Telehealth: An Opportunity for Needed Disruption? A cost-effectiveness analysis of a telehealth-supplemented prenatal care program for low-risk Medicaid patients in the United States

Abstract

BACKGROUND: Standard prenatal care has not changed since World War II despite evidence that reduced-visit prenatal care programs produce equivalent maternal and fetal clinical outcomes. With the rise of the telehealth industry and the need for virtual care during the COVID-19 pandemic, a telehealth-supplemented prenatal care program may not only disrupt and update standard care but produce beneficial results. OBJECTIVE: To investigate the claim that telehealth interventions produce clinically equivalent outcomes, increase patient satisfaction, and reduce health-system costs in prenatal care. To identify the cost-effectiveness of a reduced visit telehealth supplemented prenatal care program, Mayo Clinic OB Nest, compared to standard prenatal care. DESIGN: Cost-effectiveness analysis using a decision tree model. DATA SOURCES: Center for Disease Control’s 2018 U.S. Natality Data; Published literature. TARGET POPULATION: Pregnant women living in the United States, aged 13 to 36 years, and using Medicaid to finance their obstetric care and delivery. Patients must also be clinically “low-risk,” without comorbidity or obstetric complication. TIME HORIZON: 50 weeks (from enrollment prior to 13 gestational weeks until 8 weeks postpartum) PERSPECTIVE: Health system (payer) perspective and societal perspective INTERVENTION: OB Nest prenatal care program, comprised of 8 in-person visits supplemented with 6 virtual visits and access to a monitored online community. OUTCOME MEASURES: Incremental cost-effectiveness ratios (2020 U.S. dollars per NICU admission avoided and 2020 U.S. dollars per Cesarean Delivery averted) RESULTS: The Mayo Clinic OB Nest model and standard care model were assumed to produce clinically equivalent outcomes. Thus, incremental costs are more critical in understanding cost-effectiveness. In three out of four cost scenarios, 1) health system perspective traditional cost structure, 2) health system perspective innovative cost structure, and 3) societal perspective traditional cost structure, standard care is more cost-effective when compared to the OB Nest intervention. In Scenario 1, OB Nest increased costs by 16.44%; in Scenario 2, OB Nest increased costs by 3.79%, and in Scenario 3, OB Nest increased costs by 10.82%. In one cost scenario, 4) societal perspective innovative cost structure, the OB Nest model decreased costs by 0.83%. Probabilistic sensitivity analysis of 10,000 Monte Carlo simulations did not reveal a consistently optimal intervention. LIMITATIONS: The OB Nest clinical trial, upon which the clinical event probabilities were estimated, used a patient population that was primarily white, urban, and high income—a contrast to the Medicaid population evaluated in this model. Standard and consistent reimbursement and length of stay data were missing. The model uses NICU admissions avoided as a primary outcome which is difficult to compare across different sectors of the health system. Finally, though providers may challenge the implementation of telehealth, a provider perspective was not included in this model. CONCLUSION: The standard prenatal care program and the OB Nest program have an approximately equal probability of being cost-effective. Therefore, it cannot be concluded with certainty that either strategy outperforms the other. This conclusion is important during the COVID-19 pandemic when in-person care is not always feasible and policymakers have promoted telehealth. This foundational model can be used with future research and evolving data to make more predictive decisions on obstetric telehealth.

BACKGROUND: Standard prenatal care has not changed since World War II despite evidence that reduced-visit prenatal care programs produce equivalent maternal and fetal clinical outcomes. With the rise of the telehealth industry and the need for virtual care during the COVID-19 pandemic, a telehealth-supplemented prenatal care program may not only disrupt and update standard care but produce beneficial results. OBJECTIVE: To investigate the claim that telehealth interventions produce clinically equivalent outcomes, increase patient satisfaction, and reduce health-system costs in prenatal care. To identify the cost-effectiveness of a reduced visit telehealth supplemented prenatal care program, Mayo Clinic OB Nest, compared to standard prenatal care. DESIGN: Cost-effectiveness analysis using a decision tree model. DATA SOURCES: Center for Disease Control’s 2018 U.S. Natality Data; Published literature. TARGET POPULATION: Pregnant women living in the United States, aged 13 to 36 years, and using Medicaid to finance their obstetric care and delivery. Patients must also be clinically “low-risk,” without comorbidity or obstetric complication. TIME HORIZON: 50 weeks (from enrollment prior to 13 gestational weeks until 8 weeks postpartum) PERSPECTIVE: Health system (payer) perspective and societal perspective INTERVENTION: OB Nest prenatal care program, comprised of 8 in-person visits supplemented with 6 virtual visits and access to a monitored online community. OUTCOME MEASURES: Incremental cost-effectiveness ratios (2020 U.S. dollars per NICU admission avoided and 2020 U.S. dollars per Cesarean Delivery averted) RESULTS: The Mayo Clinic OB Nest model and standard care model were assumed to produce clinically equivalent outcomes. Thus, incremental costs are more critical in understanding cost-effectiveness. In three out of four cost scenarios, 1) health system perspective traditional cost structure, 2) health system perspective innovative cost structure, and 3) societal perspective traditional cost structure, standard care is more cost-effective when compared to the OB Nest intervention. In Scenario 1, OB Nest increased costs by 16.44%; in Scenario 2, OB Nest increased costs by 3.79%, and in Scenario 3, OB Nest increased costs by 10.82%. In one cost scenario, 4) societal perspective innovative cost structure, the OB Nest model decreased costs by 0.83%. Probabilistic sensitivity analysis of 10,000 Monte Carlo simulations did not reveal a consistently optimal intervention. LIMITATIONS: The OB Nest clinical trial, upon which the clinical event probabilities were estimated, used a patient population that was primarily white, urban, and high income—a contrast to the Medicaid population evaluated in this model. Standard and consistent reimbursement and length of stay data were missing. The model uses NICU admissions avoided as a primary outcome which is difficult to compare across different sectors of the health system. Finally, though providers may challenge the implementation of telehealth, a provider perspective was not included in this model. CONCLUSION: The standard prenatal care program and the OB Nest program have an approximately equal probability of being cost-effective. Therefore, it cannot be concluded with certainty that either strategy outperforms the other. This conclusion is important during the COVID-19 pandemic when in-person care is not always feasible and policymakers have promoted telehealth. This foundational model can be used with future research and evolving data to make more predictive decisions on obstetric telehealth.