A High-Fidelity Combined ATC-Rxnorm Drug Hierarchy for Large-Scale Observational Research.

Observational research utilizes patient information from many disparate databases worldwide. To be able to systematically analyze data and compare the results of such research studies, information about exposure to drugs or classes of drugs needs to be harmonized across these data. The NLM's RxNorm drug terminology and WHO's ATC classification serve these needs but are currently not satisfactorily combined into a common system. Creating such system is hampered by a number of challenges, resulting from different approaches to representing attributes of drugs and ontological rules. Here, we present a combined ATC-RxNorm drug hierarchy, allowing to use ATC classes for retrieval of drug information in large scale observational data. We present the heuristic for maintaining this resource and evaluate it in a real world database containing drug and drug classification information.

Descriptive analysis on disproportionate medication errors and associated patient characteristics in the Food and Drug Administration's Adverse Event Reporting System.

BACKGROUND: Medication errors (MEs) are a major public health concern which can cause harm and financial burden within the healthcare system. Characterizing MEs is crucial to develop strategies to mitigate MEs in the future. OBJECTIVES: To characterize ME-associated reports, and investigate signals of disproportionate reporting (SDRs) on MEs in the Food and Drug Administration's Adverse Event Reporting System (FAERS). METHODS: FAERS data from 2004 to 2020 was used. ME reports were identified with the narrow Standardised Medical Dictionary for Regulatory Activities® (MedDRA®) Query (SMQ) for MEs. Drug names were converted to the Anatomical Therapeutic Chemical (ATC) classification. SDRs were investigated using the reporting odds ratio (ROR). RESULTS: In total 488 470 ME reports were identified, mostly (59%) submitted by consumers and mainly (55%) associated with females. Median age at time of ME was 57 years (interquartile range: 37-70 years). Approximately 1 out of 3 reports stated a serious health outcome. The most prevalent reported drug class was "antineoplastic and immunomodulating agents" (25%). The most common ME type was "incorrect dose administered" (9%). Of the 1659 SDRs obtained, adalimumab was the most common drug associated with MEs, noting a ROR of 1.22 (95% confidence interval: 1.21-1.24). CONCLUSION: This study offers a first of its kind characterization of MEs as reported to FAERS. Reported MEs are frequent and may be associated with serious health outcomes. This FAERS data provides insights on ME prevention and offers possibilities for additional in-depth analyses.

Parasitic infections related to anti-type 2 immunity monoclonal antibodies: a disproportionality analysis in the food and drug administration's adverse event reporting system (FAERS).

Introduction: Monoclonal antibodies (mAbs) targeting immunoglobulin E (IgE) [omalizumab], type 2 (T2) cytokine interleukin (IL) 5 [mepolizumab, reslizumab], IL-4 Receptor (R) α [dupilumab], and IL-5R [benralizumab]), improve quality of life in patients with T2-driven inflammatory diseases. However, there is a concern for an increased risk of helminth infections. The aim was to explore safety signals of parasitic infections for omalizumab, mepolizumab, reslizumab, dupilumab, and benralizumab. Methods: Spontaneous reports were used from the Food and Drug Administration's Adverse Event Reporting System (FAERS) database from 2004 to 2021. Parasitic infections were defined as any type of parasitic infection term obtained from the Standardised Medical Dictionary for Regulatory Activities® (MedDRA®). Safety signal strength was assessed by the Reporting Odds Ratio (ROR). Results: 15,502,908 reports were eligible for analysis. Amongst 175,888 reports for omalizumab, mepolizumab, reslizumab, dupilumab, and benralizumab, there were 79 reports on parasitic infections. Median age was 55 years (interquartile range 24-63 years) and 59.5% were female. Indications were known in 26 (32.9%) reports; 14 (53.8%) biologicals were reportedly prescribed for asthma, 8 (30.7%) for various types of dermatitis, and 2 (7.6%) for urticaria. A safety signal was observed for each biological, except for reslizumab (due to lack of power), with the strongest signal attributed to benralizumab (ROR = 15.7, 95% Confidence Interval: 8.4-29.3). Conclusion: Parasitic infections were disproportionately reported for mAbs targeting IgE, T2 cytokines, or T2 cytokine receptors. While the number of adverse event reports on parasitic infections in the database was relatively low, resulting safety signals were disproportionate and warrant further investigation.

Supporting Pharmacovigilance Signal Validation and Prioritization with Analyses of Routinely Collected Health Data: Lessons Learned from an EHDEN Network Study.

INTRODUCTION: Individual case reports are the main asset in pharmacovigilance signal management. Signal validation is the first stage after signal detection and aims to determine if there is sufficient evidence to justify further assessment. Throughout signal management, a prioritization of signals is continually made. Routinely collected health data can provide relevant contextual information but are primarily used at a later stage in pharmacoepidemiological studies to assess communicated signals. OBJECTIVE: The aim of this study was to examine the feasibility and utility of analysing routine health data from a multinational distributed network to support signal validation and prioritization and to reflect on key user requirements for these analyses to become an integral part of this process. METHODS: Statistical signal detection was performed in VigiBase, the WHO global database of individual case safety reports, targeting generic manufacturer drugs and 16 prespecified adverse events. During a 5-day study-a-thon, signal validation and prioritization were performed using information from VigiBase, regulatory documents and the scientific literature alongside descriptive analyses of routine health data from 10 partners of the European Health Data and Evidence Network (EHDEN). Databases included in the study were from the UK, Spain, Norway, the Netherlands and Serbia, capturing records from primary care and/or hospitals. RESULTS: Ninety-five statistical signals were subjected to signal validation, of which eight were considered for descriptive analyses in the routine health data. Design, execution and interpretation of results from these analyses took up to a few hours for each signal (of which 15-60 minutes were for execution) and informed decisions for five out of eight signals. The impact of insights from the routine health data varied and included possible alternative explanations, potential public health and clinical impact and feasibility of follow-up pharmacoepidemiological studies. Three signals were selected for signal assessment, two of these decisions were supported by insights from the routine health data. Standardization of analytical code, availability of adverse event phenotypes including bridges between different source vocabularies, and governance around the access and use of routine health data were identified as important aspects for future development. CONCLUSIONS: Analyses of routine health data from a distributed network to support signal validation and prioritization are feasible in the given time limits and can inform decision making. The cost-benefit of integrating these analyses at this stage of signal management requires further research.

Comorbidity in incident osteoarthritis cases and matched controls using electronic health record data.

BACKGROUND: Comorbidities are common in patients with osteoarthritis (OA). This study aimed to determine the association of a wide range of previously diagnosed comorbidities in adults with newly diagnosed OA compared with matched controls without OA. METHODS: A case-control study was conducted. The data were derived from an electronic health record database that contains the medical records of patients from general practices throughout the Netherlands. Incident OA cases were defined as patients with one or more diagnostic codes recorded in their medical records that correspond to knee, hip, or other/peripheral OA. Additionally, the first OA code had to be recorded between January 1, 2006, and December 31, 2019. The date of cases' first OA diagnosis was defined as the index date. Cases were matched (by age, sex, and general practice) to up to 4 controls without a recorded OA diagnosis. Odds ratios were derived for each 58 comorbidities separately by dividing the comorbidity prevalence of cases by that of their matched controls at the index date. RESULTS: 80,099 incident OA patients were identified of whom 79,937 (99.8%) were successfully matched with 318,206 controls. OA cases had higher odds for 42 of the 58 studied comorbidities compared with matched controls. Musculoskeletal diseases and obesity showed large associations with incident OA. CONCLUSIONS: Most of the comorbidities under study had higher odds in patients with incident OA at the index date. While previously known associations were confirmed in this study, some associations were not described earlier.

Drug utilization analysis of osteoporosis medications in seven European electronic health databases.

We studied the characteristics of patients prescribed osteoporosis medication and patterns of use in European databases. Patients were mostly female, older, had hypertension. There was suboptimal persistence particularly for oral medications. Our findings would be useful to healthcare providers to focus their resources on improving persistence to specific osteoporosis treatments. PURPOSE: To characterise the patients prescribed osteoporosis therapy and describe the drug utilization patterns. METHODS: We investigated the treatment patterns of bisphosphonates, denosumab, teriparatide, and selective estrogen receptor modulators (SERMs) in seven European databases in the United Kingdom, Italy, the Netherlands, Denmark, Spain, and Germany. In this cohort study, we included adults aged ≥ 18 years, with ≥ 1 year of registration in the respective databases, who were new users of the osteoporosis medications. The study period was between 01 January 2018 to 31 January 2022. RESULTS: Overall, patients were most commonly initiated on alendronate. Persistence decreased over time across all medications and databases, ranging from 52-73% at 6 months to 29-53% at 12 months for alendronate. For other oral bisphosphonates, the proportion of persistent users was 50-66% at 6 months and decreased to 30-44% at 12 months. For SERMs, the proportion of persistent users at 6 months was 40-73% and decreased to 25-59% at 12 months. For parenteral treatment groups, the proportions of persistence with denosumab were 50-85% (6 month), 30-63% (12 month) and with teriparatide 40-75% (6 month) decreasing to 21-54% (12 month). Switching occurred most frequently in the alendronate group (2.8-5.8%) and in the teriparatide group (7.1-14%). Switching typically occurred in the first 6 months and decreased over time. Patients in the alendronate group most often switched to other oral or intravenous bisphosphonates and denosumab. CONCLUSION: Our results show suboptimal persistence to medications that varied across different databases and treatment switching was relatively rare.

Contextualising adverse events of special interest to characterise the baseline incidence rates in 24 million patients with COVID-19 across 26 databases: a multinational retrospective cohort study.

Background: Adverse events of special interest (AESIs) were pre-specified to be monitored for the COVID-19 vaccines. Some AESIs are not only associated with the vaccines, but with COVID-19. Our aim was to characterise the incidence rates of AESIs following SARS-CoV-2 infection in patients and compare these to historical rates in the general population. Methods: A multi-national cohort study with data from primary care, electronic health records, and insurance claims mapped to a common data model. This study's evidence was collected between Jan 1, 2017 and the conclusion of each database (which ranged from Jul 2020 to May 2022). The 16 pre-specified prevalent AESIs were: acute myocardial infarction, anaphylaxis, appendicitis, Bell's palsy, deep vein thrombosis, disseminated intravascular coagulation, encephalomyelitis, Guillain- Barré syndrome, haemorrhagic stroke, non-haemorrhagic stroke, immune thrombocytopenia, myocarditis/pericarditis, narcolepsy, pulmonary embolism, transverse myelitis, and thrombosis with thrombocytopenia. Age-sex standardised incidence rate ratios (SIR) were estimated to compare post-COVID-19 to pre-pandemic rates in each of the databases. Findings: Substantial heterogeneity by age was seen for AESI rates, with some clearly increasing with age but others following the opposite trend. Similarly, differences were also observed across databases for same health outcome and age-sex strata. All studied AESIs appeared consistently more common in the post-COVID-19 compared to the historical cohorts, with related meta-analytic SIRs ranging from 1.32 (1.05 to 1.66) for narcolepsy to 11.70 (10.10 to 13.70) for pulmonary embolism. Interpretation: Our findings suggest all AESIs are more common after COVID-19 than in the general population. Thromboembolic events were particularly common, and over 10-fold more so. More research is needed to contextualise post-COVID-19 complications in the longer term. Funding: None.

Epidemiology of chronic inflammatory demyelinating polyradiculoneuropathy in The Netherlands.

Chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) is a rare but disabling disorder that often requires long-term immunomodulatory treatment. Background incidence rates and prevalence and risk factors for developing CIDP are still poorly defined. In the current study, we used a longitudinal population-based cohort study in The Netherlands to assess these rates and demographic factors and comorbidity associated with CIDP. We determined the incidence rate and prevalence of CIDP between 2008 and 2017 and the occurrence of potential risk factors in a retrospective Dutch cohort study using the Integrated Primary Care Information (IPCI) database. Cases were defined as CIDP if the diagnosis of CIDP was described in the electronic medical file. In a source population of 928 030 persons with a contributing follow-up of 3 525 686 person-years, we identified 65 patients diagnosed with CIDP. The overall incidence rate was 0.68 per 100 000 person-years (95% CI 0.45-0.99). The overall prevalence was 7.00 per 100 000 individuals (95% CI 5.41-8.93). The overall incidence rate was higher in men compared to woman (IRR 3.00, 95% CI 1.27-7.11), and higher in elderly of 50 years or older compared with people <50 years of age (IRR 17 95% CI 4-73). Twenty percent of CIDP cases had DM and 9% a co-existing other auto-immune disease. These background rates are important to monitor changes in the frequency of CIDP following infectious disease outbreaks, identify potential risk factors, and to estimate the social and economic burden of CIDP.

Incidence and Prevalence of Knee Osteoarthritis Using Codified and Narrative Data From Electronic Health Records: A Population-Based Study.

OBJECTIVE: To determine the incidence and prevalence of knee osteoarthritis (OA) using codified and narrative data from general practices throughout The Netherlands. METHODS: This retrospective cohort study was conducted using the Integrated Primary Care Information database. Patients with codified knee OA were selected, and an algorithm was developed to identify patients with narratively diagnosed knee OA only. Point prevalence proportions and incidence rates among people age ≥30 years were assessed from 2008 to 2019. The association of comorbidities with codified knee OA was analyzed using multivariable logistic regression. RESULTS: The positive predicted value of narratively diagnosed knee OA only was 94.0% (95% confidence interval [95% CI] 87.4-100%) and for codified knee OA 96.0% (95% CI 90.6-100%). Including narrative data in addition to codified data resulted in a prevalence 1.83-2.01 times higher (over the study years); prevalence increased from 5.8% to 11.8% between 2008 and 2019. The incidence rate was 1.93-2.28 times higher and increased from 9.98 per 1,000 person-years to 13.8 per 1,000 person-years between 2008 and 2019. Among patients with codified knee OA, 39.4% were previously diagnosed narratively with knee OA, on average ~3 years earlier. Comorbidities influenced the likelihood of being recorded with codified knee OA. CONCLUSION: Our study of a Dutch primary care database showed that current incidence and prevalence estimates based on codified data alone from electronic health records are underestimated. Narrative data can be incorporated in addition to codified data to identify knee OA patients more accurately.

Antidepressant and anticonvulsant prescription rates in patients with osteoarthritis: a population-based cohort study.

OBJECTIVES: There are signs that antidepressants and anticonvulsants are being prescribed more often for OA patients, despite limited evidence. Our objectives were to examine prescription rates and time trends for antidepressants and anticonvulsants in OA patients, to assess the percentage of long-term prescriptions, and to determine patient characteristics associated with antidepressant or anticonvulsant prescription. METHODS: A population-based cohort study was conducted using the Integrated Primary Care Information database. First, episodic and prevalent prescription rates for antidepressants (amitriptyline, nortriptyline and duloxetine) and anticonvulsants (gabapentinoids) in OA patients were calculated for the period 2008-17. Logistic regression was used to assess which patient characteristics were associated with prescriptions. RESULTS: In total, 164 292 OA patients were included. The prescription rates of amitriptyline, gabapentin and pregabalin increased over time. The increase in prescription rates for pregabalin was most pronounced. Episodic prescription rate increased from 7.1 to 13.9 per 1000 person-years between 2008 and 2017. Amitriptyline was prescribed most (15.1 episodic prescriptions per 1000 person-years in 2017). Prescription rates of nortriptyline and duloxetine remained stable at 3.0 and 2.0 episodic prescriptions per 1000 person-years, respectively. For ≤3% of patients with incident OA, medication was prescribed long-term (≥3 months). In general, all medication was prescribed more frequently for older patients (except duloxetine), women, patients with OA in ≥2 joints, patients with spinal OA and patients with musculoskeletal disorders. CONCLUSION: Prescription rates of amitriptyline, gabapentin and pregabalin increased over time. Since there is little evidence to support prescription in OA, caution is necessary when prescribing.

Opioid prescriptions in patients with osteoarthritis: a population-based cohort study.

OBJECTIVES: To examine the incidence, prevalence and trends for opioid prescriptions in patients with OA. Furthermore, types of opioids prescribed and long-term prescription rates were examined. Finally, the patient characteristics associated with the prescription of opioids were assessed. METHODS: A population-based cohort study was conducted using the Integrated Primary Care Information database. Incidence and prevalence of opioid prescriptions were calculated for the period 2008-2017. Logistic regression was used to assess which patient characteristics were associated with opioid prescriptions. RESULTS: In total, 157 904 OA patients were included. The overall prescription rate remained fairly stable, at around 100 incident and 170 prevalent prescriptions per 1000 person years. However, the incident prescription rate for oxycodone increased from 7.1 to 40.7 per 1000 person years and for fentanyl from 4.2 to 7.4 per 1000 person years. The incident prescription rate for paracetamol/codeine decreased from 63.0 to 13.3 per 1000 person years. Per follow-up year, long-term use was found in 3% of the patients with incident OA. Finally, factors associated with more prescriptions were increasing age, OA in ≥2 joint groups [odds ratio (OR) 1.56; 95% CI: 1.51, 1.65] and the presence of other musculoskeletal disorders (OR 4.91; 95% CI: 4.76, 5.05). Men were less likely to be prescribed opioids (OR 0.78; 95% CI: 0.76, 0.80). CONCLUSION: Prescription rates for opioids remained stable, but types of opioids prescribed changed. Oxycodone and fentanyl were increasingly prescribed, while prescriptions of paracetamol/codeine decreased. Since the benefit of opioids for OA pain is questionable and side effects are common, opioids should be prescribed with caution.

The association of vascular disorders with incident dementia in different age groups.

BACKGROUND: There is increasing evidence that dementia risk associated with vascular disorders is age dependent. Large population-based studies of incident dementia are necessary to further elucidate this effect. Therefore, the aim of the present study was to determine the association of vascular disorders with incident dementia in different age groups in a large primary care database. METHODS: We included 442,428 individuals without dementia aged ≥ 65 years from the longitudinal primary care Integrated Primary Care Information (IPCI) database. We determined in 6 age groups (from 65-70 to ≥ 90 years) the risk of hypertension, diabetes mellitus, dyslipidemia, stroke, myocardial infarction, heart failure, and atrial fibrillation for all-cause dementia using incidence rate ratios, Cox regression, and Fine and Gray regression models. RESULTS: The mean age at inclusion of the total study sample was 72.4 years, 45.7% of the participants were male, and median follow-up was 3.6 years. During 1.4 million person-years of follow-up, 13,511 individuals were diagnosed with dementia. The risk for dementia decreased with increasing age for all risk factors and was no longer significant in individuals aged ≥ 90 years. Adjusting for mortality as a competing risk did not change the results. CONCLUSIONS: We conclude that vascular disorders are no longer a risk factor for dementia at high age. Possible explanations include selective survival of individuals who are less susceptible to the negative consequences of vascular disorders and differences in follow-up time between individuals with and without a vascular disorder. Future research should focus on the identification of other risk factors than vascular disorders, for example, genetic or inflammatory processes, that can potentially explain the strong age-related increase in dementia risk.

Identifying Data Elements to Measure Frailty in a Dutch Nationwide Electronic Medical Record Database for Use in Postmarketing Safety Evaluation: An Exploratory Study.

INTRODUCTION: The role of frailty in postmarketing drug safety is increasingly acknowledged. Few European electronic medical records (EMRs) have been used to explore frailty in observational drug safety research. OBJECTIVE: The aim of this study was to identify data elements, beyond multimorbidity and polypharmacy, that could potentially contribute to measuring frailty among older adults in the Dutch nationwide Integrated Primary Care Information (IPCI) database. METHODS: Persons aged between 65 and 90 years in the IPCI database were identified from 2008 to 2013. Clinical non-disease, non-drug measurements that could potentially contribute to measuring frailty were identified and selected if they were recorded in > 0.005% of patients and could be included in at least one of three definitions of frailty: the frailty phenotype model, the cumulative deficit model, and direct evaluations of frailty through standardized frailty scores. The frequency of these measures was calculated. RESULTS: Overall, 314,191 (17% of the source population) elderly persons were identified. Of these, 7948 (2.53%) had one or more of 12 clinical measurements identified that could potentially contribute to measuring frailty, such as clinical evaluations of cognition, mobility, and cachexia, as well as direct measures of frailty, such as the Groningen Frailty Index. Three of five measurements required for the frailty phenotype were identified in < 0.5% of the population: cachexia, reduced walking speed, and reduced physical activity; weakness and fatigue were not identified. The measurements outlined above may be appropriate for the cumulative deficit definition of frailty, provided that at least 30 deficits, including comorbidities and drug utilization, are evaluated in total. The most commonly recorded item identified that could potentially be used in a cumulative frailty model was the Mini-Mental State Examination score (N= 2850; 0.91%); the only recorded direct measurement of frailty was the Groningen Frailty Index (N = 2382; 0.76%). CONCLUSION: Non-disease, non-drug clinical data that could potentially contribute to a frailty model was not commonly recorded in the IPCI; less than 3% of a cohort of elderly persons had these data recorded, suggesting that the use of these data in postmarketing drug safety evaluation may be limited.

Translation of clinical prediction rules for febrile children to primary care practice: an observational cohort study.

BACKGROUND: Clinical prediction rules (CPRs) to identify children with serious infections lack validation in low-prevalence populations, which hampers their implementation in primary care practice. AIM: To evaluate the diagnostic value of published CPRs for febrile children in primary care. DESIGN AND SETTING: Observational cohort study among febrile children (<16 years) who consulted five GP cooperatives (GPCs) in the Netherlands. METHOD: Alarm signs of serious infection and clinical management were extracted from routine clinical practice data and manually recoded with a structured electronic data-entry program. Eight CPRs were selected from literature. CPR-variables were matched with alarm signs and CPRs were applied to the GPC-population. 'Referral to emergency department (ED)' was used as a proxy outcome measure for 'serious infection'. CPR performance was assessed by calibration analyses, sensitivity, specificity, and area under the ROC-curve (ROC-area). RESULTS: A total of 9794 GPC-contacts were eligible, 54% male, median age 2.3 years (interquartile range 1.0-4.6 years) and 8.1% referred to ED. Frequencies of CPR-variables varied from 0.5% (cyanosis, drowsy) to 25% (temperature ≥40°C). Alarm signs frequently included in CPRs were 'ill appearance', 'inconsolable', and 'abnormal circulatory or respiratory signs'. The height of the CPR's predicted risks generally corresponded with being (or not being) referred to the ED in practice. However, calibration-slopes indicated that three CPRs underestimated the risk of serious infection in the GPC-population. Sensitivities ranged from 42% to 54%, specificities from 68% to 89%. ROC-areas ranged from 0.52 to 0.81, with best performance of CPRs for children aged <3 months. CONCLUSION: Published CPRs performed moderately well in the primary out-of-hours care population. Advice is given on how to improve translation of CPRs to primary care practice.

Alarming signs and symptoms in febrile children in primary care: an observational cohort study in The Netherlands.

CONTEXT: Febrile children in primary care have a low risk for serious infection. Although several alarming signs and symptoms are proposed to have predictive value for serious infections, most are based on research in secondary care. The frequency of alarming signs/symptoms has not been established in primary care; however, in this setting differences in occurrence may influence their predictive value for serious infections. OBJECTIVE: To determine the frequency of alarming signs/symptoms in febrile children in primary care. DESIGN: Observational cohort study. Clinical information was registered in a semi-structured way and manually recoded. SETTING: General practitioners' out-of-hours service. SUBJECTS: Face-to-face patient contacts concerning children (aged ≤16 years) with fever were eligible for inclusion. MAIN OUTCOME MEASURES: Frequency of 18 alarming signs and symptoms as reported in the literature. RESULTS: A total of 10,476 patient contacts were included. The frequency of alarming signs/symptoms ranged from n = 1 (ABC instability; <0.1%) to n = 2,207 (vomiting & diarrhea; 21.1%). Of all children, 59.7% had one or more alarming signs and/or symptoms. Several alarming signs/symptoms were poorly registered with the frequency of missing information ranging from 1,347 contacts (temperature >40°C as reported by the parents; 12.9%) to 8,647 contacts (parental concern; 82.5%). CONCLUSION: Although the prevalence of specific alarming signs/symptoms is low in primary care, ≥50% of children have one or more alarming signs/symptoms. There is a need to determine the predictive value of alarming signs/symptoms not only for serious infections in primary care, but as well for increased risk of a complicated course of the illness.

Alarm signs and antibiotic prescription in febrile children in primary care: an observational cohort study.

BACKGROUND: Although fever in children is often self-limiting, antibiotics are frequently prescribed for febrile illnesses. GPs may consider treating serious infections by prescribing antibiotics. AIM: To examine whether alarm signs and/or symptoms for serious infections are related to antibiotic prescription in febrile children in primary care. DESIGN AND SETTING: Observational cohort study involving five GP out-of-hours services. METHOD: Clinical information was registered and manually recoded. Children (<16 years) with fever having a face-to-face contact with a GP were included. Children who were already using antibiotics or referred to secondary care were excluded. The relation between alarm signs and/or symptoms for serious infections and antibiotic prescription was tested using multivariate logistic regression. RESULTS: Of the 8676 included patients (median age 2.4 years), antibiotics were prescribed in 3167 contacts (36.5%). Patient characteristics and alarm signs and/or symptoms positively related to antibiotic prescription were: increasing age (odds ratio [OR] = 1.03; 95% confidence interval [95% CI] = 1.02 to 1.05), temperature measured by GP (OR = 1.72; 95% CI = 1.59 to 1.86), ill appearance (OR = 3.93; 95% CI = 2.85 to 5.42), being inconsolable (OR = 2.27; 95% CI = 1.58 to 3.22), shortness of breath (OR = 2.58; 95% CI = 1.88 to 3.56), duration of fever (OR = 1.31; 95% CI = 1.26 to 1.35). Negative associations were found for neurological signs (OR = 0.45; 95% CI = 0.27 to 0.76), signs of urinary tract infection (OR = 0.63; 95% CI = 0.49 to 0.82), and vomiting and diarrhoea (OR = 0.65; 95% CI = 0.57 to 0.74). These variables explained 19% of the antibiotic prescriptions. CONCLUSION: Antibiotics are often prescribed for febrile children. These data suggest that treatment of a supposed serious bacterial infection is a consideration of GPs. However, the relatively low explained variation indicates that other considerations are also involved.

Is OpenSDE an alternative for dedicated medical research databases? An example in coronary surgery.

BACKGROUND: When using a conventional relational database approach to collect and query data in the context of specific clinical studies, a study with a new data set usually requires the design of a new database and entry forms. OpenSDE (SDE = Structured Data Entry) is intended to provide a flexible and intuitive way to create databases and entry forms for the collection of data in a structured format. This study illustrates the use of OpenSDE as a potential alternative to a conventional approach with respect to data modelling, database creation, data entry, and data extraction. METHODS: A database and entry forms are created using OpenSDE and MSAccess to support collection of coronary surgery data, based on the Adult Cardiac Surgery Data Set of the Society of Thoracic Surgeons. Data of 52 cases are entered and nine different queries are designed, and executed on both databases. RESULTS: Design of the data model and the creation of entry forms were experienced as more intuitive and less labor intensive with OpenSDE. Both resulting databases provided sufficient expressiveness to accommodate the data set. Data entry was more flexible with OpenSDE. Queries produced equal and correct results with comparable effort. CONCLUSION: For prospective studies involving well-defined and straight forward data sets, OpenSDE deserves to be considered as an alternative to the conventional approach.

Generic computer-based questionnaires: an extension to OpenSDE.

Development of computer-based questionnaires (CQs) has been an ongoing challenge since the 1960s. The added value of such CQs for data collection and the acceptance by patients have been well documented. Many questionnaire projects, however, were temporary due to dedicated software, limited funding, and lack of integration with medical information systems. Also, the use of a fixed dedicated database makes integration cumbersome, as change in content requires change to the data model. Since much of the functional requirement of CQs is not dependent on content, the challenge is to both separate functionality and database structure from content. Following these principles, we extended OpenSDE, a generic application for structured data entry, with a tool to construct and run CQs as an alternative way of data input. We propose the combination of a generic building tool and a content-independent data model as an effective strategy to tackle the above-mentioned problems in CQ development.

OpenSDE: Row modeling applied to generic structured data entry.

Clinicians generally record medical narrative data, such as current complaints, physical examination, and progress notes, as free text in paper-based medical records. The medical narrative involves heterogeneous and detailed data that include the description of (multiple) occurrences of medical findings or symptoms that may progress over time. Structured, electronic recording of narrative data would facilitate the use of these data for research. The authors' OpenSDE application supports clinicians with the structured recording of narrative data in both research and care settings. Data entry is enabled using forms that are generated using domain-specific trees of medical concepts. For data storage, the authors have expanded the traditional row modeling methodology with additional columns that allow structured representation of medical narratives including descriptions of findings, multiple occurrences of findings, and the progression of findings over time.