Posted On:healthcare Archives - AppFerret
It’s quickly becoming apparent that blockchain technology is about far more that just Bitcoin. Across finance, healthcare, media, government and other sectors, innovative uses are appearing every day.
Here is a list of 35 which I have come across. While some may fail to live up to their promises, others could go on to become household names if blockchain proves itself to be as revolutionary as many are predicting.
Guardtime – This company is creating “keyless” signature systems using blockchain which is currently used to secure the health records of one million Estonian citizens.
REMME is a decetralized authentication system which aims to replace logins and passwords with SSL certificates stored on a blockchain.
Gem – This startup is working with the Centre for Disease Control to put disease outbreak data onto a blockchain which it says will increase effectiveness of disaster relief and response.
SimplyVital Health – Has two health-related blockchain products in development, ConnectingCare which tracks the progress of patients after they leave hospital, and Health Nexus, which aims to provide decentralized blockchain patient records.
MedRec – An MIT project involving blockchain electronic medical records designed to manage authentication, confidentiality and data sharing.
ABRA – A cryptocurrency wallet which uses the Bitcoin blockchain to hold and track balances stored in different currencies.
Bank Hapoalim – A collaboration between the Israeli bank and Microsoft to create a blockchain system for managing bank guarantees.
Barclays – Barclays has launched a number of blockchain initiatives involving tracking financial transactions, compliance and combating fraud. It states that “Our belief …is that blockchain is a fundamental part of the new operating system for the planet.”
Maersk – The shipping and transport consortium has unveiled plans for a blockchain solution for streamlining marine insurance.
Aeternity – Allows the creation of smart contracts which become active when network consensus agrees that conditions have been met – allowing for automated payments to be made when parties agree that conditions have been met, for example.
Augur – Allows the creation of blockchain-based predictions markets for trading of derivatives and other financial instruments in a decetralized ecosystem
Manufacturing and industrial
Provenance – This project aims to provide a blockchain-based provenance record of transparency within supply chains.
Jiocoin – India’s biggest conglomerate, Reliance Industries, has said that it is developing a blockchain-based supply chain logistics platform along with its own cryptocurrency, Jiocoin.
Hijro – Previously known as Fluent, aims to create a blockchain framework for collaborating on prototyping and proof-of-concept.
SKUChain – Another blockchain system for allowing tracking and tracing of goods as they pass through a supply chain.
Blockverify – A blockchain platform which focuses on anti-counterfeit measures, with initial use cases in the diamond, pharmaceuticals and luxury goods markets.
Transactivgrid – A business-led community project based in Brooklyn allowing members to locally produce and cell energy, with the goal of reducing costs involved in energy distribution.
STORJ.io – Distributed and encrypted cloud storage, which allows users to share unused hard drive space.
Dubai – Dubai has set sights on becoming the world’s first blockchain-powered state. In 2016 representatives of 30 government departments formed a committee dedicated to investigating opportunities across health records, shipping, business registration and preventing the spread of conflict diamonds.
Estonia – The Estonian government has partnered with Ericsson on an initiative involving creating a new data center to move public records onto the blockchain. 20
South Korea – Samsung is creating blockchain solutions for the South Korean government which will be put to use in public safety and transport applications.
Govcoin – The UK Department of Work and Pensions is investigating using blockchain technology to record and administer benefit payments.
Democracy.earth – This is an open-source project aiming to enable the creation of democratically structured organizations, and potentially even states or nations, using blockchain tools.
Followmyvote.com – Allows the creation of secure, transparent voting systems, reducing opportunities for voter fraud and increasing turnout through improved accessibility to democracy.
Bitgive – This service aims to provide greater transparency to charity donations, and clearer links between giving and project outcomes. It is working with established charities including Save The Children, The Water Project and Medic Mobile.
OpenBazaar – OpenBazaar is an attempt to build a decentralized market where goods and services can be traded with no middle-man.
Loyyal – This is a blockchain-based universal loyalty framework, which aims to allow consumers to combine and trade loyalty rewards in new ways, and retailers to offer more sophisticated loyalty packages.
Blockpoint.io – Allows retailers to build payment systems around blockchain currencies such as Bitcoin, as well as blockchain derived gift cards and loyalty schemes.
Ubiquity – This startup is creating a blockchain-driven system for tracking the complicated legal process which creates friction and expense in real estate transfer.
Transport and Tourism
IBM Blockchain Solutions – IBM has said it will go public with a number of non-finance related blockchain initiatives with global partners in 2018. This video envisages how efficiencies could be driven in the vehicle leasing industry.
Arcade City – An application which aims to beat Uber at their own game by moving ride sharing and car hiring onto the blockchain.
La’Zooz – A community-owned platform for synchronizing empty seats with passengers in need of a lift in real-time.
Webjet – The online travel portal is developing a blockchain solution to allow stock of empty hotel rooms to be efficiently tracked and traded , with payment fairly routed to the network of middle-men sites involved in filling last-minute vacancies.
Kodak – Kodak recently sent its stock soaring after announcing that it is developing a blockchain system for tracking intellectual property rights and payments to photographers.
Ujomusic – Founded by singer songwriter Imogen Heap to record and track royalties for musicians, as well as allowing them to create a record of ownership of their work.
It is exiting to see all these developments. I am sure not all of these will make it into successful long-term ventures but if they indicate one thing, then it is the vast potential the blockchain technology is offering.
Original article here.
Driven by specialised analytics systems and software, big data analytics has decreased the time required to double medical knowledge by half, thus compressing healthcare innovation cycle period, shows the much discussed Mary Meeker study titled Internet Trends 2017.
The presentation of the study is seen as an evidence of the proverbial big data-enabled revolution, that was predicted by experts like McKinsey and Company. “A big data revolution is under way in health care. Over the last decade pharmaceutical companies have been aggregating years of research and development data into medical data bases, while payors and providers have digitised their patient records,” the McKinsey report had said four years ago.
The Mary Meeker study shows that in the 1980s it took seven years to double medical knowledge which has been decreased to only 3.5 years after 2010, on account of massive use of big data analytics in healthcare. Though most of the samples used in the study were US based, the global trends revealed in it are well visible in India too.
“Medicine and underlying biology is now becoming a data-driven science where large amounts of structured and unstructured data relating to biological systems and human health is being generated,” says Dr Rohit Gupta of MedGenome, a genomics driven research and diagnostics company based in Bengaluru.
Dr Gupta told Firstpost that big data analytics has made it possible for MedGenome, which focuses on improving global health by decoding genetic information contained in an individual genome, to dive deeper into genetics research.
“While any individual’s genome information is useful for detecting the known mutations for diseases, underlying new patterns of complicated diseases and their progression requires genomics data from many individuals across populations — sometimes several thousands to even few millions amounting to exabytes of information,” he said.
All of which would have been a cumbersome process without the latest data analytics tools that big data analytics has brought forth.
The company that started work on building India-specific baseline data to develop more accurate gene-based diagnostic testing kits in the year 2015 now conducts 400 genetic tests across all key disease areas.
What is Big Data
According to Mitali Mukerji, senior principal scientist, Council of Scientific and Industrial Research when a large number of people and institutions digitally record health data either in health apps or in digitised clinics, these information become big data about health. The data acquired from these sources can be analysed to search for patterns or trends enabling a deeper insight into the health conditions for early actionable interventions.
Big data is growing bigger
But big data analytics require big data. And proliferation of Information technology in the health sector has enhanced flow of big data exponentially from various sources like dedicated wearable health gadgets like fitness trackers and hospital data base. Big data collection in the health sector has also been made possible because of the proliferation of smartphones and health apps.
The Meeker study shows that the download of health apps have increased worldwide in 2016 to nearly 1,200 million from nearly 1,150 million in the last year and 36 percent of these apps belong to the fitness and 24 percent to the diseases and treatment ones.
Health apps help the users monitor their health. From watching calorie intake to fitness training — the apps have every assistance required to maintain one’s health. 7 minute workout, a health app with three million users helps one get that flat tummy, lose weight and strengthen the core with 12 different exercises. Fooducate, another app, helps keep track of what one eats. This app not only counts the calories one is consuming, but also shows the user a detailed breakdown of the nutrition present in a packaged food.
For Indian users, there’s Healthifyme, which comes with a comprehensive database of more than 20,000 Indian foods. It also offers an on-demand fitness trainer, yoga instructor and dietician. With this app, one can set goals to lose weight and track their food and activity. There are also companies like GOQii, which provide Indian customers with subscription-based health and fitness services on their smartphones using fitness trackers that come free.
Dr Gupta of MedGenome explains that data accumulated in wearable devices can either be sent directly to the healthcare provider for any possible intervention or even predict possible hospitalisation in the next few days.
The Meeker study shows that global shipment of wearable gadgets grew from 26 million in 2014 to 102 million in 2016.
Another area that’s shown growth is electronic health records. In the US, electronic health records in office-based physicians in United States have soared from 21 percent in 2004 to 87 percent in 2015. In fact, every hospital with 500 beds (in the US) generate 50 petabytes of health data.
Back home, the Ministry of Electronics and Information Technology, Government of India, runs Aadhar-based Online Registration System, a platform to help patients book appointments in major government hospitals. The portal has the potential to emerge into a source if big data offering insights on diseases, age groups, shortcomings in hospitals and areas to improve. The website claims to have already been used to make 8,77,054 appointments till date in 118 hospitals.
On account of permeation of digital technology in health care, data growth has recorded 48% growth year on year, the Meeker study says. The accumulated mass of data, according to it, has provided deeper insights in health conditions. The study shows drastic increase of citations from 5 million in 1977 to 27 million in 2017. Easy access to big data has ensured that scientists can now direct their investigations following patterns analysed from such information and less time is required to arrive at conclusion.
“If a researcher has huge sets of data at his disposal, he/she can also find out patterns and simulate it through machine learning tools, which decreases the time required to arrive at a conclusion. Machine learning methods become more robust when they are fed with results analysed from big data,” says Mukerji.
She further adds, “These data simulation models, rely on primary information generated from a study to build predictive models that can help assess how human body would respond to a given perturbation,” says Mukerji.
The Meeker also study shows that Archimedes data simulation models can conduct clinical trials from data related to 50,000 patients collected over a period of 30 years, in just a span of two months. In absence of this model it took seven years to conduct clinical trials on data related to 2,838 patients collected over a period of seven years.
As per this report in 2016 results of 25,400 number of clinical trial was publically available against 1,900 in 2009.
The study also shows that data simulation models used by laboratories have drastically decreased time required for clinical trials. Due to emergence of big data, rise in number of publically available clinical trials have also increased, it adds.
Big data in scientific research
The developments grown around big-data in healthcare has broken the silos in scientific research. For example, the field of genomics has taken a giant stride in evolving personalised and genetic medicine with the help of big data.
A good example of how big data analytics can help modern medicine is the Human Genome Project and the innumerous researches on genetics, which paved way for personalised medicine, would have been difficult without the democratisation of data, which is another boon of big data analytics. The study shows that in the year 2008 there were only 5 personalised medicines available and it has increased to 132 in the year 2016.
In India, a Bangalore-based integrated biotech company recently launched ‘Avestagenome’, a project to build a complete genetic, genealogical and medical database of the Parsi community. Avestha Gengraine Technologies (Avesthagen), which launched the project believes that the results from the Parsi genome project could result in disease prediction and accelerate the development of new therapies and diagnostics both within the community as well as outside.
MedGenome has also been working on the same direction. “We collaborate with leading hospitals and research institutions to collect samples with research consent, generate sequencing data in our labs and analyse it along with clinical data to discover new mutations and disease causing perturbations in genes or functional pathways. The resultant disease models and their predictions will become more accurate as and when more data becomes available.”
Mukerji says that democratisation of data fuelled by proliferation of technology and big data has also democratised scientific research across geographical boundaries. “Since data has been made easily accessible, any laboratory can now proceed with research,” says Mukerji.
“We only need to ensure that our efforts and resources are put in the right direction,” she adds.
Challenges with big data
But Dr Gupta warns that big-data in itself does not guarantee reliability for collecting quality data is a difficult task.
Moreover, he said, “In medicine and clinical genomics, domain knowledge often helps and is almost essential to not only understand but also finding ways to effectively use the knowledge derived from the data and bring meaningful insights from it.”
Besides, big data gathering is heavily dependent on adaptation of digital health solutions, which further restricts the data to certain age groups. As per the Meeker report, 40 percent of millennial respondents covered in the study owned a wearable. On the other hand 26 percent and 10 percent of the Generation X and baby boomers, respectively, owned wearables.
Similarly, 48 percent millennials, 38 percent Generation X and 23 percent baby boomers go online to find a physician. The report also shows that 10 percent of the people using telemedicine and wearable proved themselves super adopters of the new healthcare technology in 2016 as compared to 2 percent in 2015.
Collection of big data.
Every technology brings its own challenges, with big data analytics secure storage and collection of data without violating the privacy of research subjects, is an added challenge. Something, even the Meeker study does not answer.
“Digital world is really scary,” says Mukerji.
“Though we try to secure our data with passwords in our devices, but someone somewhere has always access to it,” she says.
The health apps which are downloaded in mobile phones often become the source of big-data not only for the company that has produced it but also to the other agencies which are hunting for data in the internet. “We often click various options while browsing internet and thus knowingly or unknowingly give a third party access to some data stored in the device or in the health app,” she adds.
Dimiter V Dimitrov a health expert makes similar assertions in his report, ‘Medical Internet of Things and Big Data in Healthcare‘. He reports that even wearables often have a server which they interact to in a different language providing it with required information.
“Although many devices now have sensors to collect data, they often talk with the server in their own language,” he said in his report.
Even though the industry is still at a nascent stage, and privacy remains a concern, Mukerji says that agencies possessing health data can certainly share them with laboratories without disclosing patient identity.
Original article here.
The transformation of the healthcare industry has begun. While it will take many years, the shake-up in patient, provider and payer processes and analytics systems will leave the industry profoundly different.
On the horizon is a much more cost-efficient healthcare industry that offers truly personalized healthcare. Providers and patients will be able to leverage the ever-increasing medical knowledgebase and combine that with patient-specific historical and real-time data, including genetics, lifestyle behavior and environmental data.
The adoption of Internet of Things (IoT) networks, the data collected and the analytics of that data are accelerating the transformation of the healthcare industry.
Facts to consider
- The global IoT healthcare market is expected to grow from $32.47 billion in 2015 to $163.24 billion by 2020.
- IoT-enabled connectivity within hospital labs will increase total global laboratory test throughput by more than 3.02 billion diagnostic tests over the next 5 year.
- The value of improved health of chronic disease patients through remote monitoring could be as much as $1.1 trillion per year in 2025.
- Four million patients globally will remotely monitor their health conditions by 2020.
- Consumers utilizing home health technologies will increase from 14.3 million worldwide in 2014 to 78.5 million by 2020.
Over the next few years, patient monitoring devices will improve, and providers will increasingly implement IoT and big data analytics solutions. As a result, the global IoT healthcare market will grow at a significant rate.
Trends to watch
The following are some trends I am watching in 2016. Many are interrelated, and some are longer term than others. But all will be important to watch over the next 12 months.
- Consumer-driven healthcare. Consumers are taking more responsibility for their own heath. As they do, they will demand better access to their data and improved health technology solutions that allow them to manage their own healthcare.
- Digital healthcare transformation. Data from IoT devices, including hospital room sensors, lab equipment, employee wearables and patient monitoring devices will enable the industry to accelerate the transformation to digital. This transformation will cut healthcare costs and improve patient experiences and outcomes. Providers will increasingly look to analytics to provide predictive and prescriptive capabilities, dramatically improving the ability of healthcare providers to help patients. Payers will leverage that data to control costs and optimize patient healthcare outcomes.
- Key solution areas. Look for improvements in IoT solutions related to remote patient monitoring services, mobile health technologies, telemedicine, medication management, clinical operations, employee workflow management and inpatient monitoring.
- Extracting insights from all the data. The amount of healthcare-related data available within the industry is growing exponentially. The IoT will result in an increased flow of data for patient records, population health data and other databases, bringing a new complexity to provider and physician operations. Too much data can overload those providing care and distract them from their mission of treating patients. Providers will seek help from professional IoT services firms to help them develop processes and IoT platforms that can extract insights from many data sources.
- Remote patient monitoring. Expect new remote patient monitoring devices, wearable clothing and smartphone apps that analyze the data collected. We are at the beginning of a new era of remote patient monitoring that will automatically feed patient records with real-time data, perform analysis and send coaching notifications to both providers and patients. This will make healthcare easier, convenient, 24/7, web-enabled and personalized.
- Providers begin shift toward remote healthcare. As consumers adopt remote monitoring devices, providers will restructure in order to provide remote medical care services and solutions. New processes, roles, and skills will be required. Larger providers will offer healthcare cognitive diagnostic and coaching mobile apps for patients to use remotely.
- Creating baseline and benchmark databases. IoT emerges as a key data capture point to establish a common baseline of data for care teams to utilize when comparing treatment options. Teams of providers will leverage historical data and analytics to treat patients who have similar symptoms or diagnoses as those in the baseline data.
- Patient centered analytics. Expect more focus on using advanced analytics, visualizations and decision support tools (e.g., Watson) to improve diagnostic accuracy. Both provider and patient versions of these tools should emerge. Treatments will become more precise, effective and personalized.
- Cognitive coaching apps. Look for providers to begin releasing mobile apps that patients can use for healthcare and wellness coaching. Patients will increasingly demand these cognitive era apps, which will leverage data collected by wearables and information found in electronic health records. These apps will provide patients with personalized strategies to combat illness and behaviors in order to maintain a healthy lifestyle and manage their own health.
- Government regulations. Governments will lay out guidelines for how medical apps (those apps that make medical recommendations and affect treatments of various diseases) will be regulated.
- Better component technology. Innovation in IoT solution and network components (e.g., smaller sensors, faster CPUs at lower cost) and wearable medical devices will bring cheaper, more advanced medical devices that are much more accurate and can transmit many new health measurements to electronic health records.
- Device interoperability and data integration. Analytics adoption in healthcare is closely tied to the ease with which disparate structured and unstructured data sources can be integrated and leveraged for data-driven decision making. As the number of medical-related IoT connected devices grows, the key challenge will be to ensure that data from all these devices can be read into big data platforms and then easily integrated into analytics solutions.
- Security and privacy issues. IoT and wearable sensors are increasingly collecting patient specific data. The healthcare industry, vendors and governments need to figure out how to ensure all this private and personal data is secured appropriately. This is a significant challenge and one that will require collaboration from all involved parties.
- Sharing of patient data. While security and privacy of patient healthcare records are critical, the fact is patients see multiple providers. Information must be shared across multiple providers in order to result in proper diagnosis, treatment and ongoing effective decision making. Sharing of information electronically can also serve to improve cost efficiencies throughout the healthcare system.
- Integration of research, operational and IT analytics. Look for increased requirements to integrate data from many different internal and external sources. Researchers, business execs, doctors and IT professionals will collaborate to provide better overall care to patients. Vendors will increase their focus on integrating platforms, applications and data.
- IoT for the hospital. Leading hospitals will develop long-term strategies to leverage sensors and wearables throughout their operations in order to build a real-time sense-and-respond intelligent operation that cuts costs and improves patient experiences and outcomes. Researchers, nurses and doctors will spend less time doing administrative work and more time with patients.
- Skills gap. As the industry transforms toward digital, healthcare organizations will realize they don’t have all the data and analytics skills that are required. Competition for top-tier data scientists and related talent will remain a pervasive industry pain point for healthcare providers and payer organizations.
- Leadership challenges. There is a growing need for data-driven vision and leadership in the executive ranks within the healthcare industry. The industry needs executives who understand the value that IoT and analytics will bring to the industry. Vendors can help push this transformation with an increased focus on the benefits of analytics.
As you can see, a lot will be happening in 2016 around the intersection of healthcare and the IoT. Key drivers will be an increasing demand for advanced healthcare information systems that can cut costs and drive improved patient-centered care.
- Goldman Sachs: The Digital Revolution comes to US Healthcare
- HIMSS: 3 Ways the Internet of Things Is Improving Healthcare
- Hospitals and health networks: How The Internet of Things Will Affect Health Care
- Information Age: How to plan a hospital environment for the Internet of Things
- IBM: The future of connected health devices
- IBM CAI: Stories from data leaders
Original article here.