Prevention and Control of Trichomoniasis

Overview

1. Primary Prevention (Avoiding Infection)

A. Sexual Behavior Modification

• Abstinence from vaginal, anal, and oral sex is the only guaranteed way to prevent all STIs, including trichomoniasis.
• Reduce the number of sexual partners - having multiple partners significantly increases acquisition risk. - Textbook of Family Medicine 9e, p. 621
• Mutual monogamy - being in a mutually monogamous relationship with an uninfected partner eliminates sexual transmission risk.

B. Consistent Condom Use

• Correct and consistent use of male or female (internal) condoms is the single most important preventive measure for sexually active individuals.
• Condoms reduce the risk of acquiring trichomoniasis by creating a physical barrier to parasite transmission. - Goldman-Cecil Medicine, p. 3453; CDC STI Treatment Guidelines 2021
• Male circumcision may offer some (though not definitive) risk reduction for female partners of circumcised men.

C. Avoid Douching

• Douching is not recommended as it disrupts normal vaginal flora, reduces vaginal acidity (pH), and may increase susceptibility to trichomoniasis and other vaginal infections. - CDC STI Treatment Guidelines, 2021

D. Personal Hygiene and Avoiding Fomite Transmission

• Although trichomoniasis is transmitted almost exclusively by sexual contact, the parasite can survive briefly in moist environments.
• Avoid sharing towels, bathing suits, washcloths, and toilet articles - particularly relevant in communal settings. - Medical Microbiology 9e, p. (section: Treatment, Prevention, and Control)
• Practice good personal hygiene.

E. Open Communication with Partners

• Discuss STI status and testing history with new sexual partners before sex.
• Normalizing frank, honest communication reduces unknowing transmission.

2. Screening (Secondary Prevention)

• Goldman-Cecil Medicine, p. 3452; Textbook of Family Medicine 9e, p. 621

Diagnostic Methods

• Wet mount microscopy - motile trichomonads; sensitivity ~60% in women, ~50% in men; first-line due to cost and speed.
• NAATs (nucleic acid amplification tests) - most sensitive; preferred for men and when wet prep is inconclusive.
• Rapid point-of-care tests (OSOM Trichomonas Rapid Test, AFFIRM VP III) - FDA-approved; higher sensitivity than wet mount but more false positives.
• Culture - gold standard for sensitivity but results take 3-7 days.
• Pap smear is not recommended as a diagnostic tool (sensitivity only 58%).

3. Treatment as Prevention (Tertiary Control)

First-Line Regimens (CDC 2021)

• Both drugs have a disulfiram-like reaction with alcohol - patients must avoid alcohol for 24 hours after metronidazole and 72 hours after tinidazole. - Goldman-Cecil Medicine, p. 3452
• Metronidazole gel (intravaginal) is less effective (≤50% cure rate) and is not recommended as sole therapy. - Textbook of Family Medicine 9e, p. 622

Special Populations

• Symptomatic pregnant women at any stage should be treated. Treatment relieves symptoms and prevents neonatal respiratory or genital infection.
• Metronidazole is safe in pregnancy (no teratogenicity reported); tinidazole is not recommended in pregnancy.
• Clotrimazole 100 mg intravaginally nightly for 2 weeks may relieve symptoms but does not eradicate the infection.
• Andrews' Diseases of the Skin, p. 493; Goldman-Cecil Medicine, p. 3452

• Treat with metronidazole 500 mg twice daily for 7 days (not single-dose) due to higher recrudescence rates with single-dose therapy. - Goldman-Cecil Medicine, p. 3453

• Acquired during passage through an infected birth canal; treat only if symptomatic or if colonization persists more than 4 weeks. - Andrews' Diseases of the Skin, p. 492

4. Partner Management (Critical for Control)

• Concurrent (simultaneous) treatment of all current sex partners is mandatory - nearly 20% of male partners are coinfected, and most are asymptomatic. - Goldman-Cecil Medicine, p. 3453
• Partners should abstain from sex until both have completed treatment and symptoms have resolved.
• Expedited Partner Therapy (EPT) - prescribing treatment for partners without a prior clinical evaluation - is legally permissible in many jurisdictions and can be used to reduce barriers to partner treatment. - CDC STI Guidelines 2021
• A test of cure is not necessary if symptoms resolve after treatment. However, the CDC recommends re-testing 3 months after treatment due to high reinfection rates (~1 in 5 people within 3 months). - CDC

5. Recurrent / Resistant Trichomoniasis

1. Repeat course: Tinidazole or metronidazole 2 g once daily for 5-7 days.
2. High-dose regimen: Oral tinidazole 2 g/day plus intravaginal tinidazole 500 mg twice daily for 14 days.
3. Salvage regimen: Oral tinidazole 1 g three times/day plus intravaginal paromomycin cream (4 g of 6.25%) nightly for 14 days.
4. Drug-resistance testing: CDC provides a kit for cases refractory to treatment. - CDC Resistance Testing
5. Intravaginal boric acid (600 mg twice daily for 1 month) has documented clinical improvement in some refractory cases. - Goldman-Cecil Medicine, p. 3453

6. Public Health and Surveillance Measures

• STI surveillance and reporting to track trichomoniasis trends, particularly in high-burden communities.
• Addressing health disparities - trichomoniasis rates are 7 times higher in Black women than non-Hispanic White women in the US, calling for targeted outreach and accessible testing. - Goldman-Cecil Medicine, p. 3452
• Screening programs in STI clinics, family planning centers, HIV care settings.
• Health education in schools and communities about safe sex practices, STI awareness, and partner communication.
• No vaccine is currently available for human trichomoniasis; vaccine research is ongoing.

Summary Table

Note (PubMed 2025): A recent systematic review and meta-analysis (PMID 40864904) on global prevalence and risk factors for T. vaginalis (published 2025) confirms that multiple sexual partners and lower socioeconomic status remain dominant modifiable risk factors - reinforcing the behavioral prevention strategies outlined above.

EWARS - Early Warning, Alert and Response System

1. Definition and Background

The overall aim of EWARS is to reduce excess morbidity and mortality due to epidemic-prone diseases and other public health hazards in emergency-affected populations.

2. What is EWAR vs EWARS vs EWARN?

3. Core Objective

"To support the early detection and rapid response to acute public health events of any origin." - PAHO/WHO

• Detect outbreaks before they spread and claim lives
• Provide a simple, cost-effective surveillance infrastructure where none exists
• Work in settings with no reliable internet or electricity
• Connect field health workers to decision-makers in real time
• Generate automated epidemiological reports to inform response

4. Three Core Components of EWAR

A. Early Warning (Signal Detection)

• The rapid detection of signals that may indicate a potential acute public health event.
• Uses two complementary surveillance approaches:

• Alert thresholds are pre-set for each disease. When a threshold is crossed, the system automatically flags the event for urgent investigation.

B. Alert (Verification and Triage)

• Upon receiving a signal, the system activates an immediate investigation to verify whether the event represents a true outbreak threat.
• Verification typically occurs within 24 hours of alert generation.
• Alerts are triaged as: Discarded (false alarm), Monitored (watch and see), or Requires Response (confirmed outbreak).

C. Response (Action)

• Once an alert is verified as a real event, EWARS supports rapid public health response including:
  • Outbreak investigation (case-based line listing with GPS coordinates)
  • Generic immediate control measures
  • Agent-specific control measures (e.g., vaccination, case isolation, water chlorination)
  • Real-time epidemic curves, maps, and dashboards
  • Automated daily outbreak bulletins shared with partners

5. EWARS Technology Platform

i. EWARS Mobile (Data Collection)

• A mobile app installed on smartphones distributed to health workers at reporting sites (clinics, health posts)
• Workers submit weekly aggregate reports and immediate case alerts using pre-configured digital forms
• Works offline - data queues and submits when network is available
• Provides SMS feedback to facilities: report receipt confirmations, overdue reminders, and instant alert notifications

ii. EWARS DataHub (Server/Analysis)

• A local server that receives, stores, and processes all incoming data
• Generates automated epidemiological bulletins, epidemic curves, and maps
• Works fully offline - no internet required
• Allows customized analysis, line-list export, and anonymization of data for partner sharing
• Hosts alert threshold logic and sends alert notifications

iii. EWARS Exchange (Online Dashboard)

• An online platform for when internet connectivity is available
• Allows broader data sharing with national authorities, WHO, and partner organizations
• Supports integration with national surveillance systems

6. EWARS "in a Box"

Contents of the Box:

• 60 mobile phones (for data collection at health facilities)
• Laptops (for data management and analysis)
• A local server (DataHub - works offline)
• Solar generator and solar chargers (for areas without electricity)
• Network equipment and accessories
• Pre-loaded surveillance software

Key Specifications:

• WHO EWARS page

7. Diseases and Conditions Monitored

8. EWARS Alert Threshold System

1. The system automatically generates an alert
2. Alert is sent via SMS to surveillance officers
3. A 24-hour verification is initiated
4. If confirmed, a public health response is activated

9. EWARS Implementation Process

EMERGENCY DECLARED
        ↓
Rapid needs assessment (existing surveillance capacity?)
        ↓
Configure EWARS (diseases, thresholds, reporting sites, case definitions)
        ↓
Deploy EWARS in a Box → Train health workers
        ↓
Weekly aggregate reporting + Immediate case alerts
        ↓
Automated alert generation → 24h verification
        ↓
Response activation (investigation, control measures)
        ↓
Weekly epidemiological bulletins → Feedback to facilities
        ↓
Post-emergency: Re-integrate into national surveillance system

10. Governance and Partners

• EWARS is led and managed by WHO in coordination with:
  • Ministries of Health (national ownership)
  • UNHCR (refugee settings)
  • UNICEF, MSF, NGOs (health facility network)
  • US CDC (technical support and evaluation)
  • ECDC (European contexts)

11. EWARS vs Routine Surveillance Systems

12. Where EWARS Has Been Used

Summary

Understanding the EWARS Diagram - Simply Explained

The Players in This System

Meet the Key Players (Simply)

🟩 EDCD - Epidemiology and Disease Control Division

Think of this as the "brain" or headquarters" at the top.

• It is the national authority that receives all disease reports.
• It gives feedback back down to the system.
• It coordinates with everyone for a big-picture response.

🟩 Sentinel Sites

These are selected hospitals or clinics chosen strategically to act as "watchdogs" for disease.

• They are the main reporters - they send data weekly (routine updates) AND immediately (when something urgent happens).
• They report upward to EDCD AND sideways to VBDRTC.
• They also receive feedback from EDCD so they know what is happening nationally.

🟩 VBDRTC - Vector Borne Disease Response and Training Centre

Think of this as a specialist expert center - focused specifically on diseases spread by mosquitoes, flies, etc. (malaria, dengue, etc.)

• It receives weekly and immediate reports from Sentinel Sites.
• It has two-way coordination with EDCD - meaning they talk back and forth to plan responses together.

🟧 Health Office (RRT) - Rapid Response Team

This is the local action team - the people who physically go out to investigate and respond when an alert is raised.

• RRT = Rapid Response Team - they move fast when an outbreak is suspected.
• They coordinate with the Health Directorate above them and the local facilities below them.
• They receive referrals of suspected cases from local facilities.

🟧 Health Directorate

The district/regional administrative body - a middle manager between the Health Office and the Sentinel Sites.

• Has two-way coordination with the Health Office (RRT) for verification and response.

🟧 Local Health Facilities

The ground-level clinics and health posts where patients actually show up.

• These are the first to notice something unusual (a spike in fever cases, diarrhea, rash, etc.)
• They send informal outbreak notifications upward to the Health Office (RRT).
• They refer suspected cases to higher facilities for investigation.

🟧 Local Level (Urban/Rural Municipalities)

The community and local government level - villages, towns.

• Communities can also notice and informally report unusual health events.
• They too send informal outbreak notifications to the Health Office.

How the System Works - Step by Step

STEP 1 - DETECTION (Bottom of diagram)
A local health facility or a village notices unusual cases.
        ↓
STEP 2 - INFORMAL NOTIFICATION (Dashed arrows going up)
The local facility sends an informal notification to the
Health Office (RRT) saying "something unusual is happening here."
        ↓
STEP 3 - VERIFICATION (Two-way coordination arrows)
The Health Office (RRT) coordinates back and forth with the
Health Directorate to verify: Is this a real outbreak?
How many cases? Where?
        ↓
STEP 4 - FORMAL REPORTING (Solid arrows going up)
Sentinel Sites send official weekly reports AND immediate
alerts to EDCD and VBDRTC at the top.
        ↓
STEP 5 - RESPONSE COORDINATION
EDCD and VBDRTC coordinate with each other (two-way).
They send back feedback and directives downward (dotted arrows).
The RRT is activated and goes to the field.
        ↓
STEP 6 - REFERRAL OF CASES (Double solid arrows on left)
Suspected serious cases are referred upward from local
facilities to higher-level sentinel sites for proper diagnosis.

Understanding the Arrows

The Big Picture - In One Paragraph

Local clinics and communities at the bottom notice unusual illness and informally alert the local Health Office (Rapid Response Team). The RRT investigates and coordinates with health directorates. Meanwhile, Sentinel Sites - the system's official eyes - formally report data weekly and immediately to two national bodies: EDCD (the overall brain) and VBDRTC (the specialist vector disease center). These top-level bodies coordinate with each other, give feedback down the chain, and activate a response. Suspected cases are physically referred upward through the system for proper testing and management.

Why This Structure Works

• Speed - informal community notifications reach the RRT quickly without waiting for paperwork.
• Two-way flow - information does not just go up; feedback, guidance, and supplies come back down.
• Multiple entry points - outbreaks can be spotted at the local facility level OR the community level OR through sentinel surveillance - reducing the chance of missing something.
• Specialist involvement - VBDRTC ensures that vector-borne disease outbreaks get expert attention immediately.
• Accountability - each arrow represents a defined responsibility, so no one can say "we didn't know."

Salient Features of HMIS (Health Management Information System)

What is HMIS?

Think of HMIS as the nervous system of a country's healthcare - it collects signals (data) from every health facility, processes them, and helps the "brain" (health administrators) make informed decisions.

• Source: NHSRC India / WHO

Salient Features of HMIS

1. Comprehensive Data Collection

• HMIS captures data across all levels of the health system - sub-centers, PHCs (Primary Health Centres), CHCs (Community Health Centres), district hospitals, and tertiary institutions.
• In India, HMIS captures 300+ data items under Service Delivery and 400+ data items under Infrastructure and Human Resources on a monthly basis.
• Data categories include:
  • Reproductive, Maternal, Neonatal, Child and Adolescent Health (RMNCH+A)
  • Immunization, Family Planning
  • Vector-borne diseases (malaria, dengue)
  • Tuberculosis
  • Morbidity and Mortality
  • OPD/IPD services, Surgeries
  • Infrastructure: buildings, equipment, drugs, staff
• Source: HMIS India 2020

2. Multi-Level Hierarchical Data Flow

Sub-Centre (SC)
      ↓
Primary Health Centre (PHC)  ←→ Block Level
      ↓
Community Health Centre (CHC)
      ↓
District Headquarters (DPMU - District Programme Management Unit)
      ↓
State Headquarters
      ↓
National Level (Web Portal)
      ↑
   Feedback flows back down at each level

• Each level aggregates data from below and reports upward.
• Facility-level reporting allows identification of underperforming facilities, coverage gaps, and data quality issues - which is not possible with consolidated district-level reporting alone.
• Source: NHSRC India

3. Standardized Reporting Formats

• HMIS uses uniform, pre-defined reporting formats across all facilities and states.
• This ensures data from different geographic areas and administrative levels can be compared, aggregated, and analyzed meaningfully.
• Standardization prevents inconsistency and allows national benchmarking.
• In India, every sub-center and health facility compiles service delivery details as aggregate numbers that are entered into standardized formats.

4. Regular and Timely Reporting (Periodicity)

• Reporting occurs at fixed intervals:
  • Monthly - routine service delivery data (OPD, ANC, deliveries, immunization)
  • Quarterly - specific indicators (PNC rates, anaemia detection, etc.)
  • Annual/Semi-annual - infrastructure, human resources, outcome indicators
• Timeliness is a core principle - delayed data means delayed decisions.

  Example: If 5 out of 10 sub-centres fail to submit monthly reports on time, the Medical Officer cannot assess PHC performance or plan effectively.

5. Indicator-Based Monitoring System

• Indicators alert managers to problems, but must be compared over time and across facilities to reveal trends - a single isolated number means little.
• Source: NHSRC India

6. Dashboard and Score Card System

• HMIS powers a Health Management Dashboard for real-time visual monitoring of key indicators at national, state, and district levels.
• In India (NRHM/NHM), a Score Card system based on HMIS data rates states/districts:
  • Indicators based on a life-cycle approach (newborn → child → adolescent → pregnant woman)
  • States scored +1 to +4 (above national average) or -1 to -4 (below average)
  • States classified into four performance categories
• This creates accountability and motivates performance improvement. - Park's Textbook of Preventive and Social Medicine

7. Data Quality Assurance

• Validation rules - logical checks prevent impossible entries

  e.g., "ANC registrations in 1st trimester cannot exceed total ANC registrations"

• Completeness checks - tracking how many facilities submitted reports out of total facilities
• Timeliness monitoring - checking whether reports were submitted on time
• Random field verification - periodic cross-checks of HMIS data against physical registers at facility level
• Data Quality Review (DQR) Toolkit - WHO-supported tool for comprehensive HMIS data quality audits
• Source: NHSRC India / Global Health Data Methods

8. Web-Based National Portal

• In India, HMIS operates through a centralized national web portal where district-level aggregated data is uploaded monthly.
• This creates a central repository of health information from all public health facilities across the country.
• Accessible to planners, programme managers, and researchers.
• Enables real-time monitoring from any location.
• Data is updated monthly without interruption - a key achievement since the NRHM reform.

9. Programme-Specific Integration

10. Supports Evidence-Based Decision Making at All Levels

11. Feedback Mechanism

• HMIS is not just a one-way upward reporting chain.
• Feedback flows downward from national → state → district → facility.
• Feedback includes: performance analysis, benchmarks, problem areas identified, corrective actions suggested.
• This makes HMIS a two-way communication tool, not just a data submission system.

12. Facilitates Planning and Resource Allocation

• HMIS data is used for:
  • District Health Action Plans (DHAP) - planning based on local data
  • Budget allocation - directing funds to underperforming areas
  • Human resource deployment - posting staff where gaps exist
  • Procurement planning - medicines, equipment based on caseload data
  • Identifying underserved populations - through facility-wise coverage data

13. Interoperability and Scalability

• Modern HMIS (like DHIS2 used globally) is interoperable with other systems:
  • EWARS (outbreak surveillance)
  • Laboratory information systems
  • Community health worker tracking systems
  • Telemedicine platforms
• Fully customizable to align with national reporting structures, disease priorities, and local administrative units.
• Can scale from small districts to entire nations.

Summary Table of Salient Features

One-Line Definition to Remember

HMIS = The system that turns raw health data from every clinic in the country into actionable information for managers to improve healthcare delivery.

Salient Features of HMIS in Nepal

Background: Why Was HMIS Established in Nepal?

• Lack of uniformity and standardization
• Duplication of effort and data
• Need for more resources
• Collection of unnecessary information
• Inability to compare or combine data across programs

Definition of HMIS in Nepal

Nepal's HMIS is an organized system of collecting, storing, processing, recording, reporting, and providing feedback of health information from grassroots service delivery points up to the central level - to assist monitoring, evaluation, and policy formulation.

Administrative Structure

Salient Features of Nepal's HMIS

1. Integration of Vertical Programs (Core Feature)

• Nepal's HMIS replaced fragmented, program-specific reporting with a single unified system.
• All major health programs report through the same platform:
  • Reproductive, Maternal, Neonatal, Child and Adolescent Health (RMNCH+A)
  • Immunization and Family Planning
  • Vector-borne diseases (malaria, dengue, kala-azar)
  • Tuberculosis, Leprosy, HIV/AIDS
  • Non-communicable diseases (hypertension, diabetes)
  • Emergency obstetric care (Aama Programme, CB-NCP)
  • OPD/IPD, surgery, and inpatient services
• Key reform feature: Integration of vertical reporting systems such as EOC, Aama, CB-NCP, TB, HIV into one reporting format.

2. Hierarchical Multi-Level Data Flow

Health Post / Sub-Health Post / PHCC / Hospital
(Primary recording into registers)
          ↓ Monthly
Palika (Local Government - Ward / Municipality)
          ↓
District Health Office / DPHO (Data entry, aggregation)
          ↓
Province Health Directorate (7 Provinces)
          ↓
Department of Health Services (DoHS) - National Level
          ↓
MoHP → Annual Report (Published)
          ↑
     Feedback flows back down at each level

• Palika-level data management is a key feature added after Nepal's federalization in 2017 - local governments now play a central role in data collection and use.
• The district office maintains copies of all facility reports (at least 10 months out of 12).

3. Standardized Recording and Reporting Forms

• HMIS uses standardized recording registers and reporting formats across all public health facilities in Nepal.
• Forms are designed and distributed by the Management Division, DoHS.
• Key standardized forms include:
  • Outpatient register (OPD)
  • Inpatient register (IPD)
  • Antenatal care (ANC) register
  • Delivery register
  • Immunization register
  • Family planning register
  • Disease surveillance register
  • Monthly reporting forms (aggregated and sent upward)
• These forms use ICD-10 codes for inpatient diagnoses at hospital level.

4. DHIS2 as the Electronic Platform (Since 2016)

• Nepal introduced DHIS2 (District Health Information Software 2) nationally in 2016 as the electronic platform for HMIS data management.
• DHIS2 is a free, open-source software used in 100+ countries worldwide, maintained by the University of Oslo.
• Key capabilities of DHIS2 in Nepal:
  • Web-based data entry accessible from any location
  • Offline data entry with synchronization when internet is available
  • Automated data validation rules
  • Real-time dashboards, charts, maps (GIS), pivot tables
  • Data disaggregation by caste/ethnicity, age, sex
  • API-based interoperability with other systems (TB, HIV, EWARS, LMIS)
  • Accessible to federal, provincial, and local level managers
• Source: MoHP Nepal / PLOS ONE study

5. Disaggregation by Caste/Ethnicity and Geography

• A landmark feature of Nepal's revised HMIS is that selected indicators can be disaggregated by caste/ethnicity - enabling monitoring of health equity and identifying marginalized groups.
• Data is also disaggregated by:
  • Sex (male/female)
  • Age groups
  • Geographic area (urban/rural, province, district, Palika)
  • Facility type (health post, PHCC, district hospital, zonal hospital)
• This supports Nepal's constitutional commitment to equitable health service delivery.

6. Facility-Level Reporting

• Unlike older systems that only captured district-level consolidated data, Nepal's reformed HMIS enables facility-wise data reporting.
• Benefits of facility-level reporting:
  • Identifies which specific facility has low or high coverage
  • Pinpoints underserved populations geographically
  • Monitors which facilities report on time (timeliness tracking)
  • Allows data quality probing at the facility level
  • Enables performance comparison between facilities

7. Regular and Periodic Reporting Cycle

• The DoHS publishes the Annual Report of the Department of Health Services - Nepal's most important health data publication - entirely based on HMIS data.
• Reporting from the public sector is over 95%; however, only about 49% of the private sector is captured in the annual health report. - KUMJ Study

8. Coverage of Health Facilities

• Source: WHO HIS Evaluation Nepal

9. Nine Routine Information Systems (HMIS is One of Nine)

1. HMIS (Health Management Information System) - service statistics
2. LMIS (Logistics Management Information System) - medicines and supplies
3. HURIS (Human Resources Management Information System) - staff data
4. HIIS (Health Infrastructure Information System) - buildings and equipment
5. IMIS (Insurance Management Information System) - health insurance
6. Vital Registration / CRVS (Civil Registration and Vital Statistics)
7. Disease Surveillance Systems (EDCD / EWARS)
8. Hospital Management Information Systems (individual hospitals)
9. Community-level health worker tracking systems (e.g., FCHV data)

10. Indicator-Based Performance Monitoring

• ANC 4+ visit rate, institutional delivery rate, PNC coverage
• Full immunization coverage, BCG/MR1 dropout rates
• Contraceptive prevalence rate
• ORS/Zinc use in diarrhea, IMCI coverage
• Bed occupancy rate, average length of stay
• TB treatment success rate, PMTCT coverage

11. Data Quality Assurance Mechanisms

• Validation rules in DHIS2 - logical error checks (e.g., ANC 4+ visits cannot exceed ANC 1st visit registrations)
• Routine Data Quality Assessment (RDQA) system at facility and Palika level
• Annual sample surveys - recorded data vs. reported data cross-checked at each level
• Field verification - random checks of HMIS data against physical registers
• Reporting completeness monitoring - tracking % of facilities that submitted reports
• Timeliness monitoring - tracking submission deadlines
• Data Quality Sweeps - daily monitoring introduced during COVID-19 response

12. Feedback Mechanism

• Feedback is provided from the central/district level back down to health facilities - a two-way information flow.
• Feedback includes: performance analysis, benchmarks, problem identification, and corrective action guidance.
• SMS and digital notifications alert facilities about missing or overdue reports.
• Monthly review meetings at PHC and district level use HMIS data for performance review and planning.

13. Annual Report Publication

• Nepal's DoHS Annual Report is the flagship publication produced from HMIS data.
• Published every year covering:
  • Service delivery statistics by programme
  • Coverage indicators by province and district
  • Disease-wise morbidity and mortality data
  • Infrastructure and human resource data
  • Progress toward national health targets (NHSS, SDGs)
• It is the primary reference for Nepal's health policymakers, planners, researchers, and development partners.

14. Federal Structure Adaptation (Post-2017)

• HMIS was restructured to align with the new governance structure
• Palikas now collect reports from health facilities within their jurisdiction, keep a copy, and forward to DHO/DPHO
• Provincial Health Directorates manage province-level data
• Data management responsibilities were clarified across three levels
• A web-based Master Health Facility Registry with unique IDs for each facility was developed to support local government registration

15. Integration with Other Systems

Summary of Salient Features at a Glance

In one sentence: Nepal's HMIS is a federally structured, DHIS2-powered, integrated health data system managed by the Management Division of DoHS that collects routine health service data from over 5,500 facilities, flows it through Palika → District → Province → National levels, and produces the Annual DoHS Report used for evidence-based health planning and policymaking.