Frequently Asked Questions (FAQs)
Questions about Ontario Health Team Planning
OHT applicants were "mapped" to one or more of the PhysNets based on the scope of their partnerships. Some of this mapping was straightforward – e.g., in those cases where the OHT included hospital and physician partners aligned to the same network, the OHT would be in high alignment with the PhysNet.
Although there were instances in which there were multiple OHTs in one PhysNet or the OHT spans multiple PhysNets – there was still a high degree of alignment between PhysNets and OHTs, since the mapping was based on the providers involved in each OHT.
In instances where an OHT had many partners across multiple PhysNets, the Ministry combined those networks.
Please note that PhysNet names were created by ICES to indicate where each network is located in Ontario. These names are not an indication of what the OHTs are called or should be called.
Ontario residents are not connected to a PhysNet based on where they live, but rather on how they access care.
The patient attribution model uses health card information to assign individuals to a physician. More specifically, patients are assigned to the physician they are rostered with or from whom they receive most of their care. Physicians are aligned to the hospital where the majority of their patients are admitted for non-maternal medical care.
Those individuals who have not had any health system interactions over the past three years are considered "non-users" and are attributed to networks based on their postal codes.
For more information on the methodology, see this blog.
Questions about the partnership and the website
This website is sponsored by The Ontario Community Health Profiles Partnership (OCHPP) to make detailed, area-level health data available to everyone. Our goal is to support action to reduce health inequities in Ontario.
For more information see About Us page.
As a group of epidemiologists, medical geographers and academic health researchers, the partnership members have access to the community-level demographic, socioeconomic, and population health information and provide this important data to community organizations and health and
social services providers (all community-based service providers, planners, and policy-makers) throughout Ontario, and have the expertise to produce and provide the key health indicator statistics and maps using consistent data standards, methods and definitions.
The Ontario Community Health Profiles Partnership (OCHPP) website, www.ontariohealthprofiles.ca, is a portal that provides comprehensive, reliable and validated data on health and health-relevant indicators. The website was created in response to continuing requests from community agencies and partners for data that could be used for local and agency health planning and program development.
The website was originally launched in 2005 as the "Toronto Community Health Profiles Partnership (TCHPP)" and included data for Ontario LHINs and data for the City of Toronto. After expanding in 2016, the site now contains data that extends beyond the City of Toronto. Consequently, the site name was changed to the "Ontario Community Health Profiles Partnership (OCHPP)". Archived, Ontario LHINs and City of Toronto-specific data can be found on the OCHPP site in the Data Archives section.
Data-sharing partners include government, public health professionals, community health providers and researchers.
This site complements other health information sites (Health Quality Ontario, Statistics Canada Health Indicators, Canadian Institute for Health Information (CIHI), ICES) and neighbourhood data sites with small area community health data not otherwise available.
We provide health and health-related indicators in three basic forms: data tables, bar charts and health data maps:
Health Profiles by All areas data (Excel format): Community-level health indicators ‐ this micro-data provides detailed statistics about populations living in communities by sex and relevant age-groups for each health indicator.
Health Profiles by custom selected areas data (Excel format): A useful tool for compiling data for a custom collection of neighbourhoods. Combine Neighbourhood areas to Create Custom Geography for selected indicators.
Bar Charts: Graphs are used to show how peoples` health may differ depending on their income or immigration status.
Health Data Maps: Ontario-wide health indicators - maps give an overview of how the health of different communities within Ontario compare with each other with respect to specific health indicators. These data are shown on maps with different colours representing different values across communities.
Questions about data
For information about definitions, data quality & limitations, selection & preparation of variables and to view our on-going workplan, please visit our
About the Data page.
"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.
In comparing health outcome such as diseases or health service utilizations among different geographic areas, given the differences in the age distribution of people living in these areas, comparing crude rate is not appropriate.
In order to do a proper comparison, we need to remove the possible effect of difference in age distribution among the two areas by assuming that both areas have a standard population. This process called "age standardization".
For further information please see this link: http://www.statcan.gc.ca/eng/dai/btd/asr
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.
RPDB 2022 tables are created from Postal Code data that are linked to Census 2016 Dissemination Area (DA) boundaries using a Postal Code Conversion File (PCCF). The most current version of the PCCF file available at ICES, our data partner, is based on Census 2016 DAs. Once a version of the Postal Code file is made available for Census 2021 geographies and brought into ICES, we will incorporate those DA assignments into the OCHPP crosswalk file and data methods.
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] 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.
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.
• Interactive maps allow users to view different combinations of health and socioeconomic indicators as well as reference
information such as major roads or hospital locations on one map.
• Users can zoom-in to specific areas, query the data for them, and export the results into a table.
Questions about 2021 Census of Population
We have now posted multiple variables to the OCHPP website for Census 2021. We plan to provide three more variables by the end of March 2023. If you are looking for a very specific data set, please reach out to us at HealthProfiles@smh.ca. We may be able to assist with your request.
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.