A retrospective cohort study on lifestyle habits of cardiovascular patients: how informative are medical records?

Contains fulltext : 79771.pdf (publisher's version ) (Open Access)BACKGROUND: To evaluate the vigilance of medical specialists as to the lifestyle of their cardiovascular outpatients by comparing lifestyle screening as registered in medical records versus a lifestyle questionnaire (LSQ), a study was carried out at the cardiovascular outpatient clinic of the university hospital of Nijmegen, The Netherlands, between June 2004 and June 2005. METHODS: For 209 patients information from medical records on lifestyle habits, physician feedback, and interventions in the past year was compared to data gathered in the last month by a self-report LSQ. RESULTS: Doctors register smoking habits most consistently (90.4%), followed by alcohol use (81.8%), physical activity (50.2%), and eating habits (27.3%). Compared to the LSQ, smoking, unhealthy alcohol use, physical activity, and unhealthy eating habits are underreported in medical records by 31, 83, 54 and 97%, respectively. Feedback, advice or referral was documented in 8% for smoking, 3% for alcohol use, 12% for physical activity, and 26% for eating habits. CONCLUSION: Lifestyle is insufficiently registered or recognized by doctors providing routine care in a cardiovascular outpatient setting. Of the unhealthy lifestyle habits that are registered, few are accompanied by notes on advice or intervention. A lifestyle questionnaire facilitates screening and interventions in target patients and should therefore be incorporated in the cardiovascular setting as a routine patient intake procedure

Drug-induced acute myocardial infarction: identifying 'prime suspects' from electronic healthcare records-based surveillance system.

BACKGROUND: Drug-related adverse events remain an important cause of morbidity and mortality and impose huge burden on healthcare costs. Routinely collected electronic healthcare data give a good snapshot of how drugs are being used in 'real-world' settings. OBJECTIVE: To describe a strategy that identifies potentially drug-induced acute myocardial infarction (AMI) from a large international healthcare data network. METHODS: Post-marketing safety surveillance was conducted in seven population-based healthcare databases in three countries (Denmark, Italy, and the Netherlands) using anonymised demographic, clinical, and prescription/dispensing data representing 21,171,291 individuals with 154,474,063 person-years of follow-up in the period 1996-2010. Primary care physicians' medical records and administrative claims containing reimbursements for filled prescriptions, laboratory tests, and hospitalisations were evaluated using a three-tier triage system of detection, filtering, and substantiation that generated a list of drugs potentially associated with AMI. Outcome of interest was statistically significant increased risk of AMI during drug exposure that has not been previously described in current literature and is biologically plausible. RESULTS: Overall, 163 drugs were identified to be associated with increased risk of AMI during preliminary screening. Of these, 124 drugs were eliminated after adjustment for possible bias and confounding. With subsequent application of criteria for novelty and biological plausibility, association with AMI remained for nine drugs ('prime suspects'): azithromycin; erythromycin; roxithromycin; metoclopramide; cisapride; domperidone; betamethasone; fluconazole; and megestrol acetate. LIMITATIONS: Although global health status, co-morbidities, and time-invariant factors were adjusted for, residual confounding cannot be ruled out. CONCLUSION: A strategy to identify potentially drug-induced AMI from electronic healthcare data has been proposed that takes into account not only statistical association, but also public health relevance, novelty, and biological plausibility. Although this strategy needs to be further evaluated using other healthcare data sources, the list of 'prime suspects' makes a good starting point for further clinical, laboratory, and epidemiologic investigation