The team behind the services are experts at healthcare, as they also run Patient.Info, one of the most popular medical websites in the UK. More than 100 million people logged on to the site in 2018 to read articles about healthcare, check symptoms and learn to live a healthier life, and more than 60% of GPs in England have access to it.
They also produce a newsletter that’s sent to 750,000 subscribers and around 2,000 leaflets on health conditions and 850 on medicines.
People can access Patient.Info 24 hours a day, seven days a week. It’s the same for Patient Access but web traffic spikes every morning when people want to book appointments to see their GP. To handle that demand, Patient Access runs on Microsoft’s Azure cloud platform. As well as being reliable and stable, all patient data is protected by a high level of security – Microsoft employs more than 3,500 dedicated cybersecurity professionals to help protect, detect and respond to threats, while segregated networks and integrated security controls add to the peace of mind.
“About 62% of GP practices use Patient Access,” says Sarah Jarvis MBE, the Clinical Director behind the service. “They’re using it to manage their services, manage appointments, take in repeat medications, consolidate a patient’s personal health record and even conduct video consultations.
“Just imagine your GP being able to conduct video consultations. If you’re aged 20 to 39 you might not want or need to have a relationship with a GP because you don’t need that continuity of care.
“But imagine you are elderly and housebound, and a district nurse visits you. They phone your GP and say: ‘Could you come and visit this patient’, but the GP is snowed under and can’t get there for a couple of hours. The district nurse is also very busy and must visit someone else.
“Now, with Patient Access, a Duty Doctor can look at someone’s medical record and do a video consultation in five minutes. If the patient needs to be referred, the GP can do it there and then from inside the system. The possibilities are endless, and older people, especially, have so much to gain from this.”
For years, patient data management meant one thing—secure the data. Now, healthcare leaders must protect and openly share the data with patients and with other healthcare organizations to support quality of care, patient safety, and cost reduction. As data flows more freely, following the patient, there’s less risk of redundant testing that increases cost and waste. Legacy infrastructure and cybersecurity concerns stand on the critical path to greater interoperability and patient record portability. Learn how Microsoft 365 can help.
Impact of regulatory changes and market forces
Regulatory changes are a big driver for this shift. Through regulations like the 21st Century Cures Act in the United States, healthcare organizations are required to improve their capabilities to protect and share patient data. The General Data Protection Regulation (GDPR) in the European Union expands the rights of data subjects over their data. Failing to share patient data in an effective, timely, and secure manner can result in significant penalties for providers and for healthcare payors.
Market forces are another driver of this shift as consumers’ expectations of omni-channel service and access spill over to healthcare. This augurs well for making the patient more central to data flows.
There are unintended consequences, however. The increasing need to openly share data creates new opportunities for hackers to explore, and new risks for health organizations to manage.
It’s more important than ever to have a data governance and proactive cybersecurity strategy that enables free data flow with an optimal security posture. In fact, government regulators will penalize healthcare organizations for non-compliance—and so will the marketplace.
How Microsoft 365 can prepare your organization for the journey ahead
Modernizing legacy systems and processes is a daunting, expensive task. Navigating a digitized but siloed information system is costly, impedes clinician workflow, and complicates patient safety goals.
To this end, Microsoft Teams enables the integration of electronic health record information and other health data, allowing care teams to communicate and collaborate about patient care in real-time. Leading interoperability partners continue to build the ability to integrate electronic health records into Teams through a FHIR interface. With Teams, clinical workers can securely access patient information, chat with other team members, and even have modern meeting experiences, all without having to switch between apps.
Incomplete data and documentation are among the biggest sources of provider and patient dissatisfaction. Clinicians value the ability to communicate with each other securely and swiftly to deliver the best informed care at point of care.
Teams now offers new secure messaging capabilities, including priority notifications and message delegation, as well as a smart camera with image annotation and secure sharing, so images stay in Teams and aren’t stored to the clinician’s device image gallery.
What about cybersecurity and patient data? As legacy infrastructure gives way to more seamless data flow, it’s important to protect against a favorite tactic of cyber criminals—phishing.
Phishing emails—weaponized emails that appear to come from a reputable source or person—are increasingly difficult to detect. As regulatory pressure mounts within healthcare organizations to not “block” access to data, the risk of falling for such phishing attacks is expected to increase. To help mitigate this trend, Office 365 Advanced Threat Protection (ATP) has a cloud-based email filtering service with sophisticated anti-phishing capabilities.
For example, Office 365 ATP provides real-time detonation capabilities to find and block unknown threats, including malicious links and attachments. Links in email are continuously evaluated for user safety. Similarly, any attachments in email are tested for malware and unsafe attachments are removed.
For example, if a user or device sign-in is tagged as high-risk, Azure AD can automatically enforce conditional access policies that can limit or block access or require the user to re-authenticate via MFA. Benefitting from the integrated signals of the Microsoft Intelligent Security Graph, Microsoft 365 solutions look holistically at the user sign-in behavior over time to assess risk and investigate anomalies where needed.
When faced with the prospect of internal leaks, Supervision in Microsoft 365 can help organizations monitor employees’ communications channels to manage compliance and reduce reputational risk from policy violations. As patient data is shared, tracking its flow is essential. Audit log and alerts in Microsoft 365 includes several auditing and reporting features that customers can use to track certain activity such as changes made to documents and other items.
Using the retention policies of Advanced Data Governance, you can retain core business records in unalterable, compliant formats. With records management capabilities, your core business records can be properly declared and stored with full audit visibility to meet regulatory obligations.
Healthcare leaders must adapt quickly to market and regulatory expectations regarding data flows. Clinical and operations leaders depend on data flowing freely to make data-driven business and clinical decisions, to understand patterns in patient care and to constantly improve patient safety, quality of care, and cost management.
Microsoft 365 helps improve workflows through the integration power of Teams, moving the right data to the right place at the right time. Microsoft 365 also helps your security and compliance posture through advanced capabilities that help you manage and protect identity, data, and devices.
Microsoft 365 is the right cloud platform for you in this new era of patient data protection—and data sharing. Check out the Microsoft 365 for health page to learn more about how Microsoft 365 and Teams can empower your healthcare professionals in a modern workplace.
Social determinants of health data can help healthcare organizations deliver better patient care, but the challenge of knowing exactly how to use the data persists.
The healthcare community has long-recognized the importance of a patient’s social and economic data, said Josh Schoeller, senior vice president and general manager of LexisNexis Health Care at LexisNexis Risk Solutions. The current shift to value-based care models, which are ruled by quality rather than quantity of care, has put a spotlight on this kind of data, according to Schoeller.
But social determinants of health also pose a challenge to healthcare organizations. Figuring out how to use the data in meaningful ways can be daunting, as healthcare organizations are already overwhelmed by loads of data.
A new framework, released last month, by the not-for-profit eHealth Initiative Foundation, could help. The framework was developed by stakeholders, including LexisNexis Health Care, to give healthcare organizations guidance on how to use social determinants of health data ethically and securely.
Here’s a closer look at the framework.
Use cases for social determinants of health data
The push to include social determinants of health data into the care process is “imperative,” according to eHealth Initiative’s framework. Doing so can uncover potential risk factors, as well as gaps in care.
The eHealth Initiative’s framework outlines five guiding principles for using social determinants of health data.
Determine if a patient has access to transportation or is food is insecure, according to the document. The data can also help a healthcare organization coordinate with community health workers and other organizations to craft individualized care plans.
Using analytics to uncover health and wellness risks
Use social determinants of health data to predict a patient’s future health outcomes. Analyzing social and economic data can help the provider know if an individual is at an increased risk of having a negative health outcome, such as hospital re-admittance. The risk score can be used to coordinate a plan of action.
Mapping community resources and identifying gaps
Use social determinants of health data to determine what local community resources exist to serve the patient populations, as well as what resources are lacking.
Assessing service and impact
Monitor care plans or other actions taken using social determinants of health data and how it correlates to health outcomes. Tracking results can help an organization adjust interventions, if necessary.
Customizing health services and interventions
Inform patients about how social determinants of health data are being used. Healthcare organizations can educate patients on available resources and agree on next steps to take.
Getting started: A how-to for healthcare organizations
The eHealth Initiative is not alone in its attempt to move the social determinants of health data needle.
Niki Buchanan, general manager of population health at Philips Healthcare, has some advice of her own.
Lean on the community health assessment
Buchanan said most healthcare organizations conduct a community health assessment internally, which provides data such as demographics and transportation needs, and identifies at-risk patients. Having that data available and knowing whether patients are willing or able to take advantage of community resources outside of the doctor’s office is critical, she said.
Niki BuchananGeneral manager of population health management, Philips Healthcare
Connect the community resource dots
Buchanan said a healthcare organization should be aware of what community resources are available to them, whether it’s a community driving service or a local church outreach program. The organization should also assess at what level it is willing to partner with outside resources to care for patients.
“Are you willing to partner with the Ubers of the world, the Lyfts of the world, to pick up patients proactively and make sure they make it to their appointment on time and get them home,” she said. “Are you able to work within the local chamber of commerce to make sure that any time there’s a food market or a fresh produce kind of event within the community, can you make sure the patients you serve have access?”
Buchanan said healthcare organizations should approach social determinants of health data with the patient in mind. She recommended healthcare organizations start small with focused groups of patients, such as diabetics or those with other chronic conditions, but that they also ensure the investment is a worthwhile one.
“Look for things that meet not only your own internal ROI in caring for your patients, but that also add value and patient engagement opportunities to those you’re trying to serve in a more proactive way,” she said.
In a value-based care world, population health takes center stage.
The healthcare industry is slowly moving away from traditionalfee-for-service models, where healthcare providers are reimbursed for the quantity of services rendered, and toward value-based care, which focuses on the quality of care provided. The shift in focus on quality versus quantity also shifts a healthcare organization’s focus to more effectively manage high-risk patients.
Making the shift to value-based care and better care management means looking at new data sources — the kind healthcare organizations won’t get just from the lab.
In this Q&A, David Nace, chief medical officer for San Francisco-based healthcare technology and data analytics company Innovaccer Inc., talks about how the company is applying AI and machine learning to patient data — clinical and nonclinical — to predict a patient’s future cost of care.
Doing so enables healthcare organizations to better allocate their resources by focusing their efforts on smaller groups of high-risk patients instead of the patient population as a whole. Indeed, Nace said the company is able to predict the likelihood of an individual experiencing a high-cost episode of care in the upcoming year with 52% accuracy.
David Nace: You can’t do anything at all around understanding a population or an individual without being able to understand the data. We all talk about data being the lifeblood of everything we want to accomplish in healthcare.
What’s most important, you’ve got to take data in from multiple sources — claims, clinical data, EHRs, pharmacy data, lab data and data that’s available through health information exchanges. Then, also [look at] nontraditional, nonclinical forms of data, like social media; or local, geographic data, such as transportation, environment, food, crime, safety. Then, look at things like availability of different community resources. Things like parks, restaurants, what we call food deserts, and bring all that data into one place. But none of that data is standardized.
How does Innovaccer implement and use machine learning algorithms in its prediction model?
Nace: Most of that information I just described — all the data sources — there are no standards around. So, you have to bring that data in and then harmonize it. You have to be able to bring it in from all these different sources, in which it’s stored in different ways, get it together in one place by transforming it, and then you have to harmonize the data into a common data model.
We’ve done a lot of work around that area. We used machine learning to recognize patterns as to whether we’ve seen this sort of data before from this kind of source, what do we know about how to transform it, what do we know about bringing it into a common data model.
Lastly, you have to be able to uniquely identify a cohort or an individual within that massive population data. You bring all that data together. You have to have a unique master patient index, and that’s been very difficult, because, in this country, we don’t have a national patient identifier.
We use machine learning to bring all that data in, transform it, get it into a common data model, and we use some very complex algorithms to identify a unique patient within that core population.
How did you develop a risk model to predict an individual’s future cost of care?
David NaceChief medical officer, Innovaccer
Nace: There are a couple of different sources of risk. There’s clinical risk, [and] there’s social, environmental and financial risk. And then there’s risk related to behavior. Historically, people have looked at claims data to look at the financial risk in kind of a rearview-mirror approach, and that’s been the history of risk detection and risk management.
There are models that the government uses and relies on, like CMS’ Hierarchical Condition Category [HCC] scoring, relying heavily on claims data and taking a look at what’s happened in the past and some of the information that’s available in claims, like diagnosis, eligibility and gender.
One of the things we wanted to do is, with all that data together, how do you identify risk proactively, not rearview mirror. How do you then use all of this new mass of data to predict the likelihood that someone’s going to have a future event, mostly cost? When you look at healthcare, everybody is concerned about what is the cost of care going to be. If they go back into the hospital, that’s a cost. If they need an operation, that’s a cost.
Why is predicting individual risk beneficial to a healthcare organization moving toward value-based care?
Nace: Usually, risk models are used for rearview mirror for large population risk. When the government goes to an accountable care organization or a Medicare Advantage plan and wants to say how much risk is in here, it uses the HCC model, because it’s good at saying what’s the risk of populations, but it’s terrible when you go down to the level of an individual. We wanted to get it down to the level of an individual, because that’s what humans work with.
How do social determinants of health play a role in Innovaccer’s future cost of care model?
Nace: We’ve learned in healthcare that the demographics of where you live, and the socioeconomic environment around you, really impact your outcome of care much more than the actual clinical condition itself.
As a health system, you’re starting to understand this, and you don’t want people to come back to the hospital. You want people to have good care plans that are highly tailored for them so they’re adherent, and you want to have effective strategies for managing care coordinators or managers.
Now, we have this social vulnerability index that we have a similar way of using AI to test against a population, reiterate multiple forms of regression analysis and come up with a highly specific approach to detecting the social vulnerability of that patient down to the level of a ZIP code around their economic and environmental risk. You can pull data off an API from Google Maps that shows food sources, crime rates, down to the level of a ZIP code. All that information, transportation methods, etc., we can integrate that with all that other clinical data in that data model.
We can now take a vaster amount of data that will not only get us that clinical risk, but also the social, environmental and economic risk. Then, as a health system, you can deploy your resources carefully.
Editor’s note:Responses have been edited for brevity and clarity.
One expert says the $2 million in funding ONC is offering developers to address interoperability challenges in healthcare — although commendable — may not be enough.
“I applaud ONC for recognizing this challenge and making funds available for development of interoperability platforms and solutions,” said John McDaniel, senior vice president of innovation and technology for health IT consulting firm The HCI Group. “However, based on the work we have done with vendors that offer interoperability solutions, I don’t believe $2 million will address the issue.”
ONC funding offered in two areas
ONC will provide up to $2 million in funding to two recipients focused on developing innovative and breakthrough advances in two areas: expanding the scope of population-level data-focused application programming interfaces (APIs) and advancing clinical knowledge at the point of care, according to ONC.
For expanding the scale of APIs, ONC wants to see projects that reduce provider burdens associated with reporting through API technology, as well as assessing trade-offs associated with various big data formats and challenges to the scope of FHIR-based APIs.
As for advancing clinical knowledge at the point of care, ONC hopes to see “emerging innovations” in clinical medicine, as well as data-driven medicine infrastructure and legal and policy implications for innovative approaches, according to the ONC news release.
Additional funding may be available
ONC will fund up to $1 million per area of interest by 2019. After the funds are awarded, there will be a two-year project and budget period, but applicants are encouraged to submit responses based on a five-year project and budget period because additional funding for three to five years could be provided based on the availability of funds and “meaningful progress.”
John McDanielsenior vice president of innovation and technology, The HCI Group
The funding opportunity will be open for three years, allowing for the possibility that ONC will issue additional awards to other eligible applicants for future “priority areas of interest.”
ONC expects the funding to “further a new generation of health IT development and inform the innovative implementation and refinement of standards, methods and techniques for overcoming major barriers and challenges as they are identified.” Though he questions whether $2 million will be enough to address interoperability challenges in healthcare, McDaniel said he has seen ONC be successful with similar initiatives in the past, such as establishing incentives to motivate healthcare organizations to implement EHRs, which enabled the digitization of patient care documentation.
The full scope of interoperability challenges in healthcare
Now, McDaniel said, the challenge is to enable full interoperability to not only digitize retrospective patient data, but to “capture and use real-time patient information coupled with cognitive computing to assist care providers with decision-making and best practices given the full view of all relevant patient data.”
“Developing interoperability between EHR’s is a good start, but since only a percentage of relevant retrospective patient data is maintained in those systems, we need to establish interoperability standards for dynamic exchange of data from all source systems, including IoT, EHR’s medical devices, personal health devices, etc., to enable precision and predictive care models,” McDaniel said.
In the ongoing battle to make healthcare data ubiquitous, the U.S. Digital Service for the Department of Health and Human Services has developed a new API, Blue Button 2.0, aimed at sharing Medicare claims information.
Blue Button 2.0 is part of an API-first strategy within HHS’ Centers for Medicare and Medicaid Services, and it comes at a time when a number of major companies, including Apple, have embraced the potential of healthcare APIs. APIs are the building blocks of applications and make it easier for developers to create software that can easily share information in a standardized way. Like Apple’s Health Records API, Blue Button 2.0 is based on a widely accepted healthcare API standard known as Fast Healthcare Interoperability Resources, or FHIR.
Blue Button 2.0 is the API gateway to 53 million Medicare beneficiaries, including comprehensive part A, B and D data. “We’re starting to recognize that claims data has value in understanding the places a person has been in the healthcare ecosystem,” said Shannon Sartin, executive director of the U.S. Digital Service at HHS.
“But the problem is, how do you take a document that is mostly codes with very high-level information that’s not digestible and make it useful for a nonhealth-savvy individual? You want a third-party app to add value to that information,” Sartin said.
To date, over 500 developers are working with the new API to develop applications that bring claims data to consumers, providers, hospitals and, ultimately, into an EHR, Sartin said. But while there is a lot of interest, Sartin said this is just the first step when it comes to healthcare APIs.
“The government does not build products super well, and it does not do the marketing engagement necessary to get someone interested in using it,” she said. “We’re taking a different approach, acting as evangelists, and we’re spending time growing the community.”
And while a large number of developers are experimenting with Blue Button 2.0, Sartin’s group will be heavily vetting to eventually get to a much smaller number that will release applications due to privacy concerns around the claims data.
Looking for a user-friendly approach
Shannon Sartinexecutive director of the U.S. Digital Service at HHS
In theory, the applications will make it easier for a Medicare consumer to let third parties access their claims information and then, in turn, make that data meaningful and actionable. But Arielle Trzcinski, senior analyst serving application development and delivery at Forrester Research, said she is concerned Blue Button 2.0 isn’t pushing the efforts around healthcare APIs far enough.
“Claims information is not the full picture,” she said. “If we’re truly making EHR records portable and something the consumer can own, you have to have beneficiaries download their medical information. That’s great, but how are they going to share it? What’s interesting about the Apple effort as a consumer is that you’re able to share that information with another provider. And it’s easy, because it’s all on your phone. I haven’t seen from Medicare yet how they might do it in the same user-friendly way.”
Sartin acknowledged Blue Button 2.0 takes aim at just a part of the bigger problem.
“My team is focused just on CMS and healthcare in a very narrow way. We recognize there are broader data and healthcare issues,” she said.
But when it comes to the world of healthcare APIs, it’s important to take that first step. And it’s also important to remember the complexity of the job ahead, something Sartin said her team — top-notch developers from private industry who chose government service to help — realized after they jumped in to the world of healthcare APIs.
“We have engineers who’ve not worked in healthcare who thought the FHIR standard was overly complex,” she said. “But when you start to dig in to the complexity of health data, you recognize sharing health data with each doctor means something different. This is not as seamless as with banks that can standardize on numbers. There, a one is a one. But in health terminology, a one can mean 10 different things. You can’t normalize it. Having an outside perspective forces the health community to question it all.”
Mirembe, 24, lives in a rural village in north-east Uganda, where access to healthcare is limited. Mirembe is pregnant and walks, cradling her swollen belly and fanning herself from the heat, 15 kilometres to the closest clinic to check on her unborn child.
Hundreds of expectant mothers, elderly men and women, and sickly children line the corridors of the clinic patiently awaiting medical attention. Midwives and nurses are few, and they wearily dart from patient to patient doing what they can to help. Mirembe will wait six hours to be attended to.
When she’s finally seen, she’s told the clinic doesn’t have an ultrasound machine. If she wants to have an ultrasound, she must travel to the Mulago Hospital in Kampala, Uganda’s largest public hospital, where she must pay 20,000 Ugandan shillings, equivalent to about US$5, for a prenatal visit. In this part of the world, that is a significant amount of money.
According to the World Health Organisation (WHO), about 830 women die from pregnancy or childbirth-related complications around the world every day. It’s estimated that in 2015, roughly 303 000 women died during and after pregnancy and childbirth. Many of these deaths were in low-resource locations like Uganda, and most could have been prevented.
However, technology is helping to eliminate some of the challenges of distance and lack of trained medical staff. Mirembe can now hear her unborn child’s heartbeat from the comfort of her own home through an innovative app call WinSenga, which reassures her that both she and her baby are healthy.
WinSenga is a mobile tool, supported by Microsoft technologies, which helps mothers with prenatal care. The idea was conceived when the Microsoft Imagine Cup competition inspired then-university students Okello and Aaron Tushabe to use their computer science skills to tackle some of Africa’s biggest problems. They were motivated by the plight of mothers like Mirembe who live outside the reach of modern medical care.
The handheld device scans the womb of a pregnant woman and reports foetal weight, position, breathing patterns, gestational age, and heart rate. The app makes use of a trumpet-shaped device and a microphone which transmits the data to a smart phone. The mobile application plays the part of the nurse’s ear and recommends a course of action. The analysis and recommendations are uploaded to the cloud and can be accessed by a doctor anywhere.
This is just one example of how Africa, a continent that bears one-quarter of the global disease burden but only has two percent of the world’s doctors, could outperform developed nations’ healthcare systems by leapfrogging over inefficiencies and legacy infrastructure.
In fact, digital healthcare in the Middle East and Africa (MEA) region is booming with the proliferation of disruptive solutions underpinned by 21st century innovations like cloud, mobile, Internet of Things (IoT) and Artificial Intelligence (AI).
Let’s talk telemedicine
One trend revolutionising the delivery of healthcare in MEA is telemedicine, which is the use of telecommunication and IT to provide clinical healthcare over long distances. Given the region’s high rate of mobile penetration, telemedicine is growing rapidly. In fact, the telemedicine market in MEA was estimated at $2.19 billion in 2015 and is projected to reach $3.67 billion in 2020.
Forward-thinking countries like Botswana are making swift progress when it comes to the implementation of sustainable telemedicine projects. Microsoft and the Botswana Innovation Hub launched Africa’s first telemedicine service over TV white spaces in 2017. Through this initiative, clinics in outlying areas of Botswana can now access specialised care remotely using TV white spaces, which are unused broadcasting frequencies in the wireless spectrum.
Partners HealthCare relies on its enterprise research infrastructure and services group, or ERIS, to provide an essential service: storing, securing and enabling access to the data files that researchers need to do their work.
To do that, ERIS stood up a large network providing up to 50 TB of storage, so the research departments could consolidate their network drives, while also managing access to those files based on a permission system.
But researchers were contending with growing demands to better secure data and track access, said Brent Richter, director of ERIS at the nonprofit Boston-based healthcare system. Federal regulations and state laws, as well as standards and requirements imposed by the companies and institutions working with Partners, required increasing amounts of access controls, auditing capabilities and security layers.
“We were thinking about how do we get audit controls, full backup and high availability built into a file storage system that can be used at the endpoint and that still carries the nested permissions that can be shared across the workgroups within our firewall,” he explained.
Hybrid cloud storage as a service
At the time, ERIS was devising security plans based on the various requirements established by the different contracts and research projects, filling out paperwork to document those plans and performing time-intensive audits.
It was then that ERIS explored ClearSky Data. The cloud-storage-as-a-service provider was already being used by another IT unit within Partners for block storage; ERIS decided six months ago to pilot the ClearSky Data platform.
“They’re delivering a network service in our data center that’s relatively small; it has very fast storage inside of it that provides that cache, or staging area, for files that our users are mapping to their endpoints,” Richter explained.
From there, automation and software systems from ClearSky Data take those files and move them to its local data center, which is in Boston. “It replicates the data there, and it also keeps the server in our data center light. [ClearSky Data] has all the files on it, but not all the data in the files on it; it keeps what our users need when they’re using it.”
Essentially, ClearSky Data delivers on-demand primary storage, off-site backup and disaster recovery as a single service, he said.
All this, however, is invisible to the end users, he added. The researchers accessing data stored on the ClearSky Data platform, as well as the one built by ERIS, do not notice the differences in the technologies as they go about their usual work.
ClearSky benefits for Partners
ERIS’ decision to move to ClearSky Data’s fully managed service delivered several specific benefits, Richter said.
He said the new approach reduced the system’s on-premises storage footprint, while accelerating a hybrid cloud strategy. It delivered high performance, as well as more automated security and privacy controls. And it offered more data protection and disaster recovery capabilities, as well as more agility and elasticity.
Richter said buying the capabilities also helped ERIS to stay focused on its mission of delivering the technologies that enable the researchers.
“We could design and engineer something ourselves, but at the end of the day, we’re service providers. We want to provide our service with all the needed security so our users would just be able to leverage it, so they wouldn’t have to figure out whether it met the requirements on this contract or another,” Richter said.
He noted, too, that the decision to go with a hybrid cloud storage-as-a-service approach allowed ERIS to focus on activities that differentiate the Partners research community, such as supporting its data science efforts.
“It allows us to focus on our mission, which is providing IT products and services that enable discovery and research,” he added.
Pros and cons of IaaS platform
Partners’ storage-as-a-service strategy fits into the broader IaaS market, which has traditionally been broken into two parts: compute and storage, said Naveen Chhabra, a senior analyst serving infrastructure and operations professionals at Forrester Research Inc.
Brent Richterdirector of ERIS at Partners HealthCare
In that light, ClearSky Data is one of many providers offering not just cloud storage, but the other infrastructure layers — and, indeed, the whole ecosystem — needed by enterprise IT departments, with AWS, IBM and Google being among the biggest vendors in the space, Chhabra said.
As for the cloud-storage-as-a-service approach adopted by Partners, Chhabra said it can offer enterprise IT departments flexibility, scalability and faster time to market — the benefits that traditionally come with cloud. Additionally, it can help enterprise IT move more of their workloads to the cloud.
There are potential drawbacks in a hybrid cloud storage-as-a-service setup, however, Chhabra said. Applying and enforcing access management policies in an environment where there are both on-premises and IaaS platforms can be challenging for IT, especially as deployment size grows. And while implementation of cloud-storage-as-a-service platforms, as well as IaaS in general, isn’t particularly challenging from a technology standpoint, the movement of applications on the new platform may not be as seamless or frictionless as promoted.
“The storage may not be as easily consumable by on-prem applications. [For example,] if you have an application running on-prem and it tries to consume the storage, there could be an integration challenge because of different standards,” he said.
IaaS may also be more expensive than keeping everything on premises, he said, adding that the higher costs aren’t usually significant enough to outweigh the benefits. “It may be fractionally costlier, and the customer may care about it, but not that much,” he said.
ERIS’ pilot phase with ClearSky Data involves standing up a Linux-based file service, as well as a Windows-based file service.
Because ERIS uses a chargeback system, Richter said the research groups his team serves can opt to use the older internal system — slightly less expensive — or they can opt to use ClearSky Data’s infrastructure.
“For those groups that have these contracts with much higher data and security controls than our system can provide, they now have an option that fulfills that need,” Richter said.
That itself provides Partners a boost in the competitive research market, he added.
“For our internal customers who have these contracts, they then won’t have to spend a month auditing their own systems to comply with an external auditor that these companies bring as part of the sponsored research before you even get the contract,” Richter said. “A lot of these departments are audited to make sure they have a base level [of security and compliance], which is quite high. So, if you have that in place already, that gives you a competitive advantage.”
Oschner Health is one example of a company using AI to revolutionise healthcare. Its system is able to accurately track patients who are at risk of cardiac arrest, and can determine when there is a decline in their condition. This allows them to be admitted into intensive care hours earlier than they otherwise would have been. They are provided with potentially life-saving care, before their condition deteriorated to the point where medical care would have been less effective.
Project InnerEye, in use at Addenbrooke’s Hospital in Cambridge, is another solution which uses machine learning and computer vision for the analysis of radiological images. Designed to identify tumours, it improves the delivery of treatments such as radiotherapy, by precisely distinguishing between cancerous and healthy tissues. It can also better monitor disease progression during chemotherapy, so that treatment can be adjusted in line with how patients respond.
These AI solutions allow medical professionals to improve patient care and admittance time, thanks to their improved precision. This, in turn, reduces financial and manpower strain, improving the healthcare experience in the areas where this technology is being used.
This is supported by data from the World Health Organization (WHO), which shows that between 30 and 50 percent of cancer deaths could be avoided with prevention, early detection and treatment. With cancer costing the global economy an excess of an estimated $1.16 trillion a year, the impact of technology such as AI, is game-changing.
In the UK alone, for example, there are only 4.7 radiologists per 100,000 population, and this number will need to almost double by 2022 to meet demand. Because of this shortage, the NHS spent nearly £88 million in 2016 paying for backlogs of radiology scans to be reported – the same amount could have paid for over 1,000 full-time consultants.
“We are drowning in data in hospitals,” Kos states. “We don’t have enough human brainpower to deal with it all in a timely manner – which in healthcare, is vital.”
Using technology such as AI can therefore substantially decrease strain on healthcare systems, while simultaneously improving patient care and reducing costs, allowing doctors to spend their time on more complex medical diagnoses. Or, indeed, spending more time connecting with patients.
The human factor Introducing AI to healthcare isn’t removing the humanity from medicine. On the contrary, it’s increasing it.
A study in the Annals of Internal Medicine found that doctors spend nearly twice as much time doing administrative work (49 percent) as they do with their patients (27 percent). In other words, doctors are spending more time crunching through data, sifting through and updating records, and analysing scans, than they are speaking to their patients.
In a profession where people are dealing with often traumatic, life-changing developments, this personal, human touch, is vital for the emotional well-being of patients and their loved ones. By using tools such as AI to free up more of their time, healthcare professionals can focus more on patient interaction, offering reassurance, providing guidance, and answering more questions.
Culture, and the challenges of change Motivated by the lack of technology during his critical care period, Kos spent eight years crusading to introduce electronic medical record systems into hospitals. But nothing improved.
“We digitized, but we digitized all of the mistakes too. Then it dawned on me – digitization is important, but it’s not transformation.”
Without the supportive technology of cloud storage, or the data analysis powers of AI and machine learning, the full potential of these digitized records weren’t even close to being reached. Only years after, when cloud technology was accepted on a wider scale, and when collaborative tools such as Skype or real-time document editing in the cloud were established – could this initial digitization move on to the next level.
Research has shown that an organisation with the most advanced technology still won’t be as effective if it lacks the right company culture. Employees must be willing to embrace their new tools, while leaders must encourage a culture of learning. Only then, can the new tools be as effective as possible.
In the world of medicine, however, adopting the right culture for technological change can prove to be a challenge.
“Healthcare professionals are rather inward-looking,” says Kos. “Doctors listen to doctors. It’s a very top-down, hierarchical environment. You could have the best technology in the world, but if the culture isn’t ready to embrace it with a willingness to learn, it’s just not going to work.”
It’s an exciting time to be working shoulder-to-shoulder with our healthcare partners and customers, who represent some of the brightest minds in this important industry. We have been approaching the complexities of the healthcare industry with a growth mindset, and for the past two years our team has worked across Microsoft to accelerate healthcare innovation through artificial intelligence and cloud computing, with our initiative Healthcare NExT (New Experiences and Technologies). We shared some updates earlier this year on our work in cloud architectures, empowering clinicians and care teams, and precision medicine, and I’ve been thrilled to see the progress and reaction across the industry.
Today we are building on that progress. I’m very pleased to welcome two prominent experts in the science, technology and practice of value-based healthcare to the team. Jim Weinstein and Josh Mandel will be joining Microsoft Healthcare – which integrates Healthcare NExT and its research-driven efforts – with an added focus of creating strategic partnerships, and driving the cross-company strategy for healthcare and life sciences.
Jim Weinstein, Vice President, Microsoft Healthcare, Head of Innovation and Health Equity
Jim Weinstein will work closely with organizations on the front lines of healthcare delivery as we aim to support health systems, empower clinicians and enable the systems of care as they move to the cloud. He will be my partner in developing the strategic vision for Microsoft Healthcare, and will provide leadership that is grounded in decades of health industry experience. A widely respected visionary, author, surgeon and leader in the future of healthcare delivery who has advised three administrations on healthcare policy, Jim most recently served as CEO and president of Dartmouth-Hitchcock and the Dartmouth-Hitchcock Health system, and is the past director of the Dartmouth Institute, home of the Dartmouth Atlas of Health Care. Jim is also the co-founder and inaugural executive director of the national High Value Healthcare Collaborative, which brings together some of the nation’s top healthcare systems to share data, develop insights and advance the causes of better healthcare outcomes. He recently chaired the “Communities in Action, Pathways to Health Equity” report for the National Academy of Medicine. His book “Unraveled” looks at the broken healthcare system and how it might be repaired with patient-based clinical insights.
Joshua Mandel, Chief Architect, Microsoft Healthcare
Joshua Mandel will work closely with customers, partners and the open standards community to lay the groundwork for an open cloud architecture to unlock the value of healthcare for the entire health ecosystem. As a tireless evangelist for the importance of open standards, Josh will continue his work to help systems across the industry become more agile and interoperable. Josh’s impressive background as a physician and brilliant software architect has set him apart as a leader in the development of next-generation standards for healthcare data interoperability. In his most recent role, Josh led the health IT ecosystem work at Verily (Google Life Sciences). He is a member of the research faculty at the Boston Children’s Hospital Computational Health Informatics Program where he served as lead architect for SMART Health IT, and is a visiting scientist at the Harvard Medical School Department of Biomedical Informatics. Josh earned his bachelor of science degree in electrical engineering and computer science from Massachusetts Institute of Technology, and his M.D. from Tufts University of Medicine.
Jim and Josh join us at an exciting time, as healthcare processes undergo a digital transformation. This transformation has created a wealth of healthcare data that has potential to help identify diseases earlier, create and improve treatments and improve the lives of patients across the globe. Unfortunately, even with advances in data protection and governance, healthcare data is not easily accessible by the researchers and doctors who need it to help us all realize the potential. And so, for a variety of regulatory, technological and political reasons, we see what is called the “health data funnel,” which holds back the case of scalable innovation in healthcare.
At Microsoft, we’re confident that many aspects of the IT foundations for healthcare will move from on-premise doctors’ offices and clinics to live in the cloud. We ask the questions: Can we take advantage of this huge sea change in healthcare to unlock the innovation potential in healthcare data? Can we work as a community to ensure that we don’t simply re-create the same data silos that we have today?
We think that together, we can solve these problems. We are taking concrete steps with an initial “blueprint” intended to standardize the process for the compliant, privacy-preserving movement of a patient’s personal health information to the cloud and the automated tracking of its exposure to machine learning and data science, for example to support external audit. This is a small first step, but progress toward an open architecture that ultimately will benefit doctors, nurses and clinicians in how they interact with patients, and also allow more time for patients to spend face-to-face with their care providers. It also opens up research opportunities for this data to be shared, and to be done under the same compliance and regulatory standards which protect your health data today; all with the goal of leading to advancements in medical science.
We have our work cut out for us but know that we have the right team in place. We’re looking forward to sharing more later this year about what we’re doing to help unlock the power of healthcare data and create opportunities for the entire health ecosystem.