Notice E0 Phase 1 Shelf Readiness

Notice E for promoting investments in digital health global goods

Advancing OpenELIS Global Shelf-Readiness through Improved Quality Assurance

Two-sentence overview: 

OpenELIS Global aims to improve its Shelf-Readiness through a transition from a manual software release testing model to a robust, comprehensive, and systematic automated testing process that will improve efficiency and reliability, reduce maintenance costs for the software, and facilitate re-use of OpenELIS Global code by community members. This investment will result in: adoption of the OpenHIE testing framework and tooling for automated testing of OpenELIS; collaboration with the OpenHIE Laboratory Information Systems Community of Practice (LIS CoP) to establish re-usable LIS interoperability test cases; and dissemination of LIS/LIMS software testing protocols, guidance, and learning resources which can be adapted by other global goods communities to improve software testing practices. (updated 19 June 2020)

Executive summary: 

OpenELIS Global is recognized as a leading open-source laboratory information system (LIS), which facilitates delivery of accurate and timely laboratory test results and data to healthcare providers, patients, and public health agencies. OpenELIS Global has been used for nearly a decade in Cote d’Ivoire, Haiti, and Vietnam, and as part of the Bahmni HMIS distribution. The government of Mauritius also recently adopted OpenELIS in its national reference laboratory to manage information related to SARS-CoV-2 diagnostics and pandemic response, and is scaling up to their national network of lab testing in the near future. 

The OpenELIS Global team will employ the proposed investment from Digital Square to use the OpenHIE testing framework to develop and implement an automated testing framework for its software development cycle. Moving from manual to automated testing will improve efficiency, lower the cost of maintenance, and most importantly, increase implementer trust in the product. Adoption of a framework will increase the reliability and completeness of software testing. A more robust quality assurance process will help ensure that OpenELIS Global implementers can rely on the software from the moment they download it to the time they deploy it in laboratories.  

The OpenELIS Global team plans to collaborate with the OpenHIE community to incorporate the OpenHIE test management platform and automated test tools into its quality assurance processes, using the OpenMRS quality assurance (QA) automated testing approach as our model. We will collaborate with the OpenHIE Laboratory Information Systems community (LIS CoP) to prioritize and develop LIS interoperability test cases around established LIS interoperability specifications published by the LIS CoP that can be reused by other LIS software in the OpenHIE architecture, specifically in the Instant OpenHIE project.  In addition, I-TECH will leverage its expertise in creating high-quality training curricula to develop a learning session on automated testing for broader global goods consumption, including in the OpenHIE Academy, to aid in disseminating standardized test cases and promoting a shared foundation for quality assurance within the OpenHIE architecture. (Updated 19 June 2020)

Consortium Team: 

The project team is part of the International Training and Education Center for Health (I-TECH) at the University of Washington (UW). I-TECH is a Center within the UW Department of Global Health (DGH) that leads health systems strengthening initiatives in more than 20 countries.  In December 2018, I-TECH launched the Digital Initiatives Group at I-TECH (DIGI), a global health informatics center within I-TECH and the UW DGH, under the leadership of faculty members Nancy Puttkammer and Jan Flowers. The DIGI team brings together experienced I-TECH informatics experts and staff with a broad range of expertise in setting global health informatics standards and leading global goods communities and products at the domain level, as well as, applying those in real-world settings in LMIC in a sustainable, scalable, replicable manner.  In addition to the core team members, our center collaborates and harnesses expertise from faculty, staff, and students from the UW’s Schools and Departments including Health Sciences, Computer Science and Engineering, Bioengineering, Information Sciences, Business and others.  

Related to this proposal, DIGI has been the steward of OpenELIS Global development and national implementations in Haiti and Cote d’Ivoire since 2009 and 2010 respectively, in more than 75 national public health reference labs as well as in large-volume clinical laboratories. In addition, with funding from Digital Square Notice C, DIGI established integration between OpenELIS and OpenMRS using FHIR, and led and published the OpenHIE LIS-EMR architectural specification with the OpenHIE LIS Community of Practice. DIGI faculty and team members are leaders in the global goods communities at large, founding and actively leading the OpenHIE LIS Community of Practice; as well as, serving on the Board of Directors and in strategic leadership roles for both the OpenMRS and OpenELIS communities.

I-TECH also brings to the project the expertise in laboratory systems in LMIC, through our Laboratory Systems Strengthening (LSS) Team. Led by Dr. Lucy Perrone, a public health laboratory advisor specializing in infectious disease diagnosis, surveillance and response, and laboratory capacity building in LMICs, the team leverages partnerships within UW and with external collaborators globally on supporting laboratory capacity building. The team’s mission is to improve laboratory operations for optimal patient care and treatment, disease surveillance and response, and biosecurity. The team has conducted training and mentoring in laboratory leadership and management, supported policy development for laboratories, and worked with reference and clinical laboratories on advancement toward accreditation.  As part of reinforcing good laboratory practice, the team has also supported customization and implementation of LIS for improved information management within the laboratory.  The LSS team is available to contribute expertise in the fit between LIS and laboratory workflows and systems to the proposed project. 

Specific team members and their roles on the project are listed below, and the CVs of these team members are appended.  

Jan Flowers, Faculty Co-Lead (Role: Principal Investigator): Ms. Flowers has led informatics organizations and teams for over 20 years, focused on technology policy and law, health information systems evaluation and maturity modeling, open source communities of practice building, health technology engineering and implementation, patient centered technologies and mHealth, and standards-based interoperability for improved care at the point of service, surveillance, and program monitoring. Ms. Flowers serves on the board of directors for both OpenMRS and OpenELIS Foundations, and the founder of the OpenHIE LIS Community of Practice, which develops and shares common standards and best practices amongst the open-source LIS community. She holds an MS in Health Law and Policy from the University of California San Francisco jointly with UC Hastings Law School, and a BS in Psychology from the University of Washington.

Carli Rogosin, MIA, Senior Digital Health Specialist (Role: Project Manager- Work packages 1-3; Work Package 3 Lead): Ms. Rogosin is a specialist in software design and testing processes, and in strategies for human capacity development in digital health.  Her expertise includes curriculum development, training, and evaluation, primarily in laboratory and health systems development and strengthening. She is skilled in designing new software features based on user feedback and managing the software quality assurance process. She has also worked on stakeholder engagement and sustainability for health systems projects. She led the capacity building component of the Zimbabwe Data Improvement Project and guided the team towards deployment and implementation and managed a project funded by PATH/Digital Square to create out-of-the-box solutions for data exchange between OpenELIS and OpenMRS and between OpenELIS and OpenLMIS. She holds a Master of International Affairs degree from Columbia University and is fluent in French

Casey Iiams-Hauser, OpenELIS Product Owner (Role: Technical Lead): With more than 8 years of experience leading OpenELIS Global, Mr. Iiams-Hauser leads the OpenELIS Global team in design, development and testing, as well as installation and deployment. He manages OpenELIS security upgrades, testing and release of OpenELIS. He holds his Master of International Affairs from Columbia University School of International and Public Affairs, and is proficient in French.

Christina White, Senior Digital Health Specialist (Role: Technical Lead): Ms. White is a software engineer with more than 10 years of experience in health information systems development, deployment, administration and support. She has experience translating clinical workflows into informatics systems requirements, integrating paper-based workflows into electronic systems, and health information systems standardization and interfacing. She also specializes in User interface/User interaction (UI/UX) design and development, and has collaborated on human computer interaction studies. Additionally, she has experience with health systems database architecting, MVC frameworks, development and execution of full scope testing protocols, registration modules, and lab information systems adaptation and implementation. Ms. White holds a Master’s of Science in Cultural and Environmental Resource Management from Central Washington University and a Bachelor's of Science in Bioengineering from the University of Washington.

Greg Rossum, Senior Software Developer (Role: Developer). Mr. Rossum provides technical analysis and software development with OpenELIS, TrainSMART, and other open source software products as part of the DIGI team. He is the primary software engineer for OpenELIS, and led the effort to convert the OpenELIS Java framework from Struts I to Spring to enhance software security. He also contributed to the OpenELIS interoperability project funded by PATH/Digital Square to demonstrate interoperability between OpenELIS and OpenMRS using FHIR resources. He has worked on multiple health informatics projects in Haiti, Botswana, Namibia and Cote d’Ivoire. He holds a degree in Computer Science from the University of Calgary.

Lucy Perrone, Assistant Professor (Role: Laboratory Domain Expert): Dr. Lucy A. Perrone is a public health laboratory advisor specialized in infectious disease diagnosis, surveillance and response, and laboratory capacity building in resource-limited countries. Dr. Perrone has years of experience in these areas and has worked in multiple countries worldwide since 2009. Her areas of expertise include infectious disease diagnosis and surveillance, laboratory systems and capacity building, and improving human resources for health. Dr. Perrone is skilled in infectious disease epidemiology, evaluation of infectious disease surveillance programs, quality assurance of laboratory testing, developing international guidelines for the prevention and control of infectious diseases, as well as the training and mentoring of medical laboratory staff. Dr. Perrone is currently the Director of the Certificate Program in Laboratory Leadership and Management at the University of Washington.

Digital Health Atlas: 

OpenELIS Global in Côte d'Ivoire : DHA Unique project ID CI4QbYvpdz

OpenELIS Global in Haiti: DHA Unique project ID HToQeZV6ep

Geographic Reach: 

Côte d'Ivoire, Haiti, Vietnam, Mauritius

WHO Classification: 
Laboratory and diagnostics information system
Application Status: 
Approved - partially funded
Application Tags: 
interoperability
openhie
training courses and content
Laboratory Systems

Comments

A few thoughts / comments:

- how is this work building on / expanding the LIS COP work that is underway?

- interested around the sharing of content around the Academy; are there other channels that are being considered too?

- It would be really interesting to see the work call out more directly the validation processes (IQ, OQ, PQ processes).

- are there any explicit plans to align the deployment with the existing Instant OpenHIE project?

Great questions Carl - this was helpful for the team to realize that they needed to clarify some of the points they were making in the concept note, since the team had included most of this in their thinking on this concept.  I'll provide some brief answers here for you though as well.

  • How is this work building on / expanding the LIS COP work that is underway?

    • We will collaborate with the OpenHIE Laboratory Information Systems community (LIS CoP) to prioritize and develop LIS interoperability test cases around established LIS interoperability specifications published by the LIS CoP that can be re-usable by other LIS software in the OpenHIE architecture, specifically in the Instant OpenHIE project.  Those interop specifications are led by DIGI with the OpenELIS-OpenMRS collaborative work, and being published now by the LIS CoP, so this would take that work and automate the testing of that specification for the LIS CoP to utilize and for Intant OpenHIE to use when plugging-in an LIS component.  

  • Interested around the sharing of content around the Academy; are there other channels that are being considered too?

    • There are many channels we would be open to dissemination of knowledge sharing and education materials produced in this work.  OpenHIE Academy would be an obvious choice due to the planned collaboration with OpenHIE, but the materials could be disseminated in any web-based forum or through a series of webinars or packaged with compatible materials for digital health trainings in general - such as the WHO AFRO/ITU Digital Health Workshop.

  • It would be really interesting to see the work call out more directly the validation processes (IQ, OQ, PQ processes)

    • I think adding those aspects of QA into the software release process is super interesting.  To add in any IQ, OQ, or PQ, we would need to set some benchmarks - which probably needs to be along some sort of standard discussed in the larger OpenHIE community.  Has this been brought up in OpenHIE?  Is Instant OpenHIE doing anything along these lines to evaluate installation, operations, and performance?  I think we could flesh this idea out possibly in the full application - but the priority should be first with getting the core business cases automated, and then refining the testing of the details around those business cases.  I’d love to talk more about this with you Carl, as this should be thought about for OpenMRS QA as well.

  • Are there any explicit plans to align the deployment with the existing Instant OpenHIE project?

    • Yes, that is outlined in the concept note - utilizing the LIS CoP to work on automated testing that reflects the LIS CoP published interoperability workflow specifications and can be used to plug in LIS into Instant OpenHIE.