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A Canadian Hospital Leverages IT to Optimize the Prevention of “Code Blues”

March 17, 2017
by Mark Hagland
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Leaders at Hamilton Health Sciences in Ontario optimize clinical processes to avert patient emergencies

IT and clinician leaders are breaking important ground at Hamilton Health Sciences, the six-facility health system in Hamilton, Ontario, Canada, an academic research teaching facility affiliated with McMaster University that serves a 2.5-million population in Ontario, and that encompasses a children’s hospital, labor and delivery, and a cancer center, with 12,000 staff.

At Hamilton Health Sciences, vice president of health information technology services and CIO Mark Farrow, who leads a team of about 140 IT professionals, has been co-leading an important initiative around the alerting of clinicians to the rapid deterioration of patient conditions, along with Alison Fox-Robichaud, M.D., a physician in the Department of Critical Care. Farrow brought together a project team of five clinical informaticists, with five clinicians led by Dr. Robichaud.

Essentially, what Farrow, Fox-Robichaud, and their colleagues have done, is this: they’ve built an automated alerting system, leveraging Android smartphones, that involves the alerting of a rapid response team to patient condition results that show the deterioration of patients who are on the regular medical/surgical floors of the inpatient hospital. The Hamilton Health Services leaders have partnered with the Toronto-based ThoughtWire and with the Armonk, N.Y.-based IBM Corporation, to develop the fully automated solution. The results have been strong, including the virtual elimination of code-blue alerts in the inpatient hospital, and a drastic reduction in ICU admissions from the med/surg floors.

For their innovative work in this area, the Hamilton Health Services leaders in January received two awards from the Intelligent Health Association, an association of information technology vendors. It received both the IHA’s 2017 Award for Improving Patient Care and Health Delivery, and its 2017 Intelligent Health Grand Award.

As ThoughtWire noted in a press release issued on Jan. 23, “Through the use of an innovative early warning score (EWS), HHS is improving hospital safety by eradicating in-hospital cardiac and respiratory arrests.  With the EWS, clinicians are apt to respond to abnormal vital signs before patients progress to experience in-hospital arrests. “We believe that most cardiac arrests in an acute care setting should be considered a failure to rescue,” said Alison Fox-Robichaud, M.D., the clinical leader behind the Early Warning Score (EWS) project.  Dr. Fox-Robichaud’s clinical team was complimented by members of the Health Information Technology Services group led by Mark Farrow, vice president and chief information officer at Hamilton Health Sciences. 

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To enhance this initiative and move toward achieving even better care outcomes, HHHS collaborated with ThoughtWire and IBM Canada to find an innovative way to address the key factors that were inhibiting the initial EWS results.  Leveraging ThoughtWire’s Ambiant Health Platform, the team created a Mobile Early Warning Score Application that works in real time with Meditech. Today, nurses capture vitals at the bedside on their mobile devices. The data is then integrated into the Meditech electronic medical record system, which computes the EWS.  Based on HHS research, each score prompts the Ambiant Platform to drive a standard set of notifications and responses to the appropriate members of the care team, while machine intelligence ensures that standardized best practices are consistently executed. 

The early results have been powerful: HHS has seen a 17-percent decrease in the number of Critical Care Response Team consults requiring ICU admission and a 6-percent reduction in cardiopulmonary resuscitation (CPR) requiring Code Blue calls.  “Before rapid response teams were in place, you would hear code blue calls on average once or twice a day in the hospital’s wards,” Dr. Fox-Robichaud, said. “Fast forward to 2016 and I can now go an entire week without hearing a code blue on the wards. While they have not been eliminated, we hear far fewer – and that means that patients are staying safe.”    

Farrow spoke recently with Healthcare Informatics Editor-in-Chief Mark Hagland regarding this initiative. Below are excerpts from that interview.

Tell me about the origins of this initiative?

The Hamilton Early Warning Score (HEWS) started as a research project, and it was one of our residents’ research projects on a couple of units. We very quickly saw the merits of it and looked to see what we could do to move it forward very quickly. And one of the challenges is always, when you find evidence, how do you move it to the bedside? So, we first created it on paper to build it out, and quickly built it into the Meditech system. There wasn’t a lot of process, but it allowed us to process it and have the scores calculated automatically, and it would populate an action plan based on a score. We needed to reduce a lot of lag time. While people were documenting in Meditech, they weren’t necessarily documenting in real time. And it’s not helpful to document at the end of the shift, and have the system say, oh by the way, your patient was going to have a heart attack three hours ago, when they already did. So, it needs to be done in real time. You need to be able to create it as part of the culture of the unit. And the way to do that is to not only show that there’s benefit to this, and in a way, that doesn’t impede their workflow.


Mark Farrow

So, this had to be relatively un-intrusive to nurses. We had put in mobile carts, the computers on wheels, but they weren’t getting a good uptake; they were difficult to push around. We had the documentation in the system, but people were still putting pieces of paper in their pockets and coming back to it later. So, we needed to be able to put this data in several different places, but still have one piece of truth, with a communication link. But the second part of this is not just generating the score, but clinically, whom do you notify? And one of the challenges is, what happens if a floor nurse gets an alert at midnight, what does she do?

So, what does happen now, since the deployment of this solution and process?

So, with the handheld, the nurses are now entering seven elements into the data. Those seven are heart rate/pulse; systemic blood pressure; respiratory rate; temperature; the O2 stat (saturation level of oxygen in the body); and O2—oxygen therapy (are they getting by room air or mask, and volume they’re getting); and a visual observation by the nurse. Is the patient alert? In pain? Is the patient’s voice fading? Is the patient unresponsive? So, there are six items that can be automated, and there is still a visual assessment by the nurse that has to be entered into the system.

And essentially, what happens is that everything turns on the score that is created from the seven elements. A normal score would be 0. With a slightly elevated heart rate, you’d get a 1; if the patient’s heart rate is up by 10 percent, you’d get a score of 2. The same applies with blood pressure. If any particular measure goes outside the normal parameters, the score would end up with a 3. The measures are combined into a HEWS score, which leads to an action plan. If the HEWS score reaches 5, the nurse is required to call the rapid response team to intervene on the patient’s behalf before the patient goes into a code blue situation.

 

When did this program go live?

The original version of the process went live with the Meditech side of the system in 2013, and then we rolled it out across our organization, and began discussions. We were able to show a 17-percent decrease in the number of critical care response team consults requiring a patient to be transferred into the ICU; and we were able to document a 6-percent reduction in cardiopulmonary resuscitation requiring a code blue. And that was in the very early stages of this, before we became fully automated. The paper version was live four years. The fully automated version involving ThoughtWire and IBM, we took live in November 2016.

So the metrics were documented over four years?

That was over the initial data collection on testing the HEWS score, to see if the score worked. That was the review we did of the first 400 patients who required the HEWS data, in 2014.

And the new system basically allows the nurse to go in; she just fills in the data, the HEWS score pops up, based on entering the seven data elements—it’s very easy to do. And as soon as she or he does that, it creates a notification. So, based on the score, it will notify the charge nurse and the rapid response team. The next step will be to add a notification to the MRP, the most responsible physician. Right now, the system tells them who the MRP—most responsible person—is. Later this year, we’ll add that notification. And we want the notification to also go straight to the device of the responsible physician.

With the automation, the nurse doesn’t have to leave the bedside, because she can see who’s been notified, and at that point, either the charge nurse, or if it goes up to the rapid response team, they can all see the vitals. And if bedside nurse records new vitals, those will be documented. And the rapid response team is in charge at that point.

Have there been any technological or process challenges in this initiative?

We did this with ThoughtWire and IBM, using their design-think principles, using their people to design the ergonomics, the device, the screen layout for it; we have had some challenges in that it is an Android application, and we’ve found that certain versions of Android are not working as well as others, so we’re ensuring that all devices are working up to the proper level of Android. We also use this device to do bedside meds verification in Meditech; the object there was to have a multi-use device. And this was for front-line staff, so the buy-in was very high. They were very supportive of it, so it’s been very successful. It’s an Android smartphone device.

When did nurses start using the Android smartphone for this?

In November 2016. And it used to be very common to hear code-blues, but you don’t hear those anymore. The last two I’ve heard have been in an ambulatory clinic area that this doesn’t cover.

And essentially, Dr. Fox’s take is that if a patient ends up in a code-blue, that’s a failure to treat. We should have could intervene and see what’s going on. There will always be that odd case that wasn’t predictable, but in most cases, we should be able to determine this in advance, based on trending.

What have been the biggest lessons learned in rolling out initiative so far?

I think the big thing is that when you create that actionable knowledge, technology can provide a shortcut to assist with all the manual calculations. We’ve found that you need supportive leadership to be able to do this. It certainly works best with those rapid response teams to do this. But from a technology standpoint, when we finally provide nursing with a clear outcome of what can happen, they’re very receptive to do the work. We had been documenting for years, but all that documentation just went into the charts, and nobody knew whether it was being used. But automating this brought out the real power in it.

And we’re looking at future projects, including a pediatric version of this that we’re working on right now. And we’re looking at potentially creating a version of this for sepsis. And certainly, having the frontline staff involved from the beginning was essential. And ThoughtWire’s ability to duplicate this without heavy HL7 interfaces, was a major leap forward in our creating something very quickly, and still have something that wasn’t duplicative.

What would you like to say to our audience of CIOs, CMIOs, and other healthcare IT leaders, about this?

This shows that we are now at the age where we can harness this information and start to become useful, rather than just being large storage lockers of data. And the new technologies available to us are ones that we need to embrace and harness and get out to the bedside, so that we can change how we’re doing our business. Because if we can avoid a code blue call or an ICU admission, that’s huge for the organization—and for the patient. So IT is coming together with the clinical side of the business, to really transform how we deliver care going forward.

 

 


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How BI Tools Are Helping Jefferson Health Battle the Opioid Crisis

September 21, 2018
by David Raths, Contributing Editor
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Helping clinical leaders identify prescribing patterns across the health system

Making health system changes to address the opioid crisis is challenging if you don’t have actionable data about prescribing patterns. With guidance from their chief medical officer, the business intelligence team at Jefferson Health in Philadelphia took advantage of the recent enterprise EHR implementation to create dashboards highlighting potential prescribing issues. Internal EHR development teams have already made changes to address the issues they found.

In a recent interview, Cara Martino, enterprise business intelligence manager at 14-hospital Jefferson Health, said that Jefferson was one of the first health systems to implement its Epic EHR and Qlik Sense at the same time. Many organizations that go live on Epic use Crystal Reporting, she said. “It was the combination of the two that allowed us to do this project,” she added. Before going live on Epic and using this new BI tool, Jefferson clinicians used a bunch of disparate systems for ambulatory, inpatient and emergency department physicians. “We weren’t able to aggregate the data,” she recalled.

Jefferson departments had tried to look at opioid prescribing previously, but “they were trying to manually abstract opioid data from the system, compile it in Excel, and try to see trending across the continuum of care, but they really weren’t able to do that very well,” Martino said. “Once we went live with Epic, we were able to standardize the work flow of entering the opioid order and prescription, and Qlik Sense allowed us to look at it from that enterprise view and to slice and dice the data a bunch of different ways.”

In response to the opioid epidemic in the Philadelphia area, Jefferson has created an opioid task force. In January 2018, Edmund Pribitkin, M.D., Jefferson’s chief medical officer, came to the BI team because he saw they didn’t really have good data to share. “We were bringing physicians and pharmacists together in a room to think through what we can change to address the opioid crisis,” Martino said, “but they didn't’ have baseline data to understand where we are going wrong.”

Pribitkin asked the BI team to develop a high-level dashboard with five key metrics to share at the clinical chair department level: 

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• Prescriptions by provider and service;

• Number of orders with over 100 pills;

• Prescriptions written for more than 7 days, 5 days and 3 days;

• Patients with two or more opioid prescriptions within 30 days; and

• Morphine-equivalent daily doses over 50.

The metric around patients with two or more prescriptions within 30 days had been difficult to see when data was being entered in a lot of different ordering systems, but is much easier now because everyone is ordering through Epic.

Within a month, the BI team had a prototype created. In the dashboard, you can pick a patient with the most scripts, and below it populates the different providers who are prescribing for them. “Sometimes you pick someone on the higher end and only one person is prescribing to them. Usually it is a chronic pain clinician, and it is probably appropriate,” Martino said. “But then you pick someone who has six different providers providing them opiates. They may have no idea about each other. Now we get to have that conversation about what we can do in the EHR to notify them at the time of ordering that the patient already has something prescribed. Also, our quality department can notify these six providers via e-mail. They might ask whether we should refer this patient to a chronic pain physician. If they really need this much pain medication, are we treating them the right way?”

Showing clinical leaders a trending graph such as prescription orders of 7 days or more can have an impact on ordering trends and EHR recommendations. Martino, who is a nurse herself, described an example of how her team worked with clinician informaticists who build EHR workflow tools to make some key changes.

They saw in the data that there were examples of doctors were prescribing six opioids to the same patient within two minutes. On further examination, they found that clinicians were entering orders incorrectly and quickly canceling them. But the e-prescription interface with the pharmacy system wasn’t necessarily canceling the incorrect orders, and the patients could have six prescriptions waiting for them at the pharmacy.

“Our first step was to get a message out to providers to let them know if you are prescribing and sending to an outside pharmacy, you need to pick up the phone and talk to the pharmacy about a change in an order and make sure they know which is the correct one,” Martino said. They also worked on the pharmacy interface to generate those canceled order messages, so that if something is ordered and then canceled within 30 seconds, it alerts the pharmacy not to prepare it.

The BI team saw another EHR change that they thought might make a big difference in prescribing patterns. In the EHR quick buttons, duration of the prescription defaulted to 10 days. The quick button on order days had choices of 7, 10, 15 or 30. “We knew those were too high,” she said. “We wanted 3, 5 or 7.”

They worked with an emergency department doctor who was also an informaticist to pilot that change in the ED. “In the first month, we saw a drop from 32 scripts over 7 days to just two,” Martino said. The following month they saw a reduction of more than 65 percent in prescriptions of more than 7 days. “The best part is no one complained or said they were looking for the 10 button and it wasn’t there,” she added. Now that change is being rolled out enterprise-wide.

Although there are some other requests from clinicians for data about opioid prescribing, Martino said the BI team’s current goal is to help more clinicians gain insights into the data that already exists. “It is really hard to go from an institution that was not data-rich and had disparate systems and manually collected data to one that has one EHR and a robust BI tool that allows us to slice data in a million different ways,” Martino said. “We are trying to get the clinicians comfortable with the tools. There is so much we can do, but we have to get the data to the right people and educate them about how we are pulling it out of the EHR. It is easy for this not be a priority for clinicians because they are so invested in taking care of their patients. It is our job as informaticists to go to their meetings and talk about changes we can make. It is also important for us to have clinicians on our team and to be able to offer that informaticist viewpoint.”

 

 


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Survey: Physicians Sour on Value-Based Care Metrics, EHRs

September 19, 2018
by Rajiv Leventhal, Managing Editor
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They new research has several key findings related to value-based care, health IT and burnout

More than 50 percent of U.S. physicians who receive value-based care compensation said they do not believe that the metrics the reimbursement is tied to improve the quality of care or reduce costs, according to a new survey.

The research comes from The Physicians Foundation, an organization seeking to advance the work of practicing physicians and helps them facilitate the delivery of healthcare to patients. The Foundation’s 2018 survey of U.S. physicians, administered by Merritt Hawkins and inclusive of responses from almost 9,000 physicians across the country, reveals the impact of several factors driving physicians to reassess their careers.

Specifically, the new survey underscores the overall impact of excessive regulatory/insurer requirements, loss of clinical autonomy and challenges with electronic health record (EHR) design/interoperability on physician attitudes toward their medical practice environment and overall dissatisfaction—all of which have led to professional burnout.

The research revealed several key findings, including that value-based compensation is directly connected to the overall dissatisfaction problem, which is tied to metrics such as EHR use, cost controls and readmission rates, etc. Forty-seven percent (compared to 43 percent in the 2016 survey) of physicians have their compensation tied to quality/value, but when physicians were asked if they believe that value-based payments are likely to improve quality of care and reduce costs, 57 percent either disagreed or strongly disagreed that this is the case, while only 18 percent either agreed or strongly agreed that it is.

As one responding physician put it: “We are no longer in the business of healthcare delivery, we are in the business of ‘measures’ delivery.” More than 13 percent of physicians are not sure if they are paid on value.

What’s more, the research found that 88 percent of physicians have reported that some, many or all of their patients are affected by social determinants. Conditions such as poverty, unemployment, lack of education, and addictions all pose a serious impediment to their health, well-being and eventual health outcomes. Only one percent of physicians reported that none of their patients had such conditions.

Additional notable findings from the research included:

  • 18.5 percent of physicians now practice some form of telemedicine
  • 80 percent of physicians report being at full capacity or being overextended
  • 40 percent of physicians plan to either retire in the next one to three years or cut back on hours—up from 36 percent in 2016
  • 32 percent of physicians do not see Medicaid patients or limit the number they see, while 22 percent of physicians do not see Medicare patients or limit the number they see
  • 46 percent of physicians indicate relations between physicians and hospitals are somewhat or mostly negative

Coupled altogether, 78 percent of physicians said they have experienced burnout in their medical practices, according to the survey’s findings. And the results show that one of the chief culprits contributing to physician burnout is indeed the frustration physicians feel with the inefficiency of EHRs.

“The perceptions of thousands of physicians in The Physicians Foundation’s latest survey reflect front-line observations of our healthcare system and its impact on all of us, and it’s sobering,” Gary Price, M.D., president of the Foundation, said in a statement. “Their responses provide important insights into many critical issues. The career plans and practice pattern trends revealed in this survey—some of which are a result of burnoutwill likely have a significant effect on our physician workforce, and ultimately, everyone’s access to care.”

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Brigham Health’s 3-Pronged Approach to Reducing EHR’s Contribution to Burnout

September 18, 2018
by David Raths, Contributing Editor
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Focus is on individualized training, reducing unnecessary clicks, voice recognition tools

Research studies have found that “burnout” is nearly twice as prevalent among physicians as among people in other professions.  Physician surveys have found that 30 to 60 percent report symptoms of burnout, which can threaten patient safety and physician health. With EHR documentation ranked high among aspects of their work physicians are dissatisfied with, Brigham Health in Boston has taken a three-pronged approach to reducing the pain.

Brigham Health, which is the parent organization that includes Brigham and Women’s Hospital, Brigham and Women’s Faulkner Hospital and the Brigham and Women’s Physicians Organization, rolled out its implementation of Epic in 2015. In a Sept. 18 presentation that was part of the Harvard Clinical Informatics Lecture Series, Brigham Chief Information Officer Adam Landman, M.D., said the organization’s initial EHR physician training was eight hours of classroom training on where to find things in the EHR instead of focusing on workflows and how to use the EHR to support it.  “Our experience was not the best,” Landman admitted.  They followed up with tip sheets, a help desk and a swat team to do service calls, but providers only rated those interventions as somewhat helpful, so Brigham informaticists re-doubled their efforts to:

• Improve the EHR;

• Provide one-on-one training in the clinical setting; and

• Offer voice recognition software and training.

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Landman said IT teams at Brigham feel a sense of urgency about reducing the burden of EHR documentation. “Burnout is an epidemic, and the EHR is a component of this,” he said, adding that the changes are not just a one-year cycle but must involve continual iterative improvements. “We need to be more aggressive about making changes,” he said.

He described some efforts to reduce notifications and remove clicks from the medication refill process. They also removed a hard stop when discontinuing a medication. Those three changes alone reduced the number of clicks per month by 950,000 across the health system.

They also worked to reduce clinical decision support alerts with very low acceptance rates by turning them off. Three alerts with very low acceptance rates were turned off. “If we thought they were important, we would fine tune them to increase the acceptance rate,” Landman stressed. “That is part of clinical decision support lifecycle management. But we will continue to iterate to reduce the number of unnecessary clicks.”

A year and a half ago, Brigham also created a one-to-one support program, in which an expert trainer would meet the physicians in their practice and help them with their work flow. A pilot project involved four specialties, including general surgery. Each session was 90 minutes to two hours long, and providers were offered one or more follow-up sessions, as well as optional training on speech recognition. After seeing some negative feedback on their initial classroom training, the one-to-one sessions were met with a very positive response. Almost 95 percent said it was valuable, and 95 percent said they thought their efficiency with the EHR would improve following the training. Based on that early success, the training effort is now being rolled out to much larger groups of physicians at Brigham and across the Partners HealthCare network.

In another attempt to improve documentation turnaround time, Brigham has made voice recognition tools and training available to physicians. They made two-hour training sessions mandatory for those interested in adoption, with additional personalization sessions also available. Informaticists partnered with departments to build department-specific order sets. (Brigham also started offering 15-minute e-learning sessions for residents.) More than 90 percent of surveyed physicians said the training met expectations, and 70 percent said they would be willing to have additional training, Landman said. Currently 5,000 physicians across Partners are trained to use voice recognition tools with the EHR.

Landman also cited a study that compared U.S. and international use of Epic that saw a huge disparity in length of documentation notes. The U.S.-based users’ notes were nearly four times longer on average than those of their international counterparts. Epic users overseas tend not to complain about the burden of documentation, he noted. This has to do with how the provider notes are used in billing, he said, adding that CMS is working on proposals to change billing requirements that may alleviate some of the documentation burden for physicians.

In closing, Landman urged informatics colleagues to think about working on EHR optimization research and studying the impact of policy and technology changes. “New technology tools can seem fun and exciting, but for physicians who see up to 100 patients per day, they can be quite overwhelming,” he said. “We don’t want physicians spending half their time doing administrative work.”

 

 

 

 

 


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