Use data to disrupt healthcare industry

Data can be used to disrupt the healthcare industry in a number of ways, including:

• Improving patient care. Data can be used to develop personalized treatment plans, predict patient outcomes, and identify potential health risks. This can lead to improved patient care and reduced costs.

• Making healthcare more accessible. Data can be used to develop telemedicine services, mobile health apps, and other tools that make healthcare more accessible to people in rural or underserved areas.

• Reducing healthcare costs. Data can be used to identify and reduce wasteful spending in the healthcare system. This can lead to lower costs for patients and payers.

• Developing new drugs and treatments. Data can be used to accelerate the development of new drugs and treatments by identifying potential drug targets and predicting the efficacy and safety of new drugs.

• Leverage patient data to provide more personalized care and treatment plans based on individuals' unique genetics, lifestyles, and medical histories. This could greatly improve outcomes.

• Analyze patient data and public health data to identify risk factors for disease and develop predictive analytics models to improve preventative care. This could help curb costs.

• Apply machine learning algorithms to large datasets from images, lab tests, clinical notes etc. to uncover new insights that can aid in diagnostics and discovery of new therapies.

• Utilize wearables, sensors, mobile apps and other digital platforms to collect real-time patient data and provide more continuous care outside of clinical settings.

• Offer patient portals and tools to access medical records and test results to drive engagement, transparency, and convenience.

• Develop recommendation systems to guide doctors on best-practice treatment protocols tailored to each patient's needs based on the latest medical research.

• Leverage geospatial data to optimize location planning for healthcare facilities and route planning for mobile nursing/vaccination services.

• Use blockchain technology to securely share patient data while maintaining privacy and interoperability between different healthcare systems and databases.

• Perform analytics on claims data, readmission rates and clinical mistakes to identify inefficiencies and improve hospital practices, reducing costs.

• Apply data mining techniques to R&D and clinical trials data to accelerate drug discovery and therapeutic development.

Here are some specific examples of how data is being used to disrupt the healthcare industry:

• Personalized medicine. Companies such as Flatiron Health and Tempus are using data to develop personalized treatment plans for cancer patients. This involves using data from genetic sequencing, imaging, and other sources to identify the best treatment for each individual patient. Flatiron Health aggregates cancer patient data and sells it to researchers to accelerate cancer research and clinical trials.

• Predictive analytics. Companies such as Verily and Zebra Medical Vision are using data to predict patient outcomes and identify potential health risks. This information can be used by doctors to develop preventive care plans and to identify patients who need more intensive monitoring.

• Telemedicine. Companies such as Teladoc and Amwell are using data to provide telemedicine services. This allows patients to see a doctor remotely, without having to travel to a doctor's office.

• Mobile health apps. Apps such as MyFitnessPal and Calm are using data to help people track their health and make lifestyle changes. This can lead to improvements in overall health and well-being.

• Drug discovery. Companies such as DeepMind and Atomwise are using data to accelerate the drug discovery process. This involves using artificial intelligence to analyze large datasets of data to identify potential drug targets and predict the efficacy and safety of new drugs. DeepMind uses its AI system analyzes medical records to predict acute kidney injury and recommend treatment early.

• Oscar Health. Uses data and algorithms to predict patient needs and provide concierge care. This reduces ER visits and hospitalizations.

• Devoted Health. Leverages data to identify high-risk patients and deploys preventative care teams to improve outcomes and lower costs.

• AiCure. Uses AI and computer vision on patient video data to monitor medication adherence and treatment response.

• Precision Medicine. Analyzes genetics and biomarkers to create targeted therapies and treatments customized to patients' biological makeup.

• Atomwise. Screens molecular data to discover new potential medicines by identifying viable drug candidates.

• Nurx. Offers personalized birth control medication prescriptions and monitoring through an app based on patient health data.

• CancerLinQ. Aims to improve quality of care by analyzing vast amounts of cancer care data from providers across the country.

• Zocdoc. Provides booking and patient data tools to improve scheduling, booking rates, and reduce no-shows.

As data becomes more and more abundant and accessible, we can expect to see even more innovative ways to use data to improve healthcare. By taking a data-driven approach, companies can find ways to increase access, lower costs and produce better health outcomes - greatly benefiting patients while disrupting traditional healthcare models.

Per McKinsey, Verily and University of California reports, here are some examples of business impact by using data for healthcare industry disruption:

Predictive analytics for early detection of diseases

Predictive analytics can be used to identify patients who are at high risk of developing certain diseases. This information can then be used to develop preventive care plans or to intervene early, before the disease develops. This can lead to improved patient outcomes and reduced costs for the healthcare system.

For example, a study by Verily found that its predictive analytics model was able to identify patients at high risk of developing heart disease with 90% accuracy. This model was used to develop a preventive care program that reduced the risk of heart disease by 20%. If this preventive care program were implemented across the United States, it could save the healthcare system billions of dollars each year.

Personalized medicine

Personalized medicine uses data from genetic sequencing, imaging, and other sources to develop personalized treatment plans for patients. This can lead to improved patient outcomes and reduced costs for the healthcare system. For example, a study by Flatiron Health found that patients who received personalized treatment for cancer had a 20% higher survival rate than patients who received standard treatment. If personalized medicine were implemented across the United States, it could save the healthcare system billions of dollars each year.

Telemedicine

Telemedicine allows patients to see a doctor remotely, without having to travel to a doctor's office. This can be more convenient and affordable for patients, and it can also reduce costs for the healthcare system. For example, a study by McKinsey found that telemedicine could save the healthcare system in the United States up to $250 billion each year.

Mobile health apps

Mobile health apps can be used to track patients' health, remind them to take medications, and provide other support services. This can lead to improved patient outcomes and reduced costs for the healthcare system. For example, a study by the University of California, San Francisco found that a mobile health app for diabetes management was able to reduce the average blood sugar level of patients by 1%. If this mobile health app were used by all diabetes patients in the United States, it could save the healthcare system billions of dollars each year.

Sash Barige

Sep/08/2019

Photo Credit: Unsplash.com