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Time trends & patterns, TB
 

Time trends & patterns, TB

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    Time trends & patterns, TB Time trends & patterns, TB Presentation Transcript

    • Time trends & patterns: TB Glion sur Montreux, 21-22 September 2009 Mehran Hosseini (hosseinism@who.int) WHO/HQ/TB Monitoring and Evaluation Unit Improving the quality of health statistics for country reviews and global reporting Methods, tools and country approaches
    • Data quality: what is it? 2. Jack E. Olson "Data has quality if it satisfies the requirements of its intended use . It lacks quality to the extent that it does not satisfy the requirement. In other words, data quality depends as much on the intended use as it does on the data itself. To satisfy the intended use, the data must be accurate, timely, relevant, complete, understood, and trusted." 2. US Census Bureau " Fitness for use. To be fit for use, data products must possess all three attributes of quality defined by the Office of Management and Budget: 1) Utility - refers to the usefulness of the information for its intended users . 2) Objectivity - refers to whether information is accurate, reliable, and unbiased, and is presented in an accurate, clear, and unbiased manner. 3) Integrity - refers to the security or protection of information from unauthorized access or revision."
    • Intended use of Health Information
      • Monitor and assess disease trends
      • Guide prevention and intervention programs
      • Inform public health policy and policy makers
      • Identify issues needing public health research
      • Provide information for community and program planning
      • Protect confidentiality while providing information to those who need to know
      Source: www.cdc.gov/NEDSS/About/overview.html
    • Example: measure trend in TB incidence using notification data Kenya Pakistan Russia Brazil Thailand China
    • Key questions as far as data quality is concerned:
      • Can we assess the trend in TB incidence using these data?
      • If no, why? Can we adjust the data to make the assessment?
      New TB notification rate Kenya Zambia
      • HOW TO ASSESS DATA QUALITY?
        • M & E strengthening tool
              • (MEASURE Evaluation)
        • Performance of Routine HIS tool
              • (JSI)
        • HIS assessment tool
              • (Health Metrics Network)
        • Record reviews (DQA tools by Measure and GAVI)
        • Analytical approaches
            • Population based data
            • Commodities
            • Models
            • Patterns and trends
      System (M&E, HIS) Data Assessing quality: system vs. data
    • Framework for estimation and measurement of TB incidence using surveillance data
    • Determinants of TB notifications
      • Changes in case finding efforts (e.g. infrastructure, staff, active case finding efforts)
      • Changes in recording and reporting system
        • Quality of recording (e.g. misclassification, completeness)
        • Quality of reporting (e.g. coverage, completeness, duplicated reporting)
        • Changes in TB case definitions
      • and,
      • Changes in incidence
      New TB cases, reported by country DPR Korea
    • Pulmonary TB cases/100k/year Slides examined (k/yr) Suarez, P. G. et al. The dynamics of tuberculosis in response to 10 years of intensive control effort in Peru. J Inf. Dis 184, 473-8 (2001) DOTS Increasing diagnostic effort Declining notification rate Changes in case finding efforts
    • Change in case definition, Cuba Change in case definition
    • Changes in coverage of reporting
    • Changes in TB incidence
    • Incomplete reporting Mexico
    • Indication of completeness of data and reliability
        • Indicators
        • Percent change in notification rate (+/- 10% change)
        • Proportion of smear-positive/pulmonary (65-80%)
        • Proportion of pulmonary/New (85-90%)
        • Proportion of new/all cases
        • Checks
        • Internal consistency (across time and space)
        • External consistency (across expected values)
    • Identification of unusual fluctuations
    • Were the fluctuations were driven by a certain case type?
    • Is there a lot of variation between notification rates of new TB cases across admin1? Why? ~ 10 ~ 35
    • Were the fluctuations found for the national data were driven by certain admin 1 areas?
    • A - Proportion of all TB cases that are new
    • B - Proportion of new cases that are pulmonary
    • C - Proportion of all pulmonary cases that are smear positive
    • D - Proportion of all re-treatment cases that are 1) relapse, 2) treatment-after-failure, 3) treatment-after-default 4) other re-treatment
        • √ Relapse
        • √ Treatment-after-failure
        • √ Treatment-after-default
      • √ Other re-treatment
    • A - Proportion of all TB cases that are new
    • B - Proportion of new cases that are pulmonary
    • C - Proportion of all pulmonary cases that are smear positive
    • Adjustment of data Kenya Pakistan Russia Brazil Thailand China Reported Estimated
    • Tool on CD:
      • Workbook
      • Free software and scripts to produce graphs
    • Next steps for HMN
      • Form a technical working group to develop analytical methods as well as a compendium of indicators to assess the reported data
      • Develop guidelines for countries containing the minimum specifications of an electronic health information systems with the model implementation using open source platforms such as Open MRS and DHIS
      • Develop a data sharing platform (e.g. web page) where the successful experiences in health information system, tools and methods can be shared
    • Next steps for countries
        • Establish a data quality intelligence unit at the national level to regularly check the surveillance data for quality and provide feedback to the peripheral levels
        • The DQA studies should be guided and focused on reporting units where the questionable data quality is observed by conducting in-depth analysis of already collected data using the analytical methods for quality checks
    • The Matterhorn (German), Cervino (Italian) or Cervin (French), is a mountain in the Pennine Alps. The Matterhorn is an iconic emblem of the Swiss Alps, and Alps in general. Thank you!