using de-identified electronic medical record data to deliver insights into diabetes

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Use of De-Identified Health Data

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Page 1: Using de-identified electronic medical record data to deliver insights into diabetes

Use of De-Identified Health Data

Page 2: Using de-identified electronic medical record data to deliver insights into diabetes

Introduction: Real World Evidence has emerged as critical to valuing medicine and understanding the burden of illness

RWE Integrated Hospital:GP:Pharmacy:

EMR

Real World Evidence (RWE)

Electronic medical record and lab data

Longitudinal patient data – Prescriptions and admin data

Admin data and prescription data – snap shot

Transactional data

Genomics mHealth

Personalized Medicine

2015

2015+

2014

2000’s

1980’s

1970’s

Increased access to clinically relevant outcomes metrics

Copyright IMS Health 2014 - All rights reserved. IMS Brogan does not hold any personally identifiable patient information. All patient-level data is de-identified as part of IMS Brogan's risk management program to ensure the protection of patient privacy.

Page 3: Using de-identified electronic medical record data to deliver insights into diabetes

Examples of databases in Canada used to undertake health and disease studies

CIHI: Provincial:

Canadian Management Information System Database (CMDB) British Columbia cancer Registry

National Health Expenditure Database (NHEX) British Columbia eHealth

Discharge Abstract Database (DAD) British Columbia Healthcare Utilization Database

National Rehabilitation Reporting System (NRS) Canadian Community Health Survey

National Prescription Drug Utilization Information System (NPDUIS)

Organization for Economic Co-operation and Development (OECD) Health Database (Canadian Segment) Chronic Disease Registry

National Ambulatory Care Reporting System (NACRS) Government of Alberta: Health and Wellness

Canadian Joint Replacement Registry (CJRR) Health Services Data and Early Development Instrument

National Trauma Registry (NTR) Manitoba Centre for Health Policy

Therapeutic Abortions Database (TADB) Manitoba Health Research Database

Ontario Mental Health Reporting System (OMHRS) National Diabetes Surveillance System

Hospital Morbidity Database (HMDB) New Brunswick Department of Health

National Health Expenditure Database (NHEX)

Canadian Organ Replacement Register (CORR) Newfoundland and Labrador Centre for Health Information

Continuing Care Reporting System (CCRS) Nova Scotia Data Catalogue 2004

Hospital Mental Health Database (HMHDB) Ontario Case Costing Initiative

Canadian Management Information System Database (CMDB) Ontario Health Planning Data Guide

Canadian Multiple Sclerosis Monitoring System (CMSMS) Pediatric Inpatient and Outpatient Rehab

Population Health Research Unit

IMS Health: RAMQ - Quebec Canada

IMS Brogan LRx Saskatchewan Health Databases

IMS Brogan E360 EMR database Saskatchewan Health Research Services

IMS Brogan Rx Dynamics & claims ICES

CPCSSN Copyright IMS Health 2014 - All rights reserved. IMS Brogan does not hold any personally identifiable patient information. All patient-level data is de-identified as part of IMS Brogan's risk management program to ensure the protection of patient privacy.

Page 4: Using de-identified electronic medical record data to deliver insights into diabetes

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What to look out for with databases

» Does the data contain the variables required for the study – based on the disease state?

» Drug utilization

» Lab results

» Diagnostics

» Diagnosis

» Vital signs

» Mortality

» Demographics

» Full treatment pathway

» Costs (Intervention and drug)

Copyright IMS Health 2014 - All rights reserved. IMS Brogan does not hold any personally identifiable patient information. All patient-level data is de-identified as part of IMS Brogan's risk management program to ensure the protection of patient privacy.

Page 5: Using de-identified electronic medical record data to deliver insights into diabetes

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Where does IMS data come from?

Up to 5.3 million patients

If required for specific studies

500,000+ patients

with full data permission

Copyright IMS Health 2014 - All rights reserved. IMS Brogan does not hold any personally identifiable patient information. All patient-level data is de-identified as part of IMS Brogan's risk management program to ensure the protection of patient privacy.

Page 6: Using de-identified electronic medical record data to deliver insights into diabetes

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Minimizing patient re-identification and security

EMR

Copyright IMS Health 2014 - All rights reserved. IMS Brogan does not hold any personally identifiable patient information. All patient-level data is de-identified as part of IMS Brogan's risk management program to ensure the protection of patient privacy.

Page 7: Using de-identified electronic medical record data to deliver insights into diabetes

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Minimizing patient re-identification and security

EMR

Copyright IMS Health 2014 - All rights reserved. IMS Brogan does not hold any personally identifiable patient information. All patient-level data is de-identified as part of IMS Brogan's risk management program to ensure the protection of patient privacy.

Page 8: Using de-identified electronic medical record data to deliver insights into diabetes

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Minimizing patient re-identification and security

Physician Red Zone PHI

EMR

Static

De-identify & Risk Mitigate

Copyright IMS Health 2014 - All rights reserved. IMS Brogan does not hold any personally identifiable patient information. All patient-level data is de-identified as part of IMS Brogan's risk management program to ensure the protection of patient privacy.

Page 9: Using de-identified electronic medical record data to deliver insights into diabetes

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Minimizing patient re-identification and security

Physician Red Zone PHI

EMR

Static

De-identify & Risk Mitigate

Copyright IMS Health 2014 - All rights reserved. IMS Brogan does not hold any personally identifiable patient information. All patient-level data is de-identified as part of IMS Brogan's risk management program to ensure the protection of patient privacy.

Page 10: Using de-identified electronic medical record data to deliver insights into diabetes

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Minimizing patient re-identification and security

IMS Evidence 360 IMS Data Warehouse

IMS Green Zone – No PHI Physician Red Zone PHI

EMR

Static

De-identify & Risk Mitigate

Copyright IMS Health 2014 - All rights reserved. IMS Brogan does not hold any personally identifiable patient information. All patient-level data is de-identified as part of IMS Brogan's risk management program to ensure the protection of patient privacy.

Page 11: Using de-identified electronic medical record data to deliver insights into diabetes

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Minimizing patient re-identification and security

IMS Evidence 360 IMS Data Warehouse

IMS Green Zone – No PHI Physician Red Zone PHI

EMR

Static

De-identify & Risk Mitigate

Copyright IMS Health 2014 - All rights reserved. IMS Brogan does not hold any personally identifiable patient information. All patient-level data is de-identified as part of IMS Brogan's risk management program to ensure the protection of patient privacy.

Page 12: Using de-identified electronic medical record data to deliver insights into diabetes

IMS E360 observes BMI, BP, other CV risk factors, and interventions, providing additional insight into the full value of medicines

Copyright IMS Health 2014 - All rights reserved. IMS Brogan does not hold any personally identifiable patient information. All patient-level data is de-identified as part of IMS Brogan's risk management program to ensure the protection of patient privacy.

Page 13: Using de-identified electronic medical record data to deliver insights into diabetes

The IMS E360 EMR data has validated well with PHAC and longitudinal patient data*

Copyright IMS Health 2014 - All rights reserved. IMS Brogan does not hold any personally identifiable patient information. All patient-level data is de-identified as part of IMS Brogan's risk management program to ensure the protection of patient privacy.

Page 14: Using de-identified electronic medical record data to deliver insights into diabetes

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IMS E360 enables fast insights to data not readily available previously in Canada

Understanding HbA1c levels of patients taking diabetes medications

Copyright IMS Health 2014 - All rights reserved. IMS Brogan does not hold any personally identifiable patient information. All patient-level data is de-identified as part of IMS Brogan's risk management program to ensure the protection of patient privacy.

Page 15: Using de-identified electronic medical record data to deliver insights into diabetes

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In this study, 906 patients who have received a DPP4 prescription exhibit the following characteristics

Sex Age Smoking Status

Copyright IMS Health 2014 - All rights reserved. IMS Brogan does not hold any personally identifiable patient information. All patient-level data is de-identified as part of IMS Brogan's risk management program to ensure the protection of patient privacy.

Page 16: Using de-identified electronic medical record data to deliver insights into diabetes

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Patients taking DPP4s also typically receive the following medications

Copyright IMS Health 2014 - All rights reserved. IMS Brogan does not hold any personally identifiable patient information. All patient-level data is de-identified as part of IMS Brogan's risk management program to ensure the protection of patient privacy.

Page 17: Using de-identified electronic medical record data to deliver insights into diabetes

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Test results for DPP4 patients show a significant proportion are hypertensive

* Mayo clinic categorization

n=857

Copyright IMS Health 2014 - All rights reserved. IMS Brogan does not hold any personally identifiable patient information. All patient-level data is de-identified as part of IMS Brogan's risk management program to ensure the protection of patient privacy.

Page 18: Using de-identified electronic medical record data to deliver insights into diabetes

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Test results for DPP4 patients show a significant proportion are obese

n=581

Copyright IMS Health 2014 - All rights reserved. IMS Brogan does not hold any personally identifiable patient information. All patient-level data is de-identified as part of IMS Brogan's risk management program to ensure the protection of patient privacy.

Page 19: Using de-identified electronic medical record data to deliver insights into diabetes

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Summary

» Research of this type has been undertaken in Europe since the 1990s

» Databases such as CPRD, THIN and IMS Disease Analyzer in Europe have long delivered similar insights from de-identified patient data

» IMS Evidence 360 is the first tool built on a highly structured EMR system which delivers instant insights into patients health and treatment in Canada

» Studies are well controlled, ethics approved and designed by IMS epidemiologists and statisticians

Page 20: Using de-identified electronic medical record data to deliver insights into diabetes

“The Doctor doesn’t believe in computers, he likes to lose patient records the old fashioned way”

I think we have moved on quite a long way since I started working in the Health System

Copyright IMS Health 2014 - All rights reserved. IMS Brogan does not hold any personally identifiable patient information. All patient-level data is de-identified as part of IMS Brogan's risk management program to ensure the protection of patient privacy.

Page 21: Using de-identified electronic medical record data to deliver insights into diabetes

Thank you, questions?

Copyright IMS Health 2014 - All rights reserved. IMS Brogan does not hold any personally identifiable patient information. All patient-level data is de-identified as part of IMS Brogan's risk management program to ensure the protection of patient privacy.