Frequently Asked Questions (FAQs)

Questions about Ontario Health Team Planning
    Ontario Health Teams (OHTs) organize and deliver care that connects patients to their care providers. Under Ontario Health Teams, health care providers (primary care providers, hospitals, and home and community care providers) work as one coordinated team – no matter where they provide care. OHTs were created based on a similar methodology for Physician Networks using a model that “attributed” patients to providers. For more information on OHTs and for a scientific paper that outlines the conception and methods see the paper by Dr. Therese Stukel and Rick Glazier here: This blog also provides a visualization of attribution/physician networks. (Note the blog is not updated).
    OCHPP provides a link to a project page on its website here: where data for OHTs is updated as it becomes available. OCHPP provides data at various levels of geography. Since OHTs are not geographically-based, OCHPP does not currently provide OHT-related data.

Questions about the Ontario Community Health Profiles Partnership and the website
    OCHPP’s long-term partners include health-care planners, hospital administrators, health agencies, community groups and researchers. The OCHPP internal team of experts works together with our partners to better understand and predict trends in local areas using spatial analytic methods linked to administrative health and socio-demographic data.
    The OCHPP website was launched in 2005 in response to a growing number of data requests for data that could be accessed in one place.The website is an open-access, freely accessible site that provides free data and maps for everyone to use, download and share. Health and socio-demographic indicators are provided in three basic forms: data tables, bar charts and/ or maps.
    For more information see About Us page.
    We provide data and maps both at the local and larger areas of geography. Local level maps shine a light on health equity concerns that may be masked at larger areas allowing policy makers to identify and address gaps in access to care. Through our open-access, freely accessible website, we provide free data and maps for everyone to use, download and share. We provide health and health-related indicators in three basic forms: data tables, bar charts and health data maps.

Questions about data
    For information about definitions, data quality and limitations, selection and preparation of variables and to view our on-going workplan, please visit our About the Data page or send us an email to
    "A health indicator is a single measure that is reported on regularly and that provides relevant and actionable information about population health and/or health system performance and characteristics. An indicator can provide comparable information, as well as track progress and performance over time."
    Canadian Institute for Health Information, Health System Performance. Web. 15 December 2015.
    Health outcomes, such as disease or health services utilization, often depend on a person’s age. Most OCHPP tables report crude rates. However, when comparing health outcomes across different geographic areas, crude rates do not consider the differences in age of each area’s population. In this case, comparing crude rates is not appropriate.
    To do a proper comparison, we need to remove the possible effect of differences in age distribution between areas by assuming that each area has a standard population. This process is called "age standardization" and, where appropriate, OCHPP tables report an age-standardized rate.
    For further information please see this link:
    A conversion file is, more specifically, a "geo-aggregation" file. These files are often used by data analysts and geographers to identify which small areas of geography are contained within larger areas. Conversion files create associations among areas of geography that differ in size or extent. They are also commonly referred to as "cross-walk" or "correspondence" files.

    An example of "geo-aggregation" may include aggregating population counts from many neighbourhoods (a small area of geography) to calculate the total population within the Sub-Region (a larger area of geography) where they are located.
    The Postal Code Conversion File (PCCF) is a file issued by Canada Post and used by the OCHPP project team to convert (or assign) the location of postal codes to Dissemination Areas (smallest unit of Census geography). The OCHPP team aggregates DAs to other levels of geography such as neighbourhoods/local areas and higher (sub-regions). For a full description of the variations within the PCCF file and the process of linking postal codes to other geographic areas, see the link to the PCCF document here:

    About Postal Code Conversion Files (PCCF): PCCF Single Link Identifier and PCCF Plus
    Starting in 2016, Statistics Canada was able to use administrative tax and benefit records provided by the Canada Revenue Agency to generate Census income statistics. The reference year for these income data is the calendar year preceding the Census. All income statistics from the 2021 Census, for example, are for 2020 calendar year: January 1, 2020, to December 31, 2020.
    OCHPP uses the Registered Persons Database (RPDB) as the population of record; that is, the source of population for health indicator denominator counts and as the denominator for calculating rates. RPDB contains information on persons registered under the Ontario Health Insurance Plan (OHIP) and who are eligible for the Ontario Drug Program. RPDB is maintained at ICES. For (most) non-health related indicators such as sociodemographic indicators we use Statistics Canada’s Census of population as our source. See the link to the document on OCHPP that outlines reasons why we decided to use RPDB as the source for our health and health utilization reporting e.g hospital admissions indicators here:
    OCHPP health indicators currently use RPDB tables created from Postal Code (PC) data that are linked to Census 2016 Dissemination Area (DA) boundaries. The PC-to-DA linkages are made using a Postal Code Conversion File (PCCF). When our RPDB2023 denominators were tabulated, the most current version of the PCCF file available at ICES, our data partner, was based on DAs from the 2016 Census. A version of the Postal Code file is now available for Census 2021 geographies and in ICES; we will incorporate those DA assignments into the OCHPP crosswalk file and data methods when we next update the OCHPP RPDB denominators (sometime in Spring 2024).
    In December 2019, Ontario Health transitioned the former 14 LHINs into five Interim and Transitional Geographic Regions (“Interim Health Regions”); the number of regions subsequently expanded to six by creating two regions in the North. These six areas are now known as “Ontario Health Regions”. Additionally, as of April 1, 2023, Ontario Health (OH) realigned the borders of its Central, East and Toronto OH regions with the City of Toronto’s municipal boundaries. Health (and other) indicator data generated by OCHPP for OH regions reflect the realigned boundaries. OCHPP content prior to March 02, 2023 report on the initial five “Ontario Health Interim and Transitional Regions”. As of October 16, 2023, these data are now found in the OCHPP Archives. Disclaimer: Because of the changes between December 2019 and April 1, 2023, data analysis of legacy six OH Regions in place prior to April 1, 2023 and data from the legacy Local Health Integration Networks (LHINs) are not directly comparable. Neither are analyses of data across the Interim Health Regions and the Ontario Health Regions. Caution is required when comparing data across these data periods.
    The Ontario Community Health Profiles Partnership (OCHPP) has a partnership with ICES from where we obtain the majority of our health data. These data are provided to us as coded, de-identified, postal-code-level records. OCHPP aggregate these data and publish data tables and maps at local (“neighbourhood”) and larger areas of geography. Rates and population counts published by OCHPP exclude persons whose postal codes are located within areas classified by Statistics Canada as Census subdivision (CSD) types IRI or S-É*. Note that agreements may be in place between ICES and Indigenous communities to allow some Indigenous community data to be shared publicly. However, at this time, OCHPP will not publish health indicators or socio-demographic data about Indigenous communities as part of our standard data sets. Please contact us for more information.

Questions about maps
    Maps are a visual illustration of spatial characteristics of data. They help to identify areas of concern, where, for example, there are high concentrations of factors negatively impacting health outcomes, or regions with elevated rates of diseases. Maps can be also considered as a complementary element to tabular data. They help identify spatial patterns and formulate additional hypothesis based on those patterns.
    There are several map types on this site.

    Choropleth or shaded maps depict rates or ratios, for example `Annual Rate of Chlamydia per 100,000`. These maps are constructed using either `natural breaks` [NB], or `populated-weighted quintiles` [PWQ] data classes. Data classes are simply different ways of grouping data values into ranges depicted on a choropleth map by a specific shade of a colour. `Natural breaks` is a more common way we classify the data on maps on this site. For more info on choropleth maps and data classification methods please see `How to Read the Maps` in the `About the Data tab.

    Rate-Ratio [RR] (archived) maps compare the rate of the depicted variable in the given area (e.g. neighbourhood) to the average rate of this variable for the whole study region (e.g. Central LHIN). If the rate in the given area is higher than the one in the study area the rate-ratio value is greater than 1. If the rate in the area is lower than in the study region`s one the RR value is less than 1. RR maps also show whether the differences between the rates in specific areas and the overall study area rate are statistically significant or not. For more info on rate-ratio maps please see `How to Read the Maps` in the `About the Data` tab.

    Graduated Symbol maps can be used to depict rate, ratio, frequency, on other numeric variable types. Values of the mapped variable are sorted and grouped into classes based on Natural Breaks or other classification methods. Each class is shown with a specific symbol size, where classes including smaller values are shown with smaller symbols, and larger values are shown with larger symbols.

    Dot chart maps are typically used to show the count or frequency variables. One dot can represent the value of 1 or more, e.g.: 1 dot represents 200 people. Dots are placed randomly within an area, which value they represent.

    Pie Chart maps can be used to depict rate, ratio, frequency, on other numeric variable types. It is a variation of graduated symbol map. Pie chart maps allow for an additional level of information by dividing the circular graduated symbol into different colour parts, or slices representing portions of the variable subgroups, e.g.: 55% females and 45% males would be represented by almost the same size pie parts (slightly larger for females). The overall size of the circular symbol would represent the total sum of all females and males in the area.
    Yes, but caution needs to be applied when drawing conclusions just based on maps. Maps and tabular data are meant most of the times as complementary pieces of information and ideally they both should be used in the research or policy-oriented processes. In addition to these two elements the expert knowledge of the area`s or population`s characteristics should be also applied.

Question about Neighbourhoods
    In June of 2019, The Social Development, Finance and Administration division of the City of Toronto split Toronto`s 140 neighbourhoods to account for population change over the last 20 years. City of Toronto neighbourhood identification numbers (IDs) are sequential from 1 to 140; however, where a neighbourhood has been split, its ID under the prior numbering system has been removed and replaced with two (or more) new IDs. Numbering for new neighbourhoods begins at 141. There are 34 new identification numbers (141 thru 174) to replace 16 neighbourhoods where administrative boundaries have been reconfigured to define 18 new neighbourhoods. There are gaps in the numbering sequence between 1 and 174 to accommodate these changes. Users should exercise caution when comparing data before and after January 27, 2020, when these boundaries were officially incorporated into new OCHPP indicator data sets.
    “Small area” is the catch-all term we use when referring to the smallest level of geographic aggregation we use for reporting data and for creating thematic maps. The total population of these areas typically range between 5,000 and 30,000 to allow for a sufficient sample size of most of our indicators. “Neighbourhood” is a type of small area used in some regions, e.g. in Toronto and Ottawa. “Local area” is another type of small area used in Ontario Health Central region. The terms, “Small areas”, “local areas”, and “neighbourhoods” are often used interchangeably.

Question about terminology
    OCHPP acknowledges that the use of language such as male/female does not include those who do not identify as such. We are limited in the way data is provided to us but are mindful of the concerns of those who may query this use of language. Revisions to terminology and language are part of our website’s review process and will be revised on an on-going basis.
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