Electronic Healthcare Databases Research Articles

Combining electronic healthcare databases in Europe to allow for large‐scale drug safety monitoring: the EU‐ADR Project

In this proof-of-concept paper we describe the framework, process, and preliminary results of combining data from European electronic healthcare record (EHR) databases for large-scale monitoring of drug safety. Aggregated demographic, clinical, and prescription data from eight databases in four countries (Denmark, Italy, Netherlands, the UK) were pooled using a distributed network approach by generation of common input data followed by local aggregation through custom-built software, Jerboa(©). Comparison of incidence rates of upper gastrointestinal bleeding (UGIB) and nonsteroidal anti-inflammatory drug (NSAID) utilization patterns were used to evaluate data harmonization and quality across databases. The known association of NSAIDs and UGIB was employed to demonstrate sensitivity of the system by comparing incidence rate ratios (IRRs) of UGIB during NSAID use to UGIB during all other person-time. The study population for this analysis comprised 19,647,445 individuals corresponding to 59,929,690 person-years of follow-up. 39,967 incident cases of UGIB were identified during the study period. Crude incidence rates varied between 38.8 and 109.5/100,000 person-years, depending on country and type of database, while age-standardized rates ranged from 25.1 to 65.4/100,000 person-years. NSAID use patterns were similar for databases within the same country but heterogeneous among different countries. A statistically significant age- and gender-adjusted association between use of any NSAID and increased risk for UGIB was confirmed in all databases, IRR from 2.0 (95%CI:1.7-2.2) to 4.3 (95%CI: 4.1-4.5). Combining data from EHR databases of different countries to identify drug-adverse event associations is feasible and can set the stage for changing and enlarging the scale for drug safety monitoring.

Temporal Data Mining for Adverse Events Following Immunization in Nationwide Danish Healthcare Databases

A rarely used opportunity in pharmacovigilance is data mining for adverse drug reactions (ADRs) in population-based healthcare databases. To evaluate the potential of data mining for ADRs in the nationwide Danish healthcare databases. We specifically considered hospital contacts following measles, mumps and rubella (MMR) immunization. We constructed a cohort consisting of all children born in Denmark from 1995 to 2007 (n = 918,831) with individual-level linked data on childhood vaccinations and hospital contacts from the nationwide Danish healthcare databases. We applied a cohort-based data mining methodology to compare the observed versus the expected incidence of adverse event in different time periods relative to immunization. With this approach we evaluated temporal associations between MMR immunization and 5915 different diagnoses occurring in the cohort. In order to evaluate the ability of our approach to detect signals, we singled out a set of four adverse events previously recognized as being associated with the MMR vaccine. We were able to link a total of 3,162,251 hospital contacts and 5915 different diagnoses to the children in the cohort. Previously recognized temporal associations between adverse events (febrile convulsions, idiopathic thrombocytopenic purpura, lymphadenopathy and rash) and MMR immunization were identified in the Danish databases by our method. Data mining in the Danish population-based healthcare databases provides adequate ability to detect adverse events. Pharmacovigilance using electronic healthcare databases holds potential as an important supplement to traditional pharmacovigilance.

Longitudinal study of a 9p21.3 SNP using a national electronic healthcare database.

Genome-wide association studies have identified a number of SNPs associated with complex disease. The longitudinal significance of these variants is uncertain and clinical genomic studies are required to elucidate what clinical value these variants have. Linking DNA to clinical health information databases is a powerful and potentially low-cost means of performing such research. Here, we describe a proof-of-principle study demonstrating the potential of this method. A total of 376 individuals presenting to a hospital with severe coronary artery disease were enrolled into a prospective cohort study. DNA, demographic data, ethnicity and other clinical information was collected in an electronic database. Genotyping for SNPs rs2383207 and rs10757278 was performed using Sequenom® (CA, USA) matrix-assisted laser desorption/ionisation-time of flight mass spectrometry. Health outcomes were tracked from when patients were discharged from the hospital using the New Zealand Health Information Service (Wellington, New Zealand). A total of 253 (67%) patients were of New Zealand European descent, 47 (13%) patients were of Maori descent and 21 (6%) were of Pacific Island ancestry. The Maori and Pacific Island group were younger at presentation (63 ± 11 vs 70 ± 9 years of age; p < 0.0001) and had a higher prevalence of cardiovascular risk factors. The frequency of the at-risk rs2383207 G allele in the Maori and Pacific group was 70%, compared with 54% in Europeans (p = 0.002). Similarly, the rs10757278 G allele was also present at a higher frequency (68 vs 52%; p = 0.003). No association was seen between the rs10757278 SNP and cardiovascular risk factors or markers of disease severity. GA and GG individuals had a higher rate of cardiovascular (p = 0.04) and all-cause death (p = 0.02). The linking of genetic data to electronic medical databases is an effective tool to assess the longitudinal effect of gene variants on health outcomes and will aid in the implementation of personalized medicine. Larger sample sizes with longer study duration may yield clinically useful information that aids preventative healthcare.

A basic study design for expedited safety signal evaluation based on electronic healthcare data

Active drug safety monitoring based on longitudinal electronic healthcare databases (a Sentinel System), as outlined in recent FDA-commissioned reports, consists of several interlocked processes, including signal generation, signal strengthening, and signal evaluation. Once a signal of a potential drug safety issue is generated, signal strengthening and signal evaluation have to follow in short sequence in order to quickly provide as much information about the triggering drug-event association as possible. This paper proposes a basic study design based on the incident user cohort design for expedited signal evaluation in longitudinal healthcare databases. It will not resolve all methodological issues nor will it fit all study questions arising within the framework of a Sentinel System. It should rather be seen as a guidance that will fit the majority of situations and serve as a starting point for adaptations to specific studies. Such an approach will expedite and structure the process of study development and highlight specific assumptions, which is particularly valuable in a Sentinel System where signals are by definition preliminary and evaluation of signals is time critical.

Broadening access to electronic healthcare databases

Broadening access to electronic healthcare databases

Appraising the post-marketing safety of medicines: A description of national and international pharmacovigilance with a focus on medicines used in chronic pain

Clinicians play a key role in appraising the safety of medicines after marketing. A wide variety of adverse reactions and novel interactions may occur in individual patients. Formal reporting by prescribers and evaluation of their observations to allow timely communication of risk back to the end users is vital. Many countries have regional or national pharmacovigilance centres which contribute to the World Health Organization (WHO) Global Individual Case Safety Report (ICSR) database, VigiBase. We describe the role of pharmacovigilance in detecting and evaluating emerging evidence of adverse drug reactions, i.e. “signals” using the New Zealand Pharmacovigilance Centre as an example. The benefits to individual patient safety through a medical warning system are of particular relevance to anaesthetic practice. Effective and holistic pharmacovigilance relies on voluntary reporting systems for all therapeutic products, prescription or cohort event monitoring of selected medicines and vaccines, and specific monitoring of medication error. Ongoing development of computational methods for data-mining in the voluntary reporting databases for signal detection and the application of these methods to electronic longitudinal health care databases such as general practice records in order to detect, confirm or refute, and characterise signals of adverse drug reactions are also described.

Reviewing the application of the Glasgow Coma Scale: Does it have interrater reliability?

This article explores if the Glasgow Coma Scale (GCS) has interrater reliability. The GCS was proposed as a tool that could be used with confidence by a range of healthcare practitioners. For this to be true the agreement between persons using the GCS should be consistent. This study investigates the evidence to assess if this is the case. This was undertaken with a systematic literature review of mainly electronic journals and healthcare databases. It remains unclear if the GCS has interrater reliability: the evidence base does not show agreement between researchers. Recent research is inconsistent not only in its conclusions but also its research methodologies. The uncertain research relating to interrater reliability contradicts the fundamental principle of the assessment tool (that it could be used with confidence by a range of healthcare professionals). The use of the GCS in adult nursing should be done with the knowledge that the evidence base supports the practitioner. As a result authoritative research is required to assess if the GCS has IR reliability. This is overdue, especially in the UK where the GCS has been part of formal guidance for several years.

Don't seize the day hospital! Recent research on the effectiveness of day hospitals for older people with mental health problems

Day hospital (DH) care remains a core component of mental health services for older people. However, there has been an ongoing debate about the effectiveness and value for money of DHs in comparison to day centres (DC). The aim was to review the recent research on the effectiveness of day hospitals for older people with mental health problems. A systematic search of relevant research literature over the last decade using the major electronic healthcare databases examining the quality and effectiveness of mental health DHs for older people. In the last decade the evidence for the effectiveness of DHs has continued to increase, but still lags behind research on DHs in general adult psychiatry and geriatric medicine. The review found that DHs appear effective at assessing and meeting needs and that a systematic approach to evaluating quality can be used to improve services. Recent research supports the effectiveness of day hospitals, but further studies are needed in order to provide a more robust evidence base.

Application of data mining to intensive care unit microbiologic data.

We describe refinements to and new experimental applications of the Data Mining Surveillance System (DMSS), which uses a large electronic health-care database for monitoring emerging infections and antimicrobial resistance. For example, information from DMSS can indicate potentially important shifts in infection and antimicrobial resistance patterns in the intensive care units of a single health-care facility.