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Epic EHR Switching Video from Mary Washington Healthcare (MWHC)

Posted on May 26, 2017 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.

We’re back with another Fun Friday video (and a bonus story) to prepare you for the weekend. This week’s Fun Friday video comes from Mary Washington Healthcare (MWHC) doing a parody of a Hamilton song, “Right Hand Man,” as part of their switch to Epic. The production quality is really quite amazing and I love the choice of Hamilton. Check it out:

Now for a fun little story. I showed one of these EHR go-live videos to the Healthcare IT and EHR course I taught in Dubai. The majority of attendees were from Saudia Arabia with a few from Kuwait and UAE.

Well, the attendees loved the video. I asked them how well creating a video like this would go over in their hospitals. They all laughed and shook their heads. Certainly, the cultures are quite different. However, I did find it interesting that just as many people in the middle east were taking selfies as the US. Maybe the human desire isn’t all that different.

I don’t expect any of my students in the workshop to do anything like the above video. However, the concept of bringing your team together in an effort like what it takes to create this video is a powerful idea that could be applied regardless of culture.

Measuring Population Health ROI Is Still Tricky

Posted on May 24, 2017 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 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. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

Over the past few years, health systems have made massive investments in population health management technology. Given the forces driving the investments are still present – or even closer at hand – there’s every reason to believe that they will continue.

That being said, health leaders are beginning to ask more questions about what they’re getting in return.  While systems may have subjected the initial investments to less scrutiny than usual, having accepted that they were critically necessary, many of these organizations are now trying to figure out what kind of return on investment they can expect to realize. In the process, some are finding out that even deciding what to measure is still somewhat tricky.

Many healthcare organizations started out with a sense that while investment returns on pop health management tech would take a while, they were in the knowable future. For example, according to a KPMG survey conducted in early 2015, 20 percent of respondents believed that returns on their investment in population health IT would materialize in one to two years, 36 percent expected to see ROI in three to four years and 29 percent were looking at a five+ year horizon.

At the time, though, many of the execs answering the survey questions were just getting started with pop health. Thirty-eight percent said their population health management capabilities were elementary-stage, 23 percent said they were in their infancy and 15 percent said such capabilities were non-existent, KPMG reported.

Since then, health systems and hospitals have found that measuring – much less realizing – returns generated by these investments can be complicated and uncertain. According to Dennis Weaver, MD, a senior consultant with the Advisory Board, one mistake many organizations make is evaluating ROI based solely on whether they’re doing well in their managed care contracts.

“They are trying to pay for all of the investment – the technology, care managers, operational changes, medical homes—all with the accountable payment bucket,” said Weaver, who spoke with Healthcare Informatics.

Other factors to consider

Dr. Weaver argues that healthcare organizations should take at least two other factors into account when evaluating pop health ROI, specifically reduction of leakage and unwarranted care variation. For example, cutting down on leakage – having patients go out of network – offers a 7 to 10 times greater revenue opportunity than meeting accountable care goals. Meanwhile, by reducing unwarranted variations in care and improving outcomes, organizations can see a 5 percent to 10 percent margin improvement, Weaver told the publication.

Of course, no one approach will hold true for every organization.  Bobbie Brown, senior vice president with HealthCatalyst, suggests taking a big-picture approach and drilling down into how specific technologies net out financially.

She recommends that health organizations start the investment analysis with broad strategic questions like “Does this investment help us grow?” and “Are we balancing risk and reward?” She also proposes that health leaders create a matrix which compares the cost/benefit ratio for individual components of the planned pop health program, such as remote monitoring and care management. Sometimes, putting things into a matrix makes it clear which approaches are likely to pay off, she notes.

Over time, it seems likely that healthcare leaders will probably come to a consensus on what elements to measure when sizing up their pop health investments, as with virtually every other major HIT expense. But in the interim, it seems that figuring out where to look for ROI is going to take more work.

Predicting Readmissions, Longitudinal Record, and Physicians’ Time

Posted on May 12, 2017 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.

Here’s a quick look around the Twittersphere and a few topics that stood out to me that I think might be of interest to you.


I’ve been following algorithms like this for a while and they’re really starting to come into their own. This type of predictive technology or predictive analytics if you prefer is going to really change how we manage patients in a hospital. If done right, it can help us become proactive instead of reactive. This will require us to change a lot of processes though.


Is a longitudinal health record possible in any format? I’m beginning to think that it’s a pipe dream that will never happen. At least not with our current documentation requirements.

I find time studies like these very interesting. However, the thing I hate about them is that we don’t have a time study from before implementing EHR software so we could compare how a physician used their time before EHR and after. No doubt over 50% of their time being spent on documentation and not face-to-face with the patient feels bad. However, how far off was this from where we were in the paper world?

Looking at the chart, prescription refills can be faster in an EHR. Secure messages can be faster with an EHR since you’re not playing phone tag which was the process before secure messages. Telephone encounters were likely the same. That leaves just the progress notes as the one thing that could be more time consuming in an EHR than the paper chart. How much more is the real question. Paper chart progress notes weren’t all that fast either. That’s why stacks of paper charts that weren’t completed were always sitting on physicians’ desks.

I guess the core question I would ask is, “Are EHRs the reason doctors hate medicine, or are the ongoing regulations and requirements that have been heaped on doctors the real problem?” My guess is that all this documentation overheard that’s being required of doctors was a problem in the paper world, but has been exacerbated in the EHR world. What do you think?

2 Core Healthcare IT Principles

Posted on May 10, 2017 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.

One of my favorite bloggers I found when I first starting blogging about Healthcare IT was a hospital CIO named Will Weider who blogged on a site he called Candid CIO. At the time he was CIO of Ministry Health Care and he always offered exceptional insights from his perspective as a hospital CIO. A little over a month ago, Will decided to move on as CIO after 22 years. That was great news for me since it meant he’d probably have more time to blog. The good news is that he has been posting more.

In a recent post, Will offered two guiding principles that I thought were very applicable to any company working to take part in the hospital health IT space:

1. Embed everything in the EHR
2. Don’t hijack the physician workflow

Go and read Will’s post to get his insights, but I agree with both of these principles.

I would add one clarification to his first point. I think there is a space for an outside provider to work outside of the EHR. Think of someone like a care manager. EHR software doesn’t do care management well and so I think there’s a space for a third party care management platform. However, if you want the doctor to access it, then it has to be embedded in the EHR. It’s amazing how much of a barrier a second system is for a doctor.

Ironically, we’ve seen the opposite is also true for people like radiologists. If it’s not in their PACS interface, then it takes a nearly herculean effort for them to leave their PACS system to look something up in the EHR. That’s why I was excited to see some PACS interfaces at RSNA last year which had the EHR data integrated into the radiologists’ interface. The same is true for doctors working in an EHR.

Will’s second point is a really strong one. In his description of this principle, he even suggests that alerts should all but be done away within an EHR except for “the most critical safety situations. He’s right that alert blindness is real and I haven’t seen anyone nail the alerts so well that doctors aren’t happy to see the alerts. That’s the bar we should place on alerts that hijack the physician workflow. Will the doctor be happy you hijacked their workflow and gave them the alert? If the answer is no, then you probably shouldn’t send it.

Welcome back to the blogosphere Will! I look forward to many more posts from you in the future.

Google’s DeepMind Rolling Out Bitcoin-Like Health Record Tracking To Hospitals

Posted on May 8, 2017 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 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. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

Blockchain technology is gradually becoming part of how we think about healthcare data. Even government entities like the ONC and FDA – typically not early adopters – are throwing their hat into the blockchain ring.

In fact, according to recent research by Deloitte, healthcare and life sciences companies are planning the most aggressive blockchain deployments of any industry. Thirty-five percent of Deloitte’s respondents told the consulting firm that they expected to put blockchain into production this year.

Many companies are tackling the practical uses of blockchain tech in healthcare. But to me, few are more interesting than Google’s DeepMind, a hot new AI firm based in the UK acquired by Google a few years ago.

DeepMind has already signed an agreement with a branch of Britain’s National Health Trust, under which it will access patient data in the development healthcare app named Streams. Now, it’s launching a new project in partnership with the NHS, in which it will use a new technology based on bitcoin to let hospitals, the NHS and over time, patients track what happens to personal health data.

The new technology, known as “Verifiable Data Audit,” will create a specialized digital ledger which automatically records every time someone touches patient data, according to British newspaper The Guardian.

In a blog entry, DeepMind co-founder Mustafa Suleyman notes that the system will track not only that the data was used, but also why. In addition, the ledger supporting the audit will be set to append-only, so once the system records an activity, that record can’t be erased.

The technology differs from existing blockchain models in some important ways, however. For one thing, unlike in other blockchain models, Verifiable Data Audit won’t rely on decentralized ledger verification of a broad set of participants. The developers have assumed that trusted institutions like hospitals can be relied on to verify ledger records.

Another way in which the new technology is different is that it doesn’t use a chain infrastructure. Instead, it’s using a mathematical function known as a Merkle tree. Every time the system adds an entry to the ledger, it generates a cryptographic hash summarizing not only that latest ledger entry, but also the previous ledger values.

DeepMind is also providing a dedicated online interface which participating hospitals can use to review the audit trail compiled by the system, in real-time. In the future, the company hopes to make automated queries which would “sound the alarm” if data appeared to be compromised.

Though DeepMind does expect to give patients direct oversight over how, where and why their data has been used, they don’t expect that to happen for some time, as it’s not yet clear how to secure such access. In the mean time, participating hospitals are getting a taste of the future, one in which patients will ultimate control access to their health data assets.

E-Patient Update: Before You Call Me A “Frequent Flier,” Check Your EMR

Posted on April 28, 2017 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 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. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

While there’s some debate about what constitutes an emergency, there’s no doubt I’ve had a bunch of ambiguous, potentially symptoms lately that needed to be addressed promptly. Unfortunately, that’s exposed me to providers brainwashed to believe that anyone who comes to the emergency department regularly is a problem.

Not only is that irritating, and sometimes intimidating, it’s easy to fix. If medical providers were to just dig a bit further into my existing records – or ideally, do a sophisticated analysis of my health history – they’d understand my behavior, and perhaps even provide more effective care.

If they looked at the context their big ‘ol EMR could provide, they wouldn’t waste time wondering whether I’m overreacting or wasting their time.

As I see it, slapping the “frequent flier” label on patients is particularly inappropriate when they have enough data on hand to know better. (Actually, the American College of Emergency Physicians notes that a very small number of frequent ED visitors are actually homeless, drug seekers or mentally ill, all of which is in play when you show up a bit often. But that’s a topic for another time.)

Taking no chances

The truth is, I’ve only been hitting the ED of late because I’ve been responding to issues that are truly concerning, or doing what my primary doctor or HMO nurse line suggests.

For example, my primary care doctor routed me straight to the local emergency department for a Doppler when my calves swelled abruptly, as I had a DVT episode and subsequent pulmonary embolism just six months ago.

More recently, when I had a sudden right-sided facial droop, I wasn’t going to wait around and see if it was caused by a stroke. It turns out that I probably had an atypical onset of Bell’s Palsy, but there was no way I was going to try and sort that out on my own.

And given that I have a very strong history of family members dropping dead of MI, I wasn’t going to fool around when I felt breathless, my heart was racing and I my chest ached. Panic attack, you’re thinking? No, as it turned out that like my mother, I had aFib. Once again, I don’t have a lab or imaging equipment in my apartment – and my PCP doesn’t either – so I think I did the right thing.

The truth is, in each case I’d probably have been OK, but I erred on the side of caution. You know what? I don’t want to die needlessly or sustain major injuries to prove I’m no wimp.

The whole picture

Nonetheless, having been to the ED pretty regularly of late, I still encounter clinicians that wonder if I’m a malingerer, an attention seeker or a hypochondriac. I pick up just a hint of condescension, a sense of being delicately patronized from both clinicians and staffer who think I’m nuts. It’s subtle, but I know it’s there.

Now, if these folks kept up with their industry, they might have read the following, from Health Affairs. The article in question notes that “the overwhelming majority of frequent [ED} users have only episodic periods of high ED use, instead of consistent use over multiple years.” Yup, that’s me.

If they weren’t so prone to judging me and my choices – OK, not everyone but certainly some – it might occur to them to leverage my data. Hey, if I’m being screened but in no deep distress, why not ask what my wearable or health app data has told me of late? More importantly, why haven’t the IT folks at this otherwise excellent hospital equipped providers with even basic filters the ED treatment team can use to spot larger patterns? (Yeah, bringing big data analytics into today’s mix might be a stretch, but still, where are they?)

Don’t get me wrong. I understand that it’s hard to break long-established patterns, change attitudes and integrate any form of analytics into the extremely complex ED workflow. But as I see it, there’s no excuse to just ignore these problems. Soon, the day will come when on-the-spot analytics is the minimum professional requirement for treating ED patients, so confront the problem now.

Oh, and by the way, treat me with more respect, OK?

UCHealth Adds Claims Data To Population Health Dataset

Posted on April 24, 2017 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 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. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

A Colorado-based health system is implementing a new big data strategy which incorporates not only data from clinics, hospitals and pharmacies, but also a broad base of payer claim data.

UCHealth, which is based in Aurora, includes a network of seven hospitals and more than 100 clinics, caring collectively for more than 1.2 million unique patients in 2016. Its facilities include the University of Colorado Hospital, the principal teaching hospital for the University of Colorado School of Medicine.

Leaders at UCHealth are working to improve their population health efforts by integrating data from seven state insurers, including Anthem Blue Cross and Blue Shield, Cigna, Colorado Access, Colorado Choice Health Plans, Colorado Medicaid, Rocky Mountain Health Plans and United Healthcare.

The health system already has an Epic EMR in place across the system which, as readers might expect, offers a comprehensive view of all patient treatment taking place at the system’s clinics and hospitals.

That being said, the Epic database suffers from the same limitations as any other locally-based EMR. As UCHealth notes, its existing EMR data doesn’t track whether a patient changes insurers, ages into Medicare, changes doctors or moves out of the region.

To close the gaps in its EMR data, UCHealth is using technology from software vendor Stratus, which offers a healthcare data intelligence application. According to the vendor, UCHealth will use Stratus technology to support its accountable care organizations as well as its provider clinical integration strategy.

While health system execs expect to benefit from integrating payer claims data, the effort doesn’t satisfy every item on their wish list. One major challenge they’re facing is that while Epic data is available to all the instant it’s added, the payer data is not. In fact, it can take as much as 90 days before the payer data is available to UCHealth.

That being said, UCHealth’s leaders expect to be able to do a great deal with the new dataset. For example, by using Stratus, physicians may be able to figure out why a patient is visiting emergency departments more than might be expected.

Rather than guessing, the physicians will be able to request the diagnoses associated with those visits. If the doctor concludes that their conditions can be treated in one of the system’s primary care clinics, he or she can reach out to these patients and explain how clinic-based care can keep them in better health.

And of course, the health system will conduct other increasingly standard population health efforts, including spotting health trends across their community and better understanding each patient’s medical needs.

Over the next several months, 36 of UCHealth’s primary care clinics will begin using the Stratus tool. While the system hasn’t announced a formal pilot test of how Stratus works out in a production setting, rolling this technology out to just 36 doctors is clearly a modest start. But if it works, look for other health systems to scoop up claims data too!

EHR Implementation Accomplished – What’s Next?

Posted on April 12, 2017 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.

When you look at the world of hospital and health system EHR implementations, it’s fair to say that we can say Mission Accomplished. Depending on which numbers you use, they are all in the range of about 90% EHR adoption in hospitals. That’s a big shift from even 5-10 years ago when it comes to EHR adoption in hospitals. It’s amazing how quickly it shifted.

While it’s easy to sit back and think “Mission Accomplished” the reality is that we still have a LONG way to go when it comes to how we use the EHR. Yes, it’s “Mission Accomplished” as far as getting EHRs implemented. However, it’s just the start of the mission to make EHRs useful. I’d suggest that this is the task that will take up CIOs time the most over the next 5 years.

I think that most people looking at their EHR think about next steps in two large baskets:EHR Optimization and Extracting Value from EHR Data.

EHR Optimization
Most EHR software was slammed in so quickly that it left the users’ heads spinning. Hospitals were chasing the government money and so there was no time to think how the EHR was implemented and the best way to implement the EHR. We’re paying the price for these rushed EHR implementations now.

What’s most shocking to me is how many little things can be done for EHR end users to make their lives better. Many EHR users are suffering from poor training, lack of training, or at least an ignorance to what’s possible with the EHR. I’ve seen this first hand in the EHR implementations I’ve done. I know very clearly that a feature of the EHR was introduced and the users were shown how to do it and 6 months later when you show that feature to them they ask “Why didn’t you teach us this earlier?” Although, they then usually sheepishly say, “Did you teach us this before? I don’t remember it.” At this point it’s not about who we blame, but is about ensuring that every user is trained to the highest degree possible.

The other EHR optimization that many need is an evaluation of their EHR workflow. In most EHR implementations the organization replicates the paper processes. This is often not ideal. Now that the EHR is implemented, it’s a great time to think about why a process was done a certain way and see if there is a different workflow that makes more sense in the digital world. It’s amazing the efficiency you will find.

Extracting Value from EHR Data
As I just suggested, most EHR implementations end up being paper processes replicated electronically. This is not a bad thing, but it can often miss out on the potential value an EHR can provide. This is particularly true when it comes to how you use your EHR data. Most hospitals are still using EHR data the way they did in the paper world. We need to change our thinking if we want to extract the value from the EHR data.

I’ve always looked at EHR data like it was discovering a new world. Reports and analysis that were not even possible in the paper world now become so basic and obvious. The challenge often isn’t the reporting, but the realization that these new opportunities exist. In many cases, we haven’t thought this way and a change in thinking is always a challenge.

When thinking about extracting value from the EHR data, I like to think about it from two perspectives. First, can you provide information at the point of care that will make the patient care experience better for the provider and the patient? Second, can you use the EHR data to better understand an address the issues of a patient population? I’m sure there are other frames of reference as well, but these are two great places to start.

EHR Optimization and creating value from EHR data is going to be a great thing for everyone involved in healthcare and we’re just at the beginning of this process. I think it’s a huge part of what’s next for EHR. What’s your take? What are your plans for your EHR?

Poll: Providers Struggle To Roll Out Big Data Analytics

Posted on April 10, 2017 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 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. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

A new poll by a health IT publication has concluded that while healthcare organizations would like to roll out big data analytics projects, they lack many of the resources they need to proceed.

The online poll, conducted by HealthITAnalytics.com, found that half of respondents are hoping to recruit data science experts to serve as the backbone of their big analytics efforts. However, many are finding it very difficult to find the right staffers.

What’s more, such hires don’t come cheaply. In fact, one study found that data scientist salaries will range from $116,000 to $163,500 in 2017, a 6.4 percent increase over last year’s levels. (Other research concludes that a data scientist in management leading a team of 10 or more can draw up to $250,000 per year.) And even if the pricetag isn’t an issue, providers are competing for data science talent in a seller’s market, not only against other healthcare providers but also hungry employers in other industries.

Without having the right talent in place, many of providers’ efforts have been stalled, the publication reports. Roughly 31 percent of poll respondents said that without a data science team in place, they didn’t know how to begin implementing data analytics initiatives.

Meanwhile, 57 percent of respondents are still struggling with a range of predictable health IT challenges, including EMR optimization and workflow issues, interoperability issues and siloed data. Not only that, for some getting buy-in is proving difficult, with 34 percent reporting that their clinical end users aren’t convinced that creating analytics tools will pay off.

Interestingly, these results suggest that providers face bigger challenges in implementing health data than last year. In last year’s study by HealthITAnalytics.com, 47 percent said interoperability was a key challenge. What’s more, just 42 percent were having trouble finding analytics staffers for their team.

But at the same time, it seems like provider executives are throwing their weight behind these initiatives. The survey found that just 17 percent faced problems with getting executive buy-in and budget constraints this year, while more than half faced these issues in last year’s survey.

This squares with research released a few months ago by IT staffing firm TEKSystems, which found that 63 percent of respondents expected to see their 2017 budgets increase this year, a big change from the 41 percent who expected to see bigger budgets last year.

Meanwhile, despite their concerns, providers are coping well with at least some health IT challenges, the survey noted. In particular, almost 90 percent of respondents reported that they are live on an EMR and 65 percent are using a business intelligence or analytics solution.

And they’re also looking at the future. Three-quarters said they were already using or expect to enhance clinical decision making, along with more than 50 percent also focusing laboratory data, data gathered from partners and socioeconomic or community data. Also, using pharmacy data, patient safety data and post-acute care records were on the horizon for about 20 percent of respondents. In addition, 62 percent said that they were interested in patient-generated health data.

Taken together, this data suggests that as providers have shifted their focus to big data analytics– and supporting population health efforts – they’ve hit more speed bumps than expected. That being said, over the next few years, I predict that the supply of data scientists and demand for their talents should fall into alignment. For providers’ sake, we’d better hope so!

EMRs Can Improve Outcomes For Weekend Hospital Surgeries

Posted on April 7, 2017 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 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. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

Unfortunately, it’s well documented that people often have worse outcomes when they’re treated in hospitals over the weekend. For example, one recent study from the Association of Academic Physiatrists found that older adults admitted with head trauma over the weekend have a 14 percent increased risk of dying versus those admitted on a weekday.

But if a hospital makes good use of its EMR, these grim stats can be improved, according to a new study published in JAMA Surgery. In the study, researchers found that use of EMRs can significantly improve outcomes for hospital patients who have surgeries over the weekend.

To conduct the study, which was done by Loyola Medicine, a group of researchers identified some EMR characteristics which they felt could overcome the “weekend effect.” The factors they chose included using electronic systems designed to schedule surgeries seamlessly as well as move patients in and out of hospital rooms efficiently.

Their theories were based on existing research suggesting that patients at hospitals with electronic operating room scheduling were 33 percent less likely to experience a weekend effect than hospitals using paper-based scheduling. In addition, studies concluded patients at hospitals with electronic bed-management systems were 35 percent less likely to experience the weekend effect.

To learn more about the weekend effect, researchers analyzed the records provided by the AHRQ’s Healthcare Cost and Utilization Project State Inpatient Database.  Researchers looked at treatment and outcomes for 2,979 patients admitted to Florida hospitals for appendectomies, acute hernia repairs and gallbladder removals.

The research team found that 32 percent (946) of patients experienced the weekend effect, which they defined as having longer hospital stays than expected. Meanwhile, it concluded that patients at hospitals with high-speed EMR connectivity, EMR in the operating room, electronic operating room scheduling, CPOE systems and electronic bed management did better. (The analysis was conducted with the help of Loyola’s predictive analytics program.)

Their research follows on a 2015 Loyola study, published in Annals of Surgery, which named five factors that reduced the impact of the weekend effect. These included full adoption of electronic medical records, home health programs, pain management programs, increased registered nurse-to-bed ratios and inpatient physical rehabilitation.

Generally speaking, the study results offer good news, as they fulfill some the key hopes hospitals had when installing their EMR in the first place. But I was left wondering whether the study conflated cause and effect. Specifically, I found myself wondering whether hospitals with these various systems boosted their outcomes with technology, or whether hospitals that invested in these technologies could afford to provide better overall care.

It’s also worth noting that several of the improvement factors cited in the 2015 study did not involve technology at all. Even if a hospital has excellent IT systems in place, putting home health, pain management and physical rehabilitation in place – not to mention higher nurse-to-patient ratios – calls for different thinking and a different source of funding.

Still, it’s always good to know that health IT can generate beneficial results, especially high-ticket items like EMRs. Even incremental progress is still progress.