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1 Population and administrative datasets for research & evaluation Rahul Chhokar – Health Promotion & Prevention Amin Jivanni – Decision Support Services.

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Presentation on theme: "1 Population and administrative datasets for research & evaluation Rahul Chhokar – Health Promotion & Prevention Amin Jivanni – Decision Support Services."— Presentation transcript:

1 1 Population and administrative datasets for research & evaluation Rahul Chhokar – Health Promotion & Prevention Amin Jivanni – Decision Support Services Waqar Mughal – Workplace Health Catherine Barnardo – Decision Support Services

2 2 Objectives 1.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.Have knowledge of the policy and procedures for research related data requests in Fraser Health

3 3 Outline  Overview of administrative databases  Sources of data  External  Internal  Examples using administrative/population data for research and evaluation  Case Study  Role of Decision Support Services  Policy and procedures related to data requests in Fraser Health

4 4 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 population health trends 2.Monitor patient outcomes 3.Determine the efficacy of various treatments and medical interventions

5 5 Characteristics of administrative data  Population-based -Majority of British Columbians are covered by Medical Services Plan  Unique identifiers -Personal identifiers (e.g. PHN, name, date of birth) to link records/files  Longitudinal/follow-up -Track groups of individuals over time  Secondary data -Primary use is for billing and accounting purposes  Reliability and validity

6 6 Benefits of using administrative data  Readiness for use  Wide geographic coverage -Currently over 4 million are enrolled in MSP  Cost/time efficient  Records contacts with health care system  Large number of records allow study of rare events  Long term follow-up -Loss to follow-up less of a problem than traditional methods -Biases such as recall and response bias less likely

7 7 Limitations of using administrative data  Primary purpose is not to study health/disease outcomes -Lack of clinically relevant data  Issues surrounding validity or accuracy -Quality is highest for items directly associated with payment  Issues surrounding privacy/security  May exclude certain types of information -(e.g. services not covered under provincial health plan)

8 8 Linking across datasets  Allows you to study the trajectory of care and compensation  Linkage across files -Using personal identifiers Name, Date of Birth, Personal Health Number, etc. -Linkages to an established cohort (e.g. occupational cohort) -Linkage to geographic and census variables

9 9 British Columbia Linked Health Database (BCLHD)  Constructed in 1996 by the Centre for Health Services and Policy Research  Resource for population health research  In addition to health service use, information from Vital Statistics, WorkSafeBC, and the BC Cancer Agency  Links files to study health utilization and compensation trends over time for a given individual in BC  Provide datasets stripped of personally identifiable information  Requires a data access request 

10 10 Data for population health research - BCLHD  Hospital separations -1985/86 onward -Hospital code, level of care, ICD-9 code, procedures, separation date, responsibility of payment  Medical Services Plan -1985/86 onward -Date of service, practitioner number, speciality code, ICD-9 code, claim type  Pharmacare onward -Plan type, drug number, date of prescription, days supply dispensed

11 11 Data for population health research - BCLHD  Workers’ Compensation onwards - Injury date, short-term disability date, body part injured, nature of injury  BC Cancer Agency 1986 onwards Diagnosis date, site location, histology, method of confirmation

12 12 Databases for population health research  BC Vital Statistics -Registry of all births and deaths in BC -VISTA - an environment through which medical, social, and demographic information from vital event data can be derived -http://www.vs.gov.bc.ca/http://www.vs.gov.bc.ca/  BC Statistics  population estimates and population projections -By health regions, regional districts and developmental regions, school districts and college regions -By age and gender -http://www.bcstats.gov.bc.ca /http://www.bcstats.gov.bc.ca /

13 13 Databases for population health research  Statistics Canada census -Demographic information – age, race, income, marital status, education, immigration -Aggregate data - tabulations -http://www.statcan.ca/http://www.statcan.ca/  BC Perinatal database -2000/2001 onwards -Standardized information on antenatal, intrapartum, immediate post-partum, and newborn data on all births in BC -To evaluate perinatal outcomes, care processes and resources -http://www.rcp.gov.bc.ca/http://www.rcp.gov.bc.ca/

14 14 Survey data for population health research  National Longitudinal Survey of Children and Youth -Last release - December Started in 1994 and conducted every two years -Long-term study of Canadian children that follows development and well-being from birth to early childhood -Approximately 26,000 children and youth  National Population Health Survey -Last release - November Started in 1994/1995 and conducted every two years for 18 years -NPHS longitudinal sample includes over 17,000 persons from all ages in 1994/1995 -Provide health and disease information on a panel of people that are followed over time

15 15 Survey data for population health research  Canadian Community Health Survey -Last release - June Cross-sectional estimates of health determinants, health status, and health system utilization -Primary use is for health surveillance – prevalence of disease -Allows for analyses at the regional level  Adolescent Health Survey -McCreary Centre Society -Provincial survey to examine youth physical, mental, and emotional health -Administered in 1992, 1998, 2003, and ,000 students participated in http://www.mcs.bc.ca/http://www.mcs.bc.ca/

16 16 Other external sources for population health research  Human Early Learning Partnership (UBC) -BC Atlas of Child Development -http://www.earlylearning.ubc.ca/http://www.earlylearning.ubc.ca/  Health Canada -http://www.hc-sc.gc.ca/http://www.hc-sc.gc.ca/  Public Health Agency of Canada -http://www.phac-aspc.gc.ca/http://www.phac-aspc.gc.ca/  BC Drug and Poison Information Centre  BC Trauma Registry

17 17 External Datasets  Provincial Discharge Abstract  CIHI Portal Services  CIHI indicator reports and data holdings  CIHI-HayGroup Benchmarking  Health Ideas  Population projection P.E.O.P.L.E. series  BC Ambulance Services  BC Bedline

18 18 External Datasets  Provincial Discharge Abstract -Contains inpatient and day procedure abstracts for all health authorities -All required abstract data elements are present -Useful for service utilization by place of residence and comparative studies -For more information contact DSS

19 19 External Datasets  Canadian Institute for Health Information (CIHI) Portal Service -Based on inpatient and day procedure data for all provinces and territories -Most abstract data elements are present -Allows on-line reporting and multi- dimensional analysis on available data elements -For more information contact

20 20 External Datasets  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.casecure.cihi.ca

21 21 External Datasets  CIHI data holdings -CIHI provides data to researchers in accordance with its privacy policies -Data holdings include health services health expenditures health human resources -More information at secure.cihi.casecure.cihi.ca

22 22 External Datasets  CIHI-HayGroup Benchmarking Comparison of Canadian Hospitals -Reports and tools to compare clinical efficiency, operational efficiency and quality of care -Based on acute and day procedure abstracts and financial and statistical data from participating hospitals -For more information contact

23 23 External Datasets  Healthideas -contains information about health services to British Columbians including hospital services, physician services, and population and other reference data -healthideas.hnet.bc.cahealthideas.hnet.bc.ca  Population projection P.E.O.P.L.E series -www.bcstats.gov.bc.ca/health/www.bcstats.gov.bc.ca/health/

24 24 Fraser Health Datasets  Discharge Abstract  Meditech  Data Extracts from Meditech  Infection Surveillance  Health Incidents Reporting System  Workplace Health Injury Reporting

25 25 Fraser Health Datasets  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

26 26 Fraser Health Datasets  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

27 27 Fraser Health Datasets  Meditech -Various Modules, including financial, materiel management, human resources, admissions, abstracting, etc. -Data reported and extracted using canned or custom reports

28 28 Fraser Health Datasets  Data Extracts from Meditech -Ambulatory data All visits Includes data elements on age, dates and locations -Emergency Department Data All emergency visits Includes data elements on dates and times, locations, triage acuity scores, age, Richer dataset after implementation of EDIS

29 29 Fraser Health Datasets  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

30 30 Fraser Health Datasets  Health Incidents Reporting System -Includes medication variance, falls and more -Data elements include dates, times, age, location, nature, severity, etc.  Workplace Injury Reporting -Data elements include dates, times, nature, contributing factors, etc.

31 31 Examples of studies using population and administrative datasets

32 32 Case Study: How do we measure the health of an organization ? The Healthy Workplace Initiative Experience W Mughal, L Thomas-Olson, P Brown, D Keen Workplace Health

33 33 Overview  Background on the Healthy Workplace Initiative  First Round Experience  Challenges  Second Round Experience  Future Work

34 34 Background on the Healthy Workplace Initiative  First Ministers’ Meeting Pan-Canadian Health Human Resource Strategy 2004 First Nations Strategy HHR Interprofessional Education Recruitment & Retention -Healthy Workplace Initiative!

35 35 Background on Funding Objectives of Healthy Workplace Initiatives  Improve the health and wellbeing of healthcare workers  Decrease absenteeism, turnover, overtime, of healthcare workers to improve the health system productivity  Establish policy/settings that enhance the workplace, thereby improving provision of quality healthcare

36 36 FH’s Healthy Workplace Initiative “ Development of a Healthy Workplace Prevention Action Plan Through Integrated Data Analysis”

37 37 Issues/Drivers  How do large organizations decide where their limited resources are best spent to improve health & wellness?  “Data rich, information poor” -Harnessing the potential that exists within the vast sets of data present within the organization  Availability of substantial amount of data with little integrated analysis

38 38 Project Outline  Develop a comprehensive multifactorial model that includes multiple organizational data sets to provide a profile of the health of the workplaces and the workers.  By virtue of the industry, efforts were made to collect other relevant data: - Patient safety - Security interventions

39 39 Lit Review Findings  Examples of systems and indicators  Examples of interventions

40 40 Health Surveillance System (WHO, 2002)  Comprehensive system should steer the organization to: -Stimulate epidemiological research -Predictive activities (modeling) -Action-oriented research and interventions -Assess effectiveness of interventions -Provide guidance on policies and programmes

41 41 Health Surveillance System (WHO, 2002)  Prevention and surveillance activities -health assessments -occupational injury data -sentinel event notification -surveys, investigations and inspections  Descriptive demographic data -Health, injury, socio-economic, conditions

42 42 Data Acquired 2005 calendar year  Influenza Vaccination  LTD (Frequency, Hours, Costs)  Worker Injury (Frequency, Costs, Days Lost, Nature)  Payroll (sick, OT, Regular, others…)  Span of Control  Turnover  Security Interventions*  Adverse Events* * At Organization/Site level only

43 43 Indicators Indicators Used in Literature Demographics (age, gender, etc.) Mental Health Claims Health Risk Ax (incl. stress and personal risk factors) Prevention Activities Exposure SurveysOvertime Injury/illness recordsTurnover Health ClaimsAbsenteeism/Sick time Pharmacy Claims Immunizations (Influenza, etc.)

44 44 Levels of Reports  Executive Team  Executive Directors & Regional Directors  Workplace Health Teams -Responsible for areas in FH -Includes acute, residential and community care

45 45 Annual Report Structure  Introduction  Project Background  Costs Summary  Impact Factor  Indicator Summaries  Appendix -Healthy Workplace Indicators -Actual Costs and Frequencies

46 46

47 47 Sample Indicators

48 48 Sample Data Table

49 49 Challenges Encountered  Data Access -Locating/Sourcing  Data Quality  Mapping/Integration  Document preparation

50 50 Second Round…revision to our processes 1.Finalize Organizational Map 2.Integrate data according to Map 3.Run tables and charts 4.Check for quality (“smell test”) 5.Report Production 6.Distribution and Communication 7.Evaluation

51 51 Process…improved!  Obtained “map” from Finance – as good as it gets!  Aware of known quality issues – no more surprises  Report templates already prepared  2 nd Annual Report released May 2007

52 52 Future Work - Accountability  Reports to go to Executive and Regional Directors  Inclusion in “Strategic Actions” list in performance planning tool  Annual performance targets -To organizational average -To provincial average

53 53 Future Work - Application  Enterprise risk management  Integration within Workplace Health Teams  Identification of resources/opportunities  Exploratory analyses  Benchmarking internally/externally

54 54 Future Work – Research Activities  Development of research questions arising from discussions  Identification of research partners  Identification of sources of funding

55 55 If I had to do it all over again…  Ensure that your mapping is accurate  Check data quality before production  This is just more information for the decision-makers -Evaluate it’s usefulness! -Ensure contextual relevance (uptake)

56 56 Hospital volume and mortality for mechanical ventilation of medical and surgical patients: A population-based analysis using administrative data  Research Question - Is hospital volume associated with improved survival for medical and surgical patients receiving mechanical ventilation?  Design - Population-based retrospective cohort study  Data source - Ontario physician billing database - Hospital discharge database (126 hospitals) - Vital statistic - Three databases were linked via unique, encrypted patient identifier to create an electronic file of mechanical ventilation episodes during the Crit Care Med, 2006 Vol. 34, No.9

57 57 Hospital volume and mortality for mechanical ventilation of medical and surgical patients: A population-based analysis using administrative data  Definitions - Hospital volume = mean annual number of ventilation episodes performed at each hospital - Hospitals were grouped into five volume categories (<100, , , , ≥700) Patient cohort Excludes: - Repeat episodes - Episodes occurred across two or more hospitals - Episodes associated with trauma - Episodes with a duration <3days - Patients were defined as surgical if ventilation was initiated on the same day or subsequent day after surgery, otherwise, patients were define as n “medical” - Final cohort included 6,373 surgical and 13,846 medical patients - Crit Care Med, 2006 Vol. 34, No.9

58 58 Hospital volume and mortality for mechanical ventilation of medical and surgical patients: A population-based analysis using administrative data  Analyses -Multivariable logistic regression analysis to examine the relationship between hospital volume and 30 day mortality  Results -Volume had no effect on mortality for surgical patients with an odds ratio of 1.01, at 95% confidence interval -Among medical patients, after adjustment for clustering, the lowest volume category had a non significant increase in mortality with an odds ratio 1.13, at 95% confidence interval Crit Care Med, 2006 Vol. 34, No.9

59 59 The role of Decision Support  Provide health information for the evaluation and planning of health services in FH  Summarize and report data related to population demographics, health status and utilization of health services  Endeavor to support research and evaluation related data needs

60 60 Ways to access data  DSS Website Population 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 process For example, specific data for program planning and evaluationData Request FormData Request Form  Research related data request Governed by “Policy for the Provision of Research Related Services”

61 61 Research Related Services Policy for the Provision of Research-Related Services, Decision Support Policy 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

62 62 Data Planning  Although formal request for data occurs when application has been submitted for ethics approval, data planning typically starts much earlier  Practical questions to be considered:  Are required data being collected?  Are data Accessible?  Are there cross jurisdictional comparison issues?  Cost & time  Research intelligence unit, Decision Support (Data Consult Form) and Health Records can provide valuable adviceData Consult Form

63 63 Procedures……….. Applications to FH Research Ethics Board Contact DSS Manager/Designate to have DAR Form signed(DAR) form(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

64 64 A quick look at the DSS Website

65 65 Questions/Comments?


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