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E-Patient Update: If Hospitals Were Like Airports

Posted on June 6, 2016 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.

Almost everyone reading this blog has spent some time in an airport. And though not much of it is visible on the surface, airlines do an amazing job of managing people and things seamlessly while you sit reading the New York Times and drinking your latte. People are ushered on and off of flights, baggage is dispatched around the world and airplanes maintained and fueled at a miraculous pace. Although, you probably forget about that when it’s your flight that has delays or issues.

The hospitals many of us work for also do an amazing job of managing people and things, typically in a way that patients never need notice. While the carefully orchestrated dance of care plays out, patients simply eat their meals, sleep, visit with their friends and family and provide whatever bodily fluids are necessary to diagnose them. Meanwhile, multi-million dollar IT systems help see to it that the process works.

In some ways, however, the two industries are quite different in how they work with the people they serve. And in my opinion, the healthcare system would work better if it borrowed from the airlines when it comes to using IT to simplify the customer experience.

Status updates

One thing airlines do well is keep passengers informed about the status of their flight, or the flights of those for whom they might be waiting. Airlines began posting real-time schedules and allowing passengers to preregister for flights from early in the emergence of the commercial Internet.

In more recent times, the airlines have added a mobile dimension to their customer experience, offering small but valuable services like reminder texts and mobile-only information. While being able to check on your flight from your home desktop is great, it’s even better to know what’s up as you head for the airport, and mobile apps make this possible.

Traffic information

Unlike hospitals, airlines post scrolling information on key progress indicators — i.e. arrivals and departures. While you, as a consumer, typically only need to know the status of your own flight, having a comprehensive information source sometimes allows you to better understand delays, orient yourself to time and place and even make a mental note as to which destinations your chosen airline travels.

Such displays don’t disclose any personal information about passengers, but they still offer some value to individuals, if for no other reason than that having this information available helps to put airline staff and consumers on the same page.

Kiosks

These days, many airlines allow passengers to check in for their flights and print tickets without ever speaking to a human clerk. The process not only saves time, but also personal aggravation, as waiting in long airline ticketing queues can be quite tiring.

Checking in at a kiosk also offers passengers additional reassurance that they are indeed booked on the fight of their choice, allows them to confirm their seating choice and in some cases, even add additional flight options.

Transparency is key

I could go on, but I’m sure you get the idea. By exposing what might otherwise have been internal systems to consumers, airlines have substantially improved aspects of their customers’ experience. And they’ve done so without exposing individualized data or subjecting themselves to increased risk of hacking episodes. On the other hand, while health systems and hospitals have dabbled in these areas — for example, by posting ED waiting times on the web — it’s still something of a rarity for them to share live patient information.

Admittedly, hospitals may be leery of giving the patient too much visibility into the process they undergo. After all, their interaction with consumers is a good deal more complex than that of the airline industry, and they don’t have time to explain what they’re doing and why beyond a certain degree.

Still, as a patient who wants to know what the heck is going on with my care, a little transparency would go a long way. If you want patients to be prepared to care for themselves, treat them like adults and include them in what you’re doing.

Will Your EMR Go-Live Education Miss The Mark?

Posted on June 3, 2016 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.

LinkedIn conversations can be quite the font of wisdom, and today was no exception. In comments on a post discussing how training can lead to buy-in, David Kelley, D.O. made it clear that such training often leaves participants cold:

[Have] been the recipient in a couple of Go Lives and been on a few Go Live support teams. The younger/tech-savvy people verbalize the pre-Go Live to have been not worth their time as it was targeted for below their knowledge base. In stark contrast, the more senior/less tech-savvy verbalize near-hatred of those pre-Go Live educational courses as they were so far above their heads as to equate to tech-gibberish.

By reposting these remarks, I’m by no means suggesting that go-live training is a waste of time. Nor am I suggesting that every time hospitals attempt to prepare staffers for EMR implementation, they bore the heck out of staffers while accomplishing nothing. But if Kelley’s experience is any guide, many such trainings are doing a lousy job of connecting with their audience.

His complaints also raise several questions for me, including the following:

  • Who was teaching the courses? Was it vendor reps? If so, it’s little wonder that they produced content only a developer could love.
  • What was the focus of the courses? From Kelley’s comments, it sounds like clinicians and staff typically got a general overview which didn’t do much to foster success.
  • Did the training offer hands-on instruction? And I don’t mean a quick look at basic functions, but rather specific guidance on how to perform key job functions.
  • Did instructors explain the advantages of the new systems? To get buy-in from clinicians and staff, instructors need to hammer home how the new technologies save time, improve efficiency and better patient care.

Regardless, what I gather from Kelley’s story is that too often, hospitals often talk at future EMR users rather than helping them get productive and oriented. It would appear that those responsible for go-lives often fail to consider how the implementation impacts specific functions, and talk around the issues rather than blending training with problem-solving.

I’ve actually seen the effects of what seems to have been a questionable go-live training strategy here in metro DC. Now, the hospital talked a good change management game — even loading screen savers onto all computers stating that “[vendor] is coming!” and posting signs letting patients know about the upcoming shift — for months prior to the system kickoff.

But what do you suppose happened when I spent a few days as an inpatient later that year? I saw nurses and doctors desperately trying to make the system behave by sharing workarounds with each other. Now, you tell me: Would clinical staffers be going to these lengths if they’d had thorough, pitch-perfect, hands-on training?

EHRs Can Help Find Patients At High Risk Of Dying

Posted on June 1, 2016 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.

Much of the discussion around EMRs and EHRs these days focuses on achieving broad, long-term goals such as improved population health. But here’s some data suggesting that these systems can serve a far more immediate purpose – finding inpatients at imminent risk of death.

A study appearing in The American Journal of Medicine details how researchers from Arizona-based Banner Health created an algorithm looking for key indicators suggesting that patients were in immediate danger of death. It was set up to send an alert when patients met at least two of four systemic inflammatory response syndrome criteria, plus at least one over 14 acute organ dysfunction parameters. The algorithm was applied in real time to 312,214 patients across 24 hospitals in the Banner system.

Researchers found that the alert was able to identify the majority of high-risk patients within 48 hours of their admission to a hospital, allowing clinical staff to deliver early and targeted medical interventions.

This is not the first study to suggest that clinical data analysis can have a significant impact on patients’ health status. Research from last year on clinical decision support tools appearing in Generating Evidence & Methods to Improve Patient Outcomes found that such tools can be beefed up to help providers prevent stroke in vulnerable patients.

In that study, researchers from Ohio State University created the Stroke Prevention in Healthcare Delivery Environments tool to pull together and display data relevant to cardiovascular health. The idea behind the tool was to help clinicians have more effective discussions with patients and help address risk factors such as smoking and weight.

They found that the tool, which was tested at two outpatient settings at Ohio State University’s Wexner Medical Center, garnered a “high” level of satisfaction from providers. Also, patient outcomes improved in some areas, such as diabetes status and body mass index.

Despite their potential, few tools are in place today to achieve such immediate benefits as identifying inpatients at high risk of death. Certainly, clinicians are deluged with alerts, such as the ever-present med interaction warnings, but alerts analyzing specific patients’ clinical picture aren’t common. However, they should be. While drug warnings might irritate physicians, I can’t see them ignoring an alert warning them that the patient might die.

And I can hardly imagine a better use of EMR data than leveraging it to predict adverse events among sick inpatients. After all, few hospitals would spend dozens or hundreds of millions of dollars to implement the system which creates a repository that simply mimics paper records.

In addition to preventing adverse events, real-time EMR data analytics will also support the movement to value-based care. If the system can predict which patients are likely to develop expensive complications, physicians can do a better job of preventing them. While clinicians, understandably, aren’t thrilled will being told how to deliver care, they are trained to respond to problems and solve them.

I’m hoping to read more about technologies that leverage EMR data to solve day-to-day care problems. This is a huge opportunity.

Epic Install Triggers Loss At MD Anderson

Posted on May 31, 2016 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.

Surprising pretty much no one, another healthcare organization has attributed adverse financial outcomes largely to its Epic installation. In this case, the complaining party is the University of Texas MD Anderson Cancer Center, which attributes its recent shortfall to both EMR costs and lower revenues. The news follows a long series of cost overruns, losses and budget crises by other healthcare providers implementing Epic of late.

According to Becker’s Hospital CFO, MD Anderson reported adjusted income of $122.9 million during that period a 56.6% drop over the seven-month period ending March 31. During that period, the cancer center’s wages and salaries climbed, and Epic-related consulting costs were climbed as well. This follows a $9.9 million operating loss for the first quarter of the 2016 fiscal year, which the University of Texas attributed to higher-than-expected EMR expenses.

MD Anderson announced its choice of Epic in spring 2013, and went live on the system in March of this year as anticipated. The cancer center’s rollout was guided by Epic veteran Chris Belmont, the center’s CIO, who implemented Epic across 10 hospitals and more than three dozen clinics for New Orleans-based Ochsner Health System.

The organization didn’t announce what it was spending on the Epic install, but we all know it doesn’t come cheap. However, one would think the University of Texas health system could afford the investment. According to EHR Intelligence, the Texas health system ranks in the 99th percentile for net patient revenue in the US, with total revenue topping $5.58 billion.

And UT leaders seem to have been prepared for the bump, reporting that they’d planned for a material impact to revenues and expenses as a result of the Epic implementation. The system didn’t announce any staff cuts, hiring freezes or other budget-trimming moves resulting from these financial issues.

Having said all this, however, no organization wants to see its income drop. So what actually happened?

For example, when the UT system reports that a drop in patient revenues contributed to the drop in income, what does that mean? Does this refer to scheduled drops in patient volume, planned for ahead of time, or problems billing for services? I’d be interested to know if the center managed to keep on top of revenue cycle management during the transition.

Another question I have is what caused the unanticipated expenses. Did they come from contract disputes with Epic? Unexpected technical problems? Markups on consulting services? Or did the organization have to pour money into the project to meet its go-live deadline? There’s a lot of ways to generate costs, and I’d love to get some granular information on what happened.

Also, I wonder what steps UT leaders will take to avoid unexpected expenses in the future. While it may have learned some lessons from the problems it’s had so far, there’s no guarantee that it won’t face of the costly problems going forward.

If, perchance, and the system has figured out how to stay in the black with its Epic investment, it could sell that secret to cover its IT expenses for years. I’m betting other systems would pay good money for that information!

Why Remote Patient Monitoring and Treatment Is So Important to Healthcare

Posted on 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.

This post is sponsored by Samsung Business. All thoughts and opinions are my own.

When you think about healthcare, you often think of a visit to a doctor’s office or hospital. No doubt that is healthcare as we know it today, but that’s quickly changing. Doctors and hospitals need to wake up to the new healthcare world where you’re paid to keep patients healthy as opposed to treating the chief complaint.

It’s not surprising that we do a poor job managing patients’ health when you consider how much time our current healthcare providers get to spend with the patient. Most patient visits are between 15-30 minutes. In fact, one study showed that doctors see a patient every 11 minutes on average.

Let’s be generous and say that each one of us spends 15 minutes with a doctor once a month and that’s likely being generous for most of us that are even relatively healthy. My simple math says that would add up to us spending about 180 minutes (3 hours) each year with our doctor. There are 8760 hours in a year and so that means we spend about 0.0342% of our life with our doctor each year.

Is it any wonder that our doctors only have time to treat our chief complaint and can’t really help us be and remain healthy when they see us so little?

This simple analysis is why remote patient monitoring is so important to healthcare. We spend exponentially more time outside of our current healthcare system than we do in it. Our understanding of what happens outside the hospital and doctor’s office must change if we’re going to make a dent in the trillions of dollars we spend on healthcare.

The great thing is that we’re starting to see a reinvention of health care with things like mobile medical apps. Previous to the smartphone, how would you have monitored a patient remotely? Sure, we had some bluetooth connected devices that we sent home and people attached to their computers, but that was always cumbersome and fraught with technical challenges. Now we have an always on, always connected device that’s nearly attached to most of us at all times. Many of these devices even come with built-in health sensors. These devices are making remote patient monitoring possible

I don’t fault doctors for not really treating the entire patient in the past. First, they performed the services they were paid to provide. They weren’t paid or given the time to treat the whole patient. Second, the technology wasn’t available for them to scale their remote patient monitoring and treatment efforts. However, we’re seeing both of these things changing as we speak.

Now that I’ve made the case for remote patient monitoring and treatment, what technologies and approaches have you seen be most successful in this space?

For more content like this, follow Samsung on Insights, Twitter, LinkedIn , YouTube and SlideShare.

A Primer on Medicaid/CHIP Managed Care Reform

Posted on May 27, 2016 I Written By

The following is a guest blog post by Megan Renfrew, Director in the Cognosante Solutions Lab.
Megan Renfrew - Cognosante
On May 6, 2016, the Centers for Medicare and Medicaid Services (CMS) published a final regulation in the Federal Register concerning managed care in Medicaid and the Children’s Health Insurance Program (CHIP).  The first overhaul of Medicaid and CHIP managed care regulations in more than a decade, the rule “updates how Medicaid works for the nearly two-thirds of beneficiaries who get coverage through private managed care plans,” wrote CMS Acting Administrator Andy Slavitt and Vikki Wachino, CMS Deputy Administrator and Director for the Center for Medicaid and CHIP Services, in a CMS blog post.

Approximately 72 percent of Medicaid enrollees in 39 states and the District of Columbia are served through managed care plans, up 14 percent since 2013.  Combined Federal and state spending on Medicaid managed care exceeds $150 billion annually.  Those figures will grow steadily as states continue to expand Medicaid managed care coverage to include larger geographic areas, additional populations, and services previously covered through fee-for-service Medicaid, such as inpatient and Long-Term Services and Support (LTSS).

While the medical loss ratio and other financial requirements received the lion’s share of attention throughout the rule-making process, the rule’s focus on improving the beneficiary experience and increased reporting and data requirements are equally important.  Beneficiaries will benefit from quality improvement requirements, stricter provider access requirements, and stronger care management programs.  Plans and states will need to adjust contracts and IT systems to meet new data, reporting, and analytics requirements that support CMS’s goals of increased program integrity and transparency.

Beneficiary Experience & Protections

To strengthen the experience of beneficiaries, the rule requires states to address disparities and individuals who need long term care or have special health needs in their quality plans for the Medicaid managed care rule.  The final rule, which will be phased in over several years, also creates the first quality rating system for Medicaid managed care plans, aligning Medicaid with Medicare Advantage and Qualified Health Plans rules.  This will allow beneficiaries to better compare plans before enrollment.

On the care management front, the rule includes standards for care coordination, health assessments for new plan enrollees, and treatment plans for enrollees with special healthcare needs or who receive LTSS.  These rules are designed to make sure that beneficiaries receive appropriate care in the appropriate setting, and are assisted in navigating the complex healthcare system.

The rule helps ensure that beneficiaries have sufficient access to providers by strengthening provider network adequacy requirements.  States must add time and distance standards to their state network adequacy rule (31 states already have time and distance standards in place for primary care providers).  Under the final rule, however, CMS spells out the provider types subject to network adequacy requirements in greater detail.  As a result, states must now create standards for more than seven different provider types.  Plans must also report provider network data at least annually, and maintain an up-to-date provider directory for plan members.

Additional changes focus on targeted beneficiary education and outreach.  States must implement systems that support beneficiaries prior to and after enrollment, a role that will likely be played by enrollment brokers.  Under these systems, beneficiaries are educated about managed care, including benefits covered and choice of plans, and their rights and responsibilities under Medicaid.  The beneficiary support system also provides a venue for current managed care enrollees, including assistance navigating the grievance and appeals process.

Enhanced Data and Systems Needs

Under the final rule, states and plans are required to meet stronger data submission and reporting requirements to support program oversight, program integrity, and increased transparency.  To meet these requirements, states and plans must have adequate IT systems to ensure accurate and timely data delivery and reporting.  Some states and managed care plans will likely need to increase their data collection and analytics capabilities to comply with the new rule.

The most important change is that federal payment for Medicaid managed care is tied to the submission of accurate, complete, and timely encounter data to CMS in a CMS-specified format, likely TMSIS.  Historically, some states have struggled to collect complete and accurate encounter data from managed care plans, and to manage that data in legacy systems designed for fee-for-service claims.  Both states and plans will need to examine their current IT systems, data collection and submission processes, and contract language to ensure that they are well positioned to meet these requirements.

In addition to the encounter data requirements, CMS is requiring that states post information on their Medicaid managed care plans on a public website, including enrollee handbooks, provider directories, and plan contracts.  Also required is information about plan performance, including finances, operational performance, quality indicators, measures of customer satisfaction, and the results of program integrity audits.

To meet the stricter provider network adequacy requirements, plans will need to have, at a minimum, accurate data on their provider network.  As states revise their network adequacy rules to meet the CMS requirements and monitor their plans for compliance, they may benefit from using GIS-based tools that automate network adequacy analysis and allow for easy evaluation of policy options and plan performance.

To support program integrity goals, the CMS rule requires all providers in Medicaid managed care plan networks to enroll with the state Medicaid agency.  Enrollment in Medicaid was previously required only of those providers participating in the Medicaid fee-for-service program.  States may find that they need more automated provider enrollment and verification systems to handle the increased workload that this requirement will generate for state Medicaid agencies.  Luckily, provider enrollment solutions are available in the market.

To help ease the burden of implementing the systems necessary to manage the robust data collection, analysis, exchange, and reporting necessary under Medicaid managed care reform, states can leverage CMS’s previously issued final rule extending 90 percent federal matching funds for Medicaid enterprise system development.  In addition to ensuring the permanent availability of this funding, that rule extends its use to commercial-off-the-shelf and software-as-a-service solutions.  This allows states to take advantage of previously developed and tested products in the marketplace.

21st Century Medicaid

CMS and its stakeholders devoted thousands of hours to crafting sweeping reform that brings Medicaid manage care into the 21st Century, including supporting data-driven decision-making and oversight, and allowing for state innovation in delivery system and payment reform. Doing so solidifies Medicaid’s place as a key driver of health innovation and plans’ roles supporting and implementing that innovation.

About Megan Renfrew
Megan Renfrew is a Director in the Cognosante Solutions Lab.  An accomplished health policy expert who spent more than five years drafting healthcare bills for the U.S. House of Representatives, she previously served as the technical director at CMS responsible for collecting and analyzing Medicaid and CHIP eligibility and enrollment data from states. 

Appointment Scheduling Site Zocdoc Connects With Epic

Posted on May 25, 2016 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.

In a bid to capture hospital and health system business, appointment scheduling site Zocdoc announced that its customers can now connect the site to their Epic EMRs via an API. The updated Zocdoc platform targets the partners’ joint customers, which include Yale New Haven Health, NYU Langone Medical Center, Inova Health System and Hartford HealthCare. And I’ll admit it – I’m intrigued.

Typically, I don’t write stories about vendors other than the top EMR players. And on the surface, the deal may not appear very interesting. But the truth is, this partnership may turn out to offer a new model for digital health relationships. If nothing else, it’s a shrewd move.

Historically, Zocdoc has focused on connecting medical practices to patients. Physicians list their appointment schedule and biographical data on the site, as well as their specialty. Patients, who join for free, can search the site for doctors, see when their chosen physician’s next available appointment is and reserve a time of their choosing. If patients provide insurance information, they are only shown doctors who take their insurance.

As a patient, I find this to be pretty nifty. Particularly if you manage chronic conditions, it’s great be able to set timely medical appointments without making a bunch of phone calls. There are some glitches (for example, it appears that doctors often don’t get the drug list I entered), but when I report problems, the site’s customer service team does an excellent job of patching things up. So all told, it’s a very useful and consumer-friendly site.

That being said, there are probably limits to how much money Zocdoc can make this way. My guess is that onboarding doctors is somewhat costly, and that the site can’t charge enough to generate a high profit margin. After all, medical practices are not known for their lavish marketing spending.

On the other hand, working with health systems and hospitals solves both the onboarding problem and the margin problem. If a health system or hospital goes with Zocdoc, they’re likely to bring a high volume of physicians to the table, and what’s more, they are likely to train those doctors on the platform. Also, hospitals and health systems have larger marketing budgets than medical practices, and if they see Zocdoc as offering a real competitive advantage, they’ll probably pay more than physicians.

Now, it appears that Zocdoc had already attracted some health systems and hospitals to the table prior to the Epic linkage. But if it wants to be a major player in the enterprise space, connecting the service to Epic matters. Health systems and hospitals are desperate to connect disparate systems, and they’re more likely to do deals with partners that work with their mission-critical EMR.

To be fair, this approach may not stick. While connecting an EMR to Zocdoc’s systems may help health systems and hospitals build patient loyalty, appointment records don’t add anything to the patient’s clinical picture. So we’re not talking about the invention of the light bulb here.

Still, I could see other ancillary service vendors, particularly web-based vendors, following in Zocdoc’s footsteps if they can. As health systems and hospitals work to provide value-based healthcare, they’ll be less and less tolerant of complexity, and an Epic connection may simplify things. All told, Zocdoc’s deal is driven by an idea whose time has come.

Avoiding Revenue Crunches During EMR Transitions

Posted on May 23, 2016 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.

Most healthcare leaders know, well before their EMR rollouts, that clinical productivity and billings may fall for a while as the implementation proceeds. That being said, it seems a surprising number are caught off guard by the extent to which payments can be lost or delayed due to technical issues during the transition. This is particularly alarming as more and more hospitals are looking at switching EHR.

Far too often, those responsible for revenue cycle issues live in a silo that doesn’t communicate well with hospital IT leadership, and the results can be devastating financially. For example, consider the case of Maine Medical Center, which took a major loss after it launched its Epic EMR in 2012, due in part to substantial problems with billing for services.

But according to McKesson execs, there’s a few steps health systems and hospitals can take to reduce the impact this transition has in your revenue cycle. Their recommendations include the following:

  • Involve revenue cycle managers in your EMR migration. Doing so can help integrate RCM and EMR technologies successfully.
  • Create a revenue cycle EMR team. The team should include the CFO, revenue cycle leaders from patient access and reimbursement, vendor reps and someone familiar with revenue cycle systems. Once this team is assembled, establish a meeting schedule, team roles and goals for participants. It’s particularly important to designate a project manager for the revenue cycle portion of your EMR rollout.
  • Before the implementation, research how RCM processes will be affected by the by the rollout, particularly how the new EMR will impact claims management workflow, speed of payment and staff workloads. Check out how the implementation will affect processes such as eligibility verification, registration data quality assurance, preauthorization and medical necessity management, pre-claim editing and remittance management.
  • Pay close attention to key performance indicators throughout the transition. These include service-to-payment velocity, Days Not Final Billed, charge trends and denial rates.

The article also recommends bringing on consultants to help with the transition. Being that McKesson is a health IT vendor, I’m not at all surprised that this is the case. But there’s something to the idea nonetheless. Self-serving though such a recommendation may be, it may help to bring in a consultant who has an outside view of these issues and is not blinkered by departmental loyalties.

That being said, over the longer term healthcare leaders need to think about ways to help RCM and IT execs see eye to eye. It’s all well and good to create temporary teams to smooth the transition to EMR use. But my guess is that these teams will dissolve quickly once the worst of the rollout is over. After all, while IT and revenue cycle management departments have common interests, their jobs differ significantly.

The bottom line is that to avoid needless RCM issues, the IT department and revenue cycle leaders need to be aligned in their larger goals. This can be fostered by financial rewards, common performance goals, cultural expectations and more, but regardless of how it happens, these departments need to be interested in working together. However, unless rewards and expectations change, they have little incentive to do so. It’s about time hospital and health system leaders address problem directly.

Healthcare IT Competitive Landscape Graphic

Posted on May 20, 2016 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.

I recently did an interview with a market research firm about healthcare IT and specifically about patient portals. They sent me their final report and in that report they shared a graphic of the competitive landscape for healthcare IT (which they said I could share):

Healthcare IT Competitive Landscape

I’m sure we could quibble over some of the categories they chose, where a company resides (ie. IBM bought Truven Analytics, so they’re now technically one company), companies left off, etc, but I thought it was an interesting overview of the kind of companies that are trying to make an impact in healthcare.

In fact, what hit me most about this graphic was the diversity of companies that have a foothold in healthcare. I’ve certainly heard and worked with all of the companies on the list. However, I’d never really sat back and thought about the breadth of companies that are trying to do something in healthcare.

Of course, when you think about the trillions of dollars being spent on healthcare, it’s not that big of a surprise that these large companies would want a piece of that large pie. In fact, there are a number of other very large companies that are definitely missing from this graphic (no doubt the graphic wasn’t intended to be comprehensive).

I’d love to hear what other categories of companies you think should be represented on the list. Any other category of companies you see working in healthcare?

Are Current Population Health Tools Becoming Outdated?

Posted on May 18, 2016 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.

These days, virtually all hospitals and health systems are looking at ways to manage population health. Most of their approaches assume that it’s a matter of identifying the right big data tools and crunching the numbers, using the data already in-house. Doing this may be costly and time-consuming, but it can be done using existing databases, integration engines and the appropriate business analytics tools, or so the conventional wisdom holds.

However, at least one health IT leader disagrees. Adrian Zai, MD, clinical director of population informatics at Massachusetts General Hospital, argues that current tools designed to enable population health management can’t do the job effectively. “All of the health IT tools companies call population health today will be irrelevant because the data they look at can only see what goes through hospital, which is far too narrow in scope.”

Zai points out that most healthcare organizations attempt to leverage claims data in doing population health management analyses. But that approach is far from ideal, he told Healthcare IT News. Claims data, he points out, is typically one to two months old, which significantly limits the value healthcare providers can generate from the data. Also, most hospitals’ claims data only covers about 20% to 30% of the area’s population, he notes.

Instead, organizations need to study real-time data drawn from a significantly broader population if they hope to achieve population health management goals, Zai argues. For example, it’s important to look at the Medicaid population, whose members may get most of their care through community health centers. It’s also important to collect data from other consumer touch points. (Zai doesn’t specify which touch points he means, but mobile health and remote patient monitoring data come to mind immediately.)

I think Zai make some excellent points here. In particular, while achieving true real-time analysis is probably well the future for most healthcare organizations, the fresher data you can use the better. Certainly, analyzing archival data has a purpose, but to have a major impact on outcomes, it’s important to foster behavior change in the present.

However, I’d argue that few providers are ready to roll ahead with this approach. After all, to achieve his goals means establishing some new definitions as to what data should be included in population health analysis. And that’s not as simple as it sounds. (For a recent look at how providers look at population health, check out this survey from last summer.)

First, providers need to take a fresh look at how they define the term “population,” and develop a definition that takes in a more comprehensive view of patient data. Certainly, claims data analysis is start, but that by definition is limited to insured patients seen at the hospital. Zai recommends that population health management efforts embrace all patients seen at the hospital, insured or not. In other words, he’s recommending hospitals address the community in which they are physically located, not just the community of patients for whom they have provided care.

Just as importantly, hospitals and health systems need to consider how to collect, incorporate and analyze the exponentially-growing field of digital health data. While some middleware solutions offer to serve as a gateway for such data, it seems likely that providers will still need to do a lot of hands-on work to make use of these data sources.

Finally, providers need to continually improve the algorithms they use to pinpoint problems in a given population, as well as the ways in which they create actionable subsets of the population. For example, it may be appropriate to target patients by disease state today, but other ways of improving outcomes might arise, and providers’ IT solutions need to be flexible enough to evolve with the times.

Over time, the industry will evolve best practices for population health management, and definedthe IT tools best suited to accomplish reasons. And while some existing tools may work, I’d be surprised if most survive the transition.