Digital health technology, which was already evolving rapidly, has accelerated its transformation with the global pandemic outbreak. The pandemic is the first real global health crisis in the digital era. The health sector is witnessing exponential growth in digital health technologies from diagnostics and detection to tracking diseases, predictive analytics, screening, triage, virtual care, remote monitoring, etc.
More Refined Patient Experience
End-users of digital health technology, be it health organizations, healthcare professionals, or patients, are expected to be benefited from digital health applications. Customizing the consumer experience and personalizing their health decisions tends to be one of the popular ways users feel valued and recognized.
Self Assessment and Contact Tracing apps as an Immediate Response
Online self- risk assessment applications developed by many nations acted as an immediate response to COVID-19 diagnostics and detection. During the initial stages of the pandemic, when wide concerns and fake news were creating panic, these user-friendly online applications have helped provide medically correct information. The apps could address an individual’s symptoms, severity, duration of symptoms, changes in symptoms over time, travel history, and direct contact with travel history. It could also evaluate the number of cases in their locality and other relevant factors to create an extremely informed analysis. They were instrumental in forming guidelines, detecting the hotspots, and determining the subsequent steps, medical advice, and appropriate actions to be followed in their health care routines.
Population Health Management using AI and Data Analytics
As the transmission rates increased, the need to track and monitor population-level data management has facilitated the use of Data Analytics and other population health management tools. AI has proven successful in automating and optimizing health organizations’ existing workflows and streamlining their decision-making process by analyzing various medical data and their corresponding sources with human-level accuracy.
Along with the rise in demand for AI and Data Analytics, the need for AI-based medical imaging is also observing a tremendous growth in the global medical imaging market. AI and Machine learning technologies have helped health professionals analyze and research data from tons of anonymized diagnostic patient images. Smart devices with built-in sensors and intelligent algorithms also accelerate digital health innovations for providing healthcare services remotely through computing devices and patient-facing AI-powered apps.
Data Management fuelled by Cloud Adoption
With these tremendous increases in the real-time day-to-day data collection, data storage, and exchange between healthcare organizations, COVID-19 also acted as a catalyst in cloud computing investments. Health data like EMR data, lab results, medical images and videos, records, x-rays, prescriptions, genomic data, information from smart devices, etc. are now mostly added in the cloud. Huge volumes of medical data have made cloud computing an essential technology for ensuring technology implementation in the healthcare data sectors.
Interoperability in Healthcare
Data from different sources need a standard format for exchanging and analyzing health data, preventing fragmented medical data, identifying the health risks, controlling the spread, and managing patients’ treatment. Medical Interoperability is the ability of different information technology systems, networks, multiple health care service providers, and stakeholders to utilize the various health data, mostly in unstructured formats such as physician notes, digital photos, videos, etc.
Barriers for Expanding Digitalisation in Healthcare Sector
The rapid digitization of the healthcare industry has proven to be effective in minimizing the impact of the pandemic. Yet, the challenges and barriers to completely utilize the possibilities of digital healthcare solutions still exist. Being an area that requires utmost privacy and confidentiality, data security will be the primary concern and the risk factor in implementing online healthcare solutions.
Developing a security architecture and choosing the best strategies for improving security can ensure that the medical data remains secure. Acceptability of digital healthcare solutions from different geographies with diverse cultural, socio-economical, literacy level, moral, and religious backgrounds is another major challenge in utilizing digital solutions.
Despite all the other challenges in digitizing the healthcare industry, it is undoubtedly evident that in the future, Healthtech will evolve into sustainable transformations providing cheaper, faster, easily accessible, and secure technological solutions providing more affordable healthcare for all.
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