Neumann Daniel, Tiberius Victor, Biendarra Florin
University of Potsdam, Potsdam, Germany.
Avanos Medical, Hamburg, Germany.
BMC Med Inform Decis Mak. 2022 Apr 27;22(1):112. doi: 10.1186/s12911-022-01851-4.
Wearables, as small portable computer systems worn on the body, can track user fitness and health data, which can be used to customize health insurance contributions individually. In particular, insured individuals with a healthy lifestyle can receive a reduction of their contributions to be paid. However, this potential is hardly used in practice.
This study aims to identify which barrier factors impede the usage of wearables for assessing individual risk scores for health insurances, despite its technological feasibility, and to rank these barriers according to their relevance.
To reach these goals, we conduct a ranking-type Delphi study with the following three stages. First, we collected possible barrier factors from a panel of 16 experts and consolidated them to a list of 11 barrier categories. Second, the panel was asked to rank them regarding their relevance. Third, to enhance the panel consensus, the ranking was revealed to the experts, who were then asked to re-rank the barriers.
The results suggest that regulation is the most important barrier. Other relevant barriers are false or inaccurate measurements and application errors caused by the users. Additionally, insurers could lack the required technological competence to use the wearable data appropriately.
A wider use of wearables and health apps could be achieved through regulatory modifications, especially regarding privacy issues. Even after assuring stricter regulations, users' privacy concerns could partly remain, if the data exchange between wearables manufacturers, health app providers, and health insurers does not become more transparent.
可穿戴设备作为佩戴在身体上的小型便携式计算机系统，能够追踪用户的健康和健身数据，这些数据可用于个性化定制健康保险费用。特别是，拥有健康生活方式的被保险人可以获得保费减免。然而，这一潜力在实践中几乎未被利用。
本研究旨在确定尽管可穿戴设备在技术上可行，但哪些障碍因素阻碍了其用于评估健康保险的个人风险评分，并根据其相关性对这些障碍进行排序。
为实现这些目标，我们进行了一项分三个阶段的排序式德尔菲研究。首先，我们从16位专家组成的小组中收集可能的障碍因素，并将其整合为11个障碍类别的列表。其次，要求该小组根据其相关性对这些因素进行排序。第三，为提高小组的共识度，向专家们公布排序结果，然后要求他们重新对障碍因素进行排序。
结果表明，监管是最重要的障碍。其他相关障碍包括用户造成的错误或不准确测量以及应用错误。此外，保险公司可能缺乏适当使用可穿戴设备数据所需的技术能力。
通过监管调整，特别是在隐私问题方面，可实现可穿戴设备和健康应用的更广泛使用。即使确保了更严格的监管，如果可穿戴设备制造商、健康应用提供商和健康保险公司之间的数据交换不变得更加透明，用户的隐私担忧可能仍会部分存在。
