ArticleCost effectiveness and resource allocation : C/E2017
Defining a staged-based process for economic and financial evaluations of mHealth programs.
Article in Cost effectiveness and resource allocation : C/E, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 2 syntheses or guidelines pooled it, 30 citations in OpenAlex.
- Analytical Frameworks and Outcome Measures in Economic Evaluations of Digital Health Interventions: A Methodological Systematic Review.Medical decision making : an international journal of the Society for Medical Decision Making · 2023Pooled it
- Data Quality and Cost-effectiveness Analyses of Electronic and Paper-Based Interviewer-Administered Public Health Surveys: Systematic Review.Journal of medical Internet research · 2021Pooled it
- An Interactive Text Messaging Intervention to Improve Adherence to Option B+ Prevention of Mother-to-Child HIV Transmission in Kenya: Cost Analysis.JMIR mHealth and uHealth · 2020Trial
- Identifying and Comparing Intervention Cost Components in Remote Patient Monitoring: A Scoping Review.PharmacoEconomics · 2026Article
- Cost-Effectiveness Analysis of Chatbot-Supported Remote Patient Monitoring for Anticoagulation Management: Health Economic Evaluation Within a Pilot Crossover Trial.Journal of medical Internet research · 2026Article
- Setting priorities for healthcare interventions in Indonesia: a comprehensive conceptual framework.International journal for equity in health · 2025Review
- Appraising eHealth Investment for Africa: Scoping Review and Development of a Framework.International journal of environmental research and public health · 2024Article
- Connecting Female Entertainment Workers in Cambodia to Health Care Services Using mHealth: Economic Evaluation of Mobile Link.JMIR formative research · 2024Article
- Developing a Program Costs Checklist of Digital Health Interventions: A Scoping Review and Empirical Case Study.PharmacoEconomics · 2024Article
- Economic Evaluation of Digital Health Interventions: Methodological Issues and Recommendations for Practice.PharmacoEconomics · 2022Article
- Methods and Lessons From Costing a Large mHealth Intervention at Scale in India.Frontiers in public health · 2022Article
- Assessing costs of developing a digital program for training community health workers to deliver treatment for depression: A case study in rural India.Psychiatry research · 2022Article
- Health economic evidence in clinical guidelines in South Africa: a mixed-methods study.BMC health services research · 2021Article
- Applicability of the five case model to African eHealth investment decisions.BMC health services research · 2020Article
- m-Health Policy Readiness and Enabling Factors: Comparisons of Sub-Saharan Africa and Organization for Economic Cooperation and Development Countries.Telemedicine journal and e-health : the official journal of the American Telemedicine Association · 2018Article
- Establishing Standards to Evaluate the Impact of Integrating Digital Health into Health Systems.Global health, science and practice · 2018Article
- Forecasting the Value for Money of Mobile Maternal Health Information Messages on Improving Utilization of Maternal and Child Health Services in Gauteng, South Africa: Cost-Effectiveness Analysis.JMIR mHealth and uHealth · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mobile and wireless technology for health (mHealth) has the potential to improve health outcomes by addressing critical health systems constraints that impede coverage, utilization, and effectiveness of health services. To date, few mHealth programs have been implemented at scale and there remains a paucity of evidence on their effectiveness and value for money. This paper aims to improve understanding among mHealth program managers and key stakeholders of how to select methods for economic evaluation (comparative analysis for determining value for money) and financial evaluation (determination of the cost of implementing an intervention, estimation of costs for sustaining or expanding an intervention, and assessment of its affordability). We outline a 6 stage-based process for selecting and integrating economic and financial evaluation methods into the monitoring and evaluation of mHealth solutions including (1) defining the program strategy and linkages with key outcomes, (2) assessment of effectiveness, (3) full economic evaluation or partial evaluation, (4) sub-group analyses, (5) estimating resource requirements for expansion, (6) affordability assessment and identification of models for financial sustainability. While application of these stages optimally occurs linearly, finite resources, limited technical expertise, and the timing of evaluation initiation may impede this. We recommend that analysts prioritize economic and financial evaluation methods based on programmatic linkages with health outcomes; alignment with an mHealth solution's broader stage of maturity and stage of evaluation; overarching monitoring and evaluation activities; stakeholder evidence needs; time point of initiation; and available resources for evaluations.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.