2022 Early Hearing Detection & Intervention Virtual Conference
March 13 - 15, 2022
9/25/2018 | 2:30 PM - 3:00 PM | The Incremental Burden of Congenital Cytomegalovirus in the First Year of Life: A Retrospective Case-Control Analysis of Medicaid and Commercial Claims Data | Diamond Ballroom I
The Incremental Burden of Congenital Cytomegalovirus in the First Year of Life: A Retrospective Case-Control Analysis of Medicaid and Commercial Claims Data
Objective: To estimate health care (HC) resource use and costs associated with congenital cytomegalovirus disease (cCMV) at birth and in the first year of life in the United States.
Methods: This retrospective analysis used insurance claims data from the MarketScan Commercial Claims and Encounters and Multi-State Medicaid databases between January 1, 2011, and December 31, 2016. Infants with a cCMV diagnosis (ICD-9-CM codes 771.1, 078.5; ICD-10-CM codes P35.1, B25) were included. Claims were categorized as for the initial hospital stay at birth (“birth” analysis) or occurring in the subsequent 12 months, excluding birth (“post-birth” analysis). Infants with cCMV in both analyses were matched 1:1 to infants without cCMV based on demographic and clinical characteristics. All-cause costs were compared between infants with cCMV and matched controls. Multivariable regression analyses were conducted to control for additional confounding factors.
Results: In total, 397 cCMV patients (167 vaginal delivery, 230 caesarean delivery) were identified for the “birth” analysis and matched to controls. At birth, cCMV patients had an additional 9.1 (95% confidence interval [CI]: 5.8 to 12.3) and 9.0 (95% CI: 4.6 to 13.5) inpatient days and $24,274 (95% CI: $10,082 to $38,466) and $31,770 (95% CI:$9,911 to $53,630) more inpatient costs versus controls, for vaginal and caesarean delivery, respectively. Post-birth, 678/679 of identified cCMV patients were matched with 678 controls. Post-birth, cCMV patients had an additional $58,806 (95% CI: $41,247 to $76,365) in costs versus controls, with inpatient visits accounting for 85% of the average difference. cCMV patients accrued HC costs at birth averaging 1.5 to 2.1 times greater than controls for caesarean and vaginal delivery, respectively. During the first year of life, cCMV patients had costs averaging 7 times greater than matched controls.
Conclusions: cCMV is associated with substantial economic burden at birth and throughout the first year of life.
- To report on demographic and clinical characteristics of infants diagnosed with congenital cytomegalovirus disease in a national claims database
- To estimate U.S. health care resource utilization associated with congenital cytomegalovirus disease at birth and in the first year of life
- To estimate U.S. health care costs associated with congenital cytomegalovirus disease at birth and in the first year of life
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Presenters/Authors
Juliana Meyers
(), jmeyers@rti.org;
Juliana Meyers, MA, is a Director of Health Economics at RTI HS with more than 11 years of experience in health economics and outcomes research. Prior to joining RTI HS, Ms. Meyers worked as a research manager at Boston Health Economics. She has extensive experience in the design and analysis of studies involving retrospective health care claims data, cross-sectional and longitudinal survey data, data from prospective clinical studies, data from customized retrospective medical chart abstractions, and inpatient and long-term care data. Ms. Meyers has conducted research to estimate the prevalence, treatment patterns, and economic burden of various medical conditions.
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Anushua Sinha
(), anushua.sinha@merck.com;
Anushua Sinha, MD MPH, is a Director in Outcomes Research supporting vaccines, at Merck’s Center for Observational and Real-World Evidence. She is also an infectious disease attending physician at The University Hospital, Newark NJ, where she continues to see patients on a pro bono basis. Prior to joining Merck, she was an Associate Professor at the Rutgers New Jersey Medical School and Rutgers School of Public Health. Dr. Sinha is board certified in internal medicine and infectious diseases. She completed her training at Harvard Medical School, Massachusetts General Hospital, the Brigham and Women’s Hospital (BWH), and the Harvard School of Public Health. Her research training in health services research and decision sciences was at the Channing Laboratory (BWH). Her research has focused on the health economics of preventive services in the U.S. and internationally, with a focus on the introduction of new and underutilized vaccines.
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Salome Samant
(), salome.samant@merck.com;
Salome Samant MBBS, MPH is a trained physician who earned her medical degree (MBBS) from Seth G.S. Medical College/ KEM Hospital, Mumbai. She practiced for two years in India before receiving her Master of Public Health (MPH) degree from Johns Hopkins Bloomberg School of Public Health. She worked at the Earth Institute at Columbia University on a program evaluation of India’s National Rural Health Mission for the Government of India. For the past two years, she has been employed at Merck’s Center for Observational and Real-World Evidence, providing scientific and project management support for various outcome research studies across multiple therapeutic areas including Oncology, Vaccines, Molecular epidemiology, Infectious diseases and Primary Health
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Laurel Tranthem
(), laureljctrantham@gmail.com;
Ms. Trantham has over ten years of experience as a health care services researcher, with expertise in using health care data to conduct population health studies and program evaluations. She has extensive experience using health care claims and patient registry data to evaluate outcomes across a variety of therapeutic areas. Ms. Trantham's research has been published in numerous peer-reviewed journals.
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Sean Candrilli
(), scandrilli@rti.org;
Sean D. Candrilli, PhD, is a Global Head of Health Economics at RTI HS. During his tenure at RTI HS, Dr. Candrilli has worked extensively in the area of data management and analyses of clinical trial and commercially available and public use databases, as well as with data drawn from medical records (i.e., retrospective medical record abstractions). His academic background is heavily grounded in applied economics and econometrics, particularly as related to public health topics, and he has extensive experience in all aspects of retrospective health care claims database analyses, cross-sectional and longitudinal survey analyses, econometric modeling, and data management using a variety of statistical packages. Dr. Candrilli has conducted research to estimate the economic burden and characterize treatment patterns in various disease areas.
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