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By Jeff Robbins, CEO and Founder, LiveData, Inc


The use of Systems of Record, such as EHRs, has been a key strategy for achieving the Institute for Healthcare Improvement Triple Aim: improved patient outcomes and increased patient satisfaction, with reduced costs.

With this in mind, the Health Information Technology for Economic and Clinical Health (HITECH) Act included requirements for meaningful use of EHRs, with significant compliance subsidies. Thanks to the HITECH Act, 83 percent of hospitals had some form of EHR by 2016. However, the promised benefits — no lost data, increased efficiency, and better patient experiences — have not always materialized. Some physicians and patients think healthcare is more inefficient than ever. To combat this, Systems of Engagement are being deployed to augment EHRs, simplify data collection, and share data in easy-to-consume visualizations, getting information to the right clinician at the right time to improve patient care.

Systems Of Engagement

System of Record/EHRs provide a single data source for patient records that a hospital can use for care planning and execution. In subsidizing EHR adoption, the government expected to see 1) improvements in accuracy and completeness of patient information, 2) better coordination of care, 3) secure access for patients to their health data to foster shared decision making, and 4) safer and lower-cost care. Healthcare faces unique challenges in implementing Systems of Record due to privacy and regulatory requirements. EHRs must support data entry requirements and usability features such as:

  • Every patient encounter must be recorded in a way that is effective, efficient, and accurate, and captures the audit trail for the clinician doing the data entry.
  • The Health Insurance Portability and Accountability Act of 1996 (HIPAA) strictly governs data security, entry, storage, and privacy.
  • Archiving data must ensure safety, redundancy, and retrieval for long periods of time.

Meeting these requirements demands significant investment in time and resources. The need for comprehensive, accurate patient data increases data entry time, while the sheer amount of data to store and retrieve requires a large outlay in server space, and more IT help to manage. HIPAA requirements also affect IT resource requirements and significantly complicate the kind of system interoperability that has produced efficiency improvements in other industries.

These issues are reflected in clinical attitudes toward EHRs. Many clinicians feel that EHRs slow down care delivery. This feeling is reinforced when organizations report declines in efficiency and financial losses. Wake Forest Baptist went from a $38.9 million operating gain to a $62.9 million operating loss in the year they implemented their EHR. Only $22 million of the swing was attributable to implementation costs.

EHRs do have a measurable positive effect on patient safety. In a 2012 survey, 88 percent of providers who had attested to Meaningful Use reported that their EHR produces clinical benefits for the practice and 75 percent reported that their EHR helps them deliver better patient care. A 2016 survey showed a 30 percent lower rate of adverse events for surgical patients at facilities using an EHR versus facilities without an HER. So how can healthcare organizations resolve legitimate issues that providers have with their Systems of Record, while maintaining and improving on the patient safety gains that EHR use has delivered?

That is where Systems of Engagement come in.

Systems Of Engagement

Systems of Engagement overlay and complement Systems of Record, allowing users to share and collaborate on mission critical information, in real time or over days and weeks. The term describes everything from email to instant messenger and social media to enterprise platforms for data integration, collaboration, and comprehensive analytics. For healthcare, Systems of Engagement can mitigate the regulatory and safety burdens on Systems of Record, allowing for more rapid testing and targeted performance improvement initiatives.

Healthcare Systems of Engagement have been slow to reach the market and to be adopted. Wariness among hospitals about further investment in software solutions is understandable, given the massive outlays involved in implementing EHRs and the lack of hard data for assessing the impact of new Systems of Engagement. To address this, software companies are partnering with analytics companies or incorporating analytics into their own tools. Analytics can give hospitals insight into the return on investment for Systems of Engagement, in dollars saved and quality improvements.

The recent focus on EHR implementation has also slowed software adoption. The HITECH Act mandated three separate states of attestation for Meaningful Use of EHRs, each more complex than the previous. Given the financial incentives and penalties associated with the Act, hospital IT departments have taken an “all hands on deck” approach to each Stage’s requirements. As Stage 3 requirements were only released in October 2015, many hospitals only now have the resources to consider software approaches to quality and utilization improvements.

Lastly, hospitals as institutions tend to be risk averse, while the apprentice-based system of medical, especially surgical, education favors tradition and preservation of the status quo. In this environment, already reeling from the upheaval of the EHR, an additional layer of software can be a tough sell, but will be needed to meet the challenges of modern healthcare.

In an industry where many still pine for the days of paper records and whiteboards, forward-thinking healthcare organizations will need to show the benefits that data-driven approaches can bring. Investing in Systems of Engagement that have a track record of success is the next step in securing comprehensive institutional buy-in to create a more efficient and effective healthcare world for patients and providers.




Dave Bennett


Because the data capacity for flash drives and secure digital memory card storage increased immensely over the past two decades, mobile phones have gone from simple handsets used for text messaging, phone calls, and the occasional game of Snake, to sophisticated devices that support high-fidelity music libraries, high-definition videos, high-resolution photos and elaborate video games.

Consumer expectation for data storage has also grown over those two decades. The rapid development of new technology—combined with a dramatic reduction in the cost of data storage—has brought to all sectors the possibilities of connection and communication. For healthcare, a wealth of data has revolutionized the way we approach patient care, ushering in an era in which the entire care cycle is fueled by analytics and decision support that improves overall quality and makes the lives of physicians easier.

Patient-as-consumer demands and expectations

The demand for increased data storage has been the driving force behind this rapid expanse of data technology, creating a positive developmental feedback loop. As the capacity for data has increased, so has the consumer appetite for it; consumers demanded greater and more practical data, which opened up previously unexplored avenues for the development of data-driven services. Because patients are also users of other rapidly expanding technologies, the healthcare industry’s goal is to keep up with the expectation for a robust user experience. 

For most industries, including the retail and financial industries, big data is now a tool used to predict consumer trends and provide service improvements, like increasingly targeted advertising, which uses things like social media “likes” and app activity to deliver a personalized experience directly to the individual.

Similarly, the healthcare industry is uniquely positioned to use the increasing visibility of personal data for practical healthcare and treatment solutions. 

Healthcare’s data boom

The increase in data storage capacity has enabled the leveraging of rich data sets of patient information. It started with the adoption of EHRs and EMRs—patient records that were seldom larger than a few megabytes of text and personal health information—and it continued with the need to incorporate things like images from X-rays or CT scans, which increased the need for, and potential applications of, granular patient information.

Today, the average patient generates close to 80 megabytes of data each year, including clinical and financial information, according to a May 2017 article by the New England Journal of Medicine. The next evolution of this technology will include a massive expansion in what can be stored and, in turn, how patient data can be leveraged.

How healthcare is expanding big data solutions

The amount of viable and useful data that can be stored and utilized for an individual patient has gone from megabytes into the realm of terabytes. From a practical standpoint, this has created new and unexpected challenges for clinical data storage—challenges being met by new innovations in cloud-based and on-site data storage solutions.

For example, cloud-based data solutions allow for reduced and flexible infrastructure costs, increased speed and agility, and increased scalability and availability of data. Many cloud providers also offer infrastructure that is compliant with various regulations and certifications, such as HIPAA and HITRUST.

With these new challenges, however, has also come enormous opportunity. The benefits to patients and consumers from this collection of data has opened the door to avenues of care never thought possible.

Some of the technology solutions gained from this increase in data capacity include:

– The development and empowerment of outpatient monitoring through in-home care and off-site patient communication.

– Real-time patient-to-provider updates and communication strengthened by the speed and security of digitized health records over traditional paper records.

– The incredible developments in machine learning as a result of the utilization of anonymized patient images and video data.

Population health management that can aggregate vast data sets to identify at-risk patients for proactive intervention.

– The potential for precision medicine enabled by genomic mapping of patient information.

This is just a handful of technology utilizing patient data that is already being used by healthcare organizations globally. Some of these technologies are in their third or fourth generation, others are only just emerging, and their ongoing development is yielding promising new possibilities.

Just as mobile phones evolved into today’s smartphones, both old and emerging technology continues to get better, more precise and more meaningful. In the early 1990s, as the data boom was only beginning, few could have imagined what would be possible today. Likewise, even with a far greater understanding of the reach and capabilities of big data, few today can likely imagine what will be possible tomorrow.

Evan Sweeney


Using data analytics layered on top of the EHR, the Mayo Clinic has turned the firehose of patient data into more of a trickle.

The renowned hospital system headquartered in Rochester, Minnesota, has used that approach to filter tens of thousands of data points down to 60 pieces of critical information that are displayed for ICU physicians in a visually appealing format. Using “ambient-intelligence” applications licensed by system’s venture capital arm, the approach gives physicians an extra hour each day that can be utilized for bedside care, three Mayo Clinic physicians wrote in Harvard Business Review.

“In fast-paced critical care units, where even small errors can have big consequences, this digital team member can overload physicians with information,” the authors wrote. “The sheer volume of data in EHRs creates a staggering challenge in complex environments such as intensive care units (ICUs) and emergency medicine departments.”

The initiative began with a series of interviews with 1,500 clinicians over a two-year period to understand which data points flowing through the EHR were particularly impactful.

Using that information, researchers built an EHR interface for ICU physicians that could filter out the unnecessary information and integrated a color-coordinated dashboard that emphasized important data points along with customized alerts.

Subsequent research shows mortality rates were cut in half among ICU patients treated after the implementation of the system. ICU stays also decreased by 50%.

The ICU has been a hotspot for data analytics as hospitals look to refine the data put in front of patients. For example, Dignity Health has developed clinical decision support software to send targeted alerts that could have sepsis, and Sutter Health has used AI to improve prescribing practices.

Meanwhile, the Food and Drug Administration is grappling with how to regulate clinical decision support software, leaving some organizations wondering how the agency will oversee ICU dashboards.

Sheri Stoltenberg


Five must-watch initiatives indicate a growing emphasis on patient-focused health IT innovation.

Now that providers have near universally adopted EHR systems across the country, what is the next frontier for healthcare technology? Based on some recently launched tools, health IT researchers and vendors are focused on health-data monitoring, health data access, and clinical decision-making as the industry catches up with consumerism. As such, these five initiatives serve as must-watch health IT developments, starting with Apple’s iPhone patient health information access.

Apple mHealth integration

2017 saw 85.5 million US iPhone users and likely many more since the release of the iPhone 8 and X. Thanks to the recent operating system update this year, iPhone users can now access their EHR patient portal data through the Health app from 12 health systems. The iPhone health data access is read-only at this point and limited to allergy, clinical vitals, health condition, immunization, lab result, medication and procedural information. Users access their data through individual portal credentials to eliminate patient matching concerns that plague multi-facility organizations. The initiative shows major progress in the battle for interoperability with the hope that more EHR vendors can partner with the tech giant.

Smart thermometer app for influenza

In another mobile health development, a smart thermometer application advances flu monitoring and prediction capabilities. A recent Center for Disease Control and Prevention (CDC) study revealed that among US influenza deaths from 2010 to 2016, nearly two-thirds of child fatalities occurred within seven days of developing symptoms. With the World Health Organization estimating three to five million cases of the flu annually, real-time tracking is in high demand for more proactive care. Utilizing a smart thermometer-connected app, researchers at the University of Iowa can now predict influenza spread up to two or three weeks in advance while tracking virus activity at both the population health and individual levels. This combats the several-week delay of CDC formal reporting with more efficient and rapid surveillance for households, so they can better anticipate and identify symptoms to initiate necessary treatment. 


Genomic EHR data and nursing

The next innovation dives deeper than disease monitoring to better understand and interpret an individual’s genetic health. A patient’s genomic information for diagnostic and therapeutic decision making has yet to be seamlessly integrated into today’s EHRs. The National Institute of Health (NIH) is actively working to push genomic nursing forward through its early adopter program utilizing Allscripts Sunrise and the 2bPrecise genomics and precision medicine solution. Moving beyond basic family history information, NIH funnels genetic testing results to the point of care with EHR genomic pedigree documentation. The NIH program aims to be a model for providers and vendors moving forward in using genetic information to take predictive analytics and preventive care to the next level.

Breast cancer decision-making tool

In another initiative toward informed patient care options, a Journal of Clinical Oncology study from the University of Michigan proves that the interactive iCanDecide breast cancer tool improves high-quality decision making for surgical treatment. iCanDecide focuses on knowledge building and value clarification with patients. The study consisted of 537 early-stage breast cancer patients across 22 surgical practices. The follow-up aim of the research is to integrate patient-facing decision tools into the clinical workflow to improve informed decision making that aligns with patient values.

Center for Connected Care telehealth hub

Lastly, as telemedicine programs proliferate across the country, Penn Medicine has created the Center for Connected Care to stand as one of the largest telehealth hubs. With 50 full-time staff, the center provides around-the-clock care to the health system’s patients as well as support to clinicians throughout Pennsylvania, New Jersey, and Delaware. Telehealth specialties include urgent care, chronically ill homecare and critically ill pregnancy services. In addition, Penn Medicine’s teletrauma program links specialty providers for immediate collaboration and decision-making in emergency situations when a patient cannot be moved. The expansive connected care initiative shows how telehealth will continue to help providers overcome patient travel obstacles and clinician network limitations.

These five mHealth, telehealth, genomic medicine and decision-making tool advancements serve as a sampling of the current industry progress beyond initial EHR implementation. They are also clear examples of how healthcare organizations and technology companies are recognizing the industry shift toward consumerism and active patient engagement in care decisions. While they are encouraging first steps, expanded interoperability and integration are necessary to fully enable informed value-based patient care and diagnosis for wider patient communities across the country.



Bernie Monegain


Research team finds patterns of symptoms that might be caused by an underlying genetic variant.


Researchers at Vanderbilt University Medical Center are looking into diagnoses, such as heart failure, stroke, infertility and kidney failure to see whether they stem from undiagnosed genetic diseases.

The researchers are probing genetic data in EHRs to identify the diseases in large populations in order to tailor treatments to the true cause of the disease.

The findings are reported in the journal Science. Researchers found that 14 percent of patients with genetic variants affecting the kidney had kidney transplants and 10 percent with another variant required liver transplants.

If their genetic cause had been diagnosed, those transplants might have been avoided, the researchers note.

"We started with a simple idea: look for a cluster of symptoms and diseases to find an undiagnosed underlying disease," Josh Denny, MD, a professor of biomedical informatics and medicine and director of the Center for Precision Medicine at Vanderbilt. “We got really excited when we saw how we could systematize it across thousands of genetic diseases to figure out the impact of millions of genetic variants," Denny added.

The new method, developed by Denny, Lisa Bastarache and a team of collaborators, creates a phenotype risk score to find patterns of symptoms that may be caused by an underlying genetic variant. The findings include genetic variants whose effects were not known until now.

The authors figure that many patients currently diagnosed with issues such as heart failure, stroke, infertility or kidney failure might actually be suffering from rare genetic diseases. If that underlying disease could be identified, it might have a specific treatment that would prevent the symptoms from recurring or getting worse.

The researchers employed some new data mining techniques in their work.

"What the phenotype risk score shows us is that if you start with specific combinations of symptoms, the chances of finding a potentially causative genetic variant are pretty high,” they concluded.

“This is a really important step to using clinical genotyping to assess patient risk and inform more precise prevention and treatment of common conditions," Dan Roden, MD, senior vice president for personalized medicine at Vanderbilt and co-author of the study, said in a statement.

"Phenotype risk scoring can easily be applied in any electronic medical record system that is linked to DNA," Bastarache added. "Our work looked at only a small sample of the human genome, about 6,000 variants. The opportunity for additional discoveries using this method is huge."

Paige Minemyer

 

Healthcare leaders are increasingly on board with the trend toward value-based care, but barriers to interoperability are hampering the movement, they say. 

The Healthcare Financial Management Association (HFMA) surveyed 117 financial executives at U.S. hospitals about how ready their organizations are for value-based care. Few said their organizations are "highly capable" in areas crucial to success in these new payment models.  

External interoperability was of particular concern, with 24% saying their organization is not capable of sharing data with other providers and payers. More than 70% said the industry must make interoperability a top priority. 

Financial executives have grown more concerned about systems interoperability (or the lack thereof) since HFMA first conducted its value-based care readiness survey in 2015, it said in an announcement. In that survey, 68% said that interoperability would be a significant requirement in the future.

"Collaboration among health systems, physicians and health plans is the key to growing value-based payment," Joseph J. Fifer, HFMA's CEO, said in the announcement.

"Technology and other obstacles can be overcome if all stakeholders commit to working together for the benefit of the people we serve." 

Other barriers to success in value-based care include limited resources, inconsistency between different insurers and lack of physician support and engagement, according to the survey.  

Physicians are lukewarm on value-based care, so further engaging them in care transformation will be crucial. A recent survey found that few see value-based care as a way to lower costs, with 22% saying they believe accountable care organizations will reduce costs. 

Physicians also feel largely left out of discussions on value-based care and are more likely to embrace change if they're included.  

The financial executives who participated in the HFMA survey also widely said that ongoing regulatory uncertainty poses a significant challenge to continued adoption of value-based care programs. More than half (53%) said that updates including the Medicare Access and CHIP Reauthorization Act (MACRA) has a slightly negative influence on their ability to forecast success in value-based care, and 23% said it has a substantial negative influence. 

Despite challenges, the use of value-based payment models has grown over the past several years, according to HFMA.

Insurers' use of value-based care has increased from 12% in 2015 to 24% in 2017. And providers are seeing positive financial results, according to the survey. Seventy-four percent said they saw the benefits of value-based models, compared to 51% who said the same in 2015. 

Experts say it could provide a simpler way to predict cardiovascular risk

James Vincent

 

Scientists from Google and its health-tech subsidiary Verily have discovered a new way to assess a person’s risk of heart disease using machine learning. By analyzing scans of the back of a patient’s eye, the company’s software is able to accurately deduce data, including an individual’s age, blood pressure, and whether or not they smoke. This can then be used to predict their risk of suffering a major cardiac event — such as a heart attack — with roughly the same accuracy as current leading methods.

The algorithm potentially makes it quicker and easier for doctors to analyze a patient’s cardiovascular risk, as it doesn’t require a blood test. But, the method will need to be tested more thoroughly before it can be used in a clinical setting. A paper describing the work was published today in the Nature journal Biomedical Engineering, although the research was also shared before peer review last September.

Luke Oakden-Rayner, a medical researcher at the University of Adelaide who specializes in machine learning analysis, told The Verge that the work was solid, and shows how AI can help improve existing diagnostic tools. “They’re taking data that’s been captured for one clinical reason and getting more out of it than we currently do,” said Oakden-Rayner. “Rather than replacing doctors, it’s trying to extend what we can actually do.”

To train the algorithm, Google and Verily’s scientists used machine learning to analyze a medical dataset of nearly 300,000 patients. This information included eye scans as well as general medical data. As with all deep learning analysis, neural networks were then used to mine this information for patterns, learning to associate telltale signs in the eye scans with the metrics needed to predict cardiovascular risk (e.g., age and blood pressure).

Although the idea of looking at your eyes to judge the health of your heart sounds unusual, it draws from a body of established research. The rear interior wall of the eye (the fundus) is chock-full of blood vessels that reflect the body’s overall health. By studying their appearance with camera and microscope, doctors can infer things like an individual’s blood pressure, age, and whether or not they smoke, which are all important predictors of cardiovascular health.

When presented with retinal images of two patients, one of whom suffered a cardiovascular event in the following five years, and one of whom did not, Google’s algorithm was able to tell which was which 70 percent of the time. This is only slightly worse than the commonly used SCORE method of predicting cardiovascular risk, which requires a blood test and makes correct predictions in the same test 72 percent of the time.

Alun Hughes, professor of Cardiovascular Physiology and Pharmacology at London’s UCL, said Google’s approach sounded credible because of the “long history of looking at the retina to predict cardiovascular risk.” He added that artificial intelligence had the potential to speed up existing forms of medical analysis, but cautioned that the algorithm would need to be tested further before it could be trusted.

For Google, the work represents more than just a new method of judging cardiovascular risk. It points the way toward a new AI-powered paradigm for scientific discovery. While most medical algorithms are built to replicate existing diagnostic tools (like identifying skin cancer, for example), this algorithm found new ways to analyze existing medical data. With enough data, it’s hoped that artificial intelligence can then create entirely new medical insight without human direction. It’s presumably part of the reason Google has created initiatives like its Project Baseline study, which is collecting exhaustive medical records of 10,000 individuals over the course of four years.

For now, the idea of an AI doctor churning out new diagnoses without human oversight is a distant prospect — most likely decades, rather than years, in the future. But Google’s research suggests the idea isn’t completely far-fetched.

 

Kate Monica

 

Connecticut’s HIE will supply patient EHR data to help identify at-risk patients as part of a three-year suicide prevention initiative.

 

Connecticut’s state health information exchange (HIE) — CTHealthLink — will assist in an effort to leverage patient EHR data for improved suicide prevention, according to ShoreLine Times.

The HIE will provide centralized patient health data for a project funded by a $1.9-million, three-year grant from the National Institute of Mental Health. As part of the Institute’s initiative — called Zero Suicide — researchers will utilize patient EHRs to identify factors that may lead to suicide and spur prevention efforts targeting at-risk individuals.

Health data included in CTHealthLink includes information gathered from physician and psychotherapist practices, as well as hospital emergency departments.

UConn Health Division of Behavioral Sciences and Community Health chairman Robert Aseltine Jr. will lead the study to help providers identify and treat patients at risk of suicide.

“It bridges mental health, general health, hospital-based care,” he told ShoreLine

According to Connecticut State Medical Society CEO Matthew Katz, suicide attempts nationwide have increased by 24 percent in the last 10 years.

“Suicide is an urgent public health problem,” said Katz. “It’s the 10th leading cause of death in the U.S. It’s the second-leading cause of death among youth. Hospitalizations for suicide attempts in Connecticut have increased 15 percent between 2005 and 2015.”

CTHealthLink will give researchers access to clinical and psychological data as well as lab test results, and prescription information. Health data contained within the state HIE will be especially helpful in identifying teenagers exhibiting symptoms of depression.

“It’s often harder to get information on teens because they’re not going to the doctor as often,” Katz said. “We’re not doing a good job today identifying teens at risk of suicide.”

“They’re the ones we need,” he continued. “Where we need the most help in this country is identifying and treating youth who are at high risk for suicide.”

The HIE will also include social determinants of health data to help researchers identify individuals that may be at an increased risk of suicide due to unemployment, homelessness, or drug use.

“It helps track that information in a way that we’ve never seen before,” said Katz.

While the project aims to streamline the identification of patients that may potentially be at risk, patients will not be considered suicidal simply because they exhibit some symptoms or are subject to certain risk factors.

“We’re not going to say that patient is at risk,” Katz said. “What we’re going to say is, you need to ask questions, you need to do some identifications to assess whether that patient is at risk.”

Researchers will use CTHealthLink data along with a predictive model to get an idea of a patient’s risk of suicide over time.

“I’m using this infrastructure to create algorithms that will predict patient risk and to identify patients at risk of suicidal behaviors and to make that information available to their physicians so they can provide appropriate treatment,” said Aseltine.

“The same kind of models I’m using for suicide risk could be used to prevent re-hospitalizations, to improve medication adherence and medication management, to prevent a recurrence of cardiac events,” Aseltine continued.

To participate in the exchange, healthcare providers need to voluntarily opt-in and pay a fee. In addition to physicians and psychologists, social workers and dentists are encouraged to participate in the HIE.

 “We have to sign up a provider at a time,” said Katz.

Katz stated researchers expect to start seeing results from the study and its effect on identifying patients at-risk of suicide within 18 months.

Quality of Care Committee Chairwoman Claudia Gruss, MD, said the study could lead to primary care physicians doing yearly screenings for depression as part of annual patient check-ups.

“Obviously if it’s abnormal then we can take it a step further and either we discuss with the patient about depression and suicide prevention or we can set up a referral to a health-care professional who specializes in psychiatry or psychological social work or somebody who deals with treating depression either cognitively or through medication,” Gruss said.

CTHealthLink was established in fall of 2017 and is a member of the KaMMCO Health Solutions Network. The physician-led HIE was established by the Connecticut State Medical Society and allows clinicians, hospitals, and other in-network providers to exchange patient EHRs and utilize data analytics tools for improved patient health outcomes.

“I’m very excited about this project,” Gruss said. “I think it can markedly improve medical care.

Bernie Monegain

 

A consolidated architecture that combines patient data EHR with medication information could enable more informative and actionable medication alert systems, Charlie Hart says.

 

Charlie Hart, a pharmacy informaticist at Mercy Health, a four-hospital health system in northern Illinois and southern Wisconsin, is advocating for a rethink of medical alerts. He envisions alerts that are so relevant they would no longer be ignored.

Hart advocates alerts at the most effective point in the workflow and for integrating information from the electronic health record, with a drug knowledge database. As he sees it, this makeover would reduce nuisance alerts. Instead, warnings would provide guidance to boost clinical care.

"The EHR contains a wealth of information about the patient," he said.

But the problem is that traditional medication alerts do not leverage most of this EHR information. Vendors can be slow to program new functionality, he said, because they have a 12-to-18-month release cycle and they need to support multiple drug database products.

In turn, this makes it hard for the EHR vendor to develop and support additional advanced medication alerts features that are not supported by all drug database vendors.

Hart suggested employing a consolidated clinical document architecture to combine the patient information from the EHR and the critical medication information from the drug vendor database vendor. Those steps would allow for the integration of patient-specific information into medication alert systems.

What information is often lacking for caretakers? Traditional medication alerts are triggered by the medication, Hart pointed out.

"Basic patient information like age, sex, comorbidities and key labs are not evaluated when deciding if a medication alert is applicable to the patient and should be displayed to the clinician," he explained.

So Hart champions more specific medical alerts.

Traditional drug-to-drug interactions evaluate drug pairs, and if two drugs are known to interact with a high enough severity, an interruptive alert will be displayed to the clinician, he said.

When assessing the drug-to-drug pair, key patient information is not evaluated, Hart added. However, by incorporating these additional patient-specific factors, the decision to display an interruptive alert to a clinician can be more precise and more specific to the patient.

Hart is scheduled to present at the HIMSS18 session, “Zeroing in on the patient to reduce alert fatigue,” at noon March 9 in the Venetian, Murano 3304.

Erin Dietsche

A new survey out of Zebra Technologies found that an expected 97 percent of bedside nurses and 98 percent of physicians will use mobile devices in the hospital setting by 2022.

The Zebra study includes feedback from more than 1,500 nursing managers, IT decision makers and recently hospitalized patients in the United States, Brazil, China, Kuwait, Saudi Arabia, United Arab Emirates, Qatar and United Kingdom. All research was conducted in 2017.

Titled Future of Healthcare: 2022 Hospital Vision Study, it outlines the benefits of mobile technologies, as well as where the healthcare sector is headed as far as the topic is concerned. And according to the findings, the increasing adoption trend isn’t stopping anytime soon.

Regarding advantages, mobile devices cut back on mistakes. Sixty-one percent of nurses said mobile tech helped reduce medication errors. Fifty-six percent said it diminished specimen collection labeling errors, and 46 percent noted its assistance in reducing preventable medical errors.

Better communication is also a benefit. Sixty-seven percent of nurse managers said improved staff collaboration comes with clinical mobility. Forty-two percent said such devices helped with point-of-care decision-making.

Additionally, 55 percent of hospitals said mobile technology helps reduce the cost of patient care, and 72 percent noted it improves the quality of patient care.

The survey narrowed in on patient opinions as well. The majority of patients expressed a general liking for clinicians using mobile devices in their care, with 77 saying they felt positive about it. Ninety-five percent are willing to share electronic health data from wearables with hospital clinicians. And 37 percent of patients said they brought health monitoring data to the hospital in preparation for a stay.

Looking ahead, respondents predict mobile technologies will become more integrated into the healthcare experience. By 2022, 92 percent of surveyed nurses anticipate being able to access medical and drug databases using a mobile device. By the same time period, 91 percent of nurses expect to access EHRs on mobile devices, and 88 percent anticipate accessing lab diagnostic results on devices.

And it’s not just nurses who will see an increase in mobile technology adoption. According to the survey, 96 percent of pharmacists will use mobile devices by 2022, compared to 42 percent in 2017. Ninety-six percent of lab technicians are expected to use the technology, versus 52 percent last year.

“[T]here is a higher demand for services and support that are not sustainable with existing resources and methods,” the study notes. “Hospitals are increasingly turning to technology and automation to reduce the strain on an already fragile system.”

Kate Monica

 

Improved patient outcomes are tied to sharing diagnostic EHR data within health systems.

A recent study ties hospital and health system sharing of diagnostic EHR data to lower patient mortality rates and improve health outcomes.

Researchers studying CMS and AHA data published their findings in the American Journal of Managed Care. Specifically, Deyo et al. scrutinized information about patient mortality and readmission rates for heart failure and pneumonia in 2012 and 2013.

The AHA Annual Information Technology supplement gathered information from providers about their hospital’s health data sharing behaviors. Providers submitted responses about how frequently their hospital exchanged data between providers in their own health system, as well as with providers at outside health systems. AHA collected separate responses from providers about hospital sharing of radiology reports and lab results.

Researchers linked AHA survey data from 3,113 distinct hospitals to each hospital’s corresponding CMS Hospital Compare scores.

Ultimately, study results showed diagnostic EHR data sharing within health systems was associated with better health outcomes.

“Hospitals sharing diagnostic data through their EHRs with other hospitals and physicians within their system were associated with significant reductions in 30-day patient mortality scores,” stated researchers in the report.

Comparatively, sharing diagnostic EHR data with hospitals part of other health systems was associated with higher patient mortality scores – particularly for patients with heart failure.

Several factors may contribute to the correlation between EHR data sharing between health systems and higher patient mortality scores, researchers wrote.

“It is possible that hospitals within a system share EHR data more effectively due to team dynamics,” they suggested. “Further, as hospitals in different systems may have different EHR systems, there may be unique difficulties with sharing data across systems.”

Furthermore, the exchange of radiology reports may be limited by the fact that many patient health records do not contain radiology images.

“This may partially account for the differential between sharing with providers within and outside of systems because physicians within the system may be able to access the source images through other means when necessary,” wrote researchers. “Hospitals that solve the communication challenges associated with EHR data may be able to significantly reduce patient readmissions and mortality.”

Researchers also found communication between providers across EHR systems was generally lower than communication between providers using the same system. Seventy-two percent of hospitals shared radiology reports with hospitals within their system while only 36 percent shared radiology reports with hospitals outside their system.

Researchers observed a similar gap in the exchange of lab results within health systems as compared to between health systems.

Without significant improvements in EHR interoperability, the effectiveness of data sharing between hospitals will continue to lag behind data sharing within hospitals.

“If hospital sharing is limited by communication or compatibility among different EHR systems, the ability of EHRs to improve patient outcomes or access to care may be limited in the long run,” wrote researchers.

A lack of effective health data exchange between health systems may pose a significant threat to patient safety.

 “Our study found some evidence that when hospitals do share EHR data with hospitals outside their system, patient mortality has the potential to increase,” researchers explained. “Therefore, although there may be benefits to sharing EHR data, it may be that hospitals are not yet able to effectively use EHR data from other hospitals as well as would be desired.”

Given the low rate of diagnostic EHR data sharing between health systems, researchers suggested policymakers develop improved common standards for health data exchange between EHR systems.

“Thus, best approach for increasing patient outcomes through better provider communication of diagnostic information may not be simply expanding the degree of EHR data sharing among providers, but rather developing common standards when using different EHR systems to ensure that providers can share diagnostic information in ways that are easy for other providers to access and accurately interpret,” they concluded. 

Jessica Kent

 

Organizations can use EHR timestamp data to improve clinical workflows by approximating the time it takes to complete common tasks. The data may be able to help providers with refining scheduling methods, analyzing EHR use, and quantifying how trainees interact with health IT systems, according to a study published in JAMIA.

In order to better understand how this dataset could help optimize interactions with the EHR, Researchers observed and collected workflow data from four ophthalmologists within Oregon Health and Science University’s (OHSU) Epic EHR system.

They compared the observations of workflows to timestamp data generated within the EHR, and found that EHR timestamps provided a reasonable approximation of workflow.

For three of the four physicians, the EHR timestamp measurements were within one minute of the observed reference exam times on average.

Additionally, 84.3 percent of the EHR calculated exam times were within three minutes of the observed times, indicating that this dataset could offer providers an accurate substitute for manual observation.

“There are many possible uses of this large set of timing data available from all EHRs,” the researchers wrote.  

The team applied their findings to three different studies. The first used simulation models to test staff and exam room allocations and scheduling strategies that would prevent long wait times.

The models showed that adding staff and exam rooms didn’t reduce patient wait times, but scheduling patients who need more time toward the end of the day did help to control wait times throughout the day.

In addition to reducing patient satisfaction, long patient wait times can threaten healthcare revenue. This is especially true as the industry increasingly turns to value-based reimbursement models, in which clinicians are rewarded for providing timely access to quality care.

Researchers also applied their findings to a study on daily EHR use, and found that ophthalmologists use their EHR for an average of 3.7 hours per day. They also found that clinic volume and appointment complexity are two major factors that affect EHR use.

In general, researchers found that as patient volume increases, EHR use time decreases. However, they also found that when appointment complexity increases, so does EHR use time.

Since physicians with the highest clinic volume tend to see less complex patients, and vice versa, these findings suggest that patient volume is limited by the work required during exams. EHR use makes up a significant part of that work.

In fact, a 2017 study found that clinicians spend approximately 5.9 hours of an 11.4-hour workday on EHR documentation. This excessive amount of time spent on data entry has led to a spike in physician burnout, which negatively affects quality and cost of care.

Researchers also applied their findings to a third study that examined the impact of trainees on workflow. They found that trainees were associated with significantly longer appointment times for both fellows and residents.

While there are programs in medical schools that allow students to interact with EHR data before entering residency, the researchers write that these results show the effects trainees have on the “efficiency, productivity, and financial viability of academic medical centers.”

The application of EHR timestamp data to studies like this can lead to better planning and reimbursement models for clinics’ training activities, the researchers state.

Using this type of metadata can help justify EHR improvements. EHR optimization requires technology experts to assess the current system in place, and to examine how users interact with the EHR.

Knowing the factors that significantly impact EHR use can help experts decide where to make improvements, and ultimately increase EHR efficiency.  

Studying clinical workflow is a key way to gain insight for improving physician productivity. Providers are currently under pressure to see more patients in less time, and many believe that EHRs have only added to time pressure.

However, as the researchers indicate, workflow studies often require observational data that is too resource-intensive. The results of this study show that existing EHR timestamp data can help organizations boost physician productivity and increase patient satisfaction.

“These applications show the power of using existing EHR timing data for clinical workflow studies that would not have been possible otherwise and the possibilities for applying these methods to studies in other clinical settings,” the researchers concluded.

Evan Sweeney

 

The Centers for Disease Control and Prevention (CDC) has formed a new initiative focused on leveraging technology to get clinical guidelines in front of healthcare providers.

Through the initiative known as “Adapting Clinical Guidelines for the Digital Age,” CDC officials are looking for feedback from clinicians, EHR and third-party app developers and public health agencies about the best ways to disseminate clinical guidelines. The agency plans to hold a public meeting with stakeholders the week of February 5, according to a notice (PDF) posted this week to the Federal Register.

The CDC plans to use information from that meeting to pilot test new processes for guideline development and implementation.

“Because there are multiple roles in developing and disseminating clinical guidelines, it is important to get a comprehensive understanding of the current challenges in translating guidelines in order to develop a standardized process for the future,” the notice stated.

CDC spokesperson Melissa Brower told FierceHealthcare the initiative is "a natural extension" of an agencywide working group formed in 2016 looking at ways to ensure CDC guidance is used in practice. 

Using technology to quickly get information to clinicians, particularly during public health emergencies, is an issue the CDC has highlighted as an ongoing challenge. At a December meeting hosted by the Office of the National Coordinator for Health IT, the CDC’s Chesley Richards, M.D., who directs the Office of Public Health Scientific Service, said the Ebola outbreak led to “some soul-searching” about how the agency can improve clinical decision support.

Richards added that the CDC is especially interested in extracting data from EHRs to quickly identify outbreaks, while also limiting the reporting burden for physicians.

Eric Wicklund

 

Harvard Pilgrim Health Care is financing expansion of the eConsult telemedicine platform to two new Connecticut health systems, improving access to specialist services for patients and their doctors.

 

One of New England’s largest health plans is investing in a telemedicine platform that enables patients and their primary care providers to access specialty consults.

Harvard Pilgrim Health Care has awarded $32,000 in grants to two Connecticut health systems to expand the eConsult program, an innovative telemedicine program launched in 2015 by Middletown, Conn.-based Community Health Center (CHC) and now being used in about a dozen states across the country, including New York, Delaware and California.

Harvard Pilgrim has awarded $20,000 to Community eConsult Network to launch a year-long pilot through the Value Care Alliance (VCA). The pilot began last month at Middlesex Hospital Primary Care in Middletown nad is expected to expand soon to other VCA member organizations.

“The goal of this pilot program is to make it easier for patients to get the care they need by helping their primary care physicians obtain timely specialty consultations,” Russell Munson, MD, Harvard Pilgrim’s Connecticut Medical Director, said in a press release issued last November, when the grant was made. “In many cases, it will eliminate the need for additional appointments as well as time and travel by using technology to access prompt, high quality specialty care for patients. eConsults will help with access to specialist medical opinions, prescribing, ordering tests and the maintenance of patient medical records, bringing ease and efficiency to patients.”

In addition, the health plan has issued a $12,000 grant to help CeCN launch the telemedicine platform for the new Haven-based Community Medical Group. CMG’s Independent Practice Association serves New Haven, Shoreline and Fairfield counties with a network of some 900 primary care practitioners.

Working with the Weitzman Institute – CHC’s research and innovation arm - and Safety Net Connect, a California-based developer of online care coordination services, CHC launched its eConnect pilot in 2015. Working at first with cardiac care patients, the program routed all specialist referrals from CHC providers through an online system that allows the specialist to review the case online. This includes access to the patient’s medical record and any questions the primary care doctor may have about his/her diagnosis and treatment so far.

The model was originally developed to help federally-qualified health centers coordinate and improve care for the hard-to-reach Medicaid population.

CeCN officials say between 60 percent and 90 percent of the specialty consults have been resolved by the eConsult service since its launch, eliminating costly and unnecessary specialist appointments. More than 14 specialties are now available through the telemedicine platform, including cardiology, dermatology, gastroenterology, pediatric cardiology, orthopedics and pain management.

“Our work has clearly shown what a significant difference eConsults can make for primary care providers and their patients,” says Daren Anderson, MD, CHC’s vice president and chief quality officer and director of the Weitzman Institute. “They help to ensure that patients get access to the best care quickly and efficiently. Harvard Pilgrim is helping us to spread this work across Connecticut, helping build a stronger and more effective primary care system.”

Based on the 2015 pilot’s success, CHC and the Weitzman Institute created CeCN, a non-profit to manage and run the program. Shortly thereafter, the Centers for Medicare & Medicaid Services approved the program for Medicaid reimbursement.

“With limited specialty providers available to treat Medicaid patients, appointment wait times can be as long as a year, leading to healthcare disparities, higher rates of disability and complications in chronic diseases,” CMS officials said in a 2016 press release. “SNC’s eConsult system has been proven to increase access to timely, cost-effective specialty services for underinsured and underserved patients, many of whom live in rural areas with limited access to specialty care.”

John Donohue

 

Associate Vice President John Donohue divulges the system’s approach to telemedicine and videoconferencing, including the tech and governance components hospitals need to succeed.

While there is nothing really new about video-based collaboration — or even telemedicine for that matter — a technology ecosystem is emerging to make next-generation medical visits and business interactions mainstream. That means it should be a core component of hospital’s IT planning process. 

Video technology and clinical integration capabilities have reached a maturity level that makes enhanced collaboration a reality, and potentially a competitive differentiator.

Recently, we developed a three-tier video strategy for collaboration and telemedicine. Our strategy addresses a wide range of clinical visit types and business scenarios. Yet it is dynamic and agile enough to scale and handle future state requirements.  For example, our new patient bed tower will be opening in 2021 and we are preparing to include types of video technologies that might be built in to the core requirements of this acute care facility.

Additionally, our strategy addresses the legacy video technologies already in place across the enterprise with a transformation plan. Lastly, this scheme fits into our planning tenant of common systems, centrally managed and collaboratively implemented. 

The first component of our plan addresses clinical grade video technology. This offering is designed for more clinically oriented requirements. Examples of this type include video technology within our OR suites for grand rounds and physician education.  Additionally, this is the platform used for connected health (such as remote patient monitoring) and telemedicine solutions that touch patient care. This platform is designed with high resilience for maximum availability and has been integrated with our EHR for billing purposes. The collaboration required to design and build an integrated EHR/telemedicine capability is significant — but it paves the way for some game changing telemedicine offerings to your patient community.

Room-based video conferencing is another offering designed as a standards based collaboration technology to use throughout our health system which has grown exponentially in size and geographical footprint. Picking the right technology partner and a solution that is both easy to use and scales appropriately is instrumental in our success. We are also able to collaborate more easily outside the organization communicating with U.S. and even overseas business relationships. Interoperability is the name of the game when it comes to bridging outside your organization. This interoperability should include other industry leading room service providers and cloud service providers. For our room based video conferencing, we have templates that help guide new implementations and budget estimates for upcoming construction projects. These include one for senior executive/trustee level rooms, one with a higher level of technology for specific requirements and one for basic audio/visual needs. All of our rooms are tied back to a central control center for monitoring, support and troubleshooting.

Lastly, the mobile and desktop video conferencing is the most flexible of our tiers and is used for collaboration among staff level folks across the organization. Here we leverage our network infrastructure across to deliver unified communications capabilities. Cost is low and it’s easy to implement. The technology is already paying dividends for collaboration.

Most recently, we are piloting a concept called “VC in a Box”.  This concept includes the capability to have a mobile video conferencing configuration that can be moved around the organization for special events that don’t occur in a previously designed video conferencing room. The early success in this pilot leads me to believe that we may wind up with several of these setups as a new offering.

When rolling out video technology like this across a broad, diverse and complex organization, communication becomes paramount. How you explain these offerings (via a service catalog) and make it easy for the user community to select the right technology at the right time is key to acceptance and driving the benefits of its use. We created a video technology governance committee that steers the direction and becomes a set of champions. This group ultimately helps us with communications and the development of an effective portal for how to engage the services and maybe most importantly how to get a session scheduled and get the support that is needed. 

Our portal offers white glove support and even addresses things like re-arranging the room for an event and having food and beverages delivered. Lastly, the portal allows for calendar synchronization so that it is tightly integrated with the scheduling of the room itself.

Ultimately, having an effective and easy to use video technology ecosystem can allow a growing organization to drive down travel costs, increase collaboration and ultimately provide better patient care to drive enhanced outcomes.