Discharge Abstract Database DAD A collaboration between CIHI

Discharge Abstract Database (DAD) A collaboration between CIHI and DLI November 2012 1

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 • 27 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 2

Collaboration between CIHI and Statistics Canada’s DLI • CIHI recently developed a Data Access Strategy • Purpose: To improve timeliness and accessibility of data to users such as system planners, policy makers, and researchers – Streamlining CIHI’s existing data dissemination channels – Exploring new, trusted data dissemination channels • Resulted in a 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 31 st, 2014 3

Overview of the Discharge Abstract Database (DAD) 4

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. • Currently, more than 3 million records are submitted to DAD annually. • Data are received from all acute care facilities across Canada (except Quebec) • 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). 5

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 6

DAD data elements - Groups • Special Care Information • Blood Information • Reproductive Care Information • Not all of this information is included in the DLI sample files 7

DAD - DLI sample files 8

Regarding DAD-DLI files • DAD coverage for acute inpatient care is virtually complete for Canada, except Quebec (80% of all inpatient discharges in Canada) • 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 patient privacy and usefulness of data • 10% sample ensures privacy, but reduces richness of data files • Combining two years of data enhances richness • Two DAD-DLI files: one with more clinical detail, one with more geographic detail • Documentation accompany the data files 9

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 • Separate, non-overlapping 10% samples of persons were created for the ‘clinical’ and ‘geographic’ files • Then, all discharge records belonging to these patients over a two-year period were included in the DAD-DLI files 10

Longitudinal information • Dates are not provided in the files (privacy) • 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 selected individuals • All discharges in the 730 -day period starting with the reference day are included in the files 11

Contents of files • To protect patient privacy, there is less clinical detail in the geographic file, and vice versa • Also, some variables are made available in ‘collapsed’ form: – Age – Length of stay – Newborn weight – Gestation weeks at delivery 12

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, 1317, 18 -24, 25 -29, 30 -34, … 75 -79, 80+ years) • Admission/discharge variables 13

Clinical detail file • Clinical details: – Diagnoses(1 -25): code(ICD-10 -CA) and type – Interventions(1 -20): code(CCI), status, location, anaesthetic – 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) 14

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) 15

What is case mix? • “Mix of patient’s detailed characteristics” that are important in terms of both treatment and resource use • Classification of patients (‘grouping’) – Each class is homogeneous, with • Clinical coherence • Similar health care resource use – Manageable number of classes – Based on commonly available and relevant data elements 16

Uses of a case mix system • Provides a classification of patients that can be useful for health care facility/system: – Planning and budgeting – Performance evaluation – Utilization management – Quality improvement – Health services research – Funding 17

Case Mix Groups (CMG+) • CMG+ released in 2007 – For acute care inpatients • The classification is based primarily on diagnoses and interventions • 21 major clinical categories, 562 CMGs • Within a CMG, ‘factors’ let further patient specific characteristics affect predicted resource use • Resource use variables: Resource Intensity Weight (RIW) and Expected Length Of Stay (ELOS) 18

DAD-DLI file formats • ASCII with fixed width columns (. dat) • SPSS (. sav) • Total file size: 340 MB (. dat), 190 MB (. sav) 19

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 • Available in both English and French 20

For your information – Other ways of accessing data from CIHI 21

Option for accessing data from CIHI • CIHI website – Quick Stats and Analytic Reports – Free, pre-formatted, aggregate-level data • Customized data request – Aggregate-level – Record-level – CIHI has a Graduate Student Data Access Program 22

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 23

Customized requests Aggregate Person-level • Groups or summaries of data • De-identified data, limited to meeting the project’s needs • E. g. Counts, means, median • Data table • Each record refers to data from an individual, who may have more than one record in the database • Small cell sizes may be suppressed (counts<5) • Format (SAS, commadelimited) 24

Process of accessing data from CIHI • Step 1: Determining your own data requirement – Are the data required available on CIHI website – If not, contact CIHI for a customized data request • Step 2: Your first contact with CIHI – Online Data Inquiry Form • Step 3: Initial Assessment of data request by appropriate CIHI staff based on the requirements provided on the inquiry form • Step 4: Further documentation (e. g. , signed Request Form), Specifications approval, data extraction and verification, and data release Note: all data from CIHI are released to the users as per CIHI Privacy Policy (available on CIHI website) 25

Service standard for custom data requests Nature of the request Aggregate-level data Record-level data Standard request 10 working days 20 working days Complex request 20 working days 40 working days Very complex To be negotiated with the client 26

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 27

Any questions or comments? 28

Thank you! 29