Hospitals routinely collect vast amounts of data, including information about patients’ health, care delivery, and organizational performance. This data could theoretically be utilized to drive huge improvements in health outcomes and operational efficiency.
Rather than this massive amount of health data being an advantage, it’s most often considered a burden as there are inconsistencies in documentation, aggregation methods, organization of, display of, and most importantly, how it’s used. There’s also a lack of resources required to effectively manage this overwhelming amount of information. The data gap not only leads to lost opportunities to improve healthcare but is a major contributor to some of healthcare’s current biggest issues like burnout and staffing. Hospitals are always striving to better leverage healthcare data. Revised processes that reduce manual inputs, eliminate redundancy, and include central EHR systems are a few goals that come to mind. However, some of the biggest wins will only be gained once we tap into more advanced tools that leverage artificial intelligence (AI). With so much medical information already available, including large complex data sets, sophisticated AI systems are just what the doctor ordered to get these data sets organized and in use. To unlock data, hospitals must incorporate more data science and use artificial intelligence (AI) methods to operationalize their learnings. Data science is an umbrella term for statistical techniques, design techniques, and development methods. It involves pre-processing analysis, prediction, and visualization, whereas AI is the implementation of a predictive model to foresee events. Advanced data science and AI can not only help organize all of this information, but also generate trends and insights so that hospitals can deliver more precise care, identify operational hazards, and create a more optimized approach for managing their current workload.
Many Sources of Information
The problem, as it stands, is too much information from disparate sources and in different formats. Hospital data comes from a variety of places, such as electronic health records, administrative systems, insurance providers, patient-submitted forms, local HR systems, hospital medical devices, and, remote monitoring services.
This information also comes in various forms, including structured digital data, physical documents, photographs, charts, and more. The volume and diversity of data make it difficult to store in conventional databases and format it for use across multiple frameworks.
The biggest healthcare innovation in the last twenty years is … data. Every day, healthcare organizations use data to operate more efficiently, improve patient care, and advance medical research. Over the last 24 months, the industry used data to advance mRNA technology, which laid the groundwork for the COVID-19 vaccines, and even led to a new treatment for type-two diabetes.
The recent medical breakthroughs speak to the power of data and the vast potential it has to help improve lives. Unfortunately, as data becomes more valuable, the threats become more dire. As the attackers evolve, organizations need to take a holistic approach if they want to defeat the threats.
The Critical Risks to Healthcare Data
Ransomware is the leading risk. Sensitive data is a honey pot to cybercriminals, and because healthcare organizations maintain so much of it (i.e., medical records, patient forms, health insurance claims, provider and patient communication records, etc.) they are vulnerable targets.
Cyber attacks on healthcare organizations have become so frequent that 45 million people were directly affected in 2021. This summer, one of the largest healthcare cyber incidents to date struck more than 2 million patients across 50 facilities in an attack on Shields Health Care Group.
If the right systems aren’t in place, recovering after a cyber attack such as ransomware can be an exhausting process that takes weeks or months. Even more concerning, businesses are sometimes unable to fully restore data lost in an attack. Aside from productivity disruption, losing critical healthcare data could impact an organization’s ability to maintain its operations. If you are a hospital or healthcare provider – this could be catastrophic. Some often resort to paying large ransoms to resolve the issue, but this should never be the solution.
As COVID-19 cases push hospitals around the country to their limits, medical facilities are facing challenges beyond sick patients. Long hours and an uptick in cyberattacks are putting serious strain on existing cybersecurity defenses. Without the right practices, these defenses may fail, exposing patient and hospital data to hackers and cybercriminals.
Here is why security remains key as the coronavirus outbreak grows more severe — and how hospitals can rise to meet current cybersecurity challenges.
Why Healthcare Data Security Remains Important
While cybersecurity may seem overshadowed by other healthcare concerns, the current crisis makes hospital data security more essential than ever.
Many hospitals and health systems are currently expanding or introducing COVID health data collection programs to get the information needed to combat the novel coronavirus. Many of these same systems are also ramping up data-sharing between institutions to ensure that medical providers around the country have the best possible information to work with.
New operating conditions — like hospitals that set up tents in parking lots to expand their number of available beds — have also changed how hospital systems, like electronic health records, are used and secured.
At the same time, hackers are stepping up their operations and trying to take advantage of the chaos. Security researchers have already noticed a serious rise in attacks like phishing emails, as well as new malicious health tracking and COVID-19–related apps.
Current stress on staff may make hospitals more vulnerable to hacks. Cybersecurity professionals were, on average, overworked before the crisis began — an issue that has likely gotten worse as the crisis has progressed. Doctors, nurses and hospital administrators are working overtime, and organizations are bringing on new workers to manage the increased need for professionals. Existing staff may struggle to keep up with good security practices, and new team members may not receive the full training they need to keep data safe.
New information collecting schemes are critical for medical providers — but if the data they collect isn’t secured, it may also put a lot of patients at risk. This patient information may not seem like the most valuable target for hackers — but health data is actually widely sought after by cybercriminals. These hackers use health information, along with other personal information, to construct comprehensive identity packages about individual patients.
What Hospitals Can Do to Handle Security
There are steps hospitals can take to ensure that patient and hospital data stays as safe as possible — even while the staff is under immense pressure.
During the crisis, operational security will become more critical. Doctors, nurses and hospital staff should be highly aware of what they are sharing on social media. Personal information should be kept private, and employees must take note of any information in the background of the photos they take. A cybercriminal scouring the posts of doctors and hospital workers may find what they need to break into a network — like a password taped to a monitor.
The big data revolution has made today’s healthcare industry a vibrant hub of innovation in data, analytics, and artificial intelligence. Recent decades have brought tremendous advances in not only the science of clinical and medical services, but also in the business strategy powering those services.
Across the industry, digital pioneers are leveraging data to create new efficiencies, solutions, and breakthrough treatments. However, just as the industry offers endless examples of incredible transformation, so too does it offer endless case studies in untapped potential.
Some roadblocks to healthcare data innovation in the healthcare industry are unavoidable: Decades’ worth of legacy and proprietary systems have made modernization and integration efforts enormously challenging. Strict regulations mean that the barrier to entry for new technologies and processes are much higher than in other industries. Additionally, many healthcare organizations face governance challenges spurred by years of continuous disruption—making it even harder to bring innovative ideas to fruition.
However, these obstacles have not stopped healthcare data innovation; they’ve merely slowed the pace of change. Generally, when an organization has the resources, competencies, and will to innovate, the only thing that can thwart those intentions is an inability to build effective business data strategy.
Often, that lack of ability stems from a fundamental misconception about innovation itself—a case of mistaken identity that confuses innovation for inspiration. When this misconception flourishes, organizations can fall into a state of institutional inertia, forever waiting for the next big idea to appear out of thin air.
These organizations fail to understand that innovation is a process, not some mysterious phenomenon, and that they can build concrete business strategies with repeatable procedures designed to continually drive the formulation of breakthrough ideas. Fortunately, organizations need only three core ingredients to build an effective business data strategy that fosters innovation.
Fast Iteration
It’s been said, but it bears repeating: Innovation is a process. And when it comes to business innovation, an iterative process allows for the greatest amount of flexibility and experimentation in concepting and product development. Healthcare organizations who wish to develop new applications and revenue streams leveraging their data must create internal systems that allow for fresh ideas to be iterated upon at pace and at scale.
To do so, it is vital that these organizations drastically lower the cost to try. If, over the course of a year, the “cost to try” is 10 months of submissions, review, and approvals, then your organization will try one thing that year. If the cost to try is shortened to one week, then your organization will likely try 52 things that year. The more your organization is able to try new ideas, and iterate upon those ideas, the faster your organization will innovate.
One powerful tool helping organizations build fast iteration into their processes is the use of digital twins—detailed digital models of physical objects and processes that allow for big ideas to be tested at low cost.
Researchers at Oklahoma State University’s Computational Biofluidics and Biomechanics Laboratory have used digital twin models to optimize the delivery efficiency of aerosol medications. At the systems level, consultancy GE Healthcare recently teamed with Tampa General Hospital to launch the CareComm clinical command center, which leverages a digital twin of the hospital to predict patient needs and lower costs. Models like these significantly reduce the cost to try for innovative ideas leveraging patient data.
By Abhinav Shashank, CEO and co-founder, Innovaccer.
Abhinav Shashank
What makes Super Bowls, banking transactions, and online search results altogether more special?
As an ardent supporter, concerned customer, and curious observer, I keep witnessing all three of them in real time. I want the best experience every time that I am the end user, and so does everyone else. In this day and age, it shouldn’t be an unrealistic dream anyway. We should be able to know the score in real time and in the same way, our credit card transactions as and when they happen.
Why doesn’t my healthcare data show the complete picture?
Ironically, for healthcare organizations, real-time updates are not always available while making decisions that can potentially impact patients throughout their lives. Traditionally, many solutions were not even made to optimize the time that providers spend with their patients. Rather, they were only built to ingest data in electronic formats, evaluate macro-level performance trends, and in the best case scenario, provide top stakeholders with financial trends in a concise manner.
Though most organizations today have business intelligence (BI) infrastructures in place, most of the insights generated through them are only good for analyzing things in retrospect and do not really assist providers in the moment of care.
Activated data is the backbone of healthcare technology
It’s one thing to know what is wrong, it is another to have a way of addressing it. For instance, notes from the last appointment with a patient can only provide care teams with half of the story. Unless care providers have a holistic pool of information regarding the patient’s whereabouts, they cannot initiate personalized care plans or impart evidence-based care.
Healthcare leadership should look for activating data from different facilities in their bid to maximize the knowledge base of their providers. Once they have all the data points, they can begin to run customized analytics to support clinical decision-making.
Jane Smith, a 53-year-old diabetic patient, goes to her kitchen to grab a glass of water when she suddenly feels dizzy. She grabs her portable, battery-operated blood glucose monitor to check her blood sugar level and finds it is higher than usual. The HbA1c level from the device is immediately sent to her care team, who are connected with her via a common digital platform.
Her care coordinator calls and advises her to take an insulin shot at the earliest. Within a few minutes, she is visited by a nurse who assists in giving her the insulin received from the pharmacy. Jane is also asked to see her PCP as soon as possible. A week later when she consults her PCP, he is already aware of her medical condition and the medication dosage she received the other day. He looks at her profile on his EHR and marks the care gap that was created as closed.
Now, Jane, her care team, the PCP, the hospital, and the pharmacy can look into her medical records and manage her care with a few clicks on this online platform; and Jane herself has enough clinical insights to make an informed decision about her care.
Does all of this seem like a far-fetched dream?
Healthcare technology has birthed many dreams and turned them into a reality. And yet, it lacks the capability to share clinical data efficiently at the exact moment of care.
What do we want from 100 percent interoperability?
When we talk about technology, the first thing that pops into our heads is Google. It’s an absolute comfort when we get a notification on our calendars that we might be late for an upcoming meeting. This is not rocket science, just two different products interacting on the same layer of a platform to make our lives simpler.
By Brooke Faulkner, freelance writer, @faulknercreek.
The proliferation of wearable mobile-connected devices has done a lot of good for people trying to lead healthier lives. People are able to gather data about their sleep to help them get better rest, track insomnia, stress, and exercise, and keep up to date on their own daily routines and health.
Many of the devices exist not just as trackers but as ways for people to motivate themselves to exercise more, go to bed at more regular times, and other little things that slip by in the daily grind.
Specialists can access information far more quickly and easily to help us with medical problems. With the way technology is advancing, you can now even also use online apps to calculate sleeping patterns and wake up times.
Healthcare Data in the Modern Age
Sleep is absolutely related to health. Many health issues affect our sleep or are caused by issues with sleeping. A number of medical professionals are interested in how, when, and for how long we sleep. These days, that information is stored in digital medical records, which have a number of advantages. Specialists can access information far more quickly and easily to help us with medical problems.
There are, however, disadvantages to medical records being easily accessible and easily updatable. Privacy and security have become major concerns for healthcare providers, as the records contain our most sensitive information, which proves highly valuable to hackers.
Official medical records, however, are just the tip of the iceberg. We use the internet not only as a go-to for advice about medical conditions, but as a method to voluntarily record all sorts of data about us. Recording, storing, and tracking sleep data on our personal devices gives us a lot of power to “do it yourself” when it comes to preventative health and tracking changes in our sleep patterns. This ease of use, however, comes with a cost. It’s not all about sinister hackers, either; that data can be used in all sorts of ways that are, while not outright damaging, at least partially invasive.
Wearables, Bluetooth and Data
Tech companies are working on more advanced ways to use high-tech devices to track our sleep. These include wearables and even devices that don’t need to be attached to the body. The amount of information gathered, and its accuracy, varies greatly by device. The Bluetooth connectivity and the ability to store, track, and share the data the devices collect are parts of their appeal.
The number and type of people who benefit from this information is vast. Sleep disorders are a common side effect of other medical disorders, and managing sleep is an important part of living a healthy lifestyle, especially for people who are at greater risk for certain conditions.
You don’t need to have or be at risk for medical complications to make use of sleep data, however. There are plenty of careers in the U.S. which require people to work long or unconventional hours. Night shifts and long shifts, such as those worked by nurses, can cause havoc with the circadian rhythms that regulate our sleep. This can create complications for otherwise completely healthy people. Being able to self-regulate with the help of wearable devices is a great advantage.
Data has been regarded as the new, shiny object in every industry for the last several years—the secret key to all your unanswered questions. The healthcare industry has been no stranger to this language, but has not had as much opportunity to put data to use as other industries. With fast-paced, “ready for anything” schedules, hospitals, EMTs and private practices have had to leave data analysis to the researchers.
A 2017 Bankrate survey found that one in four Americans do not seek medical care when they need it. The survey results cite cost as the main reason for this. While healthcare providers cannot control insurance coverage and healthcare legislature, they can control the experience patients have when they seek care. A patient is much more likely to return for an annual check-up or seek medical care when sick if they hold healthcare to be positive and important. By giving patients the chance to voice their opinion, to feel heard and capturing and analyzing this powerful data, you will create a positive atmosphere. This will then lead to things like patient retention and positive online reviews.
With technology ever advancing, data analysis is simplifying. It is becoming something that a person with no research experience can do and find benefit. Take, for example, open-ended survey analysis software. Most data software analyzes the quantitative or number-based data. This includes the numerical details that you gather like a patient’s vitals. Data is much more than that. Imagine being able to analyze not only quantitative data, but qualitative too, including things like open-ended answers. This opens the possibility to hear directly from patients, doctors, and nurses, not only to better customer service, but importantly, care.
Mixed-question surveys provide health practitioners a simple way to gain new insights. Have patients answer a few questions through your medical portal or while at your office that ask basic questions like, “Rate your experience,” and, “How likely are you to recommend our practice to others?” But do not feel restricted by these types of questions, there is much more to learn beyond whether someone has had a generally good or bad experience. Ask them why. Ask for suggestions of how to improve care. Ask patients to describe their symptoms or the side effects of their medication. Each answer becomes part of a data set that you can analyze and cross-examine to give you new ideas and findings, and contribute to providing a higher standard of care for patients.
As COVID-19 cases push hospitals around the country to their limits, medical facilities are facing challenges beyond sick patients. Long hours and an uptick in cyberattacks are putting serious strain on existing cybersecurity defenses. Without the right practices, these defenses may fail, exposing patient and hospital data to hackers and cybercriminals.
The proliferation of wearable mobile-connected devices has done a lot of good for people trying to lead healthier lives. People are able to gather data about their sleep to help them get better rest, track insomnia, stress, and exercise, and keep up to date on their own daily routines and health.