Population and administrative datasets for research ... · Population and administrative datasets for research & evaluation ... •BC Surgical Patient Registry ... Case Study 1: Surveillance

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Population and administrative datasets for research &

evaluation

Carmen Ng, Epidemiologist

Decision Support Services

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Objectives1. Have some knowledge of the types of

population and administrative data available in and outside of Fraser Health

2. Have a basic understanding of the use of population and administrative data in planning, evaluation, and research

3. Examples and case studies of using population and administrative data

4. Have knowledge of the policy and procedures for research related data requests in Fraser Health.

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Outline1. Overview of administrative databases and

other health-related data2. Sources and types of data

ExternalInternalAvailabilityLinking and using multiple datasets

3. Case studies in Fraser Health4. Accessing health data and role of Decision

Support Services5. Question and answer period

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Overview of administrative databasesand other health-related data

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Background

What are administrative databases?Information routinely collected from compensation agencies, medical services plans, and hospitals for the purposes of billing and accounting

Commonly used in research settings to:1.Understand health and utilization trends2.Monitor patient outcomes3.Determine the efficacy of various treatments and

medical interventions

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Characteristics of administrative data

Population-based- Majority of British Columbians are covered by

Medical Services PlanUnique identifiers- Personal identifiers (e.g. PHN, name, date of birth)

to link records/filesLongitudinal/follow-up- Track groups of individuals over time

Secondary data- Primary use is for billing and accounting purposes

Reliability and validity

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Benefits of using administrative data

Readiness for useWide geographic coverageCost/time efficient Records contacts with health care systemLarge number of records allow study of rare eventsLong term follow-up

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Limitations of using administrative dataPrimary purpose is not to study health- Lack of clinically relevant data- Lack of concurrent controls

Issues surrounding validity or accuracy- Quality is highest for items directly associated with

paymentIssues surrounding privacy/securityMay exclude certain types of information- (e.g. services not covered under provincial health

plan)Collected by multiple agencies/groups

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Other health-related and population data

Health registries (e.g., Cancer registry)Chronic diseases

Surveillance systems (e.g., HIV, iPHIS)Infectious diseases

Surveys (e.g., census, Canadian Community Health Survey)

Longitudinal (cohorts) or cross-sectional

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Sources and types of data

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Data sources

•Census•Canadian Community Health Survey (CCHS) –annual•Adolescent Health Survey•BC Atlas of Child Development•National Longitudinal Survey of Children and Youth –old •National Population Health Survey (NPHS) –old

•iPHIS, STI cubes (infectious diseases, immunizations)•Enhanced surveillance systems for specific infections such as HIV, TB, etc.•Adverse events following immunization

•DAD•Health Incidents Reporting System•BC Perinatal Database•WorkSafe BC•BC Cancer Registry•BC Vital Statistics (births and deaths)•BC Trauma Registry•Health Status Registry (HSR)•BC Surgical Patient Registry•BC Screening Mammography Program•BC Cervical Cancer Screening Program•Mental Health (InterRAI)•BC Nurseline•Primary Health Care Registry (based on MSP)

•MSP•Pharmacare•Home and Continuing Care DW•Mental Health DW•BC Provider Registry•BC Bedline•BC Ambulance Services•Etc.

External

•Hospital-acquired infection surveillance•Panorama (Public Health)

•Discharge Abstract Database (DAD) and Cactus CAbstracting•BC Perinatal Database•Patient Safety & Learning System (PSLS)•WHITE (OH&S)•Mental Health (InterRAI)•Panorama (Public Health)•Medworxx

•Meditech•Continuing Care Management Information System (CCIMS)•Mental Health (CPIM)

Internal

SurveySurveillance SystemRegistry/Health DatabaseAdministrative

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Fraser HealthIn

tern

al D

ata

Exte

rnal

Dat

a

OccHealth

(WHITE)

DischargeAbstract

(CAbstract)

Infectiousdisease,

immunization

Healthcareassociatedinfections

CIHI(DAD)

WorkSafeBC

PICnet iPHIS

PerinatalData

BCPerinatalDatabase

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Data sources

•Census•Canadian Community Health Survey (CCHS) –annual•Adolescent Health Survey•BC Atlas of Child Development•National Longitudinal Survey of Children and Youth –old •National Population Health Survey (NPHS) –old

•iPHIS, STI cubes (infectious diseases, immunizations)•Enhanced surveillance systems for specific infections such as HIV, TB, etc.•Adverse events following immunization

•DAD•Health Incidents Reporting System•BC Perinatal Database•WorkSafe BC•BC Cancer Registry•BC Vital Statistics (births and deaths)•BC Trauma Registry•Health Status Registry (HSR)•BC Surgical Patient Registry•BC Screening Mammography Program•BC Cervical Cancer Screening Program•BC Nurseline•Mental Health (InterRAI)•Primary Health Care Registry (based on MSP)

•MSP•Pharmacare•Home and Continuing Care DW•Mental Health DW•BC Provider Registry•BC Bedline•BC Ambulance Services•Etc.

External

•Hospital-acquired infection surveillance•Panorama (Public Health)

•Discharge Abstract Database (DAD) and Cactus CAbstracting•BC Perinatal Database•Patient Safety & Learning System (PSLS)•WHITE (OH&S)•Mental Health (InterRAI)•Panorama (Public Health)•Medworxx

•Meditech•Continuing Care Management Information System (CCIMS)•Mental Health (CPIM)

Internal

SurveySurveillance SystemRegistry/Health DatabaseAdministrative

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Fraser Health Datasets

Discharge Abstracts (CAbstract and DAD)MeditechInfection SurveillanceHome and continuing careMental healthPerinatal databasePatient Safety & Learning SystemOcc Health

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Discharge Abstract Database (DAD)- Contains hospital separations data- Data entered by coding teams in Health Information

Services- Each discharge and day surgery is entered- Data content is set nationally by Canadian Institute

of Health Information (CIHI)- Data is regularly submitted to CIHI

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Purpose of DAD- Collecting, processing and analysing summaries of

hospital discharges and day surgeries- Supporting management decision making at

hospital, authority and provincial level- Facilitates comparative reporting- Provides case grouping methods, length of stay and

resource utilization analysis

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Meditech- Various Modules, including emergency, admissions,

abstracting, etc.- DSS does not have access to other modules such

as financial, material management, human resources

- Data can be reported and extracted using canned or custom reports

- Data can be downloaded for analysis

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Data Extracts from Meditech- Ambulatory data- Emergency Department Data- Admissions- Etc.

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Infection Surveillance- Antibiotic-resistant organisms (methicillin-resistant

Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE))

- Clostridium difficile-associated disease (CDAD)- Surgical site infections

• Caesarean sections at 8 FH sites • Cardiovascular surgery at RCH only• Class 1 and class 2 surgeries at CGH

- Vascular access-associated blood stream infections for chronic hemodialysis patients

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Fraser Health DatasetsHome and Continuing Care- Continuing Care

Information Management System (CCIMS)

- maintain a registry of clients and agencies providing services

- to maintain a waiting list for placement in continuing care residential services

- support planning, monitoring, funding and management

- to calculate and generate payments for provider claims

Home and Continuing Care- Province-wide interRAI

initiative- home care, assisted living,

residential care - Assessment tool for

residential care- standardized instrument

for evaluating the needs, strengths, and preferences of those in chronic care and nursing home institutional settings

- Internal- Goldcare database

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Fraser Health DatasetsMental Health- Community Patient Information Management

System (CPIM)- Captures client demographics, clinical diagnosis and

services provided at community mental health centres

- Tracks service events and clinician caseloads- Generate standard reports that can be used for

program planning and resource allocation purposes- To be replaced by PARIS in 2011

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Fraser Health DatasetsBC Perinatal Database Registry (BCPDR)- Data on perinatal outcomes, care processes and

resources- Demographic, clinical, and some risk factor data for

mothers, readmitted mothers, newborns, stillbirths, and readmitted neonates

- Province-wide- Standard reports and reporting tools

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Fraser Health DatasetsPatient Safety & Learning System (PSLS)- Live at 9 sites- Includes medication variance, falls,

incorrect/incomplete clinical processes- Data elements include dates, location, nature,

severity, etc.Occupational Health (Workplace Health Indicator Tracking and Evaluation)- The WHITE database is a web-based health and

safety system that facilitates incident tracking and case management

- Data elements include dates, times, nature, contributing factors, etc.

Types of data in various sources

Health States Health System andHealth Interventions

Health Outcomes

(e.g., infections,diseases)

(e.g., treatments, costs, utilization,

wait times, evaluation)

(e.g., death,hospitalization)

BC Vital StatisticsHealth Status Registry

WHITEINTE

RN

AL

Canadian Community Health Survey

EX

TER

NA

L

Census

PharmacareBC Cancer Registry

Screening Mammography Program

MSP

iPHIS

Determinants/Risk Factors

(e.g., socioeconomic status, ethnicity, age,

sex)Discharge Abstract Database (DAD)

MeditechPerinatal DatabaseIncidents Reporting

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Using data from multiple datasets: Linking data

Allows you to study the trajectory of disease, care and compensationLinkage across files- Individual-level data

- Using personal identifier such as PHN, chart number

- Aggregated data- Using geography such as postal codes, dissemination

areas (DA)- Using population demographics such as age and sex

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British Columbia Linked Health Database (BCLHD)/Population Data BC

Resource for population health researchIn addition to health service use, information from Vital Statistics, WorkSafeBC, and the BC Cancer AgencyLinks files to study health utilization and compensation trends over time for a given individual in BCProvide datasets stripped of personally identifiable information Requires a data access request and has a cost

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Examples using population, health and administrative datasets

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Case Study 1: Surveillance Systems for H1N1 and Olympics

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Overview of Surveillance Systems

H1N1 system based on collected data as well as syndromic surveillanceOlympics system based solely on syndromic surveillance

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Syndromic Surveillance

Public health surveillance based on syndromes rather than actual diagnoses

Original form uses real-time dataEnhanced detection of emerging illness and infection, bioterrorismCommonly used in USField accelerated in US in 2001 after Anthrax incident

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Taken from Henning, K.J. What is syndromic surveillance? MMWR Vol. 53 Suppl p. 7-11.

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Uses of Surveillance Data

Outbreak detection (infectious diseases, emerging diseases, bioterrorism)Epidemiological information on affected population (age, sex, residence location)

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Limitations

Proxy data, validity and reliabilityEvidence of effectiveness sparseMany different software availableMany different statistical methods in aberration detection

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Data Sources for H1N1 Surveillance System

ED volumeED chief complaintAdmissions volumeAdmissions reason for visitICU admissionLaboratory testing for respiratory pathogens

Lab-confirmed H1N1 hospitalized casesResidential facility outbreaksSchool absenteeism

H1N1 Hospitalizations

RCF RI Outbreaks

H1N1 Weekly Surveillance Report

ILI ED Visits

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otal

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Daily Admissions from ER

ILI Admissions

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CTAS 1 and 2CTAS 3 to 5 or no CTAS% visits# visits in previous year

Daily ER Visits with Fever or Cough

MEDITECH

Respiratory Isolates

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Upper respiratory tractSputumLower respiratory tractBlood/tissue & other invasive

*Selected respiratory pathogens are H. influenza, S.areus, S. pneumoniae, iGAS, K. pneumoniae, M. catarrhalis, N. meningitidis, P. aeruginosa.

Respiratory Pathogens by Specimen Source, Daily ReportsFigure 1

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Num

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es

Other hospitalized cases = 286ICU cases = 54Deaths = 17

Daily Hospitalized Cases of Pandemic H1N1Figure 1

0

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Num

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Negative (Serious) = 6Influenza B = 0Influenza A = 0H1N1 = 6

Declared Respiratory Outbreaks by Organism Isolated Residential Care Facilities

Figure 1

Infection Control

Residential Care

Facilities

Data Sources for H1N1 Weekly Report

School Absenteeism

Public Health

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Elem/Mid/Sec = 2Secondary = 10Middle = 8Elementary = 49

Figure 1 FH Schools Reporting 10% or Higher Absenteeism due to ILI by School Level

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esOther hospitalized cases = 286ICU cases = 54Deaths = 17

Daily Hospitalized Cases of Pandemic H1N1Figure 1

0

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% T

otal

ILI % Total Admissions

ALL Daily Admissions with ILIFigure 1

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-Apr

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930

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920

-Jun

-09

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un-0

94-

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911

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ul-0

925

-Jul

-09

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8-Au

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ug-0

922

-Aug

-09

29-A

ug-0

95-

Sep-

0912

-Sep

-09

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ep-0

926

-Sep

-09

3-O

ct-0

910

-Oct

-09

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ct-0

924

-Oct

-09

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ct-0

97-

Nov

-09

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ov-0

921

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Day

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f Vis

its

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% o

f Tot

al E

R V

isits

CTAS 1 or 2

CTAS 3 to 5 or No CTAS

% of total ED visits

Daily ED Visits with Fever, Cough, or ILI, by CTASFigure 3

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11/0

3/09

11/0

5/09

11/0

7/09

11/0

9/09

11/1

1/09

11/1

3/09

11/1

5/09

11/1

7/09

11/1

9/09

11/2

1/09

11/2

3/09

11/2

5/09

11/2

7/09

11/2

9/09

12/0

1/09

12/0

3/09

12/0

5/09

12/0

7/09

12/0

9/09

12/1

1/09

12/1

3/09

Num

ber o

f sch

ools

Elem/Mid/Sec = 2Secondary = 10Middle = 8

Elementary = 49

FH Schools Reporting 10% or Higher Absenteeism due to ILI, by School Level

Figure 1

38

Olympic Surveillance

In collaboration with BCCDC and other HAsSyndromic surveillance of ED volume and chief complaintsSyndromes include:

ILIGIRash

39

ED Visits with Symptoms of ILIAll Fraser Health Acute Care Sites

0

50

100

150

200

250

1-Se

p-09

8-Se

p-09

15-S

ep-0

9

22-S

ep-0

9

29-S

ep-0

9

6-Oc

t-09

13-O

ct-09

20-O

ct-09

27-O

ct-09

3-No

v-09

10-N

ov-0

9

17-N

ov-0

9

24-N

ov-0

9

1-De

c-09

8-De

c-09

15-D

ec-0

9

22-D

ec-0

9

29-D

ec-0

9

5-Ja

n-10

12-Ja

n-10

19-Ja

n-10

26-Ja

n-10

Num

ber o

f vis

its

Non-EDIS sitesEDIS sitesEDIS Historical (2008-2009)

ED Visits with GI SymptomsAll Fraser Health Acute Care Sites

0

50

100

150

200

250

1-Ju

n-09

8-Ju

n-09

15-Ju

n-09

22-Ju

n-09

29-Ju

n-09

6-Ju

l-09

13-Ju

l-09

20-Ju

l-09

27-Ju

l-09

3-Au

g-09

10-A

ug-0

917

-Aug

-09

24-A

ug-0

931

-Aug

-09

7-Se

p-09

14-S

ep-0

921

-Sep

-09

28-S

ep-0

95-

Oct-0

912

-Oct-

0919

-Oct-

0926

-Oct-

092-

Nov-0

99-

Nov-0

916

-Nov

-09

23-N

ov-0

930

-Nov

-09

7-De

c-09

14-D

ec-0

921

-Dec

-09

28-D

ec-0

94-

Jan-

1011

-Jan-

1018

-Jan-

1025

-Jan-

10

Num

ber o

f vis

its


ED Visits with RashAll Fraser Health Acute Care Sites

0

10

20

30

40

50

1-Ju

n-09

15-Ju

n-09

29-Ju

n-09

13-Ju

l-09

27-Ju

l-09

10-A

ug-0

9

24-A

ug-0

9

7-Se

p-09

21-S

ep-0

9

5-Oc

t-09

19-O

ct-09

2-No

v-09

16-N

ov-0

9

30-N

ov-0

9

14-D

ec-0

9

28-D

ec-0

9

11-Ja

n-10

25-Ja

n-10

Num

ber o

f vis

its


40

Case study 2: Ecologic analyses by geography

41

Linking Data by Geography:Ecologic Analysis

Not all data sources have patient identifiers for linking (e.g., Census, CCHS) but these are rich sources of data on risk factors and health determinants such as income and health behavioursAlmost all data sources can be linked by some level of geographyInvolves analyzing aggregate data for groups of individuals to make inferences about relationships at the individual levelThis type of analysis often preliminary in nature

42

43

Taken from: Canadian Institute for Health Information. Reducing gaps in health: A focus on socio-economic status in urban Canada. (Ottawa, ON: CIHI, 2008).

44

45

46

47

Is income status related to diabetes hospitalization rates?

Analysis at the Dissemination Area levelOutcome = # people hospitalized with diabetes codeVariable of interest = median incomeControl variables = pop. size, urban/rural, age, ethnic breakdown, education level

48

Is income status related to diabetes hospitalization rates?

2.12 to 3.162.64Lowest

0.73 to 1.761.25Low-medium

0.81 to 1.811.31Medium

-0.06 to 0.960.45Medium-high

ReferenceHighest

95% CIRegression Estimate

Income level (Quintiles)

49

Is income status related to the number of diabetes hospitalizations?

Analysis at the individual levelOutcome = binary; >2 visits vs. 1 visitVariable of interest = median income of their DAControl variables = age, sex, education level of DA, ethnic breakdown of DA, pop. Size of DA, urban/rural

50

0.89 to 1.211.04Lowest

0.83 to 1.140.97Low-medium

0.98 to 1.341.14Medium

0.91 to 1.251.07Medium-high

1Highest

95% CIOdds ratioIncome level (Quintiles)

Is income status related to the number of diabetes hospitalizations?

51

Three Possible Case Scenarios

I. Question: How many times do patients visit the hospital after their hip/knee surgeries? And why?

Linking acute inpatient data with emergency and ambulatory care data

Elective Arthroplasty (Hip or Knee) Pts > Checking Ambulatory Care Visits

52


II. Question: Overall, do patients who get transferred between hospitals have longer lengths of stay compared to patients who don’t get transferred? If so, why?

Linking acute inpatient data with acute inpatient data

Inpatient data ‘Transfer To’ > Inpatient data ‘Transfer From’

53


III. Question: Who are Transitional Service patients?

Linking acute inpatient data with residential care data

Transitional Services: Subacute Care (Inpatient) + Complex Rehab Care (Inpatient) + Convalescent Care (Not Inpatient, CCIMS)

54

Accessing Health Data

55

What data do I needand how do I get it?

Formulate research questionExplore possible data sources and limitationsRefine research questionEBM framework (PICO):

P – PopulationI – InterventionC – ComparisonO - Outcomes

56

Health Reports Available

CIHI indicator reports - provide comparative information on

• the overall health of the population served • the major non-medical determinants of health in

the region • the health services received by the region's

residents • characteristics of the community or the health

system that provide useful contextual information- More information at secure.cihi.ca

57

Health Reports Available

Quantum Analyzer (Quantum Analytics Ltd.)

tool for displaying and analyzing summarized custom informationpopulation data , population health measures, health service volumes, financial data, labour hours information, workload statistics, efficiency measures, performance indicators, unit cost ratios

58

The role of Decision SupportProvide health information for the evaluation and planning of health services in FHSummarize and report data related to population demographics, health status and utilization of health servicesEndeavor to support research and evaluation related data needs

59

Ways to access dataDSS WebsitePopulation data that are common knowledge and contain no personal information, e.g. seniors population, population by age and sex, population distribution/projections etc. Non-research data request - online processFor example, specific data for program planning and evaluation Data Request FormResearch related data requestGoverned by “Policy for the Provision of Research Related Services”

60

Research Related ServicesPolicy for the Provision of Research-Related Services, Decision Support

DSS determines its ability to provide research related services at a cost recovery basis Data requests must be presented with evidence of “Authorization to Conduct Research”Ensure compliance with policy and legislations regarding privacy, confidentiality and security

61

Procedures………..Applications to FH Research Ethics Board

Contact DSS Manager/Designate to have DAR Form signed (DAR) form

Manager/Designate ensures that a Data Access Agreement (DAA) is completed

Data Access Agreement

Researcher will provide Manager/Designate with a signed

copy of “Authorization to Begin Research” before data can be

released

62

Questions/Comments?

Documents

Population and administrative datasets for research ... · Population and administrative datasets for research & evaluation ... •BC Surgical Patient Registry ... Case Study 1: Surveillance