@article{Lix_Reimer_2017, title={The Canadian Chronic Disease Surveillance System: A Distributed Surveillance Model}, volume={9}, url={https://ojphi.org/ojs/index.php/ojphi/article/view/7726}, DOI={10.5210/ojphi.v9i1.7726}, abstractNote={<div style="left: 72px; top: 268.606px; font-size: 11.3333px; font-family: sans-serif; transform: scaleX(1.08137);" data-canvas-width="51.022666666666666">Objective</div><div style="left: 84px; top: 280.567px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.01062);" data-canvas-width="302.96833333333325">To describe the process, benefits, and challenges of implementing</div><div style="left: 72px; top: 293.901px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.03685);" data-canvas-width="315.53133333333324">a distributed model for chronic disease surveillance across thirteen</div><div style="left: 72px; top: 307.234px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.00255);" data-canvas-width="104.51599999999999">Canadian jurisdictions.</div><div style="left: 72px; top: 332.606px; font-size: 11.3333px; font-family: sans-serif; transform: scaleX(1.11794);" data-canvas-width="66.10733333333333">Introduction</div><div style="left: 84px; top: 344.567px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.988552);" data-canvas-width="304.4575333333333">The Public Health Agency of Canada (PHAC) established the</div><div style="left: 72px; top: 357.901px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.00535);" data-canvas-width="314.95899999999995">Canadian Chronic Disease Surveillance System (CCDSS) in 2009 to</div><div style="left: 72px; top: 371.234px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.00061);" data-canvas-width="314.77539999999993">facilitate national estimates of chronic disease prevalence, incidence,</div><div style="left: 72px; top: 384.567px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.00761);" data-canvas-width="317.02733333333316">and health outcomes. The CCDSS uses population-based linked</div><div style="left: 72px; top: 397.901px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.02635);" data-canvas-width="315.36360000000013">health administrative databases from all provinces/territories (P/Ts)</div><div style="left: 72px; top: 411.234px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.03975);" data-canvas-width="315.7715999999999">and a distributed analytic protocol to produce standardized disease</div><div style="left: 72px; top: 424.567px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.00296);" data-canvas-width="45.01599999999999">estimates.</div><div style="left: 72px; top: 449.94px; font-size: 11.3333px; font-family: sans-serif; transform: scaleX(1.07312);" data-canvas-width="46.59133333333333">Methods</div><div style="left: 84px; top: 461.901px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.07723);" data-canvas-width="306.7242">The CCDSS is founded on deterministic linkage of three</div><div style="left: 72px; top: 475.234px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.971461);" data-canvas-width="313.99226666666664">administrative health databases in each Canadian P/T: health insurance</div><div style="left: 72px; top: 488.567px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.992369);" data-canvas-width="316.54906666666676">registration files, physician billing claims, and hospital discharge</div><div style="left: 72px; top: 501.901px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.974727);" data-canvas-width="316.38019999999983">abstracts. Data on all residents who are eligible for provincial or</div><div style="left: 72px; top: 515.234px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.97139);" data-canvas-width="314.2608666666666">territorial health insurance (about 97% of the Canadian population) are</div><div style="left: 72px; top: 528.567px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.02021);" data-canvas-width="315.3466000000001">captured in the health insurance registration files. Thus, the CCDSS</div><div style="left: 72px; top: 541.901px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.998393);" data-canvas-width="314.62693333333334">coverage is near-universal. Disease case definitions are developed by</div><div style="left: 72px; top: 555.234px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.969426);" data-canvas-width="315.87133333333344">expert Working Groups after literature reviews are completed and</div><div style="left: 72px; top: 568.567px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.99209);" data-canvas-width="316.2453333333335">validation studies are undertaken. Feasibility studies are initiated</div><div style="left: 72px; top: 581.901px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.02762);" data-canvas-width="317.3979333333331">in selected P/Ts to identify challenges when implementing the</div><div style="left: 72px; top: 595.234px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.02951);" data-canvas-width="315.40666666666675">disease case definitions. Analytic code developed by PHAC is then</div><div style="left: 72px; top: 608.567px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.02427);" data-canvas-width="315.4406666666666">distributed to all P/Ts. Data quality surveys are routinely conducted</div><div style="left: 72px; top: 621.901px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.962962);" data-canvas-width="315.6911333333331">to identify database characteristics that may bias disease estimates</div><div style="left: 72px; top: 635.234px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.979515);" data-canvas-width="314.3753333333333">over time or across P/Ts or affect implementation of the analytic code.</div><div style="left: 72px; top: 648.567px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.02562);" data-canvas-width="315.47920000000005">The summary data produced in each P/T are approved by Scientific</div><div style="left: 72px; top: 661.901px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.992549);" data-canvas-width="314.4229333333333">Committee and Technical Committee members and then submitted to</div><div style="left: 72px; top: 675.234px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.00148);" data-canvas-width="185.70800000000003">PHAC for further analysis and reporting.</div><div style="left: 72px; top: 700.606px; font-size: 11.3333px; font-family: sans-serif; transform: scaleX(1.08488);" data-canvas-width="40.93600000000001">Results</div><div style="left: 84px; top: 712.567px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.975693);" data-canvas-width="302.4809999999998">National surveillance or feasibility studies are currently ongoing for</div><div style="left: 72px; top: 725.901px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.00982);" data-canvas-width="315.1822666666666">diabetes, hypertension, selected mental illnesses, chronic respiratory</div><div style="left: 72px; top: 739.234px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.01863);" data-canvas-width="317.0817333333332">diseases, heart disease, neurological conditions, musculoskeletal</div><div style="left: 72px; top: 752.567px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.979131);" data-canvas-width="316.24306666666644">conditions, and stroke. The advantages of the distributed analytic</div><div style="left: 72px; top: 765.901px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.957339);" data-canvas-width="315.82600000000014">protocol are (Figure 1): (a) changes in methodology can be easily</div><div style="left: 72px; top: 779.234px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.975751);" data-canvas-width="314.41953333333333">made, and (b) technical expertise to implement the methodology is not</div><div style="left: 72px; top: 792.567px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.999784);" data-canvas-width="314.7153333333331">required in each P/T. Challenges in the use of the distributed analytic</div><div style="left: 72px; top: 805.901px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.96775);" data-canvas-width="315.9381999999998">protocol are: (a) heterogeneity in healthcare databases across P/Ts</div><div style="left: 72px; top: 819.234px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.991653);" data-canvas-width="314.602">and over time, (b) the requirement that each P/T use the minimum set</div><div style="left: 72px; top: 832.567px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.99802);" data-canvas-width="314.72553333333326">of data elements common to all jurisdictions when producing disease</div><div style="left: 72px; top: 845.901px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.995218);" data-canvas-width="316.6782666666667">estimates, and (c) balancing disclosure guidelines to ensure data</div><div style="left: 72px; top: 859.234px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.00206);" data-canvas-width="314.7459333333333">confidentiality with comprehensive reporting. Additional challenges,</div><div style="left: 72px; top: 872.567px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.02037);" data-canvas-width="315.4316">which include incomplete data capture for some databases and poor</div><div style="left: 72px; top: 885.901px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.965025);" data-canvas-width="315.98126666666656">measurement validity of disease diagnosis codes for some chronic</div><div style="left: 72px; top: 899.234px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.981703);" data-canvas-width="316.1410666666666">conditions, must be continually addressed to ensure the scientific</div><div style="left: 72px; top: 912.567px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.00633);" data-canvas-width="155.21">rigor of the CCDSS methodology.</div><div style="left: 72px; top: 937.94px; font-size: 11.3333px; font-family: sans-serif; transform: scaleX(1.10259);" data-canvas-width="68.01133333333334">Conclusions</div><div style="left: 84px; top: 949.901px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.981002);" data-canvas-width="304.42126666666655">The CCDSS distributed analytic protocol offers one model for</div><div style="left: 72px; top: 963.234px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.01814);" data-canvas-width="317.21999999999986">national chronic disease surveillance that has been successfully</div><div style="left: 408px; top: 267.234px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.973628);" data-canvas-width="316.1206666666666">implemented and sustained by PHAC and its P/T partners. Many</div><div style="left: 408px; top: 280.567px; font-size: 11.3333px; font-family: serif; transform: scaleX(0.992236);" data-canvas-width="314.5056666666668">lessons have been learned about national chronic disease surveillance</div><div style="left: 408px; top: 293.901px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.05509);" data-canvas-width="318.09266666666656">involving jurisdictions that are heterogeneous with respect to</div><div style="left: 408px; top: 307.234px; font-size: 11.3333px; font-family: serif; transform: scaleX(1.00231);" data-canvas-width="283.2539999999998">healthcare databases, expertise, and population characteristics.</div>}, number={1}, journal={Online Journal of Public Health Informatics}, author={Lix, Lisa and Reimer, Kim}, year={2017}, month={May} }