학술논문

Quantifying Downstream Healthcare Utilization in Studies of Genomic Testing
Document Type
article
Source
Value in Health. 23(5)
Subject
Health Services and Systems
Health Sciences
Clinical Research
Human Genome
Health Services
Genetics
Patient Safety
Health and social care services research
8.1 Organisation and delivery of services
Good Health and Well Being
Female
Genetic Testing
Genomics
Humans
Infant
Longitudinal Studies
Male
Parents
Patient Acceptance of Health Care
Risk Factors
Surveys and Questionnaires
Telephone
genetic testing
genomics
healthcare utilization
health services
humans
infant
newborn
medical records
risk factors
surveys and questionnaires
whole exome sequencing
BabySeq Project Team
Public Health and Health Services
Applied Economics
Health Policy & Services
Applied economics
Health services and systems
Policy and administration
Language
Abstract
ObjectivesThe challenges of understanding how interventions influence follow-up medical care are magnified during genomic testing because few patients have received it to date and because the scope of information it provides is complex and often unexpected. We tested a novel strategy for quantifying downstream healthcare utilization after genomic testing to more comprehensively and efficiently identify related services. We also evaluated the effectiveness of different methods for collecting these data.MethodsWe developed a risk-based approach for a trial of newborn genomic sequencing in which we defined primary conditions based on existing diagnoses and family histories of disease and defined secondary conditions based on unexpected findings. We then created patient-specific lists of services associated with managing primary and secondary conditions. Services were quantified based on medical record reviews, surveys, and telephone check-ins with parents.ResultsBy focusing on services that genomic testing would most likely influence in the short-term, we reduced the number of services in our analyses by more than 90% compared with analyses of all observed services. We also identified the same services that were ordered in response to unexpected findings as were identified during expert review and by confirming whether recommendations were completed. Data also showed that quantifying healthcare utilization with surveys and telephone check-ins alone would have missed the majority of attributable services.ConclusionsOur risk-based strategy provides an improved approach for assessing the short-term impact of genomic testing and other interventions on healthcare utilization while conforming as much as possible to existing best-practice recommendations.