Free EMR Newsletter Want to receive the latest news on EMR, Meaningful Use, ARRA and Healthcare IT sent straight to your email? Join thousands of healthcare pros who subscribe to EMR and EHR for FREE!

AMA Says Med Students Don’t Get Enough EHR Training

Posted on June 20, 2018 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

Whether or not doctors like it, the U.S. healthcare industry has embraced EHR technology, and in most cases, medical groups depend on it for a number of reasons. Now, the industry may be taking the next step in this direction, with the AMA deciding that it’s time to enshrine EHR use as part of medical education.

At its recent annual meeting, the AMA released a new policy embracing two somewhat contradictory notions. On the one hand, it encouraged med schools to train students on using EHR technology, while on the other, underscored the need for future doctors to get their faces out of the computer screen and engage with patients.

According to the trade group, some medical schools actually limit student access to EHRs. The AMA contends that this is a bad idea. “Medical students and residents need to learn how to ensure quality clinical documentation within an electronic health record,” said AMA board member and medical student Karthik Sarma in a prepared statement. “There is a clear need for medical students to have access to – and learn how to properly use – EHRs well before they enter practice.”

That being said, the group’s report on this subject concedes that there’s a long way to go in making this happen. For example, it notes that many med school faculty members aren’t offering students and residents much of a role model for the appropriate use of and practices in working with EHRs.

To address this problem, the new policy urges medical schools and residency programs to design clinical documentation and EHR training. It also recommends that the training be evaluated to be sure that it’s useful for future medical practice.

The AMA also suggests that med schools and residency programs provide faculty members with EHR professional development options. These lessons will help faculty serve as better role models on EHR use during interactions between physicians and patients.

That being said, there is an inherent tension between these goals and the realities of EHR use. Yes, training students to create good clinical documentation makes sense. At the same time, there are good reasons to worry about the effects of EHRs on student and resident relationships with patients. Unfortunately, this problem seems to be unavoidable as things stand today. Either you train budding physicians to be clinical documentation experts or you encourage them to use EHRs as little as possible during patient encounters.

In short, we’ve already learned that we can’t have both at the same time. So what’s the point of telling medical students that they should try to do the impossible?

Hospitals, Doctors And Patients Impacted By Unplanned EHR Downtime

Posted on June 18, 2018 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

EHRs are going to crash and go offline from time to time. But are physicians and hospitals prepared to deal with the fallout when this happens? The answer seems to be “maybe.”

Of course, physicians and hospitals have plenty of reasons to avoid EHR downtime.

For one thing, EHR crashes can have a major impact on care delivery. After all, without EHRs, physicians may have no access to patient data, which could lead to care complications or adverse events.

Also, downtime adds addition pain (and expense) to the situation. According to one estimate, unplanned system failures can cost $634 per physician per hour. Meanwhile, according to Dean Sitting of the University of Texas, a large hospital may lose as much as $1 million per hour when their EHR is down. Those are scary numbers.

Unfortunately, despite the costs, strain to the hospital operations and consumer complaints arising from downtime, many hospitals refuse to invest in preventive technologies such as a backup data center, arguing that they’re just too expensive. As a result, hospitals can be offline for a long time when their EHR system crashes, which typically has a nasty ripple effect.

One example of how EHR downtime affects hospital operations comes from Sutter Health, the largest health system in northern California, whose EHR went offline for more than 24 hours in May. The crash took place when a fire-suppression system was activated in the system’s data center.

During the shutdown, Sutter hospitals followed a series of steps often used by its peers, such as cutting elective surgeries, transporting patients to other hospitals and discharging patients who weren’t very sick. They also switched over to paper records. But despite these efforts, Sutter still faced some problems that weren’t addressed by its plans.

For one thing, younger doctors were thrown a curve ball, as many had never worked with paper charts. This alone gummed up the works during the downtime episode. There were no signs that these doctors made any mistakes due to using paper records, but the risk was there.

Then there were the effects on patients – and some were ugly. For example, when Santa Clara resident Susan Harkema’s father died, she called Sutter Health’s Hospital of the Valley to arrange for removal of his body to a crematorium. According to a story appearing in San Jose Mercury News, Harkema tried a hotline and backup numbers but couldn’t reach anyone due to the outage. It took 8 hours for a hospice nurse to arrive and collect the body, the newspaper reported.

Another patient tweeted that they had to go out of the Sutter system for critical care, which left the treating physicians without care history to review. “It was stressful and scary, and we still aren’t sure we have a successful outcome,” they said.

The net of all of this seems to be that hospital downtime policies could use more than a few tweaks, and more importantly, a better failsafe protecting EHRs from going offline in the first place. Sure, no EHR system is perfect, and crashes are inevitable, but providers can be better prepared.

Geisinger, Penn State Researchers Predict Risk Of Rehospitalization Within Three Days Of Discharge

Posted on June 15, 2018 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

In recent times, healthcare organizations have focused deeply on the causes of patient readmissions to the hospital. It’s a problem that affects both physicians and health systems, particularly if the two are not in synch.

To date, providers have focused on readmissions happening within 30 days, largely in an effort to avoid financial penalties imposed by Medicare and Medicaid. However, if the following research is solid, it could push the focus of care much closer to hospital discharge dates.

In an effort which could change the process of avoiding readmissions, a group of researchers has found a way to predict a patient’s risk for needing additional medical care within three days of discharge. The new approach developed jointly by Penn State and Geisinger Health Plan, relies on clinical, administrative and socio-economic data drawn from patients admitted to Geisinger over two years.

The model they created is known as REDD, an acronym which stands for readmission, emergency department or death. Using this model can help physicians target interventions effective and reduce the number of adverse events, according to Deepak Agrawal, one of the Penn State researchers.

You won’t be surprised to hear that readmissions after 30 days are often related to social determinants of health, such as a poor home environment, limited access to services and scant social support. Providers are certainly working to close these gaps, but to date, this has remained a major challenge.

However, the dynamics are different when finding patients who may be readmitted quickly. “Readmissions closer to discharge are more likely to related to factors that are actually present but are not identified at the time the patient is discharged,” said research team leader Sundar Kumara, Allen E. Pearce and Allen M. Pierce Professor of Industrial Engineering with Penn State, who was quoted in a prepared statement.

Another Penn State researcher, Cheng-Bang Chen, added another interesting observation. He noted that the more time that passes after a patient gets discharged, the less likely it is that problems will be caught in time. After all, it may be a while before treating physicians have time to review lengthy hospital records, and the patient could experience a time-sensitive event before the physician completes the review.

To test the REDD program, Geisinger ran a six-month pilot tracking high-risk patients and adding additional services designed to avoid readmissions, ED visits or death.

To treat this population effectively, physicians took a number of steps, such as scheduling appointments with patients’ primary care doctors, educating patients about their medications and post-discharge care plans,  having the inpatient clinical pharmacist review the provider’s recommendations, filling patient prescriptions before discharge and having the hospital check on patients discharged to a skilled nursing facility one day after discharge.

It’s worth noting that there was one major issue which undermined the research results. Penn State reported that because of a shortage of nurses at the hospital during the pilot, they couldn’t tell whether the REDD program met its goals.

Still, researchers are convinced they’re heading in the right direction. “If the REDD model was fully implemented and aligned with clinical workflows, it has the potential to dramatically reduce hospital readmissions,” said Eric Reich, manager of health care re-engineering at Geisinger.

Let’s hope he’s right.

Early Lessons from the Front Lines of Value-based Care: How One APM Has Impacted Community-Based Oncology Practices

Posted on June 11, 2018 I Written By

The following is a guest blog post by Dr. Charles Saunders, CEO, Integra Connect.

The Oncology Care Model (OCM) – an alternative payment model introduced in July 2016 by the Center for Medicare and Medicaid Innovation – launched with the ambitious goal to further delivery of higher quality, more coordinated cancer care at a lower cost. Participants include 184 practices representing approximately one-third of community oncologists in the US. They receive a so-called “MEOS” (monthly enhanced oncology services) payment of $160 per beneficiary per month for the duration of a qualifying 6-month chemotherapy period, plus the opportunity to earn a share of savings if they exceed a target threshold. In return, oncologists are expected to take on increasing accountability for patient outcomes and well-being, while also generating sustainable cost savings across all co-morbidities and care settings, into the patient home.

OCM Performance Period 1 Results Exposed an Unexpected Misalignment   

As part of the OCM program, CMS tracks practices during 6-month intervals – so-called “performance periods” – then shares results back about one year later. In February 2018, practices participating in the OCM program received visibility into Performance Period 1 (PP1) data, including savings achieved, aggregate quality score, and effectiveness of identifying eligible patients. While most practices were unsurprised by their performance scores, many did not anticipate the extent to which CMS would recoup MEOS payments that it deemed paid in error. The most common scenario involved patients with co-morbidities who, while receiving chemotherapy and related services, also visited other providers regularly. Therefore, the oncology practice did not represent the required plurality of E/M codes for that beneficiary. It was not uncommon for practices to be asked to return up to 30% of the sum they had been paid – a major financial hit.

Lack of Data Hinders Practices’ Ability to Accurately and Proactively Identify Beneficiaries

In May 2018, practices received their Performance Period 2 (PP2) Attribution Lists, which summarized which CMS beneficiaries met OCM eligibility criteria, which episodes were attributed to each respective practice, and episode start dates from January 1, 2017 through June 30, 2017. Unfortunately, because there is a significant lag between actual Performance Period and delivery of CMS findings – delayed up to nearly a year after each performance period has ended – OCM participants were unable to retroactively apply PP1 learnings to PP2.

Why is this especially problematic? Practices are faced not only with MEOS recoupments for erroneous payments but, with only a 1-year window to submit claims, are often unable to bill in full for patients who were missed. Indeed, there are many opportunities to miss appropriate patients, as practices needed to have an accurate view of: 1) all beneficiaries; 2) those with a qualifying diagnosis; 3) those with a new chemo episode; 4) those not only prescribed an oral agent, but those who subsequently filled it; 5) those not in a hospice; and more. Given all the dimensions to track and measure, practices without advanced tools face delivering enhanced services that they cannot correctly bill for.

Best Practices from Community-Based Oncology Practices Include Robust Data

What best practices arose to get attribution right? A vanguard of OCM practices realized that they would need to take proactive steps to enable near real-time visibility into their patient populations, embracing the tenets of population health management. Below is an example of the best practices adopted by several of these community-based oncology practices:

  • Increased transparency into oral chemotherapies: Existing practice protocols did not open an episode when oral agents were prescribed, since there was no in-office administration. To address this, the practice introduced a rule-based algorithm to identify all OCM eligible patients, including those who had been prescribed orals. In addition, they enlisted a combination of automated and personal follow-ups to validate qualification and ensure orals had been filled.
  • Avoidance of duplication: To identify missed billing opportunities while also reducing the risk of duplicated claims, practice leadership invested in a robust analytics tool that enabled personalized queries at the patient level. These reports compared eligibility against their practice management report to identify gaps, from unpaid and unbilled to denied.
  • Targeted patient intervention: To balance the practice’s financial and clinical objectives while optimizing OCM performance, the practice introduced complex care management services and employed a series of triage pathways. This approach ensured engagement with attributed beneficiaries and decreased avoidable high-cost events among at-risk patients, such as inappropriate ER visits and inpatient stays.
  • Optimized treatment choices. As part of its commitment to ensure each patient received the most effective treatment for his or her disease, the practice provided increased transparency around the availability of equally effective generic or biosimilar drugs. They also supported better end-of-life planning for patients facing second or third-line therapies not expected to provide any clinical benefits, but that could significantly degrade remaining quality of life.
  • Continuous performance improvement: To track the effectiveness of these quality improvement initiatives, the practice leveraged its analytics tool to monitor resource utilization and care management performance, then intervened to address outliers in real-time.

In short, to optimize performance under the OCM, practices are beginning to leverage the data to which they already have access – both clinical and financial – to risk-stratify their patient populations; identify OCM eligible patients; and gain near real-time visibility into quality and cost performance. Practices are also investing in better data integration and analytics that enable rules-based identification of eligible patients.

Population Health Analytics Help Practices Be Proactive and Succeed Under the OCM

Oncology is on the forefront of value-based care adoption and these early experiences from the OCM have provided a guide for other specialties. Based on their early results, what has come to the forefront is the need for a combination of comprehensive data management and robust analytics, coupled with the principles of population health management, which enable practices to step up and take control of the cost and quality for their attributed populations.

This Futurist Says AI Will Never Replace Physicians

Posted on June 6, 2018 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

Most of us would agree that AI technology has amazing — almost frightening — potential to change the healthcare world. The thing is, no one is exactly sure what form those changes will take, and some fear that AI technologies will make their work obsolete. Doctors, in particular, worry that AI will undercut their decision-making process or even take their jobs.

Their fears are not entirely misplaced. Vendors in the healthcare AI world insist that their products are intended solely to support care, but of course, they need to say that. It’s not surprising that doctors fret as AI software starts to diagnose conditions, triage patients and perform radiology readings.

But according to medical futurist Bertalan Mesko, MD, Ph.D., physicians have nothing to worry about. “AI will transform the meaning of what it means to be a doctor; some tasks will disappear while others will be added to the work routine,” Mesko writes. “However, there will never be a situation where the embodiment of automation, either a robot or an algorithm, will take the place of a doctor.”

In the article, Mesko lists five reasons why he takes this position:

  1. Empathy is irreplaceable: “Even if the array of technologies will offer brilliant solutions, it would be difficult for them to mimic empathy,” he argues. “… We will need doctors holding our hands while telling us about life-changing diagnoses, their guide to therapy and their overall support.”
  2. Physicians think creatively: “Although data, measurements and quantitative analytics are a crucial part of a doctor’s work…setting up a diagnosis and treating a patient is not a linear process. It requires creativity and problem-solving skills that algorithms and robots will ever have,” he says.
  3. Digital technologies are just tools: “It’s only doctors together with their patients who can choose [treatments], and only physicians can evaluate whether the smart algorithm came up with potentially useful suggestions,” Mesko writes.
  4. AI can’t do everything: “There are responsibilities and duties which technologies cannot perform,” he argues. “… There will always be tasks where humans will be faster, more reliable — or cheaper than technology.”
  5. AI tech isn’t competing with humans: “Technology will help bring medical professionals towards a more efficient, less error-prone and more seamless healthcare,” he says. “… The physician will have more time for the patient, the doctor can enjoy his work in healthcare will move into an overall positive direction.”

I don’t have much to add to his analysis. I largely agree with what he has to say.

I do think he may be wrong about the world needing physicians to make all diagnoses – after all, a sophisticated AI tool could access millions of data points in making patient care recommendations. However, I don’t think the need for human contact will ever go away.

Patient Satisfaction Drops After Ambulatory EHR Is Rolled Out

Posted on June 4, 2018 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

In theory, EHR implementations are supposed to not only make providers’ jobs easier but ultimately, improve patient satisfaction too. The idea is that EHRs will eventually add something beneficial to physician routines and ultimately improving care processes. Of course, there’s a lot of question as to whether EHRs can now or will ever do so, but researchers continue to look at different use cases.

For example, new research published in JAMIA has concluded that while they weren’t too thrilled by the ambulatory EHR they were using, a group of OB/GYN practices showed some enthusiasm once the outpatient EHR was attached to the one collecting data on their related inpatient perinatal unit.

The purpose of the study was to look at how the installation of the ambulatory EHR within the OB/GYN practices and subsequent connection to an inpatient perinatal EHR affected providers’ attitudes toward sharing of clinical information. It also looked at the impact all of this had on patient satisfaction.

To conduct the study, researchers collected data on both provider and patient satisfaction. They assessed provider satisfaction by conducting four surveys staged across the phased implementation of the EHR. To measure patient satisfaction, meanwhile, they drew on data from Press Ganey surveys managed by the healthcare network using the usual process.

Their ultimate goal was to determine how provider and patient perceptions changed as the EHR system enabled greater information flow between the OB/GYN practices in the hospital.

What the study found was that the outpatient OB/GYN providers were less satisfied with how the EHR affected their work processes than other clinical and non-clinical staff. On the other hand, they grew more satisfied with their access to information once the inpatient perinatal triage unit offered useful functions. Specifically, they were happier with their access to information from the inpatient system once its capabilities included the ability to send automatic data flows from triage back to the OB/GYN offices.

On the other hand, overall patient reactions to the project appeared to be negative. Patient satisfaction fell after the installation of the ambulatory EHR, and researchers could find no evidence that patient satisfaction rebounded after the information sharing process began between inpatient and outpatient settings.

In summary, the study concluded, if providers are dissatisfied with their EHR system, and those difficulties undercut patient care, the process could negatively impact patient satisfaction. The authors recommended that healthcare organizations take extra care to maintain good communication with patients during this process.

Recording Doctor-Patient Visits Shows Great Potential

Posted on June 1, 2018 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

Doctors, do you know how you would feel if a patient recorded their visit with you? Would you choose to record them if you could? You may soon find out.

A new story appearing in STAT suggests that both patients and physicians are increasingly recording visits, with some doctors sharing the audio recording and encouraging patients to check it out at home.

The idea behind this practice is to help patients recall their physician’s instructions and adhere to treatment plans. According to one source, patients forget between 40% to 80% of physician instructions immediately after leaving the doctor’s office. Sharing such recordings could increase patient recall substantially.

What’s more, STAT notes, emerging AI technologies are pushing this trend further. Using speech recognition and machine learning tools, physicians can automatically transcribe recordings, then upload the transcription to their EMR.

Then, health IT professionals can analyze the texts using natural language processing to gain more knowledge about specific diseases. Such analytics are likely to be even more helpful than processes focused on physician notes, as voice recordings offer more nuance and context.

The growth of such recordings is being driven not only by patients and their doctors, but also by researchers interested in how to best leverage the content found in these recordings.

For example, a professor at Dartmouth is leading a project focused on creating an artificial intelligence-enabled system allowing for routine audio recording of conversations between doctors and patients. Paul Barr is a researcher and professor at the Dartmouth Institute for Health Policy and Clinical Practice.

The project, known as ORALS (Open Recording Automated Logging System), will develop and test an interoperable system to support routine recording of patient medical visits. The fundamental assumption behind this effort is that recording such content on smart phones is inappropriate, as if the patient loses their phone, their private healthcare information could be exposed.

To avoid this potential privacy breach, researchers are storing voice information on a secure central server allowing both patients and caregivers to control the information. The ORALS software offers both a recording and playback application designed for recording patient-physician visits.

Using the system, patients record visits on their phone, have them uploaded to a secure server and after that, have the recordings automatically removed from the phone. In addition, ORALS also offers a web application allowing patients to view, annotate and organize their recordings.

As I see it, this is a natural outgrowth of the trailblazing Open Notes project, which was perhaps the first organization encouraging doctors to share patient information. What makes this different is that we now have the technology to make better use of what we learn. I think this is exciting.

Medicare ACOs May Be Slated For Big Changes — And Health IT May Be Part Of It

Posted on May 25, 2018 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

Before I get started, I want to offer a hat tip to Becker’s Hospital Review, which turned me onto the following news. That news, in brief, is that CMS might make changes to its ACO program that could have a big impact on the doctors and hospitals that participate.

According to Becker’s, CMS Administrator had some negative things to say about so-called “upside only” risk contracts, which don’t pay out anything to the agency if they miss financial and clinical benchmarks: “These ACOs are actually increasing Medicare spending, and the presence of these ‘upside-only’ tracks may be encouraging consolidation in the marketplace, reducing competition and choice for beneficiaries,” Verma told the AHA’s Annual Membership Meeting earlier this month.

At present, a whopping 460 of 561 ACOs in the Medicare Shared Savings Program are in Track 1, the agency’s upside-only program. At present, ACOs can only participate in two three-year contracts on this track, so next year 82 ACOs will be required to take on financial risk. Obviously, they don’t like this.

However, CMS isn’t exactly being unreasonable to consider curtailing Track 1. Looked at one way, the Medicare Shared Savings Program has failed utterly achieving its core purpose, and upside-only contracts are the primary reason.

According to Becker’s, which cited research from Avalere, while the program was supposed to generate $1.7 billion in net savings from 2013 to 2016, upside-only contracts were responsible for $444 million in federal spending. On the other hand, downside-risk ACOs cut spending by $60 million, a relatively tiny number when you consider the scale of CMS’s budget but positive side nonetheless.

All that being said, let me interject here and note that HIT may be part of the problem. I’m betting some of the expected savings was based on assumptions about how health IT would help ACOs meet clinical and financial benchmarks.

After all, the federal government spent many billions of dollars paying doctors and hospitals Meaningful Use incentive, which obviously gave them a convincing reason to adopt EMRs. No one approves that level spending without believing it would make everything better.

As it turns out, though, that might have been a flawed assumption. If I’m right, the Track 1 failure suggests that health IT isn’t doing as much to create efficiencies as federal health leaders had hoped. I know, particularly if you’re a doctor reading this, you’re saying “I could’ve told you this a decade ago.” Still, it’s worth repeating.

While health IT organizations — especially those housed in progressive health systems — are making great progress with improving care, we haven’t met the lofty goals of such approaches by any means. But if they want to progress toward value-based care, they’ll probably have to put their health IT to better use.

Competition Heating Up For AI-Based Disease Management Players

Posted on May 21, 2018 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

Working in collaboration with a company offering personal electrocardiograms to consumers, researchers with the Mayo Clinic have developed a technology that detects a dangerous heart arrhythmia. In so doing, the two are joining the race to improve disease management using AI technology, a contest which should pay the winner off handsomely.

At the recent Heart Rhythm Scientific Sessions conference, Mayo and vendor AliveCor shared research showing that by augmenting AI with deep neural networks, they can successfully identify patients with congenital Long QT Syndrome even if their ECG is normal. The results were accomplished by applying AI from lead one of a 12-lead ECG.

While Mayo needs no introduction, AliveCor might. While it started out selling a heart rhythm product available to consumers, AliveCor describes itself as an AI company. Its products include KardiaMobile and KardiaBand, which are designed to detect atrial fibrillation and normal sinus rhythms on the spot.

In their statement, the partners noted that as many as 50% of patients with genetically-confirmed LQTS have a normal QT interval on standard ECG. It’s important to recognize underlying LQTS, as such patients are at increased risk of arrhythmias and sudden cardiac death. They also note that that the inherited form affects 160,000 people in the US and causes 3,000 to 4,000 sudden deaths in children and young adults every year. So obviously, if this technology works as promised, it could be a big deal.

Aside from its medical value, what’s interesting about this announcement is that Mayo and AliveCor’s efforts seem to be part of a growing trend. For example, the FDA recently approved a product known as IDx-DR, the first AI technology capable of independently detecting diabetic retinopathy. The software can make basic recommendations without any physician involvement, which sounds pretty neat.

Before approving the software, the FDA reviewed data from parent company IDx, which performed a clinical study of 900 patients with diabetes across 10 primary care sites. The software accurately identified the presence of diabetic retinopathy 87.4% of the time and correctly identified those without the disease 89.5% of the time. I imagine an experienced ophthalmologist could beat that performance, but even virtuosos can’t get much higher than 90%.

And I shouldn’t forget the 1,000-ton presence of Google, which according to analyst firm CBInsights is making big bets that the future of healthcare will be structured data and AI. Among other things, Google is focusing on disease detection, including projects targeting diabetes, Parkinson’s disease and heart disease, among other conditions. (The research firm notes that Google has actually started a limited commercial rollout of its diabetes management program.)

I don’t know about you, but I find this stuff fascinating. Still, the AI future is still fuzzy. Clearly, it may do some great things for healthcare, but even Google is still the experimental stage. Don’t worry, though. If you’re following AI developments in healthcare you’ll have something new to read every day.

Nurse Satisfaction With EHRs Rises Dramatically, But Problems Remain

Posted on May 18, 2018 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

In the past, nurses despised EHRs as much as doctors did – perhaps even more. In fact, in mid-2014, 92% of nurses surveyed weren’t satisfied with the EHR they used, according to a study by Black Book Research. But things have changed a lot since then, Black Book says. The following data is focused largely on hospital-based nursing, but I think many of these data points are relevant to medical practices too.

Despite their previous antipathy to EHR’s, as of Q2 2018, 96% of nurses told Black Book that they wouldn’t want to go back to using paper records. That score is up 24% since 2016, the research firm reports.

Part of the reason the nurses are happier is that they feel they’re getting the technical support they need. Eighty-eight percent of responding nurses said that their IT departments and administrators were responding quickly when they asked for EHR changes, as compared with 30% in 2016.

On the other hand, the study also noted that when hospitals outsource the EHR helpdesk, nurses don’t always like the experience. Twenty-one percent said their experience with the EHR’s call center didn’t meet their expectations for communication skills and product knowledge. On the other hand, that’s a huge improvement from 88% in 2016.

Not only that, RNs are eager to improve their EHR skillsets. Most nurses are now glad that they are skilled at using at least one EHR, and 65% believe that persons who are skilled at working with multiple systems are seen as highly-desirable job candidates by health systems.

Providers’ choice of EHR can be an advantage for some in attracting top dressing talented. Apparently, RNs are beginning to choose job openings for the EHR product and vendor the provider uses as an indication of how the working environment may be than the provider itself. Eighty percent of job-seeking RNs reported that the reputation of the hospital’s EHR system is one of the top three considerations impacting where they choose to work.

That being said, there are still some IT issues that concern nurses. Eighty-two percent of nurses in inpatient facilities said they don’t have computers in each room or handheld/mobile devices they can use to access the EHR. That number is down from 93% in 2016, but still high.

These statistics should be of great interest to both hospitals and physicians. Obviously, hospitals have an institutional interest in knowing how nurses feel about their EHR platform and how they supported. Meanwhile, while most average size practices don’t address the same IT issues faced by hospitals, it benefits them to know what their nurses are looking for in a system. There’s much to think about here.