Methods of data collection_ referral and collection

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					Methods of data collection, referral and
              collation

                Tom Oluoch
     KEMRI/Wellcome Trust, Kilifi – Kenya
             netSPEAR meeting
           17-19 November, 2003
Information Flow
                      Form Data

• Few fields on specimen forms
   – Patient name, IP No., Age, Sex, Specimen type, Date of
     specimen, Time of specimen, etc
• Basic/Demographic data filled in by hand by the
  Clinician
• Initial form data entered by Lab Technician
• Lab results entered by the Lab Technician
                 Types of Data Fields

• Vital Data
   – Entry cannot proceed without entering these values
       • Specimen/Sample ID (e.g. Serial No., IP No., etc.), Dob/Age, Sex

• Valuable Data to netSPEAR
   – Entry into the computer system will continue but the record will be
     flagged as incomplete
       • Date and Time of specimen


• …Ideally recorded data should be as complete as possible
               Data Entry System

• Choice to be made between FileMaker, Visual FoxPro and
  Visual Basic
• To be developed and tested in Kilifi, borrowing from
  existing systems
• Simple Entry Screen forms matching the paper form
• Data stored in dbf format at sites
• Standalone installation on PC/Mac, no requirement for a
  server or a Local Area Network
• Time reminder (15th of each month, for previous
  submission).
• Automated e-mail submission on click of a button
Sample Layout
Sample Layout
Sample Layout
  Data Referral
Site               Site



          NC                         Site




       Data
       Cleaning      Queries




       Analysis/
       Summary        Queries/Feedback




       Upload to
       website
Sending Data




           -Computer
           -Modem/LAN
           -Telecom Link to ISP
 Data Management by netSPEAR team
• Quality Control
   – Data Cleaning
      •   Consistency checks (also inbuilt in entry system)
      •   Duplicate entries
      •   Range checks
      •   Missing data
• Feedback to sites
   – No. of Isolates over time, Sensitivity to antibiotics, etc
   – Performance indicators based on submission times,
     quality of data etc
• Types of Analysis/Summaries
   – Hospital, Country, Regional summaries etc.
               Data Dissemination
• Targeted Audience
  –   Ministries of Health
  –   Donors
  –   Policy Makers in the Health Sector
  –   Researchers in related fields
  –   Academicians


• Website
  – www.netspear.org
  – Has Static and Dynamic pages
                Data Dissemination

• Static Pages:
   – Home, News, Surveillance etc
   – Mainly textual and images
• Dynamic Pages:
   – Based on data from hospitals/countries/region
   – Mainly predetermined graphs generated on-the-fly
     based on latest data uploaded by netSPEAR team
   – Highly summarised data with provision for drill-down
   – Allows flexibile queries to select periods, isolates, etc
              Website Updates

• Developed in Dreamweaver
• netSPEAR team uploads cleaned summarised data
  at regular intervals
• News Pages