Discharge Abstract Database

(DAD)

Using the DAD-DLI sample files

December 2013

1

2

Agenda

> CIHI Overview and Collaboration with Statistics

Canada’s DLI

> DAD Overview

> DAD Sample Files and Documentation for DLI

> Examples and Key Uses of the DAD Sample Files

> Other Options to access CIHI data

> Questions? Comments?

Canadian Institute for Health Information (CIHI) -

Overview

• Mandate: To provide accurate and timely information required for

− Sound health policy

− Effective management of the health system

− Public awareness about factors affecting good health

• 28 databases of comparable health information

– Health care services: primary health care, hospital care, specialized services, community and pharmaceutical care

– Health spending: by geography and by category

– Health workforce: physicians, nurses, and other health care providers

3

Collaboration between CIHI and Statistics

Canada’s DLI

• CIHI’s Data Access Goal: To improve timeliness and accessibility of data to users, such as system planners, policy makers, and researchers

• Resulted in collaboration with Statistics Canada to make CIHI data more accessible to academic researchers using the DLI

• CIHI has provided Discharge Abstract Database (DAD) sample files to be part of the DLI collection, along with complete documentation, for a pilot project ending March 31st, 2014

4

Overview of the

Discharge Abstract Database

(DAD)

5

What is the DAD?

• The Discharge Abstract Database (DAD) captures administrative,

clinical, and demographic information on hospital discharges

(including deaths, sign-outs, and transfers). Some provinces and

territories also use the DAD to capture day surgery data.

• Currently, more than 3 million records are submitted to DAD

annually.

• Data are received from all acute care facilities across Canada

(except Quebec) - 80% of all inpatient discharges in Canada

• Select chronic care, rehabilitation, and psychiatric facilities also

submit data to DAD.

• Data from Quebec is submitted to CIHI directly by the ministère de

la Santé et des Services sociaux (MSSS). This data is appended to

the DAD to create the Hospital Morbidity Database (HMDB).

6

DAD data elements - Groups

• Data elements are organized into the following groups:

• Abstract Identification

• Length of Stay

• Patient Demographics

• Admission Data

• Discharge Data

• Patient Service Information

• Service Transfers

• Provider Information

• Diagnosis Information

• Intervention Information …continued on next slide

7

DAD data elements - Groups

• Special Care Information

• Blood Information

• Reproductive Care Information

• Not all of this information is included in the DLI sample files

8

DAD - DLI sample files

9

Regarding the DAD-DLI files

• DAD data files for DLI include acute inpatient cases from

all provinces/territories except Quebec and British

Columbia

• Files were designed to maintain a balance between

protecting patient privacy and maximizing usefulness of

data

• 10% patient samples were selected to ensure privacy,

while including two years of data enhances richness

• Two DAD-DLI files are provided: one with more clinical

detail, one with more geographic detail

• Documentation accompany the data files

10

Patient-oriented Approach

• Analysis potential is greater when the sequence of

care for an individual can be followed over time

• The DAD-DLI files allow this

• Two separate, non-overlapping 10% samples of

persons were randomly selected from the DAD

• Then, all discharge records belonging to these

patients over a two-year period were included to

create the DAD-DLI ‘clinical’ and ‘geographic’ files

11

Longitudinal information

• Dates are not provided in the files to ensure no residual disclosure of individual patient

• Temporality of events is provided by the number of days as of a reference date (day zero)

• This reference date is specific to each person in the data files

• The reference dates are between March 1, 2009 and March 31, 2009, and are randomly assigned to the individuals included in the data files

• All discharges in the 730-day period starting with the reference day are included in the files

12

Contents of the Data Files

• To protect patient privacy, there is less clinical detail in

the geographic file, and vice versa

• Also, some data elements are made available in high-

level groupings/categories:

– Age

– Length of stay

– Newborn weight

– Gestation weeks at delivery

13

Common data elements

• Person identifier (meaningless except to identify discharge records for the same person within the files)

• Facility province (territories are combined)

• Discharge day (relative to reference day)

• Admission day (relative to reference day), calculated using the collapsed total length of stay

• Gender

• Age group (newborn, less than 1 year, 1-7, 8-12, 13-17, 18-24, 25-29, 30-34, … 75-79, 80+ years)

• Admission/discharge variables

14

Clinical Detail File

• Clinical details:

– Diagnoses(1-25): code (ICD-10-CA) and type

– Interventions(1-20): code (CCI), status, location, anaesthetic technique

– Special care unit visits(1-6): type/number and hours

• Length of stay: seven categories (0, 1, 2, 3, 4-5, 6-9, 10+ days)

• Newborn weights: six categories (under 750, 750-999, 1000-1499, 1500-1999, 2000-2499, 2500+ grams)

• Gestation weeks at delivery: four categories (under 32, 32-33, 34-36, 37+ weeks)

15

Geographic Detail File

• Health Region

• Case Mix variables:

– Major Clinical Category (MCC)

– Case Mix Group (CMG)

– CMG age category

– Resource Intensity Weight (RIW)

– Expected Length Of Stay (ELOS)

– RIW Atypical code

– Resource Intensity Level

• Length of Stay: three categories (0, 1-2, 3+ days)

16

DAD-DLI file formats

• ASCII with fixed width columns (.dat)

• SPSS (.sav)

• Total file size: 340 MB (.dat), 190 MB (.sav)

17

DAD Documentation for DLI

• File specifications containing methodological notes

• Record layouts with field description and values

• Data quality documentation

• DAD Abstracting Manual

• International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Canada (ICD-10-CA)

• Canadian Classification of Health Interventions (CCI)

• CMG+ Directory 2011

• Documentation are available in both English and French

18

Key uses of the DAD-DLI sample files

• Researchers can become familiar with the structure and content of DAD data

• Researchers can explore inter-relationships among DAD data elements (e.g. diagnoses and interventions, Case Mix information)

• Researchers can perform preliminary analyses and data mining

19

Provides researchers with an opportunity to work

with the DAD data and clarify data requirements

before making a formal data request to CIHI

Using the DAD Clinical file – Example #1

• Objective:

– To examine cases of acute myocardial infarction (AMI) in patients age 18 and older

• Inclusion criteria:

– AMI present on admission ICD-10-CA: I21, I22 coded as diagnosis type 1 (Pre-Admit Comorbidity) or type M (Most Responsible Diagnosis)

– Age group at discharge: 18-24 years and above

• Exclusion criteria:

– Difference between relative discharge day is 28 days or less for AMI hospitalizations belonging to the same patient (new cases defined as more than 28 days apart)

20

Example #1 (continued)

• Possible analyses:

– Mode of admission into the hospital

– procedures performed on patients with diagnosis of AMI via the

intervention or CCI code fields

– Other co-morbidities/diagnoses captured for these patients

– Age/gender distribution of these patients

– Discharge “destination” for these patients (for example, going home,

transferred to rehab/other care types)

– Whether the patients spent time in the special care units during their

hospitalizations

– Cross-tab any of the above

• This example could be applied with the geographic file via CMGs that identify

heart attacks 21

Using the DAD Clinical file – Example #2

• Objective:

– To examine Special Care Unit (SCU) visits (regardless of

type) with an intervention of ventilation

• Inclusion criteria:

– Intervention or CCI code: 1GZ31

• Exclusion criteria:

– First SCU unit: 99 (No SCU) – refer to the DAD Abstracting

Manual for applicable guidelines to recording SCU 99

22

Example #2 (continued)

• Possible analyses:

– Top conditions/diagnoses associated with ventilation use in

the special care units

– Length of time (in hours) spent in SCUs, by condition/

diagnosis, and age group

– Discharge “destination” for these patients (for example,

going home, transferred to rehab/other care types)

23

Using the DAD Geographic File – Example #3

• Objective:

– To examine cases of typical patients discharged with a

unilateral hip or knee replacement (using CMG+ codes)

• Inclusion criteria:

– CMG+: 320 Unilateral Hip Replacement

321 Unilateral Knee Replacement

– Inpatient RIW atypical code: 00 – Typical

• Data fields such as Inpatient RIW and ELOS days are

considered indicators of resource consumption for the

patients of interest

24

Example #3 (continued)

• Possible analyses:

– Patient length of stay compared to expected length of stay

(ELOS)

– Variations in resource use (average resource intensity

weights (RIW)) by gender, age, and geographic regions

– Percentage of patients who were transferred to another

facility

25

For your information – other

ways to access CIHI data

26

Options for accessing CIHI data

• CIHI website

– Quick Stats and Analytic Reports (free, pre-formatted,

aggregate-level data)

– Interactive Data Tools, including the CIHI Health

Indicators, Patient Cost Estimator, Hospital Standardized

Mortality Ratio (HSMR) reports

• Customized data requests

– Aggregate-level data request

– Record-level data request

– Data request via the Graduate Student Data Access

Program (GSDAP)

27

Aggregate data requests

• Groups or summaries of

data (for example,

counts, means, median)

• Data tables

• Small cell sizes (counts <

5) may be suppressed

Customized data requests

Record-level data requests

• De-identified data, limited

to meeting the project’s

needs

• Each record refers to data

from an individual, who

may have more than one

record in the database

• Format (SAS)

28

Graduate Student Data Access Program

• CIHI provides data to qualifying graduate students at no cost through the GSDAP (please visit www.cihi.ca)

• Objectives:

– To build the capacity of graduate students to undertake health service research; and

– To increase awareness of CIHI and CIHI’s data holdings, and the importance of data quality and privacy, as graduate students pursue health services research careers

• Criteria:

– Data are to be used by the student to fulfill graduate requirements

– The research project was reviewed by a research ethics board

– The research project will support CIHI’s mandate

29

Process of accessing data from CIHI

• Step 1: Determine your research topic and data requirement

– Explore CIHI data using the DAD DLI sample files

– Visit CIHI website to review publicly available data

• Step 2: Contact CIHI via the online Data Inquiry Form for a custom

data request (CIHI Data Request page)

• Step 3: Data request is assessed by appropriate CIHI staff based on

the requirements provided on the inquiry form

• Step 4: Provide additional documentation required for the data

request (for example, signed Data Request Form). Additional steps

include specifications approval, data extraction and verification, and

data release

Note: all data from CIHI are released to users as per CIHI Privacy Policy

(available on CIHI website)

30

For more information

• Please visit CIHI’s website at www.cihi.ca

• If you would like more information about CIHI or DAD,

please contact us via DLI dlilist@statcan.gc.ca

31

Any questions or comments?

32

Thank you!

33