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Identifying patients with rare diseases associated with common symptoms is challenging. Hunter syndrome, or Mucopolysaccharidosis type II is a progressive rare disease caused by a deficiency in the activity of the lysosomal enzyme, iduronate 2-sulphatase. It is inherited in an X-linked manner resulting in males being significantly affected. Expression in females varies with the majority being unaffected although symptoms may emerge over time. We developed a Naïve Bayes classification (NBC) algorithm utilizing the clinical diagnosis and symptoms of patients contained within their de-identified and unstructured electronic medical records (EMR) extracted by the Canadian Primary Care Sentinel Surveillance Network (CPCSSN). To do so, we created a training dataset using published results in the scientific literature and from all MPS II symptoms and applied the training dataset and its independent features to compute the conditional posterior probabilities of having MPS II disease as a categorical dependent variable for 506497 male patients. The classifier identified 125 patients with the highest likelihood for having the disease and 18 features were selected to be necessary for forecasting. Next, a Recursive Backward Feature Elimination algorithm was employed, for optimal input features of the NBC model, using a k-fold Cross-Validation with 3 replicates. The accuracy of the final model was estimated by the Validation Set Approach technique and the bootstrap resampling. We also investigated that whether the NBC is as accurate as three other Bayesian networks. The Naïve Bayes Classifier appears to be an efficient algorithm in assisting physicians with the diagnosis of Hunter syndrome allowing optimal patient management. [ABSTRACT FROM AUTHOR]

Background: Detection of undiagnosed or undertreated ("actionable") atrial fibrillation could increase the use of appropriate oral anticoagulant therapy and reduce the risk of stroke. We sought to compare newer screening technologies with a pulse-check for the detection of atrial fibrillation and to determine whether the detection of actionable atrial fibrillation increases the use of oral anticoagulant agents. Methods: This prospective multicentre cohort study involved 22 primary care clinics. We recruited participants aged 65 years and older who were attending routine appointments. Each participant underwent 3 methods of screening: a 30-second radial pulse-check; single-lead electrocardiogram; and screening by blood pressure machine with atrial fibrillation detection algorithms. Participants who received a positive result on 1 or more test underwent 12-lead electrocardiogram with or withour 24-hour Holter. Screening tests were compared using the McNemar test. Participants with confirmed atrial fibrillation received follow-up at 90 days. Results: The mean age of participants was 73.7 (± 6.9) years, and 53.4% of participants were female. Of 2171 patients, we had data from all 3 screening tests for 2054 patients. Both single-lead electrocardiogram and the blood pressure device showed superior specificity compared with pulse-check (p < 0.001 for each). Fifty-six patients (2.7%) had confirmed atrial fibrillation: 12 patients had newly detected atrial fibrillation (none of the patients were using anticoagulation agents), and 44 patients had previously diagnosed atrial fibrillation (42 patients were receiving anticoagulant therapy, 2 were not). Thus, 14 patients had actionable atrial fibrillation (0.7%). By 90 days, 77% of patients with actionable atrial fibrillation had started anticoagulant therapy. Interpretation: Newer screening technologies showed superior specificity compared with a pulse-check. Screening detected undiagnosed or undertreated atrial fibrillation in 0.7% of participants, and 77% started appropriate anticoagulant therapy. Trial registration: ClinicalTrials.gov, no. NCT02262351. [ABSTRACT FROM AUTHOR]

Background: In Ontario, a province-wide quality-improvement program (Quality Improvement and Innovation Partnership [QIIP]) was implemented between 2008 and 2010 to support improved outcomes in Family Health Teams, a care model that includes many features of the patient-centred medical home. We assessed the impact of this program on diabetes management, colorectal and cervical cancer screening and access to health care. Methods: We used comprehensive linked administrative data sets to conduct a population-based controlled before-and-after study. Outcome measures included diabetes process-of-care measures (test ordering, retinal examination, medication prescribing and completion of billing items specific to diabetes management), colorectal and cervical cancer screening measures and use of health care services (emergency department visits, hospital admission for ambulatory-care-sensitive conditions and rates of readmission to hospital). The control group consisted of Family Health Team physicians with at least 100 assigned patients during the study follow-up period (November 2009-February 2013). Results: There were 53 physicians in the intervention group and 1178 physicians in the control group. Diabetes process-of-care measures improved more in the intervention group than in the control group: hemoglobin A1c testing 4.3% (95% confidence interval [CI] 1.2- 7.5) more, retinal examination 2.5% (95% CI 0.8-4.4) more and preventive care visits 8.9% (95% CI 2.9-14.9) more. Medication prescribing also improved for use of statins (3.4% [95% CI 0.8-6.0] more) and angiotensin-converting-enzyme inhibitors or angiotensin receptor blockers (4.1% [95% CI 1.8-6.4] more). Colorectal cancer screening improved 5.4% (95% CI 3.1-7.8) more in the intervention group than in the control group, and cervical cancer screening improved 2.7% (95% CI 0.9-4.6) more. There were no significant differences in any of the measures of use of health care services. Interpretation: This large controlled evaluation of a broadly implemented quality-improvement initiative showed improvement for diabetes process of care and cancer screening outcomes, but not for proxy measures of access related to use of health care services. [ABSTRACT FROM AUTHOR]

Background. Calculating disease prevalence requires both a numerator (number of persons with a disease) and a matching denominator (the ‘population at risk’ being studied). Determining primary care practice denominators is challenging. Objective. To develop and test a method to calculate primary care practice denominators. Methods. We compared a ‘corrected yearly contact group’, or practice population, with the number of patients enrolled with practices. The yearly contact group was the set of patients with a visit noted in the electronic medical records during the past year. The correction factor was the proportion of patients that reported contacting their physician in the past year. Eighty-one physicians from Toronto and Kingston, Ontario, provided data. The main outcome measure was the ratio of practice population to the number of enrolled patients. Other measures included the change in ratio over 2 years, differences between locations, and differences by provider, practice and patient characteristics. Results. The ratio of practice population to enrolled patients was 1.03 in 2010 (95% confidence interval 1.00 to 1.05) and 1.03 in 2011 (95% confidence interval 1.00 to 1.05). There was no change in the ratio over time. Ratios by location, provider or practice characteristics differed by less than 10%. There was a slight under-estimation of practice population for younger male patients and over-estimation for female patients. Conclusion. This method provided a denominator that was reasonably similar to the enrolled population and was stable over time and by location, provider and practice characteristics. In regions without patient enrollment, this may provide an estimate of practice denominators. [ABSTRACT FROM PUBLISHER]

Abstract Objective: To compare blood pressure control, satisfaction, and adherence to drug treatment in patients with treated hypertension followed up by their family physicians either every three months or every six months for three years. Design: Randomised equivalence clinical trial. Settings: 50 family practices in south eastern Ontario, Canada. Participants: 609 patients aged 30-74 years with essential hypertension receiving drug treatment whose hypertension had been controlled for at least three months before entry into the study. Results: 302 patients were randomly assigned to follow up every three months and 307 to follow up every six months. Baseline variables in the two groups were similar. As expected, patients in the six month group had significantly fewer visits, but patients in both groups visited their doctor more frequently than their assigned interval. Mean blood pressure was similar in the groups, as was control of hypertension. Patient satisfaction and adherence to treatment were similar in the groups. About 20% of patients in each group had blood pressures that were out of control during the study. Conclusions: Follow up of patients with treated essential hypertension every six months is equivalent to follow up every three months. Patient satisfaction and adherence to treatment are the same for these follow up intervals. As about 20% of patients' hypertension was out of control at any time during the study in both groups, the frequency of follow up may not the most important factor in the control of patients' hypertension by family practitioners. [ABSTRACT FROM AUTHOR]

Presents a response to letters to the editor of the "British Medical Journal" as of March 13, 2004. Discussion of a medical study regarding the management of hypertension in medical practice; Promotion of the practice of having patients measure their own blood pressure between visits to the doctor.