Leveraging national claim and hospital big data integration: a cohort study on a statin-drug interaction use case. (Preprint)

2021 ◽  
Author(s):  
Aurélie Bannay ◽  
Mathilde Bories ◽  
Pascal Le Corre ◽  
Christine Riou ◽  
Pierre Lemordant ◽  
...  
Keyword(s):  
Big Data ◽  
Drug Interaction ◽  
Drug Interactions ◽  
Hospital Stay ◽  
Data Warehouse ◽  
Record Linkage ◽  
Claim Data ◽  
Use Case ◽  
Academic Hospital ◽  
Statin Drug

BACKGROUND Linking different sources of medical data is a promising approach to analyse care trajectories. The INSHARE project aim was to provide the blueprint of a technological platform that facilitates integration, sharing and reuse of data from two sources: the eHOP clinical data warehouse (CDW) of Rennes academic hospital, and a dataset extracted from the French national claim data warehouse (SNDS). OBJECTIVE Using a pharmacovigilance use case based on statin consumption and statin-drug interactions, the present work demonstrates how the INSHARE platform can support big data analytical tasks in the health field. METHODS A Spark distributed cluster-computing framework was used for the record linkage procedure and all the analyses. A semi-deterministic record-linkage method based on the variables common between the chosen data sources was developed to identify all patients discharged after at least one hospital stay at Rennes academic hospital between 2015 and 2017. The use case study focused on a cohort of patients treated with statins prescribed by their general practitioner and/or during their hospital stay. RESULTS The whole process (record-linkage procedure and use case analyses) required 88 minutes. Among the 161,532 and 164,316 patients from the SNDS dataset and eHOP CDW, respectively, 159,495 patients were successfully linked (98.7% and 97.0% of patients from SNDS and eHOP CDW, respectively). Among the 16,806 patients with at least one statin delivery, 8,293 patients started the consumption before and continued during the hospital stay, 6,382 patients stopped statin consumption at hospital admission, and 2,131 patients initiated taking statins in hospital. Statin-drug interactions occurred more frequently during hospitalization than in the community (36.4% and 22.2%, respectively). Only 121 patients had the most severe level of statin-drug interaction. Hospital stay burden (length of stay and in-hospital mortality) was more severe in patients with statin-drug interactions during hospitalization. CONCLUSIONS This study demonstrates the added value of combining and re-using clinical and claim data to provide large-scale measures of drug-drug interaction prevalence and care pathways outside hospitals. It builds the path to move the current healthcare system towards a Learning Health System using knowledge generated from research on real-world health data.

scholarly journals Leveraging national claim and hospital big data integration: a cohort study on a statin-drug interaction use case. (Preprint)

10.2196/29286 ◽  
2021 ◽  
Author(s):  
Aurélie Bannay ◽  
Mathilde Bories ◽  
Pascal Le Corre ◽  
Christine Riou ◽  
Pierre Lemordant ◽  
...  
Keyword(s):  
Big Data ◽  
Cohort Study ◽  
Drug Interaction ◽  
Data Integration ◽  
Use Case ◽  
Statin Drug

scholarly journals An Analysis of Drug-Drug Interactions in a Tertiary Care Hospital in Kerala: A Retrospective Study

2021 ◽  
Author(s):  
Jihana Shajahan
Keyword(s):  
Drug Interaction ◽  
Drug Interactions ◽  
Hospital Stay ◽  
Tertiary Care Hospital ◽  
Tertiary Care ◽  
Care Hospital ◽  
Care Providers ◽  
Positive Correlation ◽  
Duration Of Hospital Stay ◽  
The Impact

Introduction: Concomitant use of several drugs for a patient is often necessary for achieving therapeutic response. Understanding the profile of Drug-Drug Interactions (DDI) will help health care providers to optimise therapy for better patient outcomes, reinforcing the concept of rational drug use. Aim: To analyse the frequency, mechanisms and severity of DDIs in a tertiary care hospital at Kerala. Materials and Methods: A retrospective cross-sectional study among 350 inpatients of a tertiary care hospital in Kerala from August 2020 to September 2020. Prescriptions containing ≥3 drugs were collected from inpatient medical records. A drug interaction check was performed using the Lexicomp drug interaction checker software. Results: DDIs were present in 74.6% of prescriptions and the average number of interactions was found to be 2.78. Most number for interactions was in the age group 61-80. Average number of DDI was significantly high among patients >60 years. Percentage of prescriptions with DDI and average number of DDI was found to be increasing with increase in number of drugs. Average number of interactions were maximum (5.01) in the group >10. Drug groups most commonly involved in interactions were antiplatelets, oral hypoglycaemic agents, bronchodilators, antibiotics, diuretics, insulin, statins, beta blockers, Proton Pump Inhibitors (PPI) and Non-Steroidal Anti-Inflammatory Drugs (NSAIDs). The most common interventions for minimising the impact of DDIs were changing the timing of drug administration, monitoring for symptoms/signs/lab values/drug levels or both. There was a significant positive correlation between duration of hospital stay and number of DDI. Conclusion: This study threw light upon the pattern and profile of DDIs among inpatients of a tertiary care hospital in Kerala. Elderly people (>60 years) were most prone for DDIs. Percentage of prescriptions with DDI and average number of DDIs was found to be increasing with increase in number of drugs. There was a positive correlation between duration of hospital stay and number of DDI.

scholarly journals Statin drug-drug interactions in a Romanian community pharmacy

2016 ◽  
Vol 89 (2) ◽  
pp. 273-278 ◽  
Author(s):  
Raluca Badiu ◽  
Camelia Bucsa ◽  
Cristina Mogosan ◽  
Dan Dumitrascu
Keyword(s):  
Drug Interaction ◽  
Adverse Effects ◽  
Drug Interactions ◽  
Community Pharmacy ◽  
Safety Profile ◽  
Potential Drug ◽  
Online Program ◽  
High Prevalence ◽  
Statin Drug

Background and aim. Statins are frequently prescribed for patients with dyslipidemia and have a well-established safety profile. However, when associated with interacting dugs, the risk of adverse effects, especially muscular toxicity, is increased.The objective of this study was to identify, characterize and quantify the prevalence of the potential drug-drug interactions (pDDIs) of statins in reimbursed prescriptions from a community pharmacy in Bucharest.Methods. We analyzed the reimbursed prescriptions including statins collected during one month in a community pharmacy. The online program Medscape Drug Interaction Checker was used for checking the drug interactions and their classification based on severity: Serious – Use alternative, Significant – Monitor closely and Minor.Results. 132 prescriptions pertaining to 125 patients were included in the analysis. Our study showed that 25% of the patients who were prescribed statins were exposed to pDDIs: 37 Serious and Significant interactions in 31 of the statins prescriptions. The statins involved were atorvastatin, simvastatin and rosuvastatin.Conclusions. Statin pDDIs have a high prevalence and patients should be monitored closely in order to prevent the development of adverse effects that result from statin interactions.

scholarly journals Potential drug–drug interactions and associated factors among hospitalized cardiac patients at Jimma University Medical Center, Southwest Ethiopia

2019 ◽  
Vol 7 ◽  
pp. 205031211985735 ◽  
Author(s):  
Netsanet Diksis ◽  
Tsegaye Melaku ◽  
Desta Assefa ◽  
Andualem Tesfaye
Keyword(s):  
Drug Interaction ◽  
Confidence Interval ◽  
Drug Interactions ◽  
Hospital Stay ◽  
Prevalence Rate ◽  
Odds Ratio ◽  
Adjusted Odds Ratio ◽  
Cardiac Patients ◽  
Potential Drug ◽  
Drug Drug Interaction

Background: Concomitant use of several drugs for a patient is often imposing increased risk of drug–drug interactions. Drug–drug interactions are a major cause for concern in patients with cardiovascular disorders due to multiple co-existing conditions and the wide class of drugs they receive. This study is aimed to assess the prevalence of potential drug–drug interactions and associated factors among hospitalized cardiac patients at medical wards of Jimma University Medical Center, Southwest Ethiopia. Methods: A hospital-based prospective observational study was conducted among hospitalized cardiac adult patients based on the inclusion criteria. Patient-specific data were collected using structured data collection tool. Potential drug–drug interaction was analyzed using Micromedex 3.0 DRUG-REAX® System. Data were analyzed using statistical software package, version 20.0. To identify the independent predictors of potential drug–drug interaction, multiple stepwise backward logistic regression analysis was done. Statistical significance was considered at a p-value < 0.05. Written informed consent from patients was obtained and the patients were informed about confidentiality of the information obtained. Results: Of the total 200 patients, majority were male (52.50%) and with a mean(±standard deviation) age of 42.54(±7.89) years. Out of 673 patients’ prescriptions analyzed, 521 prescriptions comprised potential drug interactions and it was found that 967 drug interactions were present. The prevalence rate of potential drug–drug interactions among the study unit was 4.83 per patient and 1.44 per prescription regardless of the severity during their hospital stay. Overall the prevalence rate of potential drug interactions was 74.41%. Older age (adjusted odds ratio (95% confidence interval): 1.067 (2.33–27.12), p = 0.049), long hospital stay (⩾7 days) (adjusted odds ratio (95% confidence interval): 2.80 (1.71–4.61), p = 0.024), and polypharmacy (adjusted odds ratio (95% confidence interval): 1.64 (0.66–4.11), p = 0.041) were independent predictors for the occurrence of potential drug–drug interactions. Conclusion: This study demonstrated a high prevalence of potential DIs among hospitalized cardiac patients in medical wards due to the complexity of pharmacotherapy. The prevalence rate is directly related to age, number of prescribed drugs, and length of hospital stay. Pharmacodynamic drug–drug interaction was the common mechanism of drug–drug interactions. Therefore, close monitoring of hospitalized patients is highly recommended.

scholarly journals Analyzing Varieties of Agricultural Data Using Big Data Tools Pig

2017 ◽  
Vol 10 (04) ◽  
pp. 810-816
Author(s):  
Bankim L. Radadiya ◽  
Parag Shukla
Keyword(s):  
Big Data ◽  
Data Warehouse ◽  
Survey Data ◽  
Previous History ◽  
Recent Survey ◽  
Use Case ◽  
Human Data ◽  
History Of ◽  
Day By Day

Day by day, data is growing rapidly. Analysis of the data is necessity. As per recent survey data generated in last 2 years is more than the data created in entire previous history of human. Data created in different form and in diversified manner. It can be structured, it can be semi-structured, or it can be unstructured. To analyze diversified by agricultural data we can use the tools of Big Data like Pig. Using Pig, we can analyze varieties of data. Pig is a platform for analysis of data. Biggest advantage of Pig is it can process any diversified data very quickly and allows us to use user defined functions. Use Case of Pig is ETL. It is used to extract the data from sources then after applying transformation we can load it into the data warehouse. We will do analysis of state wise proportion circulation of Numeral of operative properties for all societal collections in 2005-06 and 2010-11 using Pig.

Kajian Interaksi Obat Metformin pada Pasien Diabetes Mellitus

2019 ◽  
Vol 8 (2) ◽  
pp. 55-58
Author(s):  
Havizur Rahman ◽  
Teresia Anggi Octavia
Keyword(s):  
Diabetes Mellitus ◽  
Drug Interaction ◽  
Data Collection ◽  
Drug Interactions ◽  
Degenerative Disease ◽  
Moderate Severity ◽  
Purposive Sampling ◽  
Chronic Degenerative Disease ◽  
Over Time ◽  
Diabetes Melitus

Diabetes melitus merupakan penyakit degeneratif kronis yang apabila tidak ditangani dengan tepat, lama kelamaan bisa timbul berbagai komplikasi, ini cenderung menyebabkan pasien mendapatkan banyak obat dalam satu resep yang dapat menimbulkan interaksi antar obat. Tujuan dari penelitian ini adalah mengetahui persentase terjadinya interaksi obat metformin secara teori serta mengkaji efek yang mungkin timbul dan solusinya. Teknik pengambilan data dengan purpossive sampling, yaitu resep pasien rujuk balik yang menderita diabetes mellitus yang menggunakan metformin. Data yang diperoleh ditemukan bahwa obat yang berinteraksi dengan metformin dengan tingkat keparahan minor ialah sebesar 60%. Kemudian untuk tingkat keparahan moderat ialah sebesar 20%. Sedangkan untuk tingkat keparahan mayor tidak ditemukan. Dari tabel diatas juga dapat diketahui bahwa terdapat 4 obat yang saling berinteraksi dengan metformin, sedangkan untuk obat yang tidak saling berinteraksi dengan metformin terdapat 9 obat. Jumlah obat yang berinteraksi secara teori sebesar 6,85% dan yang tidak berinteraksi 93,15%. Terdapat interaksi obat metformin dengan beberapa obat yaitu furosemid, lisinopril, acarbose dan ramipril.   Kata kunci: interaksi obat, metformin, diabetes mellitus   STUDY OF METFORMIN INTERACTION IN MELLITUS DIABETES PATIENTS   ABSTRACT Mellitus is a chronic degenerative disease which if not handled properly, over time can arise various complications, this tends to cause patients to get many drugs in one recipe that can cause interactions between drugs. The purpose of this study is to determine percentage of metformin drug interactions in theory and examine the effects that may arise and solutions. Data collection techniques using purposive sampling, which is a recipe for reconciliation patients who suffer from diabetes mellitus using metformin. The data obtained it was found that drugs that interact with metformin with minor severity were 60%. Then for moderate severity is 20%. Whereas the major severity was not found. From the table above it can also be seen that there are 4 drugs that interact with metformin, while for drugs that do not interact with metformin there are 9 drugs. The number of drugs that interacted theoretically was 6.85% and 93.15% did not interact. An interaction of the drug metformin with several drugs namely furosemide, lisinopril, acarbose and ramipril.   Keywords: drug interaction, metformin, diabetes mellitus

Pharmacokinetic Drug-drug Interaction of Antibiotics Used in Sepsis Care in China

2020 ◽  
Vol 21 ◽  
Author(s):  
Xuan Yu ◽  
Zixuan Chu ◽  
Jian Li ◽  
Rongrong He ◽  
Yaya Wang ◽  
...  
Keyword(s):  
Drug Interaction ◽  
Drug Interactions ◽  
Penicillin G ◽  
Literature Mining ◽  
Human Pharmacokinetics ◽  
P450 Enzyme ◽  
Drug Drug Interaction ◽  
Pharmacokinetic Drug ◽  
Sepsis Care

Background: Many antibiotics have a high potential for having an interaction with drugs, as perpetrator and/or victim, in critically ill patients, and particularly in sepsis patients. Methods: The aim of this review is to summarize the pharmacokinetic drug-drug interaction (DDI) of 45 antibiotics commonly used in sepsis care in China. Literature mining was conducted to obtain human pharmacokinetics/dispositions of the antibiotics, their interactions with drug metabolizing enzymes or transporters, and their associated clinical drug interactions. Potential DDI is indicated by a DDI index > 0.1 for inhibition or a treated-cell/untreated-cell ratio of enzyme activity being > 2 for induction. Results: The literature-mined information on human pharmacokinetics of the identified antibiotics and their potential drug interactions is summarized. Conclusion: Antibiotic-perpetrated drug interactions, involving P450 enzyme inhibition, have been reported for four lipophilic antibacterials (ciprofloxacin, erythromycin, trimethoprim, and trimethoprim-sulfamethoxazole) and three lipophilic antifungals (fluconazole, itraconazole, and voriconazole). In addition, seven hydrophilic antibacterials (ceftriaxone, cefamandole, piperacillin, penicillin G, amikacin, metronidazole, and linezolid) inhibit drug transporters in vitro. Despite no reported clinical PK drug interactions with the transporters, caution is advised in the use of these antibacterials. Eight hydrophilic antibacterials (all β-lactams; meropenem, cefotaxime, cefazolin, piperacillin, ticarcillin, penicillin G, ampicillin, and flucloxacillin), are potential victims of drug interactions due to transporter inhibition. Rifampin is reported to perpetrate drug interactions by inducing CYP3A or inhibiting OATP1B; it is also reported to be a victim of drug interactions, due to the dual inhibition of CYP3A4 and OATP1B by indinavir. In addition, three antifungals (caspofungin, itraconazole, and voriconazole) are reported to be victims of drug interactions because of P450 enzyme induction. Reports for other antibiotics acting as victims in drug interactions are scarce.

scholarly journals Record linkage of routine data with cohorts’ data of infants under European and Portuguese law

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
J Doetsch ◽  
I Lopes ◽  
R Redinha ◽  
H Barros
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Data Protection ◽  
Record Linkage ◽  
Data Science ◽  
Personal Data ◽  
Routine Data ◽  
Cohort Data ◽  
Education Data ◽  
Explicit Consent

Abstract The usage and exchange of “big data” is at the forefront of the data science agenda where Record Linkage plays a prominent role in biomedical research. In an era of ubiquitous data exchange and big data, Record Linkage is almost inevitable, but raises ethical and legal problems, namely personal data and privacy protection. Record Linkage refers to the general merging of data information to consolidate facts about an individual or an event that are not available in a separate record. This article provides an overview of ethical challenges and research opportunities in linking routine data on health and education with cohort data from very preterm (VPT) infants in Portugal. Portuguese, European and International law has been reviewed on data processing, protection and privacy. A three-stage analysis was carried out: i) interplay of threefold law-levelling for Record Linkage at different levels; ii) impact of data protection and privacy rights for data processing, iii) data linkage process' challenges and opportunities for research. A framework to discuss the process and its implications for data protection and privacy was created. The GDPR functions as utmost substantial legal basis for the protection of personal data in Record Linkage, and explicit written consent is considered the appropriate basis for the processing sensitive data. In Portugal, retrospective access to routine data is permitted if anonymised; for health data if it meets data processing requirements declared with an explicit consent; for education data if the data processing rules are complied. Routine health and education data can be linked to cohort data if rights of the data subject and requirements and duties of processors and controllers are respected. A strong ethical context through the application of the GDPR in all phases of research need to be established to achieve Record Linkage between cohort and routine collected records for health and education data of VPT infants in Portugal. Key messages GDPR is the most important legal framework for the protection of personal data, however, its uniform approach granting freedom to its Member states hampers Record Linkage processes among EU countries. The question remains whether the gap between data protection and privacy is adequately balanced at three legal levels to guarantee freedom for research and the improvement of health of data subjects.

scholarly journals Herb–Drug Interactions: Worlds Intersect with the Patient at the Center

Medicines ◽  
2021 ◽  
Vol 8 (8) ◽  
pp. 44
Author(s):  
Mary Beth Babos ◽  
Michelle Heinan ◽  
Linda Redmond ◽  
Fareeha Moiz ◽  
Joao Victor Souza-Peres ◽  
...  
Keyword(s):  
Drug Interaction ◽  
Case Report ◽  
Drug Interactions ◽  
Clinical Studies ◽  
Drug Information ◽  
Case Reports ◽  
Full Information ◽  
Information Need ◽  
Herbal Products ◽  
Reduce Risk

This review examines three bodies of literature related to herb–drug interactions: case reports, clinical studies, evaluations found in six drug interaction checking resources. The aim of the study is to examine the congruity of resources and to assess the degree to which case reports signal for further study. A qualitative review of case reports seeks to determine needs and perspectives of case report authors. Methods: Systematic search of Medline identified clinical studies and case reports of interacting herb–drug combinations. Interacting herb–drug pairs were searched in six drug interaction resources. Case reports were analyzed qualitatively for completeness and to identify underlying themes. Results: Ninety-nine case-report documents detailed 107 cases. Sixty-five clinical studies evaluated 93 mechanisms of interaction relevant to herbs reported in case studies, involving 30 different herbal products; 52.7% of these investigations offered evidence supporting reported reactions. Cohen’s kappa found no agreement between any interaction checker and case report corpus. Case reports often lacked full information. Need for further information, attitudes about herbs and herb use, and strategies to reduce risk from interaction were three primary themes in the case report corpus. Conclusions: Reliable herb–drug information is needed, including open and respectful discussion with patients.

Role of P-glycoprotein in Statin Drug Interactions

2006 ◽  
Vol 26 (11) ◽  
pp. 1601-1607 ◽  
Author(s):  
Carol W Holtzman ◽  
Barbara S Wiggins ◽  
Sarah A Spinler
Keyword(s):  
Drug Interactions ◽  
P Glycoprotein ◽  
Statin Drug
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