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Heathcare AI Maturity Index

Posted on October 16, 2018 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

Everywhere you turn in healthcare you’re seeing AI. I know some people would argue with how many companies define AI. In fact, there’s no doubt that AI has started to be used for everything from simple analytics to machine learning to neural networks to true artificial intelligence. I don’t personally get worked up in the definitions of various words since I think all of these things can and will benefit healthcare. Regardless of definition, what’s clear is that this broad definition of AI is going to have a big impact on healthcare.

In a recent tweet from David Chou, he shared a really interesting look at AI adoption in healthcare as compared with other industries. The healthcare AI maturity index also looks at where healthcare’s AI trajectory is headed in the next 3 years. Check out the details in the chart below:

There are a couple of things that concern me about this chart. First, it shows that healthcare is behind other industries when it comes to AI adoption. That’s not too surprising since healthcare is usually pretty risk averse with new technology. The “First Do No Harm” is an important part of the healthcare culture that scares many away from technology like AI. The only question is will this culture prevent helpful new AI technologies from coming to healthcare.

Many people would look at the chart and see that it projects a lot of growth in healthcare AI investment. That’s a good thing, but it also is a common pattern in healthcare. Lots of anticipation and hope that never fully realizes. Will we see the same in healthcare AI?

What’s been your experiences with AI in healthcare? Where do you see AI having the most impact right now? What companies are doing AI that’s going to impact your hospital or health system? Share your thoughts in the comments or on social media with @healthcarescene.

Healthcare Leaders: Feeling a Bit Discombobulated?

Posted on October 11, 2018 I Written By

The following is a guest blog post by Heather Haugen PhD and Inbal Vuletich from Atos Digital Health Solutions.

After passing through the security checkpoint at Milwaukee International Airport (MKE), a frazzled traveler is greeted by a low-hanging placard.  It reads: Recombobulation Area.  Clearly someone on the MKE management team with a sense of humor was acknowledging the fact that many travelers become a bit discombobulated as they proceed through security and that many probably need an area where they can get their collective psyche back in order.

The idea of a Recombobulation Area seemed especially appropriate as we returned from a healthcare conference on Lake Geneva where a wide spectrum of thought leaders presented and discussed their experiences from the past decade.  The group’s shared conclusion was that no one could have prepared for or predicted the level of change experienced in the healthcare environment over the past decade.

The changes we discussed encompass every aspect of how care is delivered, from EHRs to ERPs. Healthcare leaders navigate clinical, financial, and compliance hurdles daily – often all tangled together. Clinicians face new technologies, new workflows, new regulations and standards (that often conflict), new reimbursement requirements, new governance models, and something new… coming soon.  How can we expect better care in such a tumultuous environment?

During this time of dramatic change, it is important to identify a way to measure progress (or lack thereof) so that we can stay focused on our goals and desired outcomes.  One of the best mechanisms for assessing the impact of our work in healthcare is the use of data.  A simple research plan such as the one below can be used to assess the impact of changes – and could possibly even elucidate new ideas.

  • Research question: An overarching question to define the effort
    • For example:
      1. How effective are EHR alerts in preventing medication errors?
  • Specific aims: Specific objectives that address the overarching question
    • For example:
      1. To characterize the differences in medication errors before and after EHR implementation
      2. To understand the factors that increase alert fatigue
  • Methodology: How to address each specific goal. This step often requires some collaboration with a statistician or someone with research experience.
    • Define the sample population
    • Define the data elements to collect
    • Determine appropriate timeframes
    • Data analysis plan
  • Results: The presentation of the analyzed data
  • Conclusions: Discussion of the results and their meaning. What are the actionable steps for the organization?

Healthcare has evolved significantly to embrace new advancements in technology, but the challenges we continue to face need to be assessed objectively.  Thus far, our research has focused on the factors that influence adoption of new technology.  It has been fascinating and the outcomes caused us to consider new ideas and better approaches. Our EHR research published in Beyond Implementation remains relevant and valuable to healthcare leaders.  We are committed to helping healthcare organizations shift from the tumultuous set of ongoing changes to a research-based approach to ensure ongoing process improvement and discipline for technology adoption.  Our colleagues’ experiences, the rich research and data that exist today, and the stories of successes and challenges in healthcare organizations provide us with a critical Recombobulation Area. We must take the time to pause and learn from objective data and research methodologies to ensure that all this change focuses on improving patient care.

About the Authors:
Heather Haugen is the Chief Science Officer for Digital Health Solutions for Atos. She is also the author of Beyond Implementation: A Prescription for the Adoption of Healthcare Technology.

Inbal Vuletich serves as the editor for Atos Digital Health Solution publications.

About Atos Digital Health Solutions
Atos Digital Health Solutions helps healthcare organizations clarify business objectives while pursuing safer, more effective healthcare that manages costs and engagement across the care continuum. Our leadership team, consultants, and certified project and program managers bring years of practical and operational hospital experience to each engagement. Together, we’ll work closely with you to deliver meaningful outcomes that support your organization’s goals. Our team works shoulder-to-shoulder with your staff, sharing what we know openly. The knowledge transfer throughout the process improves skills and expertise among your team as well as ours. We support a full spectrum of products and services across the healthcare enterprise including Population Health, Value-Based Care, Security and Enterprise Business Strategy Advisory Services, Revenue Cycle Expertise, Adoption and Simulation Programs, ERP and Workforce Management, Go-Live Solutions, EHR Application Expertise, as well as Legacy and Technical Expertise. Atos is a proud sponsor of Healthcare Scene.

Medical Humor – Fun Friday

Posted on October 5, 2018 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

It’s Friday as we head into the weekend. Tomorrow I’m heading off to Seattle for the SHSMD 2018 conference. This is my first time attending the event, so we’ll see how it goes and report back later. If you live in the Seattle area, we have an open meetup for the Healthcare Scene community on Tuesday, Oct 9. Find all the details for the Seattle meetup here.

This is conference season, so the week after that I’m heading to Boston for the MEDITECH MD and CIO Forum and then the Connected Health Conference. There are a bunch of meetups planned, but I’m going to definitely be going to this SPM, #pinksocks, #hcldr meetup in Boston. Everyone is welcome, so if you’re in Boston, join us for some fun and good people (word on the street is that there will be a dance party after the meetup).

As always, you can see our full schedule of Healthcare Scene conferences and events. We can’t wait to see everyone in Seattle and Boston.

Ok, enough about travel. Time for some Fun Friday humor to get you ready for the weekend. This humor comes from @DocAroundthClok on Twitter. I think you’ll enjoy it.

This 2nd one seems particularly interesting after I just wrote about all the meetups in this post. If you’re like this doctor, then you should definitely join us at the meetups. No eye contact required. I’ll be surprised if the dance party doesn’t include the song Despacito.

Have a great weekend!

AI Project Set To Offer Hospital $20 Million In Savings Over Three Years

Posted on October 4, 2018 I Written By

Anne Zieger is veteran healthcare branding and communications expert with more than 25 years of industry experience. and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also worked extensively healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

While they have great potential, healthcare AI technologies are still at the exploration stage in most healthcare organizations. However, here and there AI is already making a concrete difference for hospitals, and the following is one example.

According to an article in Internet Health Management, one community hospital located in St. Augustine, Florida expects to save $20 million dollars over the next the three years thanks to its AI investments.

Not long ago, 335-bed Flagler Hospital kicked off a $75,000 pilot project dedicated to improving the treatment of pneumonia, sepsis and other high mortality conditions, building on AI tools from vendor Ayasdi Inc.

Michael Sanders, a physician who serves as chief medical informatics officer for the hospital, told the publication that the idea was to “let the data guide us.” “Our ability to rapidly construct clinical pathways based on our own data and measure adherence by our staff to those standards provides us with the opportunity to deliver better care at a lower cost to our patients,” Sanders told IHM.

The pilot, which took place over just nine weeks, reviewed records dating back five years. Flagler’s IT team used Ayasdi’s tools to analyze data held in the hospital’s Allscripts EHR, including patient records, billing, and administrative data. Analysts looked at data on patterns of care, lengths of stay and patient outcomes, including the types of medications docs and for prescribing and when doctors were ordering CT scans.

After analyzing the data, Sanders and his colleagues used the AI tools to build guidelines into the Allscripts EHR, which Sanders hoped would make it easy for physicians to use them.

The project generated some impressive results. For example, the publication reported, pathways for pneumonia treatment resulted in $1,336 in administrative savings for a typical hospital stay and cut down lengths of stay by two days. All told, the new approach cut administrative costs for pneumonia treatment by $800,000.

Now, Flagler plans to create pathways to improve care for sepsis, substance abuse, heart attacks, and other heart conditions, gastrointestinal disorders and chronic conditions such as diabetes.

Given the success of the project, the hospital expects to expand the scope of its future efforts. At the outset of the project, Sanders had expected to use AI tools to take on 12 conditions, but given the initial success with rolling out AI-based pathways, Sanders now plans to take on one condition each month, with an eye on meeting a goal of generating $20 million in savings over the new few years, he told IHM.

Flagler is not the first, nor will it be the last, hospital to streamline care using AI. For another example, check out the efforts underway at Montefiore Health, which seems to be transforming its entire data infrastructure to support AI-based analytics efforts.

Informed Consent: Let Go of the Status Quo

Posted on October 1, 2018 I Written By

The following is a guest blog post by Shahid Shah.

We’ve all heard it before: “healthcare is slow to adopt new technologies.” In fact, we’ve heard it so many times that we just accept it as gospel and don’t give it much thought.

It’s not true though.

For example, I remember when the iPhone was first released, it was easily adopted by doctors because it gave them something they craved: increased freedom by having access to information on the go.

What’s probably true is that “healthcare institutions are slow to adopt new technologies that impact status quo.

Why is that?

Because the perceived cost of maintaining the status quo is smaller than the cost of the innovation (e.g. product or solution), even if that innovation is free.

When the cost of not doing something new is low, nothing will change: and bad leadership is often able to keep the cost of maintaining status quo very low. Poor leaders add hurdles, like requiring unknowable ROI analyses, for introducing innovation but don’t penalize maintenance of status quo. This means that it’s easier to not introduce anything new – because the cost of not innovating is low but the cost of innovating is high.

Let’s take a look at digital patient consent as an example of an innovation – obtaining patient consent to perform a healthcare service is something that no hospital can do without. Called “informed consent”, this is a document that patients are required to sign before any procedure or health service is delivered. You’d think that because this form is the initial and primary document before almost any other workflow is started, that it would be the first to be digitized and turned into an electronic document.

Unfortunately, it’s 2018 and informed consent documents remain on paper. Thus:

  • JAMA reports that two-thirds of procedures have missing consent forms
  • JAMA reports that missing consent forms cause 10% of procedures to be delayed, costing hospitals over $500k per year
  • Joint Commission reports over 500 organizations annually experience compliance issues because of missing consent forms. There’s almost a 1 in 4 chance that your own organization has this compliance problem.
  • A recent JAMA Surgery paper estimated that two thirds of malpractice cases cited lack of informed consent, which increases liability risk
  • Superfluous paperwork directly contributes to clinician burnout
  • Patients often don’t understand their procedures or aren’t properly educated about the service they’re about to use

Today, many healthcare institutions go without automation of consent documents – which I’m calling the status quo. Even though this document is essential, and its non-digital status quo creates many financial, clinician, and compliance burdens, it’s not high in the list of priorities for digitization or automation.

As I enter my third decade as a health IT architect, after having built dozens of solutions in the space that are used by thousands of people, I still find it difficult to explain why even something as simple as an informed consent isn’t prioritized for automation.

It’s not because solutions aren’t out there – for example, FormFast’s eConsent is a universally applicable, easy to deploy, and easy to use software package with a fairly rapid return on investment. With eConsent software, clinicians aren’t interrupted in their workflows, patients are more satisfied, compliance becomes almost guaranteed, and procedures aren’t delayed because of lost paperwork.

A senior network engineer at East Alabama Medical Center recently wrote “the comparison of creating a form in the EHR vs. an eForms platform? There is no comparison. We are saving thousands of dollars by using eForms technology and the form creation is simple.”

Why do you think even something essential like patient consent forms remain on paper? Drop us a line below and let us know why the status quo is so powerful and what’s keeping your organization from adopting electronic forms solutions.

Note: FormFast is a proud sponsor of Healthcare Scene.

Report Champions API Use To Improve Interoperability

Posted on September 26, 2018 I Written By

Anne Zieger is veteran healthcare branding and communications expert with more than 25 years of industry experience. and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also worked extensively healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

A new research report has taken the not-so-radical position that greater use of APIs to extract and share health data could dramatically improve interoperability. It doesn’t account for the massive business obstacles that still prevent this from happening, though.

The report, which was released by The Pew Charitable Trusts, notes that both the federal government and the private sector are both favoring the development of APIs for health data sharing.

It notes that while the federal government is working to expand the use of open APIs for health data exchange, the private sector has focused on refining existing standards in developing new applications that enhance EHR capabilities.

EHR vendors, for their part, have begun to allow third-party application developers to access to systems using APIs, with some also offering supports such as testing tools and documentation.

While these efforts are worthwhile, it will take more to wrest the most benefit from API-based data sharing, the report suggests. Its recommendations for doing so include:

  • Making all relevant data available via these APIs, not just CCDs
  • Seeing to it that information already coded in health data system stays in that form during data exchange (rather than being transformed into less digestible formats such as PDFs)
  • Standardizing data elements in the health record by using existing terminologies and developing new ones where codes don’t exist
  • Offering access to a patient’s full health record across their lifetime, and holding it in all relevant systems so patients with chronic illnesses and care providers have complete histories of their condition(s)

Of course, some of these steps would be easier to implement than others. For example, while providing a longitudinal patient record would be a great thing, there are major barriers to doing so, including but not limited to inter-provider politics and competition for market share.

Another issue is the need to pick appropriate standards and convince all parties involved to use them. Even a forerunner like FHIR is not yet universally accepted, nor is it completely mature.

The truth is that no matter how you slice it, interoperability efforts have hit the wall. While hospitals, payers, and clinicians pretty much know what needs to happen, their interests don’t converge enough to make interoperability practical as of yet.

While I’m all for organizations like the Pew folks taking a shot at figuring interoperability out, I don’t think we’re likely to get anywhere until we find a way to synchronize everyone’s interests. And good luck with that.

Montefiore Health Makes Big AI Play

Posted on September 24, 2018 I Written By

Anne Zieger is veteran healthcare branding and communications expert with more than 25 years of industry experience. and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also worked extensively healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

I’ve been doing a lot of research on healthcare AI applications lately. Not surprisingly, while people find the abstract issues involved to be intriguing, most would prefer to hear news of real-life projects, so I’ve been on the lookout for good examples.

One interesting case study, which appeared recently in Health IT Analytics, comes from Montefiore Health System, which has been building up its AI capabilities. Over the past three years, it has created an AI framework leveraging a data lake, infrastructure upgrades and predictive analytics algorithms. The AI is focused on addressing expensive, dangerous health issues, HIA reports.

“We have created a system that harvests every piece of data that we can possibly find, from our own EMRs and devices to patient-generated data to socio-economic data from the community,” said Parsa Mirhaji, MD, PhD, director of the Center for Health Data Innovations at Montefiore and the Albert Einstein College of Medicine, who spoke with the publication.

Back in 2015, Mirhaji kicked off a project bringing semantic data lake technology to his organization. The first pilot using the technology was designed to find patients at risk of death or intubation within 48 hours. Now, clinicians can also see red flags for admitted patients with increased risk of mortality 3 to 5 days in advance.

In 2017, the health system also rolled out advanced sepsis detection tools and a respiratory failure detection algorithm called APPROVE, which identifies patients at a raised risk of prolonged ventilation up to 48 hours before onset, HIA reported.

The net result of these efforts was dubbed PALM, the Patient-centered Analytical  Learning Machine. PALM “represents a very new way of interacting with data in healthcare,” Miraji told HIA.

What makes PALM special is that it speeds up the process of collecting, curating, cleaning and accessing metadata which must be conducted before the data can be used to train AI models. In most cases, the process of collecting data for AI use is largely manual, but PALM automates this process, Miraji told the publication.

This is because the data lake and its graph repositories can find relationships between individual data elements on an on-the-fly basis. This automation lets Montefiore cut way down on labor needed to get these results. Miraji noted that ordinarily, it would take a team of data analysts, database administrators and designers to achieve this result.

PALM also benefits from a souped-up hardware architecture, which Montefiore created with help from Intel and other technology partners. The improved architecture includes the capacity for more system memory and processing power.

The final step in optimizing the PALM system was to integrate it into the health system’s clinical workflow. This seems to have been the hardest step. “I will say right away that I don’t think we have completely solved the problem of integrating analytics seamlessly into the workflow,” Miraji admitted to HIA.

A Nursing Informatics Perspective on Healthcare Analytics – Interview with Charles Boicey

Posted on September 21, 2018 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

Healthcare informatics has been around for a long time. However, from my perspective, it feels like there’s something different in the air when it comes to healthcare informatics. I get the feeling that we’re on the precipice of something really special happening. In fact, I think we already start to see value being created by healthcare informaticists.

As Healthcare Scene continues to explore this subject, we sat down with informatics expert, Charles Boicey, Chief Innovation Officer at Clearsense, to talk with him about what’s changed in healthcare informatics that makes it different today than in the past. We also talk about what’s needed to make healthcare analytics efforts successful at organizations and what analytics trend he’s watching most. Plus, we had to talk about his background as a nurse and how a nursing background really helps his informatics work.

If you want to hear of some practical uses of healthcare analytics and how your organization can benefit from it, you’ll enjoy our interview with Charles Boicey.

Be sure and subscribe to all of Healthcare Scene’s videos on YouTube. Also, take a minute to check out EXPO.health and join us in Boston to mix and mingle with amazing healthcare IT professionals like Charles Boicey.

Do We Need Another Interoperability Group?

Posted on September 20, 2018 I Written By

Anne Zieger is veteran healthcare branding and communications expert with more than 25 years of industry experience. and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also worked extensively healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

Over the last few years, industry groups dedicated to interoperability have been popping up like mushrooms after a hard rain. All seem to be dedicated to solving the same set of intractable data sharing problems.

The latest interoperability initiative on my radar, known as the Da Vinci Project, is focused on supporting value-based care.

The Da Vinci Project, which brings together more than 20 healthcare companies, is using HL7 FHIR to foster VBC (Value Based Care). Members include technology vendors, providers, and payers, including Allscripts, Anthem Blue Cross and Blue Shield, Cerner, Epic, Rush University Medical Center, Surescripts, UnitedHealthcare, Humana and Optum. The initiative is hosted by HL7 International.

Da Vinci project members plan to develop a common set of standards for data exchange that can be used nationally. The idea is to help partner organizations avoid spending money on one-off data sharing development projects.

The members are already at work on two test cases, one addressing 30-day medication reconciliation and the other coverage requirements discovery. Next, members will begin work on test cases for document templates and coverage rules, along with eHealth record exchange in support of HEDIS/STARS and clinician exchange.

Of course, these goals sound good in theory. Making it simpler for health plans, vendors and providers to create data sharing standards in common is probably smart.

The question is, is this effort really different from others fronted by Epic, Cerner and the like? Or perhaps more importantly, does its approach suffer from limitations that seem to have crippled other attempts at fostering interoperability?

As my colleague John Lynn notes, it’s probably not wise to be too ambitious when it comes to solving interoperability problems. “One of the major failures of most interoperability efforts is that they’re too ambitious,” he wrote earlier this year. “They try to do everything and since that’s not achievable, they end up doing nothing.”

John’s belief – which I share — is that it makes more sense to address “slices of interoperability” rather than attempt to share everything with everyone.

It’s possible that the Da Vinci Project may actually be taking such a practical approach. Enabling partners to create point-to-point data sharing solutions easily sounds very worthwhile, and could conceivably save money and improve care quality. That’s what we’re all after, right?

Still, the fact that they’re packaging this as a VBC initiative gives me pause. Hey, I know that fee-for-service reimbursement is on its way out and that it will take new technology to support new payment models, but is this really what happening here? I have to wonder.

Bottom line, if the giants involved are still slapping buzzwords on the project, I’m not sure they know what they’re doing yet. I guess we’ll just have to wait and see where they go with it.

Prioritizing Nursing Sepsis Awareness and Compliance

Posted on September 17, 2018 I Written By

The following is a guest blog post by Anne Dabrow Woods, DNP, RN, CRNP, ANP-BC, AGACNP-BC, FAAN, Chief Nurse, Health Learning, Research & Practice, Wolters Kluwer.

September is Sepsis Awareness Month—an opportune time to reflect on the state of industry as it relates to reducing the impact of this potentially deadly condition. In terms of reach, the numbers are sobering: 1.5 million people in the U.S. contract sepsis each year, and a quarter of a million die annually from the condition.

In recent years, the healthcare industry has taken important steps to improve the sepsis outlook by keeping awareness and best-practice developments front and center. The Surviving Sepsis Campaign’s (SSC’s) 2018 release of the updated hour-1 bundle reflects this commitment by keeping care delivery in sync with the latest evidence—in this case the International Guidelines for Management of Sepsis and Septic Shock 2016.

The new bundle combines the SSC’s previously-released 3-hour and 6-hour bundles and prioritizes the need for early identification and more immediate response. Nurses play a critical role in this equation as the clinicians working on the frontlines of care. While sepsis is more likely to present in emergency departments and critical care environments, it is imperative that all nurses have the knowledge to quickly identify symptoms and begin appropriate treatment protocols.

The sepsis challenge is both mammoth and complicated, requiring a multi-pronged, multi-disciplinary approach that draws on the latest evidence and institutional accountability. There is much at stake for hospitals in terms of reputation as sepsis performance scores are now published on the Centers for Medicare and Medicaid Services’ Hospital Compare website, where patients can quickly and easily see how their facility of choice stacks up in terms of sepsis mortality.

Consequently, it is more important than ever for hospital clinical leaders to prioritize nursing education on the early signs of sepsis, especially when caring for at-risk patients. In addition, nurses need quick access to hour-1 bundle protocols at the point of care to ensure they are properly following the guidelines to optimize sepsis outcomes and save lives.

Sepsis Bundle Primer

The latest revision of the SSC bundles seeks immediate resuscitation and management of sepsis. In the update, SCC authors note: “We believe this reflects the clinical reality at the bedside of these seriously ill patients with sepsis and septic shock—that clinicians begin treatment immediately, especially in patients with hypotension, rather than waiting or extending resuscitation measures over a longer period.”

The guidelines detail five steps that should take place within one hour of identifying sepsis including:

  • Measure lactate level. Remeasure if initial lactate level > 2 mmol/L.
  • Obtain blood cultures before administering antibiotics.
  • Administer broad-spectrum antibiotics.
  • Begin rapid administration of 30mL/kg crystalloid for hypotension or lactate level ≥ 4 mmol/L.
  • Apply vasopressors if patient is hypotensive during or after fluid resuscitation to maintain MAP ≥ 65 mm Hg.

The premise of the bundled elements is that the whole is better than the one. When implemented as a group, these protocols have the greatest impact on outcomes.

The Sepsis Knowledge Gap Challenge

Hospitals face nursing knowledge gaps related to sepsis on two fronts: 1) early identification; 2) adhering to best practice protocols. While nurses working in the ED or critical care are likely to have experience with sepsis and the hour-1 bundle, those working on the medical-surgical floor or in other specialty areas often lack a deep understanding of the complexities and urgency surrounding early identification and response.

To promote early identification, nurses need to first understand the symptoms that occur in patients who are septic. Key observations include:

  • Delirium
  • Extreme high or low temperatures
  • Shortness of breath
  • Extreme pain or discomfort
  • Elevated heart rate and/or low blood pressure
  • Cool and clammy skin

While the answers to these questions can provide a baseline, the reality is that sepsis is a complicated diagnosis that requires critical thinking. For instance, fever alone is not always the best indicator of the condition, as hypothermia and low temperatures are often more predictive of severity and death. In addition, nurses need awareness that certain patients are at higher risk of mortality, such as the very young and the elderly or those with certain co-morbidities like COPD, heart failure and diabetes.

The Quick Sepsis Related Organ Failure Assessment (qSOFA) provides an effective point-of-care prompt for identification of a suspected infection. The tool uses three criteria to determine sepsis mortality risk. These include one point for each of the following: low blood pressure (SBP≤100 mmHg); high respiratory rate (≥ 22 breaths per minute); or altered mentation. Nurses need to be educated to use this system and be made aware of alerts that point to these variables. For example, a positive score of 2 or higher would point to the need for intervention by a provider or initiation of rapid response protocols.

Standardizing Sepsis Identification and Response

To eliminate variations in sepsis care and ensure best-practice protocols are followed, hospitals must implement comprehensive and ongoing education programs for nurses that address three areas: 1) identification of early signs of sepsis; 2) hour-1 treatment bundle protocol and 3) use of qSOFA scoring. Technology is an important part of any strategy and should be a priority consideration for both education and point of care guidance.

The best clinical decision support tools at point of care provide automated updating of new evidence as it is established. In the case of the hour-1 sepsis bundle, these solutions foster confidence that nurses have that right information when they are with the patient, and if they forget, a quick look-up can provide the needed guidance.

Access to the most up-to-date digital professional development education resources help nurses garner a deeper understanding of sepsis, the latest standards and practice application. Hospitals can draw on the latest advancements to quickly create customized programs and exams that allow students to progress and master skills at their own unique level.

Sepsis mortality rates sit at greater than 40 percent. In the era of value-based care which focuses on patient outcomes, that’s significant and problematic for hospitals on many levels. Improving sepsis outcomes necessitates that clinical leaders invoke strategies that promote adoption of the latest evidence to move the needle on performance.

About Anne Dabrow Woods
Anne Dabrow Woods, DNP, RN, CRNP, ANP-BC, AGACNP-BC, FAAN is the Chief Nurse of the Health Learning, Research and Practice business unit at Wolters Kluwer.  She is also a critical care nurse practitioner for Penn Medicine, Chester County Hospital, and she is adjunct faculty for Drexel University in the College of Nursing and Health Professions.