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E-Patient Update: The Kaiser Permanente Approach To Consumer Health IT

Posted on May 19, 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.

Usually, particularly when I have complaints, I don’t name the providers or vendors who serve my healthcare needs, largely because I don’t want to let my personal gripes overshadow my analysis of a particular health IT issue.

That being said, I thought I’d veer from that rule today, as I wanted to share some details on how Kaiser Permanente, my new provider and health plan, supports consumers with health IT functions. Despite having started with Kaiser – in this case the DC metro division – less than a week ago, being an e-patient I’ve had my hands all over its Web – and mobile-based options for patients.

I’m not going to say the system is perfect by any means. There are some blind alleys on the web site, and some problems in integrating clinical information into consumer records, but so far their set-up largely seems thoughtful and well-managed.

Having allegedly spent $4 billion plus on its Epic rollout, it’s hard to imagine how Kaiser could have realized that big a return even several years later, but it seems that the healthcare giant is at least doing many of the right things.

Getting enrolled

My first contact with Kaiser, after signing up with Healthcare.gov, was a piece of snail-mail which provided us with our insurance cards and a summary of our particular coverage. The insurance cards included my health plan ID/medical record number.

To enroll on the core Kaiser site, kp.org, I had to supply the record number, my birth date and a few other basic pieces of information. I also downloaded the KP app, which offers a far-more-elegant interface to the same functions.

Medical appointments

Once logged in, it was easy to choose a primary care doctor and OB/GYN by searching the site and clicking a selection button. If you wished you could review physician profiles and educational history as well as testimonial quotes from patients about that doctor before you chose them.

Having chosen a doctor, booking an appointment with them online was easy.  As with Zocdoc.com, you entered a range of dates for a possible consult, then chose the slot that worked for you. And if you need to cancel one of those appointments, it’s easy to do so online.

Digital communication

I was glad to see that the Kaiser portal allows you to email your doctor directly, something which is less common than you might think. (My last primary care group wouldn’t even put their doctors on the phone.)

Not only that, everyone I’ve talked to at KP so far– three medical appointments, as I was playing catch-up — has stressed that the email function isn’t just for show. My new providers insisted that they do answer email messages, and that I shouldn’t hesitate to write if I have questions or concerns.

Another way KP leverages digital communications is the simple, but effective, device of texting me when my prescriptions are due for a refill. This may not sound like much, but convenience matters! (I can also check med reminders by logging in to a custom KP meds app.)

Data sharing

Given that everyone at Kaiser uses the same Epic EMR, clinicians are of course more aware of what their colleagues are doing than my past gaggle of disconnected specialists. They seem quite serious about reading this history before seeing me, something which past physicians haven’t always done, even if I was previously seen by someone else in their practice.

KP also uses Epic’s Care Everywhere function, which allows them to pull in a limited summary of care from other Epic-based providers. While Care Everywhere has limits, the providers are making use of what they can.

One small wrinkle was that prior to two of my visits, I filled out a questionnaire online and when asked to submit it to my electronic patient record, did so. Nonetheless, I was asked to fill out the same questionnaire again, on paper, when I saw a specialist.

Test results

KP seems to be set up appropriately to share standard test results. However, I’ve already had one test, a mammogram, and in doing so found out that their data sharing infrastructure isn’t quite complete.

After being scanned, I was told that I’d receive my results via snail-mail, in about two weeks. I’m glad that this was a routine screening, rather than a test to investigate something scary, as I would have been pretty upset with this news if I was worried.

My conclusions

I don’t want to romanticize Kaiser’s consumer HIT services. After all, looked at one way, KP is only doing what integrated health systems are supposed to do, and not without at least a few hitches.

Still, at least on first view, on the whole I’m pretty happy with how Kaiser’s interactive functions are deployed, as well the general attitude staff members seem to have about consumer use of HIT tools. Generally speaking, they seem to encourage it, and for someone like me that’s quite welcome.

As I see it, if providers outside of the Kaiser bubble were as married to a shared infrastructure as KP providers are, my care would be much improved. Let’s see if I still if I still feel that way after the new health plan smell has worn off!

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.

Using AI To Streamline EMR Workflow For Clinicians

Posted on May 10, 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.

Understandably, most of the discussion around AI use in healthcare focuses on data analytics for population health management and predictive analytics. Given the massive scale of the data we’re collecting, that’s no surprise.

In fact, one could argue that using AI technologies has gone from an interesting idea to an increasingly established parto the health IT mix. After all, few human beings can truly understand what’s revealed by terabytes of data on their own, even using well-designed dashboards, filters, scripting and what have you. I believe it takes a self-educating AI “persona,” if you will, to glean advanced insights from the eternity of information we have today.

That being said, I believe there’s other compelling uses for AI-fueled technologies for healthcare organizations. If we use even a relatively simple form of interpretive intelligence, we can improve health IT workflows for clinicians.

As clinicians have pointed out over and over, most of what they do with EMRs is repetitive monkey work, varied only by the need to customize small but vital elements of the medical record. Tasks related to that work – such as sending copies of a CT scan to a referring doctor – usually have to be done in another application. (And that’s if they’re lucky. They might be forced to hunt down and mail a DVD disc loaded with the image.)

Then there’s documentation work which, though important enough, has to be done in a way to satisfy payers. I know some practice management systems that integrate with the office EMR auto-populate the patient record with coding and billing information, but my sense is that this type of automation wouldn’t scale within a health system given the data silos that still exist.

What if we used AI to make all of this easier for providers? I’m talking about using a predictive intelligence, integrated with the EMR, that personalizes the way data entry, documentation and follow-up needs are presented. The AI solution could automatically queue up or even execute some of the routine tasks on its own, leaving doctors to focus on the essence of their work. We all know Dr. Z doesn’t really want to chase down that imaging study and mail it to Albany. AI technology could also route patients to testing and scans in the most efficient manner, adjusted for acuity of course.

While AI development has been focused on enterprise issues for some time, it’s already moving beyond the back office into day-to-day care. In fact, always-ahead-of-the-curve Geisinger Health System is already doing a great deal to bring AI and predictive analytics to the bedside.

Geisinger, which has had a full-featured EMR in place since 1996, was struggling to aggregate and manage patient data, largely because its legacy analytics systems couldn’t handle the flood of new data types emerging today.

To address the problem, the system rolled out a unified data architecture which allowed it to integrate current data with its existing data analytics and management tools. This includes a program bringing together all sepsis-vulnerable patient information in one place as they travel through the hospital. The tool uses real-time data to track patients in septic shock, helping doctors to stick to protocols.

As for me, I’d like to see AI tools pushed further. Let’s use them to lessen the administrative burden on overworked physicians, eliminating needless chores and simplifying documentation workflow. And it’s more than time to use AI capabilities to create a personalized, efficient EMR workflow for every clinician.

Think I’m dreaming here? I hope not! Using AI to eliminate physician hassles could be a very big deal.

ACP Offers Recommendations On Reducing MD Administrative Overload

Posted on March 30, 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.

As everyone knows, physicians are being overwhelmed by outsized levels of administrative chores. As if dealing with insurance companies wasn’t challenging enough, in recent years EMRs have added to this burden, with clinicians doing double duty as data entry clerks after they’re seen patients.

Unfortunately, streamlining EMR use for clinical use has proven to be a major challenge. Still, there are steps healthcare organizations can take to cut down on clinicians’ administrative frustrations, according to the American College of Physicians.

The ACP’s recommendations include the following:

  1. Stakeholders responsible for imposing administrative tasks – such as payors, government and vendors – should analyze the impact of administrative tasks on physicians. If a task is found to have a negative effect on care quality, needlessly questions a clinician’s judgment or increases costs, it should be challenged, fixed or removed.
  2. If an administrative task can’t be cut, it must be reviewed, revised, aligned or streamlined to reduce stakeholders’ burden.
  3. Stakeholders should collaborate with professional societies, clinicians, patients and EMR vendors to develop performance measures that minimize needless clinician burden and integrate performance reporting and quality improvement.
  4. All key stakeholders should collaborate in reducing, streamlining, reducing and aligning clinicians’ administrative tasks by making better use of health IT.
  5. As the US healthcare system shifts to value-based payment, stakeholders should consider streamlining or eliminating duplicative administrative demands.
  6. The ACP would like to see rigorous research done on the impact of administrative tasks on healthcare quality, time and cost; on clinicians, staff and healthcare organizations; patient and family; and patient outcomes.
  7. The ACP calls for research on best practices for cutting down on clinicians’ administrative tasks within both practices and organizations. All key stakeholders, including clinician societies, payors, regulators, vendors and suppliers, should disseminate these evidence-based best practices.

It appears that even the federal government has begun to take these issues to heart. According to Modern Healthcare, late last year CMS announced a long-term initiative intended to reduce physicians’ administrative burdens.  Then-acting CMS Administrator Andy Slavitt said the initiative would hopefully make it a bit easier for practices to meet the requirements of the Quality Payment Program under MACRA.

But other sources of administrative frustration are likely to linger for the foreseeable future, as they’re deeply ingrained in stakeholder business processes or simply difficult to change.

For example, the American Academy of Family Physicians notes that some of the biggest aggravations and time wasters for its members include the need to get prior authorizations from health plans and outdated CMS documentation guidelines for E/M services which don’t leverage EMR capabilities. Sadly, I wouldn’t hold my breath waiting for either of those problems to be solved.

Still, it seems some healthcare organizations want to take on the administrative overhead problem. The University of Pittsburgh Medical Center has launched an initiative aimed at reducing the number of computer-related tasks doctors have to perform. According to the Pittsburgh Post-Gazette, UPMC is partnering with Microsoft to minimize physicians’ need to do electronic paperwork. Executives with the two organizations say this effort should result in tools for both doctors and patients.

Accountable Care HIT Spending Growing Worldwide

Posted on November 30, 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 market research report has concluded that given the pressures advancing the development of accountable care models, the market for solutions serving ACOs should expand worldwide, though North America is likely to lead the segment for the near future.

The report, by research firm Markets & Markets, covers a wide range of technologies, including EHRs, healthcare analytics, HIE, RCM, CDSS, population health, claims management and care management. It also looks at delivery mode, e.g. on premise, web and cloud and end-user, which includes providers and payers. So bear that in mind when you look at these numbers. That being said, providers accounted for the largest share of this niche last year, and should see the highest growth in the sector over the next five years.

Broadly speaking, Markets & Markets reports that the accountable care solutions market grew a healthy growth rate during the last decade. Researchers there expect to see this market grow at a CAGR of 16.6% over the next five years, to hit $18.86 billion by 2021.

When it comes to leaders in the sector, researchers identify Cerner, IBM, Aetna and Epic as leaders in the current ACO solutions market and probable future winners between 2016 and 2021. Other major players in the space include UnitedHealth Group, Allscripts, McKesson, Verisk Health, Zeomega, eClinicalWorks and NextGen. Given how broadly they define this category, I’m not sure how important this is, but there you have it.

According Markets & Markets, the growth of the ACO solutions market worldwide is due to forces we know well, including shifting government regulations, the rollout of initiatives shifting financial risk from payers to providers, the demand to slow down healthcare cost increases in the advance of IT and big data capabilities. (Personally, I’d add the desire of health systems – ACO-affiliated or not – to differentiate themselves by performing well at the population health level.)

If your view is largely US-centric, as is mine, you might be interested to note that the trend towards ACO-like entities in the Asia-Pacific and Latin American regions is expanding, the researchers report. Most specifically, Markets & Markets researchers found that there is notable growth occurring in Asian countries, which, it reports, are modifying regulations and monitoring the implementation of procedures, policies and guidelines to promote innovation and commercialization. This has led to an increasing number of hospitals and academic institutions interested in the sector, along with a government focus on implementing health IT solutions and infrastructure – factors likely to generate an expanding ACO solutions market there.

After reading all of this, the question I’m left with is whether there’s any point in differentiating an “ACO” specific player as these researchers have. Maybe I’m playing with words too much hear, but wouldn’t it be more accurate to say that the definition of health system infrastructure is evolving, whether it’s part of an ACO as such or not?

AMA Approves List Of Best Principles For Mobile Health App Design

Posted on November 29, 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.

The American Medical Association has effectively thrown her weight behind the use of mobile health applications, at least if those apps meet the criteria members agreed on at a recent AMA meeting. That being said, the group also argues that the industry needs to expand the evidence base demonstrating that apps are accurate, effective, safe and secure. The principles, which were approved at its recent Interim Meeting, are intended to guide coverage and payment policies supporting the use of mHealth apps.

The AMA attendees agreed on the following principles, which are intended to guide the use of not only mobile health apps but also associated devices, trackers and sensors by patients, physicians and others. They require that mobile apps and devices meet the following somewhat predictable criteria:

  • Supporting the establishment or continuation of a valid patient-physician relationship
  • Having a clinical evidence base to support their use in order to ensure mHealth apps safety and effectiveness
  • Following evidence-based practice guidelines, to the degree they are available, to ensure patient safety, quality of care and positive health outcomes
  • Supporting data portability and interoperability in order to promote care coordination through medical home and accountable care models
  • Abiding by state licensure laws and state medical practice laws and requirements in the state in which the patient receives services facilitated by the app
  • Requiring that physicians and other health practitioners delivering services through the app be licensed in the state where the patient receives services, or will be providing these services is otherwise authorized by that state’s medical board
  • Ensuring that the delivery of any service via the app is consistent with the state scope of practice laws

In addition to laying out these principles, the AMA also looked at legal issues physicians might face in using mHealth apps. And that’s where things got interesting.

For one thing, the AMA argues that it’s at least partially on a physician’s head to school patients on how secure and private a given app may be (or fail to be). That implies that your average physician will probably have to become more aware of how well a range of apps handle such issues, something I doubt most have studied to date.

The AMA also charges physicians to become aware of whether mHealth apps and associated devices, trackers and sensors are abiding by all applicable privacy and security laws. In fact, according to the new policy, doctors are supposed to consult with an attorney if they don’t know whether mobile health apps meet federal or state privacy and security laws. That warning, while doubtless prudent, must not be helping members sleep at night.

Finally, the AMA notes that there are still questions remaining as to what risks physicians face who use, recommend or prescribe mobile apps. I have little doubt that they are right about this.

Just think of the malpractice lawsuit possibilities. Is the doctor liable because they relied on inaccurate app results collected by the patient? If the app they recommended presented inaccurate results? How about if the app was created by the practice or health system for which they work? What about if the physician relied on inaccurate data generated by a sensor or wearable — is a physician liable or the device manufacturer? If I can come up with these questions, you know a plaintiff’s attorney can do a lot better.

New Effort Would Focus HIE Data Around Patients

Posted on June 7, 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.

In theory, doctors should be able to pull up all data available on a patient located within any networks to which they have access. In other words, not only should they be able to see any data on Patient A within the EMR where A’s care is documented, but also retrieve data on A from within any HIEs which connect with the EMR. But the reality is, that’s not always the case (in fact, it’s rarely the case).

To help weave together patient data strung across various HIEs, three exchanges have teamed up to pilot test the idea of a patient-centered data home (PCDH). While many health leaders have looked at the idea of putting patients in charge of their own data, largely by adding to or correcting existing records, getting patients involved in curating such data has been difficult at best.

In this model, Arizona Health-e Connection, western Colorado’s Quality Health Network and the Utah Health Information Network are testing a method of data sharing in which the other HIEs would be notified if the patient undergoes an episode of care within their network.

The alert confirms the availability and specific location of the patient’s clinical data, reports Healthcare Informatics. Providers will then be able to access real-time information on that patient across network lines by initiating a simple query. Unlike in other models of HIE data management, all clinical data in a PCDH will become part of a comprehensive longitudinal patient record, which will be located in the HIE where the patient resides.

The PCDH’s data sharing model works as follows:

  • A group of HIEs set up a PCDH exchange, sharing all the zip codes within the geographic boundaries that their exchanges serve.
  • Once the zip codes are shared, the HIEs set up an automated notification process which detects when there is information on the patient’s home HIE that is available for sharing.
  • If a patient is seen outside of their home territory, say in a hospital emergency department, the event triggers an automated alert which is sent to the hospital’s HIE.
  • The hospital’s HIE queries the patient’s home HIE, which responds that there is information available on that patient.
  • At that point providers from both HIEs and query and pull information back and forth. The patient’s home HIE pulls information on the patient’s out-of-area encounter into their longitudinal record.

The notion of a PCDH is being developed by the Strategic Health Information Exchange Collaborative, a 37-member HIE trade group to which the Utah, Arizona and Colorado exchanges belong.

Developing a PCDH model is part of a 10-year roadmap for interoperability and a “learning health system” which will offer centralized consent management and health records for patients, as well as providing national enterprises with data access. The trade group expects to see several more of its members test out PCDHs, including participants in Arkansas, Oklahoma, Indiana, Kentucky and Tennessee.

According to the Collaborative, other attempts at building patient records across networks have failed because they are built around individual organizations, geographies such as state boundaries, single EHR vendors or single payers. The PCDH model, for its part, can bring information on individual patients together seamlessly without disrupting local data governance or business models, demanding new technical infrastructure or violating the rights of local stakeholders, the group says.

Like other relatively lightweight data sharing models (such as the Direct Project) the PCDH offers an initial take on what is likely to be a far more complex problem. But it seems like a good idea nonetheless.

New Payment Model Pushes HIT Vendors To Collaborate

Posted on April 20, 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.

CMS has launched a new program designed to shift more risk to and offer more rewards to primary care practices which explicitly requires HIT vendors to be involved at advanced stages. While the federal government has obvious done a great deal to promote the use of HIT in medical practices, this is the first I’ve seen where HHS has demanded vendors get involved directly, and I find it intriguing. But let me explain.

The new Comprehensive Primary Care Plus payment scheme – which builds upon an existing model – is designed to keep pushing risk onto primary care practices. CMS expects to get up to 5,000 practices on board over the next five years, spanning more than 20,000 clinicians serving 25 million Medicare beneficiaries.

Like Medicare payment reforms focused on hospitals, CPC+ is designed to shift risk to PCPs in stages. Track 1 of the program is designed to help the practices shift into care management mode, offering an average care management fee of $15 per beneficiary per month on top of fee-for-service payments. Track 2, meanwhile, requires practices to bear some risk, offering them a special hybrid payment which mixes fee-for-service and a percentage of expected Evaluation & Management reimbursement up front. Both tracks offer a performance-based incentive, but risk-bearing practices get more.

So why I am I bothering telling you this? I mention this payment model because of an interesting requirement CMS has laid upon Track 2, the risk-bearing track. On this track, practices have to get their HIT vendor(s) to write a letter outlining the vendors’ willingness to support them with advanced health IT capabilities.

This is a new tack for CMS, as far as I know. True, writing a letter on behalf of customers is certainly less challenging for vendors than getting a certification for their technology, so it’s not going to create shockwaves. Still, it does suggest that CMS is thinking in new ways, and that’s always worth noticing.

True, it doesn’t appear that vendors will be required to swear mighty oaths promising that they’ll support any specific features or objectives. As with the recently-announced Interoperability Pledge, it seems like more form than substance.

Nonetheless, my take is that HIT vendors should take this requirement seriously. First of all, it shines a spotlight on the extent to which the vendors are offering real, practical support for clinicians, and while CMS may not be measuring this just yet, they may do so in the future.

What’s more, when vendors put such a letter together in collaboration with practices, it brings both sides to the table. It gives vendors and PCPs at least a marginally stronger incentive to discuss what they need to accomplish. Ideally – as CMS doubtless hopes – it could lay a foundation for better alignment between clinicians and HIT leaders.

Again, I’m not suggesting this is a massive news item, but it’s certainly food for thought. Asking HIT vendors to stick their necks out in this way (at least symbolically) could ultimately be a catalyst for change.

Our Uncontrolled Health Care Costs Can Be Traced to Data and Communication Failures (Part 2 of 2)

Posted on April 13, 2016 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.

The previous section of this article provided whatever detail I could find on the costs of poor communications and data exchange among health care providers. But in truth, it’s hard to imagine the toll taken by communications failures beyond certain obvious consequences, such as repeated tests and avoidable medical errors. One has to think about how the field operates and what we would be capable of with proper use of data.

As patients move from PCP to specialist, from hospital to rehab facility, and from district to district, their providers need not only discharge summaries but intensive coordination to prevent relapses. Our doctors are great at fixing a diabetic episode or heart-related event. Where we fall down is on getting the patient the continued care she needs, ensuring she obtains and ingests her medication, and encouraging her to make the substantial life-style changes that can prevent reoccurrences. Modern health really is all about collaboration–but doctors are decades behind the times.

Clinicians were largely unprepared to handle the new patients brought to them by the Affordable Care Act. Examining the impact of new enrollees, who “have higher rates of disease and received significantly more medical care,” an industry spokesperson said, “The findings underscore the need for all of us in the health care system, and newly insured consumers, to work together to make sure that people get the right health care service in the right care setting and at the right time…Better communication and coordination is needed so that everyone understands how to avoid unnecessary emergency room visits, make full use of primary care and preventive services and learn how to properly adhere to their medications.” Just where the health providers fall short.

All these failures to communicate may explain the disappointing performance of patient centered medical homes and Accountable Care Organizations. While many factors go into the success or failure of such complex practices, a high rate of failure suggests that they’re not really carrying out the coordinated care they were meant to deliver. Naturally, problems persist in getting data from one vendor’s electronic health record to another.

Urgent care clinics, and other alternative treatment facilities offered in places such as pharmacies, can potentially lower costs, but not if the regular health system fails to integrate them.

Successes in coordinated care show how powerful it can be. Even so simple a practice as showing medical records to patients can improve care, but most clinicians still deny patients access to their data.

One care practice drastically lowered ER admissions through a notably low-tech policy–refering their patients to a clinic for follow-up care. This is only the beginning of what we could achieve. If modern communications were in place, hospitals would be linked so that a CDC warning could go to all of them instantly. And if clinicians and their record systems were set up to handle patient-generated data, they could discover a lot more about the patients and monitor behavior change.

How are the hospitals and clinics responding to this crisis and the public pressure to shape up? They push back as if it was not their problem. They claim they are moving toward better information sharing and teamwork, but never get there.

One of their favorite gambits is to ask the government to reward them for achieving interoperability 90 days out of the year. They make this request with no groveling, no tears of shame, no admission that they have failed in their responsibility to meet reasonable goals set seven years ago. If I delivered my projects only 25% of the time, I’d have trouble justifying myself to my employer, especially if I received my compensation plan seven years ago. Could the medical industry imagine that it owes us a modicum of effort?

Robert Schultz, a writer and entrepreneur in health care, says, “Underlying the broken communications model is a lack of empathy for the ultimate person affected–the patient. Health care is one of the few industries where the user is not necessarily the party paying for the product or service. Electronic health records and health information exchanges are designed around the insurance companies, accountable care organizations, or providers, instead of around understanding the challenges and obstacles that patients face on a daily basis. (There are so many!) The innovators who understand the role of the patient in this new accountable care climate will be winners. Those who suffer from the burden of legacy will continue to see the same problems and will become eclipsed by other organizations who can sustain patient engagement and prove value within accountable care contracts.”

Alternative factors

Of course, after such a provocative accusation, I should consider the other contributors that are often blamed for increasing health care costs.

An aging population

Older people have more chronic diseases, a trend that is straining health care systems from Cuba to Japan. This demographic reality makes intelligent data use even more important: remote monitoring for chronic conditions, graceful care transitions, and patient coordination.

The rising cost of drugs

Dramatically increasing drug prices are certainly straining our payment systems. Doctors who took research seriously could be pushing back against patient requests for drugs that work more often in TV ads than in real life. Doctors could look at holistic pain treatments such as yoga and biofeedback, instead of launching the worst opiate addiction crisis America has ever had.

Government bureaucracy

This seems to be a condition of life we need to deal with, like death and taxes. True, the Centers for Medicare & Medicaid Services (CMS) keeps adding requirements for data to report. But much of it could be automated if clinical settings adopted modern programming practices. Furthermore, this data appears to be a burden only because it isn’t exploited. Most of it is quite useful, and it just takes agile organizations to query it.

Intermediaries

Reflecting the Byzantine complexity of our payment systems, a huge number of middlemen–pharmacy benefits managers, medical billing clearinghouses, even the insurers themselves–enter the system, each taking its cut of the profits. Single-payer insurance has long been touted as a solution, but I’d rather push for better and cheaper treatments than attack the politically entrenched payment system.

Under-funded public health

Poverty, pollution, stress, and other external factors have huge impacts on health. This problem isn’t about clinicians, of course, it’s about all of us. But clinicians could be doing more to document these and intervene to improve them.

Clinicians like to point to barriers in their way of adopting information-based reforms, and tell us to tolerate the pace of change. But like the rising seas of climate change, the bite of health care costs will not tolerate complacency. The hard part is that merely wagging fingers and imposing goals–the ONC’s primary interventions–will not produce change. I think that reform will happen in pockets throughout the industry–such as the self-insured employers covered in a recent article–and eventually force incumbents to evolve or die.

The precision medicine initiative, and numerous databases being built up around the country with public health data, may contribute to a breakthrough by showing us the true quality of different types of care, and helping us reward clinicians fairly for treating patients of varying needs and risk. The FHIR standard may bring electronic health records in line. Analytics, currently a luxury available only to major health conglomerates, will become more commoditized and reach other providers.

But clinicians also have to do their part, and start acting like the future is here now. Those who make a priority of data sharing and communication will set themselves up for success long-term.

Our Uncontrolled Health Care Costs Can Be Traced to Data and Communication Failures (Part 1 of 2)

Posted on April 12, 2016 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.

A host of scapegoats, ranging from the Affordable Care Act to unscrupulous pharmaceutical companies, have been blamed for the rise in health care costs that are destroying our financial well-being, our social fabric, and our political balance. In this article I suggest a more appropriate target: the inability of health care providers to collaborate and share information. To some extent, our health care crisis is an IT problem–but with organizational and cultural roots.

It’s well known that large numbers of patients have difficulty with costs, and that employees’ share of the burden is rising. We’re going to have to update the famous Rodney Dangerfield joke:

My doctor said, “You’re going to be sick.” I said I wanted a second opinion. He answered, “OK, you’re going to be poor too.”

Most of us know about the insidious role of health care costs in holding down wages, in the fight by Wisconsin Governor Scott Walker over pensions that tore the country apart, in crippling small businesses, and in narrowing our choice of health care providers. Not all realize, though, that the crisis is leaching through the health care industry as well, causing hospitals to fail, insurers to push costs onto subscribers and abandon the exchanges where low-income people get their insurance, co-ops to close, and governments to throw people off of subsidized care, threatening the very universal coverage that the ACA aimed to achieve.

Lessons from a ground-breaking book by T.R. Reid, The Healing of America, suggests that we’re undergoing a painful transition that every country has traversed to achieve a rational health care system. Like us, other countries started by committing themselves to universal health care access. This then puts on the pressure to control costs, as well as the opportunities for coordination and economies of scale that eventually institute those controls. Solutions will take time, but we need to be smart about where to focus our efforts.

Before even the ACA, the 2009 HITECH act established goals of data exchange and coordinated patient care. But seven years later, doctors still lag in:

  • Coordinating with other providers treating the patients.

  • Sending information that providers need to adequately treat the patients.

  • Basing treatment decisions on evidence from research.

  • Providing patients with their own health care data.

We’ll look next at the reports behind these claims, and at the effects of the problems.

Why doctors don’t work together effectively

A recent report released by the ONC, and covered by me in a recent article, revealed the poor state of data sharing, after decades of Health Information Exchanges and four years of Meaningful Use. Health IT observers expect interoperability to continue being a challenge, even as changes in technology, regulations, and consumer action push providers to do it.

If merely exchanging documents is so hard–and often unachieved–patient-focused, coordinated care is clearly impossible. Integrating behavioral care to address chronic conditions will remain a fantasy.

Evidence-based medicine is also more of an aspiration than a reality. Research is not always trustworthy, but we must have more respect for the science than hospitals were found to have in a recent GAO report. They fail to collect data either on the problems leading to errors or on the efficacy of solutions. There are incentive programs from payers, but no one knows whether they help. Doctors are still ordering far too many unnecessary tests.

Many companies in the health analytics space offer services that can bring more certainty to the practice of medicine, and I often cover them in these postings. Although increasingly cited as a priority, analytical services are still adopted by only a fraction of health care providers.

Patients across the country are suffering from disrupted care as insurers narrow their networks. It may be fair to force patients to seek less expensive providers–but not when all their records get lost during the transition. This is all too likely in the current non-interoperable environment. Of course, redundant testing and treatment errors caused by ignorance could erase the gains of going to low-cost providers.

Some have bravely tallied up the costs of waste and lack of care coordination in health care. Some causes, such as fraud and price manipulation, are not attributable to the health IT failures I describe. But an enormous chunk of costs directly implicate communications and data handling problems, including administrative overhead. The next section of this article will explore what this means in day-to-day health care.