Accuracy of syndrome definitions based on diagnoses in physician claims

<p>Abstract</p> <p>Background</p> <p>Community clinics offer potential for timelier outbreak detection and monitoring than emergency departments. However, the accuracy of syndrome definitions used in surveillance has never been evaluated in community settings. This study's objective was to assess the accuracy of syndrome definitions based on diagnostic codes in physician claims for identifying 5 syndromes (fever, gastrointestinal, neurological, rash, and respiratory including influenza-like illness) in community clinics.</p> <p>Methods</p> <p>We selected a random sample of 3,600 community-based primary care physicians who practiced in the fee-for-service system in the province of Quebec, Canada in 2005-2007. We randomly selected 10 visits per physician from their claims, stratifying on syndrome type and presence, diagnosis, and month. Double-blinded chart reviews were conducted by telephone with consenting physicians to obtain information on patient diagnoses for each sampled visit. The sensitivity, specificity, and positive predictive value (PPV) of physician claims were estimated by comparison to chart review.</p> <p>Results</p> <p>1,098 (30.5%) physicians completed the chart review. A chart entry on the date of the corresponding claim was found for 10,529 (95.9%) visits. The sensitivity of syndrome definitions based on diagnostic codes in physician claims was low, ranging from 0.11 (fever) to 0.44 (respiratory), the specificity was high, and the PPV was moderate to high, ranging from 0.59 (fever) to 0.85 (respiratory). We found that rarely used diagnostic codes had a higher probability of being false-positives, and that more commonly used diagnostic codes had a higher PPV.</p> <p>Conclusions</p> <p>Future research should identify physician, patient, and encounter characteristics associated with the accuracy of diagnostic codes in physician claims. This would enable public health to improve syndromic surveillance, either by focusing on physician claims whose diagnostic code is more likely to be accurate, or by using all physician claims and weighing each according to the likelihood that its diagnostic code is accurate.</p

Association between risk factors for injurious falls and new benzodiazepine prescribing in elderly persons

<p>Abstract</p> <p>Background</p> <p>Benzodiazepines are frequently prescribed to elderly patients' despite concerns about adverse effects leading to injurious falls. Previous studies have not investigated the extent to which patients with pre-existing risk factors for falls are prescribed benzodiazepines. The objective of this study is to assess if some of the risk factors for falls are associated with new benzodiazepine prescriptions in elderly persons.</p> <p>Methods</p> <p>Using provincial administrative databases, elderly Quebec residents were screened in 1989 for benzodiazepine use and non-users were followed for up to 5 years. Logistic regression models were used to evaluate potential predictors of new benzodiazepine use among patient baseline characteristics.</p> <p>Results</p> <p>In the 252,811 elderly patients who had no benzodiazepine prescription during the baseline year (1989), 174,444 (69%) never filled a benzodiazepine prescription and 78,367 (31%) filled at least one benzodiazepine prescription. In the adjusted analysis, several risk factors for falls were associated with statistically significant increases in the risk of receiving a new benzodiazepine prescription including the number of prescribing physicians seen at baseline (OR: 1.12; 95% CI 1.11–1.13), being female (OR: 1.20; 95% CI 1.18–1.22) or a diagnosis of arthritis (OR: 1.11; 95% CI 1.09–1.14), depression (OR: 1.42; 95% CI 1.35–1.49) or alcohol abuse (OR: 1.24; 95% CI 1.05–1.46). The strongest predictor for starting a benzodiazepine was the use of other medications, particularly anti-depressants (OR: 1.85; 95% CI 1.75–1.95).</p> <p>Conclusion</p> <p>Patients with pre-existing conditions that increase the risk of injurious falls are significantly more likely to receive a new prescription for a benzodiazepine. The strength of the association between previous medication use and new benzodiazepine prescriptions highlights an important medication safety issue.</p

Effect of a web-based chronic disease management system on asthma control and health-related quality of life: study protocol for a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Asthma is a prevalent and costly disease resulting in reduced quality of life for a large proportion of individuals. Effective patient self-management is critical for improving health outcomes. However, key aspects of self-management such as self-monitoring of behaviours and symptoms, coupled with regular feedback from the health care team, are rarely addressed or integrated into ongoing care. Health information technology (HIT) provides unique opportunities to facilitate this by providing a means for two way communication and exchange of information between the patient and care team, and access to their health information, presented in personalized ways that can alert them when there is a need for action. The objective of this study is to evaluate the acceptability and efficacy of using a web-based self-management system, My Asthma Portal (MAP), linked to a case-management system on asthma control, and asthma health-related quality of life.</p> <p>Methods</p> <p>The trial is a parallel multi-centered 2-arm pilot randomized controlled trial. Participants are randomly assigned to one of two conditions: a) MAP and usual care; or b) usual care alone. Individuals will be included if they are between 18 and 70, have a confirmed asthma diagnosis, and their asthma is classified as not well controlled by their physician. Asthma control will be evaluated by calculating the amount of fast acting beta agonists recorded as dispensed in the provincial drug database, and asthma quality of life using the Mini Asthma Related Quality of Life Questionnaire. Power calculations indicated a needed total sample size of 80 subjects. Data are collected at baseline, 3, 6, and 9 months post randomization. Recruitment started in March 2010 and the inclusion of patients in the trial in June 2010.</p> <p>Discussion</p> <p>Self-management support from the care team is critical for improving chronic disease outcomes. Given the high volume of patients and time constraints during clinical visits, primary care physicians have limited time to teach and reinforce use of proven self-management strategies. HIT has the potential to provide clinicians and a large number of patients with tools to support health behaviour change.</p> <p>Trial Registration</p> <p>Current Controlled Trials <a href="http://www.controlled-trials.com/ISRCTN34326236">ISRCTN34326236</a>.</p