NMI eSHARE Webinar: Overview of NMI Implementation and Technical Assistance Tools March 17, 2016 Conference Number: 888-972-4312 Participant Code: 7650657.

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Presentation transcript:

NMI eSHARE Webinar: Overview of NMI Implementation and Technical Assistance Tools March 17, 2016 Conference Number: Participant Code: Join the Adobe Connects meeting at: Click “Enter as a Guest,” provide your name, and click “Enter Room.” Center for Surveillance, Epidemiology, and Laboratory Services Division of Health Informatics and Surveillance

2 Agenda  Announcements Message Validation, Processing, and Provisioning System User Acceptance Testing Update on Arboviral Nationally Notifiable Disease Submission New National Notifiable Diseases Surveillance System (NNDSS) HL7 Case Notification Resource Center:  Panel Discussion NNDSS Modernization Initiative (NMI) Implementation and Technical Assistance (TA) Tools  Questions and Answers

Panel Moderator: Lesliann Helmus, NNDSS Program Manager NMI Implementation and Technical Assistance Tools: Jurisdiction Perspectives

4 Topics for Discussion  Staff resources and capacity  Surveillance system infrastructure  Technical assistance tools and resources use  Lessons learned

5 Panel Participants  Tamara Hennessy-Burt, California Department of Public Health  Kim Wiley, Florida Department of Health  Edward Hartwick, Michigan Department of Health and Human Services  Sarah Solarz, Minnesota Department of Health  Frank Murphy, New York Department of Health  Michelle Barber, Oregon Public Health Division

6 What staff resources are available to you? Pilot StateStaff Resources Available for NMI Implementation California Surveillance Coordinator Program Subject Matter Experts (SMEs) Rhapsody Developer IT/Database Staff PHINMS Admin Florida Program SMEs Project Manager Integration Broker Staff Developer Michigan Program SMEs Project Manager Rhapsody Developers Minnesota App Developer Program SMEs Rhapsody Developer IT/Database Staff PHINMS Admin New York Director, Statistical Unit Two Developers Project Manager Oregon Interoperability Director Interoperability Analyst Four Epidemiologists

7 How does your system create case notifications? Pilot StateSurveillance System System Overview and Message Creation CaliforniaAtlasData pulled from existing data warehouse. NMI Rhapsody route developed for message transformation and sending. FloridaCustomMessage created within surveillance system. Data sent to CDC via Mirth channel. MichiganCustomRhapsody used to transform and translate data extract from surveillance system. MinnesotaMavenMaven denormalized tables used to develop messages. Data warehouse and NMI Rhapsody route built for sending messages. New YorkCustomInitial independent implementation; now receiving technical assistance. Message created within surveillance system; Rhapsody used. OregonCustomHighly customizable surveillance system used, with SMEs able to work directly within database.

8 What NMI tools and resources did you use? Pilot States TANMI Tools and Resources Used California On-site Implementation spreadsheet Test case scenario spreadsheet Extract validation spreadsheet Rhapsody route TA staff as a resource Florida Virtual Implementation spreadsheet Validation of messages; assistance with errors TA staff as a resource Michigan On-site Implementation spreadsheet Test case scenario spreadsheet Rhapsody route Coordination of deliverables Minnesota Hybrid Technical architecture design TA staff as a resource Rhapsody route Coordination of deliverables New York Virtual Implementation spreadsheet Rhapsody support Oregon On-site Implementation spreadsheet Test case scenario spreadsheet Validation of messages; assistance with errors Coordination of deliverables

9 NMI Pilot Jurisdictions: Lessons Learned  California Found that dedicating staff for NMI implementation is important. Ask NMI Technical Assistance Team questions; tap into their expertise.  Florida Ensure that test cases can be preserved in the TEST system. Start mapping with matrix rather than message mapping guide.  Michigan Bring your program people in early and often; get them vested in the process. Use the NMI Technical Assistance Team even if you think getting them access to your systems will be difficult; there are workarounds.

10 NMI Pilot Jurisdictions: Lessons Learned  Minnesota Found NMI Technical Assistance Team site visits very helpful. Found technical architecture design assistance critical due to complexity of system. Have planning meetings early in process. Pull in variety of resources. Ensure staff availability for NMI implementation.  New York Filter implementation spreadsheet to focus on one section at a time.

11 NMI Pilots: Lessons Learned  Oregon Found that having dedicated staff time was critical. Engage with epidemiologists responsible for data management; this was crucial because they are the most familiar with their data and its structure and limitations. Expect a fair amount of iteration during message validation; submitting messages, getting feedback, and correcting and resubmitting multiple times a day was a much better use of time than making a plan to provide feedback within a week.

12 Special Thanks  Association of Public Health Laboratories (APHL) NMI Technical Assistance Team Gretl Glick, Project Coordinator Riki Merrick, Lead Terminologist Susan Downer, Terminologist John Park, Technical Architect  APHL Leadership Patina Zarcone, Director, Informatics Program Linda Cohen, Manager, Informatics Program Laura Carlton, Senior Specialist, Informatics Program

13 Questions

Next NMI eSHARE Webinar: Overview of Jurisdiction Onboarding Process April 21, 2016 Conference Number: Participant Code: Join the Adobe Connects meeting at: Click “Enter as a Guest,” provide your name, and click “Enter Room.” Center for Surveillance, Epidemiology, and Laboratory Services Division of Health Informatics and Surveillance

For more information, please contact Centers for Disease Control and Prevention 1600 Clifton Road NE, Atlanta, GA Telephone: CDC-INFO ( )/TTY: Visit: | Contact CDC at: CDC-INFO or The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention. Center for Surveillance, Epidemiology, and Laboratory Services Division of Health Informatics and Surveillance