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ICES Pr imary Care and Populat ion Heal th Research Program Ins t i tu te for C l in ica l Eva luat ive Sc iences ICES Pr imary Care and Populat ion Heal th Research Program

Using linked data to measure performance at the healthcare system and clinical practice

level in Canada: putting primary healthcare in the picture

Challenging Ideas Seminar Nov 9, 2015 NSW Bureau of Health Information

Rick Glazier, MD, MPH, FCFP Senior Scientist, Institute for Clinical Evaluative Sciences

Scientist, Centre for Research on Inner City Health, St. Michael’s Hospital Professor, Family and Community Medicine, University of Toronto

ICES Pr imary Care and Populat ion Heal th Research Program

Faculty/Presenter Disclosure

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•Faculty: Rick Glazier

•Relationships with commercial interests:

– Grants/Research Support: none

– Speakers Bureau/Honoraria: none

– Consulting Fees: none

– Other: none


Disclosure of Commercial Support

This program has received financial support from N/A in the form of N/A

This program has received in-kind support from N/A in the form of N/A.

Potential for conflict(s) of interest: – Rick Glazier has received N/A from N/A

– N/A a product that will be discussed in this program: N/A

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Mitigating Potential Bias

• Mitigation N/A

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Learning Objectives

1. Appreciate the role of primary healthcare in health systems

2. Compare Canadian and Australian contexts

3. Learn about Canadian data linkage initiatives

4. Appreciate varied sources and types of primary healthcare data

5. Consider the benefits of aligned versus linked data

6. Discuss the value of putting primary healthcare in the picture

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Health System Role of Primary Healthcare

•Health services accessed each day

- extensive contact with the public

•Primary care and health outcomes

- better health outcomes, satisfaction with care, lower costs

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Health Services Accessed Each Day (ICES Primary Care Atlas)

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Primary Healthcare and Outcomes

•Primary care associated with

• Lower • mortality, premature mortality, infant mortality

• disparities in overall mortality, infant mortality, low birth weight, stroke mortality, self-reported health, and avoidable hospitalizations

• Higher • satisfaction in relation to overall costs

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Macinko J et al. Health Services Research. 2003;38:831-65

Shi L et al. Health Services Research. 2002;37:529-50

Engstrom S et al. Scand J Prim Health Care 2001; 19:131-4

ICES Pr imary Care and Populat ion Heal th Research Program 9

Population 35.4 m 23.6 m Population density 3.8 per sq km 2.9 per sq km Seniors 16.8% 14.7% Net migration 5.66/1000 5.74/1000 Life expectancy 79.1/84.4 79.6/84.6 GDP per capita US $43,100 US$43,000 Health care spending 10.9% GDP 9.4% GDP Public vs private 69.8% 66.6%

We’re the same!


Physicians 2.5/1000 pop 3.4/1000 pop Primary care physicians 1.0/1000 pop 1.4/1000 pop Physician visits 7.7 per person 7.1 per person Hospital beds 1.7/1000 pop 3.4/1000 pop Same day/next day access 45% 65% Difficulty after hours 65% 59% ER use in past 2 years 44% 33% Data sources: OECD, Commonwealth Fund

But there are differences in health care


Canadian Health Care

• Canada Health Act • doctors and hospitals fully covered, no deductibles or co-payments

• drug coverage only for seniors and social assistance

• all other services vary

• Provinces and territories • responsible for health, organization of care and services vary

• Federal • transfer payments, national standards, drug approvals

• Primary healthcare • mostly independent small businesses, trend from solo to groups

• private provision, public payment

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Systems are Transforming

•Health systems reforms •rapid change – teams, EMRs, guidelines, payment reform

• Australia – GP Divisions, Medicare Locals, Primary Health Networks

• Canada – different in every province/territory, Patient’s Medical Home

• U.S. – PCMH, ACOs, Affordable Care Act

• U.K. – constant reform of funding, incentives

• New Zealand – independent practitioner associations

• Netherlands – regulated competition

• other countries – multiple reforms

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Primary Healthcare Transformation - Canada

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Hutchison B, Levesque JF, Strumpf E, Coyle N. Primary health care in Canada: systems in motion. Milbank Q. 2011;89(2):256-88. doi: 10.1111/j.1468-0009.2011.00628.x.


Canadian Data Linkages Example: Institute for Clinical Evaluative Sciences, Ontario

These data sets are held securely in a linked, de-identified form

Similar settings: Manitoba Centre for Health Policy, Population Health BC

1. Health Services Administrative Data

Physician billings

Prescription drug claims for those 65 and older

Inpatient hospital discharges

Emergency and ambulatory care visits

Home care and rehabilitation claims

Long-term care visits

2. People and Geography

Population estimates

Canada census profiles

Death records

All Ontarians eligible for health care benefits

3. Special Collections

Registries (cancer, stroke, cardiac care)

First Nations/Métis

Developmental disabilities

Federal immigration information

Electronic primary care office records

4. Derived Conditions

Diabetes

Hypertension

Chronic obstructive pulmonary disease (COPD)

Asthma

Acute myocardial infarction

Congestive heart failure

Inflammatory bowel disease

5. Survey Data

Health Surveys

6. Clinical Data

Patient information collected with consent in primary clinical studies

Supplementary clinical data from individual hospitals and other institutions

7. Chart Abstraction Data

Information on processes and quality of care collected directly from

patients’ charts

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Coded ICES Data

• Most data collected by ICES are record level with direct personal identifiers —

usually health card number and/or last name, first name, date of birth, gender and

postal code. This is necessary for the accurate assignment of a unique, confidential

ICES number — or "code". Each person in Ontario is assigned his/her own ICES

number. This ICES number (IKN) is the key to successful linkage across data sets.

• The first step when ICES collects data is the removal of direct personal

identifiers and assignment of a confidential code, the IKN, to each record. An

IKN exists for every Ontario resident who has been eligible for health care over

time. This identifier is created using a secure ICES algorithm that is based on the

Ontario health card number. Once records in a data set have an IKN assigned, the

directly identifying information is stripped off the file and the data become part of the

ICES data inventory – uniquely coded and linkable across health services data

bases within the inventory. Researchers have access only the ICES data

inventory that contains coded data.

Heal th Sys tem Trans format ion 17


Sources of Primary Healthcare Data (Ontario)

• Databases • population registry – age, sex, rurality, SES, immigration status

• physician and lab claims (FPs and specialists)

• model of care – FFS, blended FFS, blended capitation, salary, team

• hospitals, ER, homecare, long-term care, medications

• EMR data (sample) - diseases, health behaviours, BP, BMI, lab results

• population surveys of access, patient experience

• payments

• Derived measures through linkage • disease registries – cancer, diabetes, hypertension, CHF, COPD, mental health, etc.

• continuity of care, comprehensiveness

• performance – chronic disease management (eg diabetes), cancer screening

• costs by sector

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Aligned versus Linked Data

• Aligned data (system or practice level aggregation)

• obtained from different sources, different sectors

• about the same practice, with comparators

• ability to construct composite measures

• useful to practices for identifying priorities for improvement

• descriptive

• Linked data (patient level aggregation)

• same patient within and across different sectors

• unique identifier, track health care trajectories

• relate utilization and outcomes to patient characteristics (eg rurality, low income)

• useful for performance measurement, essential for research

• analytic

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System-Level Aligned Data: Patient Survey and ER Use


Glazier RH, Kopp A, Schultz SE, Kiran T, Henry DA. Healthc Q. 2012;15(3):17-21

ICES Pr imary Care and Populat ion Heal th Research Program Heal th Sys tem Trans format ion 21

Practice-Level Aligned

Data: Demographics and

Patent Survey


Linked Data: Income, Morbidity and Capitation Payments

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Sibley LM, Glazier RH. Health Policy. 2012;104(2):186-92.


Linked Data: Cancer Screening and Payments

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• No change in cervix or breast cancer screening

• Net increase of 1.7% per year in colorectal screening after incentives

• Combined annual costs more than $35 million

Kiran T. et al. Ann Fam Med. 2014 Jul;12(4):317-23


Linked Data: Performance of Models of Care

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Diabetes processes of care Colorectal cancer screening

Kiran T et al CMAJ 2015


Linked data: Population Survey and Model of Care

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Health Analytics Branch MOHLTC: Ontario Health Care Experience Survey 2012/13

Capitation Fee for service

ICES Pr imary Care and Populat ion Heal th Research Program Heal th Sys tem Trans format ion 26

Linked Data: Population Survey, ED Visits and Admissions

Glazier RH, Moineddin, R, Agha MM, Zagorski B, Hall R, Manuel DG, Sibley LM, Kopp A. The Impact of Not Having a Primary Care Physician Among People with Chronic Conditions. ICES Investigative Report. Toronto: Institute for Clinical

Evaluative Sciences; 2008. www.ices.on.ca


Practice Level Linked Data: EMR and Diabetes Care Measures


Standardized Feedback Reports


Extensively Linked Data

• Primary healthcare • utilization and performance in relation to health system transformation

• payment reform

• inter-professional teams

• impact of technology

• Other topics and sectors • cardiac care, cancer care

• management of chronic conditions – diabetes, hypertension, CHF, COPD, mental health

• drug safety and effectiveness

• Integration • avoidable hospitalizations

• readmissions

• 1% and 5% highest system users

• system costs

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Putting Primary Healthcare in the Picture

• Underpinning of high functioning health systems

• Measurement has historically lagged other sectors, especially hospitals

• Technology enabling rich data (EMRs)

• Align data at the system or practice level (descriptive)

• Link for research and performance measurement (analytic) • effectiveness, safety

• efficiency

• equity

• integration

• achieving healthy system goals

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Team-Based Research

Project: 177411

Alex Kopp, Sue Schultz, Brandon Zagorski, ICES

Tara Kiran, St. Michael’s Hospital, ICES

Brian Hutchison, Health Quality Ontario

Jennifer Rayner, Community Health Centres

many others

ICES Pr imary Care and Populat ion Heal th Research Program ICES Pr imary Care and Populat ion Heal th Research Program

Comments, Questions?
