Full Acknowledgements

Stukel TA, Croxford R, Rahman F, Bierman AS, Glazier RH. Variations in Quality Indicators Across Ontario Physician Networks, Applied Health Research Question (AHRQ) 2017 0900 918 000. Toronto: Institute for Clinical Evaluative Sciences; 2016.

Some data is provided from Applied Health Research Question 2017 0900 918 000. This study was supported by the Institute for Clinical Evaluative Sciences (ICES) which is funded by the Ontario Ministry of Health and Long-Term Care (MOHLTC).The opinions, results and conclusions are those of the authors and are independent from the funding source. No endorsement by ICES or the Ontario MOHLTC is intended or should be inferred. Parts of this material are based on data and/or information compiled and provided by CIHI. However, the analyses, conclusions, opinions and statements expressed in the material are those of the author(s), and not necessarily those of CIHI.

Parts of this material are based on data and information provided by Cancer Care Ontario (CCO). The opinions, results, view, and conclusions reported in this paper are those of the authors and do not necessarily reflect those of CCO. No endorsement by CCO is intended or should be inferred. These datasets were linked using unique encoded identifiers and analyzed at the Institute for Clinical Evaluative Sciences (ICES).

Disease Prevalence

Study period:

Fiscal year: 2014/15

Study population:

Champlain population estimates (2015/16) for individuals > 19

Cohort Inclusion Criteria:

1. Alive at index March, 31, 2015
2. DOLC is within 7 years – individuals had some contact with the healthcare system within 7 years of index
3. Person must be eligible for OHIP at index
4. Non-Ontario residents are excluded

Analysis:

1. The 2014/15 population of Champlain was pulled using RPDP and limiting to LHIN = ’11’ (Champlain).
2. Crosswalk files were used to identify: (1) Sub Regions; (2) Sub-Sub Regions; and (3) Ottawa Neighbourhoods.
3. Prevalence of each chronic disease was identified using the ICES derived cohorts (ODD, ASTHMA, HYPER, COPD) and Mental Health definitions from the HQO Physician Practice Reports (HQO Primary Care Practice Report (Technical Appendix).

Cancer Prevention

Study period:

Mammography: 2013/14 – 2014/15
Pap Smears: 2012/13 – 2014/15
Colorectal Cancer Screening: 2004/065 – 2014/15

Study population:

Champlain population estimates (2014/15) for individuals > 19

Cohort Inclusion Criteria:

Mammography:
Includes only women aged 52-69 years living in Ottawa on March 31st, 2015 who were eligible for OHIP and who had used services in past 3 years (who had DOLC in past 3 years).

Pap Smears:
Includes only women aged 21-69 years living in Ottawa on March 31st, 2015 who were eligible for OHIP and who had used services in past 3 years (who had DOLC in past 3 years).

Colorectal Cancer Screening:
Includes individuals aged 52-74 years living in Ottawa on March 31st, 2015 who were eligible for OHIP and who had used services in past 3 years (who had DOLC in past 3 years)

Any colorectal investigation – includes individuals belonging to denominator group who had any colorectal investigation between:
1) April 1st, 2013 and March 31st, 2015 for FOBT (2 years)
2) April 1st, 2010 and March 31st, 2015 for flexible sigmoidoscopy, single contrast barium enema, double contrast barium enema (5 years)
3) April 1st, 2005 and March 31st, 2015 for colonoscopy (10 years)

Cohort Exclusion Criteria:

Mammography:
– Had no DOLC ever (no health system contact)
– Died before index
– Breast cancer diagnosed ever (to end of observation period) using: ICD-9 codes: 174 in CIHI OR Record in OCR

Pap Smears
– Had no DOLC ever (no health system contact)
– Had a previous diagnosis of cervical cancer (ICD-9 codes: 180.0, 180.1, 180.8, 180.9; 182.0, 182.1, 182.8, 183.0, 183.2, 183.3, 183.4, 183.5, 183.8, 183.9, 179; ICD-10 equivalents)
– Had a hysterectomy (OHIP fee codes S810, S757, S758, S759, S816, S710, S763, S762, S727, S765, S766, S767; CIHI prcode 80.3, 80.4, 80.5, 80.6, 80.7, 86.42; incode 1RM89, 1RM91, 5CA89 4. )
– Died within the observation period.

Colorectal Cancer Screening
– Had no DOLC ever (no health system contact)
– Diagnosed with any colorectal cancer ever (OCR): ICD-9 codes: 153.0 to 153.4, 153.6 to 154.1
– Diagnosed with any severe inflammatory bowel disease ever (DAD/SDS): ICD-9 codes: 556, 556.0 to 556.9 and 555, 555.0 to 555.9; ICD-10 code equivalents

Analysis:

1. The 2014/15 population of Champlain was pulled as the denominator using RPDB and limiting to LHIN = ’11’ (Champlain).
2. Crosswalk files were used to identify: (1) Sub Regions; (2) Sub-Sub Regions; and (3) Ottawa Neighbourhoods.
3. Rates of each prevention indictor was identified at each level of geography

Mothers and Babies

Study period:

Fiscal year: 2014/15

Study population:

Champlain population estimates (2014/15)

Cohort Inclusion Criteria:

1. Alive at index March, 31, 2015
2. DOLC is within 7 years – individuals had some contact with the healthcare system within 7 years of index
3. Person must be eligible for OHIP at index
4. Non-Ontario residents are excluded

Analysis:

1. Children born in Ontario Hospitals during 3 fiscal years (2012/13 to 2014/15) was obtained from MOMBABY, then linked to DAD/SDS to identify all mothers who gave birth in hospital. Only births among women 15-49 were identifed.

2. The following rates were calculated:
– Total birth rate for total population, all age groups (sex-combined)
– Fertility rate (among females 15-49)
– Teen birth rate (among females 15-19)
– Low birth rate
– Births to women not born in Canada

3. Repeat analysis for all levels of geography

Mortality

Study period:

Fiscal year: 2011/12

Study population:

Champlain population estimates (2011/12)

Cohort inclusion criteria:

1. DOLC is within 7 years – individuals had some contact with the healthcare system within 7 years of index
2. Person eligible for OHIP
3. Non-Ontario residents are excluded

Analysis:

1) Pull death data from ORGD, and link to cohort to identify the number of deaths among persons under the age of 75 (i.e. Premature deaths)
2) Identify the top 5 leading causes of premature mortality (name, %)
3) Repeat analysis for all levels of geography.