SayPro’s data integrity form

SayPro Health Records Data Management Protocol

1. Curate: Select and Prepare Relevant Records

• Source Identification: Pull only verified electronic health records (EHRs) from SayPro-approved clinics, partner databases, and regional health surveys.
• Relevance Filtering: Focus on records related to:
  • Priority health conditions (e.g., HIV, TB, maternal health)
  • Active regions (urban/rural split)
  • Recent timeframes (e.g., past 24 months)
• De-identification: Ensure all patient identifiers (names, IDs, contact info) are removed before uploading.

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2. Clean: Validate and Format Records

• Use SayPro’s Data Integrity Form to enforce consistency:
  • Check for missing fields (e.g., age, diagnosis code, date of visit)
  • Correct format issues (e.g., date formats, measurement units)
  • Validate against master lists (e.g., ICD-10 codes, facility names)
• Flag duplicates or suspicious entries for manual review
• Standardize terms (e.g., “HIV Positive” vs. “HIV+”)

🛠 Tip: Use Excel/CSV pre-load filters or Notion tables to assist with batch validation before SayPro web upload.

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3. Categorize: Assign Tags and Organize Records

Each health record should be categorized using SayPro’s taxonomy:

Category	Subcategories/Tags
Disease Type	Infectious, Chronic, Maternal, Mental Health
Geographic Region	Province, District, Urban/Rural
Demographic	Child, Adult, Elderly, Gender
Service Type	Outpatient, Emergency, Follow-up, Preventive
Outcome	Recovered, Ongoing, Deceased

Use dropdowns or predefined tag menus in the SayPro portal upload interface.

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4. Upload and Trace:

• Log in to the SayPro portal
• Go to: Health > EHR Upload > Data Integrity Submission
• Use the SayPro Data Integrity Form (attached in the portal)
  • Fill in for each batch: Source, Curator Name, Timestamp, Notes
• Submit and validate via confirmation page and audit trail

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5. Continuous Monitoring

• Revisit flagged or incomplete submissions weekly
• Ensure all uploaded data feeds into SayPro’s M&E dashboards

Link data to demographic and regional identifiers

Linking Health Data to Demographic & Regional Identifiers

1. Standardize Demographic Identifiers

Include the following fields in every health record:

Field	Format Example
Age	Integer (e.g., 32)
Gender	Male / Female / Other
Age Group	Child (0–14), Youth (15–24), etc.
Ethnic Group	As per SayPro standard codes
Socioeconomic Tier	Low / Middle / High Income

Use SayPro’s demographic dropdown or mapping sheet to ensure consistency.

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2. Attach Regional Identifiers

Map each record to spatial data points:

Field	Format Example
Province	Gauteng, KwaZulu-Natal, etc.
District/Municipality	Tshwane, uMgungundlovu, etc.
Health Facility Code	Unique SayPro-aligned code
Urban/Rural Code	Urban / Rural / Peri-urban
Geo-coordinates (if available)	Lat/Long

Reference the official SayPro regional mapping table during upload.

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3. Data Integration Process on SayPro Website

1. During Upload via SayPro Data Integrity Form:
   • Include demographic and regional columns for each record.
   • Use dropdown menus to enforce accuracy (if uploading via portal).
2. System-Level Linking:
   • The SayPro backend links data entries to dashboards and mapping tools via unique identifiers (region codes, demographic tags).
   • This enables real-time filtering and disaggregation for visualizations and reports.

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4. Use Cases Enabled

• Regional Disease Surveillance (e.g., HIV prevalence in Eastern Cape vs. Limpopo)
• Targeted Policy Planning (e.g., maternal health access for low-income rural women)
• Equity Analysis (e.g., age- or gender-specific treatment gaps)
• Performance Reporting by Province and Demographic Segments