Here’s how different technology trends can contribute to digital transformation in the healthcare industry

1. Telemedicine

2. Using Big Data in Healthcare

  • Big Data can solve this issue. Data from a wide array of sources can be used to generate daily and hourly predictions of how many patients are expected to be at the hospital or clinic. In Paris, four hospitals that are part of the Assistance Publique-Hôpitaux de Paris has used a variety of sources like 10 years of hospital admission records to provide daily and hourly predictions of how many patients are expected to be at the hospital at any specific time.
  • Therefore, collecting data and using it to discover patterns to predict behavior can help improve staffing by predicting patients’ admission rates.
  • Wearable devices are used to collect the patient’s health data continuously and send it to the cloud. For example, if a patient’s heartbeat increases suddenly, the system sends a real-time notification to the doctor who can then take action to lower the rate and reach the patient.
  • Since IoT devices generate a massive amount of data, implementing intelligence on it can help health professionals make important decisions and get real-time alerts.
  • The University of Florida used free global health data and Google Maps to create heat maps targeted at specific issues like chronic diseases and population growth. Therefore, healthcare data can also be used for planning informed strategies.
  • Prescription data collected from different medical professionals can be monitored using the big data healthcare tool. The software can flag up prescription mistakes made by any physicians and help save many lives.

3. Internet of Things

  • IoT enables real-time remote monitoring and is beneficial for elderly patients. It uses an alert mechanism and sends a notification to concerned healthcare providers and family members.
  • Hospitals also have to deal with the spread of infection that is the primary concern for them. IoT-based hygiene monitoring devices assist in preventing patients from getting the infection. For example, smart IoT-enabled cameras can detect if patients are washing or sanitizing their hands before taking a meal or medication or visitors are not sitting close to the patient.
  • Also, IoT devices can help in managing assets, for example, monitoring refrigerator temperature and humidity.
  • IoT devices introduce transparency between customers and insurers in the underwriting, claims management, risk assessment process and pricing.
  • Insurers can retain customers by rewarding them for using and sharing health data captured by IoT devices. They can give incentives if a person keeps track of their routine activities and maintains a healthy lifestyle. It will help insurers reduce claims drastically.
  • Insurers can also verify the claims with the help of data generated from IoT devices.

The diagram shown below represents how IoT-enabled devices work.

Source: LeewayHertz

4. Virtual Reality

Here’s how VR can help the healthcare industry:

  • The program involved around 40 children aged between 7 to 23. Each child was provided a VR headset covered in protective gear to cut down germs. Then, children selected between different scenarios, including walking through a jungle, talking with a friendly snake and taking a roller coaster ride. VR headsets were connected to screens so that parents could see what their children were watching.
  • During the whole activity, kids did not experience any pain and parents were thrilled as their child was happy and tolerated the procedure peacefully.
  • Therefore, many healthcare institutes are adopting VR technology for pain reduction therapies.
  • Neuro Rehab VR, one of the leading providers in Virtual Reality Physical Therapy, has introduced a gamified approach to physical therapy. The company has developed VR training exercises with machine learning to customize each exercise to the patient’s therapeutic requirements.
  • That’s how VR is being used widely in speeding up recovery in physical therapy.
  • The company’s first lab, We are Alfred, converts users into Alfred, a 74-year old African-American who has high-frequency hearing loss and macular degeneration.
  • “Students would put on the headset, and even though they would read in their introduction that they were about to embody Alfred, they would immediately say, ‘There’s something broken, I can’t see.’ Or, ‘Turn up the volume, I can’t hear,’ and then realize [that was the point],” Shaw, Founder of Embodied Labs, says.
  • With VR, Embodied Labs can adjust what wearer can’t or can see and hear.
  • Therefore, such VR simulations help people understand how someone suffering from deadly disease feels and experiences. It can also help students who are researching and studying that specific disease to understand its symptoms and what it feels like in real life.

5. Artificial Intelligence

  • Large caseloads and incomplete medical histories can result in deadly human errors. However, AI can help predict and diagnose diseases fastly than any medical professionals. For example, in one of the studies, an AI model used algorithms and deep learning to diagnose breast cancer at a higher rate than 11 pathologists.
  • Breast cancer is found to be the second leading cause of cancer deaths among women in the US and screening mammography has been observed to reduce mortality.
  • Computer-assisted detection and diagnosis (CAD) software have been built in the 1990s to help radiologists enhance the predictive analytics of screening mammography. Unluckily, data suggested that early CAD systems had not led to an improvement in performance.
  • However, the remarkable success of deep learning in visual object detection and recognition, deep learning tools assisted radiologists in improving the accuracy of screening mammography.
  • According to Jeffrey Golden, MD, Chair of the Department of Pathology and a Professor of Pathology at HMS, “Seventy percent of all decisions in healthcare are based on a pathology result. Somewhere between 70 and 75 percent of all the data in an EHR are from a pathology result. So the more accurate we get, and the sooner we get to the right diagnosis, the better we’re going to be. That’s what digital pathology and AI has the opportunity to deliver.”
  • One of the digital pathology platforms, Proscia, uses AI to identify patterns in cancer cells. It helps pathologists remove bottlenecks from data management and leverage AI-enabled image analysis to link data points that support cancer diagnosis and treatment.
  • AI can also enhance productivity by exploring features of interest in slides before a clinician reviews the data.
  • Since the quality of smartphones is improving every year, phones can produce images that are viable for analysis by AI algorithms. Some of the researchers in the UK have built a tool that recognizes developmental diseases by analyzing a child’s face image. The algorithm can identify discrete features, such as the child’s eye and nose placement, jawline and other attributes that indicate a craniofacial abnormality. Therefore, it’s an excellent opportunity for us to convert a lot of data into valuable insights.
  • Smartphones can be used to collect images of skin lesions, wounds, medications, infections or eyes to help underserved areas manage a shortage of specialists while reducing the time to diagnosis for some complaints.
  • Electronic health record systems, combined with AI, can provide healthcare professionals with the ability to manage their observations instead of adding the data manually. In EHRs, AI provides healthcare professionals the opportunity to examine the existing data and extract significant insights that they can use to give recommendations.
  • AI facilitates healthcare professionals to leverage the information in EHRs, transforming them into virtual assistants that can deliver value to healthcare professionals.
  • With AI-powered EHR, healthcare professionals can get notification about things they should consider when recommending a drug or treatment. For example, if a medicine is not good for a patient based on the profiling of patients’ genes, the AI-based system can provide a more relevant recommendation.
  • Researchers find out a target protein that’s causing the disease. They examine such proteins diligently for a long time. Otherwise, there can be a significant risk of losing a lot of money on the wrong protein. Then, the research protein tries to explore a molecule or a compound that would affect the protein. The compound should be able to modify the protein to determine the disease-causing protein effectively.
  • During the process, ineffective compounds are thrown aside and only safe and efficient compounds are taken ahead for the development of drugs. The entire process is manual and time-consuming; therefore, AI comes into the picture.
  • As there are hundreds and thousands of molecules out there, human researchers are not able to test each of these molecules manually. Yet, without testing each of the molecules, it is not possible to determine which molecule would be the most relevant to fight against a specific disease.
  • Using AI, first of all, experts would feed in the parameters. They search through all the molecules and every molecule is compared against parameters. The AI-enabled system will keep learning from the generated data and find out one or more compounds that are most equipped to fight the disease.
  • Similarly, vaccines can be developed and tested successfully with the help of artificial intelligence.
  • Olive, one of the AI-as-a-service tools can be integrated easily into a hospital’s existing software, removing the need for expensive downtimes or integrations.
  • By gathering patients’ symptoms and entering them into the DeepMind platform, the doctor can detect the disease more efficiently and quickly.

6. Alexa

  • Using Sugarpod, Alexa can help diabetics patients handle their treatment and track progress effectively. It shows how Alexa can be implemented to transform chronic diseases such as type 2 diabetes.





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