Interoperability of Public Health and Clinical Information Systems

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Introduction

Exchange of data between clinical information systems (CIS) and public health information systems (PHIS) is critical to public health. The ability to promote disease prevention at a population level and to respond to public health emergencies, such as disease outbreaks, is dependent on the flow of patient and population-level data, which has been highlighted in the COVID-19 pandemic.[1]

  • The most common use case is reporting of electronic lab data from CIS to PHIS to support disease surveillance and contact tracing, but bidirectional information exchange related to key public health interventions such as immunizations is also necessary.
  • As of 2014, 67% of lab reports for notifiable conditions were transmitted electronically, but adoption was inconsistent (much higher for large laboratory companies than hospital laboratories).[2] Additionally, electronic transmission of the data alone may not be a sufficient metric if the PHIS cannot interpret the meaning of that data.[3]
  • Recent trends have helped to push CIS-PHIS integration to the forefront, including increased financial incentives and policies by governmental and private insurance providers to promote population health.[4]

Barriers to CIS/PHIS Interoperability

Lack of consistent use of vocabulary standards within CIS

  • Meaningful use provision within HITECH act incentivized use of vocabulary standards but those still have not been universally adopted A. 2010-11 analysis of Indiana and Wisconsin public health systems revealed less than 20% of incoming transmitted electronic laboratory reporting messages were in standard SNOMED/LOINC vocabularies and while use of standardized vocabularies has likely improved since then, it is undoubtedly below 100% [5]

Mapping codes is resource-intensive

  • Mapping local codes to standardized vocabulary is complex and costly and Public health systems are chronically underfunded so these resources are either unavailable or need to be diverted from other projects[3]

Patient identification is not straightforward

  • Lack of national patient identifier makes patient identification challenging which can impede a rapid response to a public health emergency[1]

Need to protect patient privacy

  • Volume of data that needs to be transmitted should be sufficient to properly identify and track the case of concern, but be the minimum required to respect patient privacy – requires more complex and mutually agreed upon query templates to regulate the information transmitted [6]

Siloed data systems

  • There are not only silos between information systems (e.g. CIS vs PHIS) but also intra-information system with multiple disjointed databases within PHIS systems. For example, there are at least 60 distinct state and regional immunization information systems that transmit data nationally to CDC, but they are not directly linked, impeding the ability for health systems to query a single repository [1]

Solutions to improve CIS/PHIS Interoperability

There are numerous opportunities and approaches to improve interoperability between clinical and public health information systems. Increasing use of data vocabulary standards to improve semantic interoperability is one key step, and HITECH has incentivized institutions to adopt these standards as part of "meaningful use". For clinical systems to devote resources toward improving semantic interoperability to PHIS, there also needs to be a benefit to the clinical system, however, beyond governmental incentives which do not fully meet the costs required for a CIS to achieve true meaningful interoperability. [3]

One key incentive for a clinical system to devote resources towards use of data standards and tools to promote interoperability would be for the CIS to be able to access information from the PHIS in a bidirectional manner. Immunization information systems (IIS) are one example of how collaborative data exchange can promote operational adoption and investment by healthcare providers [1]. Currently, regional and state IIS are disjointed though and the ability for healthcare providers to broadly query those databases is limited. Lenert et al discuss development of a centralized data repository architecture using flat FHIR interoperability (e.g. a standard that permits push button population health queries of patient-level data across a population).[1][7]. Their VacTrac data architecture would wrap IIS data into a flat FHIR clinical data repository that would improve access to data across immunization registries by health systems. To be successful though, disambiguation of patient identification would be needed, which would be most easily achieved via a national patient identifier. [1].

References

  1. ↑ 1.0 1.1 1.2 1.3 1.4 1.5 Lenert LA, Ding W, Jacobs J. Informatics for public health and health system collaboration: Applications for the control of the current COVID-19 pandemic and the next one. Journal of the American Medical Informatics Association, 28(8), 2021, 1807-1811. http://doi.org/10.1093/jamia/ocab066
  2. ↑ Lamb W, Satre J, Pon S, et al. Update on Progress in Electronic Reporting of Laboratory Results to Public Health Agencies - United States, 2014. Morbidity and Mortality Weekly Report, 64(12), 2015, 328-30. http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6412a5.htm
  3. ↑ 3.0 3.1 3.2 Dixon BE, Vreeman DJ, Grannis SJ. The long road to semantic interoperability in support of public health: Experiences from two states. Journal of Biomedical Informatics, 49, 2014, 3-8. http://dx.doi.org/10.1016/j.jbi.2014.03.011
  4. ↑ Gamache R, Kharrazi H, Weiner J. Public and Population Health Informatics: The Bridging of Big Data to Benefit Communities. IMIA Yearbook of Medical Informatics, 2018, 199-206. http://dx.doi.org/10.1055/s-0038-1667081
  5. ↑ Dixon BE, Siegel JA, Oemig, TV, Grannis SJ. Electronic Health Information Quality Challenges and Interventions to Improve Public Health Surveillance Data and Practice. Public Health Reports, 2013, 546-53. http://dx.doi.org/10.1177%2F003335491312800614
  6. ↑ Mishra NK, Duke J, Lenert L, Karki S. Public health reporting and outbreak response: synergies with evolving clinical standards for interoperability. Journal of the American Medical Informatics Association, 27(7), 2020, 1136-38. http://dx.doi.org/10.1093/jamia/ocaa059
  7. ↑ SMART/HL7 Bulk Data Access (Flat FHIR). https://smarthealthit.org/smart-hl7-bulk-data-access-flat-fhir/
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