A Mobile Health Intervention for Patients With Depressive Symptoms: Protocol for an Economic Evaluation Alongside Two Randomized Trials in Brazil and Peru.

BACKGROUND: Mobile health interventions provide significant strategies for improving access to health services, offering a potential solution to reduce the mental health treatment gap. Economic evaluation of this intervention is needed to help inform local mental health policy and program development. OBJECTIVE: This paper presents the protocol for an economic evaluation conducted alongside 2 randomized controlled trials (RCTs) to evaluate the cost-effectiveness of a psychological intervention delivered through a technological platform (CONEMO) to treat depressive symptoms in people with diabetes, hypertension, or both. METHODS: The economic evaluation uses a within-trial analysis to evaluate the incremental costs and health outcomes of CONEMO plus enhanced usual care in comparison with enhanced usual care from public health care system and societal perspectives. Participants are patients of the public health care services for hypertension, diabetes, or both conditions in São Paulo, Brazil (n=880) and Lima, Peru (n=432). Clinical effectiveness will be measured by reduction in depressive symptoms and gains in health-related quality of life. We will conduct cost-effectiveness and cost-utility analyses, providing estimates of the cost per at least 50% reduction in 9-item Patient Health Questionnaire scores, and cost per quality-adjusted life year gained. The measurement of clinical effectiveness and resource use will take place over baseline, 3-month follow-up, and 6-month follow-up in the intervention and control groups. We will use a mixed costing methodology (ie, a combination of top-down and bottom-up approaches) considering 4 cost categories: intervention (CONEMO related) costs, health care costs, patient and family costs, and productivity costs. We will collect unit costs from the RCTs and national administrative databases. The multinational economic evaluations will be fully split analyses with a multicountry costing approach. We will calculate incremental cost-effectiveness ratios and present 95% CIs from nonparametric bootstrapping (1000 replicates). We will perform deterministic and probabilistic sensitivity analyses. Finally, we will present cost-effectiveness acceptability curves to compare a range of possible cost-effectiveness thresholds. RESULTS: The economic evaluation project had its project charter in June 2018 and is expected to be completed in September 2021. The final results will be available in the second half of 2021. CONCLUSIONS: We expect to assess whether CONEMO plus enhanced usual care is a cost-effective strategy to improve depressive symptoms in this population compared with enhanced usual care. This study will contribute to the evidence base for health managers and policy makers in allocating additional resources for mental health initiatives. It also will provide a basis for further research on how this emerging technology and enhanced usual care can improve mental health and well-being in low- and middle-income countries. TRIAL REGISTRATION: ClinicalTrials.gov NCT12345678 (Brazil) and NCT03026426 (Peru); https://clinicaltrials.gov/ct2/show/NCT02846662 and https://clinicaltrials.gov/ct2/show/NCT03026426. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/26164.

Factors Associated with the Costs of Palliative Care: A Retrospective Cost Analysis at a University Cancer Hospital in Brazil.

Background: There have been few studies evaluating the costs of palliative care (PC) in low- and middle-income countries (LMICs), especially for patients with cancer. Objectives: The objective of this study was to identify the sociodemographic and clinical variables that could explain the cost per day of PC for cancer in Brazil. Methods: This was a retrospective cost analysis of PC at a quaternary cancer center in São Paulo, Brazil, between January 2010 and December 2013. Factors influencing the cost per day were assessed with generalized linear models and generalized linear-mixed models in which the random effect was the site of the cancer. Results: The study included 2985 patients. The mean total cost per patient was $12,335 (standard deviation [SD] = 14,602; 95% confidence interval [CI] = 11,803 to 12,851). The mean cost per day per patient was $325.50 (SD = 246.30, 95% CI = 316.60 to 334.30). There were statistically significant differences among cancer sites in terms of the mean cost per day. Multivariate analysis revealed that the drivers of cost per day were Karnofsky performance status, the number of hospital admissions, referral to PC, and place of death. Place of death had the greatest impact on the cost per day; death in a hospital and in hospice care increased the mean cost per day by $1.56 and $1.83, respectively. Conclusion: To allocate resources effectively, PC centers in LMICs should emphasize early enrollment of patients at PC outpatient clinics, to avoid hospital readmission, as well as advance planning of the place of death.

Economic Evaluation of Population-Based BRCA1/BRCA2 Mutation Testing across Multiple Countries and Health Systems.

Clinical criteria/Family history-based BRCA testing misses a large proportion of BRCA carriers who can benefit from screening/prevention. We estimate the cost-effectiveness of population-based BRCA testing in general population women across different countries/health systems. A Markov model comparing the lifetime costs and effects of BRCA1/BRCA2 testing all general population women ≥30 years compared with clinical criteria/FH-based testing. Separate analyses are undertaken for the UK/USA/Netherlands (high-income countries/HIC), China/Brazil (upper-middle income countries/UMIC) and India (low-middle income countries/LMIC) using both health system/payer and societal perspectives. BRCA carriers undergo appropriate screening/prevention interventions to reduce breast cancer (BC) and ovarian cancer (OC) risk. Outcomes include OC, BC, and additional heart disease deaths and incremental cost-effectiveness ratio (ICER)/quality-adjusted life year (QALY). Probabilistic/one-way sensitivity analyses evaluate model uncertainty. For the base case, from a societal perspective, we found that population-based BRCA testing is cost-saving in HIC (UK-ICER = $-5639/QALY; USA-ICER = $-4018/QALY; Netherlands-ICER = $-11,433/QALY), and it appears cost-effective in UMIC (China-ICER = $18,066/QALY; Brazil-ICER = $13,579/QALY), but it is not cost-effective in LMIC (India-ICER = $23,031/QALY). From a payer perspective, population-based BRCA testing is highly cost-effective in HIC (UK-ICER = $21,191/QALY, USA-ICER = $16,552/QALY, Netherlands-ICER = $25,215/QALY), and it is cost-effective in UMIC (China-ICER = $23,485/QALY, Brazil-ICER = $20,995/QALY), but it is not cost-effective in LMIC (India-ICER = $32,217/QALY). BRCA testing costs below $172/test (ICER = $19,685/QALY), which makes it cost-effective (from a societal perspective) for LMIC/India. Population-based BRCA testing can prevent an additional 2319 to 2666 BC and 327 to 449 OC cases per million women than the current clinical strategy. Findings suggest that population-based BRCA testing for countries evaluated is extremely cost-effective across HIC/UMIC health systems, is cost-saving for HIC health systems from a societal perspective, and can prevent tens of thousands more BC/OC cases.