National Pharmacare in Canada: Equality or Equity, Accessibility or Affordability; Comment on “Universal Pharmacare in Canada: A Prescription for Equity in Healthcare”

Canada’s federal government intends to take steps to implement national pharmacare so that all Canadians have prescription drug coverage they need at an affordable price. Relatively limited funds have so far been pledged to support national pharmacare, which raises the question: what kind of program is envisioned? Since the government has already introduced regulations intended to reduce new drug prices drastically, national pharmacare seems likely to be a basic system designed to assist low-income Canadians with accessing primary care medicines. What Canadians actually need is a system that provides access to the medicine considered appropriate by the patient and their healthcare provider for the patient’s specific condition. Equitable national pharmacare will not be achieved if patients are denied access to new high-cost specialized medicines that can improve or extend their lives, any more than if patients who cannot afford basic drugs are not helped

The aging Canadian population and hospitalizations for acute myocardial infarction: projection to 2020

<p>Abstract</p> <p>Background</p> <p>The risk of experiencing an acute myocardial infarction (AMI) increases with age and Canada's population is aging. The objective of this analysis was to examine trends in the AMI hospitalization rate in Canada between 2002 and 2009 and to estimate the potential increase in the number of AMI hospitalizations over the next decade.</p> <p>Methods</p> <p>Aggregated data on annual AMI hospitalizations were obtained from the Canadian Institute for Health Information for all provinces and territories, except Quebec, for 2002/03 and 2009/10. Using these data in a Poisson regression model to control for age, gender and year, the rate of AMI hospitalizations was extrapolated between 2010 and 2020. The extrapolated rate and Statistics Canada population projections were used to estimate the number of AMI hospitalizations in 2020.</p> <p>Results</p> <p>The rates of AMI hospitalizations by gender and age group showed a decrease between 2002 and 2009 in patients aged ≥ 65 years and relatively stable rates in those aged < 64 years in both males and females. However, the total number of AMI hospitalizations in Canada (excluding Quebec) is projected to increase by 4667 from 51847 in 2009 to 56514 in 2020, a 9.0% increase. Inflating this number to account for the unavailable Quebec data results in an increase of approximately 6200 for the whole of Canada. This would amount to an additional cost of between $46 and$54 million and sensitivity analyses indicate that it could be between $36 and$65 million.</p> <p>Conclusions</p> <p>Despite projected decreasing or stable rates of AMI hospitalization, the number of hospitalizations is expected to increase substantially as a result of the aging of the Canadian population. The cost of these hospitalizations will be substantial. An increase of this extent in the number of AMI hospitalizations and the ensuing costs would significantly impact the already over-stretched Canadian healthcare system.</p

Promoting adherence to medicines: possible lessons for Canada?

Abstract Non-adherence to medication regimens is a major issue that can negatively impact patient health and wastes health care system resources. This commentary considers whether approaches to strategies undertaken in Israel to promote adherence could be viable in Canada. The structure of the Canadian health care system and budgetary constraints make new initiatives similar to those in Israel seem unlikely in Canada without some compelling stimulus

Developing algorithms for healthcare insurers to systematically monitor surgical site infection rates.

BackgroundClaims data provide rapid indicators of SSIs for coronary artery bypass surgery and have been shown to successfully rank hospitals by SSI rates. We now operationalize this method for use by payers without transfer of protected health information, or any insurer data, to external analytic centers.ResultsWe performed a descriptive study testing the operationalization of software for payers to routinely assess surgical infection rates among hospitals where enrollees receive cardiac procedures. We developed five SAS programs and a user manual for direct use by health plans and payers. The manual and programs were refined following provision to two national insurers who applied the programs to claims databases, following instructions on data preparation, data validation, analysis, and verification and interpretation of program output. A final set of programs and user manual successfully guided health plan programmer analysts to apply SSI algorithms to claims databases. Validation steps identified common problems such as incomplete preparation of data, missing data, insufficient sample size, and other issues that might result in program failure. Several user prompts enabled health plans to select time windows, strata such as insurance type, and the threshold number of procedures performed by a hospital before inclusion in regression models assessing relative SSI rates among hospitals. No health plan data was transferred to outside entities. Programs, on default settings, provided descriptive tables of SSI indicators stratified by hospital, insurer type, SSI indicator (inpatient, outpatient, antibiotic), and six-month period. Regression models provided rankings of hospital SSI indicator rates by quartiles, adjusted for comorbidities. Programs are publicly available without charge.ConclusionWe describe a free, user-friendly software package that enables payers to routinely assess and identify hospitals with potentially high SSI rates complicating cardiac procedures

Developing algorithms for healthcare insurers to systematically monitor surgical site infection rates.

Claims data provide rapid indicators of SSIs for coronary artery bypass surgery and have been shown to successfully rank hospitals by SSI rates. We now operationalize this method for use by payers without transfer of protected health information, or any insurer data, to external analytic centers.We performed a descriptive study testing the operationalization of software for payers to routinely assess surgical infection rates among hospitals where enrollees receive cardiac procedures. We developed five SAS programs and a user manual for direct use by health plans and payers. The manual and programs were refined following provision to two national insurers who applied the programs to claims databases, following instructions on data preparation, data validation, analysis, and verification and interpretation of program output. A final set of programs and user manual successfully guided health plan programmer analysts to apply SSI algorithms to claims databases. Validation steps identified common problems such as incomplete preparation of data, missing data, insufficient sample size, and other issues that might result in program failure. Several user prompts enabled health plans to select time windows, strata such as insurance type, and the threshold number of procedures performed by a hospital before inclusion in regression models assessing relative SSI rates among hospitals. No health plan data was transferred to outside entities. Programs, on default settings, provided descriptive tables of SSI indicators stratified by hospital, insurer type, SSI indicator (inpatient, outpatient, antibiotic), and six-month period. Regression models provided rankings of hospital SSI indicator rates by quartiles, adjusted for comorbidities. Programs are publicly available without charge.We describe a free, user-friendly software package that enables payers to routinely assess and identify hospitals with potentially high SSI rates complicating cardiac procedures

Developing algorithms for healthcare insurers to systematically monitor surgical site infection rates

<p>Abstract</p> <p>Background</p> <p>Claims data provide rapid indicators of SSIs for coronary artery bypass surgery and have been shown to successfully rank hospitals by SSI rates. We now operationalize this method for use by payers without transfer of protected health information, or any insurer data, to external analytic centers.</p> <p>Results</p> <p>We performed a descriptive study testing the operationalization of software for payers to routinely assess surgical infection rates among hospitals where enrollees receive cardiac procedures. We developed five SAS programs and a user manual for direct use by health plans and payers. The manual and programs were refined following provision to two national insurers who applied the programs to claims databases, following instructions on data preparation, data validation, analysis, and verification and interpretation of program output.</p> <p>A final set of programs and user manual successfully guided health plan programmer analysts to apply SSI algorithms to claims databases. Validation steps identified common problems such as incomplete preparation of data, missing data, insufficient sample size, and other issues that might result in program failure. Several user prompts enabled health plans to select time windows, strata such as insurance type, and the threshold number of procedures performed by a hospital before inclusion in regression models assessing relative SSI rates among hospitals. No health plan data was transferred to outside entities.</p> <p>Programs, on default settings, provided descriptive tables of SSI indicators stratified by hospital, insurer type, SSI indicator (inpatient, outpatient, antibiotic), and six-month period. Regression models provided rankings of hospital SSI indicator rates by quartiles, adjusted for comorbidities. Programs are publicly available without charge.</p> <p>Conclusion</p> <p>We describe a free, user-friendly software package that enables payers to routinely assess and identify hospitals with potentially high SSI rates complicating cardiac procedures.</p

Developing algorithms for healthcare insurers to systematically monitor surgical site infection rates-0

<p><b>Copyright information:</b></p><p>Taken from "Developing algorithms for healthcare insurers to systematically monitor surgical site infection rates"</p><p>http://www.biomedcentral.com/1471-2288/7/20</p><p>BMC Medical Research Methodology 2007;7():20-20.</p><p>Published online 6 Jun 2007</p><p>PMCID:PMC1896175.</p><p></p> percentage surgical site infection indicators following a cardiac procedure. Hospitals are ranked by their odds ratio compared to a hypothetical control hospital with the median percentage of SSI indicators from among the lowest quartile of hospitals. Odds ratios were derived from a multivariate model controlling for insurer type, sex, chronic disease score, and epoch (see text). Unadjusted percentages of SSI indicators are also shown for each hospital