Dataset Information

Describing the content of primary care: limitations of Canadian billing data.

ABSTRACT:

Background

Primary health care systems are designed to provide comprehensive patient care. However, the ICD 9 coding system used for billing purposes in Canada neither characterizes nor captures the scope of clinical practice or complexity of physician-patient interactions. This study aims to describe the content of primary care clinical encounters and examine the limitations of using administrative data to capture the content of these visits. Although a number of U.S studies have described the content of primary care encounters, this is the first Canadian study to do so.

Methods

Study-specific data collection forms were completed by 16 primary care physicians in community health and family practice clinics in Winnipeg, Manitoba, Canada. The data collection forms were completed immediately following the patient encounter and included patient and visit characteristics, such as primary reason for visit, topics discussed, actions taken, degree of complexity as well as diagnosis and ICD-9 codes.

Results

Data was collected for 760 patient encounters. The diagnostic codes often did not reflect the dominant topic of the visit or the topic requiring the most amount of time. Physicians often address multiple problems and provide numerous services thus increasing the complexity of care.

Conclusion

This is one of the first Canadian studies to critically analyze the content of primary care clinical encounters. The data allowed a greater understanding of primary care clinical encounters and attests to the deficiencies of singular ICD-9 coding which fails to capture the comprehensiveness and complexity of the primary care encounter. As primary care reform initiatives in the U.S and Canada attempt to transform the way family physicians deliver care, it becomes increasingly important that other tools for structuring primary care data are considered in order to help physicians, researchers and policy makers understand the breadth and complexity of primary care.

SUBMITTER: Katz A

PROVIDER: S-EPMC3305652 | biostudies-literature | 2012 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Describing the content of primary care: limitations of Canadian billing data.

Katz Alan A Halas Gayle G Dillon Michael M Sloshower Jordan J

BMC family practice 20120215

<h4>Background</h4>Primary health care systems are designed to provide comprehensive patient care. However, the ICD 9 coding system used for billing purposes in Canada neither characterizes nor captures the scope of clinical practice or complexity of physician-patient interactions. This study aims to describe the content of primary care clinical encounters and examine the limitations of using administrative data to capture the content of these visits. Although a number of U.S studies have descri ...[more]

PMID: 22335900

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Project description:BackgroundCommercial data brokers have amassed large collections of primary care patient data in proprietary databases. Our study objective was to critically analyze how entities involved in the collection and use of these records construct the value of these proprietary databases. We also discuss the implications of the collection and use of these databases.MethodsWe conducted a critical qualitative content analysis using publicly available documents describing the creation and use of proprietary databases containing Canadian primary care patient data. We identified relevant commercial data brokers, as well as entities involved in collecting data or in using data from these databases. We sampled documents associated with these entities that described any aspect of the collection, processing, and use of the proprietary databases. We extracted data from each document using a structured data tool. We conducted an interpretive thematic content analysis by inductively coding documents and the extracted data.ResultsWe analyzed 25 documents produced between 2013 and 2021. These documents were largely directed at the pharmaceutical industry, as well as shareholders, academics, and governments. The documents constructed the value of the proprietary databases by describing extensive, intimate, detailed patient-level data holdings. They provided examples of how the databases could be used by pharmaceutical companies for regulatory approval, marketing and understanding physician behaviour. The documents constructed the value of these data more broadly by claiming to improve health for patients, while also addressing risks to privacy. Some documents referred to the trade-offs between patient privacy and data utility, which suggests these considerations may be in tension.ConclusionDocuments in our analysis positioned the proprietary databases as socially legitimate and valuable, particularly to pharmaceutical companies. The databases, however, may pose risks to patient privacy and contribute to problematic drug promotion. Solutions include expanding public data repositories with appropriate governance and external regulatory oversight.

Project description:Introduction: Depression is a serious disorder that brings a tremendous health and economic burden. Many antidepressants (AD) have obesogenic effects, increasing the population of obese patients at increased risk for a more severe disease course and poor treatment response. In addition, obese patients with depression may not be receiving the recommended standard of care due to "obesity bias." It is important to evaluate prescribing pharmacological treatment of depression in patients with obesity. Objectives: To describe the prevalence and patterns of AD prescribing for patients with depression and comorbid obesity compared with normal weight patients, and to examine the association of prescribing prevalence with obesity class. Methods: Study sample of adult patients (>18 years old) with depression was extracted from the national Canadian Primary Care Sentinel Surveillance Network (CPCSSN) Electronic Medical Records database for 2011-2016. Measures were prescribing of at least one AD (outcome) and body mass index (BMI) to categorize patients into weight categories (exposure). Data were analyzed cross-sectionally using descriptive statistics and mixed effects logistic regression model with clustering on CPCSSN networks and adjusting for age, sex, and the comorbidities. Results: Of 120,381 patients with depression, 63,830 patients had complete data on studied variables (complete cases analysis). Compared with normal weight patients, obese patients were more likely to receive an AD prescription (adjusted Odds Ratio [aOR] = 1.17; 95% Confidence Interval [CI]: 1.12-1.22). Patients with obesity classes II and III were 8% (95% CI: 1.00, 1.16) and 6% (95% CI: 0.98, 1.16) more likely, respectively, to receive AD. After imputing missing data using Multiple Imputations by Chained Equations, the results remained unchanged. The prevalence of prescribing >3 AD types was higher in obese category (7.27%, [95% CI: 6.84, 7.73]) than in normal weight category (5.6%; [95% CI: 5.24, 5.99]). Conclusion: The association between obesity and high prevalence of AD prescribing and prescribing high number of different AD to obese patients, consistent across geographical regions, raises a public health concern. Study results warrant qualitative studies to explore reasons behind the difference in prescribing, and quantitative longitudinal studies evaluating the association of AD prescribing patterns for obese patients with health outcomes.

Dataset Information

Describing the content of primary care: limitations of Canadian billing data.

Background

Methods

Results

Conclusion

Publications

Describing the content of primary care: limitations of Canadian billing data.

Similar Datasets

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