Biometric.md

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-# Biometric Attendance System in Health Sector of Bangladesh
-
-## Background
-
-In remote areas of Bangladesh, absenteeism among health service providers at hospitals and health centers was a significant issue. This challenge is common not only in Bangladesh but also in many other countries. To address this, the Management Information System (MIS) under the Directorate General of Health Services (DGHS) introduced biometric time-attendance systems to track office attendance of government health staff at workplaces.
-
-## Implementation of Biometric Attendance System
-
-### Phase 1: Fingerprint Biometric Machines
-- **Installation Timeline:** 
-  - Introduced in 2012 and gradually expanded.
-  - Covered all Upazila Health Complexes (UHCs) and District Hospitals (DHs) in phases.
-- **Technical Details:**
-  - Low-cost fingerprint biometric devices.
-  - Each device can store up to 30,000 touch encounters.
-- **Operational Mechanism:**
-  - Staff fingerprints are registered during installation.
-  - Daily attendance is recorded through touch-based fingerprint scanning.
-  - Attendance data is captured by a central server at MIS-DGHS whenever local computers are connected to the Internet.
-  - Web-based attendance reports can be accessed remotely.
-
-### Performance Metrics
-- **Statistics:**
-  - In 2015: 423 active devices with 38.21% attendance.
-  - In 2016: 457 active devices with 51.05% attendance.
-  - In 2017: 476 active devices with 74.59% attendance.
-- **Impact:**
-  - Attendance rates increased by 36.38% from 2013 to 2017.
-- **Pre-COVID-19 Period (Till August-September 2023):**
-  - Attendance rate reached 92% with data from 600 active devices.
-
-### Impact of COVID-19
-- **Pandemic Disruption:** 
-  - Biometric attendance machines were shut down from 2019 to 2021.
-
-### Phase 2: Face Recognition System
-- **Introduction:** 
-  - Implemented from September 2023.
-- **Upgrades:**
-  - Face recognition technology replaced fingerprint systems.
-  - Devices are now required to remain online, connecting directly to the central MIS-DGHS server.
-  - Attendance confirmation is based on face recognition linked to the HRM ID of employees.
-  - Face ID registration occurs once per organization, and updates (e.g., transfers) are synchronized automatically.
-- **Features:**
-  - Supports outsourced employees and simplifies processes for reporting, leave management, scheduling, and activation/inactivation.
-  - Centralized server manages real-time data and reporting.
-
-## Coverage
-As of the latest update, the attendance system connects:
-- **Institutions:**
-  - Divisional Health Offices: 8
-  - Sadar Upazila Health Offices: 60
-  - District Health Offices: 63
-  - Chest Hospitals: 11
-  - Chest Clinics: 41
-  - Former UHCs, Sadar/District Hospitals, Specialized Hospitals, Medical Colleges, and Medical College Hospitals.
-- **Total Coverage:** 787 institutions.
-
-## Current Status
-The upgraded system has enhanced operational efficiency and attendance monitoring in government health facilities across the country. Regular attendance data is now being received from all connected institutions, ensuring better accountability and service delivery.
-
----
-
-This article provides an overview of the biometric attendance system implemented by MIS-DGHS to improve attendance tracking in the health sector of Bangladesh. For further queries, please contact the MIS-DGHS support team.

HID.md

@@ -32,7 +32,7 @@ The Health ID system offers multiple convenient ways for citizens to register, e
         
 3.  **Online Portal:**
     
-    *   An **online portal** (https://eappointment.dghs.gov.bd) allows citizens to obtain a health ID by providing their NID or birth registration number. In selected pilot areas, from this portal, anyone can book appointments for outdoor services. However, getting an online appointment for outdoor services is limited to only piloting areas. This convenient feature enables access to health services even before visiting a healthcare facility and allows patients to obtain their own Health ID from home. Even if a person is out-of-country or abroad, they can also obtain a Health ID from this online portal.
+    *   In selected pilot areas, an **online portal** (https://eappointment.dghs.gov.bd) allows citizens to book appointments for outdoor services. From this portal, anyone can get a health ID by providing their NID or birth registration number. However, getting an online appointment for outdoor services is limited to only piloting areas. This convenient feature enables access to health services even before visiting a healthcare facility and allows patients to obtain their own Health ID from home. Even if a person is out-of-country or abroad, they can also obtain a Health ID from this online portal.
 
 ---
 
@@ -72,4 +72,8 @@ The progress of Health ID distribution is monitored through a **real-time dashbo
 ---
 
 **Conclusion**
-The Health ID system marks a significant step in Bangladesh's journey toward a **digitally empowered healthcare system**. By ensuring universal health coverage, preventing duplication, and enabling seamless data exchange, the Health ID enhances the efficiency and effectiveness of health services. With multiple registration pathways and real-time monitoring, the initiative is poised to transform healthcare delivery for millions of citizens.
+The Health ID system marks a significant step in Bangladesh's journey toward a **digitally empowered healthcare system**. By ensuring universal health coverage, preventing duplication, and enabling seamless data exchange, the Health ID enhances the efficiency and effectiveness of health services. With multiple registration pathways and real-time monitoring, the initiative is poised to transform healthcare delivery for millions of citizens.
+
+---
+
+Would you like any further modifications or additional details?

ICD11.md

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-# Bangladesh's Transition from ICD-10 to ICD-11: A Journey Towards Modernized Health Coding
-
-## Introduction
-
-In late 2023, Bangladesh started the journey of transitioning from ICD-10 to ICD-11, aiming to modernize its health information system and improve disease classification and reporting. As part of this transition, a pilot phase was initiated in six hospitals, employing two different approaches for ICD-11 integration based on the existing digital infrastructure.
-
-## The Pilot Phase: Implementing ICD-11 in Six Hospitals
-
-To assess the feasibility and effectiveness of ICD-11, six hospitals were selected for piloting, categorized based on their health information systems:
-
-### 1. OpenMRS-Based Hospitals (WHO ICD-11 API Integration)
-
-Three district hospitals leveraged OpenMRS, integrated with the WHO ICD-11 API to facilitate morbidity (OPD, emergency) and mortality (MCCoD) coding. The hospitals included:
-
-- **Cumilla District Hospital**
-- **Nilphamari District Hospital**
-- **Barguna District Hospital**
-
-This integration enabled structured coding of patient diagnoses and causes of death.
-
-### 2. DHIS2-Based Hospitals (ICD-11 Codes in Dropdowns)
-
-Three other hospitals incorporated ICD-11 into the existing DHIS2 platform by manually adding ICD-11 codes into dropdown menus. These hospitals were:
-
-- **Cox’s Bazar District Hospital**
-- **Khulna Medical College Hospital**
-- **Rajshahi Medical College Hospital**
-
-Bangladesh initially planned for an integrated morbidity and mortality tracker within DHIS2. While WHO had already developed a customized ICD-11 application for MCCOD (Medical Certification of Cause of Death), there was no equivalent app available for morbidity coding at the time of piloting. As a result, ICD-11 morbidity and mortality coding had to be manually incorporated using dropdown menus. Bangladesh continued using this approach to maintain consistency while simultaneously requesting WHO to develop a customized morbidity app to enable full ICD-11 integration within DHIS2.
-
-## Challenges Encountered During the Pilot Phase
-
-### 1. Challenges in OpenMRS Implementation
-
-- **Limited Scope of ICD-11 Usage:** The inpatient module of OpenMRS is still under development. Consequently, ICD-11 could only be utilized in outpatient departments (OPD), emergency departments, and for MCCOD.
-- **Data Remains Locally Stored:** The lack of centralized synchronization meant that hospitals using OpenMRS continued entering routine health information into DHIS2, leading to a double workload.
-- **Limited Use of Postcoordination:** Findings from the pilot phase indicated very little usage of postcoordination in OpenMRS-based piloting areas, suggesting the need for further training and system improvements.
-- **Initial Absence of Foundation URI Storage:** Initially, only ICD-11 codes were stored, without keeping the `foundationUri`. Later, it was realized that storing `foundationUri` is essential for usability and data analysis. As a result, this functionality was added to the backend.
-
-### 2. Challenges in DHIS2 Implementation
-
-- **Dropdown Limitations:** Since DHIS2 lacked a built-in API connection for ICD-11, the dropdown approach was used. However, ICD-11 is not designed to function as a dropdown-based classification, making data entry cumbersome and inefficient.
-- **Dual Data Entry Burden:** As Bangladesh’s national health statistics are still produced using ICD-10, hospitals using ICD-11 in DHIS2 were also required to enter the same data in ICD-10. This double data entry requirement led to frustration among healthcare workers, resulting in low motivation to input ICD-11 data.
-- **Future System Constraints:** Given that ICD-11 was not intended to be used as dropdown selections, it became evident that long-term implementation should focus on full-fledged hospital automation rather than manual input into DHIS2.
-
-### 3. Inconsistent MCCOD Data Entry
-
-In Bangladesh, routine health information system (HIS) data is formulated by a statistician, while MCCOD data entry is performed by a nurse from the inpatient department. Regardless of the HIS platform (OpenMRS or DHIS2), nurses had to enter the same data twice. This redundancy led to minimal data entry for MCCOD. However, OPD and emergency departments performed well because physicians use the automation system in real time, eliminating redundant data entry and additional workload for them.
-
-## Lessons Learned and Next Steps
-
-The pilot phase provided crucial insights into the strengths and limitations of ICD-11 integration in Bangladesh’s healthcare system. The key takeaways shaped the country’s next phase of implementation.
-
-### 1. Establishing a Central Terminology Registry
-
-Bangladesh is in the process of formulating a **Central Terminology Registry**, which will adopt ICD-11 for coding symptoms, signs, diagnoses, and medications. This initiative paves the way for nationwide expansion of ICD-11 implementation in hospitals equipped with automation systems.
-
-#### Why ICD-11 for the Terminology Registry?
-
-- **Free of Cost** – No licensing fees are required, making it a cost-effective solution.
-- **Global Community Support** – ICD-11 is backed by a robust global community, ensuring continuous updates and improvements.
-- **Ready Technology** – WHO has provided APIs and tools that facilitate seamless integration with existing health information systems.
-
-### 2. Switching to Localized ICD-11 Deployment
-
-Initially, ICD-11 was deployed using the WHO ICD-11 API. However, Bangladesh is now transitioning to a **localized Docker container deployment**. This shift significantly reduces dependency on internet connectivity, ensuring a more stable and efficient system for hospitals, especially in remote areas.
-
-### 3. Scaling Up ICD-11 to 150 Hospitals
-
-Building on the lessons from the pilot phase, Bangladesh plans to **expand ICD-11 implementation to 150 hospitals** that have hospital automation systems. This expansion will facilitate the integration of ICD-11 data directly into a central shareable health record repository, eliminating the need for duplicate data entry into DHIS2.
-
-### 4. Future of DHIS2 and ICD-11 Integration
-
-- **MCCOD Application Adoption:** In DHIS2, the WHO MCCOD app with ICD-11 API will be adopted for mortality coding.
-- **Exploring Custom Morbidity Apps:** If a customized app for morbidity coding with ICD-11 API becomes available, Bangladesh will integrate it into DHIS2. Otherwise, ICD-10 will continue to be used for morbidity coding, but a **mapping system** will be developed to transition ICD-10 data into ICD-11 over time.
-
-### 5. Capacity Building for ICD-11 Data Analysis
-
-Bangladesh recognizes the need for **capacity building** in analyzing data coded with ICD-11. Training healthcare professionals and statisticians in **interpreting and utilizing ICD-11-coded data** effectively will be essential for decision-making and policy development.
-
-### 6. Gradual Phase-Out of DHIS2 for Hospital-Based Coding
-
-Over time, as hospital automation systems expand, **ICD-11 data will be directly recorded in these systems**. DHIS2 will gradually be phased out for individual patient coding but will continue to serve **program-specific purposes and aggregate data collection** at the national level.
-
-## Conclusion
-
-Bangladesh’s transition from ICD-10 to ICD-11 represents a **significant leap** in modernizing the country’s health information system. While the pilot phase revealed implementation challenges, it also provided a roadmap for future scaling. By addressing **data synchronization issues, reducing dependency on internet-based APIs, eliminating redundant data entry, and strengthening capacity building** for ICD-11 data analysis, Bangladesh aims to **enhance healthcare coding efficiency, improve statistical accuracy, and align with global health standards** for morbidity and mortality reporting.
-