Docker experience with OpenEMPI

Legacy client-registry
1

Hi All,

As we contemplate using containers, such as Docker for client registry components, we wanted to share our recent experience with a Dockerized version of OpenEMPI (available at https://github.com/alessfg/docker-openempi.git). Our goal was to understand the current state, general feasibility, and relative advantages of installing and loading demographic data using a Dockerized component. We describe our experience below:

  • The original Docker config from GitHub (https://github.com/alessfg/docker-openempi.git) contained a corrupt war file, so we downloaded the original software from OpenEMPI to obtain a valid war file.
  • Once updated, the docker installation was successful, and we were able to run the web app.
  • The OpenEMPI app appeared to function correctly as we tested various configuration options.
  • Importing the CSV file containing a test patient set that was provided in the OpenEMPI distribution did not appear to work properly. While it generated no errors when importing, we were unable to successfully query/identify imported data in the application.

After identifying the batch data import issue, we chose an alternate route for adding patients using the PIX/PDQ HL7 interface. When we submitted a test HL7 message for a fake patient, we noted data issues that could confuse someone new to OpenEMPI. Those issues notwithstanding, we were able to load a patient record. Those issues included:

  • When starting the OpenEMPI server, it doesn’t automatically start the PIX/PDQ interface. We needed to start it manually from the OpenEMPI UI.
  • OpenEMPI didn’t recognize the MRN pool/domain in our test HL7 message, and the error message it returned was not easy to understand. Eventually, we were able to address that issue manually in the UI tool.
  • After addressing these issues, we were able to send an HL7 message to OpenEMPI, and we were able to find our test patient using the UI’s search feature. We noted a data accuracy issue with the data stored for that patient in OpenEMPI: our test patient’s birthday was initially 1/1/1970, but it was stored in OpenEMPI as 12/31/1969. All other fields appeared correct.
  • We also noted through trial and error that patient search functionality is case-sensitive. For example, searching for “DOE” might work, but searching for “Doe” or “doe” would return no results. Lack of clear documentation for case sensitive search can be confusing for users.

We hope this description is informative and stimulates further discussion. While this represents our team’s experience, your’s may differ. As we explore new approaches, such as software containers like Docker, we feel it important that we as a community share our collective experiences.

Please let us know what questions you might have.

Thank you,

Shaun

2

Thank you for sharing your experience!

···

On Thu, Jan 11, 2018 at 7:35 AM, Shaun Grannis sgrannis@gmail.com wrote:

Hi All,

As we contemplate using containers, such as Docker for client registry components, we wanted to share our recent experience with a Dockerized version of OpenEMPI (available at https://github.com/alessfg/docker-openempi.git). Our goal was to understand the current state, general feasibility, and relative advantages of installing and loading demographic data using a Dockerized component. We describe our experience below:

  • The original Docker config from GitHub (https://github.com/alessfg/docker-openempi.git) contained a corrupt war file, so we downloaded the original software from OpenEMPI to obtain a valid war file.
  • Once updated, the docker installation was successful, and we were able to run the web app.
  • The OpenEMPI app appeared to function correctly as we tested various configuration options.
  • Importing the CSV file containing a test patient set that was provided in the OpenEMPI distribution did not appear to work properly. While it generated no errors when importing, we were unable to successfully query/identify imported data in the application.

After identifying the batch data import issue, we chose an alternate route for adding patients using the PIX/PDQ HL7 interface. When we submitted a test HL7 message for a fake patient, we noted data issues that could confuse someone new to OpenEMPI. Those issues notwithstanding, we were able to load a patient record. Those issues included:

  • When starting the OpenEMPI server, it doesn’t automatically start the PIX/PDQ interface. We needed to start it manually from the OpenEMPI UI.
  • OpenEMPI didn’t recognize the MRN pool/domain in our test HL7 message, and the error message it returned was not easy to understand. Eventually, we were able to address that issue manually in the UI tool.
  • After addressing these issues, we were able to send an HL7 message to OpenEMPI, and we were able to find our test patient using the UI’s search feature. We noted a data accuracy issue with the data stored for that patient in OpenEMPI: our test patient’s birthday was initially 1/1/1970, but it was stored in OpenEMPI as 12/31/1969. All other fields appeared correct.
  • We also noted through trial and error that patient search functionality is case-sensitive. For example, searching for “DOE” might work, but searching for “Doe” or “doe” would return no results. Lack of clear documentation for case sensitive search can be confusing for users.

We hope this description is informative and stimulates further discussion. While this represents our team’s experience, your’s may differ. As we explore new approaches, such as software containers like Docker, we feel it important that we as a community share our collective experiences.

Please let us know what questions you might have.

Thank you,

Shaun

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3

Shaun, thanks for sharing. What version of OpenEMPI were you using? Do you think any of the issues were attributable to Docker?

···

On Thu, Jan 11, 2018 at 10:35 AM, Shaun Grannis sgrannis@gmail.com wrote:

Hi All,

As we contemplate using containers, such as Docker for client registry components, we wanted to share our recent experience with a Dockerized version of OpenEMPI (available at https://github.com/alessfg/docker-openempi.git). Our goal was to understand the current state, general feasibility, and relative advantages of installing and loading demographic data using a Dockerized component. We describe our experience below:

  • The original Docker config from GitHub (https://github.com/alessfg/docker-openempi.git) contained a corrupt war file, so we downloaded the original software from OpenEMPI to obtain a valid war file.
  • Once updated, the docker installation was successful, and we were able to run the web app.
  • The OpenEMPI app appeared to function correctly as we tested various configuration options.
  • Importing the CSV file containing a test patient set that was provided in the OpenEMPI distribution did not appear to work properly. While it generated no errors when importing, we were unable to successfully query/identify imported data in the application.

After identifying the batch data import issue, we chose an alternate route for adding patients using the PIX/PDQ HL7 interface. When we submitted a test HL7 message for a fake patient, we noted data issues that could confuse someone new to OpenEMPI. Those issues notwithstanding, we were able to load a patient record. Those issues included:

  • When starting the OpenEMPI server, it doesn’t automatically start the PIX/PDQ interface. We needed to start it manually from the OpenEMPI UI.
  • OpenEMPI didn’t recognize the MRN pool/domain in our test HL7 message, and the error message it returned was not easy to understand. Eventually, we were able to address that issue manually in the UI tool.
  • After addressing these issues, we were able to send an HL7 message to OpenEMPI, and we were able to find our test patient using the UI’s search feature. We noted a data accuracy issue with the data stored for that patient in OpenEMPI: our test patient’s birthday was initially 1/1/1970, but it was stored in OpenEMPI as 12/31/1969. All other fields appeared correct.
  • We also noted through trial and error that patient search functionality is case-sensitive. For example, searching for “DOE” might work, but searching for “Doe” or “doe” would return no results. Lack of clear documentation for case sensitive search can be confusing for users.

We hope this description is informative and stimulates further discussion. While this represents our team’s experience, your’s may differ. As we explore new approaches, such as software containers like Docker, we feel it important that we as a community share our collective experiences.

Please let us know what questions you might have.

Thank you,

Shaun

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4

Hi Dave,

Thank you for taking a look at our review. I have added Chris Beesley and Andrew Martin from Regenstrief to this thread as they did the heavy lifting on this and Shaun is out of office for the next week.

**Jamie Thomas **|****Health Information Project Manager/Communications

Center for Biomedical Informatics

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···

On Thu, Jan 11, 2018 at 10:35 AM, Shaun Grannis
sgrannis@gmail.com wrote:

Hi All,

As we contemplate using containers, such as Docker for client registry components, we wanted to share our recent experience with a Dockerized version of OpenEMPI (available at
https://github.com/alessfg/docker-openempi.git ). Our goal was to understand the current state, general feasibility, and relative advantages of installing and loading demographic
data using a Dockerized component. We describe our experience below:

  • The original Docker config from GitHub (https://github.com/alessfg/docker-openempi.git ) contained a corrupt war file, so we downloaded the original software from OpenEMPI
    to obtain a valid war file.
  • Once updated, the docker installation was successful, and we were able to run the web app.
  • The OpenEMPI app appeared to function correctly as we tested various configuration options.
  • Importing the CSV file containing a test patient set that was provided in the OpenEMPI distribution did not appear to work properly. While it generated no errors when importing, we were unable to successfully query/identify imported data in the application.

After identifying the batch data import issue, we chose an alternate route for adding patients using the PIX/PDQ HL7 interface. When we submitted a test HL7 message for a fake patient, we noted data issues that could confuse someone new to OpenEMPI. Those
issues notwithstanding, we were able to load a patient record. Those issues included:

  • When starting the OpenEMPI server, it doesn’t automatically start the PIX/PDQ interface. We needed to start it manually from the OpenEMPI UI.
  • OpenEMPI didn’t recognize the MRN pool/domain in our test HL7 message, and the error message it returned was not easy to understand. Eventually, we were able to address that issue manually in the UI tool.
  • After addressing these issues, we were able to send an HL7 message to OpenEMPI, and we were able to find our test patient using the UI’s search feature. We noted a data accuracy issue with the data stored for that patient in OpenEMPI: our test patient’s
    birthday was initially 1/1/1970, but it was stored in OpenEMPI as 12/31/1969. All other fields appeared correct.
  • We also noted through trial and error that patient search functionality is case-sensitive. For example, searching for “DOE” might work, but searching for “Doe” or “doe” would return no results. Lack of clear documentation for case sensitive search can
    be confusing for users.

We hope this description is informative and stimulates further discussion. While this represents our team’s experience, your’s may differ. As we explore new approaches, such as software containers like Docker, we feel it important that we as a community share
our collective experiences.

Please let us know what questions you might have.

Thank you,

Shaun

–

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