6th Annual PHIN Conference August 25-28, 2008 Direct Import of Electronic Laboratory Reports into Ohio’s Disease Reporting System Lynn K. Giljahn, MPH Infectious Disease Surveillance Ohio Department of Health 6th Annual PHIN Conference August 25-28, 2008

Contributors Lilith Tatham Jenny Seiler Jim Gallant Greg Buskirk Bob Campbell Others on Ohio Disease Reporting System Team at Ohio Department of Health

Objectives Describe: Outline: benefits, challenges, and next steps receiving, processing, and directly importing electronic laboratory reports automated and manual processing of reports Outline: benefits, challenges, and next steps

Definitions ELR = Electronic Laboratory Reporting HL7 = Health Level 7 standard for electronic data exchange in healthcare environments ELR standard for order and structure of data in an electronic message LOINC = Logical Observation Identifiers Names and Codes ELR standard for test names SNOMED = Systematized Nomenclature of Medicine clinical terms ELR standard for non-numeric results

Lab data stored in database ELR Import Process Lab 1 - HL7 2.3.1 Lab 2 - HL7 2.3.z Lab 3 -ASCII HL7 Gateway Parsing Normalization ODRS HL7 2.5 Lab data stored in database Identification STD*MIS ASCII

Step 1 – Lab Sends a HL7 File assembles list of test names/codes and result names/codes for tests performed in lab and submits to ODH sets up a secure mechanism for file transfer composes a complete and properly formatted HL7 message works with ODH to test messages and fix problems

Test Names/Codes LOINCs are preferred Labs map local test codes to LOINCs Labs reporting to ODH via ELR have identified over 400 LOINCs they may be sending Over 2400 additional LOINCs identified by ODH and mapped to Ohio’s reportable diseases

Result Names/Codes SNOMED preferred Laboratories map results to SNOMED codes ODH has mapped 165 SNOMED codes to Ohio’s reportable diseases Mappings are used when LOINC code does not identify the reportable disease

Step 2 - File is Processed in HL7 Gateway Data parsed and normalized Test name is identified Test name determines reportable condition Reportable condition determines information system to receive the report Report is routed to the appropriate disease surveillance system for import

Step 2 – HL7 Gateway Manual Processes Messages that fail in parsing Messages that fail in normalization Messages with tests not yet mapped to a reportable condition

Step 3 – Ohio’s Disease Reporting System (ODRS) Web-based, functionalities similar to NEDSS base system, person-based Accommodates traditional paper-based reporting Disease reports entered by state/local public health, more recently health care providers Imports ELR messages with minimal human intervention

Step 3: Report is Imported into ODRS Search for person match Search for disease match Search for event match

Step 3 – Automated Import Person Match Various matching algorithms based on combinations of last name, first name, sex, date of birth, zip code, county, medical record number, facility name, specimen ID, lab name, reportable disease One person match set to ‘exact’ – last name, first name, sex, and date of birth All other matches are set to ‘possible’

Step 3 – Automated Import Disease Match Exact match to a reportable condition or a group of reportable conditions Examples of “grouped” reportable conditions hepatitis B acute and chronic E. coli O157:H7 and E. coli unknown serotype If ‘exact’ reportable condition, system checks for event match

Step 3 – Automated Import Event Match Determines whether report is new episode of disease based on event date range Examples of event date range 7 days for Chlamydia and gonorrhea 30 days for Salmonella infinite for hepatitis B Within event date range set to ‘exact’

Step 3 – Automated Import Person Match If ‘exact’ person match, demographic fields on existing person record are updated with any additional information in ELR record If neither ‘exact’ nor ‘possible’ person match, a new person and disease report are created

Step 3 – Automated Person Record

Step 3 – Automated Import Disease/Event Match If ‘exact’ disease and event match, laboratory fields on existing disease report are updated with any additional information in ELR record. If ‘exact’ disease but not event, a new disease report is created for the person. If neither ‘exact’ nor ‘group’ disease match, a new disease report is created for the person.

Step 3 – Automated Lab Record

Step 3 – Automated Lab Record

Step 3 – Other Automated Processes Data edited to meet ODRS formats Person addresses are geocoded and jurisdiction determined Providers and facilities are associated with existing information Anything processed automatically through ELR import is noted

Step 3 - Automated ELR Notes

Step 3 – Manual Import Manual ‘Possible’ person match ‘Exact’ person match with “grouped” disease match ‘Possible’ person and either ‘exact’ or “grouped” disease match

Step 3 – Manual Import ODRS Home Page

Step 3 – Manual Import ELR Queue

Manual ELR Import ‘Grouped’ Disease Match

ELR Import ‘Grouped’ Disease Match

ELR Import ‘Grouped’ Disease Match

ELR Import ‘Grouped’ Disease Match

Step 3 – Other Manual Processes Determine reportable disease ‘generic’ test name (“ODRS unknown”) with unmapped result or locally coded result or result in note result only reportable for certain ages result only reportable for certain specimen types Map test name, test result, or text result Discard test

Test Name Mapping

Test Result Mapping

Text Result Mapping

Step 3 – End Result New person and disease report created OR New disease report created for an existing person OR Existing disease report updated OR Report discarded

Results January-June 2008 Type of import Type of processing 25.2% new person and new disease report 1.5% new disease report for an existing person 73.3% update of existing disease report Type of processing 84.3 % automatically 15.7% manually

Timeliness January-June 2008 Reportable Disease ELR Created NOT ELR Created # Reports Mean Lag (days) Hepatitis B Chronic 254 4.7 968 17.4 Hepatitis C Chronic 1424 3.0 3833 18.4 Aseptic Meningitis 16 5.7 239 8.5 Pertussis 27 12.1 300 14.3 Varicella 17 3.6 1590 10.9

Benefits to ODH More timely reporting More complete reporting Reduction in paper and manual processing Receipt of information in a standardized format

Benefits for Laboratories Reduction in paper and manual processing Elimination of the need to determine jurisdiction for case reporting Ability to send all disease reporting information to ODH in a standardized format Ability to send all disease reporting information to a single location at ODH

Challenges Limitations of lab IT systems: don’t always capture patient demographics can’t send a HL7 file file can’t be formatted to PHIN standard Non-reportable results Time investment to set up – labs and ODH Other IT systems at ODH not ready to receive HL7 files

Next Steps ELR from more labs – state lab, other national labs, other hospital labs Develop and implement use of standard ASCII ELR format Implement use of PHIN-MS Accept non-infectious disease ELR reports

Contacts Lily Tatham – Program Jenny Seiler – IT Lilith.tatham@odh.ohio.gov 614-644-2718 Jenny Seiler – IT Jenny.seiler@odh.ohio.gov 614-728-9579