GARDE: a standards-based clinical decision support platform for identifying population health management cohorts

Bradshaw, Richard L.; Kawamoto, Kensaku; Kaphingst, Kimberly A.; Kohlmann, Wendy; Hess, Rachel; Flynn, Michael; Nanjo, Claude; Warner, Phillip B.; Shi, Jianlin; Morgan, Keaton; Kimball, Kadyn E.; Ranade-Kharkar, Pallavi; Ginsburg, Ophira; Goodman, Melody S.; Chambers, Rachelle; Mann, Devin; Narus, Scott P.; González, Javier; Loomis, Shane; Chan, Priscilla; Monahan, Rachel; Borsato, Emerson P; Shields, David; Martin, Douglas K.; Kessler, Cecilia; Fiol, Guilherme Del

doi:10.1093/jamia/ocac028

Cited by 9 publications

(3 citation statements)

References 15 publications

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“…The SMART Dev Sandbox 3 with the FHIR R4 Server was used to persist the created FHIR resources and sample data. LHC LForms v30 4 was used to generate functional web-forms from FHIR Questionnaire resources. The SMART on FHIR JavaScript Library v2.5.0 5 was used to enable the needed SMART API functionality and enable basic FHIR CRUD operations.…”

Section: Methodsmentioning

confidence: 99%

“…FHIR is a standard to exchange health data in a semantically interoperable way, SMART relies on FHIR to develop apps once and run them in any health care system and CDS Hooks is a specification for CDS systems. In [4] Bradshaw et al present a system based on CDS Hooks and FHIR to identify population health management cohorts. Watkins and Eilbeck implemented CDS Hooks into a FHIR lab report system as a SMART on FHIR app with different response cards for each test [5].…”

Section: Introductionmentioning

confidence: 99%

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Evaluating a CDS Hook for FHIR Questionnaires in a SMART on FHIR App and an Existing Dermatological CDS System

Tschandl

Rinner

2023

dHealth 2023

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Background: To deploy clinical decision support (CDS) systems in routine patient care they have to be certified as a medical device. The European Medical Device Regulation explicitly asks for the use of standards and interoperability in the approval process. Objectives: We extended an existing dermatological CDS system with emerging standards for CDS interoperability, to facilitate a future integration into existing healthcare infrastructure, and approval as a medical device. Methods: The data collection part of a CDS system was extended with the endpoints required by the CDS Hooks specification. FHIR QuestionnaireResponse resources trigger a newly defined hook. Results: One hundred and seventeen clinical observations and patient variables needed for the ranking of a disease were mapped to SNOMED CT or LOINC and modeled as FHIR Questionnaire which is rendered using LHC LForms in a SMART on FHIR app with the SMART Dev Sandbox. Conclusion: SMART on FHIR in combination with CDS Hooks facilitates the integration of existing CDS systems into EHR systems, potentially improving education and patient care.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluating a CDS Hook for FHIR Questionnaires in a SMART on FHIR App and an Existing Dermatological CDS System

Tschandl

Rinner

2023

dHealth 2023

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“…The Genetic Cancer Risk Detector (GARDE) platform is an EHR innovation that uses algorithms to identify patient populations that meet criteria set by National Comprehensive Cancer Network (NCCN) guidelines for genetic testing of hereditary cancer syndromes using patients’ family health history from the EHR. [ 8 , 9 ] GARDE has been used to support the Broadening the Reach, Impact, and Delivery of Genetic Services (BRIDGE) trial. BRIDGE is a randomized controlled trial with 3,073 patients who receive primary care at the University of Utah Health (UHealth) and New York University (NYU) Langone Health.…”

Section: Introductionmentioning

confidence: 99%

Enhanced family history-based algorithms increase the identification of individuals meeting criteria for genetic testing of hereditary cancer syndromes but would not reduce disparities on their own

Bradshaw,

Kawamoto,

Bather

et al. 2024

Journal of Biomedical Informatics

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Screening Familial Risk for Hereditary Breast and Ovarian Cancer

Kiser,

Elhanan,

Bolze

et al. 2024

JAMA Netw Open

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ImportanceMost patients with pathogenic or likely pathogenic (P/LP) variants for breast cancer have not undergone genetic testing.ObjectiveTo identify patients meeting family history criteria for genetic testing in the electronic health record (EHR).Design, Setting, and ParticipantsThis study included both cross-sectional (observation date, February 1, 2024) and retrospective cohort (observation period, January 1, 2018, to February 1, 2024) analyses. Participants included patients aged 18 to 79 years enrolled in Renown Health, a large health system in Northern Nevada. Genotype was known for 38 003 patients enrolled in Healthy Nevada Project (HNP), a population genomics study.ExposureAn EHR indicating that a patient is positive for criteria according to the Seven-Question Family History Questionnaire (hereafter, FHS7 positive) assessing familial risk for hereditary breast and ovarian cancer (HBOC).Main Outcomes and MeasuresThe primary outcomes were the presence of P/LP variants in the ATM, BRCA1, BRCA2, CHEK2, or PALB2 genes (cross-sectional analysis) or a diagnosis of cancer (cohort analysis). Age-adjusted cancer incidence rates per 100 000 patients per year were calculated using the 2020 US population as the standard. Hazard ratios (HRs) for cancer attributable to FHS7-positive status were estimated using cause-specific hazard models.ResultsAmong 835 727 patients, 423 393 (50.7%) were female and 29 913 (3.6%) were FHS7 positive. Among those who were FHS7 positive, 24 535 (82.0%) had no evidence of prior genetic testing for HBOC in their EHR. Being FHS7 positive was associated with increased prevalence of P/LP variants in BRCA1/BRCA2 (odds ratio [OR], 3.34; 95% CI, 2.48-4.47), CHEK2 (OR, 1.62; 95% CI, 1.05-2.43), and PALB2 (OR, 2.84; 95% CI, 1.23-6.16) among HNP female individuals, and in BRCA1/BRCA2 (OR, 3.35; 95% CI, 1.93-5.56) among HNP male individuals. Being FHS7 positive was also associated with significantly increased risk of cancer among 131 622 non-HNP female individuals (HR, 1.44; 95% CI, 1.22-1.70) but not among 114 982 non-HNP male individuals (HR, 1.11; 95% CI, 0.87-1.42). Among 1527 HNP survey respondents, 352 of 383 EHR-FHS7 positive patients (91.9%) were survey-FHS7 positive, but only 352 of 883 survey-FHS7 positive patients (39.9%) were EHR-FHS7 positive. Of the 29 913 FHS7-positive patients, 19 764 (66.1%) were identified only after parsing free-text family history comments. Socioeconomic differences were also observed between EHR-FHS7-negative and EHR-FHS7-positive patients, suggesting disparities in recording family history.Conclusions and RelevanceIn this cross-sectional study, EHR-derived FHS7 identified thousands of patients with familial risk for breast cancer, indicating a substantial gap in genetic testing. However, limitations in EHR family history data suggested that other identification methods, such as direct-to-patient questionnaires, are required to fully address this gap.

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GARDE: a standards-based clinical decision support platform for identifying population health management cohorts

Cited by 9 publications

References 15 publications

Evaluating a CDS Hook for FHIR Questionnaires in a SMART on FHIR App and an Existing Dermatological CDS System

Evaluating a CDS Hook for FHIR Questionnaires in a SMART on FHIR App and an Existing Dermatological CDS System

Enhanced family history-based algorithms increase the identification of individuals meeting criteria for genetic testing of hereditary cancer syndromes but would not reduce disparities on their own

Screening Familial Risk for Hereditary Breast and Ovarian Cancer

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