OBJECTIVE: Preplanned economic analysis of a pragmatic trial using electronic-medical-record-linked interactive voice recognition (IVR) reminders for enhancing adherence to cardiovascular medications (i.e., statins, angiotensin-converting enzyme inhibitors [ACEIs], and angiotensin receptor blockers [ARBs]). METHODS: Three groups, usual care (UC), IVR, and IVR plus educational materials (IVR+), with 21,752 suboptimally adherent patients underwent follow-up for 9.6 months on average. Costs to implement and deliver the intervention (from a payer perspective) were tracked during the trial. Medical care costs and outcomes were ascertained using electronic medical records. RESULTS: Per-patient intervention costs ranged from $9 to $17 for IVR and from $36 to $47 for IVR+. For ACEI/ARB, the incremental cost-effectiveness ratio for each percent adherence increase was about 3 times higher with IVR+ than with IVR ($6 and $16 for IVR and IVR+, respectively). For statins, the incremental cost-effectiveness ratio for each percent adherence increase was about 7 times higher with IVR+ than with IVR ($6 and $43 for IVR and IVR+, respectively). Considering potential cost offsets from reduced cardiovascular events, the probability of breakeven was the highest for UC, but the IVR-based interventions had a higher probability of breakeven for subgroups with a baseline low-density lipoprotein (LDL) level of more than 100 mg/dl and those with two or more calls. CONCLUSIONS: We found that the use of an automated voice messaging system to promote adherence to ACEIs/ARBs and statins may be cost-effective, depending on a decision maker's willingness to pay for unit increase in adherence. When considering changes in LDL level and downstream medical care offsets, UC is the optimal strategy for the general population. However, IVR-based interventions may be the optimal choice for those with elevated LDL values at baseline.
RCT Entities:
OBJECTIVE: Preplanned economic analysis of a pragmatic trial using electronic-medical-record-linked interactive voice recognition (IVR) reminders for enhancing adherence to cardiovascular medications (i.e., statins, angiotensin-converting enzyme inhibitors [ACEIs], and angiotensin receptor blockers [ARBs]). METHODS: Three groups, usual care (UC), IVR, and IVR plus educational materials (IVR+), with 21,752 suboptimally adherent patients underwent follow-up for 9.6 months on average. Costs to implement and deliver the intervention (from a payer perspective) were tracked during the trial. Medical care costs and outcomes were ascertained using electronic medical records. RESULTS: Per-patient intervention costs ranged from $9 to $17 for IVR and from $36 to $47 for IVR+. For ACEI/ARB, the incremental cost-effectiveness ratio for each percent adherence increase was about 3 times higher with IVR+ than with IVR ($6 and $16 for IVR and IVR+, respectively). For statins, the incremental cost-effectiveness ratio for each percent adherence increase was about 7 times higher with IVR+ than with IVR ($6 and $43 for IVR and IVR+, respectively). Considering potential cost offsets from reduced cardiovascular events, the probability of breakeven was the highest for UC, but the IVR-based interventions had a higher probability of breakeven for subgroups with a baseline low-density lipoprotein (LDL) level of more than 100 mg/dl and those with two or more calls. CONCLUSIONS: We found that the use of an automated voice messaging system to promote adherence to ACEIs/ARBs and statins may be cost-effective, depending on a decision maker's willingness to pay for unit increase in adherence. When considering changes in LDL level and downstream medical care offsets, UC is the optimal strategy for the general population. However, IVR-based interventions may be the optimal choice for those with elevated LDL values at baseline.
Authors: Ted A Skolarus; Tabitha Metreger; Daniela Wittmann; Soohyun Hwang; Hyungjin Myra Kim; Robert L Grubb; Jeffrey R Gingrich; Hui Zhu; John D Piette; Sarah T Hawley Journal: J Clin Oncol Date: 2019-03-29 Impact factor: 44.544
Authors: Charles Elder; Lynn DeBar; Cheryl Ritenbaugh; John Dickerson; William M Vollmer; Richard A Deyo; Eric S Johnson; Mitchell Haas Journal: J Gen Intern Med Date: 2018-06-25 Impact factor: 5.128