Ontario Community Health Profiles Partnership (OCHPP) - FAQs
 
 
 
 
 
 
 
 

Questions about the partnership and the website                 top

 
 
 
 

  Q: What is the Ontario Community Health Profiles Partnership (OCHPP) 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 (through inclusion of selected indicators for other Ontario communities.) For more information see About Us.
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  Q: Who created Ontario Community Health Profiles Partnership?

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.

In 2016 the Ontario Community Health Profiles Partnership launched this website with the purpose of making detailed, area-level health data available to everyone. We provide health profiles of Ontario communities for Ontario communities, with relevant and timely information.

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), Institute for Clinical Evaluative Sciences) and neighbourhood data sites with small area community health data not otherwise available.
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  Q: What kind of information can I find here?

We provide health and health-related indicators in two basic forms:

Ontario Health Profiles:
Community-level health indicators - the Health Profiles provide detailed statistics about people living in communities by sex and relevant age-groups for each health indicator and how these communities compare with the LHINs/Neighbourhoods overall. These data are available in pdf and table format.

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.
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Questions about data                 top

 
 
 
 

  Q: Where can I get more information about the data?

For information about definitions, data quality & limitations, and selection & preparation of variables, please visit our
About the Data page.
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  Q: What is an "indicator"?

"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."
Reference:
Canadian Institute for Health Information, Health System Performance. Web. 15 December 2015.
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  Q: Need additional clarification on what it means to age standardize.

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
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Questions about maps                 top

 
 
 
 

  Q: What can I infer from the 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.
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  Q: What is the difference between different map types?

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.
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  Q: Can I use maps exclusively for my research and omit the use of relevant data tables?

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.
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