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Interoperability Problems Undercut Conclusions of CHIME Most Wired Survey

Posted on November 11, 2018 I Written By

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

Most of you have probably already seen the topline results from CHIME’s  “Healthcare’s Most Wired: National Trends 2018” study, which was released last month.

Some of the more interesting numbers coming out of the survey, at least for me, included the following:

  • Just 60% of responding physicians could access a hospital network’s virtual patient visit technology from outside its network, which kinda defeats the purpose of decentralizing care delivery.
  • The number of clinical alerts sent from a surveillance system integrated with an EHR topped out at 58% (alerts to critical care units), with 35% of respondents reporting that they had no surveillance system in place. This seems like quite a lost opportunity.
  • Virtually all (94%) participating organizations said that their organization’s EHR could consume discrete data, and 64% said they could incorporate CCDs and CCRs from physician-office EHRs as discrete data.

What really stands out for me, though, is that if CHIME’s overall analysis is correct, many aspects of our data analytics and patient engagement progress still hang in the balance.

Perhaps by design, the hospital industry comes out looking like it’s doing well in most of the technology strategy areas that it has questions about in the survey, but leaves out some important areas of weakness.

Specifically, in the introduction to its survey report, the group lists “integration and interoperability” as one of two groups of foundational technologies that must be in place before population health management/value-based care,  patient engagement and telehealth programs can proceed.

If that’s true, and it probably is, it throws up a red flag, which is probably why the report glossed over the fact that overall interoperability between hospitals is still very much in question. (If nothing else, it’s high time the hospitals adjust their interoperability expectations.) While it did cite numbers regarding what can be done with CCDs, it didn’t address the much bigger problems the industry faces in sharing data more fluidly.

Look, I don’t mean to be too literal here. Even if CHIME didn’t say so specifically, hospitals and health systems can make some progress on population health, patient engagement, and telehealth strategies even if they’re forced to stick to using their own internal data. Failing to establish fluid health data sharing between facility A and facility B may lead to less-than-ideal results, but it doesn’t stop either of them from marching towards goals like PHM or value-based care individually.

On the other hand, there certainly is an extent to which a lack of interoperability drags down the quality of our results. Perhaps the data sets we have are good enough even if they’re incomplete, but I think we’ve already got a pretty good sense that no amount of CCD exchange will get the results we ultimately hope to see. In other words, I’m suggesting that we take the CHIME survey’s data points in context.

Hospitals Taking Next-Gen EHR Development Seriously

Posted on October 22, 2018 I Written By

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

Physicians have never been terribly happy with EHRs, most of which have done little to meet the lofty clinical goals set forth by healthcare leaders. Despite the fact that EHRs have been a fact of life in medicine for nearly a decade, health IT leaders don’t seem to have figured out how to build a significantly better one — or even what “better” means.

While there has been the occasional project leveraging big data from EHRs to improve care processes, little has been done that makes it simple for physicians to benefit from these insights on a day-to-day basis. Not only that, while EHRs may have become more usable over time, they still don’t present patient data in an intuitive manner.

However, hospital leaders have may be developing a more-focused idea of how a next-gen EHR should work, at least if recent efforts by Stanford Medicine and Penn Medicine are any indication.

For example, Stanford has developed a next-gen EHR model which it argues could be rolled out within the next 10 years. The idea behind the model would be that clinicians and other healthcare professions would simply take care of patients, with information flowing automatically to all relevant parties, including payers, hospitals, physicians and patients. Its vision seems far less superficial than much of the EHR innovation happy talk we’ve seen in the past.

For example, in this model, an automated physician’s assistant would “listen” to interactions between doctors and patients and analyze what was said. The assistant would then record all relevant information in the physical exam section of the chart, sorting it based on what was said in the room and what verbal cues clinicians provided.

Another initiative comes from Penn Medicine, where leaders are working to transform EHRs into more streamlined, interactive tools which make clinical work easier and drive best outcomes. Again, while many hospitals and health centers have talked a good game on this front, Penn seems to be particularly serious about making EHRs valuable. “We are approaching this endeavor as if it were building a new clinical facility, laboratory or training program,” said University of Pennsylvania Health System CEO Ralph Muller in a prepared statement.

Penn hasn’t gone into many specifics as to what its next-gen EHR would look like, but in its recent statement, it provided a few hints. These included the suggestion that they should allow doctors to “subscribe” to patients’ clinical information to get real-time updates when action is required, something along the lines of what social media networks already do with feeds and notifications.

Of course, there’s a huge gap between visions and practical EHR limitations. And there’s obviously a lot of ways in which the same general goals can be met. For example, another way to talk about the same issues comes from HIT superstar Dr. John Halamka, chief information officer of the Beth Israel Deaconess Medical Center and CIO and dean for technology at Harvard Medical School.

In a blog post looking at the shift to EHR 2.0, Halamka argues for the development of a new Care Management Medical Record which enrolls patients in protocols based on conditions then ensures that they get recommended services. He also argues that EHRs should be seen as flexible platforms upon which entrepreneurs can create add-on functionality, something like apps that rest on top of mobile operating systems.

My gut feeling is that all told, we are seeing from real progress here, and that particularly given the emergence of more mature AI tools, a more-flexible EHR demanding far less physician involvement will come together. However, it’s worth noting that the Stanford researchers are looking at a 10-year timeline.  To me, it seems unlikely that things will move along any faster than that.

Taming the Healthcare Compliance and Data Security Monster: How Well Are We Doing?

Posted on October 18, 2018 I Written By

The following is a guest blog post by Lance Pilkington, Vice President of Global Compliance at Liaison Technologies.

Do data breach nightmares keep you up at night?

For 229 healthcare organizations, the nightmare became a reality in 2018. As of late August, more than 6.1 million individuals were affected by 229 healthcare-related breaches, according to the Department of Health and Human Services’ HIPAA Breach Reporting Tool website – commonly call the HIPAA “wall of shame.”

Although security and privacy requirements for healthcare data have been in place for many years, the reality is that many healthcare organizations are still at risk for non-compliance with regulations and for breaches.

In fact, only 65 percent of 112 hospitals and hospital groups recently surveyed by Aberdeen, an industry analyst firm, reported compliance with 11 common regulations and frameworks for data security. According to the healthcare-specific brief – Enterprise Data in 2018: The State of Privacy and Security Compliance in Healthcare – protected health information has the highest percentage of compliance, with 85 percent of participants reporting full compliance, and the lowest compliance rates were reported for ISO 27001 and the General Data Protection Regulation at 63 percent and 48 percent respectively.

An index developed by Aberdeen to measure the maturity of an organization’s compliance efforts shows that although the healthcare organizations surveyed were mature in their data management efforts, they were far less developed in their compliance efforts when they stored and protected data, syndicated data between two applications, ingested data into a central repository or integrated data from multiple, disparate sources.

The immaturity of compliance efforts has real-world consequences for healthcare entities. Four out of five (81 percent) study participants reported at least one data privacy and non-compliance issue in the past year, and two out of three (66 percent) reported at least one data breach in the past year.

It isn’t surprising to find that healthcare organizations struggle with data security. The complexity and number of types of data and data-related processes in healthcare is daunting. In addition to PHI, hospitals and their affiliates handle financial transactions, personally identifiable information, employee records, and confidential or intellectual property records. Adding to the challenge of protecting this information is the ever-increasing use of mobile devices in clinical and business areas of the healthcare organization.

In addition to the complexities of data management and integration, there are budgetary considerations. As healthcare organizations face increasing financial challenges, investment in new technology and the IT personnel to manage it can be formidable. However, healthcare participants in the Aberdeen study reported a median of 37 percent of the overall IT budget dedicated to investment in compliance activities. Study participants from life sciences and other industries included in Aberdeen’s total study reported lower budget commitments to compliance.

This raises the question: If healthcare organizations are investing in compliance activities, why do we still see significant data breaches, fines for non-compliance and difficulty reaching full compliance?

While there are practical steps that every privacy and security officer should take to ensure the organization is compliant with HIPAA, there are also technology options that enhance a healthcare entity’s ability to better manage data integration from multiple sources and address compliance requirements.

An upcoming webinar, The State of Privacy and Security Compliance for Enterprise Data: “Why Are We Doing This Ourselves?” discusses the Aberdeen survey results and presents advice on how healthcare IT leaders can evaluate their compliance-readiness and identify potential solutions can provide some thought-provoking guidance.

One of the solutions is the use of third-party providers who can provide the data integration and management needs of the healthcare organization to ensure compliance with data security requirements. This strategy can also address a myriad of challenges faced by hospitals. Not only can the expertise and specialty knowledge of the third-party take a burden off in-house IT staff but choosing a managed services strategy that eliminates the need for a significant upfront investment enables moving the expense from the IT capital budget to the operating budget with predictable recurring costs.

Freeing capital dollars to invest in other digital transformation strategies and enabling IT staff to focus on mission-critical activities in the healthcare organization are benefits of exploring outsource opportunities with the right partner.

More importantly, moving toward a higher level of compliance with data security requirements will improve the likelihood of a good night’s sleep!

About Lance Pilkington
Lance Pilkington is the Vice President of Global Compliance at Liaison Technologies, a position he has held since joining the company in September 2012. Lance is responsible for establishing and leading strategic initiatives under Liaison’s Trust program to ensure the company is consistently delivering on its compliance commitments. Liaison Technologies is a proud sponsor of Healthcare Scene.

Heathcare AI Maturity Index

Posted on October 16, 2018 I Written By

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

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

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

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

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

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

Montefiore Health Makes Big AI Play

Posted on September 24, 2018 I Written By

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

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

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

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

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

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

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

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

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

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

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

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

Posted on September 21, 2018 I Written By

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

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

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

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

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

Pricing Transparency and Provider Quality: Insights from Utah HIMSS

Posted on September 10, 2018 I Written By

Healthcare as a Human Right. Physician Suicide Loss Survivor. Janae writes about Artificial Intelligence, Virtual Reality, Data Analytics, Engagement and Investing in Healthcare. twitter: @coherencemed

Working to improve Health IT has been a major focus of Utah HIMSS this year. I am honored to serve as part of the Utah HIMSS Board. Utah HIMSS hosts educational events and luncheons for members. On August 29, 2018  the meeting focused on Pricing Transparency and Provider Quality. Health Informatics is positioned to help reduce waste in healthcare and providing better care for patients.

Bob White works with Select Health, one of the major insurance providers in the state, which is a subsidiary of Intermountain Healthcare. He was able to talk about payment models and value based care work within the Select Health group. Providing more visibility into the cost for patients and physicians has been a major focus on Select Health and payer provider entities have a unique market position. They want the cost of care delivery to be lower since they are paying the cost. Point of service adjudication requires that a lot of workflows need to be coordinated before the patient leaves the office.

Bob asked: How often do we feel like we don’t have complete information to know what is going on and what your options are?

One of the most notable things that he spoke about was the lack of adoption. They have great visibility but not everyone knows where to find that information. Some of the employees at Selecthealth have high deductible plans and in effect, become self-pay members. Becoming more educated consumers is a huge part of what Select Health has done with their pricing transparency.

Katie Harwood from the University Of Utah discussed their pricing transparency tool. The University of Utah is one of the first systems in the country to create an online interactive tool to help predict cost to patients. Patients can look up what a procedure might cost and enter information about their copay and caps. Most importantly, the cost estimator included the cost of facility and cost of provider, so patients don’t get stuck with unexpected out of network bills.

The most common search? Vaginal delivery without complications. I was thrilled to hear them speak because I’m pregnant and my provider is with the University of Utah Health. I got a cost estimate on my second visit to the OB and I was pleasantly surprised that they gave that information.  I was able to pay for what (might be) the cost of my maternity care. Being able to plan ahead is very valuable. The University of Utah has invested in creating bundled payment models to improve care coordination and as a patient, having that information has improved my healthcare experience.

While in development, the University of Utah wanted to add appointment scheduling for patients. Harwood mentioned this created a larger data matching challenge, as it was difficult to match exact providers with procedures. Insurance companies are trying to make it easier for patients to schedule and understand what their costs will be, and physician directories create unique challenges. What if you were a surgeon who performed a total knee replacement but you didn’t have the information connected with the correct insurance company for you to appear in the online scheduling tool?

Interestingly, many people go to the cost estimator tool enter “I don’t know” for some of their search criteria such as deductible and copay. Bridging the consumer gap to give even better information and creating the most accurate scheduling possible starts with efforts to create great health IT tools and adjusting them according to user behavior.

Holly Rimmasch from Health Catalyst was able to ask great questions and mentioned a program that Health Catalyst is doing to promote women in health IT. She served as a moderator and has an extensive background with pricing. They have promoted women in Health IT in the Utah area, including providing student scholarships for their Healthcare Analytics Summit in September.  A key question that Holly has focused on is “Are we making a difference in both quality and costs?”  “Does it translate into cost savings for those that are paying?” Part of her work involves bringing data sources together (clinical, financial, claims, etc.) to create transparency to services and care being provided and at what cost.  Over the last 6 years, Holly has been involved in developing a more accurate activity-based costing system. Accurate costing leads to more accurate pricing and more accurate pricing leads to improved price transparency. I am looking forward to learning more about what Health Catalyst does for improving Healthcare IT in Utah.

Norm Thurston is a Utah State Representative and I was surprised how much I enjoyed his presentation and I will tell you why. Norm Thurston has a background in statistics and I felt confident that the Utah legislature was getting good information about improving healthcare. Representative Thurston spoke about the availability of state data to see things like prescribing trends and billing trends among physicians. He asked Bob White about upcoding- and how the government of Utah looks at billing data to make that information more transparent for payers and providers. The checks and balances of legislators asking about trends based on data aren’t something I see every day in healthcare. Data backed inquiry can improve prescribing. Utah has had a decrease in opioid deaths in the last year, and the healthcare system and state efforts have actively used data to improve the numbers. Utah has historically been a state with a problem and has actively worked to improve rates of opioid deaths. One of the audience comments that I enjoyed was a question from Todd Allen, MD about how they evaluate the statistical significance of prescribing and billing differences. How do we know if using this drug or billing code 75% of the time has better outcomes that in the hospital where it is used less than 65% of the time? Having visibility and data is part of the equation for improving healthcare outcomes, and another part is interpreting the data and deciding best practices.

Problems We Need To Address Before Healthcare AI Becomes A Thing

Posted on September 7, 2018 I Written By

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

Just about everybody who’s anybody in health IT is paying close attention to the emergence of healthcare AI, and the hype cycle is in full swing. It’d be easier to tell you what proposals I haven’t seen for healthcare AI use than those I have.

Of course, just because a technology is hot and people are going crazy over it doesn’t mean they’re wrong about its potential. Enthusiasm doesn’t equal irrational exuberance. That being said, it doesn’t hurt to check in on the realities of healthcare AI adoption. Here are some issues I’m seeing surface over and over again, below.

The black box

It’s hard to argue that healthcare AI can make good “decisions” when presented with the right data in the right volume. In fact, it can make them at lightning speed, taking details into account which might not have seemed important to human eyes. And on a high level, that’s exactly what it’s supposed to do.

The problem with this, though, is that this process may end up bypassing physicians. As things stand, healthcare AI technology is seldom designed to show how it reached its conclusions, and it may be due to completely unexpected factors. If clinical teams want to know how the artificial intelligence engine drew a conclusion, they may have to ask their IT department to dig into the system and find out. Such a lack of transparency won’t work over the long term.

Workflow

Many healthcare organizations have tweaked their EHR workflow into near-perfect shape over time. Clinicians are largely satisfied with work patterns and patient throughput is reasonable. Documentation processes seem to be in shape. Does it make sense to throw an AI monkeywrench into the mix? The answer definitely isn’t an unqualified yes.

In some situations, it may make sense for a provider to run a limited test of AI technology aimed at solving a specific problem, such as assisting radiologists with breast cancer scan interpretations. Taking this approach may create less workflow disruption. However, even a smaller test may call for a big investment of time and effort, as there aren’t exactly a ton of best practices available yet for optimizing AI implementations, so workflow adjustments might not get enough attention. This is no small concern.

Data

Before an AI can do anything, it needs to chew on a lot of relevant clinical data. In theory, this shouldn’t be an issue, as most organizations have all of the digital data they need.  If you need millions of care datapoints or several thousand images, they’re likely to be available. The thing is, they may not be as usable as one might hope.

While healthcare providers may have an embarrassment of data on hand, much of it is difficult to filter and mine. For example, while researchers and some isolated providers are using natural language processing to dig up useful information, critics point out that until more healthcare info is indexed and tagged there’s only so much it can do. It may take a new generation of data processing and indexing tech to prepare the data before we have the right data to feed an AI.

These are just a few practical issues likely to arise as providers begin to use AI technologies; I’m sure there are many others you might be able to name. While I have little doubt we can work our way through such issues, they aren’t trivial, and it could take a while before we have standardized approaches in place for addressing them. In the meantime, it’s probably a good idea to experiment with AI projects and prepare for the day when it becomes more practical.

Health IT Consulting Demand To Explode This Year

Posted on August 24, 2018 I Written By

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

As payment models shift from fee-for-service to value-based care, hospitals are having to adopt new technologies and tweak existing ones. The thing is, it takes a mighty team of IT pros to make all this happen. In some cases, a provider has enough resources to handle this kind of big transition, but most need some help, especially when they’re handling major infrastructure improvements or even switching out technologies.

This seems to be at least part of what’s driving a dramatic increase in spending on health IT consulting, according to a new study from Black Book Research. The study drew on input from 1,586 professionals with knowledge of the US health IT industry.

Black Book concluded that health IT management consulting spending has grown from $20 billion in 2016 to $45 billion last year. Not only that, the firm expects to see this number climb to nearly $53 billion for 2018. That’s a massive increase, particularly given that providers were already spending heavily on consultants as they beat their enterprise EHRs into shape.

According to the analyst firm, 64% of last year’s spending paid for implementation of software, information systems, systems integration and optimization and support for mergers and acquisitions. This summary covers a lot of ground, but it’s hardly surprising given the drastic changes underway.

Going forward, respondents expect three key forces to drive healthcare consulting spend, including a lack of highly-skilled IT professionals (cited by 81% of respondents), adoption of cloud technology in healthcare (74%) and growing industry digitalization (71%). (I’d also expect to see investment in new organizational infrastructures — for, let’s say, ACOs)  — will continue to increase in importance as well.)

Providers responding to the study said that they expect to hire health IT consultants for EHR and RCM system optimization (61%) and to offer expertise in software training and implementation (46%) next year. Other areas providers hope to address include value-based care (39%), cloud infrastructure (36%), compliance issues (33%) and a grab bag of big data, decision support and analytics projects (31%).

The vast majority of respondents (84%) said they expect to enter into a wide range of consulting agreements to include work with single-shop consultants, single freelancers, group purchasing organizations, HIT vendors, networks of freelancers, boutique advisory firms and traditional major consultancies, Black Book reported. In other words, it’s all hands on deck!

Clinicians Say They Need Specialized IT To Improve Patient Safety

Posted on July 24, 2018 I Written By

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

Hospitals are loaded down with the latest in health IT and have the bills to prove it. But according to a new survey, they need to invest in specialized technologies to meet patient safety goals, as well as providing more resources and greater organizational focus.

Health Catalyst recently conducted a national survey of physicians, nurses and health executives to gather their thoughts on patient safety issues. Among its main findings was that almost 90% of respondents said that their organizations were seeing success in improving patient safety. However, about the same percentage said there was room for improving patient safety in their organization.

The top obstacle they cited as holding them back from the patient safety goals was having effective information technology, as identified by 30% of respondents. The same number named a lack of technologies offering real-time warnings of possible patient harm.

These were followed by lack of staffing and budget resources (27%), organizational structure, culture priorities (19%), a lack of reimbursement for safety initiatives (10%) and changes in patient population practice setting (9%).

Part of the reason clinicians aren’t getting as much as they’d like from health IT is that many healthcare organizations rely largely on manual methods to track and report safety events.

The top sources of data for patient safety initiatives respondents used for safety initiatives voluntary reporting (82%). Hospital-acquired infection surveys (67%), manual audits (58%) and retrospective coding (29%). Such reporting is typically based on data sets which are at least 30 days old, and what’s more, collecting and analyzing the data can be time and resource-consuming.

Not surprisingly, Health Catalyst is launching new technology designed to address these problems. Its Patient Safety Monitor™ Suite: Surveillance Module uses protective and text analytics, along with concurrent critical reviews of data, to find and prevent patient safety threats before they result in harm.

The announcement also falls in line with the organization’s larger strategic plans, as Health Catalyst has applied to the AHRQ to be certified as a Patient Safety Organization.

The company said that he had spent more than $50 million to create the Surveillance module, whose technology includes the use of predictive analytics models and AI. It expects to add new AI and machine learning capabilities to its technology in the future which will be used to propose strategies to eliminate patient safety risks.

And more is on the way. Health Catalyst is working with its clients to add new features to the Suite including risk prediction, improvement tracking and decision support.

I’m not sure if it’s typical for PSOs to bringing their own specialized software to the job, but either way, it should give Health Catalyst a leg up. I have little doubt that doing better predictive analytics and offering process recommendations would be useful.