Survey on Health Care Access and Experiences - Primary and Specialist Care (SHCAE-PSC)

Detailed information for 2024

The purpose of the SHCAE-PSC is to better understand how Canadians navigate the health care system, including challenges or barriers they may face.

Data release - July 29, 2025

• Questionnaire(s) and reporting guide(s)
• Description
• Data sources and methodology
• Data accuracy

Description

This survey covers topics such as the use of and access to primary health care and specialist care, care coordination, barriers to care, prescription medications, and out-of-pocket expenses.

The results may be used by Health Canada, the Public Health Agency of Canada, and provincial ministries of health to help inform the delivery of health care services and develop and improve programs and policies to better serve all Canadians.

Reference period: Varies according to the question (for example: "in the past 12 months", "the most recent time", etc.)

Subjects

• Health
• Health care services

Data sources and methodology

Target population

The target population for the SHCAE-PSC is all persons 18 years of age or older living in private residences in the ten provinces of Canada. Excluded are people living in dwellings located on reserves and people living in collective dwellings, such as institutions.

Instrument design

The content for the SHCAE-PSC electronic questionnaire was drafted in consultation with the Public Health Agency of Canada, Health Canada and the Canadian Institute for Health Information.

The questionnaire underwent cognitive testing in the form of in-depth interviews in both of Canada's official languages, conducted by Statistics Canada's Questionnaire Design Resource Centre. The goal of the qualitative study was to test the survey content.

The questionnaire follows standard practices and wording used in a computer-assisted interviewing environment, such as the automatic control of flows that depend upon answers to earlier questions and the use of edits to check for logical inconsistencies and capture errors. The computer application for data collection was tested extensively.

Sampling

This is a sample survey with a cross-sectional design.

The SHCAE-PSC sample has a stratified two-stage design. A random sample of private dwellings is selected in each of the ten provinces. In each sampled dwelling, one person is selected from among all residents aged 18 years or older.

Sampling unit:
At the first stage, the sampling unit is a dwelling. At the second stage, the sampling unit is a person.

Stratification method:
Stratification of dwellings is done by province and by the expected number of dwelling residents aged 18 years or older.

Sampling and sub-sampling:
A sample of 75,000 dwellings is selected probabilistically according to the stratified design. Within each dwelling, one person is selected at random to respond to the survey.

Data sources

Data collection for this reference period: 2024-01-03 to 2024-11-03

Responding to this survey is voluntary.

Data are collected directly from survey respondents and extracted from administrative files.

Data is collected from survey respondents either through an electronic questionnaire (EQ) directly online or assisted by a Statistics Canada interviewer through CATI (computer assisted telephone interviewing). A letter is mailed to the selected dwelling, which contains a code that gives access to the online questionnaire.

A Statistics Canada interviewer may follow up by calling, emailing, or texting the respondent if a completed online questionnaire is not received within a certain period of time.

Proxy reporting (when a selected respondent is unable to answer for themselves) is allowed, although certain questions may be skipped.

The questionnaire is available in both official languages and can be completed by interview in either English or French. To remove language as a barrier to conducting interviews, each of the Statistics Canada regional offices recruited interviewers with a wide range of language competencies. When necessary, cases are transferred to an interviewer with the language competency needed to complete an interview. The average time to complete the survey is 30 minutes.

The information collected during the 2024 SHCAE-PSC is linked to the personal tax records of respondents, and tax records of all household members. Household information (address, postal code, and telephone number) and respondent's information (social insurance number, surname, name, date of birth/age, sex) are key variables for the linkage.

Respondents are notified of the planned linkage before and during the survey. Any respondents who object to the linkage of their data have their objections recorded, and no linkage to their tax data takes place. Income information obtained from income tax records will also be provided to federal and provincial share partners but only with respondent consent.

View the Questionnaire(s) and reporting guide(s) .

Error detection

Most editing of the data is performed at the time of completing the electronic questionnaire or the interview by the computer-assisted interviewing application. It is not possible for respondents and interviewers to enter out-of-range values and flow errors are controlled through programmed skip patterns. For example, the application ensures that questions that did not apply to the respondent are not asked.

In response to some types of inconsistent or unusual reporting, warning messages are invoked but no corrective action is taken at the time of completing the questionnaire. Where appropriate, edits are instead developed to be performed after data collection at Head Office. Inconsistencies are usually corrected by setting one or both of the variables in question to "not stated".

Imputation

Concepts related to personal and total household income were not asked of respondents for this cycle of SHCAE-PSC. These income concepts were instead appended to the file from administrative sources for respondents who did not object to this process and for whom the process was possible. For the other respondents, total household income and some related variables were imputed using donor imputation.

Estimation

In order for estimates produced from survey data to be representative of the covered population, and not just the sample itself, users must incorporate the survey weights in their calculations. A survey weight is given to each respondent included in the final sample. This weight corresponds to the number of persons in the entire population that are represented by the respondent.

The adjustments to the initial weight include an adjustment for out-of-scope records followed by a non-response adjustment based on modeling probabilities of response at the household level. Variables based on characteristics of the units are used to create the models. Then, these probabilities are used to create groups of respondents and nonrespondents in which the weights of the nonrespondents are transferred to the respondents. These household-level weights are then adjusted to account for the number of people in the household from which each respondent was selected via the age order selection process. The resulting person-level weights undergo two more adjustments (Winsorization and Calibration to known population totals such as by geography, age and gender) and become the final person-level weights.

Bootstrap weights are created through resampling the original sample by applying similar adjustments to the bootstrap weights as to the sample weights. Bootstrap weights are used to evaluate the quality of survey estimates.

The sample design used for this survey is not self-weighting. That is to say, the sampling weights are not identical for all individuals in the sample. When producing simple estimates, including the production of ordinary statistical tables, users must apply the proper sampling weight.

Estimates of the number of people with a certain characteristic are obtained from the data file by summing the final weights of all records possessing the characteristic of interest.

Proportions and ratios are obtained by summing the final weights of records having the characteristic of the numerator and the denominator, and then dividing the first estimate by the second.

Quality evaluation

Throughout the collection process, control and monitoring measures were put in place and corrective action was taken to minimize non-sampling errors. These measures included response rate evaluation, reported and non-reported data evaluation, interviewer observation, improved collection tools for interviewers and others.

While quality assurance mechanisms are applied at all stages of the statistical process, the validation and review of data by statisticians is the final verification of quality prior to release. Validation measures that were implemented include:
a) verification of estimates through cross-tabulations
b) consultation with stakeholders internal to Statistics Canada

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects that could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.

Revisions and seasonal adjustment

This methodology does not apply to this survey.

Data accuracy

The quality of estimates produced with SHCAE-PSC data is measured using the confidence interval or the coefficient of variation (CV), both produced using bootstrap weights.

Survey errors come from a variety of different sources. One dimension of survey error is sampling error. Sampling error is defined as the error that arises because an estimate is based on a sample rather than the entire population. Sampling error can be expressed through a confidence interval or coefficient of variation.

Non-sampling error
Measurement errors (sometimes referred to as response errors) occur when the response provided differs from the real value; such errors may be attributable to the respondent, the questionnaire, the collection method or the respondent's record-keeping system. Such errors may be random or they may result in a systematic bias if they are not random.

Processing errors are the errors associated with activities conducted once survey responses have been received. They include all data handling activities after collection and prior to estimation. Like all other errors, they can be random in nature, and inflate the variance of the survey's estimates, or they can be systematic, and introduce bias. It is difficult to obtain direct measures of processing errors and their impact on data quality especially since they are mixed in with other types of errors (nonresponse, measurement and coverage).

Non-response bias
To mitigate potential nonresponse bias, the survey weights are adjusted for total non-response and are calibrated to population totals for age, sex, geography, and educational attainment.

Coverage error
Coverage errors consist of omissions, erroneous inclusions, duplications and misclassifications of units in the survey frame. Coverage errors may cause a bias in the estimates and the effect can vary for different sub-groups of the population.