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Medical Practice Use Of Automated Claims Options Growing Slowly

Posted on June 25, 2018 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 study by a healthcare industry group has concluded that medical and dental practices are processing claims manually rather than going for full automation, a trend which is robbing the industry of very high levels of potential savings. While many physicians and dentists are using web portals to process claims, in most cases they haven’t reached the ”set it and forget it” level, a trend which could undercut possible savings.

The group, CAQH, tracks health plan and healthcare provider adoption of electronically-based administrative transactions for medical and dental practices. CAQH’s research estimates the time required for providers administrative transactions, including verifying a patient’s insurance coverage, sending and receiving payments, checking on the status of claims and handling prior authorization processes.

Its research concluded that despite the potential rewards, the medical and dental practices made only a modest level of progress in automating claims and related business processes over the past year. According to CAQH calculations, practices are still leaving roughly $11.1 billion in savings on the table, an estimate which has climbed by $1.8 billion over the prior year.

If these savings are realized, the majority ($9.5 billion) would end up in providers’ hands. However, many practices just haven’t gotten there yet.

A rise in portal use is certainly an improvement over paper-based claims processes. In fact, some of the increase in potential savings noted by the study is being created by a rise in online portal use.

However, providers’ adoption of fully-electronic claims is basically growing only a small amount or even declining for most transactions that can be done via a portal. For example, for prior authorizations, a big increase in portal use correlated with the decline in the adoption of fully-electronic transactions.

For CAQH, the endgame is getting all providers to automate claims processes complete, so the modest to flat growth in automated claims transactions is not exactly good news. In fact, it’s not a winning situation for medical practices either. According to the group’s estimates, each manual transaction costs practices $4.40 more than each electronic transaction and eats up five more minutes of provider time, which can create a real drag on profits.

Meanwhile, processing a single claim electronically through its lifecycle would save medical practices almost 40 minutes on average, and more than $15 in direct cost savings. Meanwhile, processing a single dental claim from start to finish could save dental practices almost 30 minutes on average and almost $11.75.

The CAQH press release doesn’t spell out what’s holding dentists and doctors back from automating the claims process completely, but it’s not hard to guess was going on. Unlike some providers, medical and dental practices typically don’t have deep pockets or large staff they can make this transition. If health plans want these providers to get on board, they’ll probably have to help them make the transition. However, even health plans haven’t invested in automated claims processing enough either.

Competition Heating Up For AI-Based Disease Management Players

Posted on May 21, 2018 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.

Working in collaboration with a company offering personal electrocardiograms to consumers, researchers with the Mayo Clinic have developed a technology that detects a dangerous heart arrhythmia. In so doing, the two are joining the race to improve disease management using AI technology, a contest which should pay the winner off handsomely.

At the recent Heart Rhythm Scientific Sessions conference, Mayo and vendor AliveCor shared research showing that by augmenting AI with deep neural networks, they can successfully identify patients with congenital Long QT Syndrome even if their ECG is normal. The results were accomplished by applying AI from lead one of a 12-lead ECG.

While Mayo needs no introduction, AliveCor might. While it started out selling a heart rhythm product available to consumers, AliveCor describes itself as an AI company. Its products include KardiaMobile and KardiaBand, which are designed to detect atrial fibrillation and normal sinus rhythms on the spot.

In their statement, the partners noted that as many as 50% of patients with genetically-confirmed LQTS have a normal QT interval on standard ECG. It’s important to recognize underlying LQTS, as such patients are at increased risk of arrhythmias and sudden cardiac death. They also note that that the inherited form affects 160,000 people in the US and causes 3,000 to 4,000 sudden deaths in children and young adults every year. So obviously, if this technology works as promised, it could be a big deal.

Aside from its medical value, what’s interesting about this announcement is that Mayo and AliveCor’s efforts seem to be part of a growing trend. For example, the FDA recently approved a product known as IDx-DR, the first AI technology capable of independently detecting diabetic retinopathy. The software can make basic recommendations without any physician involvement, which sounds pretty neat.

Before approving the software, the FDA reviewed data from parent company IDx, which performed a clinical study of 900 patients with diabetes across 10 primary care sites. The software accurately identified the presence of diabetic retinopathy 87.4% of the time and correctly identified those without the disease 89.5% of the time. I imagine an experienced ophthalmologist could beat that performance, but even virtuosos can’t get much higher than 90%.

And I shouldn’t forget the 1,000-ton presence of Google, which according to analyst firm CBInsights is making big bets that the future of healthcare will be structured data and AI. Among other things, Google is focusing on disease detection, including projects targeting diabetes, Parkinson’s disease and heart disease, among other conditions. (The research firm notes that Google has actually started a limited commercial rollout of its diabetes management program.)

I don’t know about you, but I find this stuff fascinating. Still, the AI future is still fuzzy. Clearly, it may do some great things for healthcare, but even Google is still the experimental stage. Don’t worry, though. If you’re following AI developments in healthcare you’ll have something new to read every day.

AI Software Detects Diabetic Retinopathy Without Physician Involvement

Posted on April 27, 2018 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 FDA has approved parent company IDx to market IDx-DR, the first AI technology which can independently detect diabetic retinopathy. The software can make basic recommendations without any physician involvement.

Before approving the software, the FDA reviewed data from a clinical study of 900 patients with diabetes across 10 primary care sites. IDx-DR accurately identified the presence of diabetic retinopathy 87.4% of the time and accurately identified those without the disease 89.5% of the time. In other words, it’s not perfect but it’s clearly pretty close.

To use IDx-DR, providers upload digital images of a diabetic patient’s eyes taken with a retinal camera to the IDx cloud server. Once the image reaches the server, IDx-DR uses an AI algorithm to analyze the images, then tells the user whether the user has anything more than mild retinopathy.

If it finds significant retinopathy, the software suggests referring the patient to an eye care specialist for an in-depth diagnostic visit. On the other hand, if the software doesn’t detect retinopathy, it recommends a standard rescreen in 12 months.

Apparently, this is the first time the FDA has allowed a company to sell a device which screens and diagnoses patients without involving a specialist. We can expect further AI approvals by the FDA in the future, according to Commissioner Scott Gottlieb, MD. “Artificial Intelligence and Machine Learning hold enormous promise for the future of medicine,” Gottlieb tweeted. “The FDA is taking steps to promote innovation and support the use of artificial intelligence-based medical devices.”

The question this announcement must raise in the minds of some readers is “How far will this go?” Both for personal and clinical reasons, doctors are likely to worry about this sort of development. After all, putting aside any impact it may have on their career, they may be concerned that patient will get short-changed.

They probably don’t need to worry, though. According to an article in the MIT Technology Review, a recent research project done by Google Cloud suggests that AI won’t be replacing doctors anytime soon.

Jia Li, who leads research and development at Google Cloud, told a conference audience that while applying AI to radiology imaging might be a useful tool, it can automate only a small part of radiologists’ work. All it will be able to do is help doctors make better judgments and make the process more efficient, Li told conference attendees.

In other words, it seems likely that for the foreseeable future, tools like IDx-DR and its cousins will help doctors automate tasks they didn’t want to do anyway. With any luck, using them will both save time and improve diagnoses. Not at all scary, right?

EHR Usability Problems Linked To Potential Patient Harm

Posted on April 9, 2018 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.

If you’re a clinician, you’ve probably always felt that EHR usability problems were a factor in some patient care glitches. Now, there’s some research backing up this hunch. While the numbers of EHR-specific events represented in the study are relatively low, its lead researcher said that it probably underestimated the problem by several orders of magnitude.

The study, which was profiled in the American Journal of Managed Care concluded, that at least some patient safety events were attributable to usability issues. The study, which was just published in JAMA, involved the analysis of nearly 2 million reported safety events taking place from 2013 to 2016 in 571 healthcare facilities in Pennsylvania. The data also included records from a large mid-Atlantic multi-hospital academic medical system.

Of the 1.735 million reports, 1,956 (0.11%) directly mentioned an EHR vendor or product. Also, 557 (0.03%) include language explicitly suggesting that usability concerns played a role in possible patient harm, AJMC reported.

Meanwhile, of the 557 events, 84% involved a situation where patients needed to be monitored to preclude harm, 14% of events potentially caused temporary harm, 1% potentially caused permanent harm and under 1% (2 cases), resulted in death.

The lead researcher on the study, Raj Ratwani, PhD, MA, told the AJMC that these issues are unlikely to resolve unless EHR vendors better understand how providers manage the rollout of their products.

Even if the vendor has done a good job with usability, he suggests, healthcare organizations adopting the platform sometimes make changes to the final configuration during their implementation of the product, something which could be undoing some of the smart usability choices and safety choices made by the vendor. “We really need to focus on the variability that’s occurring during the implementation and ensuring that vendors and providers are working together,” Ratwani said.

Along the way, it’s worth pointing out that the researchers themselves feel that the actual number of usability-related patient safety events could be far higher than the study would suggest.

Ratwani cautioned that he and his team took a “very, very conservative approach” to how they analyzed the patient safety reports. In fact, he suspects that since patient safety events are substantially underreported, the number of events related to poor usability is probably also very understated as well.

He also noted that while the study only included reports that explicitly mentioned the name of the vendor or product, clinicians usually don’t include such names when their writing up a safety report.

Physicians, Patients Intrigued By Digital Health Options

Posted on March 12, 2018 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.

While digital health technologies have been available for many years, it’s taken a long time to get both doctors and patients comfortable with using them. However, the time is fast approaching, as the following study suggests.

New research from Ernst & Young has concluded that both physicians and consumers want to collaborate using digital technologies. The study found that consumers are comfortable reaching out to the doctors via digital channels and that physicians agree that digital technologies and data sharing can improve patient well-being.

More than half (54%) of consumers responding to the survey said they were comfortable contacting their doctor digitally. Also, they were interested in using technologies found outside of the physician’s office, including at-home diagnostic testing (36%), using a smartphone or connected device to share information (33%) and video consultations (21%).

Meanwhile, 83% of physicians told researchers that harvesting consumer and patient-generated data would make more personalized care plans possible and improve care quality. In addition, 66% said they felt increased use of digital technologies would make the healthcare system more efficient and lower costs, while 64% said it would help lower the burden on doctors and nurses, reducing the potential for burnout.

To make such cooperation practical, however, providers need to create incentives for data sharing, the E&Y researchers concluded.

When asked whether they were prepared to share lifestyle information with their physician, only 26% said yes. On the other hand, if doing so would allow them to reduce waiting times, 61% said they would share such data, if it would lower costs, 55% were interested. Also of note, 26% said they would be willing to share dietary and exercise information if they got tailored diet and exercise plans.

That being said, the level of interest in digital cooperation varied by demographics. Specifically, the survey found much lower levels of engagement and interest from consumers age 45 years and older, regardless of the form of technology discussed.

Still, both consumers and physicians seem to have a fair amount of optimism about the future of health. Sixty-four percent of consumers reported that they saw the US health industry as innovative, and 70% of physicians saw currently used technology as effective, both of which are high-water marks.

As this research points out, the gap between physician users of medical data and consumer portal users is narrowing by the day, but it’s still far from closed. It may take some time to figure out what incentives consumers find the most motivating. At the moment, it’s still a shot in the dark.

New Program Trains Physicians In Health Informatics Basics

Posted on January 18, 2018 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 program has emerged to help physicians make better use of the massive flow of health information they encounter on a day-to-day basis. With any luck, it will not only improve the skills of individual doctors but also seed institutions with clinicians who understand health IT in the practice of medicine.

The Indiana Training Program in Public and Population Health Informatics, which is supported by a five-year, $2.5 million award from the National Library of Medicine, focuses on public and population health issues. Launched in July 2017, it will support up to eight fellows annually.

The program is sponsored by Indiana University School of Medicine Richard M. Fairbanks School of Public Health at Indiana University-Purdue University Indianapolis and the Regenstrief Institute. Regenstrief, which is dedicated to healthcare quality improvement, supports healthcare research and works to bring scientific discoveries to bear on real-world problems.

For example, Regenstrief participates in the Healthcare Services Platform Consortium, which is addressing interoperability issues. There’s also the Regenstrief EHR Clinical Learning Platform, an AMA-backed program training medical student to cope with misidentified patient data, learn how different EHRs work and determine how to use them to coordinate care.

The Public and Population Health training, for its part, focuses on improving population health using advanced analytics, addressing public health problems such as opioid addiction, obesity and diabetes epidemics using health IT and supporting the implementation of ACOs.

According to Regenstrief, fellows who are accepted into the program will learn how to manage and analyze large data sets in healthcare public health organizations; use analytical methods to address population health management; translate basic and clinical research findings for use in population-based settings; creating health IT programs and tools for managing PHI; and using social and behavioral science approaches to solve PHI management problems.

Of course, training eight fellows per year is just a tiny drop in the bucket. Virtually all healthcare institutions need senior physician leaders to have some grasp of healthcare informatics or at least be capable of understanding data issues. Without having top clinical leaders who understand informatics principles, health data projects could end up at a standstill.

In addition, health systems need to train front-line IT staffers to better understand clinical issues — or hire them if necessary. That being said, finding healthcare data specialists is tricky at best, especially if you’re hoping to hire clinicians with this skill set.

Ultimately, it’s likely that health systems will need to train their own internal experts to lead health IT projects, ideally clinicians who have an aptitude for the subject. To do that, perhaps they can use the Regenstrief approach as a model.

Supercharged Wearables Are On The Horizon

Posted on January 3, 2018 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.

Over the last several years, the healthcare industry has been engaged in a rollicking debate over the value of patient-generated health data. Critics say that it’s too soon to decide whether such tools can really add value to medical care, while fans suggest it’s high time to make use of this information.

That’s all fine, but to me, this discussion no longer matters. We are past the question of whether consumer wearables data helps clinicians, which, in their current state, are under-regulated and underpowered. We’re moving on to profoundly more-capable devices that will make the current generation look like toys.

Today, tech giants are working on next-generation devices which will perform more sophisticated tracking and solve more targeted problems. Clinicians, take note of the following news items, which come from The New York Times:

  • Amazon recently invested in Grail, a cancer-detection start-up which raised more than $900 million
  • Apple acquired Beddit, which makes sleep-tracking technology
  • Alphabet acquired Senosis Health, which develops apps that use smartphone sensors to monitor health signals

And the action isn’t limited to acquisitions — tech giants are also getting serious about creating their own products internally. For example, Alphabet’s research unit, Verily Life Sciences, is developing new tools to collect and analyze health data.

Recently, it introduced a health research device, the Verily Study Watch, which has sensors that can collect data on heart rate, gait and skin temperature. That might not be so exciting on its own, but the associated research program is intriguing.

Verily is using the watch to conduct a study called Project Baseline. The study will follow about 10,000 volunteers, who will also be asked to use sleep sensors at night, and also agreed to blood, genetic and mental health tests. Verily will use data analytics and machine learning to gather a more-detailed picture of how cancer progresses.

I could go on, but I’m sure you get the point. We are not looking at your father’s wearables anymore — we’re looking at devices that can change how disease is detected and perhaps even treated dramatically.

Sure, the Fitbits of the world aren’t likely to go away, and some organizations will remain interested in integrating such data into the big data stores. But given what the tech giants are doing, the first generation of plain-vanilla devices will soon end up in the junk heap of medical history.

Mercy Shares De-Identified Data With Medtronic

Posted on October 20, 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.

Medtronic has always performed controlled clinical trials to check out the safety and performance of its medical devices. But this time, it’s doing something more.

Dublin-based Medtronic has signed a data-sharing agreement with Mercy, the fifth largest Catholic health system in the U.S.  Under the terms of the agreement, the two are establishing a new data sharing and analysis network intended to help gather clinical evidence for medical device innovation, the company said.

Working with Mercy Technology Services, Medtronic will capture de-identified data from about 80,000 Mercy patients with heart failure. The device maker will use that data to explore real-world factors governing their response to Cardiac Resynchronization Therapy, a heart failure treatment option which helps some patients.

Medtronic believes that the de-identified patient data Mercy supplies could help improve device performance, according to Dr. Rick Kuntz, senior vice president of strategic scientific operations with Medtronic. “Having the ability to study patient care pathways and conditions before and after exposure to a medical device is crucial to understanding how those devices perform outside of controlled clinical trial setting,” said Kuntz in a prepared statement.

Mercy’s agreement with Medtronic is not unique. In fact, academic medical centers, pharmaceutical companies, health insurers and increasingly, broad-based technology giants are getting into the health data sharing game.

For example, earlier this year Google announced that it was expanding its partnerships with three high-profile academic medical centers under which they work to better analyze clinical data. According to Healthcare IT News, the partners will examine how machine learning can be used in clinical settings to sift through EMR data and find ways to improve outcomes.

“Advanced machine learning is mature enough to start accurately predicting medical events – such as whether patients will be hospitalized, how long they will stay, and whether the health is deteriorating despite treatment for conditions such as urinary tract infections, pneumonia, or heart failure,” said Google Brain Team researcher Katherine Chou in a blog post.

As with Mercy, the academic medical centers are sharing de-identified data. Chou says that offers plenty of information. “Machine learning can discover patterns in de-identified medical records to predict what is likely to happen next, and thus, anticipate the needs of the patients before they arise,” she wrote.

It’s worth pointing out that “de-identification” refers to a group of techniques for patient data protection which, according to NIST, include suppression of personal identifiers, replacing personal identifiers with an average value for the entire group of data, reporting personal identifiers as being within a given range, exchanging personal identifiers other information and swapping data between records.

It may someday become an issue when someone mixes up de-identification (which makes it quite difficult to define specific patients) and anonymization, a subcategory of de-identification whereby data can never be re-identified. Such confusion would, in short, be bad, as the difference between “de-identified” and “anonymized” matters.

In the meantime, though, de-identified data seems likely to help a wide variety of healthcare organizations do better work. As long as patient data stays private, much good can come of partnerships like the one underway at Mercy.

New Research Identifies Game-Changing Uses For AI In Healthcare

Posted on June 27, 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.

In recent times, the use of artificial intelligence technology in healthcare has been a very hot topic. However, while we’ve come tantalizingly close to realizing its promise, no application that I know of has come close to transforming the industry. Moreover, as John Lynn notes, healthcare organizations will not get as much out of AI use if they are not doing a good job of working with both structured and unstructured data.

That being said, new research by Accenture suggests that those of us dismissing AI tech as immature may be behind the curve. Researchers there have concluded that when combined, key clinical health AI applications could save the US healthcare economy as much $150 billion by 2026.

Before considering the stats in this report, we should bear Accenture’s definition of healthcare AI in mind:

“AI in health presents a collection of multiple technologies enabling machines to sense, comprehend, act and learn, so they can perform administrative and clinical healthcare functions…Unlike legacy technologies that are only algorithms/tools that complement a human, health AI today can truly augment human activity.”

In other words, the consulting firm sees AI as far more than a data analytics tool. Accenture analysts envision an AI ecosystem that transforms and serves as an adjunct to the many healthcare processes. That’s a pretty ambitious take, though probably not a crazy one.

In its new report, Accenture projects that the AI health market will reach $6.6 billion by 2021, up from $600 million in 2014, fueled by the growing number of health AI acquisitions taking place. The report notes that the number of such deals has leapt from less than 20 in the year 2012 to nearly 70 by mid-2016.

Researchers predict that the following applications will generate the projected $150 billion in savings/value:

  • Robot-assisted surgery: $40 billion
  • Virtual nursing assistants: $20 billion
  • Administrative workflow assistance: $18 billion
  • Fraud detection: $17 billion
  • Dosage error reduction: $16 billion
  • Connected machines: $14 billion
  • Clinical trial participant identifier: $13 billion
  • Preliminary diagnosis: $5 billion
  • Automated image diagnosis: $3 billion
  • Cybersecurity: $2 billion

There are a lot of interesting things about this list, which goes well beyond current hot topics like the use of AI-driven chatbots.

One that stands out to me is that two of the 10 applications address security concerns, an approach which makes sense but hadn’t turned up in my research on the topic until now.

I was also intrigued to see robot-assisted surgery topping the list of high-impact health AI options. Though I’m familiar with assistive technologies like the da Vinci robot, it hadn’t occurred to me that such tools could benefit from automation and data integration.

I love the picture Accenture paints of how this might work:

“Cognitive robotics can integrate information from pre-op medical records with real-time operating metrics to physically guide and enhance the physician’s instrument precision…The technology incorporates data from actual surgical experiences to inform new, improved techniques and insights.”

When implemented properly, robot-assisted surgery will generate a 21% reduction in length of hospital stays, the researchers estimate.

Of course, even the wise thinkers at Accenture aren’t always right. Nonetheless, the broad trends report identifies seem like reasonable choices. What do you think?

And by all means check out the report – it’s short, well-argued and useful.

Collaborating With Patients On Visit Agendas Improves Communication

Posted on April 26, 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.

Maybe it’s because I spent many years as a reporter, but when I meet with a doctor I get all of my questions out, even if I don’t plan things out in advance. I realize that this barrage may be unnerving for some doctors, but if I need to fire off a bunch of questions to understand my care, I’m going to do it.

That being said, I realize most people are more like my family members. Both my husband and my mother feel overwhelmed at medical visits, and often fail to ask the questions they want answered. I don’t know if they feel pressured by the rapid pace of your typical medical visit, afraid to offend their doctor or have trouble figuring out what information will help them most effectively, but clearly, they don’t feel in control of the situation.

Given their concerns, I wasn’t surprised to learn that letting patients create and share an agenda for their medical visit – before they see their provider – seems to improve physician-patient communication substantially. New research suggests that when patients set the agenda for their visit, both the patient and their doctor like the results.

Study details

The paper, which appeared in the Annals of Family Medicine, said that researchers conducted their study at Harborview Medical Center, a safety-net county hospital in Seattle. The researchers recruited patients and clinicians for the study between June 9 and July 22, 2015 at the HMC Adult Medicine Clinic. The 67-clinician primary care clinic serves about 5,000 patients per year.

When participating patients came in for a visit, a researcher assistant met them in the waiting room and gave them a laptop computer with the EMR interface displayed. The participating patients then typed their agenda for the visit in the progress notes section of their medical record. Clinicians then reviewed that agenda, either before entering the exam room or upon entering.

After the visit, patients were given a survey asking them for demographic information, self-reported health status and perceptions of the agenda-driven visit. Meanwhile, clinicians filled out a separate survey asking them for their gender, age, role in the clinic and their own perceptions of the patient agenda.

After reviewing the survey data, researchers concluded that using a collaborative visit agenda is probably a good idea. Seventy nine percent of patients and 74 percent of clinicians felt the agendas improved patient-clinician communication, and both types of participants wanted to use visit agendas agenda (73 percent of patients and 82 percent of clinicians).

Flawed but still valuable

In closing, the authors admitted that the study had its technical limits, including the use of a small convenient sample at a single clinic with no comparison group, It’s also worth noting that the study drew from a vulnerable population which might not be representative of most healthcare consumers.

Nonetheless, researchers feel these data points to a broader trend, in which patients have become increasingly comfortable with electronic health data. “The patient cogeneration of visit notes, facilitated by new EMR functionality, reflects a shift in the authorship and “ownership” of [their data],” the study points out. (I can’t help but agree that this is the case, and moreover, that patients’ response to programs  like Open Notes support their conclusion.)

I’m not sure if my mom or hubby would buy into this approach, but I imagine that if they did, they might find it helpful. Let’s hope the idea catches fire, and helps ordinary consumers take more control of their clinical relationships.