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The app follows an approach that addresses physical and psychological factors of the disease.
January 22, 2019
By: Kaia Health
A peer-reviewed clinical study, published in the International Journal of Chronic Obstructive Pulmonary Disease, has shown to successfully reduce symptoms of Chronic Obstructive Pulmonary Disease (COPD) using a new artificial intelligence (AI) app, developed by digital therapeutics company Kaia Health. COPD is an umbrella term to describe chronic lung diseases that cause limitations in lung airflow. According to the World Health Organization (WHO), 64 million people are diagnosed with COPD and it will be the third leading cause of death worldwide by 2030.* Users who completed 20 therapy days with the Kaia COPD app had a clinically significant benefit in their Health-Related Quality of Life (HRQL) scores, a medical marker of perceived physical health, compared to their baseline values.** After this short period, the digital intervention improved their scores in other areas, including emotion, mastery, and fatigue. This suggests that a multidisciplinary digital treatment can contribute to improvements in important areas of successfully self-managing COPD after a short course. Unlike traditional inpatient therapies, the Kaia COPD app is widely accessible which means more people globally can benefit. The new digital treatment combines physiotherapy, psychosocial support and patient education, resulting in effective and affordable pulmonary rehabilitation in the comfort of a patient’s home. This is particularly important in developed countries with ageing populations and rapidly increasing health care costs. The Kaia COPD app follows an approach that addresses physical and psychological factors of the disease. The content is based on clinically validated patient guidelines and allows patients to better self-manage their COPD. The app includes video-based AI physiotherapy, which offers exercises to help patients build muscle and promote a healthy cardiovascular system, while a machine learning algorithm adjusts the support based on each patient’s disease profile. Psychosocial support provides audio-based relaxation exercises to manage anxiety and depression. Patients can also contact a coach via the app who will answer app-specific questions and offer motivation. Patient Education, covering topics ranging from breathing and coughing techniques to nutrition and the impact of air pollution, is also provided. Medication tracking alerts the patient when medication is due with video instructions to perfect the inhalation technique for all commonly prescribed inhalers, a necessity as up to 60 percent of COPD patients do not adhere to their medication correctly.*** “Conventional rehabilitation as a treatment for COPD is expensive and resource-intense, particularly in developed countries with a rapidly aging population and huge health care costs—which makes it difficult to integrate in health care systems,” said Konstantin Mehl, founder and CEO of Kaia Health. “Therefore, it is underutilized even though international guidelines recommend its widespread use. This clinical study indicates that, by digitizing therapy, we can democratise access to effective COPD treatment globally which can be administered in the comfort of a patient’s home. This will empower patients to take control and self-manage their COPD with evidenced-based, non-pharmacological, affordable alternatives.” Kaia Health is rapidly expanding globally, with innovative digital therapies. The company recently launched the world’s first computer vision fitness app which turns your smartphone into a personal trainer, as well as a machine learning based app which significantly reduces lower back pain by 40 percent. Kaia Health is a member of the Digital Therapeutics Alliance, an association of international manufacturers for digital therapeutic products that meet excellence in high quality standards. Dr. Frank Rassouli of the Hospital St. Gallen, Switzerland, who co-authored the research, said, “The Kaia COPD app has the potential to improve the management of COPD patients either living in remote areas with limited access to conventional pulmonary rehabilitation or where pulmonary rehabilitation is minimal or absent. The app complements any other COPD treatment as it empowers patients to better manage their disease in all areas.” The Kaia COPD app is available on smartphones and tablets (iOS and Android) and can be downloaded via the Apple App Store or Google Play. For a limited period, users can participate free in a usability test for their COPD when filling out a questionnaire at the start of the therapy. Several health insurers in Germany are already providing the Kaia COPD app to their members. The app is currently available in German and will soon be translated to English and more major languages. The Kaia COPD app is only available through select insurers and providers or by participating in the free usability test. Patients are encouraged to enquire about the app at their health insurer or provider. Founded in 2016, Kaia Health is a digital therapeutics company that creates evidence-based treatments for a range of disorders including back pain, Parkinson’s disease, osteoarthritis and chronic obstructive pulmonary disease (COPD). Kaia Health uses technology including artificial intelligence and apps, and works with experts in each medical field to create an interdisciplinary digital approach. This empowers and motivates individuals to take control and self-manage their condition with effective, non-pharmacological, digital alternatives at low costs. *The World Health Organisation on Chronic Obstructive Pulmonary Disease (COPD) (2018)http://www.who.int/respiratory/copd/en/ *International Journal of Chronic Obstructive Pulmonary Disease. Digitalizing multidisciplinary pulmonary rehabilitation in COPD with a smartphone application: an international observational pilot study (2018) https://www.dovepress.com/articles.php?article_id=42567 ***International Journal of Chronic Obstructive Pulmonary Disorder. Medication adherence issues in patients treated for COPD (2008) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2629978/
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