The Ontario Health & Environment Integrated Surveillance (OHEIS) - PowerPoint PPT Presentation

The Ontario Health & Environment Integrated Surveillance (OHEIS) Project Presented to: The Association of Public Health Epidemiologists in Ontario (APHEO) E. Holowaty, P. Brown, T. Norwood, S . Wanigaratne Population S tudies and S urveillance, Cancer Care Ontario May 2, 2008

2 2 Overview � Introduction to the RIF � Relevance to APHEO � Technical details & requirements � RIF database � RIF demo � Opportunities and Challenges � Questions & Discussion

3 3 The Rapid Inquiry Facility � S mall Area Health S tatistics Unit at Imperial College London � User friendly tool, used to rapidly address public health questions using routinely collected health and population data • risk analysis around putative hazard sources and across covariate categories • sophisticated risk mapping � Calculates standardised incidence ratios and directly standardised rates for any health outcome, for specified age and year ranges, for any given geographic area

4 Disease Mapping with the RIF � Addresses problems of small populations and counts by calculating indirectly standardised incidence ratios � Covariate-adj usted S IRs using Poisson assumption for rare health outcomes � Allows for spatial dependence between neighbouring regions using random effects models � Interfaces to other readily available statistical programs to perform Bayesian inference and cluster analysis

5

6

7 � slide of income

8

9

10 Risk Analysis: point source exposures � Calculates standardised incidence ratios and directly standardised rates for each exposure band or covariate category, does test for homogeneity and linear test for trend

11 � tables and graphs are output from risk analysis

12 How is this relevant to APHEO? Ontario Public Health Standards … establish requirements for fundamental public health programs and services, which include assessment and surveillance… … key component of the requirements… is to identify and work with local priority populations… identified by surveillance, epidemiological, or other research studies…

13 Population Health Assessment Surveillance Protocol The board of health shall: … adopt, adapt, or develop techniques, tools and/ or systems for… collection, management, and integration of data… … make comparisons by person, place and time to consider the relationships among these elements… includes analysis of health unit data and how data are spatially distributed… … consider the following aids to interpret and understand various aspects of a health issue… by… maps…

14 Identification, Investigation and Management of Health Hazards Protocol Purpose: to prevent or reduce the burden of illness from environmental health hazards. The board of health shall: … monitor and collect data on the health status of residents in the board of health area, including but not limited to epidemiological studies focusing on adverse health outcomes potentially related to health hazards in the environment … conduct analysis and evaluation of the data collected to identify potential human health risks from health hazards in the environment

15 RIF – Technical Details � RIF Version 3.11 • An extension for ArcGIS 9.0 or higher. Primarily, hardware requirements are determined by ArcGIS requirements: - 1.6 GHz processor or better Intel Duo, Pentium or Xenon processors - 1 GB RAM minimum; 2GB recommended - Disk space 1.2 GB - 64 MB video card recommended • Windows XP, 2003, or Vista • Microsoft Office 2003 or higher • Microsoft Access or Oracle 10 or higher

16 Technical Details - RIF application architecture Geographic Information RIF Database System (GIS) SQL Commands OCR & Read ArcGIS Census data (Access or Write Oracle)

17 RIF Technical Details � CCO’ s OHEIS S erver Architecture ArcGIS Database Server External Users Web Server (Project collaborators) Firewall RDMS Web server: Web map Service WWW Open GIS Web map Service compliant ArcGIS service (e.g. RIF (ArcGIS Server WMS) Desktop) RIF (ArcGIS Internal Desktop) Users LAN

18 RIF Database � Designed on basis of geographical hierarchies. � For Canadian data: SGC SAC LHIN PHU Hierarchy (Standard Geographical (Statistical Area (Local Health (Public Health Unit) name: Classification ) Classification) Integrated Network) Hierarchical PR* PR* PR* PR* levels: CD* CMA LHIN* PHU CSD* CT DA PHU Custom Geography+ DA/EA DA DA * Note: intercensal population estimates available for these geographical levels. +Note: if applicable

19 RIF Database � RIF Database contains 48 tables required by the application to run � You add tables for population, health events, covariates and geographic hierarchy lookup � Of these tables that you add to the database, generally, you can think of them as: • numerator data – your health outcome file • denominator data – population by age-sex groups

20 RIF Database � Numerator data: coded by age-sex groups, and health event coding if applicable � Denominator data: population by geographic area. You may use multiple geographic hierarchic levels. For each geographic level: • lookup table • table of population by age-sex groups • covariate table (optional)

21 RIF Demonstration � S IRs by 2001 DA for Windsor CS D � WinBUGS – Full Bayesian S moothing using the Besag, York and Mollié (BYM) model

22 Opportunities � Interest and use of GIS for health data � Computing power and software availability � Availability of georeferenced data � Expectations for rapid hazard appraisal and more granularity in community health profiling � General calls for widespread use and easy access � S ignificant advances in spatial analysis

23 How can GIS help Public Health? � Research, S urveillance and Planning • Hypothesis generation – maps, correlations, clusters • Models of disease risk • S ervice planning and optimisation • Making predictions e.g. Health Impact Assessment � S patial Decision S upport S ystems • Infrastructure – roads, towns, HC services/ availability • Census – population statistics; socio-demographics � Emergency/ Pandemic Response S ystems • 911 services • Disease/ event registers, including infectious diseases

24 Special challenges � Accuracy, granularity and completeness of exposure, health and population data, and boundary files � Geocoding, i.e., accurately assigning spatial coordinates to location info. � Current place of residence may not be good proxy for exposure � Problems adj usting for known confounders � Necessity of aggregating counts � S cale/ zone translation problems (MAUP) � S patial autocorrelation � Data access and confidentiality restrictions

25 Measuring and reducing disclosure risk � Estimating risk • Population uniques • Probabilities of identification • Absolute vs. relative risk of disclosure � Institutional approaches • Full public access if no disclosure risk • Licensing of users • Data enclaves � Technical approaches • Aggregation • Data limitation – cell suppression, rounding • Geo-masking – swapping, random perturbation

26 Aims of OHEIS Proj ect � To design, implement and test an enhanced spatial surveillance system for mapping and risk assessment � Rapid assessment (3-6 mos. <1 week) � S cientifically sound, robust, understandable and transparent � Easily export data to more sophisticated spatial analysis systems – WinBUGS ; S aTS can; EXCEL � To share data, software and/ or RIF outputs with PH partners thru web-based portal and/ or stand-alone, secure PC applications.

27 Resources � “The GIS Primer” web-based http:/ / www.innovativegis.com/ basis/ primer/ primer.html � “Health and Environment Information Systems for Exposure and Disease Mapping and Risk Assessment” Jarup et al. Environmental Health Perspectives. 2004. Vol. 112: 995-525. � “GIS and Public Health” Cromley EK and McLafferty S L. Guildford Press. 2002. � “ Putting People on the Map : Protecting Confidentiality with Linked Socio-Spatial Data” Gutmann MP et al. National Research Council. 2007. http:/ / books.napedu/ catalog/ 11865.html

28 Resources (cont’ d) � “Spatial Epidemiology : Methods and Applications” Elliott P. et al. Oxford University Press. 2000. � “Applied Spatial Statistics for Public Health” Waller LA and Gotway CA. Wiley Interscience. 2004. � “ Geographic Information Systems and Public Health” Richards TB et al. Public Health Reports Vol.114.1999. http:/ / www.healthgis-li.com/ library/ phr/ phr.htm � “ Public Health and GIS” Rushton G et al. Annual Review of PH. Vol.24.2003.

29 Appendix A – RIF Demonstration S lides These slides are intended to allow teleconference users to follow the live demonstration of the Rapid Inquiry Facility (RIF).

30 Disease Mapping: Lung Cancer Incidence in Windsor, Ontario � The RIF is an extension to ArcGIS and adds a “ RIF” menu to the ArcMap application. To start a new study, within the menu, simply go to “ S tudy” ->” New” :

31 S tep 1 – Define S tudy Type � For this demonstration, we will be showing a disease mapping analysis: Click “ Next”