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HIMSS Study Shows IT Pay Gaps Persist Between Genders, Races

Posted on March 14, 2018 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

It would be nice to think that, in a profession focusing on hard, measurable skills, that given the same experience level and skill set, HIT staffers would make more or less the same salaries. However, that doesn’t seem to be the case, according to data from the latest health IT compensation study by HIMSS.

Researchers found that as of previous years, race and gender seem to play a significant role in how much a health IT professional is paid. According to the study, females make 18% less than their male peers, and minorities make 12% less than non-minorities on average across all positions and number of years in a given position.

As the level of responsibility grows, the gap in pay seems to increase as well. The study found that women in executive roles actually face a larger salary gap versus their male counterparts than women at other levels in their organization. Moreover, that gap is growing. Meanwhile, minority females are particularly hard-hit, with the lowest average salaries of the four combinations of gender and racial groups studied, HIMSS reports.

Overall, respondents working in digital health reported being moderately satisfied with the current base salaries, while non-white respondents tended to be less satisfied than respondents who defined themselves as white.

Oddly, despite the substantial pay gap between them and their male peers, females in digital health appeared to be just as satisfied with their pay as their male peers. HIMSS researchers speculate that the reason women are satisfied with lower pay is that they simply don’t know they’re being under compensated. (Given my experience as a professional female, I’d also speculate that some women simply get tired of fighting to close the pay gap and make peace with what they’ve got.)

Having summed all of this up, HIMSS researchers made a few recommendations as to how health organizations can address pay gaps, such as accepting that these gaps exist, educating managers and why gender and racial equality is good for business and adopting strategies that help to reduce such disparities. The researchers also suggest making tools available that can help all health IT professionals understand what they’re worth and negotiate fair pay agreements.

As for me, I’d go a bit further. I’d argue that professionals whose gender and/or minority status have impacted their pay should speak out. It’s all well and good to have provider organizations recognize that their pay structure may not be fair and take action. But ultimately, drawing attention to these gaps both within and outside of the healthcare industry may have the biggest long-term effect.

New Study Suggests That HIEs Deliver Value by Aggregating Patient Data

Posted on March 5, 2018 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

Historically, I’ve been pretty skeptical about the benefits that HIEs offer, not because the concept was flawed, but that the execution was uncertain. Toss in the fact that few have figured out how to be self-supporting financially, and you have a very shaky business model on your hands. But maybe, at long last, we’re discovering better uses for the vast amount of data HIEs have been trading.

New research by one exchange suggests that some of the key value they offer is aggregating patient data from multiple providers into a longitudinal view of patients. The research, completed by the Kansas Health Information Network and Diameter Health suggests that the Qualified Clinical Data Registries promoted by MACRA/QPP could be a winning approach.

To conduct the research, the partners extracted data from the KHIN exchange on primary care practices in which more than 50,000 patients visited toward 214 care sites in 2016 and 2017. This is certainly interesting, as most of the multi-site studies I’ve seen on this scale are done within a single provider’s network. It’s also notable that the data is relatively fresh, rather than relying on, say, Medicare data which is often several years older.

According to KHIN, using interoperable interfaces to providers and collecting near real-time clinical data makes prompt quality measure calculation possible. According to KHIN executive director Laura McCrary, Ed.D., this marks a significant change from current methods. “This [approach is in stark contrast to the current model which computes quality measures from only the data in the provider’s EHR,” she notes.

FWIW, the two research partners will be delivering a presentation on the research study at the HIMSS18 conference on Friday, March 9, from 12 to 1 PM. I’m betting it will offer some interesting insights.

But even if you can’t make it to this presentation, it’s still worth noting that it emphasizes the increasing importance of the longitudinal patient record. Eventually, under value-based care, it will become critical to have access not only to a single provider’s EHR data, but rather a fuller data set which also includes connected health/wearables data, data from payer claims, overarching population health data and more. And obviously, HIEs play a major role in making this happen.

Like other pundits, I’d go so far to say that without developing this kind of robust longitudinal patient record, which includes virtually every source of relevant patient data, health systems and providers won’t be able to manage patients well enough to meet their individual patient or population health goals.

If HIEs can help us get there, more power to them.

Nokia May Exit Digital Health Business

Posted on March 2, 2018 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

The digital health market has become phenomenally competitive over the last few years, with giants like Google and Apple duking it out with smaller, fast-moving startups over the choicest opportunities in the sector.

Even with a behemoth like Google, you expect to see some stumbles, and the Internet giant has taken a few. But seldom have we seen a billion-dollar company walk away from the digital health market, which arguably stands to grow far more. Still, according to a recent news report, that’s just what Nokia may be doing.

A story published in The Verge reports that the Finnish telecom giant has launched a strategic review of its health division. While Nokia apparently isn’t spilling the beans on its plans, the news site got a look at an internal company memo which suggests that its digital health business is indeed in trouble.

In the memo, The Verge says, Nokia chief strategy officer Kathrin Buvac wrote that “our digital health business has struggled to scale and meet its growth expectations… [And] currently, we don’t see a path for [the digital health business] to become a meaningful part of a company as large as Nokia.”

While it’s hard to tell much from a press release, it notes that Nokia’s digital health division makes and sells an ecosystem of hybrid smart watches, scales and digital health devices to consumers and enterprises. Its digital health history includes the acquisition of Withings, a French startup with a sexy line up of connected health-focused digital health devices.

This may be in part because it just hasn’t been aggressive enough or offered anything unique. In the wake of the Withings acquisition, Nokia doesn’t seem to have done much to build on Withings’ product line. Though much of the success in this market depends on execution, its current roster of products doesn’t sound like anything too exciting or differentiated.

It’s interesting to note that Buvac blames at least part of the failure of its digital health excursion on Nokia’s size. That doesn’t seem to be a problem for industry-leading companies like Apple, which seems to be carving out its digital health footprint one launch at a time and cultivating health leaders along the way. For example, Apple recently partnered with Stanford Medicine launch an app using its smartwatch to collect data on irregular heart rhythms. Arguably, this is the way to win markets and influence people — slow and steady.

In the end, though, Buvac is probably right about is digital health prospects. Nokia’s seeming failure may indeed be attributed to its sprawling portfolio, and probably an inflexible internal culture as well. The moral of the story may be that winning at the digital health game has far more to do with understanding the market than it does with having very deep pockets.

Some Of The Questions I Plan To Ask At #HIMSS18

Posted on February 23, 2018 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

As always, this year’s HIMSS event will feature enough noise, sound and color to overwhelm your senses for months afterward. And talk about a big space to tread — I’ve come away with blisters more than once after attending.

Nonetheless, in my book it’s always worth attending the show. While no one vendor or session might blow you away, finding out directly what trends and products generated the most buzz is always good. The key is not only to attend the right educational sessions or meet the right people but to figure out how companies are making decisions.

Below, here are some of the questions that I hope to ask (and hopefully find answers) at the show. If you have other questions to suggest I’d love to bring them with me to the show —  the way I see it, the more the merrier!



Vendors:  What functions does blockchain perform in your solution and what are the benefits of these additions? What made that blockchain the best technology choice for getting the job done? What challenges have you faced in developing a platform that integrates blockchain technology, and how are you addressing them? Is blockchain the most cost-efficient way of accomplishing the task you have in mind? What problems is blockchain best suited to address?

Providers: Have you rolled out any blockchain-based systems? If you haven’t currently deployed blockchain technology, do you expect to do so the future? When do you think that will happen? How will you know when it’s time to do so? What benefits do you think it will offer to your organization, and why? Do you think blockchain implementations could generate a significant level of additional server infrastructure overhead?


Vendors: What makes your approach to healthcare AI unique and/or beneficial?  What is involved in integrating your AI product or service with existing provider technology, and how long does it usually take? Do providers have to do this themselves or do you help? Did you develop your own algorithms, license your AI engine or partner with someone else deliver it? Can you share any examples of how your customers have benefited by using AI?

Providers: What potential do you think AI has to change the way you deliver care? What specific benefits can AI offer your organization? Do you think healthcare AI applications are maturing, and if not how will you know when they have? What types of AI applications potentially interest you, and are you pilot-testing any of them?


Vendors:  How does your solution overcome barriers still remaining to full health data sharing between all healthcare industry participants? What do you think are the biggest interoperability challenges the industry faces? Does your solution require providers to make any significant changes to their infrastructure or call for advanced integration with existing systems? How long does it typically take for customers to go live with your interoperability solution, and how much does it cost on average? In an ideal world, what would interoperability between health data partners look like?

Providers: Do you consider yourself to have achieved full, partial or little/no health data interoperability between you and your partners? Are you happy with the results you’ve gotten from your interoperability efforts to date? What are the biggest benefits you’ve seen from achieving full or partial interoperability with other providers? Have you experienced any major failures in rolling out interoperability? If so, what damage did they do if any? Do you think interoperability is a prerequisite to delivering value-based care and/or population health management?

What topics are you looking forward to hearing about at #HIMSS18? What questions would you like asked? Share them in the comments and I’ll see what I can do to find answers.

Radiology Centers Poised To Adopt Machine Learning

Posted on February 8, 2018 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

As with most other sectors of the healthcare industry, it seems likely that radiology will be transformed by the application of AI technologies. Of course, given the euphoric buzz around AI it’s hard to separate talk from concrete results. Also, it’s not clear who’s going to pay for AI adoption in radiology and where it is best used. But clearly, AI use in healthcare isn’t going away.

This notion is underscored by a new study by Reaction Data suggesting that both technology vendors and radiology leaders believe that widespread use of AI in radiology is imminent. The researchers argue that radiology AI applications are a “have to have” rather than a novel experiment, though survey respondents seem a little less enthusiastic.

The study, which included 133 respondents, focused on the use of machine learning in radiology. Researchers connected with a variety of relevant professionals, including directors of radiology, radiologists, techs, chiefs of radiology and PACS administrators.

It’s worth noting that the survey population was a bit lopsided. For example, 45% of respondents were PACS admins, while the rest of the respondent types represented less than 10%. Also, 90% of respondents were affiliated with hospital radiology centers. Still, the results offer an interesting picture of how participants in the radiology business are looking at machine learning.

When asked how important machine learning was for the future of radiology, one-quarter of respondents said that it was extremely important, and another 59% said it was very or somewhat important. When the data was sorted by job titles, it showed that roughly 90% of imaging directors said that machine learning would prove very important to radiology, followed by just over 75% of radiology chiefs. Radiology managers both came in at around 60%. Clearly, the majority of radiology leaders surveyed see a future here.

About 90% of radiology chiefs were extremely familiar with machine learning, and 75% of techs. A bit counterintuitively, less than 10% of PACS administrators reported being that familiar with this technology, though this does follow from the previous results indicating that only half were enthused about machine learning’s importance. Meanwhile, 75% of techs in roughly 60% of radiologists were extremely familiar with machine learning.

All of this is fine, but adoption is where the rubber meets the road. Reaction Data found that 15% of respondents said they’d been using machine learning for a while and 8% said they’d just gotten started.

Many more centers were preparing to jump in. Twelve percent reported that they were planning on adopting machine learning within the next 12 months, 26% of respondents said they were 1 to 2 years away from adoption and another 24% said they were 3+ years out.  Just 16% said they don’t think they’ll ever use machine learning in their radiology center.

For those who do plan to implement machine learning, top uses include analyzing lung imaging (66%), chest x-rays (62%), breast imaging (62%), bone imaging (41%) and cardiovascular imaging (38%). Meanwhile, among those who are actually using machine learning in radiology, breast imaging is by far the most common use, with 75% of respondents saying they used it in this case.

Clearly, applying the use of machine learning or other AI technologies will be tricky in any sector of medicine. However, if the survey results are any indication, the bulk of radiology centers are prepared to give it a shot.

Nearly 6 Million Patient Records Breached In 2017

Posted on February 1, 2018 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

Just how bad a year was 2017 for health data? According to one study, it was 5.6 million patient records bad.

According to health data security firm Protenus, which partnered with to conduct its research, last year saw an average of at least one health data breach per day. The researchers based their analysis on 477 health data breaches reported to the public last year.

While Protenus only had 407 such incidents, those alone affected 5,579,438 patient records. The gross number of exposed records fell dramatically from 2016, which saw 27.3 million records compromised by breaches. However, the large number of records exposed in 2016 stems from the fact that there were a few massive incidents that year.

According to researchers, the largest breach reported in 2017 stemmed from a rogue insider, a hospital employee who inappropriately accessed billing information on 697,800 patients. The rest of the top 10 largest data breaches sprung from insider errors, hacking, and one other incident involving insider wrongdoing.

Insider wrongdoing seems to be a particular problem, accounting for 37% of the total number of breaches last year. These insider incidents affected 30% of compromised patient data, or more than 1.7 million records.

As bad as those stats may be, however, ransomware and malware seem to be even bigger threats. As the study notes, last year a tidal wave of hacking incidents involving malware and ransomware hit healthcare organizations.

Not surprisingly, last year’s wave of attacks seems to be part of a larger trend. According to a Malwarebytes report, ransomware attacks on businesses overall increased 90 percent last year, led by GlobeImposter and WannaCry incidents.

That being said, healthcare appears to be a particularly popular target for cybercriminals. In 2016, healthcare organizations reported 30 incidents of ransomware and malware attacks, and last year, 64 organizations reported attacks of this kind. While the increase in ransomware reports could be due to organizations being more careful about reporting such incidents, researchers warn that the volume of such attacks may be growing.

So what does this suggest about the threat landscape going forward?  In short, it doesn’t seem likely the situation will improve much over the next 12 months. The report suggests that last year’s trend of one breach per day should continue this year. Moreover, we may see a growth in the number of incidents reported to HHS, though again, this could be because the industry is getting better at breach detection.

If nothing else, one might hope that healthcare organizations get better at detecting attacks quickly. Researchers noted that of the 144 healthcare data breaches for which they have data, it took an average of 308 days for the organization to find out about the breach. Surely we can do better than this.

Federal Advisors Say Yes, AI Can Change Healthcare

Posted on January 26, 2018 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

The use of AI in healthcare has been the subject of scores of articles and endless debate among industry professionals over its benefits. The fragile consensus seems to be that while AI certainly has the potential to accomplish great things, it’s not ready for prime time.

That being said, some well-informed healthcare observers disagree. In an ONC blog post, a collection of thought leaders from the agency, AHRQ and the Robert Wood Johnson Foundation believe that over the long-term, AI could play an important role in the future of healthcare.

The group of institutions asked JASON, an independent group of scientists and academics who advise the federal government on science and technology issues, to look at AI’s potential. JASON’s job was to look at the technical capabilities, limitations and applications for AI in healthcare over the next 10 years.

In its report, JASON concluded that AI has broad potential for sparking significant advances in the industry and that the time may be right for using AI in healthcare settings.

Why is now a good time to play AI in healthcare? JASON offers a list of reasons, including:

  • Frustration with existing medical systems
  • Universal use of network smart devices by the public
  • Acceptance of at-home services provided by companies like Amazon

But there’s more to consider. While the above conditions are necessary, they’re not enough to support an AI revolution in healthcare on their own, the researchers say. “Without access to high-quality, reliable data, the problems that AI will not be realized,” JASON’s report concludes.

The report notes that while we have access to a flood of digital health data which could fuel clinical applications, it will be important to address the quality of that data. There are also questions about how health data can be integrated into new tools. In addition, it will be important to make sure the data is accessible, and that data repositories maintain patient privacy and are protected by strong security measures, the group warns.

Going forward, JASON recommends the following steps to support AI applications:

  • Capturing health data from smartphones
  • Integrating social and environmental factors into the data mix
  • Supporting AI technology development competitions

According to the blog post, ONC and AHRQ plan to work with other agencies within HHS to identify opportunities. For example, the FDA is likely to look at ways to use AI to improve biomedical research, medical care and outcomes, as well as how it could support emerging technologies focused on precision medicine.

And in the future, the possibilities are even more exciting. If JASON is right, the more researchers study AI applications, the more worthwhile options they’ll find.

UPMC Sells Oncology Analytics Firm To Elsevier

Posted on January 22, 2018 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

Using analytics tools to improve cancer treatment can be very hard. That struggle is exemplified by the problems faced by IBM Watson Health, which dove into the oncology analytics field a few years ago but made virtually no progress in improving cancer treatment.

With any luck, however, Via Oncology will be more successful at moving the needle in cancer care. The company, which offers decision support for cancer treatment and best practices in cancer care management, was just acquired by information analytics firm Elsevier, which plans to leverage the company’s technology to support its healthcare business.

Elsevier’s Clinical Solutions group works to improve patient outcomes, reduce clinical errors and optimize cost and reimbursements for providers. Via Oncology, a former subsidiary of the University of Pittsburgh Medical Center, develops and implements clinical pathways for cancer care. Via Oncology spent more than 15 years as part of UPMC prior to the acquisition.

Via Oncology’s Via Pathways tool relies on evidence-based content to create clinical algorithms covering 95% of cancer types treated in the US. The content was developed by oncologists. In addition to serving as a basis for algorithm development, Via Oncology also shares the content with physicians and their staff through its Via Portal, a decision support tool which integrates with provider EMRs.

According to Elsevier, Via Pathways addresses more than 2,000 unique patient presentations which can be addressed by clinical algorithms and recommendations for all major aspects of cancer care. The system can also offer nurse triage and symptom tracking, cost information analytics, quality reporting and medical home tools for cancer centers.

According to the prepared statement issued by Elsevier, UPMC will continue to be a Via Oncology customer, which makes it clear that the healthcare giant wasn’t dumping its subsidiary or selling it for a fire sale price.

That’s probably because in addition to UPMC, more than 1,500 oncology providers and community, hospital and academic settings hold Via Pathways licenses. What makes this model particularly neat is that these cancer centers are working collaboratively to improve the product as they use it. Too few specialty treatment professionals work together this effectively, so it’s good to see Via Oncology leveraging user knowledge this way.

While most of this seems clear, I was left with the question of what role, if any, genomics plays in Via Oncology’s strategy. While it may be working with such technologies behind the scenes, the company didn’t mention any such initiatives in its publicly-available information.

This approach seems to fly in the face of existing trends and in particular, physician expectations. For example, a recent survey of oncologists by medical publication Medscape found that 71% of respondents felt genomic testing was either very important or extremely important to their field.

However, Via Oncology may have something up its sleeve and is waiting for it to be mature before it dives into the genomics pool. We’ll just have to see what it does as part of Elsevier.

Are there other areas beyond cancer where a similar approach could be taken?

Health IT and ROI (Release of Information) Vendor Sues HHS Over Patient Records Fees

Posted on January 19, 2018 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

Now here’s one for the ages – a vendor taking HHS head-on. The vendor, CIOX Health, has sued HHS in an effort to stop the agency from enforcing HIPAA rules limiting how much providers and business associates can charge patient records. While the vendor may not get anywhere, the lawsuit raises the important question of what patient record retrieval should cost.

According to Becker’s Hospital Review, the suit focuses on changes to the privacy law put into place in 2013 and 2016. The article notes that these modifications broadened the type of information providers and BAs must send while capping the fees vendors could charge for doing so. Specifically, the changes made in 2016 require that vendors that the costs associated with record requests for a reasonable or flat rate of about $6.50.

In its complaint, CIOX says the flat fee “was drawn from thin air and bears no rational relationship to the actual costs associated with processing such requests.” It contends that the HIPAA provisions in question established the limits “unlawfully, unreasonably, arbitrarily and capriciously.”

It’s hard to tell whether CIOX will get anywhere (though my guess is “not very far”). Government agencies are all but immovable, and HHS particularly so. I appreciate the spunk involved in filing the suit, the premise of which actually sounds reasonable to me, but I think the company has about as much chance of prevailing as a gnat fighting a combine harvester.

That being said, I think this suit focuses on an important issue, which is that the fee limits imposed by states and the federal government for providing medical records are all over the map. While such limits may be necessary to protect consumers, it’s probably fair to say that they aren’t exactly based on actual estimates of provider and vendor costs.

The truth is, the healthcare industry hasn’t come to grips yet with the cost of delivering healthcare information to patients. After all, while basic information delivered by a portal may be good enough for patients, these aren’t real medical records and they can’t be used as a basis for care.  And delivering an entire medical record can be expensive.

Plus, this issue is really complicated by the number of records requests that healthcare organizations are receiving from parties other than the patient. The number of records request from insurance companies, lawyers, and other third parties has increased dramatically. Not to mention how much of the record these organizations want to get. If it were just patients requesting their records, this question would be much simpler.

I can only think of a few ways to handle this problem, none of which are really satisfactory. For example, HHS or the states could create some sort of system which permits different fees depending on the difficulty of retrieving the information. Providers and business associates could submit their fees to some kind of review board which would approve or reject the proposal. Or perhaps we could just allow vendors to charge whatever the market would bear. None of these sound great to me.

If we want patients to manage their health effectively, they need to be able to share their records, and they must be able to access those records without paying a fortune for the privilege. At the same time, we can’t ask providers and business associates to share records at their own expense. Given the importance of this problem, I think it’s high time that healthcare leaders look for solutions.

Hospitals Still Lagging On Mobile

Posted on January 18, 2018 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

One would think that these days, when the desktop computer is an extension of mobile devices rather than the other way around, hospitals would have well-defined, mature plans in place for managing mobile technology. But according to one survey, that’s definitely not the case.

In a study sponsored by Spok, which provides clinical communication services, many healthcare providers are still in the early years of developing a mobile strategy.

The study, which drew on contacts with more than 300 healthcare professionals in the US, found that 21% had had a mobile strategy in place for less than one year, 40% for one to three years,14% for 3 to 5 years and 25% for more than five years. In other words, while one-quarter of organizations had settled in and developed a mobile approach, an almost equal amount were just getting their feet wet.

Not only that, many of those who do have a mobile strategy in place may be shooting from the hip. While 65% of those surveyed had a documented mobility strategy in place, 35% didn’t.

That being said, it seems that organizations that have engaged with mobile are working hard to tweak their strategy regularly. According to Spok, their reasons for updating the strategy include:

* Shifting mobile needs of end-users (44%)
* The availability of new mobile devices (35%)
* New capabilities from the EHR vendor (26%)
* Changes in goals of mobile strategy (23%)
* Challenges in implementing the strategy (21%)
* Changes in hospital leadership (16%)

(Seven percent said their mobile strategy had not changed since inception, and 23% weren’t sure what changes had been made.)

Nonetheless, other data suggest there has been little progress in integrating mobile strategy with broader hospital goals.

For example, while 53% wanted to improve physician-to-physician communications, only 19% had integrated mobile strategy with this goal. Fifty-three percent saw nurse-to-physician communications as a key goal, but only 18% had integrated this goal with their mobile plans. The gaps between other top strategies and integration with mobile plans were similar across the strategic spectrum.

Ultimately, it’s likely that it will take a team approach to bring these objectives together, but that’s not happening in the near future. According to respondents, the IT department will implement mobile in 82% of institutions surveyed, 60% clinical leadership, 37% doctors, 34% telecom department, 27% nurses and 22% outside help from consultants and vendors. (Another 16% didn’t plan to have a dedicated team in place.)

The whole picture suggests that while the hospital industry is gradually moving towards integrating mobile into its long-term thinking, it has a ways to go. Given the potential benefits of smart mobile use, let’s hope providers catch up quickly.