Introduction

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In Canada and internationally, a great deal of work is being done to monitor and understand the degree to which the supply of workers in health occupations is meeting (and will meet) the health needs of the population. A common theme throughout this work is the need for new and improved data for monitoring health human resources and to build models for health planning. In Canada, a health human resources (HHR) strategy has been developed from the work done by the Commissioner Roy Romanow, the Senate Committee chaired by Michael Kirby as well as both the 2003 First Ministers' Accord on Health Care Renewal and the First Ministers' Meeting (FMM) 2004 communiqué.

The issues in health human resources management are complex. Teams at the national, provincial / territorial and sub-provincial / territorial levels are working to understand the factors that influence health human resources management in Canada.

In 2004, as part of the work coordinated through the Advisory Committee on Health Delivery and Human Resources (ACHDHR), Health Canada contracted the Centre for Education Statistics (CES) at Statistics Canada to study the interface between education and training and the supply of entrants into health occupations. Through research and consultation, Statistics Canada was asked to investigate the availability of data to measure the infrastructure of health education programs in public and private educational institutions and the flow of individuals through these programs and into health and health-related occupations.

The first stage of the HHRE project, which focused solely on the role of the education system in overall health human resources management, was to identify the information needs related to HHRE. This was done through consultations with a variety of stakeholders during 2005. During this stage, an HHRE conceptual framework (see Figure 1.1) was developed to illustrate the generic flows of individuals through educational institutions and into the health labour market (refer to Appendix 8 for more information on the HHRE conceptual framework). The information needs collected during the consultations have been incorporated into this framework and published in "Health Human Resources and Education: Outlining Information Needs" (Allen et. al. 2006).

The second stage of this project was to present detailed information that would address some of the questions identified during the HHRE consultation process at the national level. As such, a report entitled "Educating Health Workers: A Statistical Portrait" was released in August 2007 (Allen et. al. 2007).

Figure 1.1
Health human resources and education (HHRE) conceptual framework

Following a study presented to Health Canada which outlined data availability and gaps on some issues raised during the 2005 nation-wide consultations, this second data report marks the last stage of the HHRE project. The purpose of this second data report is to provide a jurisdictional view of the information already released at the national level, as well as to provide information (at the Canada and jurisdictional levels) on some of the topics from the information needs outline that were not covered in the first data report (Allen et. al. 2007).

Given that both education and health care are managed by the provinces and territories in Canada, much of the HHRE information is required by jurisdiction. Information is also needed for specific occupation and personal characteristics (sex, age, aboriginal identity, educational attainment, etc.) as some issues relate to specific populations only. This level of detail is not being supported by all surveys at Statistics Canada and, depending on the sample size and the data quality, information may not be available for all jurisdictions. Health occupations may also need to be aggregated.

The first sections of this report present information related to what happens before entry into health education programs, which encompass questions related to interest in health occupations. Questions on recognition of foreign credentials by educational institutions are also addressed in this section.

This is followed by information on the period "during" health education, which covers questions about educators teaching in health education programs and characteristics of students enrolled in such programs.

The final sections of the report encompass information about the period immediately following graduation. They include basic information on the characteristics of graduates from health education programs and detailed information on their transitions into the labour market, including work activity, earnings and mobility. Also presented is information on adult literacy skills and ability of adults to use information and communications technologies, as well as on the supply of continuing education in workplaces and participation of adults in such training.

Data quality indicators

Data collected from sample surveys are presented in the tables along with data quality indicators (standard errors), which will help in the interpretation of the different survey results.

Standard errors are used to express the degree of uncertainty associated with sampling error and measurement error. The standard error can be used to construct a confidence interval, which provides a way of making inferences about the population means and proportions in a manner that reflects the uncertainty associated with sample estimates. A 95% confidence interval is used in this report and represents a range of plus or minus about two standard errors around the sample average. Using this confidence interval it can be inferred that the population mean or proportion would lie within the confidence interval in 95 out of 1 00 replications of the measurement, using different samples randomly drawn from the same population.

Thresholds related to the reliability of the estimate (denoted by "E" or "F") are a function of the standard error as measured by the Coefficient of Variation or CV. Estimates are suppressed (shown by F) where the CV is above 33.3% of the estimate. Where the CV is from 16.6% to 33.3%, data reliability is noted with an "E."

Otherwise stated, comparisons of estimates in the text are considered to be reliable if differences are statistically significant with a 95% level of confidence.

As explained above, statistical significance is determined by mathematical formulas and considers issues such as sampling. It is a matter of interpretation as to whether a difference in results has policy significance. There are situations where a statistically significant difference may have little policy significance (e.g., the difference is very small). There are also situations where a difference that is perceived to have policy significance may not in fact have statistical significance1.

1. This has been adapted from Council of Ministers of Education, Canada. 2005. School Achievement Indicators Program: Science III 2004.