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PREPARED BY ISTRATEGY LTD.
WITH SUPPORT FROMBANGLADESH ENTERPRISE INSTITUTE
(BEI)
SPONSORED BYROCKEFELLER FOUNDATION
Preliminary Findings of Study on
“Policy issues fore-Health in Bangladesh”
Background
iStrategy and BEI were given the task to conduct the following: Critical analysis of the current e-Health and HIS
scenario in Bangladesh Identify policy-level issues that need prioritization
This presentation is based on some results of that study
Agenda
Proposing realistic goals for HIS and e-Health in Bangladesh
Policy issues that need to be addressed for attaining those goals in the context of local realities and global experiences
A proposed phase-wise approach towards those goals
Purpose
Incite discussions and debates – not to suggest that there is only one way of looking at things
Part of an on-going exercise to bring out the policy issues that need attention
Setting Goals for Stronger HIS
Moving gradually from “integrated” system thinking to “inter-operable” system thinking
Moving gradually from aggregated data to individual-based data in electronic form
Using open standards to avoid lock-in and keeping flexibility for customization as needed
Focusing on “requirements specifications” and design before developing information systems
1. Managing Identities
Managing Identities
The fundamental pre-requisite of a health system
Issues for MoHFW: Health Service Provider Identity
Organization Individual Service
System user’s ID Patient ID
Inter-ministerial issue: Geo Location Code: Address and location
Managing IDs – Current Status
Unique universally accepted IDs for: BMDC registration no for Physicians Drug License Hospital License Medical College License License for nurses
Issues that we don’t have unique IDs across systems for are: Service ID Health Indicators ID Diseases ID Patient ID System User’s ID Risk factors ID
Potential Consequences of not having IDs
Data from different systems cannot be aggregated
Data can never be normalized in a single data dictionary
Data exchange can be very expensive and time consuming
Like developed countries, data can be locked in several silos and never being used across the systems, expensive adaptors are taking place for data interchange
Managing IDs – global example
Australian ID standardization
Implementation Issues
Unique ID system for every patient in the context of Bangladesh is a huge challenge and will take time to be developed
However, many of the other IDs are more doable and can provide a basic platform for taking HIS to next level
Short to medium term: IDs for health-service providers – individual and
organizational, services, geo-locations
Long term: Patient ID
2. Privacy and Confidentiality
Privacy and Confidentiality
Setting rules for ‘governance of data’ is absolutely critical for designing an HIS Who owns data? Who has access to what data?
Specially important for public-private collaborations and data sharing
Consent of the patient regarding use of data
Privacy and confidentiality – current status
In practice, patient-doctor confidentiality is maintained by doctor himself
Scope for improvement in the Privacy Act in Bangladesh being made more relevant for medical field
No rules yet for ownership and access of data
Potential consequences of not having privacy and confidentiality rules
Critical to designing of health systems Defining the role of each user of the system Defining access control Designing security standards
Without these, system development can be haphazard and adhoc – leading to expensive upgrades and changes later on
Citizens will not be comfortable in letting their data to be digitized
Privacy and Confidentiality: global scenario
Every e-Health policy and guideline has privacy and confidentiality Example: HIPAA (Health Insurance Portability and
Accountability Act) provides federal protections for personal health
information held by different entities gives patients an array of rights with respect to that
information.
Privacy and Confidentiality - Implementation Issues
We need to distinguish between individual and aggregated data since the former is much more sensitive
We can start with issues around aggregated data first
Short-to-Medium Term: Regulations may be passed by the government regarding:
Ownership of health data Access rights of health data Security standards that need to be maintained by health
systems
Long Term: Deal with sharing of individual-level data Patient’s consent
Reporting Standardization
Reporting Standardization
National Level Reporting Governmental organizations reporting to higher
authority NGOs and private health-facilities reporting to the
government
International Level Reporting WHO Health-related donors
Reporting Standardization – current status
National-level reporting: Within MoHFW
Some standards such as those proposed by HMN, UN and Paris 21 declaration are used
However, standards that can be used across systems are yet to be defined
Collected manually, aggregated and sent through Excel spreadsheets Entered in DHIS from different districts Some of the comments that have come from the workshops:
Duplication in report generation Aggregation across departments is often not possible For many organizations, there is no reporting software – it is done
manually and the results entered in Excel formats Inter-ministry
Adhoc as needed NGO/private sector reporting to MoHFW
Adhoc as needed International reporting:
According to requirements of individual donors Varies from project to project Significant scope for standardization across projects
Potential consequences of not standardizing reports
Aggregation is not easily possible For instance: Very difficult to track MDG goals
effectively at national level
Costly and time consumingExpensive adapters and mapping
mechanisms may be required for aggregation
Reporting standardization – global practices
WHO Indicator and Measurement Registry (IMR) Central source of metadata of health-related indicators
used by WHO and other organizations It promotes interoperability through the SDMX-HD
indicator exchange format
4. Enabling Standardized Data Entry
Enabling standardized data entry
Standardized entry of diseases, signs and symptoms
Standardized entry of patient data at: Facility-level Community-level
Enabling standardized data entry – current status
Public sector Facility-level:
Aggregated data from record rooms at some hospitals are digitized and sent through Excel sheets or entered in DHIS
DHIS indicators are not standardized across systems but it has provided a solid foundation for further work
Community-level: Data collection is done manually and aggregated manually,
which is digitized at district levelsNGO sector
Each NGO has their own way of inputting data – no standardization
Private sector 2 or 3 top private hospitals are found to be using ICD-10
Enabling standardized data entry: Implementation issues
ICD10 (International Classification of Diseases) Coding of diseases, signs and symptoms, abnormal findings,
complaints, social circumstances and external causes of injury or diseases
SNOMED (Systemized Nomenclature of Medicine) Wider coverage than just diseases, including findings, procedures,
microorganisms, pharmaceuticals etc. Licensing involved Less uptake than ICD10
Short term: Standardized digitization of aggregated data from record rooms at
facilities Standardized digitization of aggregated data coming from community
level Mid-term:
EMR for community level intervention based on remote feedback from doctors
Long term: EMR at hospitals
Enabling standardized data exchange
Enabling standardized data exchange
Data may be entered in numerous ways and we cannot change those, we cannot change legacy systems already in place
What we can do is have a standard for exchanging of data
If the standards for data entry are not followed as discussed earlier, then aggregation will not be possible automatically
Enabling standardized data exchange – current status
Within MoHFW Different projects have their own MIS –no interchange
of data between systems
Between private sector and government Adhoc as needed Some comments from the workshops:
Private sector is willing to send data if there is a specific format for exchange is given to them
Scenario at Public Hospital
Hospital Customized Software IT Team
Dhaka Medical College - -
BSMMU Lab reporting & Accounting 1-2
NITOR n/a 2 and 2 vacancies
Kidney Diseases Hospital n/a 6-10 people
2 vacanciesNICVD
Shaheed Suhrawardy Medical College n/a n/a
National Institute of Mental Health n/a n/a
Sir Salimullah Medical College n/a n/a
NIPSOM n/a n/a
Institute of Public Health Nutrition (IPHN) n/a n/a
EPI n/a n/a
Scenario of selected private hospitals
Hospital Customized Software IT Team
Lab Aid Desktop based, Locally Build, In-House, for the use of HR, Billing, Accounting, Pharmacy, Imaging, Pathological Data, Prescription, Medical Inventory
10
Popular HR- ExcelBilling- System NetworkingEMR- System NetworkingAccounting- ExcelPharmacy-S/NImaging- GEPathological Data- S/NMedical Inventory- S/N
3-5
Central Locally Developed, Desktop Based HR-Bangladesh General Automation, Billing, Accounting , Pharmacy- Bangladesh Southtek
3-5
Samorita HR- local,In house; Billing- Local, In house; EMR- local, in house, Accounting- Foreign, ACCPAC; Pharmacy- local, In house; Pathological- Local, in house; Medical inventory- local, Datasoft System Bd ltd.; Admin & Investigation- local,, in house, all are desktopased
3-5
United HR, billing, EMR, Accountin, Pharmacy, Pathological, Prescription, medical inventory-local, developed by Sycraft Solution ltd.;
6-10
Ibne-Sinha HR, Billing, Accounting, Pharmacy, Imaging, Pathological, Medical Inventory: local, desktop based
14
Apollo HR, Billing, EMR: Foreign made, India Akhil Systems ( Desktop Based) 17
Scenario of Projects Under DGHS
National AIDS/ STD program and safe blood transfusion
- CRIS software (National MIS database system on piloting phase for country wise HIV AIDS activities reporting)
- National MIS on HAIS base DICs for digital reporting of DICs services
Up to 5
Alternative Medical Care n/a n/a
Communicable Disease Control (CDC) n/a n/a
In-service Training TMIS – To maintain training data and to evaluate field workers work Upto 5
Human Resource Management (Health) n/a n/a
Sector –wide program management (Health)
LLP Toolkit Software n/a
TB & Leprosy Control TB Data Management- Use for TB related Data and Generating report
Upto 5
IFM n/a n/a
Quality Assurance FMRS n/a
Micro Nutrient Supplementation n/a n/a
Essential Service Department n/a n/a
Improved Hospital Service Management n/a n/a
Family Planning SMIS 11-15
Scenario of some selected NGOs
Hospital Customized Software IT Team
Marie Stopes Clinical Service Entry, PMIS; SUN Accounting for Accounts 3-5
Friebdship ERP System- HMS, Research Tools, payrolls, leave management, Travel record mgmt, procurement, telemedicine, Microfinance, Accts & finance
6-10
Action Aid HR, IT and Finance 3-5
Helen Keller International Data Collection Software 1-2
National Heart Foundation OPD, Patient admission, cash counter, Bill, All investigation, HRM, Accounts, General/ Medical Store, Cathlab, Pharmacy, Research, Ward/ cabin, website
1-2
Grameen Kalyan Accounting n/a
Sajida Micro Finance Management, Hospital Management, Human Resource Management, Automated Accounting System, Cheque Management, System, Tele medicine system, Fixed Asset Management System
6-10
BRAC Accounting, HR, IT More than 15
Enabling standardized data exchange – implementation issues
SDMX-HD It is not about data
entry or data storage format
SDMX-HD messages are defined for the process of exchanging indicator definitions and aggregate data and metadata
HL7Also a messaging
protocolMuch more extensive
than SDMX-HDCovers
standardization in different workflows in the continuum of care – starting from billing to patient tracking
Country membership based
Enabling standardized data exchange – implementation issues
Short term: Standardizing the format for data exchange with
respect to indicators and IDs Mid to long term:
Standardizing data exchange and inter-operability Standardization for privacy and security during
data exchange and inter-operability
Enabling standardized data exchange – global practices
For individual-level data, HL7 messaging format is often used
For aggregated data, SDMX-HD is being increasingly used because of its simplicity compared to HL7
Use of software that already has SDMX-HD standards: OpenMRS adopted by more than 50 countries
Data Interoperability
Exchange Format Content Format
Individual DataHL7 ICD10/ SNOMED
Aggregated Data SDMX-HD IMR/ ICD10
Going beyond data exchange
Getting data by querying into other information systems
Service Oriented Architecture (SOA) approach
Going beyond data exchange – current status
In the government: SOA-based approach is not prevalent yet
In the private sector: Sporadic instances Example: inter-operability within different systems of
BRAC
Potential consequences of sole dependence on data exchange
It is not feasible for everybody to have every data.
Systems cannot share functionalityRedundant data storageCostlyData integrityNot taking advantage of “starting late”
Proposed Implementation Phases
Phase 1: Building on already developed foundation
Phase 2: Basic Inter-operability Phase 3: Advanced Inter-operability
Phase 1:Building on already developed foundation
Form a high level steering committee for the following: Identity Management of Health Service Providers,
Locations and Services. Role Based Privacy and Confidentiality Rules (like HIPAA). Use a terminology standard ICD10/SNOMED during data
entry before sending to the accumulation point
Implement regulation for Data interchangeDevelop standardized formats for data
interchange Enterprise service bus (developed by A2I)
Phase 2: Basic Inter-operability
Digitization of record room (aggregated data) Implementation of ICD10, SDMX-HD
Major private hospital and major NGOs involved in data interchange according to standardized formats
Shared registry of National level health information (building on NPR)
Implementation of privacy and security guideline (like HIPAA)
First steps towards EMR at health-facilities
Phase 3: Advanced Inter-operability
Identity management of patientsRoll out of EMR at health-facilitiesInteroperability in HIS
SOA based- hub and spoke model ESB based