Respiratory Medicine, Royal Liverpool Hospital and Health Services Research, University of Liverpool, Liverpool, UK.
Dept of Pediatrics, National Jewish Health, Denver, CO, USA.
Eur Respir J. 2018 Nov 22;52(5). doi: 10.1183/13993003.01147-2018. Print 2018 Nov.
Outcomes for patients with chronic respiratory diseases remain poor despite the development of novel therapies. In part, this reflects the fact that adherence to therapy is low and clinicians lack accurate methods to assess this issue. Digital technologies hold promise to overcome these barriers to care. For example, algorithmic analysis of large amounts of information collected on health status and treatment use, along with other disease relevant information such as environmental data, can be used to help guide personalised interventions that may have a positive health impact, such as establishing habitual and correct inhaler use. Novel approaches to data analysis also offer the possibility of statistical algorithms that are better able to predict exacerbations, thereby creating opportunities for preventive interventions that may adapt therapy as disease activity changes. To realise these possibilities, digital approaches to disease management should be supported by strong evidence, have a solid infrastructure, be designed collaboratively as clinically effective and cost-effective systems, and reflect the needs of patients and healthcare providers. Regulatory standards for digital interventions and strategies to handle the large amounts of data generated are also needed. This review highlights the opportunities provided by digital technologies for managing patients with respiratory diseases.
尽管有新的治疗方法,但慢性呼吸疾病患者的治疗效果仍然不佳。部分原因是治疗依从性低,临床医生缺乏准确评估这一问题的方法。数字技术有望克服这些护理障碍。例如,对健康状况和治疗使用等大量信息以及其他与疾病相关的信息(如环境数据)进行算法分析,可以帮助指导个性化干预,从而对健康产生积极影响,例如建立习惯性和正确的吸入器使用习惯。数据分析的新方法还为统计算法提供了可能性,这些算法能够更好地预测恶化,从而为可能随着疾病活动变化而调整治疗的预防干预创造机会。为了实现这些可能性,数字疾病管理方法应该有强有力的证据支持,有坚实的基础设施,作为具有临床效果和成本效益的系统进行协作设计,并反映患者和医疗保健提供者的需求。还需要数字干预措施的监管标准和处理大量数据生成的策略。这篇综述强调了数字技术为管理呼吸疾病患者提供的机会。