Open MRS: Components and Connections to Integrated Health Information Systems

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Open MRS Components and Connections to
Integrated Health Information Systems

• Christopher BaileyChristopher SeebregtsHamish
  Fraser

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Rwinkwavu hospital, Rwanda
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OpenMRSOpen Medical Record System

• Developed by a collaboration between the
  Regenstrief Institute, Partners In Health, the
  South African Medical Research Council, and the
  Millennium Villages project
• Open source
• Web-based, but can also be run locally
• Designed simplifies adding new functionality
• Supports open standards for data exchange
• Uses concept dictionary for data storage
• Allows local users to create EMR forms and
  reports
• Can be downloaded for free at www.openmrs.org

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OpenMRS Sites

• 9 countries so far
• Kenya (REG)
• Rwanda (PIH)
• South Africa (MRC)
• Tanzania
• Uganda (REG)
• Haiti
• Zimbabwe (MRC)
• Malawi (PIH)
• Lesotho (PIH)
• In process
• Peru, Mozambique, India, Pakistan and others we
  may not know about

Lesotho
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Stages in creation of generalizable framework for
patient level data

• Vertical stovepipe system for one disease e.g.
  HIV/AIDS in one site (Epinfo TB system SA, Access
  based systems)
• Vertical system accessible over multiple sites
  (PIH-EMR, Peru, ETR.Net, SA, Careware)
• General purpose EMR architecture supporting
  multiple diseases and work flows (OpenMRS,
  OpenEHR)
• EMR systems supporting interoperability
• with other clinical care components (LIMS,
  pharmacy etc.)
• with national reporting systems (DHIS, CRIS,
  TRACnet)

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Integrated hospital information system
National reporting system DHIS, ETR.Net? CRIS,
TRACnet
Example systems in italics
IXF
EMR SystemOpenMRS
Pharmacy system PIH, MSH Brazil
Laboratory System OpenELIS
HL7
HL7
Dicom
HL7
HL7
HL7
Patient registration and tracking
Mobile health systemsOpenROSA
Radiology information system
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Integration of Patient and Public Health
DataExample South Africa

• TB managed at (sub)district or provincial level
  according to a public health model using
  registers.
• HIV/ART managed at an individual level according
  to a chronic care model using structured medical
  record forms.
• District Health Information System collects
  aggregate data on many diseases

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Export to District Health Information Systems
(DHIS)
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Integration of OpenMRS with ETR.Net for TB
OpenMRS-MDR-TB
ETR.Net
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Pharmacy system ltgt EMR interoperability

• Requirements
• What is the essential core functionality?
• In which system should particular functionality
  be supported?
• Define the data items that must be supported in
  both systems
• Define the interactions that need to occur
• What standard should be used for data exchange?
• How will the system function when the network is
  down

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Outline of interactions for pharmacy system and
EMR
Health facility
Reporting system
Pharmacy
Quantify/Analysis Reporting
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OASIS(Open Architecture, Standards and
Information Systems)?
Laboratory professionals community
Laboratory systems
Developer and Implementer Communities
(e.g. diagnostic and testing equipment)?
EMR systems
Pharmacy professionals community
Pharmacy
(clinical records, admissions, scheduling, etc.)?
(e.g. stock management and procurement)?
Other Domains
Collaboration between domain-specific networks of
people as an approach to implementing standards
for data exchange and ensuring semantic
interoperability. Based on the OpenMRS model.
(e.g. imaging)?
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Next steps

• Documentation of interactions necessary between
  systems
• Focus on the need for new systems to support
  basic interoperability standards
• Create reference implementations showing
  interoperability
• Data model/data dictionary standardization to
  ease exchange of core data
• Open processes for design and coding of systems
  especially APIs

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Funders and Collaborators

• Centers for Disease Control Bill Coggin,
  Subroto Banerji
• Dept of Health (KZN) Chris Jack, Roger Pillay
• Dept of Health (National) Carina Idema, Shaheen
  Khotu
• Foundation for Professional Development Margot
  Uys
• Google Inc
• Health Information Systems Program Calle
  Hedberg, Jorn Braa
• International Development Research Centre
  Heloise Emdon, Steve Song
• Medical Research Council Karin Weyer, Natasha
  Naidoo
• Harvard Medical School and Partners in Health
  Hamish Fraser
• Regenstrief institute Burke Mamlin, Paul
  Biondich, Bill Tierney
• University of KwaZulu-Natal Yashik Singh, Carl
  Fourie
• University of the Western Cape Harry Haussler
• WAM Technology cc Paul Maree
• World Health Organisation Christopher Bailey,
  Mark Spohr

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What is wrong with business as usual?

• The default approach re-implement small vertical
  systems that support one project and one disease
• Results in constant re-invention of the wheel and
  loss of previous experience and fine tuning of
  systems
• Technologies chosen are typically quick to
  implement, not designed to scale
• Existing general purpose EMR systems tend to be
  large, expensive and difficult to implement
• How do we build on existing systems and
  experience while encouraging innovation?