Free EMR Newsletter Want to receive the latest news on EMR, Meaningful Use, ARRA and Healthcare IT sent straight to your email? Join thousands of healthcare pros who subscribe to EMR and HIPAA for FREE!!

Why Should Patients Control Their Health Data? Here Are A Few Ideas.

Posted on September 29, 2017 I Written By

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

Lately, healthcare organizations have begun working to give patients more access to their personal health data. They’ve concluded that the more control patients have, the more engaged they become in your care, which in turn leads to better outcomes.

But patient engagement isn’t the only reason for giving patients the keys to their PHI. In fact, organizational control of patient health data can cause problems for everyone in the healthcare data exchange chain.

An item found on the Allscripts blog does a nice job of articulating issues that can arise.  According to the blog item, those issues include the following:

  • The patient is in the best position to address inconsistencies in their medical record. For example, if one doctor diagnoses the patient with asthma, then another physician conclusively demonstrates the patient is not asthmatic, the patient can reconcile the two physicians’ conclusions.
  • Patients have a better overview of their care than most doctors. When a chronically ill patient sees multiple clinicians, their impressions may conflict with one another, but the patient can provide context on their overall conditions.
  • If a patient consents to multiple uses of their health data, and the consents seem to be in conflict, only the patient can articulate what their intentions were.
  • If the master patient indexing process generates a false match with someone else’s records, the patient will recognize this immediately, while physicians may not.
  • Giving patients control of the record allows them to decide how long those records should be maintained. Otherwise, HIEs — or other entities not bound by record retention laws — might destroy the data prematurely.
  • When patients have control of their data, they can make sure it gets to whomever they choose. On the other hand, patient data may not make it to other care settings if providers drop the ball.

To be sure, delegating control of their PHI to patients can go too far.

For example, if they’re transmitting most or all of their health data between providers, it could pose a significant administrative burden.  Patients may not have the time or energy to route the data files between their providers, assure that data has been received on the other end and make certain that the data was formatted in a way their clinicians can use.

Also, if the patient is chronically ill and sees multiple providers, they may end up having to manage a large body of data files, and not everyone can do so effectively. Ultimately, they may get too overwhelmed to send their records to anyone, or send the wrong records, which can create complications of its own.

Still, on the whole, healthcare organizations are giving patients more control of their health data for good reasons. When patients take responsibility for their health data, they’re far more likely to understand their condition and take steps to address problems. Establishing a balance between patient and provider control may be tricky, but it can and should be done.

NY-Based HIE Captures One Million Patient Consents

Posted on September 28, 2017 I Written By

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

One of the big obstacles to the free exchange of health data is obtaining patient consent to share that data. It’s all well and good if we can bring exchange partners onto a single data sharing format, but if patients don’t consent to that exchange things get ugly. It’s critical that healthcare organizations solve this problem, because without patient consent HIEs are dead in the water.

Given these issues, I was intrigued to read a press release from HEALTHeLINK, an HIE serving Western New York, which announced that it had obtained one million patient consents to share their PHI. HEALTHeLINK connects nearly 4,600 physicians, along with hospitals, health plans and other healthcare providers. It’s part of a larger HIE, the Statewide Health Information Network of New York.

How did HEALTHeLINK obtain the consents? Apparently, there was no magic involved. The HIE made consent forms available at hospitals and doctors’ offices throughout its network, as well as making the forms available for download at whyhealthelink.com. (It may also have helped that they can be downloaded in any of 12 languages.)

I downloaded the consent form myself, and I must say it’s not complicated.

Patients only need to fill out a single page, which gives them the option to a) permit participating providers to access all of their electronic health information via the HIE, b) allow full access to the data except for specific participants, c) permit health data sharing only with specific participants, d) only offer access to their records in an emergency situation, and e) forbid HIE participants to access their health data even in the case of an emergency situation.

About 95% of those who consented chose option a, which seems a bit remarkable to me. Given the current level of data breaches in news, I would’ve predicted that more patients would opt out to some degree.

Nonetheless, the vast majority of patients gave treating providers the ability to view their lab reports, medication history, diagnostic images and several additional categories of health information.

I wish I could tell you what HEALTHeLINK has done to inspire trust, but I don’t know completely. I suspect, however, that provider buy-in played a significant role here. While none of this is mentioned in the HIE’s press release or even on its website, I’m betting that the HIE team did a good job of firing up physicians. After all, if you’re going to pick someone patients would trust, physicians would be your best choice.

On the other hand, it’s also possible patients are beginning to get the importance of having all of the data available during care. While much of health IT is too abstruse for the layman (or woman), the idea that doctors need to know your medical history is clearly beginning to resonate with your average patient.

The Subtle Signs of Sepsis Infographic

Posted on September 27, 2017 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.

Sepsis has been a major challenge in healthcare for a long time. This was highlighted really well on the Wolters Kluwer Nursing Center website:

Throughout my experience in health care over the past 30 plus years, the diagnosis of sepsis has been one of the most challenging. Sepsis affects millions of people worldwide and one in four of the people affected will die. The way we recognize and treat sepsis has changed over the years, and in January 2017, the International Guidelines for Management of Sepsis and Septic Shock: 2016 was published. This update to the 2012 guidelines, emphasizes that patients with sepsis should be viewed as having a medical emergency, necessitating urgent assessment and treatment.

According to the Advisory Board, the average direct cost per case for a primary sepsis diagnosis is $18,700, yet the typical Medicare reimbursement for sepsis and sepsis with complications is just $7,100-12,000. It’s no wonder so many hospitals are worried about sepsis.

I’ve been impressed with the way technology has been used to address the problem of Sepsis. I’ve seen a lot of companies working to use analytics to predict sepsis or identify it in real time as it’s happening. I recently saw where Wolters Kluwer partnered with Vocera to be able to connect the Sepsis risk analysis data with the providers, carrying Vocera badges, who can make the proper diagnosis and start treatment in the early stages when Sepsis is most treatable.

This kind of collaboration between healthcare IT vendors is the only way we’re going to make a dent in major healthcare problems like Sepsis. So, I applaud these two companies for working together.

For those that don’t know, September is Sepsis Awareness Month. As part of this month long recognition of Sepsis, Wolters Kluwer put together an infographic that shows the subtle signs of sepsis. While technology can certainly help with Sepsis identification and treatment, there’s still an important human element as well. This infographic highlights the signs that healthcare providers can and should look for and methods of treatment.

What efforts have you seen effective in identifying and treating sepsis in your healthcare organization?

Condition Management vs. Episodic Care Management – #HITsm Chat Topic

Posted on September 26, 2017 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.

We’re excited to share the topic and questions for this week’s #HITsm chat happening Friday, 9/29 at Noon ET (9 AM PT). This week’s chat will be hosted by Brian Eastwood (@Brian_Eastwood) from @ChilmarkHIT on the topic of “Condition Management vs. Episodic Care Management.”

The status quo of episodic care management – static care plans that rely heavily on high-touch interventions – is unsustainable if the healthcare industry truly intends to lower costs and improve outcomes. In response, the industry has seen growing interest in digital chronic condition management programs that take a more holistic and individualized approach to care. By and large, these programs use short but frequent interventions that aim to address the root causes of a condition, rather than just the symptoms themselves, in an effort to help program participants manage their condition(s) and improve their quality of life.

Given the current market, health insurers and employers are more interested in adopting condition management programs that provider organizations. This isn’t surprising – employers and insurers have clear “skin in the game” to cut costs, and providers do not – but it is nonetheless disappointing. This week’s #HITsm chat will discuss what it will take for condition management programs to gain the interest of those who deliver care, not just those who pay for care.

References:

  • Assessing the Growing Market for Condition Management Solutions: Blog post and webinar
  • Condition Management: A Healthcare Disruption That Just Might Stick: Blog post

Here are the questions that will serve as the framework for this week’s #HITsm chat:
T1: What are the key drawbacks to static condition mgmt. (both tech and workflow)? #HITsm

T2: What does holistic condition mgmt. do that episodic care mgmt. doesn’t? #HITsm

T3: How can condition mgmt. show that it’s not just a “wellness program” in new clothes? #HITsm

T4: Aside from payment reform, what will it take for provider orgs to pivot to condition mgmt.? #HITsm

T5: Where do you see the market for holistic condition mgmt. in the next 3 years? #HITsm

Bonus: Which vendors or orgs are getting condition mgmt. right? #HITsm

Upcoming #HITsm Chat Schedule
10/6 – After Death Data Donation – A #hITsm Halloween Horror Chat
Hosted by Regina Holliday (@ReginaHolliday), Founder of #TheWalkingGallery

10/13 – Role of Provider Engagement for Improving Data Accuracy
Hosted by @CAQH

10/20 – Community Sharing Chat
Hosted by the #HITsm Community

10/27 – Aggregating the Patient Perspective and Incorporating It Into Software to Change Healthcare
Hosted by Lisa Davis Budzinski (@lisadbudzinski)

We look forward to learning from the #HITsm community! As always, let us know if you’d like to host a future #HITsm chat or if you know someone you think we should invite to host.

If you’re searching for the latest #HITsm chat, you can always find the latest #HITsm chat and schedule of chats here.

Translating Social Determinants of Health Into Clinical Action

Posted on September 25, 2017 I Written By

The following is a guest blog post by Anton Berisha, MD, Senior Director, Clinical Analytics and Innovation, Health Care, LexisNexis Risk Solutions.
The medical community recognizes the importance of social determinants of health (SDOH) – social, economic and environmental conditions in which people are born, grow, live, work and age that impact their health – as significant and direct risk factors for a large number of health care outcomes.

The negative outcomes include stress, mental health and behavioral disorders, alcoholism and substance abuse, to name a few. Negative SDOH worsen a slew of major chronic conditions, from hypertension and Coronary Artery Disease to obesity; they also lead to lower patient engagement and medication adherence while increasing low-intensity ER visits and hospital admissions and readmissions.

In fact, a study shows that medical care determines only 20% of overall health outcomes while social, economic and environmental factors determine about 50% of overall health. The National Quality Forum, Centers for Disease Control and Prevention and World Health Organization have all acknowledged the importance of addressing SDOH in health care.

Not all SDOH are “created equal”

When it comes to SDOH, there is a misconception that all data regarding a person’s lifestyle, environment, situation and behaviors relate to their health. Although there is a myriad of basic demographic data, survey data and other Electronic Health Records (EHR) data available to providers today, much of it has a limited potential for identifying additional health costs and risks.

The key to addressing SDOH is to use current, comprehensive and longitudinal data that can be consistently linked to specific patient populations and provided in a standardized format. One example is attributes derived from public records data such as proximity to relatives, education, income, bankruptcy, addresses and criminal convictions.

Moreover, each SDOH attribute has to be clinically validated against actual healthcare outcomes. Clinically validating attributes is critical to successful predictive analytics because some attributes do not correlate strongly to health outcomes.

For example, while knowing how close an individual’s nearest relative or associate lives to the patient does correlate to health outcomes; knowing how many of those relatives or associates have registered automobiles does not. Even when attributes are clinically validated, different attributes correlate to different outcomes with different accuracy strengths.

Translating SDOH into actionable intelligence

After SDOH have been correlated to healthcare outcomes, providers have two implementation options. One is to use relevant individual SDOH attributes per outcome in clinical and analytic models to better assess and predict risk for patients. Another is to use SDOH as part of risk scores estimating specific healthcare risks; for e.g., to estimate an individual’s total health care risk over the next 12 months based on cost; a 30-day readmission risk; or a patient engagement score.

Risk estimation can be done either in combination with other types of legacy healthcare data, such as claims, prescription and EHR data or with SDOH alone, in the absence of medical claims.

Recently, a client of LexisNexis® Health Care did an independent study to evaluate the impact and usefulness of Socioeconomic Health Score (SEHS) in risk assessment for several key chronic conditions, when no other data are available. Findings proved that the top decile of SEHS captures significantly more members with given conditions than the bottom decile. The study concluded that the difference was important and very helpful in estimating risks in a newly acquired population without legacy healthcare data.

Integrating SDOH into clinical workflows and care recommendations

Validated SDOH can be presented in a form of risk drivers or reason codes directing the clinician toward the most important factors influencing a given negative outcome for each patient: income, education, housing or criminal records.

The risk drivers and reason codes can then be integrated into workflows within the clinician’s IT systems, such as the EHR or care and case management, in the form of an easy-to-understand presentation. It could be a data alert that is customizable to patients, treatments and conditions, helping the provider make score-based decisions with greater accuracy and confidence. At this point, the SDOH information becomes actionable because it has the following characteristics:

  • It is based on hard facts on every individual.
  • It is based on correlation and statistical significance testing of large pools of patients with similar behavior.
  • It provides clear and understandable reason codes driving the negative outcomes.
  • It can be tied to intervention strategies (outlined below) that have demonstrated positive results.

Clinicians empowered with actionable SDOH information can modify their interventions and follow-up strategies accordingly. Based on resources at hand, patients living in negative SDOH could be either properly managed by clinicians themselves or other medical staff, social workers and newly created roles such as health coaches. Sub-populations at risk could benefit from access to community resources to get help with housing (permanent supportive housing for homeless), transportation, education, childcare and employment assistance.

Moreover, SDOH are particularly effective in helping providers develop a population health management strategy fueled by prioritized tactics for preventive care. Tactics can range from promotion of healthy food to free screening services. For patients with chronic diseases (who can typically be managed appropriately when they adhere to therapy and healthy lifestyle choices), SDOH-informed interventions can help keep them under control and potentially reduce severity. For patients recently released from the hospital, aftercare counseling could prevent complications and readmissions.

To sum it up

Socioeconomic data is a vital force for healthcare risk prediction as it provides a view into the otherwise hidden risks that cannot be identified through traditional data sources. When SDOH are clinically validated and correlated to healthcare outcomes, they help providers better understand an individual’s risk level and address it through appropriate intervention strategies.

E-Patient Update: Sometimes Tech Gets In The Way

Posted on September 22, 2017 I Written By

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

Being such an enthusiastic tech user, I tend to assume that adding technology to the healthcare equation is a plus in almost any situation. Why not automate scheduling?  Data gathering? Pharmacy?

To me, it’s always seemed like a no-brainer that tech adoption works to my advantage as a patient. The more I can avoid going through basic motions manually, the better processes work, giving me more time to spend with my clinicians. Right?

Apparently, not so right. When you take patients into account, sometimes doing transactions the old-fashioned way may actually be more efficient – or at least more flexible – than running things through an automated process. If nothing else, it may be easier to accommodate patients if you don’t have to run them through your workflow.

That, at least, is the lesson I’ve gleaned from studying the day-to-day flow at Kaiser Permanente, where I get all of my healthcare. After watching Kaiser employees work, and asking a few unobtrusive questions, I’ve come to believe that going offline may actually be better in some situations.

Tech-friendly, but not tech-dependent

Now, make no mistake: Kaiser isn’t in the stone age technically. For example, it seems to build most of its clinical operations around what is reputed to be the mother of all Epic installations. (Back in the day, it was rumored that Kaiser spent roughly $4 billion to roll out Epic, a massive sum even by national organization standards.)

Throughout my care process, the fact that clinicians and support staffers are all on Epic has played to my advantage, particularly given that I have a few chronic illnesses and see several specialists. I’ve also benefited from other Kaiser technology, such as kiosks which automate my check-in process for medical visits.

In addition, I’ve gotten a lot of benefits from using Kaiser’s robust web portal, which offers the capability to exchange email messages with clinicians, set appointments, pay premiums and co-pays, order and track prescriptions and check test results.

All that being said, I’ve encountered manual processes at many steps in my journey through the Kaiser system. While some of these processes seem wasteful – such as filling out a standard pre-visit form on paper – others turn out to be more useful than I had expected.

‘People forget their card’

One situation where technology might not be needed is taking people into the doctors’ suite for consults. In theory, Kaiser could set up an airport- or DMV-style ticker letting people know when their doctor was ready to see them, but having nurses yell last names seems to work fine. I’d file this under “if it ain’t broke don’t fix it.”

The pharmacy is another area relying on a mix of low- and high-tech approaches. Interestingly, the pharmacy offers an airport-like board displaying the names of patients whose meds are ready. But when it comes to retrieving patient info and dispensing drugs, the front-line staffers enter the patient numbers by hand. I would have expected there to be a barcode on the membership card, but no dice.

According to one pharmacy tech, it has to be this way. “People forget their [Kaiser member] card all of the time,” she said. “We can’t assume members have It with them.”

These are just a couple of examples, but to me they’re telling. I may be missing something here, but it seems to me that Kaiser’s approach is practical. I’d still like to automate everything in my healthcare world, but obviously, that doesn’t work for everyone. Clearly, offline patient management models still matter.

Public Health Agencies Struggle To Integrate With HIEs

Posted on September 21, 2017 I Written By

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

New research by ONC suggests that while public health agencies might benefit from connecting with HIEs, there are still some significant barriers many need to address before doing so.

Public health agencies at both the state and local level collect information from providers as part of conducting disease surveillance activities and maintaining data registries. Though some of these registries are common – notably those focusing on childhood immunizations, birth defects and cancer—the agencies’ technical infrastructure and data formats still vary. This makes sharing data between them difficult.

One alternative to cumbersome data matching between agencies is for the agencies to integrate with an HIE. According to the ONC report, public health researchers have begun to find that at least some of the time, the data they get from HIE organizations is richer than data from clinical systems. Not only that, when public health agencies integrate their information systems with HIEs, it can help them conduct many of their functions more effectively. However, it’s still unusual to find HIE-connected agencies as of yet.

In its new report, ONC outlines what it learned about what the agencies hoped to accomplish with HIE integration and how they moved ahead with integration. To find this out, ONC contracted with Clinovations Government + Health, which participated in discussions with eight entities and analyzing more detailed information on 10 others.

Virtually all respondents had two goals for HIE integration: 1) Minimizing the number of connections needed to link providers, HIEs and agencies and 2) Helping providers meet public health requirements for Medicare and Medicaid EHR incentive programs. A small subset also said that over the longer term, they wanted to create a sustainable platform for clinical and public health exchange which could support enhanced analytics and quality measurement.

Not surprisingly, though, they face considerable challenges in making HIE integration actually happen. In most cases, technology issues were possibly the toughest nut to crack, and almost certainly the most complex. To connect with an HIE, agencies may confront incompatible transport and messaging protocols, standards problems, data classification and coding issues, inconsistent data quality, and their often-inflexible legacy systems, to name just a few of the many problems ONC cites.

As if that weren’t enough, the agencies may not have the funding in place to take on the integration effort, and/or lack a stable funding stream; don’t have the kind of cross-functional leaders in place needed to integrate their systems with HIEs; grapple with complicated patient data privacy and security issues; and bump up against state laws limiting data sharing methods.

However, through its research, the ONC did gather some useful feedback on how the agencies were coping with the long list of HIE integration challenges they face. For example, to win over the support of policymakers, some agencies have emphasized that they’ll be able to use HIE data for higher-level analytics and quality measures. The respondents also noted that HIE integration got more internal support when they got buy-in from top leaders and second-tier leaders have project management, technical and policy skills.

Given these odds, it’s little wonder that the number of public health agencies successfully integrating with HIEs is still small. That being said, there’s good reason for them to keep pushing for integration, so their number is likely to grow over the next few years.

Will Medical Device Makers Get Interoperability Done?

Posted on September 20, 2017 I Written By

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

Most of the time, when I think about interoperability, I visualize communication between various database-driven applications, such as EMRs, laboratory information systems and claims records. The truth is, however, that this is a rather narrow definition of interoperability. It’s time we take medical device data into account, the FDA reminds us.

In early September, the FDA released its final guidance on how healthcare organizations can share data between medical devices and other information systems. In the guidance, the agency asserts that the time has come to foster data sharing between medical devices, as well as data exchange between devices and information systems like the ones I’ve listed above.

Specifically, the agency is offering guidelines to medical device manufacturers, recommending that they:

  • Design devices with interoperability in mind
  • Conduct appropriate verification, validation and risk management to ensure interoperability
  • Make sure users clearly understand the device’s relevant functional, performance and interface characteristics

Though these recommendations are interesting, I don’t have much context on their importance. Luckily, Bakul Patel has come to the rescue. Patel, who is associate director for digital health the FDA‘s Center for Devices and Radiological Health, offered more background on medical device interoperability in a recent blog entry.

As the article points out, the stakes here are high. “Errors and inadequate interoperability, such as differences in units of measure (e.g., pounds vs. kilograms) can occur in devices connected to a data exchange system,” Patel writes. Put another way, in non-agency-speak, incompatibilities between devices and information systems can hurt or even kill patients.

Unfortunately, device-makers seem to be doing their own thing when it comes to data sharing. While some consensus standards exist to support interoperability, specifying things like data formats and interoperability architecture design, manufacturers aren’t obligated to choose any particular standard, Patel notes.

Honestly, the idea of varied medical devices using multiple data formats sounds alarming to me. But Patel seems comfortable with the idea. He contends that if device manufacturers explain carefully how the standards work and what the interface requires, all will be well.

All told, If I’m understanding all this correctly, the FDA is fairly optimistic that the healthcare industry can network medical devices on the IoT with traditional information systems.

I’m glad that the agency believes we can work this out, but I’d argue that such optimism may be premature. Patel’s assurances raise a bunch of questions for me, including:

  • Do we really need another set of competing data exchange standards to resolve, this time for medical device interoperability?
  • If so, how do we lend the consensus medical device standards with consensus information system standards?
  • Do we need to insist that manufacturers provide more-consistent software upgrades for the devices before interoperability efforts make sense?

Hey, I’m sure medical device manufacturers want to make device-to-device and device-to-database data sharing as simple and efficient as possible. That’s what their customers want, after all.

Unfortunately, though, the industry doesn’t have a great track record even for maintaining their devices’ operating systems or patching industrial-grade security holes. Designing devices that handle interoperability skillfully may be possible, but will device-makers step up and get it done anytime soon?

The Impact of HIEs in Natural Disasters – #HITsm Chat Topic

Posted on September 19, 2017 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.

We’re excited to share the topic and questions for this week’s #HITsm chat happening Friday, 9/22 at Noon ET (9 AM PT). This week’s chat will be hosted by Brian Mack (@BFMack) from @GLHC_HIE on the topic of “The Impact of HIEs in Natural Disasters.”

On August 29th, 2005, Hurricane Katrina, a category 3 storm, made landfall in SE Louisiana. Torrential rain and sustained winds exceeding 110 MPH quickly overwhelmed the protective measures in place, and the subsequent storm surge breached levies and flooded huge swaths of New Orleans and surrounding areas. Mass-devastation across Louisiana and Mississippi contributed to the deaths of nearly 1,500 people, forced tens of thousands more from their homes, and caused an estimated $108 billion in property damage. At that time, only 10% of physicians were actively using electronic medical records, and electronic health information exchange was still was in its infancy. An incalculable number of paper health records were lost forever. The lack of access to patient information during and following the storm significantly hindered medical response efforts, and required years to replace.

Fast forward to Aug. 24th-26th, 2017, when Hurricane Harvey, an even larger (Cat. 4) storm struck Southern Texas, and dumped more than 40 inches of rain on the greater Houston area. While Harvey has been described as “Houston’s Katrina” in terms of its intensity and impact, the story was significantly different for the healthcare delivery system. Two health information exchanges in the region, the Greater Houston Healthconnect (GHHC) and Healthcare Access San Antonio (HASA) worked together to assist both those who stayed through the storm, as well as those who were evacuated. GHHC staff actually shuttled between shelters in the Houston area, overseeing the set-up of HIE portals, to help clinicians provide care for patients. Providers were able to maintain access to patient records, even from remote locations, using laptops and WiFi to access EHR systems in the normal way. As a result, the response to medical needs, and continuity of care for the population impacted by Harvey across Texas was seamlessly maintained at a very high level.

This week’s #HITSM Twitter chat will discuss the opportunities, challenges, and value of community-based Health Information Exchange in connecting the “last mile” of interoperability, particularly in emergency situations.

Some additional reading:

Here are the questions that will serve as the framework for this week’s #HITsm chat:
T1: What lesson(s) should we, as participants in the healthcare ecosystem, take away from events like Hurricanes Katrina & Harvey? #HITsm

T2: What roles do/should stakeholders: government (local, state, federal), HC providers, private sector, citizenry play in assuring adequate preparation for disasters? #HITsm

T3: What responsibilities do health IT infrastructure vendors (EHR), and Health Information Exchange have in supporting successful emergency response? #HITsm

T4: How do community based HIE’s differ from national interoperability efforts and/or vendor based solutions in emergency situations? #HITsm

T5: What examples from your own local communities can you share where community-based health information exchange either made a difference, or COULD have made a difference in responding to a public emergency? #HITsm

Bonus: Aside from the basic task of networking disparate healthcare providers, how could Health Information Exchange contribute to better connected communities? #HITsm

Upcoming #HITsm Chat Schedule
9/29 – Condition Management vs Episodic Care Management
Hosted by Brian Eastwood (@Brian_Eastwood) from @ChilmarkHIT

10/6 – After Death Data Donation – A #hITsm Halloween Horror Chat
Hosted by Regina Holliday (@ReginaHolliday), Founder of #TheWalkingGallery

10/13 – Role of Provider Engagement for Improving Data Accuracy
Hosted by @CAQH

We look forward to learning from the #HITsm community! As always, let us know if you’d like to host a future #HITsm chat or if you know someone you think we should invite to host.

If you’re searching for the latest #HITsm chat, you can always find the latest #HITsm chat and schedule of chats here.

Searching EMR For Risk-Related Words Can Improve Care Coordination

Posted on September 18, 2017 I Written By

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

Though healthcare organizations are working on the problem, they’re still not as good at care coordination as they should be. It’s already an issue and will only get worse under value-based care schemes, in which the ability to coordinate care effectively could be a critical issue for providers.

Admittedly, there’s no easy way to solve care coordination problems, but new research suggests that basic health IT tools might be able to help. The researchers found that digging out important words from EMRs can help providers target patients needing extra care management and coordination.

The article, which appears in JMIR Medical Informatics, notes that most care coordination programs have a blind spot when it comes to identifying cases demanding extra coordination. “Care coordination programs have traditionally focused on medically complex patients, identifying patients that qualify by analyzing formatted clinical data and claims data,” the authors wrote. “However, not all clinically relevant data reside in claims and formatted data.”

For example, they say, relying on formatted records may cause providers to miss psychosocial risk factors such as social determinants of health, mental health disorder, and substance abuse disorders. “[This data is] less amenable to rapid and systematic data analyses, as these data are often not collected or stored as formatted data,” the authors note.

To address this issue, the researchers set out to identify psychosocial risk factors buried within a patient’s EHR using word recognition software. They used a tool known as the Queriable Patient Inference Dossier (QPID) to scan EHRs for terms describing high-risk conditions in patients already in care coordination programs.

After going through the review process, the researchers found 22 EHR-available search terms related to psychosocial high-risk status. When they were able to find nine or more of these terms in the patient’s EHR, it predicted that a patient would meet criteria for participation in a care coordination program. Presumably, this approach allowed care managers and clinicians to find patients who hadn’t been identified by existing care coordination outreach efforts.

I think this article is valuable, as it outlines a way to improve care coordination programs without leaping over tall buildings. Obviously, we’re going to see a lot more emphasis on harvesting information from structured data, tools like artificial intelligence, and natural language processing. That makes sense. After all, these technologies allow healthcare organizations to enjoy both the clear organization of structured data and analytical options available when examining pure data sets. You can have your cake and eat it too.

Obviously, we’re going to see a lot more emphasis on harvesting information from structured data, tools like artificial intelligence and natural language processing. That makes sense. After all, these technologies allow healthcare organizations to enjoy both the clear organization of structured data and analytical options available when examining pure data sets. You can have your cake and eat it too.

Still, it’s good to know that you can get meaningful information from EHRs using a comparatively simple tool. In this case, parsing patient medical records for a couple dozen keywords helped the authors find patients that might have otherwise been missed. This can only be good news.

Yes, there’s no doubt we’ll keep on pushing the limits of predictive analytics, healthcare AI, machine learning and other techniques for taming wild databases. In the meantime, it’s good to know that we can make incremental progress in improving care using simpler tools.