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The Art of the Possible Using CPCSSN Data for Primary Care Research. Family Medicine Forum Nov 16, 2012 Karim Keshavjee - EMR Consultant & Research Data Architect Ken Martin - Information and Technology Manager. Outline. Introduction to CPCSSN CPCSSN Data Holdings

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the art of the possible using cpcssn data for primary care research

The Art of the Possible Using CPCSSN Data for Primary Care Research

Family Medicine Forum

Nov 16, 2012

Karim Keshavjee - EMR Consultant & Research Data Architect

Ken Martin - Information and Technology Manager

  • Introduction to CPCSSN
  • CPCSSN Data Holdings
  • A Tour of CPCSSN Data Tables
  • Current Research Projects at CPCSSN
  • The Art of the Possible
  • How to use CPCSSN data for your research
  • Goodies for Today
329 physicians in 8 provinces using 10 emrs


  • British Columbia
  • - BCPCReN(Wolf )
  • Alberta
  • - SaPCReN, Calgary (Med Access, Wolf)
  • - AFRPN, Edmonton (Med Access)
  • Manitoba
  • - MaPCReN, Winnipeg (Jonoke)
  • Ontario
  • - DELPHI, London (Healthscreen, Optimed, OSCAR
  • - NorTReN, Toronto (Nightingale, xwave, Practice
  • Solutions)
  • - CSPC, Kingston (P&P, OSCAR, xwave)
  • Quebec
  • - Q-Net, Montréal (Da Vinci, Purkinje)
  • Nova Scotia / New Brunswick
  • - MarNet, Halifax (Nightingale, Purkinje)
  • Newfoundland
  • - APBRN, St. John’s (Wolf , Nightingale)

329 physicians in 8 provinces using 10 EMRs


CPCSSN population

CPCSSN Population

  • Data Extracted on all patients in the practice, including children
  • Studying patients with the following chronic diseases
    • Chronic Obstructive Lung Disease
    • Depression
    • Diabetes
    • Hypertension
    • Osteoarthritis
  • Chronic Neurological Disease
    • Dementia
    • Epilepsy
    • Parkinson's Disease
data cleaning recoding
Data Cleaning/Recoding
  • We clean and recode the following fields
  • Billing, Encounter and Problem List Diagnoses (ICD9)
  • Medications (ATC)
  • Lab results (LOINC)
  • Referrals (SNOMED CT)
  • Physical signs (Wt, Ht, BP, unit conversion, calculate BMI)
  • Vaccines (ATC)
  • Risk factors (smoking, alcohol, diet --Text)

Patient Demographics

368,000 Records

} < 5%

}< 5%


6.8 Million Records

Dates of Encounter

Original diagnosis sent for billing

Text from Code Recoded by CPCSSN

Original Diagnosis Code sent for billing

Recoded by CPCSSN

research discussion
Research Discussion
  • Useful for case finding
  • Useful for understanding deficiencies of using billing information for clinical research
  • There is some inconsistency in use of billing codes across the country
  • CPCSSN recodes all billing diagnosis codes to a standard version

5.1 Million Records

Dates of Encounter

Data inconsistent across the Country

CPCSSN Cleaning Not Started

Active area of Cleaning

E.g., Office Visit, Phone, E-mail etc

research discussion1
Research Discussion
  • Can we segment patients by pattern of visits?
  • Does pattern of visits predict other things?
    • Control of disease
    • Frequency of prescriptions
    • Multiple comorbidities
  • Does visit type affect quality of care?
  • Reason for Encounter is poorly captured in most EMRs
problem list diagnoses

Original Text

Original Text

Problem List Diagnoses

1.8 Million Records

Original Diagnosis Written by User

E.g. DMT2

Recoded by CPCSSN

E.g., Diabetes Mellitus, Type 2

}Not well populated

Active = Problem List

Inactive = Past Medical History

problem list diagnoses1
Problem List Diagnoses

List of cleaned up diagnoses

Chronic airway obstruction, not elsewhere classified (496)

Bronchitis, not specified as acute or chronic (490)

Chronic bronchitis (491)

Emphysema (492)

Diabetes mellitus (250)

Depressive disorder, not elsewhere classified (311)

Suicide and self-inflicted poisoning by solid or liquid substances (E590)

Suicidal ideation (V62.84)

Adjustment reaction (309)

Post traumatic stress disorder (309.81)

Major depressive disorder, recurrent episode (296.3)

Bipolar I disorder, most recent episode (or current) (296.7)

Mental disorders complicating pregnancy, childbirth, or the puerperium (648.4)

Essential hypertension (401)

Osteoarthrosis and allied disorders (715)

Spondylosis and allied disorders (721)

Total knee replacement (81.54)

Total hip replacement (81.51)

Polycystic ovarian syndrome (256.4)

Abnormal glucose tolerance of mother complicating pregnancy childbirth or the puerperium (648.8)

Secondary diabetes mellitus (249)


Other abnormal glucose (790.29)

Migraine (346)

Heart failure (428)

Acute myocardial infarction (410)

Old myocardial infarction (412)

Other forms of chronic ischemic heart disease (414)

Cardiac dysrhythmias (427)

Essential and other specified forms of tremor (333.1)

Esophageal varices with bleeding (456.0)

Esophageal varices without bleeding (456.1)

Angina pectoris (413)

Other acute and subacute forms of ischemic heart disease (411)

Calculus of kidney and ureter (592)

Portal hypertension (572.3)

Asthma (493)

Dementias (290)

Alzheimer's disease (331.0)

Dementia with lewy bodies (331.82)

Parkinson's disease (332)

Epilepsy and recurrent seizures (345)

Epileptic convulsions, fits, or seizures nos (345.9)

research discussion2
Research Discussion
  • Sensitivity and specificity of problem list diagnoses not currently known, so cannot determine incidence and prevalence of disease from problem list alone
  • Need to develop case finding criteria for diseases (includes diagnosis, meds, labs, etc)
  • Need to identify sensitivity and specificity of having a diagnosis in the problem list
  • Currently in the process of validating 8 case finding criteria across the country
vital signs
Vital Signs

5 Million Records

Name of exam (e.g., sBP)

Cleaned up result

(e.g, lbs -> kg, inch -> cm)

Cleaned up unit of measure

(e.g., unit is kg, but result was lb)

research discussion3
Research Discussion
  • Currently have access to
    • sBP/dBP
    • Ht
    • Wt
    • BMI
    • Waist circum

155K Records

Name of allergen

Cleaned up name

Data will be coded as ATC

research discussion4
Research Discussion
  • Not yet cleaned, but will soon clean it
  • Focus of cleaning will be on medication allergies
    • All other allergies will be retained as original text
  • Useful when assessing why patients are not receiving medications for a particular disease
risk factors
Risk Factors

588K Records

Name of Risk Factor (e.g., smoking)

Cleaned up version of Risk Factors.

Working on cleaning up Current Exposures & Cumulative Exposures

research discussion5
Research Discussion
  • Risk factors are actively being cleaned
  • Getting the status of the risk factor (i.e., smoker/non-smoker) is difficult, but easier than
  • Current levels of exposure (e.g., # of cig/day)
  • Cumulative exposure (e.g., pack years)
  • Alcohol use is also being cleaned up
laboratory results
Laboratory Results

3 Million Records

Original Lab Result Name

(e.g., Hb A1c, HGbA1c, etc)

Recoded by CPCSSN 100% LOINC

(e.g., HBA1C)

research discussion6
Research Discussion
  • Currently only capturing the following
  • One site does not capture labs yet
encounter diagnoses
Encounter Diagnoses

6.3 Million Records

Original Diagnosis Recorded in Encounter

(e.g., axniety)

83% Recoded by CPCSSN

(Anxiety ICD-9 300)

63% Originally coded by Doctor

research discussion7
Research Discussion
  • Not all EMRs capture Encounter Diagnoses in a structured manner
  • This table is not ready for prime time across all sites, but may be useful for projects where data from just a few sites is acceptable

4.9 Million Records

56% Coded as DIN

What the doctor ordered

E.g., HCTZ 25 mg bid

91% Recoded by CPCSSN

E.g., Hydrochlorthiazide

72% Coded by doctor (DIN + other)


91% Coded by CPCSSN (ATC)

Strength 56%

Dose 70%

Unit of Measure 84%

Frequency 95%

Duration 52%

Dispensed 86%

research discussion8
Research Discussion
  • Medication name data is relatively clean
  • Medications coded as ATC
    • Allows easy grouping by class
  • Don’t have daily dose and months supply for many records –working on clean up

600 K Records

Original Text of Referral

80% Recoded by CPCSSN



1.3 Million Records

Original Text of Procedure

Not Currently Coded by CPCSSN


960 K Records

What the doctor typed

93% Recoded by CPCSSN(ATC)

46% Coded by Doctor (DIN)

disease cases
Disease Cases

Case Definitions are developed by CPCSSN and are in the process of

being validated through chart reviews

173,000 Records

How a Case is identified is recorded in this table

Allows full traceability for each case

research opportunities
Research Opportunities
  • Population Health and Epidemiological Studies
    • Incidence/Prevalence of disease
    • Impact of SES on health
    • Rates of treatment for diseases
    • Rates of disease control
    • Burden of illness and multi-morbidity
  • Clinical –database studies
    • Comparative effectiveness
    • Case-Control
    • Exposure-Outcome
    • Quality Improvement
    • Associations
    • Intervention-Outcome
    • Guideline effectiveness
research opportunities1
Research Opportunities
  • Clinical –prospective, interventional studies
    • Conduct pragmatic RCTs –data is already collected
    • Conduct in-clinic interventions
    • Not ready for these yet
  • Health Services
    • EMR adoption
    • Resource Utilization (consults, labs, procedures)
    • Policy Intervention (cross-province comparisons)
    • Patient behaviors –frequency of visits
    • Medical errors and patient safety
research opportunities2
Research Opportunities
  • Health informatics
    • Natural language processing
    • Machine learning
    • De-identification algorithms
    • Predictive Analytics
  • eHealth and mHealth
    • Develop and test apps using CPCSSN data
    • Patient education apps with their own data
    • Apps for healthcare providers to educate patients about their disease with nice visualizations
research using cpcssn data
Research Using CPCSSN Data

Letter of Intent

1 page, includes: Researchers, Organization, Research Title, Objective, Methodology,

Data Required



Letter of Intent


CPCSSN Research Committee




Letter of Acceptance

1. Protocol

2. Data Access Request Form

3. Data Sharing Agreement

1. Resubmit

2. Not Feasible

3. Outside Mandate



CPCSSN Research Committee




goodies for today
Goodies For Today
  • Copy of the presentation: The Art of the Possible:Using CPCSSN Data for Primary Care Research
  • Sample of CPCSSN data for 200 patients
    • Anonymized and scrambled to protect patient privacy
    • (MS Access file format)
  • CPCSSN database entity relationship diagram (ERD)
  • CPCSSN database data dictionary
  • CPCSSN central repository data holdings summary
  • CPCSSN Data Access Request Form Central Repository
  • Process for Requesting Access to CPCSSN Data
next steps
Next Steps
  • Sign a License Agreement today to get your copy of the CPCSSN Data Product
  • Evaluate the data CPCSSN has
  • Plan your next grant application around CPCSSN data
  • Add CPCSSN Data as a budget item into your next grant application
    • You can contact us to get a quote

Tyler Williamson, Senior Epidemiologist

Canadian Primary Care Sentinel Surveillance Network

Centre for Studies in Primary Care

Queen’s University

Kingston   ON  K7L 5E9

Tel: (613) 533-9300, Ext. 73838

Fax: (613) 533-9302



Thanks to all Funders, Stakeholders,

Partners, AND sentinel Physicians

Funding for this publication was provided by the Public Health Agency of Canada The views expressed herein do not necessarily represent the views of the Public Health Agency of Canada.

Cette publication a été réalisée grâce au financement de l'Agence de la santé publique du Canada. Les opinions exprimées ici ne reflètent pas nécessairement celles de l'Agence de la santé publique du Canada.