Amidst the social-distancing norms of the COVID-19 pandemic, it has become more crucial than ever to come up with innovations in remote patient care. It is no wonder that big tech conglomerates like Amazon and Microsoft are pouring capital into digital healthcare investment, with a special focus on Remote Patient Monitoring (RPM).
Sworkit is a digital health and fitness company based in Bethesda, Maryland. Founded in 2012, it provides customizable workout plans and resources that allow people to adopt and maintain a healthy lifestyle. Their workout offerings are a combination of strength, cardio, yoga, and stretching with some tough nutrition challenges to help people stay fit. The Sworkit app has 10 million registered users with an average rating of 4.5 on iOS and Google Play stores. As of May 2021, the fitness company has worldwide revenue of $90K.
Hospital-based healthcare services are not always viable when it comes to people with special health conditions or geriatric care. Issues with traveling come in the way of healthcare for this class of citizens. Additionally, lengthy hospital stays are reported to cause deterioration in certain medical conditions, especially autoimmune ailments.
The lack of information prioritization in the current healthcare climate has put strict limits on the care that clinicians can provide. To resolve this, innovators of Electronic Health Record (EHR) systems must introduce ways to plan for a patient's health management. This blog discusses how EHR's capabilities can be optimized and extended to make this move.
Biotech and pharmaceutical companies are required to comply with regulations enforced by the US Food and Drug Administration (FDA). Among these regulations is the Current Good Manufacturing Practice (CGMP) which governs the quality control of not just manufacturing practices and facilities but also the technology components of the drug production process.
Telemedicine can simply be defined as online healthcare and diagnosis through apps and videoconferencing. It is lately becoming a widely accepted alternative to physical patient-doctor consultation. Global attention towards providing sustainable telemedicine services has exploded. This has especially been witnessed throughout the accessibility struggles faced during the COVID-19 crisis.
The radiology wing of hospital systems and diagnostic centers generates an abundance of sensitive data. However, they often lack the analytics infrastructure to access and parse the data efficiently. To make the most of this available big data, radiologists are leveraging AI-based imaging analytics.
The COVID-19 pandemic has put tremendous pressure on the healthcare system, globally. Hospitals have experienced a surge in the volume of patients. The hospital staff has been asked to perform roles they were unfamiliar with. Many hospitals even stopped elective procedures and consultations to ensure that COVID-affected patients are attended well.
Machine Learning (ML) is one of the most versatile technologies of Artificial Intelligence (AI). The healthIT sector has realized the importance of ML in the prediction, management, and treatment of various health issues. These days, researchers are coming up with some innovative ways in which machine learning is improving the quality of patient care.