Technical notes

These notes provide general comments to assist with accurate interpretation of the health indicators. Please see the descriptions for specific information on indicator definitions, sources, calculation methods, and other details. Additional information on interpretation, comparability, relevant standards/benchmarks, and other material is available upon request.

• Regional health indicators
• Health status indicators based on vital statistics (Statistics Canada - STC)
• Indicators based on Cancer Incidence (STC)
• Indicators based on National Population Health Survey and the National Longitudinal Survey of Children and Youth (STC)
• Indicators based on 1996 to 2000 labour force data (STC)
• Indicators based on 1996 Census data (STC)
• Health System Indicators (Canadian Institute for Health Information - CIHI)
• Appendix 1

Regional health indicators

The methodology used for these indicators was designed to maximize inter-regional and inter-provincial comparability given the characteristics of available national datasets. For this reason, there may be differences between definitions, data sources, and extraction procedures used in some local, regional, or provincial/territorial reports when compared to those described here. In addition, discrepancies may exist due to on-going updates to databases.

Rates are standardized wherever possible to facilitate comparability across provinces/regions and over time.

Health region level rates and population estimates presented in this publication are based on the boundaries in effect as of January 1999.

Indicators based on hospitalization records are limited to health regions with population greater than 100,000.

Health region level population estimates:

Population estimates for health regions were produced by Statistics Canada (Demography Division) for all provinces, except Quebec, Alberta and British Columbia. Quebec health region population estimates were provided by l'Institut de la statistique du Québec, Alberta population estimates from Alberta Health and Wellness and British Columbia population estimates were provided by BC Stats. See Appendix 1 for methodology.

Highlights:

The Highlights contain a number of data comparisons. For all tables containing National Population Health Survey (NPHS) and National Longitudinal Survey of Children and Youth (NLSCY) data, rate comparisons have been tested for statistical significance. For all tables containing vital statistics data and average personal income, the rates have been compared for statistical significance at the 95% confidence level to their respective Canada rates. These highlights contain terms such as "significantly high", "not significantly different" or "signficantly low" and refer to statistical significance tests. They should not be confused with terms such as "much higher" or "much lower", which refer strictly to numerical differences. All other highlights have been written according to comparisons of point estimates and do not take into account sampling variability.

Health status indicators based on vital statistics (Statistics Canada - STC)

• Rates are based on place of residence for indicators derived from birth and death events.

• Indicators presented in this product which were derived from vital statistics, are based on three years of data in both numerator and denominator. For low birth weight, three years (e.g., 1995 to 1997) of the appropriate birth data are used in both the numerator and denominator. For infant and perinatal mortality, three years of death or stillbirth data are divided by the same three years of birth data. For mortality, three years of death data (e.g., 1995 to 1997) are divided by three times the mid-year (e.g., 1996) population estimate. In all vital statistics table titles, the year mentioned simply refers to the middle year (e.g., 1996).

• All data presented have an associated 95% confidence interval (CI). The confidence interval illustrates the degree of variability associated with a rate. Wide confidence intervals indicate high variability, thus, these rates should be interpreted and compared with due caution. Some age-standardized rates were suppressed due to both a very small underlying count plus extremely high variability. Confidence intervals can also be used to determine whether a rate in one health region is statistically below, above or no different than the rate for the same indicator in another health region.

• The confidence intervals for the age-standardized rates were produced using the Spiegelman method. Reference: Spiegelman M. Introduction to Demography, Revised Edition. Cambridge Massachusetts: Harvard University Press, 1968. p 113, Formula 4.29

• The confidence intervals for the crude count, crude rate and birth-related data were produced via the Fleiss method. Reference: Fleiss JL, Statistical Methods for Rates and Proportions, 2nd Ed, Wiley and Sons, NY, 1981. Take note that the lower confidence interval (CI) in this formula is constrained by zero, which means the difference between the rate and the lower CI is not always equal to the difference between the rate and the upper CI.

• Due to the small population of Churchill health region (4690), Manitoba (pop. 1,110 in 1996) and the number of deaths, virtually all vital statistics data for this health region would, in the absence of any adjustment, need to be suppressed. As such, in this product all vital statistics data presented for region 4680 (Burntwood) are an aggregate of Burntwood and Churchill regions. For census-related data, however Burntwood and Churchill are presented separately.

• Mortality rates, with the exception of crude rates, potential years of life lost (PYLL) and infant and perinatal mortality, are age-standardized using the direct method, and the 1991 Canadian Census population structure. The use of a standard population results in more meaningful mortality rate comparisons, because it adjusts for variations in population age distributions over time and across different geographic areas.

• Birth and death data for 1996 and beyond (and 1995 birth and death data from Alberta) have been linked to health regions using postal codes reported with place of residence and converted to enumeration area (EA) using the automated geo-coding system developed in Health Statistics Division. These data were then aggregated to health region based on the EA level correspondence developed in Health Statistics Division with the cooperation of provincial Ministries of Health, Alberta Treasury and BC Stats.

• Birth and death data (except Alberta) from 1995 and the small portion of records from 1996 onwards which had no postal code information were linked to health regions using at least one of two methods:

1. For most records (where health regions are comprised of complete census subdivisions) the standard geographical classification codes recorded on the vital statistics database were used to link records to health region.
2. Selected records (those linked to census subdivisions which are associated with more than one health region) were extracted from the data base. Using the registration numbers of these events, birth registration records and death certificates were accessed and the postal codes for place of residence were captured. These records were then geo-coded to enumeration areas (same as for data years 1996 and 1997), linked to health regions using the EA-to-HR correspondence, then merged with the remaining data for that year to get the most accurate health region link.

• Birth statistics: Birth data on our Vital Statistics Database for Ontario are underestimated for data years 1995, 1996 and 1997 due to incomplete files. Birth data for those same years for some other provinces may also be affected by this incompleteness. Thus, birth-related data (low birth weight, infant mortality and perinatal mortality), particularly for Ontario, should be interpreted with caution.

Life expectancy: This variable was calculated using the Chiang methodology for abridged life tables. The estimates are based on three years (e.g., 1995-1997) of mortality data and the mid-year population estimates, as described above. Abridged life tables use five-year age groupings of both population and mortality rate inputs (as opposed to single year age breakdown). Since there is more variability in the number of events by age in smaller geographic areas, abridged life tables are more suitable for the adaptation to a sub-provincial level (health region). Chiang’s method in particular was chosen because it was relatively easy to adapt to the health region level data and included the calculation of standard error (in this case, addressing the variability of deaths from one year to the next).

Life expectancy revisions (Vol. 2001, No. 3 and beyond): A methodological adjustment was made to the calculation of life expectancy. The change only affects the life expectancy values for both sexes combined. Users are encouraged to use the life expectancy data found in Health Indicators issues from this release onwards.

Disability-free life expectancy: Estimates of disability-free life expectancy are calculated using Sullivan’s method (Sullivan, DF. A single index of mortality and morbidity. HSMHA Health Reports 86 (April 1971) : 347-354). Essentially, the latter generalizes Chiang’s method (Chiang, CL. The Life Table and its Applications. Robert E. Krieger Publishing Company, Malabar, Florida, 1984: 316).

Sullivan’s method is based on activity limitation rates within a population, according to sex and age group, in the calculation of life expectancy with disability. In the case of people living in health institutions, it was assumed that everyone had at least one activity limitation. For people living in other types of institutions, the hypothesis established is that the activity limitation rate by age group and sex was identical to the population in private households.

Disability-free life expectancy represents the difference between life expectancy and life expectancy with disability. The standard deviations of disability-free life expectancy estimates (and consequently the upper and lower limits of the confidence intervals associated with these estimates) are based on Colin Mathers’ method (Mather, C. Health Expectancies in Australia 1981 and 1988. Australian Government Publishing Service, Canberra, 1991: 117). This method takes into account both the stochastic fluctuations in the observed death rates and the sampling variability of the activity limitation rates.

NOTE: The disability data for DFLE came from the 1996 Census of Population. Questions on disability in the Census of Population are generally used to capture the sample of post-censal Health and Activity Limitations Survey. Because of the decision not to conduct this survey in 1996, data on disability from the Census of population of 1996 were neither verified nor imputed. More precisely, no validation was undertaken to check the completeness or consistency of the data, and as a result, no corrections to the data were made. In addition, the data were not adjusted to account for population undercounts.

DFLE estimates will vary according to both the concepts from which they are based and the surveys from which the data are extracted.

DFLE (Volume 2001, No’s. 1 and 2): For these issues, disability was defined as "having any activity limitation or handicap".

DFLE (Volume 2001, No. 3 and beyond): For this issue and for future issues, disability is defined as "having an activity limitation that affects activities at home, work or at school". This differs from previous Health Indicators issues by excluding limitations that only affect activities other than home, work or school as well as respondents who stated that they had some form of handicap other than an activity limitation.

Deaths due to medically treatable diseases

• The definitions the medically treatable diseases were taken from a paper written by JRH Charlton (Charlton JRH, "Avoidable deaths and diseases as monitors of health promotion", pp. 467-479, in Measurement in health promotion and protection, Copenhagen and Albany NY: World Health Organization and the International Epidemiological Association, 1987). The types of medically treatable diseases mentioned in Charlton originally came from a paper by DD Rutstein (Rutstein DD, "Monitoring progress and failure: sentinel health events (unnecessary diseases, disabilities and untimely deaths", pp. 195-212, in Measurement in health promotion and protection, Copenhagen and Albany NY: World Health Organization and the International Epidemiological Association, 1987).

• All results were age-standardized according to the age group considered for reasonable odds of survival. These age-standardized rates per 100,000 reflect these age groups, not the total population.

• The method of calculating confidence intervals was the Spiegelman method. Reference: Spiegelman M. Introduction to Demography, Revised Edition. Cambridge, Massachusetts: Harvard University Press, 1968. p. 113, Formula 4.29

Potential Years of Life Lost

• In this publication, death was considered premature if the person died before age 75. This is more reflective of life expectancies in recent years and is more reflective of international standards. Many previous Statistics Canada publications provide PYLL data based on death before age 70. Additionally, PYLL can be presented as an age-standardized rate or as a crude rate; in this publication, it is presented as a crude rate. As well, the denominator can be based on population aged 0 to 74 or for the total population. In this publication, the denominator is based on the former. Thus, the data in this publication cannot be easily compared with prior analyses.

• In this publication, a PYLL rate was produced, where the weights are taken as proportions of the years lost per death within each age group over the total years lost in all age groups. Each death event is multiplied by its age-specific weight. The sum of all these values represents the total PYLL. The PYLL rate is PYLL per 100,000 population aged 0 to 74. The use of weights allows for the calculation of confidence intervals. The confidence intervals for each PYLL rate were produced by the Spiegelman method. Reference: Spiegelman M. Introduction to Demography, Revised Edition. Cambridge, Massachusetts: Harvard University Press, 1968. p. 113, Formula 4.29

AGE GROUP	YEARS LOST	WEIGHT
Under 1	74.9	74.9/636.9
1-4	72.0	72.0/636.9
5-9	67.5	67.5/636.9
10-14	62.5	62.5/636.9
15-19	57.5	57.5/636.9
20-24	52.5	52.5/636.9
25-29	47.5	47.5/636.9
30-34	42.5	42.5/636.9
35-39	37.5	37.5/636.9
40-44	32.5	32.5/636.9
45-49	27.5	27.5/636.9
50-54	22.5	22.5/636.9
55-59	17.5	17.5/636.9
60-64	12.5	12.5/636.9
65-69	7.5	7.5/636.9
70-74	2.5	2.5/636.9
SUM	636.9	1.0

This publication only presents PYLL rates based on the sum of all age groups. Thus, the rate is calculated as follows:

Where PYLL is the sum of PYLL for ages 0 to 74 for the three years of data, WT is a weight of 1.0 and POP is the population aged 0-74 for the middle year of the three years.

If a user wanted to calculate age-specific PYLL rates based on their own data, the formula would be:

where i is the specific age group.

Indicators based on Cancer Incidence (STC)

Cancer Incidence

The Canadian Cancer Registry (CCR) is a central database located at Statistics Canada that contains patient-oriented information about diagnosis of cancers in Canada. Data on the incidence of cancer are collected by the provincial and territorial cancer registries. The information is used for descriptive and analytic epidemiological studies: to identify risk factors for the cancer; to plan, monitor and evaluate a broad range of cancer control programs (e.g., screening); and for health services and economic research and planning.

• Cancer incidence is based on place of residence at time of diagnosis.

• Data contained in this table have been tabulated using the September 30, 2000 file and the International Agency for Research on Cancer (IARC) rules for determining multiple primaries sites. Included are cancer sites 140 to 208 from the International Classification of Diseases, Ninth Edition (ICD-9).

• Cancer incidence data in this product are based on three years of data (e.g., 1994 to 1996) averaged over the 1995 population estimate. Table titles associated with these data reflect the mid-point of the three-year period being averaged (i.e., 1995).

• All data presented have an associated 95% confidence interval (CI). The confidence interval illustrates the degree of variability associated with a rate. Wide confidence intervals indicate high variability, thus, these rates should be interpreted and compared with due caution. Some age-standardized rates were suppressed due to both a very small underlying count plus extremely high variability. Confidence intervals can also be used to determine whether a rate in one health region is statistically below, above or no different than the rate for the same indicator in another health region.

• The confidence intervals for the age-standardized cancer incidence rates were produced via the Spiegelman method. Reference: Spiegelman M. Introduction to Demography, Revised Edition. Cambridge, Massachusetts: Harvard University Press, 1968. p. 113, Formula 4.29

• Some age-standardized rates were suppressed (- -) due to both a very small underlying count plus extremely high variability.

• Due to the small population of Churchill health region (4690), Manitoba (pop. 1,110 in 1996) and the number of events, virtually all cancer incidence statistics data for this health region would, in the absence of any adjustment, need to be suppressed. As such, in this product all cancer incidence data presented for region 4680 (Burntwood) are an aggregate of Burntwood and Churchill regions. For census-related data, however Burntwood and Churchill are presented separately.

• Cancer incidence rates are age-standardized using the direct method and the 1991 Canadian Census population structure. The use of a standard population results in more meaningful incidence rate comparisons, because it adjusts for variations in population age distributions over time and across different geographic areas.

• Over 95% of the cancer incidence data for 1994, 1995 and 1996 have been linked to health regions using postal codes reported with place of residence and converted to enumeration area (EA) using the automated geo-coding system developed in Health Statistics Division.

• The remaining 5% of cancer incidence data (for which there were no postal codes available) were linked to health regions using the census subdivision (CSD) of residence using the automated geo-coding system developed in Health Statistics Division.

• Approximately 7% of Ontario cancer incidence records over the 3-year period could not be linked to health region geography. As such, cancer incidence data for Ontario are only published at the provincial level.

• Cancer incidence data for the three northern health regions in Quebec (2410, 2417 and 2418) have been suppressed at the request of the Quebec Cancer Registry.

• Cancer incidence data for health regions in Newfoundland, Prince Edward Island and Alberta have been suppressed at the request of their respective Cancer Registries.

Indicators based on National Population Health Survey and the National Longitudinal Survey of Children and Youth (STC)

National Population Health Survey

The National Population Health Survey (NPHS), which began in 1994/95, collects information about the health of the Canadian population every two years. It covers household and institutional residents in all provinces and territories, except persons living on Indian reserves, Canadian Forces bases, and in some remote areas. The NPHS has both a longitudinal and a cross-sectional component. Respondents who are part of the longitudinal component will be followed for up to 20 years.

The Health Indicators data are based on both the longitudinal and cross-sectional components for household residents (institutional excluded) living in the provinces (territories excluded). Data are available for the first three cycles (1994/95, 1996/97 and 1998/99).

The 1994/95 and 1996/97 cross-sectional samples are made up of longitudinal respondents and their household members and individuals who were selected as part of supplemental samples, or "buy-ins", in some provinces. The 1998/99 cross-sectional sample is made up mostly of longitudinal respondents and their cohabitants. No buy-ins were added to 1998/99 data. However, to keep the sample representative, infants born in 1995 and thereafter and immigrants who entered Canada since the beginning of 1995 were randomly selected and added to the NPHS sample.

The 1994/95 provincial, non-institutional cross-sectional sample consisted of 27,263 households, of which 88.7% agreed to participate in the survey. After application of a screening rule to maintain the representativeness of the sample, 20,725 households remained in scope. In 18,342 of these households, the selected person was aged 12 or older. Their response rate to the in-depth health questions was 96.1% or 17,626 respondents. In 1996/97, the overall response rate at the household level was 82.6%. The response rate for the randomly selected individuals aged 2 or older in these households was 95.6%. In 1998/99, the overall response rate was 88.2% at the household level. The response rate for the randomly selected respondents 0 or older in these households was 98.5%.

The 1994/95 provincial, non-institutional longitudinal sample consisted of 17,276 respondents. A response rate of 93.6% was achieved in 1996/97, and a response rate of 88.9% was achieved in 1998/99.

National Longitudinal Survey of Children and Youth

The National Longitudinal Survey of Children and Youth (NLSCY), developed jointly by Human Resources Development Canada and Statistics Canada, is a comprehensive survey which follows the development of children in Canada and paints a picture of their lives. The survey monitors children’s development and measures the incidence of various factors that influence their development, both positively and negatively.

The first cycle of the NLSCY, conducted in late 1994 and early 1995, interviewed parents of approximately 23,000 children up to the age of 11. They shared information not only about their children, but also about themselves and the children's families, schools and neighbourhoods.

The second cycle, carried out in winter and spring of 1996-97, interviewed parents of the same children and provides unique insights into the evolution of children and their family environments over a two-year period. A new sample of newborn and 1-year-old children was added to cycle 2 to allow for cross-sectional estimates.

Collection of cycle 3 began in the fall of 1998 and was carried until June 1999. In addition to the original sample of children, who were aged 2 to 13 years at the time of the second data collection, a new sample of newborn and 1-year-old children was added to cycle 3 to allow for cross-sectional estimates. An extra cross-sectional sample of children 5 years old was also added to allow some provincial estimates for that age group.

BOOTSTRAPPING:

To ensure high data quality for estimates from the NPHS and NLSCY, a weighted bootstrap resampling procedure was used to calculate coefficients of variation (CVs) for totals and rates. If the CV was greater than 33.3% or the sample size was less than 10, the data were suppressed and an ‘F’ symbol appears in the data cell. If the CV is greater than 16.5% and no greater than 33.3%, the data should be interpreted with caution and an ‘E’ symbol appears in the same cell as the data. Data with CVs of 16.5% or less are presented without restrictions.

Sampling theory dictates that sample survey results of exactly 100% or 0% must have a coefficient of variation of exactly 0. In reality it is possible that in rare circumstances the true estimate may be lower than 100% or conversely greater than 0% and results should be interpreted as such.

Indicators based on 1996 to 2000 labour force data (STC)

• Regional unemployment rates and youth unemployment rates where calculated as annual averages from the Canadian Labour Force Survey (LFS). The estimates were derived by linking, at the enumeration area (EA) level, the LFS geography to health regions.

• Some health regions could not be published as the estimated rate did not meet the minimum requirements for quality and confidentiality.

• The LFS is a monthly sample of approximately 52,000 households. The survey is designed to represent the Canadian population aged 15 years and older. The survey excludes Indian reserves, full time members of the Canadian Forces, and persons living in institutions. The survey also excludes the Territories.

• The unemployment rate is the number of unemployed persons divided by the labour force population, expressed as a percentage. An unemployed person is someone who:

• was without work and had looked for work

• was on temporary layoff and available for work

• had a new job to start in the future.

The labour force population consists of the unemployed people plus the employed persons. To be employed, a person

• worked at any job at all

• had a job but was not at work during the reference week.

Indicators based on 1996 Census data (STC)

• Regional data on non-medical determinants of health indicators and certain community characteristics were extracted from the 1996 Census, based on enumeration areas (EA). A correspondence file, linking EAs to current health regions has been developed in the Health Statistics Division of Statistics Canada with the cooperation of provincial Ministries of Health, Alberta Treasury and BC Stats.

• Income-related indicators from 1996 Census are based on 1995 income.

• Low income rate, children in low income families: Low income data were not derived for economic families or unattached individuals in the Territories or on Indian reserves. For health regions containing Indian reserves, analysis of low income data should only be done with this caveat explicitly noted.

• Housing affordability: Farm homes and band housing on Indian reserves were not included in the calculation of housing affordability. For health regions containing Indian reserves, analysis of housing affordability should only be done with this caveat explicitly noted.

• Proportion Aboriginal population: This variable is derived from three questions asked in the 1996 Census (20% sample). Aboriginal population refers to those persons who reported identifying with at least one Aboriginal group, i.e. North American Indian, Métis or Inuit and/or those who reported being a treaty Indian or a Registered Indian as defined by the Indian Act of Canada and/or who were members of an Indian Band or First Nation. Census coverage studies were used to adjust these data with the population estimates for incompletely enumerated Indian Bands or reserves. The 1996 demographic population estimates (which adjusts for census undercoverage and refusal reserves) were used as the denominator for these percentages.

• Owner-occupied dwellings: Band housing on Indian reserves and collective dwellings were not included. For health regions containing Indian reserves, analysis of owner-occupied dwellings should only be done with this caveat explicitly noted.

• Average expected dwelling values: The same exclusions for owner-occupied dwellings apply for this variable, in addition to farms.

For more information on census concepts, please refer to the 1996 Census Dictionary, Statistics Canada, Catalogue no. 92-351-XPE.

Health System Indicators (Canadian Institute for Health Information - CIHI)

• CIHI’s Privacy and Confidentiality policy does not permit the publication of data that might reasonably identify an individual, whether a patient or care provider, without consent. As a result, measures were taken to protect against residual disclosure from the dissemination of the regional rates including the suppression of small cell sizes. . In addition, reporting data based on the region of the patient’s residence (not hospitalization) for most jurisdictions reduces opportunities for identifying individual care providers.

Hospitalization data and rates (CIHI)

• Data are reported based on the region of the patient’s residence, not region of hospitalization. Consequently, these figures reflect the hospitalization experience of residents of the region wherever they are treated, as opposed to the comprehensive activity of the region’s hospitals (who will also treat people from outside of the region).

• Regional estimates for British Columbia are derived from reported postal codes using a translation file developed by BC STATS, BC Ministry of Finance and Corporate Relations. Health region level data for other provinces were produced through a geo-coding process using correspondence files developed with input from each provincial health ministry and Alberta Treasury. The link between enumeration areas and health regions was first created to provide the best resolution to census geography, and a census subdivision link to health regions was derived from this file. The boundaries are those that were in effect in January 1999. Records with invalid, missing, or partial postal codes are not included in regional counts. The absence of complete postal codes from Quebec may affect rates for the Champlain District Health Council (Ottawa area) and other border regions.

• Where possible, Canadian indicator values, based on data from all provinces and territories, are provided for comparison purposes.

• At the national level, rates for health data that are based on a fiscal year (April to March) use October 1^st population estimates. Unless otherwise specified, Canadian hospitalization rates are standardized using the same methodology as regional rates (see specific note below). Other rates are based on appropriate population figures. Canadian rates for physicians are based on July 1^st population estimates.

• Standardized rates are age adjusted using a direct method of standardization based on the July 1^st, 1991 Canadian population as follows:

Source : Statistics Canada Cat. No. 84F0208XPB, Causes of Death 1997, Appendix 3

• Unless otherwise specified, hospitalizations include discharges and deaths for inpatients in acute care hospitals for the reference period. Same day surgery (outpatient) cases and patients admitted to non-acute care hospitals (e.g. chronic care, psychiatric or rehabilitation facilities) are not included in the totals.

• Data from the Discharge Abstract Database (DAD) include only jurisdictions that submit comprehensively to the database. Therefore, data from Quebec regions are not available for indicators derived from the DAD.

• Cancelled and previous procedures: Where information is available, cancelled and previous procedures are excluded from the calculations. For Quebec data, cancelled procedures are not reported and therefore have not been excluded.

• Bypass Surgery: In some cases, an alternative intervention to improve blood flow to the heart muscle is coronary angioplasty. Variations in the extent of this procedure may result in variations in bypass surgery.

• 1998 figures for indicators derived from the Discharge Abstract Database may vary in some regions from previous figures due to recent updates to the database for hospitalizations in Saskatchewan, Alberta, New Brunswick and Ontario.

• Indicator values for Alberta, Newfoundland and Nova Scotia regions may vary from previously published figures as a result of revised population estimates, improved techniques to clarify boundaries or due to actual changes in health region boundaries.

Physician data (CIHI)

• In some regions, health facilities and personnel provide services to a larger community than the residents of the immediate region. In others, residents will frequently seek care from physicians outside the region where they live. The ratios of physicians to population reflect the number of doctors in a region and have not been adjusted to take these movements into account. The extent to which this affects individual regions is likely to vary.

• Figures include active civilian physicians (including those that are not providing clinical services, e.g. health research, administration and teaching) and exclude interns and residents. At a regional level, records with invalid, missing, or partial postal codes were excluded from the totals. Reporting is generally based on the region of the physician’s office or hospital address (over 80% of cases), not region of residence. Reporting is based on total number of physicians on December 31 of the reference year (full or part time), not full time equivalent figures.

National Health Expenditure Database

• Expenditure figures include spending by both the public and private sectors. For further information, see National Health Expenditure Trends, 1975-2000.

• Provincial per capita figures are affected by numerous factors that will affect inter-provincial comparisons including, but not limited to, differing provincial inflation rates that are related to provincial differences in arbitration agreements between provincial governments and, for example, medical associations; different population distributions; geography; and differences in provincial purchasing power.

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