Dataset Information

Adverse drug events with hyperkalaemia during inpatient stays: evaluation of an automated method for retrospective detection in hospital databases.

ABSTRACT:

Background

Adverse drug reactions and adverse drug events (ADEs) are major public health issues. Many different prospective tools for the automated detection of ADEs in hospital databases have been developed and evaluated. The objective of the present study was to evaluate an automated method for the retrospective detection of ADEs with hyperkalaemia during inpatient stays.

Methods

We used a set of complex detection rules to take account of the patient's clinical and biological context and the chronological relationship between the causes and the expected outcome. The dataset consisted of 3,444 inpatient stays in a French general hospital. An automated review was performed for all data and the results were compared with those of an expert chart review. The complex detection rules' analytical quality was evaluated for ADEs.

Results

In terms of recall, 89.5% of ADEs with hyperkalaemia "with or without an abnormal symptom" were automatically identified (including all three serious ADEs). In terms of precision, 63.7% of the automatically identified ADEs with hyperkalaemia were true ADEs.

Conclusions

The use of context-sensitive rules appears to improve the automated detection of ADEs with hyperkalaemia. This type of tool may have an important role in pharmacoepidemiology via the routine analysis of large inter-hospital databases.

SUBMITTER: Ficheur G

PROVIDER: S-EPMC4164763 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Publications

Adverse drug events with hyperkalaemia during inpatient stays: evaluation of an automated method for retrospective detection in hospital databases.

Ficheur Grégoire G Chazard Emmanuel E Beuscart Jean-Baptiste JB Merlin Béatrice B Luyckx Michel M Beuscart Régis R

BMC medical informatics and decision making 20140912

<h4>Background</h4>Adverse drug reactions and adverse drug events (ADEs) are major public health issues. Many different prospective tools for the automated detection of ADEs in hospital databases have been developed and evaluated. The objective of the present study was to evaluate an automated method for the retrospective detection of ADEs with hyperkalaemia during inpatient stays.<h4>Methods</h4>We used a set of complex detection rules to take account of the patient's clinical and biological co ...[more]

PMID: 25212108

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Project description:BackgroundThe incremental hospital cost and length of stay (LOS) associated with adverse events (AEs) has not been well characterized for planned and unplanned inpatient spine, hip, and knee surgeries.MethodsRetrospective cohort study of hip, knee, and spine surgeries at an academic hospital in 2011-2012. Adverse events were prospectively collected for 3,063 inpatient cases using the Orthopaedic Surgical AdVerse Event Severity (OrthoSAVES) reporting tool. Case costs were retrospectively obtained and inflated to equivalent 2021 CAD values. Propensity score methodology was used to assess the cost and LOS attributable to AEs, controlling for a variety of patient and procedure factors.ResultsThe sample was 55% female and average age was 64; 79% of admissions were planned. 30% of cases had one or more AEs (82% had low-severity AEs at worst). The incremental cost and LOS attributable to AEs were $8,500 (95% confidence interval [CI]: 5100-11,800) and 4.7 days (95% CI: 3.4-5.9) per admission. This corresponded to a cumulative $7.8 M (14% of total cohort cost) and 4,290 bed-days (19% of cohort bed-days) attributable to AEs. Incremental estimates varied substantially by (1) admission type (planned: $4,700/2.4 days; unplanned: $20,700/11.5 days), (2) AE severity (low: $4,000/3.1 days; high: $29,500/11.9 days), and (3) anatomical region (spine: $19,800/9 days; hip: $4,900/3.8 days; knee: $1,900/1.5 days). Despite only 21% of admissions being unplanned, adverse events in these admissions cumulatively accounted for 59% of costs and 62% of bed-days attributable to AEs.ConclusionsThis study comprehensively demonstrates the considerable cost and LOS attributable to AEs in orthopaedic and spine admissions. In particular, the incremental cost and LOS attributable to AEs per admission were almost five times as high among unplanned admissions compared to planned admissions. Mitigation strategies focused on unplanned surgeries may result in significant quality improvement and cost savings in the healthcare system.

Project description:IntroductionAdverse events are a major cause of patient harm in the hospitalised setting. Low-income and middle-income countries account for a disproportionate share of the global burden of adverse events. However, patient safety research is still centred around high-income countries and high-resource health systems. The methods and data produced from these efforts are ill-suited to low-income and middle-income systems due to the social and technical differences between these settings. We aim to use our pilot-tested, locally developed methodology to estimate the frequency and characteristics of adverse events in hospitalised patients in a lower-middle-income country to inform patient safety policies and initiatives.Methods and analysisThis multi-centre study will employ a two-step chart review methodology to identify adverse events in a representative sample of patients admitted at five hospitals between 1 January 2019 and 31 December 2019. The first step will include assessing patient files against a list of triggers to detect adverse events and the second step will involve an in-depth review of the events to capture pertinent characteristics. The triggers have been adapted from validated tools used in other studies. The reviewing team will be trained on the use of research tools and operational definitions to ensure that data are collected uniformly. The main outcome of interest is the rate at which adverse events occur in hospitalised patients. Further analysis will look to identify and quantify associations between the main outcome of interest and a variety of variables such as patient age and gender using tests of independence and regression techniques.Ethics and disseminationThis study protocol has been approved by the Ethics Review Committee at Aga Khan University (Reference number: 2023-6324-24566). The findings of this study will be published in a peer-reviewed journal and disseminated to the public through national and international conferences, workshops, websites and social media.

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Project description:ObjectiveMost studies based on state and nationwide registries evaluating perioperative outcome after carotid endarterectomy (CEA) rely on hospital discharge data only. Therefore, the true 30-day complication risk after carotid revascularization may be underestimated.MethodsWe used the National Surgical Quality Improvement Program database 2005-2010 to assess the in-hospital and postdischarge rate of any stroke, death, cardiac event (new Q-wave myocardial infarction or cardiac arrest), and combined stroke/death and combined adverse outcome (S/D/CE) at 30 days following CEA. Multivariable analyses were used to identify predictors for in-hospital and postdischarge events separately, and in particular, those that predict postdischarge events distinctly.ResultsA total of 35,916 patients who underwent CEA during 2005-2010 were identified in the National Surgical Quality Improvement Program database; 59% were male, median age was 72 years, and 44% had a previous neurologic event. Thirty-day stroke rate was 1.6% (n = 591), death rate was 0.8% (n = 272), cardiac event rate was 1.0% (n = 350), stroke or death rate was 2.2% (n = 794), and combined S/D/CE rate was 2.9% (n = 1043); 33% of strokes, 53% of deaths, 32% of cardiac events, 40% of combined stroke/death, and 38% of combined S/D/CE took place after hospital discharge. Patients with a prior stroke or transient ischemic attack had similar proportions of postdischarge events compared with patients without prior symptoms. Independent predictors for postdischarge events, but not for in-hospital events were female sex (stroke [odds ratio (OR), 1.6; 95% confidence interval (CI), 1.2-2.1] and stroke/death [OR, 1.4; 95% CI, 1.1-1.7]), renal failure (stroke [OR, 3.0; 95% CI, 1.4-6.2]) and chronic obstructive pulmonary disease (death [OR, 2.5; 95% CI, 1.6-3.7], stroke/death [OR, 1.8; 95% CI, 1.4-2.4], and S/D/CE [OR 1.8, 95% CI 1.4-2.3]).ConclusionsWith 38% of perioperative adverse events after CEA happening posthospitalization, regardless of symptoms status, we need to be alert to the ongoing risks after discharge particularly in women, patients with renal failure, or chronic obstructive pulmonary disease. This emphasizes the need for reporting and comparing 30-day adverse event rates when evaluating outcomes for CEA, or comparing carotid stenting to CEA.

Dataset Information

Adverse drug events with hyperkalaemia during inpatient stays: evaluation of an automated method for retrospective detection in hospital databases.

Background

Methods

Results

Conclusions

Publications

Adverse drug events with hyperkalaemia during inpatient stays: evaluation of an automated method for retrospective detection in hospital databases.

Similar Datasets

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