequent adverse drug events among elderly – a Swedish population-based matched case-control study

Rausch

Laflamme

Rooij

et al. 2016

Parallel Session Monday 19.9.2016 16:30–18:00

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Background: Fall injuries are stressful and painful and they have a range of serious consequences for older people. While there is some clinical evidence of unintentional poisoning by medication following a severe fall injuries, populationbased studies on that association are lacking. This is investigated in the current study, in which attention is also paid to different clinical conditions of the injured patients. Methods: We conducted a matched case-control study of Swedish residents 60 years and older from various Swedish population-based registers. Cases defined as adverse drug events (ADE) by unintentional poisoning leading to hospitalization or death were extracted from the National Patient Register (NPR) and the Cause of Death Register from January 2006 to December 2009 (n = 4418). To each case, four controls were matched by sex, age and residential area. Information on injurious falls leading to hospitalization six months prior to the date of hospital admission or death from ADE by unintentional poisoning, and corresponding date for the controls, was extracted from the NPR. Data on clinical conditions, such as dispensed medications, comorbidity and previous fall injuries were also extracted from the Swedish Prescribed Drug Register (SPDR) and NPR. Effect estimates were calculated using conditional logistic regression and presented as odds ratios (OR) and 95% confidence intervals (CI). Results: We found a three-fold increased risk of unintentional poisoning by medication in the six-month period after an injurious fall (OR 3.03; 95% CI, 2.54-3.74), with the most pronounced increase 1-3 weeks immediately after (OR, 7.66; 95% CI, 4.86-12.1). In that time window, from among those hospitalized for a fall (n = 92), those who sustained an unintentional poisoning (n = 60) tended to be in poorer health condition and receive more prescribed medications than those who did not, although this was not statistically significant. Age stratified analyses revealed a higher risk of poisoning among the younger (aged 60-79 years) than older elderly (80+ years). Conclusion: Medication-related poisoning leading to hospitalization or death can be an ADE subsequent to an episode of hospitalization for a fall-related injury. Poisoning is more likely to occur closer to the injurious event and among the younger elderly. It cannot be ruled out that some of those falls are themselves ADE and early signs of greater vulnerability among certain patients.

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“…Unfortunately, these data sources and methods generate incomplete data that lack important clinical details [10,11]. For example, a validation study comparing trigger methods to prospectively collected ADE data found that only 2-15% of events were identifiable using trigger methods compared to prospective data collection [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Why Clinicians Don�t Report Adverse Drug Events: Qualitative Study (Preprint)

Hohl¹,

Small²,

Peddie³

et al. 2017

Preprint

Self Cite

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(248/450)Background: Adverse drug events (ADEs) are unintended and harmful events related to medications. ADE outcomes are important for patients, quality improvement, drug safety research, and post-marketing surveillance; yet they are vastly underreported. Objective: Our objectives were to identify barriers to ADE documentation and factors contributing to underreporting. Methods: This qualitative study was conducted in one ambulatory centre and three hospitals in British Columbia between March 2014 and December 2016. We completed workplace observations and focus groups with family, hospitalist and emergency physicians, and hospital and community pharmacists. We analyzed field notes by coding and iteratively analyzing our data to identify emerging concepts, generate thematic and event summaries, and create workflow diagrams. Clinicians validated emerging concepts by applying them to cases from their clinical practice. Results: We completed 238 hours of observations during which clinicians investigated 65 suspect ADEs. The observed events were often complex and diagnosed over time, requiring the input of multiple providers. Providers documented ADEs in charts to support continuity-of-care, but never reported them to external agencies. Providers faced time constraints, and reporting would have required duplication of documentation. Conclusions: Existing reporting systems are not suited to capture the complex nature of ADEs nor adapted to workflow, and simply not used by frontline clinicians. Systems that are integrated into electronic medical records (EMRs), make use of existing data to avoid duplication of documentation, and generate alerts to improve safety may address the shortcomings of existing systems, and generate robust ADE data as a byproduct of safer care.

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ICD-10 codes used to identify adverse drug events in administrative data: a systematic review

Cited by 125 publications

References 58 publications

Diagnosis-based and external cause-based criteria to identify adverse drug reactions in hospital ICD-coded data: application to an Australia population-based study

Diagnosis-based and external cause-based criteria to identify adverse drug reactions in hospital ICD-coded data: application to an Australia population-based study

175 Injurious falls and subsequent adverse drug events among elderly – a Swedish population-based matched case-control study

Why Clinicians Don�t Report Adverse Drug Events: Qualitative Study (Preprint)

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