Canadian Primary Care Sentinel Surveillance Network Database Research Articles

Development of a case definition for hearing loss in community-based older adults: a cross-sectional validation study.

Background:Research based in primary care suggests that hearing loss may be underreported as well as inconsistently recorded in patient histories. In this study, we aimed to develop and validate a case definition for hearing loss among older adults in primary care, using electronic medical records.Methods:We used data from adult patients aged 55 years and older from 13 practices in the Southern Alberta Primary Care Research Network database, part of the Canadian Primary Care Sentinel Surveillance Network (CPCSSN), from Dec. 1, 2014, to Dec. 31, 2016. We developed a hearing loss case definition that was translated into an electronic algorithm. A record review was undertaken as the reference standard, followed by application of the algorithm to the sample. Validation metrics included sensitivity, specificity, positive predictive value and negative predictive value, as well as prevalence. We assessed risk factors using the Fisher exact test and odds ratios.Results:The sample included 1000 patients; 496 (49.6%) were female and the mean age was 67.5 (standard deviation 9.6) years. Sensitivity of the case definition algorithm was determined to be 87.3% (95% confidence interval [CI] 76.5%–94.4%) with specificity valued at 94.8% (95% CI 93.1%–96.1%). Positive and negative predictive values were 52.9% (95% CI 42.8%–62.8%) and 99.1% (95% CI 98.2%–99.6%), respectively. The prevalence of hearing loss within the sample was 6.3% (95% CI 4.9%–7.9%). Older age was a significant risk factor for hearing loss (t = 4.98, 95% CI 3.76–8.65). Men had greater odds of hearing loss than women (odds ratio 1.65, 95% CI 0.98–2.79).Interpretation:The validated case definition for hearing loss in community-based older adults had high sensitivity and specificity. It may be applied to surveillance and future epidemiologic research within the CPCSSN database.

Patients eligible and referred for bariatric surgery in southeastern Ontario: Retrospective cohort study.

To evaluate the proportion of eligible individuals, within one health region in Ontario, who were referred for publicly funded medical and surgical weight-loss interventions (MSWLI). A retrospective cohort study that used primary care data from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) and referral data from the Ontario Bariatric Network (OBN). Primary care practices within southeastern Ontario that contribute data to CPCSSN. Patients with class II (body mass index [BMI] 35.0 to 39.9 kg/m2) or III (BMI ≥ 40 kg/m2) obesity who were eligible for referral to the OBN for MSWLI. Primary care data about patients within the CPCSSN database were linked to referral records within the OBN database using 3 indirect identifiers to determine the proportion of patients with class II and III obesity who were referred to the OBN for MSWLI. An adjusted multivariate logistic regression model was used to determine the most significant predictors of referral. Of the 87 276 patients within one health region in Ontario, 15 526 (17.8%) patients had class II or III obesity and were eligible for referral for MSWLI. Only 966 out of those 15 526 (6.2%) patients were actually referred for MSWLI. In the multivariate regression analysis, BMI had the strongest association with referral in terms of adjusted odds ratio (AOR), varying from 2.50 (95% CI 2.04 to 3.06) for a BMI of 40.0 to 44.9 kg/m2, to 5.15 (95% CI 4.21 to 6.30) for a BMI of 50.0 kg/m2 or greater. Referral was more likely for female than male patients (AOR = 2.18; 95% CI 1.86 to 2.57), those living rurally than for urban dwellers (AOR = 1.39; 95% CI 1.20 to 1.60), and those aged 30 to 39 (AOR = 1.61; 95% CI 1.24 to 2.09) and 40 to 49 (AOR = 1.53; 95% CI 1.18 to 1.98) compared with other age groups. Within one health region in Ontario, the referral rate of patients with class II and III obesity for MSWLI was low. Our findings highlight the need for further research to understand and address the barriers to referral of patients with class II and III obesity for MSWLI.

Association rule mining to identify potential under-coding of conditions in the problem list in primary care electronic medical records

IntroductionThe problem list of a patient’s primary care electronic medical record (EMR) generally reflects their important medical conditions. We will use association rule mining to assess between-provider and between-clinic variation in the coding of select conditions in the EMR problem list, in order to identify possible under-coding outliers.
 Objectives and ApproachEMR data from participating clinics in the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) will be used, with a focus on three commonly-occurring conditions (hypertension, diabetes, and depression). Association rule mining will be used to develop association rules between these conditions and other clinical information available in the EMR, such as other diagnoses in the problem list, billing codes, medications, and laboratory results (e.g., a rule of “diabetic medication→diabetes” indicates that patients prescribed a diabetic medication are likely to have diabetes in the problem list). Under-coding outliers at the provider and clinic levels will be identified by comparing rule enforcement.
 ResultsResults from this work in progress will be presented at the conference. An estimated 270 clinics, 1340 providers, and 1.8 million patients will be included from the CPCSSN database. Rule ‘confidence’ will be used to identify outliers; the confidence of a rule X→Y is the proportion of individuals with X who also have Y (Pr(Y|X)). For example, we may find that on average 80% of patients prescribed a diabetic medication will also have a diagnosis of diabetes in the problem list (average confidence of 80%), but an outlier clinic may have a confidence of 40%; this low rule confidence may indicate under-coding of diabetes in the problem list. Confounding by patient demographics (e.g., age, sex, urban/rural) will be assessed and adjusted for, if necessary.
 Conclusion/ImplicationsThis work examines a novel method to identify potential under-coding in the EMR problem list. Providers/clinics could use this information to update patients’ problem list or inform quality improvement interventions. Researchers using primary care EMR data need to be aware of potential under-coding and take steps to mitigate the effects.

Manual review of electronic medical records as a reference standard for case definition development: a validation study.

The Canadian Primary Care Sentinel Surveillance Network (CPCSSN) previously carried out a validation study of case definitions for 8 chronic diseases (diabetes mellitus, hypertension, osteoarthritis, depression, dementia, chronic obstructive pulmonary disease, parkinsonism and epilepsy) using direct review of "raw" electronic medical record data. Although effective, this method is time-consuming and can present methodological and organizational challenges. We aimed to determine whether the processed and standardized data contained with the CPCSSN database might function as a reference standard for case definition validation. Using a traditional validation study design, we compared the case identification results of the chart reviews for the 8 chronic diseases with the results of a manual review of the CPCSSN processed data for the same conditions in the same patient sample. Patients were randomly sampled from the June 30, 2012 CPCSSN database, with oversampling of patients with rare conditions. We analyzed data for 1906 patients. Manual review of the CPCSSN records for case ascertainment yielded sensitivity ranging from 77.5% (95% confidence interval [CI] 73.3%-81.6%) for depression to 97.2% (95% CI 95.4%-99.0%) for diabetes. Specificity was high for all definitions (range 93.1% [95% CI 91.4%-94.7%] to 99.4% [95% CI 99.0%-99.8%]). Positive predictive values and negative predictive values also showed high accuracy of the manual CPCSSN record review relative to review of the raw chart data. The use of CPCSSN records as the reference standard to validate case definitions substantially reduces the burden on sentinel physicians and clinic managers as well as on researchers while offering a reference standard that is a reasonable substitution for chart review.

Methods to describe referral patterns in a Canadian primary care electronic medical record database: modelling multi-level count data

BackgroundA referral from a family physician (FP) to a specialist is an inflection point in the patient journey, with potential implications for clinical outcomes and health policy. Primary care electronic...

A national surveillance project on chronic kidney disease management in Canadian primary care: a study protocol

IntroductionEffective chronic disease care is dependent on well-organised quality improvement (QI) strategies that monitor processes of care and outcomes for optimal care delivery. Although healthcare is provincially/territorially structured in Canada,...

Development of a validated algorithm for the diagnosis of paediatric asthma in electronic medical records.

An accurate estimation of the prevalence of paediatric asthma in Alberta and elsewhere is hampered by uncertainty regarding disease definition and diagnosis. Electronic medical records (EMRs) provide a rich source of clinical data from primary-care practices that can be used in better understanding the occurrence of the disease. The Canadian Primary Care Sentinel Surveillance Network (CPCSSN) database includes cleaned data extracted from the EMRs of primary-care practitioners. The purpose of the study was to develop and validate a case definition of asthma in children 1–17 who consult family physicians, in order to provide primary-care estimates of childhood asthma in Alberta as accurately as possible. The validation involved the comparison of the application of a theoretical algorithm (to identify patients with asthma) to a physician review of records included in the CPCSSN database (to confirm an accurate diagnosis). The comparison yielded 87.4% sensitivity, 98.6% specificity and a positive and negative predictive value of 91.2% and 97.9%, respectively, in the age group 1–17 years. The algorithm was also run for ages 3–17 and 6–17 years, and was found to have comparable statistical values. Overall, the case definition and algorithm yielded strong sensitivity and specificity metrics and was found valid for use in research in CPCSSN primary-care practices. The use of the validated asthma algorithm may improve insight into the prevalence, diagnosis, and management of paediatric asthma in Alberta and Canada.

Implementation of data management and effect on chronic disease coding in a primary care organisation: A parallel cohort observational study

BackgroundConsistent and standardized coding for chronic conditions is associated with better care; however, coding may currently be limited in electronic medical records (EMRs) used in Canadian primary care.ObjectivesTo implement data...

Adult obesity prevalence in primary care users: An exploration using Canadian Primary Care Sentinel Surveillance Network (CPCSSN) data.

This research examines the feasibility of using electronic medical records within the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) for obesity surveillance in Canada by assessing obesity trends over time and comparing BMI distribution estimates from CPCSSN to those obtained from nationally representative surveys. Data from 2003-2012 on patients 18 years and older (n = 216,075) were extracted from the CPCSSN database. Patient information included demographics (age and sex) and anthropometric measures (height, weight, body mass index (BMI), waist circumference, and waist-to-hip ratio). Standard descriptive statistics were used to characterize the sample, including, as appropriate, means, proportions and medians. The BMI distribution of the CPCSSN population was compared to estimates from the Canadian Community Health Survey (CCHS) and the Canadian Health Measures Survey (CHMS) for the years: 2004, 2007-2009 and 2009-2011. The estimated prevalence of obesity increased from 17.9% in 2003 to 30.8% in 2012. Obesity class I, II and III prevalence estimates from CPCSSN in 2009-2011 (18.0%, 95% CI: 17.8-18; 7.4%, 95% CI: 7.3-7.6; 4.2%, 95% CI: 4.1-4.3 respectively) were greater than those from the most recent (2009- 2011) cycle of the CHMS (16.2%, 95% CI: 14-18.7; 6.3%, 95% CI: 4.6-8.5; 3.7%, 95% CI: 2.8-4.8 respectively), however these differences were not statistically significant. The data from CPCSSN present a unique opportunity for longitudinal obesity surveillance among primary care users in Canada, and offer prevalence estimates similar to those obtained from nationally representative survey data.

Examining the prevalence and patterns of multimorbidity in Canadian primary healthcare: a methodologic protocol using a national electronic medical record database.

In many developed countries, the burden of disease has shifted from acute to long-term or chronic diseases – producing new and broader challenges for patients, healthcare providers, and healthcare systems. Multimorbidity, the coexistence of two or more chronic diseases within an individual, is recognized as a significant public health and research priority. This protocol aims to examine the prevalence, characteristics, and changing burden of multimorbidity among adult primary healthcare (PHC) patients using electronic medical record (EMR) data. The objectives are two-fold: (1) to measure the point prevalence and clusters of multimorbidity among adult PHC patients; and (2) to examine the natural history and changing burden of multimorbidity over time among adult PHC patients. Data will be derived from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN). The CPCSSN database contains longitudinal, point-of-care data from EMRs across Canada. To identify adult patients with multimorbidity, a list of 20 chronic disease categories (and corresponding ICD-9 codes) will be used. A computational cluster analysis will be conducted using a customized computer program written in JAVA. A Cox proportional hazards analysis will be used to model time-to-event data, while simultaneously adjusting for provider- and patient-level predictors. All analyses will be conducted using STATA SE 13.1. This research is the first of its kind using a pan-Canadian EMR database, which will provide an opportunity to contribute to the international evidence base. Future work should systematically compare international research using similar robust methodologies to determine international and geographical variations in the epidemiology of multimorbidity.

PREVALENCE OF DYSLIPIDEMIA IN NEWFOUNDLAND ADULTS: APPROACHES TO ESTIMATION USING ELECTRONIC MEDICAL RECORDS

IntroductionDyslipidemia is a leading risk factor for cardiovascular disease (CVD). Newfoundland and Labrador (NL) has a higher level of CVD mortality than any other province in Canada. This high level...