Top 6 Trends to Cure Healthcare Startup Problems in 2019

Top 6 Trends to Cure Healthcare Startup Problems in 2019

Healthcare Tech Outlook | Monday, June 17, 2019

FREMONT, CA: With the gradual addition of AI, Chatbots, and Robotics in various process of healthcare sector last year, the need for the update has set ablaze innovations. The availability of state-of-art technologies is overriding the risk factors that the legacy institutions are advertising for. The wave of change has hit the industry with latest technologies like health informatics, AI-powered surgery robots, telemedicine, and 3D printed medicines; the healthcare providers have decided to dive deep into sophisticated technologies that make a difference. The top 5 trends recognized to hit the healthcare markets are:

1.  IoT Big Data Analytics:

The Internet of Medical Things (IoMT) plays a pivotal role in laying the groundwork for health telematics in the processes such as diagnostics and condition monitoring. The IoMT and Big data Analytics (BDA) have imprinted its marks in the acquisition, storage, retrieval, and health informatics in the industry. With the IoMT BDA paradigm, the current effort to cut down the cost of healthcare services is encouraged, along with increased efficiency in healthcare. There are three critical drivers of IoMT BDA convergence identified as promises of development in the near future. The implementation of technology primarily reduces data congestion and inefficiencies of emergency systems. Second, is the storage solutions of IoMT BDA are handled, as an entire stockpile of IoMT devices produces vast quantities of data are classified into critical and non-critical data, sending the former to fog computing and the latter to centralized cloud systems. The crucial third driver is data abstraction; this feature has assisted development in the emergence of many startups in health applications and systems

2.  Grey Model Approach for Performance Evaluation:

E-Health records and claims systems have simplified the collection of data creating efficient systems in the healthcare industry. The congregation of field level primary data is made, and the accumulated secondary data generates insights on the performance of the healthcare industry. The improved grey model approach analyzes the KPIs of a hospital based on secondary data insights, even though the data is unstructured. The grey model is enhanced to execute processing and predict estimates relative to the quantitative indicators.

These KPIs such as bed turnover rate, bed occupancy rate, the average length of stay, and hospital death rate are observed to qualitatively evaluate the hospital’s performance and enhance patients’ satisfaction and improved profit margin. The grey model approach provides the healthcare managers an empirical basis upon which strategies and analysis can be carried out to reach the goals set and attain a predicted value. 

3.  Blockchain to Solve Patient-Driven Data Management:

Blockchain technology enacts the role of a platform in the exchange of digital information without a traditional intermediary. The sharing of data requires several points of collaboration among entities. Since inter-working of transactions becomes largely patient-centric, the blockchain technology facilitates the exchange and avails greater control of data to patients.

•  Digital access rules: Access to data are controlled, and patients can choose the level of access to provide and the recipients of the data.

•  Data immutability: A patient can log in into multiple institutional interfaces and offer the same key and the permission to transfer data securely and privately by pre-determining the accessibility levels of various other parties

•  Data liquidity: Highly sensitive clinical data like advanced care planning—code status—can be published into a public blockchain, guaranteeing quick and access to the liquid information.

• Patient identity: Patients can have the freedom to manage their public keys with a wallet or a mobile device by utilizing the public key infrastructure to confirm their identity while retrieval of clinical data from the blockchain.

4.  3D printing for Personalized Medicine:

3D printing has grown substantially since the successful printing of dental implants and prosthetics and has transformed to make personalized medication dosing possible. By adopting this technology of 3D printing fulfills the basic needs of personalization of dosage in medicine at different stages.

 3D Printing fulfills the possibility of using various drug layers to obtain a personalized pill for different stages and treats all the conditions of the patient specifically. The effectiveness of 3D printing the medicines has been analyzed to be positive, posing both advantages and risks, later being minimal and can be managed with precautionary measures.  A 3D printing powered technology to compound a pharmacy is an innovation that has been envisioned in 2019, It has proven to be economical, and the ambitious goal in the technology is to gain the capability to print living tissues and organs in another decade or two.

5.  Telematics and Smart Wearables:

Wireless Sensors, Telematics, and smart wearables are among the few areas that are currently being processed for application in the healthcare industry. The telematics in health informatics has produced implantable body area network systems are that are continually improving the communication systems among healthcare professionals as they are utilized to collect real-time data while monitoring the patient’s stats. The applications of the technologies can be verified in cases of collection of patient information, database generation, connecting to payment gateways for insurance providers, management of cadaver systems, compliance with the legal formalities all form a single platform. The advanced technology is unobtrusive, energy efficient, with a scalable system that provides a comprehensive analysis of the patient. 

The smart wearable and implantable wireless body sensors transfer information from the body part to the central station through a wireless sensor. The main station integrates the data which is received and transmits it to a major system or an internet-based application via the same wireless sensor network maintained by a software-defined network (SDN) technology. Here the data is controlled through a software-based application of networking.

6.  Telemedicine and AI:

A vast majority of working individuals are expected to have access to telemedicine in 2019. Telemedicine is a contrast to conventional consulting of medical professionals for chronic, preventive, and acute care to improve clinical outcomes. With telemedicine, healthcare access that was previously available only in hospital or clinics will move to the vicinity of the house in the industrialized world. In the developing world with limited infrastructure and facilities, telemedicine will optimize connections among providers, hospitals, and tertiary centers. The advancement of this technology is mainly dependent on three key drivers— human factors, economics, and technology. Healthcare organizations have incorporated the technology by encouraging the synergies between AI and telemedicine. For example, machine learning algorithms are used by doctors to tenuously diagnose, treat, and prescribe medicines for diabetic retinopathy.

With the enhancement of AI and telemedicine, there are more advantages than the conventional use of AI that has been followed in the healthcare industry. The AI-powered telemedicine will provide quicker answers, recommendations of a better quality of diagnosis and medicine for minor cases. Older people and the disabled also benefit from telemedicine, as it offers improved logistics. AI-based telemedicine will also assist doctors and give them a breather to avoid burnouts among professionals.

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