Tag: EMR

Notes & Links: August 26, 2013

Consumers’Perceptions of Patient-Accessible Electronic Medical Records
Zarcadoolas, Vaughon, et. al publishing in JMIR completed a qualitative study to to identify vulnerable consumers response to patient portals and how they perceived the value and utility. 

The authors do an excellent job of defining an electronic health tool and patient portal with the bottom line being “allowing consumers to take greater control of their health information by changing traditional top-down (doctor to patient) methods of health communication and improving satisfaction with provider communications and overall care”. This is the outcome we’ve all been seeking in healthcare. 

The authors take care to clearly establish how consumers are more and more interested in accessing their personal health information online and reference a Markle Survey on Health in A Networked Life reports that nearly 70% of the publish and 65% of physicians believe patient should be able to access and retain their health records. In addition the authors note and examine the fact their is a vulnerability of certain populations to disparities in health outcomes and quality care. These groups being poor, immigrants, and lacking English proficiency. 

The authors examined participants record-keeping behaviors, sources of health information and initial response to the idea of patient portals. The Key Themes that emerged from this study were:

  • Consumer/Patient Empowerment-“Information is Power”
  • Extending the Doctor’s Visit/Enhancing Communication with HCP
  • Literacy and Health Literacy (The authors capture critical information that will drive these results)
  • Prevention and Health Maintenance
  • Privacy and Security Concerns
  • Response to the Concept of Patient Portals with More Information: Post Demonstration

Conclusion 
The intent and promise of patient portals is that they will help engage people with their health, improve preventive care behaviors, and permit better management of chronic conditions. A handful of recent studies have begun to examine patients’ uptake of portals as well as patients’ perceptions and assessments of their actual use. Consistent with the views of our study participants, users report finding great value in patient portals [73], a perception shared by a wide range of patients, including those with mental health and substance abuse issues [68] as well as patients with HIV [67]. In general, patients report that portals positively impact communication with providers, and improved knowledge, empowerment, and self-care.

This is a great study and will help those of us looking to improve and expand patients involved in their healthcare and their engagement with their HCP. Another paper to print read and save. Their conclusions are more extensive and deserve to read and considered. 

Why Doctors Should Stay Out of The Business of Building EHRs
Fred Trotter writing on The Health Care Blog addresses the fact many physicians are ‘writing their EHR’ from scratch and how they have to step away from the screen and leave it to the professionals. His primary argument is that we need to have these tools built by those who know how. 

A doctor developing a new EHR system from scratch, by themselves, without extensive Health IT programming experience is in over their head. If they continue to develop an EHR, even after being warned of the dangers here, then this is hubris.

Ask yourself: Are you absolutely sure that this action is not a fundamental violation of the oath that you took when you became a doctor?

I would take it a step further and consider the article above from JMIR on how a well developed and crafted EMR along with a patient portal can change care and the patient physician engagement model. This further speaks to the need for educators and communicators to build and drive EMR.

By the way the comments are one big pissing battle which should not be confused with the need to use EMRs to drive engagement, patient care, learning, and outcomes.  

Notes & Links: August 22, 2013

The Emergent Discipline of Health Web Science

Luciano, Cumming, et. al from Web Science Research Center, Tetherless World Constellation, Rensselaer Polytechnic Institute published a viewpoint examining how Web Science in relation to health maintenance, health care, and health policy opens the door to Health Web Science as a sub discipline of Web Science. It is different from Medicine 2.0 but fits within. 

This is one paper that you may want to print and read over and over and examine. It is rich with ideas not just for the Web but, ideas that we can use to create new, better, smarter, and practical patient/HCP engagement and drive improved outcomes. 

Understanding and appreciating the overlapping yet divergent disciplinary orientation of Health Web Science (HWS) compared to related research domains motivates specific research efforts around better utilization of, innovation on, and communication over and within the Web. 

They ask what is Health Web Science. Their answer is multi layered but this sums it up the best:

The distributed, adaptable, and highly flexible nature of the Web facilitates the shift from the current model of a centralized, hospital-focused and provider-centric infrastructure, to one where the hospital plays a coordinating role and interacts with the “long tail” of the patient population in a more distributed manner, such as through a peer-to-peer model [12]. Moreover, the Web can play a useful role in tailoring health care to individual needs based not only on medical conditions but also on personal, family, and social factors. Thus, HWS is integral to exploring options and finding solutions to the health problems of the 21st century in both the developing and developed worlds. HWS will enable this shift to a more patient-centric model, as it helps provide the evidence base of which technologies designs and structures work best where and when, under what conditions, and for whom. 

They continue with a discussion of Web Observatories which is interesting just from a language use. For them it is ‘an integrated collection of data sources and data analysis tools that enables observation and experimentation for Web study‘. They offer the challenge that most of the data residing on the Web is difficult to access and use. We need to change that if we want to create ‘software application that use the transformed collection of datasets‘. 

Other discussions they have are:

  • Social Networks in Health Web Science
  • Patient Engagement Through Citizen Science and Crowdsourcing
  • Sensors, “Smart” Technologies, and “Expert Patients”
  • “Big Data”, Semantics, and Other Integration Technologies
  • Rapid, Automated, Contextualized Knowledge Discovery and Application

This is worth reading just to know what the hell is citizen science or learning about big data and semantics. More importantly it is points to our future in healthcare and the Web. I would imagine all those 20 somethings coding apps for healthcare may not read this. 

Antipsychotic Drugs Raise Diabetes Rich in Kids’, Study Finds 

This title popped up in an email from the Wall Street Journal. It was behind the WSJ paywall so I am resorting to WebMD whose title read “Antipsychotic Drugs May Triple Kids’ Diabetes Risk”. In either case my gut check was, like we didn’t know this? We knew for years the cardiovascular risk of antipsychotic drugs in adults and weight gain etc. etc. So why wouldn’t this apply to children? Especially since these drugs are off label for children. 

“We found that children who received antipsychotic medications were three times as likely to develop type 2 diabetes,” Ray said. “It’s well known that antipsychotics cause diabetes in adults, but until now the question hadn’t been fully investigated in children.”

The study published in JAMA Psychiatry (also behind a paywall), looked at 29,000 children aged 6 to 24 in Tennessee Medicaid program who recently started taking antipsychotic drugs for other then schizophrenia or related psychoses. 

That is only one state. That is a socioeconomic group of the poorest and most disadvantaged. Stop and consider 29k recently dx in one state. And most of this prescribing is off label for most. That’s a whole different discussion.

The findings should lead doctors and parents to question the “off-label” use of antipsychotic drugs for conditions other than schizophrenia and psychosis, said Dr. Ken Duckworth, medical director of the National Alliance on Mental Illness.

You think? 

More Unintended Consequences of Digital Data: An EMR Gave My Patient Syphilis

How can you not want to read this. You know you do. Just goes to show us that a great headline drives readership. Think about the NY Post famous headline “Headless Body in Topless Bar”. 

Val Jones, MD writing in Better Health presents his experiences with EMR and it is eye opening. I have largely steered away from getting caught up in HCP bitching about going EMR since change for the better is not easy. Suck it up and do it. Dr. Jones clearly states up front that he wanted this to happen.

I used to be a big believer in the transformative power of digital data in medicine. In fact, I devoted the past decade of my life to assisting the “movement” towards better record keeping and shared data. It seemed intuitive that breaking down the information silos in healthcare would be the first logical step in establishing price transparency, promoting evidence-based practices, and empowering patients to become more engaged in their care decisions. Unfortunately I was very wrong.

So let’s peek behind the curtain on the ground of EMR. 

In one of my recent notes the Indian transcriptionist misheard my word for “hydrocephalus” and simply entered “syphilis” as the patient’s chief diagnosis. If I hadn’t caught the error with a thorough reading of my reformatted note, who knows how long this inaccurate diagnosis would have followed the poor patient throughout her lifetime of hospital care?

I am a crap proof reader this is a huge responsibility for HCP to catch these errors and the time it takes as well to proof the EMR against the actual record. In advertising, CME, etc. proof reading is critical. In healthcare it is life and death. 

Situated in a dark room surrounded by enough flat panel monitors to put a national cable network to shame, about 40 young tech support engineers were furiously working to keep the EMR from crashing on a daily basis – an event which halts all order processing from the ER to the ICU. Ominous reports of the EMR’s instability were piped over the entire hospital PA system, warning staff when they could expect screen freezes and data entry blockages. Doctors and nurses scurried to enter their orders and complete documentation during pauses in the network overhaul. It was like a scene from a futuristic movie where humans are harnessed for work by a centralized computer nexus.

And we wonder why hospitals charge so much for knee replacement. And to think once this effort is completed those rooms, equipment, and personal will be ‘downsized’ and savings realized is dead wrong. 

I give Jones credit and credibility because he started he was and is an advocate and now sees how a good idea is being ruined by crapy execution. 

Karl Rove’s Health Care ‘Ideas’

Aaron Carroll writing in The Incidental Economist deconstructs Karl Rove’s WSJ article ‘Republican Do Have Ideas for Health Care”

Carroll goes basically point by point examining and referencing Rove’s statements. This is well written and can help us all see some of the issues, needs, and solutions that must be addressed in healthcare. As usual Carroll states his view well and supports it equally well. Let me give you the money shot: 

No matter what Mr. Rove says, however, none of these constitute real reform. None of them will significantly decrease the number of uninsured in this country. None of them will help people with chronic conditions to get care. We may lower spending, but by making things worse for the people who need care the most. It’s easy to insure people who are healthy; it’s also cheap. That’s not the point of the health care system, though. Real reform tries to get care to those who need it most. That’s much harder, and it can cost more money, but that’s what we need.

That is it in a nutshell, caring for those who need it and knowing it will cost more money. 

Learner First and Foremost, Patient Second

I’m a staunch believer in adult learning and how when the theory is put into healthcare practice it can improve patient care and create durable outcomes for the patient, aid the HCP in improving patient management, and help lower utilization costs.  

This weekend I read with rapped attention Jim Rutenberg’s article in the New York Times Magazine “Data You Can Believe In” and last week I listened to Jonathan Alter’s interview on Fresh Air about the Obama reelection. Both spoke in great detail about how the analysis and use of data was the difference in victory for the Obama win the 2012 election.

What does this have to do with healthcare outcomes? I was struck by how the Obama campaign accessed Facebook data, identified people who supported the President, and were able to have those supporters reach out to friends on the fence or not active become active. Further they were able to identify better tools to find and reach uncommitted voters by comparing TV cable box data with lists of uncommitted voters in order to change their behavior.

In healthcare we have been striving to improve physician patient engagement while recognizing that more and more patients and caregivers are searching the WWW to learn about their health. All the while providers and HCP are moving toward EMR. This is creating one the richest databases in healthcare.

The questions becomes; how can we analyze current patient files within a provider system (I would submit that is being done), and take subsets of that data to identify areas where learning would yield the greatest improvement in patient care, and finally how do we identify (think set top box) who would be the most active learners and least active? How can using data as they did in the Obama campaign improve patient physician engagement?

We can look at data within the provider system to determine which patients are yielding the best outcomes with the lowest utilization cost. And as we move further away from best outcomes to not so good outcomes within the same CD9 code we can identify what the differences are in age, gender, socioeconomic data etc. This will yield a picture on who is doing well and who is not while hinting at why and what are the differences between great and not great. We have a map per disease of behaviors and a model relative to outcomes identifying key demographics.

I don’t believe we will learn what learning behavior or motivation is present from this analysis. What we need to add to patient EMR is data on the patient as an active learner, how, why, where, etc. This is a simple and easy to administer inventory which becomes our set top box of user behavior around learning. It tells us who is learning and where. Are they active learners or not. It’s that extra bit of knowledge that can be used to intervene in disease management and its progress. Matching learning behavior with outcomes with patients would be powerful tool to know where we want to apply pressure to foster and drive healthcare change at the patient level.

Keep in mind I’ve lead this post with the patient first and added patient as a learner. Now let’s reverse that to lead with the learner as a patient. It would be easy to use this data to identify the characteristics of learners who wants to know more about their disease, think active learners.

Now consider a provider or HCP offering this well identified and targeted group improved knowledge access and uptake. Not just better care but becoming learning partner with the patient. If providers can target learners better and either bring new patients into their system or better anchor current patients to improve outcomes and lower cost. Isn’t that what we want from healthcare, a long-term productive and learning driven relationship? Healthcare is not passive; it is an active learning relationship between peers with different skills sharing decision-making. 

The proviso for all of the above, any data analysis would work within HIPAA guidelines etc.