Dataset Information

The identification of cases of major hemorrhage during hospitalization in patients with acute leukemia using routinely recorded healthcare data.

ABSTRACT:

Introduction

Electronic health care data offers the opportunity to study rare events, although detecting these events in large datasets remains difficult. We aimed to develop a model to identify leukemia patients with major hemorrhages within routinely recorded health records.

Methods

The model was developed using routinely recorded health records of a cohort of leukemia patients admitted to an academic hospital in the Netherlands between June 2011 and December 2015. Major hemorrhage was assessed by chart review. The model comprised CT-brain, hemoglobin drop, and transfusion need within 24 hours for which the best discriminating cut off values were taken. External validation was performed within a cohort of two other academic hospitals.

Results

The derivation cohort consisted of 255 patients, 10,638 hospitalization days, of which chart review was performed for 353 days. The incidence of major hemorrhage was 0.22 per 100 days in hospital. The model consisted of CT-brain (yes/no), hemoglobin drop of ?0.8 g/dl and transfusion of ?6 units. The C-statistic was 0.988 (CI 0.981-0.995). In the external validation cohort of 436 patients (19,188 days), the incidence of major hemorrhage was 0.46 per 100 hospitalization days and the C-statistic was 0.975 (CI 0.970-0.980). Presence of at least one indicator had a sensitivity of 100% (CI 95.8-100) and a specificity of 90.7% (CI 90.2-91.1). The number of days to screen to find one case decreased from 217.4 to 23.6.

Interpretation

A model based on information on CT-brain, hemoglobin drop and need of transfusions can accurately identify cases of major hemorrhage within routinely recorded health records.

SUBMITTER: Kreuger AL

PROVIDER: S-EPMC6093651 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Publications

The identification of cases of major hemorrhage during hospitalization in patients with acute leukemia using routinely recorded healthcare data.

Kreuger Aukje L AL Middelburg Rutger A RA Beckers Erik A M EAM de Vooght Karen M K KMK Zwaginga Jaap Jan JJ Kerkhoffs Jean-Louis H JH van der Bom Johanna G JG

PloS one 20180815 8

<h4>Introduction</h4>Electronic health care data offers the opportunity to study rare events, although detecting these events in large datasets remains difficult. We aimed to develop a model to identify leukemia patients with major hemorrhages within routinely recorded health records.<h4>Methods</h4>The model was developed using routinely recorded health records of a cohort of leukemia patients admitted to an academic hospital in the Netherlands between June 2011 and December 2015. Major hemorrh ...[more]

PMID: 30110326

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Project description:BackgroundRoutinely recorded data held in electronic health records can be used to inform the conduct of randomised controlled trials (RCTs). However, limitations with access and accuracy have been identified.ObjectiveUsing epilepsy as an exemplar condition, we assessed the attributes and agreement of routinely recorded data compared to data collected using case report forms in a UK RCT assessing antiepileptic drug treatments for individuals newly diagnosed with epilepsy.MethodsThe case study RCT is the Standard and New Antiepileptic Drugs II (SANAD II) trial, a pragmatic, UK multicentre RCT assessing the clinical and cost-effectiveness of antiepileptic drugs as treatments for epilepsy. Ninety-eight of 470 eligible participants provided consent for access to routinely recorded secondary care data that were retrieved from NHS Digital Hospital Episode Statistics (N=71) and primary and secondary care data from The Secure Anonymised Information Linkage Databank (N=27). We assessed data items relevant to the identification of individuals eligible for inclusion in SANAD II, baseline and follow-up visits. The attributes of routinely recorded data were assessed including the degree of missing data. The agreement between routinely recorded data and data collected on case report forms in SANAD II was assessed using calculation of Cohen's kappa for categorical data and construction of Bland-Altman plots for continuous data.ResultsThere was a significant degree of missing data in the routine record for 15 of the 20 variables assessed, including all clinical variables. Agreement was poor for the majority of comparisons, including the assessments of seizure occurrence and adverse events. For example, only 23/62 (37%) participants had a date of first-ever seizure identified in routine datasets. Agreement was satisfactory for the date of prescription of antiepileptic drugs and episodes of healthcare resource use.ConclusionsThere are currently significant limitations preventing the use of routinely recorded data for participant identification and assessment of clinical outcomes in epilepsy, and potentially other chronic conditions. Further research is urgently required to assess the attributes, agreement, additional benefits, cost-effectiveness and 'optimal mix' of routinely recorded data compared to data collected using standard methods such as case report forms at clinic visits for people with epilepsy.Trial registrationStandard and New Antiepileptic Drugs II (SANAD II (EudraCT No: 2012-001884-64, registered 05/09/2012; ISRCTN Number: ISRCTN30294119 , registered 03/07/2012)).

Project description:BACKGROUND:In the UK, routinely recorded data may benefit prospective studies including randomised controlled trials (RCTs). In an on-going study, we aim to assess the feasibility of access and agreement of routinely recorded clinical and non-clinical data compared to data collected during a RCT using standard prospective methods. This paper will summarise available UK routinely recorded data sources and discuss our experience with the feasibility of accessing routinely recorded data for participants of a RCT before finally proposing recommendations for improving the access and implementation of routinely recorded data in RCTs. METHODS:Setting: the case study RCT is the Standard and New Antiepileptic Drugs II (SANAD II) trial, a pragmatic, UK, multicentre, phase IV RCT assessing the clinical and cost-effectiveness of antiepileptic drug treatments for newly diagnosed epilepsy. PARTICIPANTS:98 participants have provided written consent to permit the request of routinely recorded data. Study procedures: routinely recorded clinical and non-clinical data were identified and data requested through formal applications from available data holders for the duration that participants have been recruited into SANAD II. The feasibility of accessing routinely recorded data during a RCT is assessed and recommendations for improving access proposed. RESULTS:Secondary-care clinical and socioeconomic data is recorded on a national basis and can be accessed, although there are limitations in the application process. Primary-care data are recorded by a number of organisations on a de-identified basis but access for specific individuals has not been feasible. Access to data recorded by non-clinical sources, including The Department for Work and Pensions and The Driving and Vehicle Licensing Agency, was not successful. CONCLUSIONS:Recommendations discussed include further research to assess the attributes of routinely recorded data, an assessment of public perceptions and the development of strategies to collaboratively improve access to routinely recorded data for research. TRIAL REGISTRATION:International Standard Randomised Controlled Trials, ISRCTN30294119 . Registered on 3 July 2012. EudraCT No: 2012-001884-64. Registered on 9 May 2012.

Dataset Information

The identification of cases of major hemorrhage during hospitalization in patients with acute leukemia using routinely recorded healthcare data.

Introduction

Methods

Results

Interpretation

Publications

The identification of cases of major hemorrhage during hospitalization in patients with acute leukemia using routinely recorded healthcare data.

Similar Datasets

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