Traditional RESTful APIs Will Not Solve Healthcare’s Biggest Interoperability Problems

Traditional RESTful APIs Will Not Solve Healthcare's Biggest Interoperability Problems
Brian Platz, Co-CEO and Co-Chairman of Fluree

Interoperability is a big discussion in health care, with
new regulations requiring interoperability for patient data. Most approaches
follow the typical RESTful API approach that has become the standard method for
data exchange. Yet Health Level Seven (HL7), with its new Fast Healthcare Interoperability
Resources (FHIR) standard for the electronic transfer of health data, is
leading to a rash of implementations that, to date, are not solving core interoperability
issues. 

Data is still insecure, users can’t govern their own health
records, and the need for multiple APIs for different participants with
different rights (human and machine) in the network is adding unneeded
expenditures to an already burdened healthcare system. The way out is not to
add more middleware, but to upgrade the basic tools of interoperability in a
way that finally brings healthcare
technology
into the 21st century.  

A Timely Policy 

Doctors, hospitals, pharmacists, insurance providers,
outpatient treatment centers, labs and billing companies are just a few of the
parties that comprise the overcomplicated U.S. healthcare system. 

In digitizing medical files, as required by the 2009 Health
Information Technology for Economic and Clinical Health (HITECH) Act, providers
have adopted whatever solution was most convenient. This has led to the mess of
interoperability
issues that HL7 seeks to remedy with FHIR. 

Existing Electronic Medical Records
(EMR)
systems do not easily share data. Best case, patients have to sign
off to share data with two incompatible systems. Worst case, information must
be turned into a physical CD or document to follow the patient between
providers. Data security is also notoriously poor. Hackers prioritized the healthcare sector as their main target in 2019; breach
costs exceeded $17.7 billion.

The New Infrastructure Rush

When common formats, by way of FHIR and HL7, provided
standards and solutions to empower global health data interoperability, the
industry erupted into a flurry of activity. Thousands of healthcare databases
are now being draped in virtual construction tarps and surrounded by digital
scaffolding. 

Building a new, interoperable data ontology for the entire
healthcare system is a massive undertaking. For one, 80% of hospital data is
managed using the cryptic, machine-language HL7 Version 2. Most of the rest
uses the inefficient, dated XML data format. HL7 FHIR promotes the use of more
modern data syntaxes, like JSON and RDF (Turtle). 

Secondly, databases have no notion of the new FHIR schema.
Armies of developers must build frameworks and middleware to facilitate interoperability.
This is why Big Tech incumbents including Google Cloud Healthcare, Amazon AWS
and Microsoft for Healthcare are jumping into the fray with their own
solutions. 

The outcome, once HL7’s 22 resources are fully normative, will
be seamless information sharing, electronic notifications, and collaboration
between every player in the giant web of patients, providers, labs, and
middlemen. But it will come at a steep cost in the current traditionally RESTful
API-based manner that is being broadly pursued. 

The Problem with APIs

The new scaffolding is expensive, takes data control away
from patients, and is not inherently secure. The number of unique APIs required
to support the access, rights and disparate user base in the healthcare network
are the reason. 

Interoperability requires a common syntax and “language” to
enable databases to talk to each other. The average traditional API costs up to
$30,000 to build, plus half that cost to manage annually. That is not to
mention the cost to integrate and secure each API. A small healthcare
organization with only 10 APIs faces costs of $450,000 annually for basic API
services. 

When you consider that most big healthcare organizations will
need to connect thousands of APIs, HL7’s interoperability schema really is the
best way forward. The traditional API tooling to manage the interoperability of
the well-framed data structures, however, is the problem. 

Moreover, the patient, the rightful owner of their own
health record, still doesn’t have the ability to govern their own data. Because
change only happens in the database itself, the manager of the database, not
the patient, controls the data within. 

In the best case, this puts an additional burden on patients
to give explicit permission every time health records move between providers.
In the worst case, a provider sees an entire medical history without a
patient’s consent–your podiatrist seeing your psychiatric records, for
example.

Finally, each API enables one data store to talk to the
next, opening opportunities for bad actors to make changes to databases from
the outside. The firewalls that protect databases and networks are penetrable,
and user profiles are sometimes created outside of the database itself, making
it possible to expose, steal and change data from outside the database. 

In that light, HL7 is paving the wrong road with good
intentions. But there is another way. 

Semantic Standards and Blockchain to the Rescue

If you eliminate data APIs, secure interoperability, with
data governance fully in the hands of the patient, becomes possible. Healthcare
data silos will be replaced with a dynamic, trusted and shared data network
with privacy and security directly baked in. The solution involves adding
semantic standards for full interoperability, blockchain for data governance
and data-centric security. 

Semantic standards, such as RDF formatting and SPARQL
queries, let users quickly and easily gain answers from multiple databases and
other data stores at once. Relational databases, the ones currently in use in healthcare,
are all formatted differently, and need API middleware to talk to one another.
Accurate answers are not guaranteed. Semantic standards, on the other hand,
create a common language between all databases. Instead of untangling the
mismatched definitions and formatting inevitable with relational databases,
doctors’ offices, for example, could easily pull in pertinent patient records,
insurance coverage, and the latest research on diseases.

Patients, for their part, would use blockchain to regain control
of their data. Patients would be able to turn on aspects of their data to
specific caregivers, instead of relinquishing control to database business
managers, as is currently the case. Your podiatrist, in other words, will not
be able to see your psychiatric records unless you choose to share them. 

The data ledger, which lives on the blockchain, will contain
instructions as to who can update (writer new records on) the ledger, who can
read it, and who can make changes. All changes are controlled by private-key
encryption that is in the hands of the patient; only those with authorization
can see select histories of health data (or, as in the case of an ER doctor,
entire histories, with permission). 

Data security is controlled in the data layer itself,
instead of through middleware such as a firewall. Data can be shared without
API, thanks to those semantic standards, and data are natively embedded with
security in the blockchain. Compliance, governance, security and data
management all become easier. Data cannot be stolen or manipulated by an
outside party, the way it commonly is by healthcare hackers today. 

The interoperability conundrum, in other words, is solved.
Fewer APIs means fewer security vulnerabilities; a common, semantic standard
eliminates confusion and minimizes mistakes. Blockchain puts patients in
control of who sees what parts of their health records. Eliminating the need
for API middleware also saves tens of thousands of dollars, at a minimum.


About Brian Platz 

Brian is the Co-CEO and Co-Chairman of Fluree, PBC, a decentralized app platform that aims to remodel how business applications are built. Before establishing Fluree, Brian was the co-founder of SilkRoad technology which expanded to over 2,000 customers and 500 employees in 12 international offices.


Meaningful Use of Genomics Requires Informatics Beyond EMRs

Why EHRs fall short w/ providing valuable genetic insights
Assaf Halevy, Founder and CEO of 2bPrecise

Electronic medical records (EMRs) are widely expected to serve as a cornerstone technology that drives the delivery of modern patient care. 

But can the EMR alone support all the informatics capabilities required by an ever-evolving healthcare industry? The rapid growth of precision medicine, particularly the use of genetic and genomic information during clinical decision making, is a compelling example that functionality beyond the EMR is required. Not only does genomic data represent a category of information used differently than traditional clinical knowledge, but the volume of data generated through molecular testing alone also requires informatics and management of a higher magnitude than previously required.

The EMR is designed to reflect a snapshot (or collection of snapshots) in time: clinical summaries, annotated lab and test results, operation notes, etc. These are mostly stored as isolated documents, loosely coupled with the rest of the patient chart. They need to remain available for reference over time, in some instances, so providers can chart and contextualize ongoing trends and chronic conditions. However, these views are anchored in time and represent limited actionable value during clinical decision-making months, years, and decades later.

Genomic information, on the other hand, represents a patient’s life signature. DNA rarely changes over the course of an individual’s lifetime. This means the results from germline testing – a patient’s molecular profile – conducted early in life are relevant, meaningful, and actionable during clinical decision making far into the future. They can also deliver insights exposing heritable proclivities that may be life-changing or life-saving for family members as well.

This recognition in and of itself alerts healthcare leaders that they need to adopt an advanced, more sophisticated strategy for data governance, management, and sharing than the approach traditionally applied to other clinical information systems, such as EMRs. 

To be successful, healthcare organizations need an accelerator external to the EMR that is built on a data model unique to the management of molecular knowledge so test results and genomic insights can be used and shared across clinical specialties and care settings, as well as overtime. In addition, the rise of precision medicine requires an agile informatics platform that enables the cross-pollination of genomic data with clinical insights and ever-advancing discoveries in genomic science.

Consider these examples of how EMRs fall short of expectations for optimal use of genomic intelligence:

1. Studies have found that, despite ubiquitous availability of molecular tests, providers consistently fail to identify patients most at risk for heritable diseases. The Journal of the American Medical Informatics Association (JAMIA) recently released research showing that half the women meeting national guidelines for genetic screening are not getting the tests they need to determine their breast and ovarian cancer risk. 

The reason? “The full story of a patient’s risk for heritable cancer within their record often does not exist in a single location,” says the JAMIA article. “It is fragmented across entries created by many authors, over many years, in many locations and formats, and commonly from many different institutions in which women have received care over their lifetimes.” In other words, no matter which EMRs they use, health systems routinely miss opportunities to improve care for patients they see. To achieve greater success, providers need tools that exceed EMR functionality and span multiple clinical systems.

2. Shortly after birth, Alexander develops a seizure disorder. The neonatologist orders a germline test to help her arrive at a precise diagnosis and begin targeted treatment. This approach is successful and Alexander thrives. In addition to genomic variants identifying the cause of his seizure disorder, the test results also contain information about other heritable risk factors, including cardiovascular disease.

Decades later, in the 70s, Alexander sees his primary care provider (PCP) with a rapid heartbeat and shortness of breath. After doing routine lab work, the PCP diagnoses congestive heart failure (CHF). If, however, the PCP had access to Alexander’s genomic test results – which remain as relevant and accurate as when he was an infant – the PCP would have noted a variation that indicated the CHF was due to dilated cardiomyopathy, requiring a different treatment regime.

It is vital that health leaders immediately begin to plan an informatics strategy that accommodates genetic and genomic data while empowering providers to leverage these insights at the point of care as they make routine, yet critical, clinical decisions. As they evaluate their approach, they would do well to ask the following questions:

– Which providers in my organization are already ordering genomic tests on their patients? How are test results being stored and managed – and can they be easily shared with and accessed by others in the health system?

– As the volume of genetic and genomic testing accelerates – and it will – how will we manage the volume of data generated? How will we apply consistent governance to the ordering process? How can we ensure results will be consumed as discrete data so our organization can optimize its value now and in the future?

– What steps do we need to take so our precision medicine strategy remains current with changing science? Which informatics tools deliver access to up-to-date knowledge bases and clinical guidelines to ensure optimal medical decisions are made?

The advent of precision medicine represents a new standard of care for healthcare providers from coast to coast. Genetic and genomic information supplies a new data set that can be used to arrive at more accurate diagnoses sooner and more effective treatment faster. This, in turn, supports better outcomes, higher patient (and provider) satisfaction, and competitive differentiation for the health system adopting precision medicine first in its market.

But to capture this value, healthcare leaders must look beyond their legacy EMRs, recognizing that they were not developed nor do they have the capacity to properly handle the upcoming data revolution. Instead, industry innovators are looking for platforms agnostic to individual EMRs and integrated with molecular labs to address the next-generation demands of precision medicine.


About Assaf Halevy

Assaf Halevy is the founder and CEO of 2bPrecise, LLC, leading an international team dedicated to bridging the final mile between the science of genomics and making that data useful at the point of care. He joined Allscripts as senior vice president of products and business development in 2013 when the company acquired Israel-based dbMotion. An initial inventor and co-founder of dbMotion, Halevy helped develop the leading clinical integration and population health management platforms in the industry today.

With 13 patents pending in the areas of actionable clinical integration, interoperability, and precision medicine, Halevy leverages his industry expertise by evaluating strategic alliances and partnerships for U.S. and international markets. Halevy was invited to participate in several U.S. government activities and contribute to an HHS privacy committee task force. In 2016, he was part of a small selective group of executives invited to the White House by Vice President Joe Biden to discuss the future of interoperability.


AI Algorithms Can Predict Outcomes of COVID-19 Patients with Mild Symptoms in ER

AI Algorithms Can Predict Outcomes of COVID-19 Patients with Mild Symptoms in ER

What You Should Know:

– Artificial intelligence algorithms can predict outcomes
of COVID-19 patients with mild symptoms in emergency rooms, according to recent
research findings published in Radiology: Artificial Intelligence journal.

– Researchers trained the algorithm from data on 338
positive COVID-19 patients between the ages of 21 and 50 by using diverse
patient data from emergency departments within Mount Sinai Health System
hospitals (The Mount Sinai Hospital in Manhattan, Mount Sinai Queens, and Mount
Sinai Brooklyn) between March 10 and March 26.


Mount Sinai researchers have developed an artificial intelligence algorithm to rapidly predict outcomes of COVID-19 patients in the emergency room based on test and imaging results. Published in the journal, Radiology: Artificial Intelligence, the research reveals that if the AI algorithms were implemented in the clinical setting, hospital doctors can identify patients at high risk of developing severe cases of COVID-19 based on the severity score.  This can lead to closer observation and more aggressive and quicker treatment.

Research Background/Protocols

They trained the algorithm using electronic medical records (EMRs) of patients between 21 and 50 years old and combined their lab tests and chest X-rays to create this deep learning model. Investigators came up with a severity score to determine who is at the highest risk of intubation or death within 30 days of arriving at the hospital. If applied in a clinical setting, this deep learning model could help emergency room staff better identify which patients may become sicker and lead to closer observation and quicker triage, and could expedite treatment before hospital admission.

Led by Fred Kwon, Ph.D., Biomedical Sciences at the Icahn School of Medicine at Mount Sinai, researchers trained the algorithm from data on 338 positive COVID-19 patients between the ages of 21 and 50 by using diverse patient data from emergency departments within Mount Sinai Health System hospitals (The Mount Sinai Hospital in Manhattan, Mount Sinai Queens, and Mount Sinai Brooklyn) between March 10 and March 26. Data from the emergency room including chest X-rays, bloodwork (basic metabolic panel, complete blood counts), and blood pressure were used to develop a severity score and predict the disease course of COVID-19. 

Patients with a higher severity score would require
closer observation. The researchers then tested the algorithm using patient data on other patients in all adult age groups and
ethnicities.  The algorithm has an 82 percent sensitivity to predict intubation and death within 30 days of
arriving at the hospital. 

Why It
Matters

Many patients with COVID-19, especially younger ones, may show non-specific symptoms when they arrive at the emergency room, including cough, fever, and
respiratory issues that don’t provide any indication of disease severity. As a
result, clinicians cannot easily identify patients who get worse quickly. This algorithm can provide the probability that a patient may
require intubation before they get worse. That way clinicians can make more accurate decisions for appropriate
care.

Algorithms that predict outcomes of patients with COVID-19 do exist, but they are used in admitted patients who have already developed more severe symptoms and have additional imaging and laboratory
data taken after hospital admission.  This algorithm is different since it predicts outcomes in COVID-19 patients while they’re in the emergency room—even in those with mild symptoms. It only uses information from the initial
patient encounter in the hospital emergency department. 

“Our algorithm demonstrates that initial imaging and laboratory tests contain sufficient information to predict outcomes of patients with COVID-19. The algorithm can help clinicians anticipate acute worsening (decompensation) of patients, even those who present without any symptoms, to make sure resources are appropriately allocated,” explains Dr. Kwon. “We are working to incorporate this algorithm-generated severity score into the clinical workflow to inform treatment decisions and flag high-risk patients in the future.”

Despite COVID-19: Providers Should Not Lose Sight of MIPS Compliance

Despite COVID-19: Providers Should Not Lose Sight of MIPS Compliance
Courtney Tesvich, VP of Regulatory at Nextech

When 2020 began, no one anticipated that complying with the Merit-based Incentive Payment System (MIPS)—the flagship payment model of the Centers for Medicare & Medicaid Services (CMS) Quality Payment Program (QPP)—would look so different halfway through the year. Like many other things, the COVID-19 crisis has delayed, diverted, or derailed many organizations’ reporting efforts and capabilities. Lower procedure volumes, new remote work scenarios, and shifting priorities have taken attention away from MIPS work. 

Despite the disruptions and uncertainties associated with the pandemic, healthcare organizations should not lose track of MIPS compliance and the program’s intent to improve care quality, reduce costs, and facilitate interoperability. Here are a few strategies for keeping a MIPS program top of mind. 

Understand the immediate effects of the pandemic on MIPS reporting 

Due to COVID-19, CMS granted several 2019 data reporting exceptions and extensions to clinicians and providers participating in Medicare quality reporting programs. These concessions were enacted to let providers focus 100% of their resources on caring for and ensuring the health and safety of patients and staff during the early weeks of the crisis. For the 2020 MIPS performance period, CMS has also chosen to use the Extreme and Uncontrollable Circumstances policy to allow requests to reweight any or all of the MIPS performance categories to 0%.

Clinicians and groups can complete the application any time before the end of this performance year. If practices are granted reweighting one or more categories but submit data during the attestation period, the reweighting will be void and the practice will receive the score earned in the categories for which they submit data

Seize the opportunity to improve interoperability 

Interoperability is a key area that organizations were focused on before the crisis, and this work still warrants attention. If an organization is not on the front lines of the COVID-19 response, it should use this time to shore up communications with other entities so, once things return to “normal,” it will be well prepared to seamlessly exchange information with peer organizations. 

Establishing processes for sending and receiving care summaries via direct messaging is important for practices to earn a high score in the Promoting Interoperability category. Direct messaging is a HIPAA-compliant method for securely exchanging health information between providers, which functions as an email but is much more secure due to encryption. A regular pain point organizations face is being unable to obtain direct messaging addresses from peer organizations, including referral partners.

To assist providers in this area, the Office of the National Coordinator for Health Information Technology (ONC) and CMS has created a mandatory centralized directory of provider electronic data exchange addresses published by the National Plan & Provider Enumeration System (NPPES). The NPPES directory is searchable through a public API and allows providers to look up the direct messaging addresses for other providers. To meet current interoperability requirements, providers must have entered their direct messaging address into the system by June 30, 2020. If they haven’t done so, the provider could be publicly reported for failure to comply with the requirement, which could constitute information blocking. 

Take time now to ensure direct messaging addresses have been entered correctly for all members of your practice. This is also a good time to begin reaching out to top referral sources to make sure they are also prepared to send and receive information.

Look for ways to streamline quality reporting 

Over the next few months, the focus will return to quality measure reporting. As such, it’s wise to take advantage of this time to ensure solid documentation and reporting methods. Electronic medical records (EMRs) can be helpful in streamlining these efforts.

For example, dropdown menus with frequently used descriptions and automated coding can enable greater accuracy and specificity while easing the documentation process for providers. Customizable screens that can be configured to include specialty-specific choices based on patient history and problem list can also smooth documentation and coding, especially if screen layouts mirror favored workflow.

Regarding MIPS compliance in particular, it can be helpful to use tools that offer predictive charting. This feature determines whether a patient qualifies for preselected MIPS measures in real-time and presents the provider with data fields related to those items during the patient encounter—allowing the physician to collect the appropriate information without adding additional charting time later on. 

With respect to reporting, providers may benefit from using their certified EMR in addition to reporting through a registry. At the beginning of the MIPS program, providers could report through both a registry and EMR directly and would be scored separately for their quality category through each method. They would then be awarded the higher score of the two. This method had the potential to leave some high-scoring measures on the table.

Beginning in 2019, providers reporting through both registry and EMR direct are scored across the two methods. CMS uses the six highest scoring measures between the two reporting sets to calculate the provider’s or group’s quality score, potentially resulting in a higher score than the provider would earn by reporting through either method alone. 

A knowledgeable partner can pave the way to better performance

COVID-19 has impacted healthcare like no other event in recent history, and it’s not surprising that MIPS compliance has taken a back seat to more pressing concerns. However, providers still have the opportunity to make meaningful progress in this area. By working with a technology partner that keeps up with the current requirements and offers strategies and solutions for optimizing data collection and reporting, a provider can realize solid MIPS performance during and beyond this unprecedented time.


About Courtney Tesvich, VP of Regulatory at Nextech

Courtney is a Registered Nurse with more than 20 years in the healthcare field, 15 of which have been focused on quality improvements and regulatory compliance. As VP of Regulatory at Nextech, Courtney is responsible for ensuring that Nextech’s products meet government certification requirements and client needs related to the regulatory environment.  


Amazon Launches HealthLake for Healthcare Orgs to Aggregate & Structure Health Data

AWS Announces Amazon HealthLake

What You Should Know:

– Amazon today announced the launch of Amazon HealthLake,
a new HIPAA-eligible service enables healthcare organizations to store, tag,
index, standardize, query, and apply machine learning to analyze data at
petabyte scale in the cloud.

– Cerner, Ciox Health, Konica Minolta Precision Medicine,
and Orion Health among customers using Amazon HealthLake.


Today at AWS re:Invent, Amazon
Web Services, Inc. (AWS),
an Amazon.com company today announced Amazon HealthLake, a
HIPAA-eligible service for healthcare and life sciences organizations. Current
Amazon HealthLake customers include Cerner, Ciox Health, Konica Minolta
Precision Medicine, and Orion Health.

Health data is frequently incomplete and inconsistent, and is often unstructured, with the information contained in clinical notes, laboratory reports, insurance claims, medical images, recorded conversations, and time-series data (for example, heart ECG or brain EEG traces) across disparate formats and systems. Every healthcare provider, payer, and life sciences company is trying to solve the problem of structuring the data because if they do, they can make better patient support decisions, design better clinical trials, and operate more efficiently.

Store, transform, query, and analyze health data in
minutes

Amazon HealthLake aggregates an organization’s complete data across various silos and disparate formats into a centralized AWS data lake and automatically normalizes this information using machine learning. The service identifies each piece of clinical information, tags, and indexes events in a timeline view with standardized labels so it can be easily searched, and structures all of the data into the Fast Healthcare Interoperability Resources (FHIR) industry-standard format for a complete view of the health of individual patients and entire populations.

Benefits for Healthcare Organizations

As a result, Amazon HealthLake makes it easier for customers to query, perform analytics, and run machine learning to derive meaningful value from the newly normalized data. Organizations such as healthcare systems, pharmaceutical companies, clinical researchers, health insurers, and more can use Amazon HealthLake to help spot trends and anomalies in health data so they can make much more precise predictions about the progression of the disease, the efficacy of clinical trials, the accuracy of insurance premiums, and many other applications.

How It Works

Amazon HealthLake offers medical providers, health insurers,
and pharmaceutical companies a service that brings together and makes sense of
all their patient data, so healthcare organizations can make more precise
predictions about the health of patients and populations. The new
HIPAA-eligible service enables organizations to store, tag, index, standardize,
query, and apply machine learning to analyze data at petabyte scale in the
cloud.

Amazon HealthLake allows organizations to easily copy health
data from on-premises systems to a secure data lake in the cloud and normalize
every patient record across disparate formats automatically. Upon ingestion,
Amazon HealthLake uses machine learning trained to understand medical
terminology to identify and tag each piece of clinical information, index
events into a timeline view, and enrich the data with standardized labels
(e.g., medications, conditions, diagnoses, procedures, etc.) so all this
information can be easily searched.

For example, organizations can quickly and accurately find
answers to their questions like, “How has the use of cholesterol-lowering
medications helped our patients with high blood pressure last year?” To do this,
customers can create a list of patients by selecting “High Cholesterol” from a
standard list of medical conditions, “Oral Drugs” from a menu of treatments,
and blood pressure values from the “Blood Pressure” structured field – and then
they can further refine the list by choosing attributes like time frame,
gender, and age. Because Amazon HealthLake also automatically structures all of
a healthcare organization’s data into the FHIR industry format, the information
can be easily and securely shared between health systems and with third-party
applications, enabling providers to collaborate more effectively and allowing
patients unfettered access to their medical information.

“There has been an explosion of digitized health data in recent years with the advent of electronic medical records, but organizations are telling us that unlocking the value from this information using technology like machine learning is still challenging and riddled with barriers,” said Swami Sivasubramanian, Vice President of Amazon Machine Learning for AWS. “With Amazon HealthLake, healthcare organizations can reduce the time it takes to transform health data in the cloud from weeks to minutes so that it can be analyzed securely, even at petabyte scale. This completely reinvents what’s possible with healthcare and brings us that much closer to everyone’s goal of providing patients with more personalized and predictive treatment for individuals and across entire populations.”

Cleveland Clinic Develop COVID-19 Risk Prediction Model through Epic MyChart

Cleveland Clinic Develop COVID-19 Risk Prediction Model through Epic MyChart

What You Should Know:

– Cleveland Clinic develops the COVID-19 risk prediction model through Epic MyChart that is now available to health systems around the world.

– Healthcare organizations can present the clinically
validated model to patients in MyChart to assess their risk of having COVID-19.


Cleveland Clinic researchers have developed a COVID-19 risk prediction model that uses information from the patient’s comprehensive health records combined with patient-centered information in Epic’s patient-facing app, MyChart, to show an individual’s likelihood of testing positive for COVID-19. The COVID-19 risk prediction model is now available to health systems around the world through Epic.

 A COVID-19 risk prediction model designed by Cleveland Clinic researchers is
now available to health systems around the world through EpicDeveloped and tested using
clinical data from more than 11,000 Cleveland Clinic patients
, the model
uses information from patients’

COVID-19 Risk Prediction Model Development

Predicting positive COVID-19 tests could help direct limited healthcare resources, encourage those who are likely to have the virus to get tested, and tailor decision-making about care. Cleveland Clinic’s model was developed and validated using retrospective patient data from more than 11k patients tested for COVID-19 at Cleveland Clinic locations in Northeast Ohio and Florida. Data scientists used statistical algorithms to transform data from patients’ electronic medical records into the first-of-its-kind risk-prediction model. All data collected was housed in a secure database.

How It Works

Patients complete a short self-assessment in MyChart,
documenting information like symptoms they are experiencing and potential
exposure to COVID-19. The model uses that information, as well as clinical and
demographic data already in their electronic chart, to calculate their score.
Patients with high risk for having COVID-19 are advised to receive a test, and
their care team members can be automatically notified of a high-risk score.

Other healthcare providers around the country also have
developed risk prediction models, which they can integrate with Epic. For
organizations that want to use an existing model rather than developing their
own, they can quickly turn on the model designed, developed, and tested–and now
being shared–by Cleveland Clinic researchers.

“We have developed the first validated prediction model that can forecast an individual’s risk for testing positive with COVID-19 and then simplified this tool while retaining exceptional accuracy for easy adoption,” said Lara Jehi, M.D., Chief Research Information Officer at Cleveland Clinic. “We are excited to make this tool available to the 250 million patients around the world who have a record in Epic. The ability to accurately predict which patients are likely to test positive will be paramount in effectively managing a patient’s care as well as allocating our resources.”

To Solve Healthcare Interoperability, We Must ‘Solve the Surround’

To Solve Healthcare Interoperability, We Must ‘Solve the Surround’
Peter S. Tippett, MD, Ph.D., Founder & CEO of careMesh

Interoperability in healthcare is a national disgrace. After more than three decades of effort, billions of dollars in incentives and investments, State and Federal regulations, and tens of thousands of articles and studies on making all of this work we are only slightly better off than we were in 2000.  

Decades of failed promises and dozens of technical, organizational, behavioral, financial, regulatory, privacy, and business barriers have prevented significant progress and the costs are enormous. The Institute of Medicine and other groups put the national financial impact somewhere between tens and hundreds of billions of dollars annually. Without pervasive and interoperable secure communications, healthcare is missing the productivity gains that every other industry achieved during their internet, mobile, and cloud revolutions.   

The Human Toll — On Both Patients and Clinicians

Too many families have a story to tell about the dismay or disaster wrought by missing or incomplete paper medical records, or frustration by the lack of communications between their healthcare providers.  In an era where we carry around more computing power in our pockets than what sent Americans to the moon, it is mystifying that we can’t get our doctors digitally communicating.   

I am one of the many doctors who are outraged that the promised benefits of Electronic Medical Records (EHRs) and Health Information Exchanges (HIEs) don’t help me understand what the previous doctor did for our mutual patient. These costly systems still often require that I get the ‘bullet’ from another doctor the same way as my mentors did in the 1970s.

This digital friction also has a profoundly negative impact on medical research, clinical trials, analytics, AI, precision medicine, and the rest of health science. The scanned PDF of a fax of a patient’s EKG and a phone call may be enough for me to get the pre-op done, but faxes and phone calls can’t drive computers, predictive engines, multivariate analysis, public health surveillance programs, or real-time alerting needed to truly enable care.

Solving the Surround 

Many companies and government initiatives have attempted to solve specific components of interoperability, but this has only led to a piecemeal approach that has thus far been overwhelmed by market forces. Healthcare interoperability needs an innovation strategy that I call “Solving the Surround.” It is one of the least understood and most potent strategies to succeed at disruptive innovation at scale in complex markets.  

“Solving the Surround” is about understanding and addressing multiple market barriers in unison. To explain the concept, let’s consider the most recent disruption of the music industry — the success of Apple’s iPod. 

The iPod itself did not win the market and drive industry disruption because it was from Apple or due to its great design. Other behemoths like Microsoft and Philips, with huge budgets and marketing machines, built powerful MP3 players without market impact. Apple succeeded because they also ‘solved the surround’ — they identified and addressed numerous other barriers to overcome mass adoption. 

Among other contributions, they: 

– Made software available for both the PC and Mac

– Delivered an easy (and legal) way for users to “rip” their old CD collection and use the possession of music on a fixed medium that proved legal “ownership”

– Built an online store with a massive library of music 

– Allowed users to purchase individual tracks 

– Created new artist packaging, distribution, licensing, and payment models 

– Addressed legalities and multiple licensing issues

– Designed a way to synchronize and backup music across devices

In other words, Apple broke down most of these barriers all at once to enable the broad adoption of both their device and platform. By “Solving the Surround,” Apple was the one to successfully disrupt the music industry (and make way for their iPhone).

The Revolution that Missed Healthcare 

Disruption doesn’t happen in a vacuum. The market needs to be “ready” to replace the old way of doing things or accept a much better model. In the iPod case, the market first required the internet, online payment systems, pervasive home computers, and much more. What Apple did to make the iPod successful wasn’t to build all of the things required for the market to be ready, but they identified and conquered the “surround problems” within their control to accelerate and disrupt the otherwise-ready market.

Together, the PC, internet, and mobile revolutions led to the most significant workforce productivity expansion since WWII. Productivity in nearly all industries soared. The biggest exception was in the healthcare sector, which did not participate in that productivity revolution or did not realize the same rapid improvements. The cost of healthcare continued its inexorable rise, while prices (in constant dollars) leveled off or declined in most other sectors.  Healthcare mostly followed IT-centric, local, customized models.  

Solving the Surround for Healthcare Interoperability

‘Solving the Surround’ in healthcare means tackling many convoluted and complex challenges. 

Here are the nine things that we need to conquer:  

1. Simplicity — All of the basics of every other successful technology disruptor are needed for Health communications and Interoperability. Nothing succeeds at a disruption unless it is perceived by the users to be simple, natural, intuitive, and comfortable; very few behavioral or process changes should be required for user adoption. 

Simplicity must not be limited to the doctor, nurse, or clerical users. It must extend to the technical implementation of the disruptive system.  Ideally, the new would seamlessly complement current systems without a heavy lift. By implication, this means that the disruptive system would embrace technologies, workflows, protocols, and practices that are already in place.  

2. Ubiquity — For anything to work at scale, it must also be ubiquitous — meaning it works for all potential players across the US (or global) marketplace.  Interoperability means communicating with ease with other systems.  Healthcare’s next interoperability disruptor must work for all healthcare staff, organizations, and practices, regardless of their level of technological sophistication. It must tie together systems and vendors who naturally avoid collaboration today, or we are setting ourselves up for failure.  

3. Privacy & Security — Healthcare demands best-in-class privacy and security. Compliance with government regulations or industry standards is not enough. Any new disruptive, interoperable communications system should address the needs of different use cases, markets, and users. It must dynamically provide the right user permissions and access and adapt as new needs arise. This rigor protects both patients from unnecessary or illegal sharing of their health records and healthcare organizations in meeting privacy requirements and complying with state and federal laws. 

4. Directory — It’s impossible to imagine ubiquitous national communications without a directory.   It is a crucial component for a new disruptive system to connect existing technologies and disparate people, organizations, workflows, and use cases. This directory should maintain current locations, personnel, process knowledge, workflows, technologies, keys, addresses, protocols, and individual and organizational preferences. It must be comprehensive at a national level and learn and improve with each communication and incorporate each new user’s preferences at both ends of any communication.  Above all, it must be complete and reliable — nothing less than a sub-1% failure rate.  

5. Delivery — Via the directory, we know to whom (or to what location) we want to send a notification, message, fetch request or record, but how will it get there? With literally hundreds of different EHR products in use and as many interoperability challenges, it is clear that a disruptive national solution must accommodate multiple technologies depending on sender and recipient capabilities. Until now, the only delivery “technology” that has ensured reliable delivery rates is the mighty fax machine.

With the potential of a large hospital at one end and a remote single-doctor practice at the other, it would be unreasonable to take a one size fits all approach. The system should also serve as a useful “middleman” to help different parties move to the model (in much the same way that ripping CDs or iTunes gave a helping hand to new MP3 owners). Such a delivery “middleman” should automatically adapt communications to each end of the communication’s technology capabilities, needs, and preferences..  

6. Embracing Push — To be honest, I think we got complacent in healthcare about how we designed our technologies. Most interoperability attempts are “fetch” oriented, relying on someone pulling data from a big repository such as an EHR portal or an HIE. Then we set up triggers (such as ADTs) to tell someone to get it. These have not worked at scale in 30+ years of trying. Among other reasons, it has been common for even hospitals to be reluctant to participate fully, fearing a competitive disadvantage if they make data available for all of their patients. 

My vision for a disruptive and innovative interoperability system reduces the current reliance on fetch. Why not enable reliable, proactive pushing of the right information in a timely fashion on a patient-by-patient basis? The ideal system would be driven by push, but include fetch when needed. Leverage the excellent deployment of the Direct Trust protocol already in place, supplement it with a directory and delivery service, add a new digital “middleman,” and complement it with an excellent fetch capability to fill in any gaps and enable bi-directional flows.

7. Patient Records and Messages — We need both data sharing and messaging in the same system, so we can embrace and effortlessly enable both clinical summaries and notes. There must be no practical limits on the size or types of files that can easily be shared. We need to help people solve problems together and drive everyday workflows. These are all variations of the same problem, and the disruptor needs to solve it all.  

8. Compliance — The disruptor must also be compliant with a range of security, privacy, identity, interoperability, data type, API, and many other standards and work within several national data sharing frameworks. Compliance is often showcased through government and vendor certification programs. These programs are designed to ensure that users will be able to meet requirements under incentive programs such as those from CMS/ONC (e.g., Promoting Interoperability) or the forthcoming CMS “Final Rule” Condition of Participation (CoP/PEN), and others. We also must enable incentive programs based on the transition to value-based and quality-based care and other risk-based models.  

9. On-Ramp — The iPod has become the mobile phone. We may use one device initially for phone or email, but soon come to love navigation, music, or collaboration tools.  As we adopt more features, we see how it adds value we never envisioned before — perhaps because we never dreamed it was possible. The healthcare communications disruptor will deliver an “On-Ramp” that works at both a personal and organizational scale. Organizations need to start with a simple, driving use case, get early and definitive success, then use the same platform to expand to more and more use cases and values — and delight in each of them.  

Conclusion

So here we are, decades past the PC revolution, with a combination of industry standards, regulations, clinician and consumer demand, and even tens of billions in EHR incentives. Still, we have neither a ‘killer app’ nor ubiquitous medical communications. As a result, we don’t have the efficiency nor ease-of-use benefits from our EHRs, nor do we have repeatable examples of improved quality or lower errors — and definitively, no evidence for lower costs. 

I am confident that we don’t have a market readiness problem. We have more than ample electricity, distributed computing platforms, ubiquitous broadband communications, and consumer and clinician demand. We have robust security, legal, privacy, compliance, data format, interoperability, and related standards to move forward. So, I contend that our biggest innovation inhibitor is our collective misunderstanding about “Solving the Surround.” 

Once we do that, we will unleash market disruption and transform healthcare for the next generation of patient care. 


About Peter S. Tippett

Dr. Peter Tippett is a physician, scientist, business leader, and technology entrepreneur with extensive risk management and health information technology expertise. One of his early startups created the first commercial antivirus product, Certus (which sold to Symantec and became Norton Antivirus).  As a leader in the global information security industry (ICSA Labs, TruSecure, CyberTrust, Information Security Magazine), Tippett developed a range of foundational and widely accepted risk equations and models.

He was a member of the President’s Information Technology Advisory Committee (PITAC) under G.W. Bush, and served with both the Clinton Health Matters and NIH Precision Medicine initiatives. Throughout his career, Tippett has been recognized with numerous awards and recognitions  — including E&Y Entrepreneur of the Year, the U.S. Chamber of Commerce “Leadership in Health Care Award”, and was named one of the 25 most influential CTOs by InfoWorld.

Tippett is board certified in internal medicine and has decades of experience in the ER.  As a scientist, he created the first synthetic immunoglobulin in the lab of Nobel Laureate Bruce Merrifield at Rockefeller University. 

ViewPoints Article: Digital Healthcare in India – Current Trends & Future

Digital healthcare means using communications and information technologies in medicine to diagnose, predict, treat, and monitor diseases. It is also widely used for prognosis, rehabilitation, behavioral health, and public health.  Indians have witnessed a surge of smartphone and internet use since the last decade. This had led to an easier delivery of smart digital solutions. Known inequalities in access to healthcare, lack of trained professionals, outdated infrastructure, and low healthcare budget are some of the problems in India. Modern healthcare technology and innovation is the solution to improve the health status of the country. Similarly, the healthcare system is continuously being transformed with the latest technology. It is believed that in the coming decade, all pharmaceutical companies will leverage available technology to improve clinical outcomes.  India`s healthcare industry has grown from $100 Billion (2015) to $280 Billion (2020) and is rapidly surging at a CAGR of 18.3%

Amidst Covid-19, there is a fortunate surge in innovation and locally made technology in India. The government is enthusiastic about digital solutions for rapid diagnostic methods among other innovations. Technology should be consumer-friendly, efficacious, and affordable. India is not far behind in terms of innovation.

The objectives of digital health products and services are: 

  • To improve clinical outcomes
  • To improve the patient experience
  • To be consumer-friendly
  • To improve the physician provider experience.
  • To address health problems 

Need of Digital Technology to Manage Health

A plethora of issues exist in India`s healthcare sector which are still untouched by digital technology. Antibiotic resistance, medical reimbursement, TB, malaria, diabetes should be targeted in the coming decade.

The ratio of patients to doctors is below the acceptance rate. India does not meet minimum WHO recommendations for the healthcare workforce and infrastructure.

Image Source: PwC Analysis

In short, Digital healthcare is needed for the following:

  • To improve access to healthcare
  • To reduce healthcare inefficiency
  • To improve the quality of care
  • To lower the cost of healthcare
  • To Provide individualized health care

Current Scenario

India is climbing the peak of the digital health revolution. The majority of healthcare professionals (HCPs) use electronic medical records (EMRs) for more efficient medical practice.

For a few years, novel digital solutions are gaining popularity with joints from private and public sectors. The government has recently launched the much needed National Digital Health Mission (NDHM). The private sector has rolled out mobile apps, telemedicine, research centers among other initiatives. Telemedicine, Artificial Intelligence (AI), mobile apps, robotics, and virtual reality (VR) are gaining popularity. Digital intervention in healthcare is expected to drive the industry at a CAGR of 23% by 2020.

India is climbing the peak of the digital health revolution. The majority of healthcare professionals (HCPs) use electronic medical records (EMRs) for more efficient medical practice.

Top 10 Digital Health Solutions

  1. M-health: A simple mobile app that provides online video consultation and an added feature to book laboratory tests online. It has an estimated market size of 5,184 crore INR in 2020.
  2. Remote diagnosis – These products provide point-of-care diagnostics, teleconsultation, and online prescription capabilities thus increasing access to healthcare in rural areas. For example, a wireless monitor that measures blood pressure, oxygen saturation, pulse, body temperature, blood sugar, blood cholesterol, and total hemoglobin (Hb) count with a mobile application on your smartphone. It is expected to grow at a CAGR of 20%.
  3. Telemedicine – It is the use of digital technology for remote diagnosis, monitoring, and patient counseling. The high volume of patient load (millions) on a few doctors (thousands) may burden the whole system and reduce its efficiency. Telemedicine or Virtual consultation will enhance patient experience and engagement; fewer tests would be prescribed; the rate of hospital re-admission will be less; better medication and patient adherence would lead to desired clinical outcomes.  It is a rapidly emerging sector in India and the telemedicine market in India is expected to reach $32 million by 2020
  4. Digital Connectivity – support groups and knowledge portals for patients and digital chatting platforms for medical professionals.
  5. Wearables – They are used to measure basic health parameters such as heart rate, number of steps, sleep pattern, etc. For example, exercise trackers, oximeters. The overall market for this is currently valued at 30 crore INR.
  6. Big Data Analytics – Healthcare players have realized the value of combining consumer insights and internal company data to optimize their products. Advantages are a) lower rate of medication errors, b) Facilitating Preventive Care c) More Accurate.
  7. Artificial Intelligence (AI) – It helps in automation of clinical tasks and virtual nursing assistants. AI has the capability to transform health management. It is used in precision medicine, medical imaging, drug discovery, and genomics. DeepGenix helps the user in understanding their problems based on questions and then predicts the diagnosis. It uses deep phenotyping and deep learning (a form of AI).
  8. Electronic medical records (EMR): This should help reduce medical errors and improve health outcomes. Automated patient history has a lot of benefits. Arintra, an AI-based software incorporates branching techniques to collect and store patient history. It also helps in diagnosing and suggesting laboratory tests. It can also be used in telemedicine before the consultation.
  9. Virtual reality – Surgeons are using virtual-reality simulations to improve their skills or to plan complicated surgeries. 
  10. Blockchain – It is proven to be effective in preventing data breaches, improving the accuracy of medical records, and reducing costs.
Image Source: PwC Analysis

Future

Digital healthcare will continue to remain an essential part of healthcare in India. Now medical tasks like analyzing radiology, pathology, or ophthalmology images are performed by computers. Telemedicine, E-pharmacy, fitness apps, wearable devices have become an integral part of the patient`s lives, especially during Covid-19.

Opportunities for the future

  • Electronic medical records (EMRs)
  • Robotics
  • Smart health monitor
  • Mobile health apps
  • Computer processing
  • Genomics
  • Virtual Reality (VR)

Though some innovations are still in the early stages, they look promising. For example, research on 3D-printed hearts and other organs is being carried out; doctors are using VR instead of medication to treat pain; robots are being used in surgeries; genomic analysis. The need for digital innovations has become even more urgent during the Covid-19 pandemic. 

Conclusion

There is a significant need for digital technology to bridge healthcare gaps. India holds the potential for digital growth, given its innovation rate, identification of problems, growing population, and surging healthcare industry. Digital technology will help India achieve healthcare for all and will soon emerge as a global leader in digital health.

References

  1. PwC Digital Health Whitepaper: Indian Healthcare on the cusp of a digital transformation.
  2. Digital Healthcare in India
  3. Digital Health

Related Article: ViewPoints Article: Digital Revolution in Healthcare and Strategic Role of Medical Affairs Amidst Covid-19 Outbreak

The post ViewPoints Article: Digital Healthcare in India – Current Trends & Future first appeared on PharmaShots.

4 Ways Businesses Will Adapt Their Healthcare Landscape

 Four ways businesses will adapt their healthcare landscape
Dr. Donald Brown, CEO and founder of LifeOmic

The coronavirus pandemic has affected every aspect of our lives, from how we work to how we get our health care. The crisis has put the creativity of many small businesses to the test after being forced to move operations online once social distancing became the norm. As economies reopen, many aspects of our life that changed in response to the virus will likely return to the way they were.

However,  we have the opportunity to emerge stronger from this crisis if the salient shortcomings from our economic system are addressed. Regarding health care, the virus has exposed deep flaws in the way services are provided and has shown us how businesses and people can be better prepared when the next pandemic hits.

1. The way companies insure their workers will change 

One trend we will likely see occurring is the decentralization of healthcare. Before the pandemic, there had been growing signs of American businesses becoming tired of a rigged system where costs to keep employees insured often spiraled out of control. One example of this dissatisfaction was the partnership between Amazon, JP Morgan, and Berkshire Hathaway, who more than 2 years ago announced the formation of their own joint venture to provide healthcare coverage to their employees. 

The pandemic is going to introduce a long term change in healthcare and especially the relationship between companies and healthcare providers. More companies will make the switch to self-funded insurance and assume the healthcare expenses of their employees while being reimbursed for claims that exceed a certain amount through stop-loss insurance. Businesses will also start to hire their own physicians to offer services to their employees directly to reduce their dependence on the healthcare system.

Given our early struggle to increase our virus testing capabilities, companies may take steps to avoid waiting for the federal or local governments to step in during a pandemic.  Businesses may start partnering with local labs to design their own diagnostic tools and serological tests which would allow them to react more quickly and successfully to an outbreak. Businesses will value knowing which of their employees have been exposed, how many might be immune, and which might be more susceptible to infection based on parameters such as BMI or blood pressure readings.  

2. Businesses and people will take charge of their own health

Although the United States spends close to 20% of its GDP on healthcare, diseases that put people at higher risk for severe COVID-19 illness, including obesity, diabetes, and heart disease, are still prevalent in the population. 

This crisis exposed the need for businesses to help employees maintain a healthy lifestyle in order to protect themselves and their jobs. Businesses may start promoting behaviors proven to strengthen the immune system and improve overall health, including taking active breaks at work to increase physical activity or encouraging healthy eating by offering healthy food choices. Companies may also start to offer testing equipment in office locations to help employees keep track of their health. Businesses may start investing in mini-physiology lab stations that include equipment to measure blood pressure, lung function, and heart health. They may also invest in blood tests that measure important biomarkers that allow employees to make better health choices that reduce their risk of disease.

3. Telehealth solutions will become widely available 

The pandemic has amplified the need for a technology-driven transformation of healthcare. Companies can invest in built-in telemedicine capabilities so that employees have an easy way to get online care when they need it.  The regulatory barriers that have delayed widespread use of telehealth should start to disappear. Hospitals can benefit from offering these services and implementing them now will better equip them for future crises. Doctors can remotely provide care to vulnerable patients so they don’t have to be exposed by going to a hospital, and physicians and nurses who have to quarantine themselves can still see patients through telehealth means so that hospitals don’t have to face staff shortages when they believe they might have been exposed. 

4. Artificial Intelligence will change everything

The use of AI in healthcare will combine with the trends described above to completely disrupt healthcare, especially in terms of corporate wellness. Skyrocketing costs and disillusionment with the governmental response to COVID-19 will convince organizations of all sizes to take more direct responsibility for the health and wellness of their employees. Cloud-based systems can aggregate everything from electronic medical records to whole-genome sequences. Fitness trackers and other inexpensive devices can add real-time physiologic data that can be tracked over time.

All this data would be overwhelming for human physicians, but it’s perfect for AI-based systems. For example, an AI can continuously calculate the probabilities of dozens of diseases for each employee and generate automatic recommendations when a probability exceeds a certain threshold. Such systems can also give employees personalized advice to help them reduce such probabilities and return to a healthy state. The advice can range from lifestyle changes (nutrition, exercise, etc.) to supplements or further testing. These AI-based systems will grow in sophistication over time to rival – and even exceed – the capabilities of human physicians.

Summary

The American healthcare system was clearly dysfunctional even before COVID-19. However, the pandemic has put the flaws into sharp relief and will almost certainly push companies and other organizations to seek better solutions. Those solutions will leverage many recent developments including:

  • Cloud platforms with nearly limitless storage and compute capacity
  • Engaging mobile apps
  • Direct-to-consumer molecular and genetic testing
  • Fitness trackers and other medical devices
  • Artificial intelligence

Together, these trends will usher in lasting change that will transform the healthcare landscape for all businesses.


About Dr. Don Brown

Don is a serial software entrepreneur (founder of 4 companies), life-long learner (4 degrees: a bachelor’s in physics, a master’s in computer science +  biotechnology and an MD) and philanthropist (donated  $30 million for the establishment of the Brown Immunotherapy Center at the Indiana University School of Medicine).  Prior to LifeOmic, Don founded Software Artistry which became the first software company in Indiana ever to go public and was later acquired by IBM for $200 million. Don then founded and served as CEO of Interactive Intelligence which went public and was acquired by Genesys Telecommunications Laboratories in 2016 for $1.4 billion.

5 Critical Considerations for Patient Privacy in Telehealth

5 Critical Considerations for Patient Privacy in Telehealth
Sachin Nayyar, CEO at Securonix

The COVID-19 pandemic has had a tremendous ripple effect across all industries, with one of the most impacted being healthcare. Providers have had to quickly adapt to supporting patients ‘virtually’ in a secure manner, while simultaneously developing procedures to support accurate reporting to government organizations. These changes have placed added pressure on security and privacy professionals, as they struggle to keep up with urgent demand.

Mature healthcare organizations already have stringent policies and procedures in place to remain compliant with government regulatory requirements (i.e., HIPAA, HITECH Act, etc.) and protect patients’ privacy. However, with the new focus on telehealth, unprecedented patient growth, and strict regulations on reporting, the key threats healthcare security and privacy teams need to be able to detect are also evolving: 

  • Unauthorized access to patient data by employees
  • Patient data snooping (by employees, family members, co-workers, etc.)
  • Compromised records (unusual access patters – new locations, multi-location access, etc.)
  • Failed logins and download spikes 
  • Terminated or dormant user accounts being used to gain access
  • Accessing discharged patient records or deceased patient records

Identifying these threats and uncovering suspicious patterns or activities, however, is no easy feat. Most security monitoring solutions cannot integrate with and consume electronic medical records (EMR) in a usable format. As a result, these solutions have limited out of the box content, leaving a majority of threat detection engineering to the security operations teams, which are already overwhelmed. Legacy security tools are no longer cutting it, as they use rule-based security event monitoring methods that do not account for the need to protect patient data privacy required by regulations such as HIPAA, HITRUST, and GDPR. They also lack the ability to protect patient data from insider threats, advanced persistent threats, or targeted cyberattacks.

Successfully monitoring patient data privacy must focus on two key entities: the employees accessing records and the patients whose records are being accessed. Organizations need to be able to visualize and correlate events across these entities and throughout the IT infrastructure and EMR applications to detect suspicious patterns while adhering to reporting and compliance mandates.

Monitoring EMR applications is crucial to detect and prevent suspicious activity that may lead to data compromise. However, this can be a cumbersome process. Given that nearly all EMR records contain patient data information, organizations must maintain the confidentiality of this data while enabling security monitoring. Unfortunately, most traditional SIEMs do not provide solutions to this problem. As a result, organizations are forced to intermix sensitive patient data with other IT data, risking compliance violations.

To achieve these goals in the near term, there are five crucial areas where healthcare security and privacy teams need to focus attention:

1. Remote Access Protocol: Like all other industries, healthcare organizations must now grant remote access to a large percentage of their workforce. As they migrate workers to remote access these organizations must address logistical challenges such as ensuring IT support can keep up with requests and implementing multi-factor authentication. 

2. Security Training: Organizations must make sure that their employees are abreast of the unique challenges that accompany working remotely and associated security best practices (i.e., security hygiene, secure internet connections, strong vs. weak passwords, signs of phishing attacks, etc.)

3. Critical App Exposure: Typically, critical applications containing electronic health records are not exposed to the internet without very rigid security controls. However, with the need to share and access more information via apps, strict security is more critical than ever before. 

4. Use of Personal Devices: Many organizations do not issue corporate devices to all their employees. Therefore, there is a greater security risk as workers are being permitted to use their personal devices to access critical systems.

5. User Monitoring and Detection: Identity activity patterns are vastly different as employees adapt to the new normal. As a result, prospective attack vectors have changed drastically. Monitoring and detecting new patterns of human and non-human identities must happen quickly in order to adapt to the new reality and detect attacks.

With the entire world experiencing unprecedented changes, we must learn to adapt quickly and strategically. New threat patterns will emerge, but it is crucial to remain vigilant about all activity and access occurring across IT infrastructure. Stringent regulations and ethical codes of conduct also mean that organizations need to be more vigilant about protecting patient data privacy than ever before. 

The constantly evolving data landscape makes it hard to differentiate new and normal, from malicious and threatening. Healthcare organizations need to assess their security posture, ensuring that they have proper tools in place to accurately analyze and correlate events across the IT infrastructure and electronic records. Only with access to this full picture will they be able to detect any suspicious patterns and ultimately protect patient data.


About Sachin:

Sachin Nayyar is the CEO of Securonix, a company redefining Next-Gen SIEM using the power of big data and machine learning. drives the vision and overall business strategy for Securonix. Built on an open Hadoop platform, Securonix Next-Gen SIEM provides unlimited scalability and log management, behavior analytics-based advanced threat detection, and automated incident response on a single platform.

Prior to Securonix, Nayyar served as the founder & CEO of VAAU where he led the company from conception to acquisition by Sun Microsystems. Following the acquisition by Sun, Sachin served as the Chief Identity Strategist for Sun Microsystems where he led the vision and strategy for the Sun security portfolio. Sachin is a renowned thought leader in areas of risk, regulations, compliance, identity/access, and governance and speaks frequently at professional conferences and seminars.

Enhancing Patient Care With a Touchscreen EMR Interface

Enhancing Patient Care With a Touchscreen EMR Interface
 Jeff Fountaine, Director, Healthcare Vertical Market, Elo

A clinician’s mission is to deliver the best possible care to his or her patients. However, when technology gets in the way of the workflow, clinicians are obligated to spend valuable time making sure data inputs are accurate and complete across disparate systems. Nowhere is this more prevalent than with electronic medical records (EMRs).

Dr. Peter Greene, MD, CMIO, with Johns Hopkins, said, “Efficiency is really at the heart of what troubles us most. Clinicians really want the EMR to make their work easier. Current EMRs take up too much of their time and pull them away from face-to-face time with patients and care teams.”

Dr. Greene’s reflections embody the concerns that the design of the EMR system in critical workflows does not put the patient first. To address this, EMR developers are devoting significant effort into making the EMR design work on behalf of the clinician and patient. Many are finding the greatest room for improvement is in implementing touchscreen technology into the workstation on wheels (WoW) or on in-room wall mounts. Such technology allows clinicians to quickly access key sections of the EMR and input important data like physical exam findings and medication type and dosage. 

Transform Healthcare With Touch Technology 

EMR developers are recognizing that touchscreens significantly enhance the clinician’s experience and patient interaction. From the chief medical officer to the clinicians and medical staff, everyone is familiar with touchscreen technology in their daily lives via their mobile devices. Bringing this technology to clinicians’ and nurses’ workflows frees them from needing to use a keyboard and mouse in favor of a more intuitive and dynamic display. This allows them to more quickly and easily access medical records, view medical images, prescribe medication and document care, and improve their efficiency by up to 20%

It’s faster and easier to clean touchscreen displays too, especially when comparing them to a traditional keyboard and mouse. With a solid piece of glass and a seamless surface, the touchscreen is easily cleaned with wipes commonly available is patient settings. Whether it’s COVID-19, common influenza, or another infectious disease, implementing a streamlined touchscreen solution can help protect patients.  

Build a Unified Architecture for Clinicians

Many modern touchscreen-based workflows are built on a mobile architecture like Android. As healthcare organizations invest in streamlined solutions for clinicians, there’s often a gap that occurs when the mobile operating system doesn’t link seamlessly with the desktop architecture. Without a unified platform connecting every touchpoint, organizations lose precious time continually replacing outdated platforms and hardware. Making the decision to invest in a unified architecture will streamline the entire ecosystem, shorten future deployment time, and enable flexibility across the organization. 

The first step for CIOs, CMIOs, CNIOs, and health systems to achieve this is to create a proof of concept that brings together key leaders within the clinical staff to showcase inclusion of touch technology at the desktop level, coupled with mobile devices for a variety of clinical applications. Next, they can deploy a trial built on a flexible, scalable architecture to help the organization better envision the investment they are making before committing more money. 

In this trial, they can demonstrate how the EMR improves key workflows as clinicians more easily enter data and health information while taking care of their patients. From this demonstration, CIOs and health systems can receive feedback from clinicians to share with the EMR engineering team to help them better understand how they can improve the design of their UI/UX to get the most out of the unified desktop and mobile experience. 

From trial and iteration to solution deployment, the objective remains the same – to create an infrastructure that scales to the demands of the environment while leaving the user satisfied. The outcome of patient care is always first and foremost in the minds of clinicians, so the technology should enable them to focus on care and deliver on that ultimate goal.


About Jeff Fountaine

As director of the healthcare vertical market for Elo, Jeff Fountaine develops and delivers solutions that enhance provider experiences and patient engagement in the healthcare and medical market. With 15 years of experience, he addresses critical workflow challenges for clinicians while ensuring positive patient outcomes through the use of technology.

Hospital Wayfinding: The Next Frontier in Healthcare Design

Wayfinding: The Next Frontier in Healthcare Design
Christopher Thompson, RN, Director of Patient Experience, CenTrak

Healthcare facilities and their sprawling campuses can be overwhelming and challenging to navigate. In fact, facilities lose close to $800 million a year due to missed hospital appointments, and many physicians blame a significant portion of this lost revenue on the problems patients have navigating these facilities.

Figuring out where to park and finding the correct office can be stressful and negatively impact the patient’s experience. Making matters worse, most hospital staff members work in the same unit day in and day out. If a patient approaches them with a question regarding directions, they may not be able to provide an answer or will spend valuable time searching for one. When patients get lost, they tend to arrive late for their appointment, which can back up schedules and create costly inefficiencies for facilities. 

Digital wayfinding can help ease this burden on busy staff while improving the patient experience. Visitors also benefit from feeling at ease, knowing they can quickly locate their loved ones. Implementing a wayfinding solution enables healthcare organizations to automate turn-by-turn directions and highlighted routes, making it easy for patients and visitors to find their desired location. 

Hospital Wayfinding Mechanics

Wayfinding: The Next Frontier in Healthcare Design

Most hospital wayfinding systems utilize Bluetooth Low Energy (BLE) technology found in smartphones, which allows for seamless connectivity and lets patients and visitors view the hospital map on their device and navigate in real-time. To deploy this application successfully, all buildings and outdoor areas of the facility must first be mapped. 

Once a facility’s maps are finalized, they are uploaded to a Content Management System (CMS) with correlating data such as pathways, routes, and points of interest (POIs). If desired, facility administrators can easily access the cloud-based CMS to create, update and manage maps, points of interest, and pathway routing. Advanced analytics such as real-time occupancy, the volume of visits, historical routing and heatmaps, dwell times, space utilization rates, and web usage data are available for in-depth reporting. This information can help your facility better prepare for the future and ensure your patients receive the care they need. 

Locating infrastructure, including BLE beacons, are easily installed to provide indoor location data to the application layer. For more precise coverage and use case expansion, facilities can leverage other Real-Time Location System components using a combination of technologies such as Wi-Fi, Second Generation Infrared, Low Frequency, and BLE. Combining a wayfinding solution with other location services investments reduces IT burden, enhances patient and staff satisfaction, and improves ROI. A future-proof solution can continue to add immense value to healthcare facilities for years to come. 

Hospital Wayfinding and Patient Experience

The most advanced indoor wayfinding applications offer many features, including interactive hospital directories, pathway management, informative POIs, navigation from home, geofencing, and location sharing. They can trigger appointment reminders, GPS driving directions to the facility, and turn-by-turn directions once a patient has arrived. Various routes are provided to patients, visitors, and staff who can select filters such as ADA compliance or minimized outdoor travel time in poor weather conditions. These routes are customizable and can also be modified for construction routes, new additions, staff-only and visitor access, and even pathways that avoid specific areas, like COVID-19 units, to support infection control. 

The mobile application can contain keyword smart search and can also share helpful details such as contact information, hours of operation, images, videos, descriptions, and URLs. While at the facility, patients and visitors can share their indoor location via text and email. When it is time to leave, they can use the save my parking feature to locate their parked car. In the case of an emergency, the application can direct patients where to go to receive urgent assistance to avoid wasting precious minutes. 

Other technologies such as Electronic Medical Records (EMR)/Electronic Health Records (EHR) and Real-Time Location Systems are easily integrated with the wayfinding solution to improve patient experience and make healthcare workers’ shifts easier. Patients can access personalized appointment information such as care plans, questionnaires, and check-in capabilities through the app. In-app access to leading EMR/EHR systems allow users to launch navigation directly from appointment reminder texts or notifications as well as search for a physician.

Staff members can utilize the solution to quickly search for and locate available equipment, such as wheelchairs. Additional integrations include visibility to ER and urgent care wait times, transportation services, scheduling systems, and more. Multiple delivery options, including mobile applications, touchscreen digital kiosk displays, and web browsers, are also available. 

One day soon, healthcare facilities will be entirely revolutionized by IoT technologies including wayfinding applications. Digital wayfinding solutions are the first application to provide seamless connectivity of indoor and outdoor environments with navigation and routing from home, across campuses, between buildings, and to parking areas. By investing in wayfinding, healthcare facilities can design a better patient experience, improve operational efficiency, and save valuable resources.


About Christoper Thompson

Christopher Thompson is the Director of Patient Experience at CenTrak, a leading provider of location and sensing technology for the healthcare industry. Thompson has a master’s degree in nursing and more than 20 years of experience improving hospital workflow and operations.