What is the economic evidence for mHealth? A systematic review of economic evaluations of mHealth solutions.
What is the economic evidence for mHealth? A systematic review of economic evaluations of mHealth solutions.
复制标题
DOI：
10.1371/journal.pone.0170581
复制
发表时间：
2017
期刊：
影响因子：
3.7
通讯作者：
Stone PW
中科院分区：
文献类型：
--
作者：
Iribarren SJ;Cato K;Falzon L;Stone PW
移动医疗（mHealth）通常被认为具有成本效益或节省成本。尽管乐观，但支持这一主张的证据力度有限。在这篇系统综述中，对与移动医疗干预的经济评估相关的证据进行了评估和总结。检索了7个电子书目数据库、灰色文献和相关参考文献。资格标准包括原创文章、干预措施的成本和后果比较（其中一项被归类为初级移动健康干预措施或移动健康干预措施作为其他干预措施的组成部分）、健康和经济结果，并以英文发表。采用综合卫生经济评价报告标准（CHEERS）核对表对全面经济评价进行评价，并遵循PRISMA指南。检索确定了5902个结果，其中318个被全文检查，39个被纳入本综述。39项研究跨越19个国家，其中大部分在高收入和中高收入国家进行（34.87.2%）。初级移动健康干预措施（35,89.7%）、行为改变通信类型干预措施（例如，提高出勤率、药物依从性）（27,69.2%）和短信系统（SMS）作为移动健康功能（例如，用于发送提醒、信息、提供支持、进行调查或收集数据）（22,56.4%）是最常见的；最常见的疾病或状况是门诊就诊、心血管疾病和糖尿病。报告的干杯清单项目的平均百分比为79.6%（范围47.62-100,STD 14.18），前四分之一报告91.3-100%。在29项研究（74.3%）中，研究人员报告称，移动医疗干预在基本情况下具有成本效益、经济效益或成本节约。研究结果表明，越来越多的经济证据支持移动医疗干预。虽然所有的研究都包括了与健康相关的结果的干预效果与报告的经济数据的比较，但许多研究没有报告所有推荐的经济结果项目，也缺乏全面的分析。所确定的经济评估因疾病或病症焦点、经济结果测量、观点而异，并且地理分布不均匀，限制了正式的荟萃分析。需要在低收入和中低收入国家进行进一步的研究，以了解不同移动健康类型的影响。遵循既定的经济报告准则将改善这一研究体系。
Mobile health (mHealth) is often reputed to be cost-effective or cost-saving. Despite optimism, the strength of the evidence supporting this assertion has been limited. In this systematic review the body of evidence related to economic evaluations of mHealth interventions is assessed and summarized. Seven electronic bibliographic databases, grey literature, and relevant references were searched. Eligibility criteria included original articles, comparison of costs and consequences of interventions (one categorized as a primary mHealth intervention or mHealth intervention as a component of other interventions), health and economic outcomes and published in English. Full economic evaluations were appraised using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist and The PRISMA guidelines were followed. Searches identified 5902 results, of which 318 were examined at full text, and 39 were included in this review. The 39 studies spanned 19 countries, most of which were conducted in upper and upper-middle income countries (34, 87.2%). Primary mHealth interventions (35, 89.7%), behavior change communication type interventions (e.g., improve attendance rates, medication adherence) (27, 69.2%), and short messaging system (SMS) as the mHealth function (e.g., used to send reminders, information, provide support, conduct surveys or collect data) (22, 56.4%) were most frequent; the most frequent disease or condition focuses were outpatient clinic attendance, cardiovascular disease, and diabetes. The average percent of CHEERS checklist items reported was 79.6% (range 47.62–100, STD 14.18) and the top quartile reported 91.3–100%. In 29 studies (74.3%), researchers reported that the mHealth intervention was cost-effective, economically beneficial, or cost saving at base case. Findings highlight a growing body of economic evidence for mHealth interventions. Although all studies included a comparison of intervention effectiveness of a health-related outcome and reported economic data, many did not report all recommended economic outcome items and were lacking in comprehensive analysis. The identified economic evaluations varied by disease or condition focus, economic outcome measurements, perspectives, and were distributed unevenly geographically, limiting formal meta-analysis. Further research is needed in low and low-middle income countries and to understand the impact of different mHealth types. Following established economic reporting guidelines will improve this body of research.