Establishing an expert consensus for the operational definitions of asthma-associated infectious and inflammatory multimorbidities for computational algorithms through a modified Delphi technique

Jungwon Yoon, Heather Billings, Chung Il Wi, Elissa Hall, Sunghwan Sohn, Jung Hyun Kwon, Euijung Ryu, Pragya Shrestha, Hongfang Liu, Young J. Juhn

Research output: Contribution to journalArticlepeer-review

Abstract

Background: A subgroup of patients with asthma has been reported to have an increased risk for asthma-associated infectious and inflammatory multimorbidities (AIMs). To systematically investigate the association of asthma with AIMs using a large patient cohort, it is desired to leverage a broad range of electronic health record (EHR) data sources to automatically identify AIMs accurately and efficiently. Methods: We established an expert consensus for an operational definition for each AIM from EHR through a modified Delphi technique. A series of questions about the operational definition of 19 AIMS (11 infectious diseases and 8 inflammatory diseases) was generated by a core team of experts who considered feasibility, balance between sensitivity and specificity, and generalizability. Eight internal and 5 external expert panelists were invited to individually complete a series of online questionnaires and provide judgement and feedback throughout three sequential internal rounds and two external rounds. Panelists’ responses were collected, descriptive statistics tabulated, and results reported back to the entire group. Following each round the core team of experts made iterative edits to the operational definitions until a moderate (≥ 60%) or strong (≥ 80%) level of consensus among the panel was achieved. Results: Response rates for each Delphi round were 100% in all 5 rounds with the achievement of the following consensus levels: (1) Internal panel consensus: 100% for 8 definitions, 88% for 10 definitions, and 75% for 1 definition, (2) External panel consensus: 100% for 12 definitions and 80% for 7 definitions. Conclusions: The final operational definitions of AIMs established through a modified Delphi technique can serve as a foundation for developing computational algorithms to automatically identify AIMs from EHRs to enable large scale research studies on patient’s multimorbidities associated with asthma.

Original languageEnglish (US)
Article number310
JournalBMC Medical Informatics and Decision Making
Volume21
Issue number1
DOIs
StatePublished - Dec 2021

Keywords

  • Asthma
  • Delphi
  • Electronic health records
  • Multimorbidities
  • Natural language processing

ASJC Scopus subject areas

  • Health Policy
  • Health Informatics

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