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ONC To Farm Out Certification Testing To Private Sector – MACRA Monday

Posted on August 14, 2017 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 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. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

This post is part of the MACRA Monday series of blog posts where we dive into the details of the MACRA Quality Payment Program (QPP) and related topics.

EHR certification has been a big part of the meaningful use program and is now part of MACRA as well. After several years of using health IT certification testing tools developed by government organizations, the ONC has announced plans to turn the development of these tools over to the private sector.

Since its inception, ONC has managed its health IT’s education program internally, developing automated tools designed to measure health IT can compliance with certification requirements in partnership with the CDC, CMS and NIST. However, in a new blog post, Office of Standards and Technology director Steven Posnack just announced that ONC would be transitioning development of these tools to private industry over the next five years.

In the post, Posnack said that farming out tool development would bring diversity to certification effort and help it perform optimally. “We have set a goal…to include as many industry-developed and maintained testing tools as possible in lieu of taxpayer financed testing tools,” Posnack wrote. “Achieving this goal will enable the Program to more efficiently focus its testing resources and better aligned with industry-developed testing tools.”

Readers, I don’t have any insider information on this, but I have to think this transition was spurred (or at least sped up) by the eClinicalWorks certification debacle.  As we reported earlier this year, eCW settled a whistleblower lawsuit for $155 million a few months ago;  in the suit, the federal government asserted that the vendor had gotten its EHR certified by faking its capabilities. Of course the potential cuts to ONC’s budget could have spurred this as well.

I have no reason to believe that eCW was able to beat the system because ONC’s certification testing tools were inadequate. As we all know, any tool can be tricked if you throw the right people at the problem. On the other hand, it can’t hurt to turn tool development over to the private sector. Of course, I’m not suggesting that government coders are less skilled than private industry folks (and after all, lots of government technology work is done by private contractors), but perhaps the rhythms of private industry are better suited to this task.

It’s worth noting that this change is not just cosmetic. Poznack notes that with private industry at the helm, vendors may need to enter into new business arrangements and assume new fees depending on who has invested in the testing tools, what it costs to administer them and how the tools are used.

However, I’d be surprised if private sector companies that develop certification arrangements will stay tremendously far from the existing model. Health IT vendors may want to get their products certified, but they’re likely to push back hard if private companies jack up the price for being evaluated or create business structures that don’t work.

Honestly, I’d like to see the ONC stay on this path. I think it works best as a sort of think tank focused on finding best practices health IT companies across government and private industry, rather than sweating the smaller stuff as it has in recent times. Otherwise, it’s going to stay bogged down in detail and lose whatever thought leadership position it may have.

The Sexiest Data in Health IT: Datapalooza 2017

Posted on May 15, 2017 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

The data at this conference was the Best Data. The Biggest Data. No one has better data than this conference.

The sexiest data in all of healthIT was highlighted in Washington DC at Datapalooza April 27-28, 2017.  One of the main themes was how to deal with social determinants of health and the value of that data.  Sachin H. Jain, MD of Caremore Health reminded us that “If a patient doesn’t have food at home waiting for them they won’t get better” social data needs to be in the equation. Some of the chatter on the subject of healthcare reform has been criticism that providing mandatory coverage hasn’t always been paired with knowledge of the area. If a patient qualifies for Medicaid and has a lower paying job how can they afford to miss work and get care for their health issues?
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Rural areas also have access issues. Patient “Charles” works full time during the week and qualifies for Medicaid. He can’t afford to miss a lot of work but needs a half a day to get treatments which affect his ability to work. There is no public transportation in his town to the hospital in a city an hour and a half away. Charles can’t afford the gas or unpaid time off work for his treatment.

Urban patient “Haley” returns to her local ER department more than once a week with Asthma attacks.  Her treatments are failing because she lives in an apartment with mold in the walls. As Craig Kartchner from the Intermountain Healthcare team responded to the #datapalooza  hashtag online- These can be the most difficult things to change.

The 2016 report to Congress addresses the difficulty of the intersection between social factors and providing quality healthcare in terms of Social Determinants of Health:

“If beneficiaries with social risk factors have worse health outcomes because the providers they see provide low quality care, value based purchasing could be a powerful tool to drive improvements in care and reduce health disparities. However, if beneficiaries with social risk factors have worse health outcomes because of elements beyond the quality of care provided, such as the social risk factors themselves, value based payment models could do just the opposite. If providers have limited ability to influence health outcomes for beneficiaries with social risk factors, they may become reluctant to care for beneficiaries with social risk factors, out of fear of incurring penalties due to factors they have limited ability to influence.”

Innovaccer just launched a free tool to help care teams track and monitor Medicare advantage plans. I went to their website and looked at my county and found data about the strengths in Salt Lake where I’m located. They included:

  • Low prevalence of smoking
  • Low Unemployed Percentage
  • Low prevalence of physically inactive adults

Challenges for my area?

  • Low graduation rate
  • High average of daily Air pollution
  • High income inequality
  • High Violent crime rate per 100,000 population

Salt Lake actually has some really bad inversion problems during the winter months and some days the particulate matter in the air creates problems for respiratory problems. During the 2016-2017 winter there were 18 days of red air quality and 28 days of yellow air quality. A smart solution for addressing social determinants of health that negatively impact patients in this area could be addressing decreasing air pollution through increased public transportation. Healthcare systems will see an increase in cost of care during those times and long term population health challenges can emerge. You can look at your county after you enter your email address on their site. This kind of social data visualization can give high level insights into the social factors your population faces.

One of the themes of HealthDataPalooza was how to use system change to navigate the intersection between taking care of patients and not finding way to exclude groups. During his panel discussion of predictive analytics, Craig Monson the medical director for analytics and reporting discussed how “data analytics is the shiny new toy of healthcare.”    In addition to winning the unofficial datapalooza award for the most quotes and one liners – Craig presented the Clinical Risk Prediction Initiative (CRISPI).  This is a multi variable logistic regression model with data from the Atrius health data warehouse. His questions for systems to remember in their data analysis selection are “Who is the population you are serving? What is the outcome you need? What is the intervention you should implement?”

Warning- Craig reminds us that in a world of increasing sexy artificial intelligence coding a lot of the value analysis can be done with regression. Based on that statement alone I think he can be trusted. I still need to see his data.

CRISPI analyzed the relative utility of certain types of data, and didn’t have a large jump in utility when adding Social Determinant Data. This data was one of the most popular data sets during Datapalooza discussions but the reality of making actionable insights into system improvement? Craig’s analysis said it was lacking. Does this mean social determinant data isn’t significant or that it needs to be handled with a combination of traditional modeling and other methods?  Craig’s assertion seemed to fly in the face of the hot new trend of Social Determinants of Health data from the surface.

Do we have too much data or the wrong use of the data? Most of the companies investing into this space used data sources outside the traditional definition to help create solutions with social determinate of health and Patient outcomes. They differed in how they analyzed social determinant data. Traditional data sources for the social determinants of health are well defined within the public health research.  The conditions in which you work and live impact your health.

Datapalooza had some of the greatest minds in data analytics and speakers addressed gaps in data usefulness. Knowing that a certain large county wide population has a problem with air quality might not be enough to improve patient outcomes. There is need for analysis of traditional data sources in this realm and how they can get meaningful impact for patients and communities. Healthcare innovators need to look at different data sources.  Nick Dawson, Executive director of Johns-Hopkins Sibley Innovation Hub responded to the conversation about food at home with the data about Washington DC.  “DC like many cities has open public data on food scarcity. But it’s not part of a clinical record. The two datasets never touch.” Data about food scarcity can help hospital systems collaborate with SNAP and Government as well as local food programs. Dawson leads an innovation lab at Johns Hopkins Sibley where managers, directors, VPs and C Suite leaders are responsible for working with 4 innovation projects each year.

Audun Utengen, the Co Founder of Symplur said “There’s so much gold in the social media data if you choose to see it.” Social data available online helps providers meet patients where they are and collect valuable data.  Social media data is another source to collect data about patient preferences and interactions for reaching healthcare populations providers are trying to serve. With so much data available sorting through relevant and helpful data provides a new challenge for healthcare systems and providers.

New Data sources can be paired with a consultative model for improving the intersection of accountable care and lack of access due to social factors. We have more sophisticated analytic tools than ever for providing high value care in the intersection between provider responsibility and social collaboration. This proactive collaboration needs to occur on local and national levels.  “It’s the social determinants of health and the behavioral aspects that we need to fund and will change healthcare” we were reminded. Finding local community programs that have success and helping develop a strategy for approaching Social Determinants of Health is on the mind of healthIT professionals.

A number of companies examine data from sources such as social media and internet usage or behavioral data to design improvements for social determinants of health outcomes.   They seek to bridge the gaps mentioned by Dawson. Data sets exist that could help build programs for social determinants of health.  Mandi Bishop started Lifely Insights centered around building custom community plans with behavioral insights into social determinant data. Health in all Policies is a government initiative supporting increased structure and guidelines in these areas. They support local and State initiatives with a focus on prevention.

I’m looking forward to seeing how the data landscape evolves this year. Government Challenges such as the Healthy Behavior Data Challenge launched at Datapalooza will help fund great improvements. All the data people will get together and determine meaningful data sets for building programs addressing the social determinants of health. They will have visualization tools with Tableau. They will find ways to get food to patients at home so those patients will get better. Programs will find a way to get care to rural patients with financial difficulty and build safe housing.

From a healthcare delivery perspective the idea of collaborating about data models can help improve community health and decrease provider and payer cost. The social determinants of health can cost healthcare organizations more money than data modeling and proactive community collaboration.

Great regressions, saving money and improving outcomes?

That is Datapalooza.

Health Data Sharing Varies Widely From State To State

Posted on November 4, 2016 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 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. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

A new report from the CDC concludes that many physicians have interacted with shared health data, though only a small percentage of them had checked off all of the boxes by sending, receiving, integrating and searching for patient health data from other providers. The study also found that data sharing practices varied widely from state to state.

According to the CDC data, 38.2% of office-based physicians had sent data electronically to their peers in 2015. A nearly identical amount (39.3%) had received data, 31.1% integrated such data and 34% has searched such data from other providers.

On the other hand, physicians’ data interactions seem to have been somewhat limited. The CDC indicated that just 8.7% of office-based doctors had performed all four of these data sharing activities, a level which suggests that few are completely comfortable with such exercises.

Another striking aspect to the data was that it laid out the extent to which physicians in different states had different levels of data sharing activity.

For example, it found that in 2015, physicians fell below the national average for sending patient data in Idaho (19.4%), Connecticut (22.7%) and New Jersey (24.3%). In another anomaly, 56.3% of physicians in Arizona had sent information electronically other providers, a figure well above the 38.2% national average, with Idaho at the bottom of the range.

Meanwhile, the percentage of physicians who had received information electronically from other providers fell below the national average of 38.3% in Louisiana (23.6%), Mississippi (23.6%), Missouri (24.2%) and Alabama (24.3%). States where physicians exceeded the average for receiving information included Massachusetts (52.9%), Minnesota (55%), Oregon (59.2%) in Wisconsin (66.5%).

Where things get particularly interesting is when we look at the states were physicians had integrated electronic patient information they had received into their health data systems, a significantly more advanced step than sending or receiving data.

States that fell below the 31.1% average of physicians during such integration include Alaska (18.4%), the District of Columbia (18.6%), Montana (18.6%), Alabama (18.8%) and Idaho (20.6%). States that performed above the national average included Indiana (44.2%) and Delaware (49.3%).

Also worth noting was the diverse levels to which physicians had searched for patient health information from other providers, a data point which might suggest how much confidence they had in finding data. (Physicians who felt interoperability wasn’t serving them might not bother to search after all.)

The study found that while the average level of physicians who searched was 34%, several states fell below that average, including the District of Columbia (15.1%), Mississippi (19.7%), Pennsylvania (20.8%), Texas (21%), Missouri (21.6%) and Oklahoma (22.8%).

On the other hand, 10 states boasted a higher level physicians who searched than the national average. These included Ohio (47.2%), Alaska (47.3%, Colorado (47.5%), Maryland (47.9%), Virginia (48.3%), North Carolina (48.8%), Delaware (53.9%), Wisconsin (54.1%), Washington (58%) and Oregon (61.2%).

If it’s true that integrating and searching for data indicate higher levels of faith in the ability to use shared data, this actually looks like an encouraging report. Clearly, we have a long way to go, but substantial numbers of physicians are engaging in shared data use. To me this looks like progress.

How Complicated Is It to Simplify Medication Adherence?

Posted on November 17, 2015 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

Of all the things that irrationally inflate health costs, one of the top concerns is people who just don’t take their prescribed medications. Medication adherence doesn’t sound like a high-tech issue, but a lot of interesting technology is being thrown at the problem.

One pharmacist (obviously harboring an interest in increasing orders) estimated that we’d save 290 billion dollars a year if everybody took the medications prescribed for them. But don’t dismiss their claim as self-serving–the Centers for Disease Control suggests they may be right. It also says that half of all medications are discontinued too early. As the “fee for value” movement starts extending to the performance of medications, concerns that patients actually follow through on prescriptions will increase.

At the recent Connected Health Conference I talked to several companies taking on the difficult adherence problem from different angles. Medisafe aids patients in self-monitoring, Insightfil creates convenient packaging that groups pills the ways patients take them, and Dose doles out medication at prescribed times.

Medisafe is one of a wave of firms that address medication adherence, representing an advance over jotting down daily practices in a paper journal. These services share a good deal in common with other solutions in the marketplace that carry out patient monitoring, care planning, and the patient-centered medical home. In all these areas, services boast of tracking behavior, providing feedback to both patients and clinicians, promoting communication, and similar aspects of the connected health vision.

Medisafe handles patients’ nonadherence in multiple ways, including importing the patient’s medication list, along with vital signs such as blood pressure. Visualizations help both the patient and the doctor see the relationship between taking medication and the relevant vital signs. Patients can manage their doctor office visits or when they have been assigned a change in medication, and monitor the effects of such events on adherence through Medisafe. Finally, doctors will be able to compare data on patients within their practices, grouping them by condition, by medication taken, by demographics, or by behavior traits.

Other medication solutions try to reduce the burden of compliance that falls on the patient–or to look at it in another way, reduce the patient’s discretion. At something of an extreme, Proteus inserts a tiny radio device into each pill and makes the patient wear a patch that can detect the presence of the pill in the body. People have suggested one or two use cases for this intrusive system (for instance, during a drug trial, to guarantee accuracy) but in general, treating patients like criminals doesn’t encourage healthy behavior.

A lot of people, especially the elderly and those with the most severe medical conditions, need so many pills and capsules that it’s hard to remember which ones to take, and when. I’ve seen relatives loading little pillboxes every Sunday morning with the pills for the upcoming week.

Insightfil hopes to take all the manual labor, and consequent chances for error, out of this process. It ships each person a customized blister pack with a week’s worth of medications, offering up to four compartments per day to cover different times. This may seem like a simple problem, but it’s actually a major logistical feat.

First, according to founder and CEO Ted Acworth, his company had to develop a robot that could recognize different pills and accurately load them into the blister packs. Then they had to find a pharmacy with nationwide reach and room in its warehouse for the robot.

Dose solves the problem a different way, through a dispenser into which a patient or caregiver can pour bottles of pills. The dispenser, which has been configured to know the patient’s medication regimen, can automatically separate the pills and release them at the right time.

Once the pills are in the box, control can be removed from the patient. This can be important for doling out opiates or other drugs that can be dangerous or that patients have a tendency to abuse.

Dose’s dispenser is a very smart machine, supporting some of other goals of connected health I mentioned. Clinicians, caregivers, and patients can get alerts about doses taken or missed. The device has bi-directional programming capabilities with a web portal and mobile app, and clinicians can change regimens over the Internet. Biometric devices can be attached to let users map medication adherence to vital signs, or to report a user’s exercise and eating habits. The device’s forward facing camera can be used for scanning the barcode of a pill bottle, as well as for video consultations with a clinician. Along with these features, the device is integrated with an FDA Drug Database and therefore an accurate drug list, along with information about potential drug interactions is readily available.

On many levels, then, advanced technology can help patients with the apparently simple problem of opening a bottle at the right time and popping a pill in their mouths. This article has been a limited look at the problem–I haven’t dealt with over-prescription or side effects, but just the question of how to get patients to take the drugs that are understood to improve their health. We’ll see over time which of these solutions–perhaps all of them at different times–can help of hundreds of millions who regularly take prescription drugs.

Using APIs at the Department of Health and Human Services to Expand Web Content

Posted on October 21, 2015 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

Application Programming Interfaces (APIs) appeal mostly to statisticians and researchers whose careers depend on access to data. But these programming tools are also a useful part of a Web that is becoming increasingly supple and sophisticated. I have written a series of articles about the use of APIs to share and run analytics on patient data, but today I’ll cover a cool use of an API developed by the Department of Health and Human Services for disseminating educational material.

The locus for this activity started with the wealth of information created by the Centers for Disease Control for doctors, public health workers, and the general public. Striving to help the public understand vaccinations, West Nile fever, Ebola (when that was a major public issue), and even everyday conditions such as diabetes, the CDC realized they had to make their content simple to embed in web sites for all those audiences.

The CDC also realized that it would be helpful to let outsiders quickly choose content along a number of dimensions. Not only would a particular web site be interested in a particular topic (diabetes, for instance), but they would want to filter the content to offer information to a particular audience in a particular language. One Web page might offer content aimed at doctors in English, while another might offer content for the general public in English and yet another offer content in Spanish. To allow all these distinctions, a RESTful API called from JavaScript allows each Web page to bring in just what is needed. Topics and languages are offered now, and filtering by audience will be supported soon. At some point, the API will even recognize ICD-10 codes and find any content related to those disease conditions.

We are all familiar with Web pages that embed dynamic content from other sites, such as videos from YouTube or Vimeo. Web developers embed the content by visiting the desired page, clicking on an Embed button, and copying some dense HTML to their own pages. The CDC offers several ways for visitors to syndicate content in this manner to their own web sites. If they are using a popular content management system (WordPress, Drupal, or Joomla!) they can install a plug-in that uses familiar practices to embed the content. Mobile app support is also provided. But the API developed by the CDC takes the process to a much more advanced level.

First, as already described, the API lets each page specify filters that extract content on the desired topic for the desired audience. Second, if a new video, e-card, or microsite is added to the CDC site, the API automatically picks it up when a user revisits the embedding page. Thus, without fussing with HTML, a site can integrate CDC content that’s tailored pretty precisely to its needs.

This API is also in use at the FDA–see for instance their Center for Tobacco Products–and at HHS more broadly. A community is starting to build around the code, which is open source, and soon it will be on GitHub, the most popular site for code sharing. A terse documentation page is available.

The API from Health and Human Services offers several lessons for health IT. First, communications can be improved by using the advanced features provided by the Web. (In addition to the API, the CDC tools make sophisticated use of HTML5 and iFrames to offer dynamic content in ways that fit in smoothly with the sites that choose to embed it.) Second, sites need to consider the people at the other end of the transaction in order to design tools that deliver an easy-to-use and easy-to-understand experience. And finally, releasing code as open source maximizes its value to the health care community. These trends need to be more widely adopted.

EHR Usage – Best and Worst States

Posted on September 11, 2015 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.

A recent Becker’s article used some CDC data to rank the best and worst states when it comes to EHR usage. Here’s the top 8 states for EHR usage:

• North Dakota — 79.1 percent
• Minnesota
• Montana
• North Carolina
• South Dakota
• Utah
• Wisconsin
• Iowa — 64.7 percent

And here are the bottom 6 states:

• Tennessee — 38.5 percent
• Florida
• Louisana
• Nevada
• Rhode Island
• New Jersey —29.2 percent

What’s ironic is that just this week I was talking with someone about me writing this healthcare IT blog from the healthcare hub known as Las Vegas (that’s a joke for those following along at home). This person commented that Nevada was way behind on EHR adoption and then they added the small caveat, right? I acknowledged that we were behind, but I must admit that seeing Nevada on this list kind of makes me sad. No one wants their state to be on the bottom of anything.

I did end our discussion by saying that maybe being on the bottom could be a good thing. In other states, they may have rushed their EHR selection and implementation process. If you’re going to choose the wrong EHR or not spend the time to implement the EHR properly, then it might be better to not have an EHR. With that said, I’m still pro-EHR and I hope my state catches up and implements the right EHR in the right way.

Is your state on the list? It would be interesting to see if there’s a correlation between states that have adopted EHR and the quality of care those states provide. Of course, the real challenge is knowing how to measure quality of care.

A Thoughtful Approach to EHR Implementation – 5 Tips

Posted on May 9, 2013 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.

While many in the EHR industry have started moving beyond EHR implementation, it’s worth realizing that only 55% of physicians have adopted an electronic health record (EHR). Yes, that means that 45% of physicians are still working on selecting and adopting an EHR. Ok, it’s probably more like 40% of doctors are looking to implement an EHR. The other 5% will stick with their paper.

Plus, along with the 45% of doctors who don’t use EHR, there are a whole slew of existing EHR users that are selecting and implementing an EHR as well. For example, 2 days ago I was at my son’s cub scout event where an opthamologist friend of mine cornered me and asked me about how he should go about selecting an EHR for his practice. He had just decided to go out on his own and open his own opthamology practice. What a perfect time to select and implement an EHR.

With this in mind, today I came across this whitepaper by ADP AdvancedMD called A Thoughtful Approach to EHR Implementation. They provide a number of stats, charts, and graphs using data from the CDC about EHR satisfaction and EHR use. The most intriguing number to me was the number of physicians that reported accessing the patient chart remotely using their EHR. That’s an EHR benefit that I don’t see talked about very often.

The whitepaper also offered these 5 tips for a successful EHR Implementation:

  1. Stay committed to your goal, but flexible in your approach
  2. Don’t short-change your training opportunities
  3. Don’t underestimate the impact to your workflow
  4. To pilot or not to pilot
  5. Optimizing the EHR

A lot more could be said about each point and they cover each point in detail in the full whitepaper, but the first and third ones really stand out to me. EHR is a commitment, but requires some flexibility. The best way to have a failed EHR implementation is to not be committed or to be inflexible. Your workflow will be impacted, but if you take a thoughtful approach to your EHR implementation it can be impacted for good.

MyPassport, Transcription Costs, and CDC App — Around Healthcare Scene

Posted on January 20, 2013 I Written By

Katie Clark is originally from Colorado and currently lives in Utah with her husband and son. She writes primarily for Smart Phone Health Care, but contributes to several Health Care Scene blogs, including EMR Thoughts, EMR and EHR, and EMR and HIPAA. She enjoys learning about Health IT and mHealth, and finding ways to improve her own health along the way.

Hospital EHR and EMR

Hospitals Beware: EMR Copy and Paste Common

EMR Templates can be helpful, but also makes life harder as well. A recent study found that 82 percent of progress notes by residents had 20 percent or more copied and pasted material. This function is tempting for physicians who need to cut time somewhere, but its something that needs to be watched out for and prevented.

iPad App Helps Patients Understand Inpatient Care Process

In an effort to eliminate confusion that often comes during an inpatient stay, Boston Children’s Hospital has developed an iPad app. The app, called MyPassport, helps patients understand more about what is going on during their stay. It displays photos of doctors and nurses, others involved in care, as well as lab results that have been condensed to patient-friendly terms.

EMR, EHR, and HIPAA

EHR Benefit — Transcription Costs Savings

This is the next part of the EHR benefits series. Many doctors were thrilled to give up their transcription for an EHR in hopes of saving costs. However, some are feeling that their EHR may not be the best solution after all. Because of this, some are wanting to implement transcription services again. So, for some, eliminating transcription may not have saved as much money as some had hoped.

Mixing Physical, Mental Health Data Lowers Readmissions

Physicians aren’t often given access to the psychiatric records of patients they are treating. However, a study by Johns Hopkins found that perhaps they should be. The study showed that a signficant percentage of patients whose physicians had access to both physical and mental health data had a smaller readmission rate than those whose mental health records weren’t available.

Smart Phone Healthcare

CDC Launches New Mobile App

The CDC is getting into mHealth with the recent release of their mobile app. The app has many different features, such as health articles, quizzes, and a news room with information outbreaks or other pertinent information. The app is free and definitely one that should be downloaded if you enjoy hearing about health news.

Google Gets Into Activity Tracking

After the failure of Google Health, Google is making an attempt to get into the activity tracking world. “Google Now” basically turns the phone into a personal tracking device, including for fitness. It isn’t as accurate as some of the more sophisticated tracking devices out there, but it is a lot easier to use because it is embedded into the phone. It may make it easier for people to

Cognitive Dissonance and EMRs

Posted on July 18, 2012 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 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. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

A new CDC study has documented what’s pretty much old news to us EMR watchers, that more than half of U.S. doctors have taken their charts digital. The study also concluded that most are pretty happy with their EMR, heaven help us, and that it’s improved patient care.

According to a study by the CDC’s National Center for Health Statistics, 55 percent of U.S. doctors have adopted some type of EMR.  More interestingly, for folks like me at least, 75 percent of those who have have met Meaningful Use Stage 1 criteria, something I might not have predicted if I hadn’t read the study.

This seems a bit strange to me, honestly. I’ve talked to countless doctors about their EMRs, both hospital- and practice-based, and I’ve only met a couple who actually felt satisfied with the system(s) they use. I haven’t met any that felt the systems have improved patient care, though I admit my sample isn’t drawn scientifically. (Vendors, I’m not saying that *nobody’s* happy, just that these numbers sound high, to be clear.)

The best explanation I can come up with for such results, which came from 3,200 doctors completing a mail-in survey, is the impact of cognitive dissonance.  Let me explain.

Doctors are being  pressured with thumb screws to make the switch, and it’s hardly surprising that most have come around.  So they’ve gone ahead and spent what in some cases are huge sums of money to make the leap.

The thing is, when you’re forced to use something every day, you can’t just keep on hating it more and more. Nobody has that much energy.  So over time, you resolve the cognitive dissonance — the battling “EMR painful” and “EMR necessary” thoughts — by learning to love Big Brother EMR, or at least believe that you do.

Then again, though I’d have trouble believing this, maybe there’s hordes of satisfied doctors that never come to the attention of a cynic like me. What do you think?

EMRs Have Potential Role to Play in Curbing Global Contagion

Posted on July 11, 2012 I Written By

As Social Marketing Director at Billian, Jennifer Dennard is responsible for the continuing development and implementation of the company's social media strategies for Billian's HealthDATA and Porter Research. She is a regular contributor to a number of healthcare blogs and currently manages social marketing channels for the Health IT Leadership Summit and Technology Association of Georgia’s Health Society. You can find her on Twitter @JennDennard.

I had some rare time to myself at home the other night and decided to finally watch the Netflix DVD that had literally been gathering dust on our entertainment center. (No matter how hard I try, I can’t seem to watch a movie and return it in less than a week these days.) For better or worse, I popped in the star-studded, virus-filled Contagion – an ode to the absolute insanity that could befall modern society should a highly contagious and highly untreatable virus strike nearly every society on Earth.

Other than the autopsy scene in which Gwyneth Paltrow’s character – otherwise known as the “index patient” – gets what I’ll delicately call a “facial,” I was pretty fascinated by the inner workings, procedures, protocol and backstabbing of the CDC and WHO. They, of course, used technology to track the virus’ origin and its rapid spread, and I kept waiting to hear a doctor refer to accessing victims’ electronic medical records to track development of their illnesses. (Come to think of it, this movie would have made for great EMR product placement opportunities.)

Though EMRs were given short shrift, the movie made a good case for population health management, and the corresponding role technology can potentially play in tracking outbreaks. I wondered if such an outbreak were to actually ever occur, would EMRs, HIEs and other data exchange programs help providers isolate worst cases of conatgion quicker?

Coming across a headline like “Officials search for more clues in disease killing Cambodian children” makes me wonder if the CDC and WHO are using population health management tools in their investigations, and if data exchange is playing a part in developing countries like Cambodia. A quick Google search of Kantha Bopha Children’s Hospitals, which seems to be ground zero for treatment of the outbreak, leads me to believe the hospitals likely don’t have the resources for sophisticated healthcare IT systems. A broader search for mention of EMRs in Cambodia yielded information from late last year on University Research Company’s Cambodia Better Health Systems Project participating in an Open Medical Record System Annual Implementer’s Meeting meeting in Rwanda, focused on enhancing EMR systems. So it seems that EMRs are definitely on the country’s radar to some extent.

Could EMRs in a developing country like Cambodia help to contain the spread of highly contagious diseases? Could they at least help spread message of the contagion amongst providers across affected regions, helping to transmit daily updates regarding spread, treatment, cause, etc.? These are all questions I’m sure global health agencies have already spent considerable time considering. I came across a very interesting report from the Rockefeller Foundation and its partners on this very subject. Highly recommended reading: “The Promise of Electronic Medical Records (PDF).”

Are you aware of more up-to-date implementations of EMRs in developing countries? Any third-world success stories we should know about? Please share your thoughts in the comments below.