OHDSI MEETINGS THIS WEEK
OHDSI Community Call - Tuesday at 12pm EThttps://meetings.webex.com/collabs/#/meetings/detail?uuid=M59X2V1U61WC9ASID2Z5N3UT95-D1JL&rnd=811649.9868221
NLP working group - Wednesday at 2pm EThttps://global.gotomeeting.com/join/707196421
Population-Level Estimation (Eastern hemisphere) workgroup meeting - Wednesday at 3pm Hong Kong timehttps://meetings.webex.com/collabs/meetings/join?uuid=M6WE9AOKFETH2VEFPVCZWWBIT0-D1JL
Architecture Working Group - Thursday at 10am EThttps://jjconferencing.webex.com/jjconferencing/j.php?MTID=m3e1ceeca56f1e94c9fcf1ae98c10e02e1
GIS working group meeting - Monday (January 15th) at 10am ET
Simple, modern video meetings for the global workforce. Join from anywhere, including your desktop, browser, mobile device, or video room device.
ANNOUNCEMENTS
State of the Collaborative Address - Our third annual State of the Collaborative address will take place next Tuesday’s OHDSI call (January 16th from 12-1pm ET). This year we’ll be hearing from community members about their OHDSI journey in 2017. We highly encourage you to attend this call and support your fellow collaborators as they share their experiences.
During our opening community call of 2018 (either January 9th or 16th) we'll be giving our annual state of the collaborative address. We want to hear from you guys, what your experience of OHDSI has been in 2017. Whether that was publishing papers,...
2018 OHDSI F2F: It’s official! The next OHDSI face-to-face will take place on May 2-3rd 2018 at Columbia University Medical Center in New York. More details to come.
What I know for sure is that speaking your truth is the most powerful tool we all have
COMMUNITY PUBLICATIONS
Finding treatment-resistant depression in real-world data: How a data-driven approach compares with expert-based heuristics.http://europepmc.org/abstract/med/29244906
Monitoring prescribing patterns using regression and electronic health records
It is beneficial for health care institutions to monitor physician prescribing patterns to ensure that high-quality and cost-effective care is being provided to patients. However, detecting treatment patterns within an institution is challenging,...
Guidelines for the Content of Statistical Analysis Plans in Clinical Trials
Machine Learning based Drug Indication Prediction using Linked Open Datahttp://www.swat4ls.org/wp-content/uploads/2017/11/SWAT4LS-2017_paper_30.pdf
Antibiotic-Induced Liver Injury in Paediatric Outpatients: A Case-Control Study in Primary Care Databases.
C Ferrajolo, KM Verhamme, G Trifirò, GW 't Jong, G Picelli, C Giaquinto, G Mazzaglia, BH Stricker, F Rossi, A Capuano and MC Sturkenboom,
Drug safety , 2017 04
Antibiotics are the most commonly prescribed drug class in children. Real-world data mining on the paediatric population showed potential associations between antibiotic use and acute liver injury.We assessed risk estimates of liver injury associated with antibiotic use in children and adolescent outpatients.A large, multi-database, population-based, case-control study was performed in people <18 years of age from two European countries (Italy and The Netherlands) during the period 2000-2008. All potential cases of liver injury were automatically extracted from three databases and then manually validated based on Council for International Organizations of Medical Sciences (CIOMS) criteria and by exclusion of all competing causes for liver injury. Up to 100 control participants were sampled for each case and were matched on index date of the event, age, sex and database. Based on prescription data, antibiotic exposure was categorized as current, recent or past use by calculating the time period between the end of prescription and the index date. Multivariate conditional logistic regression analyses were applied to calculate odds ratios (ORs) as a measure of the association (with 95% confidence interval [CI]).We identified 938 cases of liver injury and matched to 93,665 controls. Current use of overall antibiotics is associated with a threefold increased risk of liver injury compared with past use (adjusted OR [ORadj] 3.22, 95% CI 2.57-4.03). With regard to individual antibiotics, the risk is significantly increased for current use of each antibiotic (p < 0.005), except for azithromycin. Risk estimates vary from the lowest ORadj of 1.86 (95% CI 1.08-3.21) for amoxicillin to the highest ORadj of 24.16 (95% CI 11.78-49.54) for cotrimoxazole (i.e. sulphamethoxazole/trimethoprim) and 26.70 (95% CI 12.09-58.96) for ceftriaxone. Sensitivity analyses confirm the associations for ceftriaxone, cotrimoxazole, and clarithromycin.Antibiotic-induced liver injury in children is heterogeneous across the use of individual antibiotics. When prescribing ceftriaxone, cotrimoxazole and clarithromycin in children, paediatricians should definitely be aware of their potential risk of liver injury, even if for short periods.
Benzodiazepine Use and Risk of Dementia in the Elderly Population: A Systematic Review and Meta-Analysis.
MM Islam, U Iqbal, B Walther, S Atique, NK Dubey, PA Nguyen, TN Poly, JH Masud, YJ Li and SA Shabbir,
Neuroepidemiology , 2016
Benzodiazepines are a widely used medication in developed countries, particularly among elderly patients. However, benzodiazepines are known to affect memory and cognition and might thus enhance the risk of dementia. The objective of this review is to synthesize evidence from observational studies that evaluated the association between benzodiazepines use and dementia risk.We performed a systematic review and meta-analysis of controlled observational studies to evaluate the risk of benzodiazepines use on dementia outcome. All control observational studies that compared dementia outcome in patients with benzodiazepine use with a control group were included. We calculated pooled ORs using a random-effects model. Ten studies (of 3,696 studies identified) were included in the systematic review, of which 8 studies were included in random-effects meta-analysis and sensitivity analyses. Odds of dementia were 78% higher in those who used benzodiazepines compared with those who did not use benzodiazepines (OR 1.78; 95% CI 1.33-2.38). In subgroup analysis, the higher association was still found in the studies from Asia (OR 2.40; 95% CI 1.66-3.47) whereas a moderate association was observed in the studies from North America and Europe (OR 1.49; 95% CI 1.34-1.65 and OR 1.43; 95% CI 1.16-1.75). Also, diabetics, hypertension, cardiac disease, and statin drugs were associated with increased risk of dementia but negative association was observed in the case of body mass index. There was significant statistical and clinical heterogeneity among studies for the main analysis and most of the sensitivity analyses. There was significant statistical and clinical heterogeneity among the studies for the main analysis and most of the sensitivity analyses. Key Messages: Our results suggest that benzodiazepine use is significantly associated with dementia risk. However, observational studies cannot clarify whether the observed epidemiologic association is a causal effect or the result of some unmeasured confounding variable. Therefore, more research is needed.
IT-CARES: an interactive tool for case-crossover analyses of electronic medical records for patient safety.
A Caron, E Chazard, J Muller, R Perichon, L Ferret, V Koutkias, R Beuscart, JB Beuscart and G Ficheur,
Journal of the American Medical Informatics Association : JAMIA , Mar 2017 01
The significant risk of adverse events following medical procedures supports a clinical epidemiological approach based on the analyses of collections of electronic medical records. Data analytical tools might help clinical epidemiologists develop more appropriate case-crossover designs for monitoring patient safety.To develop and assess the methodological quality of an interactive tool for use by clinical epidemiologists to systematically design case-crossover analyses of large electronic medical records databases.We developed IT-CARES, an analytical tool implementing case-crossover design, to explore the association between exposures and outcomes. The exposures and outcomes are defined by clinical epidemiologists via lists of codes entered via a user interface screen. We tested IT-CARES on data from the French national inpatient stay database, which documents diagnoses and medical procedures for 170 million inpatient stays between 2007 and 2013. We compared the results of our analysis with reference data from the literature on thromboembolic risk after delivery and bleeding risk after total hip replacement.IT-CARES provides a user interface with 3 columns: (i) the outcome criteria in the left-hand column, (ii) the exposure criteria in the right-hand column, and (iii) the estimated risk (odds ratios, presented in both graphical and tabular formats) in the middle column. The estimated odds ratios were consistent with the reference literature data.IT-CARES may enhance patient safety by facilitating clinical epidemiological studies of adverse events following medical procedures. The tool's usability must be evaluated and improved in further research.
Diagnostic Yield of 2 Strategies for Adult Celiac Disease Identification in Primary Care.
R Scoglio, G Trifirò, A Sandullo, G Marangio, C D'Agate, S Costa, S Pellegrino, A Alibrandi, A Aiello, G Currò, C Cuzzupè, F Comisi, S Amato, R Conti Nibali, S Oteri, G Magazzu and A Carroccio,
Journal of clinical gastroenterology , Dec 2017 18
To compare the diagnostic yield and cost-consequences of 2 strategies, screening regardless of symptoms versus case finding (CF), using a point-of-care test (POCT), for the detection of celiac disease (CD) in primary care, to bridge the diagnostic gap of CD in adults.All subjects under 75 years of age who consecutively went to their general practitioners' offices were offered POCT for anti-transglutaminase immunoglobulin A antibodies. The POCT was performed on all subjects who agreed, and then a systematic search for symptoms or conditions associated with higher risk for CD was performed, immediately after the test but before knowing the test results. The 2 resulting groups were: (a) POCT positive and (b) symptomatic subject at CF. Subjects were defined as symptomatic at CF in the presence of 1 or more symptoms. All POCT-positive or symptomatic subjects at CF were referred to the CD Centers for confirmation of CD. Data on resource consumption were gathered from patients' charts. Cost of examinations, and diagnostic and laboratory tests were estimated with regional outpatient tariffs (Sicily), and a price of &OV0556;2.5 was used for each POCT.Of a total of 2197 subjects who agreed to participate in the study, 36 (1.6%) and 671 (30.5%) were POCT positive and symptomatic at CF, respectively. The yield from the screening and CF was 5 new celiac patients. The total cost and mean cost for each new CD case were &OV0556;7497.35 and &OV0556;1499.47 for the POCT screening strategy, and &OV0556;9855.14 and &OV0556;1971.03 for the CF strategy, respectively. Assuming consecutive use of both strategies, performing POCT only in symptomatic subjects at CF, the calculated yield would be 4 new diagnoses with a total cost of &OV0556;2345.84 and a mean cost of &OV0556;586.46 for each newly diagnosed patient. Only 1 patient was celiac despite a negative POCT.Testing symptomatic subjects at CF only by POCT seems the most cost-effective strategy to bridge the diagnostic gap of adult CD in primary care.
Constructing an Open-Access Bio-Signal Repository from Intensive Care Units.
D Kim, S Lee, TY Kim, S Jin, J Park, J Ko, RW Park and D Yoon,
Studies in health technology and informatics , 2017
Bio-signals can be crucial evidence in detecting urgent clinical events. However, until now, access to this data was limited. We aim to construct and provide a new open bio-signal repository with data gathered from more than 40 intensive care unit (ICU) beds. For doing so, we completed the interfacing system with the patient monitors at the target beds and plan to expand this data set to more than 100 ICU beds. Once completed, we plan to publicly open the data to catalyze interesting clinical-event detection research.
Conversion of National Health Insurance Service-National Sample Cohort (NHIS-NSC) Database into Observational Medical Outcomes Partnership-Common Data Model (OMOP-CDM).
SC You, S Lee, SY Cho, H Park, S Jung, J Cho, D Yoon and RW Park,
Studies in health technology and informatics , 2017
It is increasingly necessary to generate medical evidence applicable to Asian people compared to those in Western countries. Observational Health Data Sciences a Informatics (OHDSI) is an international collaborative which aims to facilitate generating high-quality evidence via creating and applying open-source data analytic solutions to a large network of health databases across countries. We aimed to incorporate Korean nationwide cohort data into the OHDSI network by converting the national sample cohort into Observational Medical Outcomes Partnership-Common Data Model (OMOP-CDM). The data of 1.13 million subjects was converted to OMOP-CDM, resulting in average 99.1% conversion rate. The ACHILLES, open-source OMOP-CDM-based data profiling tool, was conducted on the converted database to visualize data-driven characterization and access the quality of data. The OMOP-CDM version of National Health Insurance Service-National Sample Cohort (NHIS-NSC) can be a valuable tool for multiple aspects of medical research by incorporation into the OHDSI research network.
Rate of electronic health record adoption in South Korea: A nation-wide survey.
YG Kim, K Jung, YT Park, D Shin, SY Cho, D Yoon and RW Park,
International journal of medical informatics , 2017 05
The adoption rate of electronic health record (EHR) systems in South Korea has continuously increased. However, in contrast to the situation in the United States (US), where there has been a national effort to improve and standardize EHR interoperability, no consensus has been established in South Korea. The goal of this study was to determine the current status of EHR adoption in South Korean hospitals compared to that in the US.All general and tertiary teaching hospitals in South Korea were surveyed regarding their EHR status in 2015 with the same questionnaire as used previously. The survey form estimated the level of adoption of EHR systems according to 24 core functions in four categories (clinical documentation, result view, computerized provider order entry, and decision supports). The adoption level was classified into comprehensive and basic EHR systems according to their functionalities.EHRs and computerized physician order entry systems were used in 58.1% and 86.0% of South Korean hospitals, respectively. Decision support systems and problem list documentation were the functions most frequently missing from comprehensive and basic EHR systems. The main barriers cited to adoption of EHR systems were the cost of purchasing (48%) and the ongoing cost of maintenance (11%).The EHR adoption rate in Korean hospitals (37.2%) was higher than that in US hospitals in 2010 (15.1%), but this trend was reversed in 2015 (58.1% vs. 75.2%). The evidence suggests that these trends were influenced by the level of financial and political support provided to US hospitals after the HITECH Act was passed in 2009.The EHR adoption rate in Korea has increased, albeit more slowly than in the US. It is logical to suggest that increased funding and support tied to the HITECH Act in the US partly explains the difference in the adoption rates of EHRs in both countries.
