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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.

Avoiding Financial Losses After EMR Implementation

Posted on April 3, 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 hospitals buy EMRs to improve their operations – both clinically and financially – too often they take a hit before they work out the kinks in their installation.  In fact, healthcare institutions often end up losing up to 5 percent of their gross revenue after EMRs are implemented, according to consultant Erick McKesson.

One typical story comes from Maine Medical Center, which found that patient charges weren’t appearing after its $150 million Epic installation in 2012. These billing errors were one of the reasons the medical center posted a $13.4 million loss in the first six months after the installation, hospital executives reported.

But according to McKesson, managing consultant with Navigant, it’s possible to overcome these problems. In an article for Becker’s Hospital Review, he tells the story of a group of health systems which worked together to avoid such losses. The group worked together to identify the most valuable software features that flagged mischarges or reporting errors. They then identified the five charge program “edits” which had the largest financial impact.

Areas the cooperating health systems considered the most important included:

* Administrative codes

The health systems noted that incorrect administrative codes lead to lagging revenue. That’s particularly the case when there are different codes for the same procedure. Hospitals need to be sure that clinicians use the higher code if appropriate, which can be helped by the right technological fixes.

* Anesthesia

It’s important to monitor your charges when there are two distinct aspects of a single procedure that are charged separately, particularly with anesthesia services. If your audit system flags the absence of the added codes, it can recapture a substantial level of missing revenue.

* CT

Seeing to it that radiology charges are automatically reviewed can ensure that appropriate levels of revenue are generated. For example, in the case of CT exams, it’s important to see that charges are assessed for both the exam and if needed, the use of a contrast agent.

* Emergency Department

It’s not unusual for ED physicians to undercode high-acuity patients. But it’s important to address this issue, as undercoding can result in significant financial consequences.  Not only that, in addition to generating financial losses, undercoding can create problems with performance-based reimbursement contracts. If patients are depicted as less acute than they actually are, payors may expect better outcomes than the patients are likely to have. And that can lead to lower revenue or even significant financial penalties.

* Infusions

Auditing infusion charges can be very helpful in capturing added revenues, given that they are one of the most frequent charges in healthcare. Infusion codes are very complex, including the need to track start and stop times, difficult rules regarding what charges are appropriate during infusions and issues related to “carve out periods.” Auditing systems can help clinicians comply with requirements, including simple-to-create functions which automatically flag missing stop times.

As readers will doubtless know, getting competing health systems to engage in “coopetition” can be tough, even if it helps them improve their operations. But given the need to combat post-EMR lags in revenue, maybe more of them will risk it in the future.

Database Linked With Hospital EMR To Encourage Drug Monitoring

Posted on March 31, 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.

According to state officials, Colorado occupies the unenviable position of second worst in the US for prescription drug misuse, with more than 255,000 Coloradans misusing prescribed medications.

One way the state is fighting back is by running the Colorado Prescription Drug Monitoring Program which, like comparable efforts in other states, tracks prescriptions for controlled medications. Every regular business day, the state’s pharmacists upload prescription data for medications listed in Schedules II through V.

While this effort may have value, many physicians haven’t been using the database, largely because it can be difficult to access. In fact, historically physicians have been using the system only about 30 percent of the time when prescribing controlled substances, according to a story appearing in HealthLeaders Media.

As things stand, it can take physicians up to three minutes to access the data, given that they have to sign out of their EMR, visit the PDMP site, log in using separate credentials, click through to the right page, enter patient information and sort through possible matches before they got to the patient’s aggregated prescription history. Given the ugliness of this workflow, it’s no surprise that clinicians aren’t searching out PDMP data, especially if they don’t regard a patient as being at a high risk for drug abuse or diversion.

But perhaps taking some needless steps out of the process can make a difference, a theory which one of the state’s hospitals is testing. Colorado officials are hoping a new pilot program linking the PDMP database to an EMR will foster higher use of the data by physicians. The pilot, funded by a federal grant through the Bureau of Justice Assistance, connects the drug database directly to the University of Colorado Hospital’s Epic EMR.

The project began with a year-long building out phase, during which IT leaders created a gateway connecting the PDMP database and the Epic installation. Several months ago, the team followed up with a launch at the school of medicine’s emergency medicine department. Eventually, the PDMP database will be available in five EDs which have a combined total of 270,000 visits per year, HealthLeaders notes.

Under the pilot program, physicians can access the drug database with a single click, directly from within the Epic EMR system. Once the PDMP database was made available, the pilot brought physicians on board gradually, moving from evaluating their baseline use, giving clinicians raw data, giving them data using a risk-stratification tool and eventually requiring that they use the tool.

Researchers guiding the pilot are evaluating whether providers use the PDMP more and whether it has an impact on high-risk patients. Researchers will also analyze what happened to patients a year before, during and a year after their ED visits, using de-identified patient data.

It’s worth pointing out that people outside of Colorado are well aware of the PDMP access issue. In fact, the ONC has been paying fairly close attention to the problem of making PDMP data more accessible. That being said, the agency notes that integrating PDMPs with other health IT systems won’t come easily, given that no uniform standards exist for linking prescription drug data with health IT systems. ONC staffers have apparently been working to develop a standard approach for delivering PDMP data to EMRs, pharmacy systems and health information exchanges.

However, at present it looks like custom integration will be necessary. Perhaps pilots like this one will lead by example.