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Curbside Consult with Dr. Jayne 10/22/18

October 22, 2018 Dr. Jayne 1 Comment

Clinician burnout is at epidemic levels, so I always keep my eye out for scientific papers looking at the issue. A recent paper titled “Implementing Optimal Team-Based Care to Reduce Clinician Burnout” talks about team-based care as a model that “strives to meet patient needs and preferences by actively engaging patients as full participants in their care, while encouraging all health care professionals to function to the full extent of their education, certification, and experience.”

The idea of working at the top of one’s education and licensure is one that I continue to struggle with as I work with physicians who feel that EHRs have turned them into data entry clerks. Although I work with some high-functioning offices, there are far too many where people are doing work that could be done by individuals with less training or experience and at a lower cost. Getting the team composition just right is a challenge, and in the corporate practices I work with, there are barriers such as headcount caps to content with.

I recently worked with a practice that was dealing with a “brick in, brick out” philosophy from their health system HR department. When a highly-paid and long-tenured RN retired, the practice wanted to split her salary and hire three lower-level resources to handle some high-volume office tasks. The hospital-focused HR team would have no part of that strategy, even though it was budget neutral and would benefit the practice, citing various policies and a temporary hiring freeze as barriers. The practice could hire a less-expensive resource to fill her shoes, but then it would lose that salary difference out of their budget for the following fiscal year, hobbling them in a different way.

The practice’s leaders elected to replace the nurse with a similarly-priced resource, which didn’t solve their problem, but preserved their overall budget in hopes that they might be able to make a change in the future if they could get the HR team onboard. It was sad to watch a practice be forced to make bad business decision that reduces their ability to deliver the patient care that needs to be delivered because the corporate structure couldn’t get out of their way.

The paper addresses digital barriers to team-based care, noting that “although EHRs have important advantages in terms of improving continuous access to legible clinical information, they are not optimally designed to support clinical care.” The authors encourage organizations to look at ways to expand the utility of EHRs, including:

  • Examining excessive signature requirements or mandates that physicians must perform certain documentation elements.
  • Accelerating information exchange.
  • Including systems other than EHRs in the discussion of interoperability, including patient health records, registries, etc.
  • Facilitating a learning health system including the use of predictive analytics and artificial intelligence.

They go further to call for CMS to modernize “outdated” documentation guidelines that were created to support billing in the era of paper records. They also suggest that ONC and CMS “could make prescribed medication selection, alternatives, and pricing transparency available to clinical teams at the point of care as a regulatory EHR requirement.”

I’m sure vendors wouldn’t be too thrilled about additional requirements, but as a clinician, I would be thrilled to have that kind of functionality in my EHR. Right now, the only price transparency I have for medications is for the prescriptions we dispense in-house, which are either $10, $20, or $30 at the time of checkout. We don’t make a lot of money on them and we don’t run them through insurance but offer them as a convenience to patients who don’t want to have to stop by the pharmacy on the way home.

The article also looks at workforce barriers, including issues “from the training and mind-set of health care team members to team organization and leadership.” Employee turnover is a challenge for many of the ambulatory organizations I counsel, and usually it’s driven by several factors: inadequate interview and hiring processes, inadequate training, lack of on-the-job mentorship and support, and work/life balance challenges.

Poor interview and hiring processes can lead to mismatched expectations and poor fit with workplace culture. Poor training can lead not only to patient care issues, but to fear and trepidation for employees who feel they’re being asked to perform beyond their comfort zone. When I worked for Big Hospital System, new medical assistants received zero standardized training beyond HIPAA and other compliance trainings. Any clinical training was at the purview of the office manager, who didn’t report to the physicians in the office but rather to a regional administrator. The result was a staff that didn’t always know what they should know to be successful, which led to physician distrust and reluctance to allow them to handle even basic clinical tasks such as taking a blood pressure.

At my current practice, clinical support staff are put through a rigorous training program including clinical terminology, procedures, organizational culture, patient communication, and more. They are then scheduled a certain number of “training shifts” with a clinical leader, where they must complete their procedure logs and document their clinical tasks. These training shifts are added on to a practice’s regular staffing. Although they are training on the job, they’re not expected to immediately fill a standard scheduled position – they are there to learn.

We lose some folks along the way with this rigorous training. Mostly people who realize that our staff really do work at the top of their licenses and who aren’t on board with working as independently as we allow our staff or doing the procedures we expect our staff to perform on a daily basis. I’d rather lose them in training, though, rather than a month or two in.

Once training is complete, each employee is assigned to a “core team” of employees for the purposes of communication, mentoring, and ongoing training. This core team may or may not include people they work with regularly, which gives them the opportunity to have a sounding board about situations which may have happened in the clinic or with other employees. It also provides accountability for ongoing training and mentorship opportunities.

Lack of work/life balance certainly contributes to burnout, not only among physicians, but among all clinicians. I’ve worked with practices where employees can only request a certain number of days off each month regardless of how much vacation they have in their bank. I spoke to one nurse recently who was working during a family wedding because his son also had religious confirmation that month and he was only allowed to “protect” one weekend.

Although I realize the need to balance schedule coverage, this doesn’t build loyalty or allow team members to meet their personal needs. This employee made no secret of the fact that he’s interviewing for a position in telemedicine, where he can work more flexible schedules. Employers need to be in tune with the needs of the current workforce, especially in fields where there are shortages and competition among employers to be the workplace of choice.

The paper closes by noting that our “current payment system is not designed to offset the costs associated with forming, training, and sustaining clinical teams.” Because these tasks are often considered soft skills, organizations often give them less attention than hard-data items like patient volume, patient satisfaction scores, and clinical quality metrics. The money spent on building high-functioning teams is well worth it, but comes at a cost that might derive from a chicken-or-egg finance equation. Programs like the Comprehensive Primary Care Plus initiative are designed to provide this money up front, but only time will tell if that approach is as successful as we hope.

What is your organization doing to foster team-based care? What are they doing to unwittingly sabotage it? Leave a comment or email me.

Email Dr. Jayne.

Morning Headlines 10/22/18

October 21, 2018 Headlines No Comments

Head of IBM Watson Health leaving post after company stumbles, growing criticism

Deborah DiSanzo, general manager of IBM Watson Health for the past three years, will will take a demotion to the strategy team of IBM Cognitive Solutions.

Perficient Announces Formation of a Dedicated Digital Health Service Line

Consulting firm Perficient launches a digital health line of services that will focus on delivery of care, data and insights, and engagement.

CMS Responding to Suspicious Activity in Agent and Broker Exchanges Portal

CMS Administrator Seema Verma assures consumers open enrollment at will not be negatively impacted by the breach of 75,000 consumer files on the Federally Facilitated Exchanges for agents and brokers.

Monday Morning Update 10/22/18

October 21, 2018 News 2 Comments

Top News

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Stat reports that Deborah DiSanzo, general manager of IBM Watson Health for the past three years, will leave her role.

DiSanzo will be replaced by SVP John Kelly III, PhD, who wrote a defense of Watson Health in an August 2018 blog post in which he refuted an unflattering article by The Wall Street Journal.

DiSanzo will take a demotion to the strategy team of IBM Cognitive Solutions.

IBM announced last week that earnings from its cognitive offerings were down 6 percent year over year, although it said Watson Health is growing.

Reader Comments


From Vaporware?: “Re: VA’s Cerner contract. Kudos to them for transparency in listing what they bought, but it looks like they and the VA will be running different systems. Also, DoD didn’t purchase CommonWell even though 60 percent of care happens outside MHS.” The VA’s list of which Cerner systems it and the DoD bought in their respective contracts reveals quite a few differences, some of them understandable due to the types of services offered. DoD skipped quite a few modules that while not useful in battlefield hospitals, would seem to have a place in the dependent care that makes up much of its volume. The DoD passed on modules for cardiology, gastroenterology, CommonWell, most of population health management, integrated radiology dictation, and all transaction services except for automated messaging. I didn’t realize that CommonWell is something you have to buy as an upfront cost, although its documentation says that health IT vendors may charge “commodity-like” fees. Cerner previously pledged not to charge users until at least through the end of 2019.

HIStalk Announcements and Requests


Most of us might make our living advocating medical standardization, use of technology, and applying patient care experience to our own situation, but poll respondents don’t find those to be positives when choosing our own doctor, instead valuing participative decision-making. Debtor concludes, “Here is the problem with the concept of socialized medicine in the United States. Even among an informed group, we put personal patient ‘concerns’ and ‘decisions’ ahead of evidence-based guidelines and vetted treatment protocols. I fully support your right to have concerns and make decisions about your own health,  but I’d prefer not to pay for them if they’re not supported by science.” Matt says, “We get a ton of policy push in healthcare, which we’ve seen create its own echo-chamber to the detriment (in some very real cases) of beneficial practice. It runs its course until the downstream consequences create push back and the the policy is pulled back, which creates a difficult environment for real and helpful innovation.”

New poll to your right or here: where do you keep locally stored copies of your medical information?


Only 20 percent of providers are using biometric patient identification, with most of the remaining 80 percent saying either there’s no business case for it or because they haven’t really thought about it. They aren’t really worried about patient perception or hacker concerns. Industry Analyst Supporter of Biometrics approves “perception deception” in using phones as the biometric reader, adding, “Most folks don’t blink about their biometrics being the vehicle to access their iPads and phones, but feel that their privacy and security regulated healthcare provider asking is too invasive.” Ed A warns of potential lawsuits for providers that fail to follow laws like the Illinois Biometric Privacy Act that require obtaining patient consent and following requirements for biometric use and retention. XCIO’s health system employer biometrically verifies identity in registration areas to reduce duplicate records, insurance fraud, and inaccurate patient billing. 


October 30 (Tuesday) 2:00 ET. “How One Pediatric CIN Aligned Culture, Technology and the Community to Transform Care.” Presenters: Lisa Henderson, executive director, Dayton Children’s Health Partners; Shehzad Saeed, MD, associate chief medical officer, Dayton Children’s Health Partners; Mason Beard, solutions strategy leader, Philips PHM; Gabe Orthous, value-based care consultant, Himformatics. Sponsor: Philips PHM. Dayton Children’s Health Partners, a pediatric clinically integrated network, will describe how it aligned its internal culture, technology partners, and the community around its goal of streamlining care delivery and improving outcomes. Presenters will describe how it recruited network members, negotiated value-based contracts, and implemented a data-driven care management process.

November 7 (Wednesday) 3:00 ET. “Opioid Crisis: What One Health Plan is Doing About It.” Presenter: Samuel DiCapua, DO, chief medical director, New Hampshire Health Families; and chief medical officer, Casenet. Sponsor: Casenet. This webinar will describe how managed care organization NH Health Families is using innovative programs to manage patients who are struggling with addiction and to help prevent opioid abuse.

Previous webinars are on our YouTube channel. Contact Lorre for information.


  • Lavaca Medical Center (TX) went live on Cerner in April 2018
  • Pershing Memorial Hospital (MO) will go live on Cerner in June 2019
  • Kennedy Health System (NJ) will replace Cerner with Epic in 2019
  • Hutchinson Health Hospital (MN) will replace Microsoft Dynamics GP with Infor for financial and supply chain management in October 2018

These provider-reported updates are supplied by Definitive Healthcare, which offers a free trial of its powerful intelligence on hospitals, physicians, and healthcare providers.



GetWellNetwork hires Sameer Siraj (Optum) as chief product officer.

Announcements and Implementations

A new Black Book report on HIM-related technologies names these winners:

  • Nuance (end-to-end coding, clinical documentation improvement, and health information management solutions in both inpatient and ambulatory settings; CDI software)
  • Optum360 (coding and CAC outsourcing)
  • MModal (document capture and transcription)
  • 3M (coding consulting, document imaging)
  • Dolbey (medical speech recognition)
  • Revspring (patient communications and financial satisfaction)
  • Recondo (patient identification and tracking)


Patients who are involved in “non-emergent” ED visits exhibit the same symptoms as ED-appropriate visits 88 percent of the time, an analysis concludes, so it’s probably not reasonable for insurers to demand that patients make an accurate ED-or-not decision. One in six ED visits could be avoided by warning patients that their insurance won’t pay for a non-emergent visits, but such a policy would also discourage the 40 percent of those patients who have ED-appropriate symptoms from going there.

A study finds that hospitals accredited by Joint Commission deliver no better patient outcomes than those certified by other private groups, while hospitals with only a state survey accreditation perform just as well as any of them.

Sponsor Updates

  • Lightbeam Health Solutions publishes a new white paper, “Data-Driven Solutions Providers and Payers Need for Value-Based Care Alignment.”
  • LiveProcess will exhibit at the Health Care Association of New Jersey event October 23-25 in Atlantic City.
  • Meditech releases a new video, “Palo Pinto Mobile Clinic Uses Meditech Ambulatory to Bridge Care Gaps.”
  • Clinical Computer Systems, developer of the Obix Perinatal Data System, will exhibit at the HMHB Annual Meeting & Conference October 22-23 in Atlanta.
  • OmniSys will exhibit at the McKesson Pharmacy Systems Chain & Health System User Conference October 23-24 in Pittsburgh.
  • The SSI Group will exhibit at the MAPAM Annual Fall Conference October 22-23 in South Yarmouth, MA.
  • Surescripts and ZeOmega will exhibit at the 2018 CAHP Annual Conference October 22-24 in San Diego.

Blog Posts


Mr. H, Lorre, Jenn, Dr. Jayne.
Get HIStalk updates. Send news or rumors.
Contact us.


Weekender 10/19/18

October 19, 2018 Weekender No Comments


Weekly News Recap

  • FDA updates draft guidance on managing cybersecurity issues for the premarket submission of medical devices
  • Digital prescription savings company OptimizeRx acquires interactive patient messaging vendor CareSpeak Communications
  • MIT will spend $1 billion to create an artificial intelligence college
  • Varian Medical acquires Noona Healthcare, whose software captures oncology patient-reported outcomes and supports symptom management
  • Pathology image detection support system vendor Deep Lens announces $3.2 million in seed funding and availability of its free VIPER service for pathologists
  • A judge rejects a bid by former Theranos executives Elizabeth Holmes and Ramesh Balwani to block prosecutors from extending their investigation deeper into the company

Best Reader Comments

The only way to improve things is to get [users]to open up about what’s on their mind. What you get is like an archeological dig where you are sifting and sorting, trying to find the treasures scattered amidst the dirt and rocks. (Brian Too)

I really wish folks would stop referring to the US healthcare “system.” We have a healthcare industry, not a system (unless you’re talking about Medicare or the VA), with competing entities looking for market share. Competitors don’t share information. Also, with the emphasis on reimbursement, preventive care (and pharmaceutical cures vs. treatments) take a back seat. (Kermit)

Watercooler Talk Tidbits

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Readers funded the DonorsChoose teacher grant request of Mr. V in rural Maine, who requested programmable robots for his student-driven coding class for grades 6-8. He reports, “The robotics and coding materials that you have allowed us to acquire have opened many new avenues for my students. Students have been able to try their hands at coding, program design, and problem solving. This project has offered students who struggle in other content areas like reading by offering them a chance to view reading in an entirely new light. The simplicity of the coding commands in combination with the ability to see their work in action has proven to be very successful in engaging a broad array of students. These materials have allowed students who have struggled in other aspects of their learning to become leaders.”

Epic tells Wisconsin utility regulators that its expected peak demand usage of electricity will double in the next 10 years, placing the company among the state’s top electricity users that are otherwise mostly manufacturing plants. That’s in addition to its extensive use of solar, wind, and geothermal energy.


A hospital in England installs wall-mounted buttons near its doors that can be pushed by people who notice someone smoking their despite clearly visible “no smoking” signs. The buttons trigger the playing of a recorded announcement over a loudspeaker, with a child’s voice asking them nicely to stop using terms such as, “Someone’s mummy or daddy could be having their treatment today.” A pro-smoking group (who knew?) calls the system “Orwellian” and says a better idea would be to move the smoking area further away, but not so far that less-mobile smokers can’t reach it easily. That sounds great on paper, but as many of us have observed first hand, is a lot harder than it sounds, especially evenings and nights when patients, visitors, and employees are illuminated only by the glow of their cigarettes as darkness encourages them to choose personal convenience over posted rules. I was interested that the BBC announcement referred to “tannoy,” which is apparently like Kleenex having turned a company name (in this case, a loudspeaker manufacturer) into a common noun.

An Atlanta radiologist who made a fortune from his medical device patents is sentenced to six months in prison for a $2 million tax fraud scheme in which he claimed to be a minister who had taken a vow of poverty. Michael Jon Kell, MD made up a church, named himself as pastor, and placed all his assets in church accounts from which he funded vacations, private school tuition for his kids, online dating services, and ownership of his lavish mansion.

In England, the BBC notes that Member of Parliament Dan Poulter is working 28 hours per week at a side job – in his case, as a doctor taking psychiatric training – than any other member. The article also notes that his voting record is among the lowest of Conservative members.

A shoeshine man who worked from the halls of UPMC Children’s Hospital of Pittsburgh died this week at 76, having donated all of his tips since 1982 – over $200,000 — to the hospital’s Free Care Fund.

In Case You Missed It

Get Involved


Morning Headlines 10/19/18

October 18, 2018 Headlines No Comments

FDA proposes updated cybersecurity recommendations to help ensure device manufacturers are adequately addressing evolving cybersecurity threats

The FDA updates draft guidance on managing cybersecurity issues for the premarket submission of medical devices.

Gauss Raises $20 Million in Series C from Northwell Health and Softbank Ventures Korea for AI-Enabled Platform for the Operating Room

Gauss Surgical raises $20 million in a funding round led by Northwell Health (NY) and SoftBank Ventures Korea, with help from seven other health systems.

Duplication causes headaches for state patient exchange

Vermont Information Technology Leaders struggles to pare down the number of duplicate patient records in the state’s HIE.

FDA and DHS increase coordination of responses to medical device cybersecurity threats under new partnership; a part of the two agencies’ broader effort to protect patient safety

FDA and DHS will work together to share information on cybersecurity vulnerabilities in medical devices so that threats to patient safety can be addressed more quickly.

News 10/19/18

October 18, 2018 News No Comments

Top News


The FDA updates draft guidance on managing cybersecurity issues for the premarket submission of medical devices. FDA Commissioner Scott Gottlieb, MD says the document, initially penned in 2014, offers “recommendations for manufacturers on how they can better protect their products against different cybersecurity risks, from ransomware to a catastrophic attack on a health system.”

HIStalk Announcements and Requests

I don’t pay much attention to the “Like” button at the bottom of each HIStalk post, but did happen to notice that Alexander Scarlat’s first Readers Write installment on machine learning had already garnered several dozen clicks. It hasn’t quite gained the notoriety of the most popular post in recent memory, which deals with remedying poor clinician engagement with health IT. Both tap into several pieces of advice I give those interested in submitting editorial:

1. Readers will give your content more credence if you write from a place of experience. Both authors of the aforementioned posts have MDs, and other in-the-trenches educational and professional experience to back up their right to editorialize. Vendor authors – unless they too have immense clinical chops – will never quite escape the subconscious bias of readers who see a company name in the byline and immediately worry their time is being wasted by someone trying to sell them something.

2. Of-the-moment topics written for an audience with significant experience working in the health IT trenches are key to a good read, and will often sustain relevance for some time. Submissions that offer a 1,000-foot view rather than diving into the nitty gritty will attract critics who aren’t afraid to lambast authors. (Granted, I try to filter those out, but some slip through.)


3. Pop culture and humor are always good bets, provided they are in good taste. (I’m still shaking my head at the submission sent over with a curse word in the headline.) I often point interested parties to the “All I Needed to Know to Disrupt Healthcare I Learned from ‘Seinfeld’” series penned in 2015 by Bruce Bandes as a great example of original, humorous content that speaks to a timely topic.


October 30 (Tuesday) 2:00 ET. “How One Pediatric CIN Aligned Culture, Technology and the Community to Transform Care.” Presenters: Lisa Henderson, executive director, Dayton Children’s Health Partners; Shehzad Saeed, MD, associate chief medical officer, Dayton Children’s Health Partners; Mason Beard, solutions strategy leader, Philips PHM; Gabe Orthous, value-based care consultant, Himformatics. Sponsor: Philips PHM. Dayton Children’s Health Partners, a pediatric clinically integrated network, will describe how it aligned its internal culture, technology partners, and the community around its goal of streamlining care delivery and improving outcomes. Presenters will describe how it recruited network members, negotiated value-based contracts, and implemented a data-driven care management process.

Previous webinars are on our YouTube channel. Contact Lorre for information.

Acquisitions, Funding, Business, and Stock


Gauss Surgical raises $20 million in a Series C funding round led by Northwell Health (NY) and SoftBank Ventures Korea, with help from seven other health systems. Funding thus far comes to $52 million. The company has developed tablet-based software that uses machine learning and digital imaging to monitor maternal surgical blood loss in real time.


Digital prescription savings company OptimizeRx acquires interactive patient messaging vendor CareSpeak Communications for an undisclosed amount.


Muscular dystrophy nonprofit CureDuchenne invests in ZappRx, and will help the vendor optimize its e-prescribing and electronic prior authorization software for Duchenne patients.


23andMe CEO Anne Wojcicki tells Rock Health conference attendees that she hopes to soon roll out a test that will help consumers better understand how their bodies react to certain antidepressants. Price points for similar services offered by Color Genomics and Albertsons grocery store pharmacists range from $250 to $750. The FDA shut down 23andMe’s first attempt at such a test in 2013 based on the fear that consumers could misinterpret the results as medical advice.



Patrick Flavin (Outcome Health) joins Arches Technology as president.

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HCTec names Salome Isbell (MedHOK) CFO, Victor Ayers (Infor) VP of professional services, and Heather Espino (Centura Health) VP of clinical solutions.

Announcements and Implementations


Bassett Medical Center (NY) adopts Masimo’s Patient SafetyNet and Root with Vital Signs Check across its 54-bed med-surg unit.

Massachusetts EHealth Collaborative and Cognizant will provide technical and financial consulting services to the MassHealth Delivery System Reform Incentive Payment technical assistance program’s ACOs and community partners.

Partners Connected Health adds a mobile app to its PGHDConnect program, giving users the ability to securely share health data with their providers from 250 devices.

Government and Politics


The FDA and Department of Homeland Security announce they will work together to share information on cybersecurity vulnerabilities in medical devices so that threats to patient safety can be addressed more quickly.

Privacy and Security


Following a similar GDPR-induced move in Europe, Apple gives US users the ability to view, edit, and delete data it has collected on them using a new tool on its privacy website. The tool does not apply to data collected by and stored on Apple devices, including biometric data like fingerprints and heart rates.



The Sequoia Project creates the Interoperability Matters Advisory Group and solicits nominations for workgroup members who will provide feedback and recommendations on interoperability endeavors. I was not aware that Sequoia relinquished Carequality earlier this month to operate as a standalone entity.


In Dublin, St. James’s Hospital goes live on expanded Cerner functionality, making it the largest EHR implementation in Ireland’s history. The three-year project was dubbed “Project Oak” as an homage to the paper the Millenium conversion will save.

Vermont Information Technology Leaders struggles to pare down the number of duplicate patient records in the state’s HIE. An audit last year found 1.7 million unique records for 624,000 residents and patients from out of town. VITL staff have deemed at least 35 percent of those to be duplicates, and hope to have that number down to 21 percent by the end of the year. The struggle for a unique patient identifier in the Green Mountain State is real.

Sponsor Updates

  • EClinicalWorks will exhibit at CHCANYS18 Annual Conference and Clinical Forum October 21-23 in Tarrytown, NY.
  • FormFast will host virtual user group meetings October 23 and 24.
  • Healthwise will exhibit at the 2018 PNEG Conference October 19-21 in Fort Wayne, IN.
  • Foundations Health Solutions wins an Excellence in Technology Award from McKnight’s for its use of Hyland OnBase.
  • Formativ Health adds Conversa Health’s AI-powered chatbot messaging tool to its line of patient engagement services.
  • Imprivata completes the Zebra Technologies Validated Program for its Mobile Device Access.
  • Casenet becomes a founding member of the private-sector Da Vinci project, which aims to leverage FHIR to improve data-sharing in value-based care arrangements.
  • ZeOmega adds MCG Health’s Cite AutoAuth prior authorization software to its Jiva population health management technology.
  • HCTec publishes a new case study featuring Montefiore Health System.
  • NHS approves Elsevier as a supplier for its NHS England Health Systems Support Framework.

Blog Posts


Mr. H, Lorre, Jenn, Dr. Jayne.
Get HIStalk updates. Send news or rumors.
Contact us.


EPtalk with Dr. Jayne 10/18/18

October 18, 2018 Dr. Jayne No Comments

A reader recently asked how/where I keep my own personal medical records. I may have written about it in the past, but my strategy is always evolving, so I’ll share my answer. From my college and medical school days, I have a few paper documents, mostly pathology reports printed from our hospital’s HIM system, and an original vaccination record from our student health clinic. The vaccinations I also keep as a PDF, which becomes useful when I have to turn in my annual health form to volunteer at a youth summer camp. I always chuckle when I have to transfer that data, because I received my last two non-influenza vaccinations (Hepatitis A and Tdap) only because my staff mistakenly drew up doses that were going to have to go to waste, so I had them “waste” the vaccine into my left deltoid.

Beyond that, I have a thumb drive with my entire OB/GYN medical record, provided to me by my physician when she closed her practice. I’m pretty sure it’s not encrypted, and I’ve summarized the important parts into a Word document. I used to have an account on a commercial patient health record courtesy of my employer, but it was clunky and cumbersome, and frankly just creating my own word document was more useful. My genetic counseling records are all on paper, given to me at the end of my visit by my counselor. Her office does not store records electronically or communicate via patient portal. It’s very old-school. When my local health system began their conversion to Epic last year, I did download all my records from their portal, storing them as PDFs on my OneDrive. That way, I can access them from anywhere should I need them. I also store copies of my living will and healthcare power of attorney on the OneDrive, because I’ve seen too many bad things happen and I trot those documents out as needed.

It’s not an elegant solution, but as a physician I have a pretty good handle on my health status and can quickly put my fingers on the data I need even, if it’s not very well organized or categorized. I’m relatively young and healthy, so I don’t have a lot of records to track. I love the idea of patients having their own curated records that they can share, but that concept still scares a lot of physicians silly. I’ve seen some really good solutions on the market, but there hasn’t really been a lot of traction with patients, even with Apple on the scene. I do have an iBlueButton account with Humetrix, although I haven’t used it in a while. Hopefully I’ll stay healthy with no additional data to add.

Speaking of staying healthy, many of us in clinical informatics pride ourselves on delivering evidence-based care using robust clinical decision support tools. Still, the last mile in making evidence-based care a reality is often the conversation between the clinician, his or her staff, and the patient. During this year’s influenza vaccination season, we’re seeing patients who are resistant to the vaccine because of the perception that it was ineffective last year. This is borne out in a recent survey by Stericycle, which notes that a third of US respondents don’t plan to get a flu shot this year. Last year, influenza killed more than 80,000 people, but the data doesn’t appear to sway these folks. My staff has practiced and role-played various talk-tracks for patients, so we’ll have to see if we can continue to convince our patients that it’s the right thing to do. For certain, we’ll be getting an EHR-delivered score card at the end, so every vaccination counts.


I recently learned about the Neighborhood Navigator tool, released by the EveryONE Project in partnership with the American Academy of Family Physicians. The tool uses more than 100 languages and integrates with Google Maps to help patients find directions and connect with social services for needs such as food, housing, transportation, employment, legal services, and more. There is a set of training videos for physicians to help them understand the tool and how to best refer patients.

My colleagues in the physician lounge often lament the changes in healthcare brought on by the growing presence of the Internet and the rise of social media in everyday life. Data from recent surveys reveals some interesting statistics: 54 percent of millennials (and 42 percent of all adults) have either “friended” their provider on social media or would like to do so; 65 percent of millennials (and 43 percent of all adults) find social media appropriate to use to contact their provider about a health issue; and 32 percent of those surveyed have taken a health-related action as a result of information they read on social media.


I stumbled across the “Shots by AAFP/STFM” app in the Google Play store. It includes full CDC vaccine schedules and footnotes, as well as dosing information, contraindications, and catch-up schedule information for all available vaccines. Content is written by immunization experts at the Society of Teachers of Family Medicine. You can also enter a patient’s age and various parameters to get a recommendation on what vaccinations are needed. I use multiple resources in trying to figure out vaccine schedules for people, so I’m looking forward to giving this a try to see if it will be my new one-stop-shop. It’s also available on iTunes.


My slow day in the clinic allowed for a lot of Web surfing in between studying for boards, and I also stumbled upon ePrognosis from University of California, San Francisco. The site’s goal is “to be a repository of published geriatric prognostic indices where clinicians can go to obtain evidence-based information on patients’ prognosis.” I ran the profiles of my favorite community-living nonagenarians, and it looks like the odds of them continuing to do well are very good indeed.


Working at an urgent care that also provides occupational medicine services, we see a number of patients who come in for drug screens. Many employers require these to be observed drug screens, so that there is no question of an employee substituting someone else’s urine sample. I chuckled when I saw this feature on a Florida convenience store that has had to put up a sign telling users not to microwave urine samples. Even our drug screens that are not observed include taking the temperature of the sample to make sure it’s within a valid physiological range, so if someone were going to try to microwave it, they’d have to get it just right. Still, it makes one think twice about using a public microwave.

Email Dr. Jayne.

Morning Headlines 10/18/18

October 17, 2018 Headlines No Comments

OptimizeRx Acquires CareSpeak Communications

Digital prescription savings company OptimizeRx acquires interactive patient messaging vendor CareSpeak Communications for an undisclosed sum.

Apple gives U.S. users tool to see what data it has collected

Following a similar GDPR-induced move in Europe, Apple gives US users the ability to view, edit, and delete the data it has collected on them.

Sequoia Project Launches Interoperability Matters Forum

The Sequoia Project creates the Interoperability Matters Advisory Group and solicits nominations for workgroup members who will provide feedback and recommendations on interoperability endeavors.

A Machine Learning Primer for Clinicians–Part 1

Alexander Scarlat, MD is a physician and data scientist, board-certified in anesthesiology with a degree in computer sciences. He has a keen interest in machine learning applications in healthcare. He welcomes feedback on this series at


AI State of the Art in 2018

Near human or super-human performance:

  • Image classification
  • Speech recognition
  • Handwriting transcription
  • Machine translation
  • Text-to-speech conversion
  • Autonomous driving
  • Digital assistants capable of conversation
  • Go and chess games
  • Music, picture, and text generation

Considering all the above — AI/ML (machine learning), predictive analytics, computer vision, text and speech analysis — you may wonder:

How can a machine possibly learn?!

As a physician with a degree in CS and curious about ML, I took the ML Stanford/Coursera course by Andrew Ng. It was a painful, but at the same time an immensely pleasurable educational experience. Painful because of the non-trivial math involved. Immensely pleasurable because I’ve finally understood how a machine actually learns.

If you are a clinician who is interested in AI / ML but short on math / programming skills or time, I will try to clarify in a series of short articles — under the gracious auspices of HIStalk — what I have learned from my short personal journey in ML. You can check some of my ML projects here.

I promise that no math or programming are required.

Rules-Based Systems

The ancient predecessors of ML are rules-based systems. They are easy to explain to humans:

  • IF the blood pressure is between normal and normal +/- 25 percent
  • AND the heart rate is between normal and normal + 27 percent
  • AND the urinary output is between normal and normal – 43 percent
  • AND / OR etc.
  • THEN consider septic shock as part of the differential diagnosis.

The problem with these systems is that they are time-consuming, error-prone, difficult and expensive to build and test, and do not perform well in real life.

Rules-based systems also do not adapt to new situations that the model has never seen.

Even when rules-based systems predict something, it is based on a human-derived rule, on a human’s (limited?) understanding of the problem and how well that human represented the restrictions in the rules-based system.

One can argue about the statistical validation that is behind each and every parameter in the above short example rule. You can imagine what will happen with a truly big, complex system with thousands or millions of rules.

Rules-based systems are founded on a delicate and very brittle process that doesn’t scale well to complex medical problems.

ML Definitions

Two definitions of machine learning are widely used:

  • “The field of study that gives computers the ability to learn without being explicitly programmed.” (Arthur Samuel).
  • “A computer program is said to learn from experience (E) with respect to some class of tasks (T) and performance measure (P) — IF its performance at tasks in T, as measured by P, improves with experience E.” (Tom Mitchell).

Rules-based systems, therefore are by definition NOT an ML model. They are explicitly programmed according to some fixed, hard-wired set of finite rules

With any model, ML or not ML, or any other common sense approach to a task, one MUST measure the model performance. How good are the model predictions when compared to real life? The distance between the model predictions and the real-life data is being measured with a metric, such as accuracy or mean-squared error.

A true ML model MUST learn with each and every new experience and improve its performance with each learning step while using an optimization and loss function to calibrate its own model weights. Monitoring and fine-tuning the learning process is an important part of training a ML algorithm.

What’s the Difference Between ML and Statistics?

While ML and statistics share a similar background and use similar terms and basic methods like accuracy, precision, recall, etc., there is a heated debate about the differences between the two. The best answer I found is the one in Francois Chollet’s excellent book “Deep Learning with Python.”

Imagine Data going into a black box, which uses Rules (classical statistical programming) and then predicts Answers:


One provides Statistics, the Data, and the Rules. Statistics will predict the Answers.

ML takes a different approach:


One provides ML, the Data, and the Answers. ML will return the Rules learned.

The last figure depicts only the training / learning phase of ML known as FIT – the model fits to the experiences learned – while learning the Rules.

Then one can use these machine learned Rules with new Data, never seen by the model before, to PREDICT Answers.

Fit / Predict are the basics of a ML model life cycle: the model learns (or train / fit) and then it predicts on new Data.

Why is ML Better than Traditional Statistics for Some Tasks?

There are numerous examples where there are no statistical models available: on-line multi-lingual translation, voice recognition, or identifying melanoma in a series of photos better than a group of dermatologists. All are ML-based models, with some theoretical foundations in Statistics.

ML has a higher capacity to represent complex, multi-dimensional problems. A model, be it statistical or ML, has inherent, limited, problem-representation capabilities. Think about predicting inpatient mortality based on only one parameter, such as age. Such a model will quickly achieve a certain performance ceiling it cannot possibly overpass, as it is limited in its capabilities to represent the true complexity involved in this type of prediction. The mortality prediction problem is much more complicated than considering only age.

On the other hand, a model that takes into consideration 10,000 parameters when predicting mortality (diagnosis at admission, procedures, lab, imaging, pathology results, medications, consultations, etc.) has a theoretically much higher capacity to better represent the problem complexity, the numerous interrelations that may exist within the data, non-linear, complex relation and such. ML deals with multivariate, multi-dimensional complex issues better than statistics.

ML model predictions are not bound by the human understanding of a problem or the human decision to use a specific model in a specific situation. One can test 20 ML models with thousands of dimensions each on the same problem and pick the top five to create an ensemble of models. Using this architecture allows several mediocre-performing models to achieve a genius level just by combining their individual, non-stellar predictions. While it will be difficult for a human to understand the reasoning of such an ensemble of models, it may still outperform and beat humans by a large margin. Statistics was never meant to deal with this kind of challenge.

Statistical models do not scale well to the billions of rows of data currently available and used for analysis.

Statistical models can’t work when there are no Rules. ML models can – it’s called unsupervised learning. For example, segment a patient population into five groups. Which groups, you may ask? What are their specifications (a.k.a. Rules)? ML magic: even as we don’t know the specs of these five groups, an algorithm can still segment the patient population and then tell us about these five groups’ specs.

Why the Recent Increased Interest in AI/ML?

The recent increased interest in AI/ML is attributed to several factors:

  • Improved algorithms derived from the last decade progress in the math foundations of ML
  • Better hardware, specifically designed for ML needs, based on the video gaming industry GPU (graphic processor unit)
  • Huge quantity of data available as a playground for nascent data scientists
  • Capability to transfer learning and reuse models trained by others for different purposes
  • Most importantly,  having all the above as free, open source while being supported by a great users’ community

Articles Structure

I plan this structure for upcoming articles in this series:

  • The task or problem to solve
  • Model(s) usually employed for this type of problem
  • How the model learns (fit) and predicts
  • A baseline, sanity check metric against which model is trying to improve
  • Model(s) performance on task
  • Applications in medicine, existing and tentative speculations on how the model can be applied in medicine

In Upcoming Articles

  • Supervised vs. unsupervised ML
  • How to prep the data before feeding the model
  • Anatomy of a ML algorithm
  • How a machine actually learns
  • Controlling the learning process
  • Measuring a ML model performance
  • Regression to arbitrary values with single and multiple variables (e.g. LOS, costs)
  • Classification to binary classes (yes/no) and to multiple classes (discharged home, discharged to rehab, died in hospital, transferred to ICU, etc.
  • Anomaly detection: multiple parameters, each one may be within normal range (temperature, saturation, heart rate, lactic acid, leucocytes, urinary output, etc.) , but taken together, a certain combination may be detected as abnormal – predict patients in risk of deterioration vs. those ready for discharge
  • Recommender system: next clinical step (lab, imaging, med, procedure) to consider in order to reach the best outcome (LOS, mortality, costs, readmission rate)
  • Computer vision: melanoma detection in photos, lung cancer / pneumonia detection in chest X-ray and CT scan images, and histopathology slides classification to diagnosis
  • Time sequence classification and prediction – predicting mortality or LOS hourly, with a model that considers the order of the sequence of events, not just the events themselves

HIStalk Interviews Rizwan Koita, CEO, CitiusTech

October 17, 2018 Interviews No Comments

Rizwan Koita is CEO of CitiusTech of Princeton, NJ.


Tell me about yourself and the company.

I’m the founder and chief executive officer of CitiusTech. We founded the company in 2005. This is my second company — I started a tech support company. Before that, I spent about five years with McKinsey & Company.

When you and I spoke last in 2015, CitiusTech was about 1,600 or 1,700 people strong. We are now at 3,200 people. It’s been a fairly strong growth year this past year and over the last few years. We do a whole bunch of stuff in healthcare technology for our customers across what we call the Clinical Value Chain.

What is driving the company’s strong growth?

From the revenue perspective, we are now part of the Healthcare Informatics Top 100. Our revenue was $127 million last year and are on track for close to $150 million this year. We also made a strategic investment in a company called FluidEdge Consulting, which is at about $25 to $30 million. We are hoping that, on a consolidated basis, we will end this year with revenue of about $175 million. As you can see, that’s a very significant jump from where we were last year.

The growth of the company is essentially coming in a couple of areas. We do a lot of work with payer organizations in the US market. We do a lot of work with provider organizations. Both of those markets have accepted CitiusTech solutions and our services very nicely. We also work with some of the medical software and technology companies and support their growth. That business is actually doing quite well. It’s a fairly homogeneous growth across our offering with providers and tech companies as well as with payer organizations. To a smaller extent, we work with pharma organizations as well.

There is a tremendous shift toward data management, a tremendous shift toward analytics, and now a significant shift toward data science and machine learning. We at CitiusTech have a significant amount of expertise in these areas. We’ve been able to do value-added work for our customers.

How will artificial intelligence and machine learning affect healthcare in the next five to 10 years?

I’m going to talk about history a little bit. Ten years back, the emphasis was on deploying what I would call foundational applications, such EMRs, health information exchanges, and connectivity software. A lot of big problems in data integration still remain and are getting solved. Steadily the focus of the industry has moved towards, what do we do with all the patient data, clinical data, financial data, and operational data that is getting generated? What’s the best way to manage that data? That could be on-premise, cloud, or a more traditional enterprise data warehouse versus big data solutions.

After the data management problem starts to get solved, the next logical question is, how do we start to use more analytics? Increasingly there is a lot of focus on what I would call the standard analytics, like regulatory reporting and and Level 1 analytics. But as the industry is maturing, we see a tremendous focus towards a slightly more advanced analytics. How do you take this massive amount of data that is now getting captured — EMR, lab, pharmacy, or claims — and put it together to be able to solve more complex problems? These are often not possible to solve using traditional analytics, But some large healthcare entities are using machine learning and AI tools to use that information to drive their problem solving.

If you look at the market, there are a lot of smaller proofs of concept and very interesting pilots going on. But the number of real-life deployed applications at scale is still small. You have lots of tools and utilities, but a small number are actually being used for inpatient care at scale. We are trying to help our customers solve that problem.

There is a dichotomy between what’s happening in pilots, research, or academic settings but little of it in production. In the next five to 10 years, we are going to see a tremendous number of successful models getting deployed in the real world for improving patient care, improving efficiency, and reducing cost, all of which are critical for healthcare.

Will use of AI and machine learning create a competitive advantage for health systems that deploy them more quickly or skillfully?

There will be a clear stratification of the types of organizations that can use machine learning and AI. At a simple level, if you take the provider market and hospital systems, a very large entity — Mayo Clinic, Cleveland Clinic, New York Presbyterian, Baylor Scott & White, and other large health systems — will be able to gather that information, and for research purposes or otherwise, build and create their own models.

The bulk of the healthcare ecosystem will largely be dependent on the vendor community to facilitate the use of such advanced tools. If I had to fast-forward five to 10 years, I would say that a lot of the deployment of these tools will be driven by the vendor community — EMR vendors, medical imaging vendors, lab services companies, or some of the other guys who have the financial, intellectual, and technical horsepower. They can aggregate large data sets, build models, and then test those models and get them through the FDA approval process and other barriers that are required before deploying these models in the real world. I see a greater likelihood of that happening. Some of the very large health systems also have a strong R&D inclination and have the ability to drive innovation, but that would be much harder for mid-tier and small hospital systems.

Thousands of models are being created today in healthcare using machine learning and AI. These models can be created in hospital research centers, academic institutions, or by five guys in a garage who have deep clinical insight. If you look at thousands of these models and then look on the production side, you find that the number of real-life applications in production is low.

The reason for that is that customers are getting bombarded by a lot of models — created internally or externally — but they don’t necessarily have the skills required for model validation. Imagine that I’m a large medical imaging company. Tons of folks are coming to me and saying they have great algorithms for medical imaging. I as a medical imaging company must have the horsepower to be able to put together a team that can independently take clinical data, run it through the models, validate the efficacy of the models, and fine-tune the models before I can validate whether the model is effective or not. Model validation is a huge pain area for the industry.

The second area is model operationalization. If you have a validated model, the task of integrating it with the clinical workflow is reasonably complex. Say, for example, that I have a model in medical imaging. Knowing that it’s a validated model, I still must be able to incorporate that model into the workflow of a radiologist. If it’s a colon cancer detection algorithm, then the characteristics of the colon cancer patient’s image needs to then fire up this AI or machine learning algorithm. The algorithm should be able to give back a response that is clearly visible to that radiologist or specialist who is looking at the colon cancer image. The radiologist should be able to either accept or reject the proposition or the findings of the machine, the AI algorithm. Once they accept it, that information should get fed back into the algorithm to incrementally optimize and enhance the algorithm. The result should be presented back as part of the report or to the patient or what have you.

It requires a certain degree of engineering effort to incorporate the model into the clinical workflow in addition to meeting the data science capability. To operationalize the model, you need a bundle of different skill sets — data sciences, product development, QA and validations, and perhaps FDA certification.

We find that technology companies and hospital systems that are trying to operationalize their data science models often don’t have that blend of capabilities that is required for them to truly operationalize the model. We end up with a scenario in which there are a lot of pilot models, the number of models that are validated are fewer, and the number of models that are operationalized is really, really small. Obviously these things will change in the next five years, so we’re at a very exciting juncture, but it will require a serious level of thought on the part of the stakeholders to be able to actually achieve the validation operationalization, which is one of CitiusTech’s core value-add to our customers.

Do you have any final thoughts?

Our company is on an interesting trajectory where are helping our customers drive innovation in healthcare. We are also seeing tremendous growth from a business perspective. I’m really excited about the kind of work that we are doing for the segments that I described. We are setting up a very strong advisory board that we will announce in the next two or three weeks. We’re doing other things to drive the growth of the company both organically and inorganically, actively engaging with other companies that may have complementary skills and solutions to ours. I’m really excited about the growth part of the company and looking forward to the next five years.

Morning Headlines 10/17/18

October 16, 2018 Headlines No Comments

Influential Leapfrog Group Jumps In To Rate 5,600 Surgery Centers

Hospital grading organization Leapfrog Group will launch safety and quality surveys of the country’s 5,600 outpatient surgery centers after an investigation revealed poor oversight and substandard clinical practices.

M.I.T. Plans College for Artificial Intelligence, Backed by $1 Billion

MIT will spend $1 billion to create an artificial intelligence college spanning all five of its schools that will begin instruction in the fall of 2019.

This company, led by veteran athenahealth execs, just raised $300m

Medicare Advantage insurer Devoted Health raises $300 million in a Series B round, increasing its total to $362 million.

News 10/17/18

October 16, 2018 News 6 Comments

Top News


Radiation oncology and software vendor Varian Medical acquires Finland-based Noona Healthcare, whose software captures patient-reported outcomes and supports symptom management.

Reader Comments

From Managing Director, Otium cum Dignitate: “Re: HIMSS Form 990. Here’s the latest from Guidestar.” I should have been more specific in saying that I couldn’t find what I assume should be the latest HIMSS Form 990. I saw this one, which covers the year ending 6/30/16. HIMSS should have filed one last year and is due to file another one this year, but they haven’t responded to my request. More interesting is the title used by this semi-retired reader, who says he just likes the title “Managing Director” and the Latin from Cicero translates to “leisure with dignity,” which is about as cool a goal as someone could set for themselves (although the occasional episode of leisure with dishonor might keep it interesting).


From No Mas: “Re: Athenahealth’s partnership with U of Toledo. The new product for academic medical centers was supposed to be complete by now, three years after you interviewed CMIO Bryan Hinch, MD. Maybe you can reach out for an update.” I’ve emailed Bryan to see what happened since our interview about the co-development of an inpatient EHR as University of Toledo Medical Center tried desperately to unload its problematic and expiration-dated McKesson systems.


From Robert D. Lafsky, MD: “Re: this article. I think a big reason there’s so much lately about physician ‘burnout’ is that medical training teaches you to ask ‘why’ about everything. Even if it’s wrong, there has to be a theory. But when the EMR came along, it urged doctors to not ask so many questions, just do what it says. It’s remarkable that it took this long for a major medical journal to run a piece on the theoretical basis for computerized medical information.”  The NEJM article reviews the need for ontologies (controlled, descriptive terminology that describes the semantic relationships among concepts) to overcome the limitations of incomplete, incorrect, or unsourced EHR data since those systems were designed for billing, thus having no convenient way to store behavioral phenotypes, environmental exposure, genomic sequencing data, and information collected from mobile health sensors. It notes that use of ontologies on huge data sets can discover association and even causation to create new diagnostic and therapeutic insight. The authors also suggest that clinician data entry is not a good use of their time and advocates instead collecting device information and patient-entered information electronically and greater use of speech recognition.

HIStalk Announcements and Requests


Need consulting services? Fill out my minimally intrusive “RFI Blaster” online form (which I just rebuilt) with details about your needs and then choose one or all HIStalk consulting firm sponsors you’d like to hear from. It doesn’t get much easier.

I had another moment of music-driven cognitive dissonance in the senior citizen-filled grocery store the other day when in between sappy, buy-more-stuff music (Beach Boys, Pilot) was inserted “Break On Through (To the Other Side)” from the magnificent 1967 debut album of The Doors. I smugly felt rebellious as I noted no reaction from the older shoppers, but then I realized they were probably just suppressing the fist pumps since they were likely in their mid-20s peak rebellion years when the song charted 51 years ago. Mr. Mojo Risin’ himself would be 74 if he hadn’t broken on through to the other side at 27 in 1971. As I often say, nursing homes are now occupied by those who want to hear Pink Floyd rather than Lawrence Welk.


October 30 (Tuesday) 2:00 ET. “How One Pediatric CIN Aligned Culture, Technology and the Community to Transform Care.” Presenters: Lisa Henderson, executive director, Dayton Children’s Health Partners; Shehzad Saeed, MD, associate chief medical officer, Dayton Children’s Health Partners; Mason Beard, solutions strategy leader, Philips PHM; Gabe Orthous, value-based care consultant, Himformatics. Sponsor: Philips PHM. Dayton Children’s Health Partners, a pediatric clinically integrated network, will describe how it aligned its internal culture, technology partners, and the community around its goal of streamlining care delivery and improving outcomes. Presenters will describe how it recruited network members, negotiated value-based contracts, and implemented a data-driven care management process.

Previous webinars are on our YouTube channel. Contact Lorre for information.

Acquisitions, Funding, Business, and Stock


Medicare Advantage insurer Devoted Health raises $300 million in a Series B round, increasing its total to $362 million. The founders are Todd Park (Athenahealth, Castlight Health, White House), his brother Ed Park (Athenahealth), and some VCs. Also on the team are former Athenahealth CTO Jeremy Delinsky and  former US Chief Data Scientist DJ Patil.


  • Oregon will integrate its prescription drug monitoring program database with EHRs and pharmacy systems using Appriss Health’s PMP Gateway.
  • Legacy Health (OR) goes live on Vynca for capturing, storing, and accessing advance care planning documents.



AAFP promotes Steven Waldren, MD, MS to VP/CMIO, where he will focus on the potential impact of AI and machine learning on family medicine and continue work on reducing EHR burden.

Announcements and Implementations


A KLAS report finds that two-thirds of health systems are just beginning to implement opioid stewardship programs, with the less-advanced ones considering best-of-breed technologies (such as drug dispensing systems that detect or prevent drug diversion) while more advanced health systems expect their EHR vendor to deliver tools to prevent and treat opioid misuse. Epic is the most-used of all technologies used in opioid stewardship programs, while Cerner is least-used.  Customers expect their EHR to integrate with prescription drug monitoring program databases, to offer opioid-specific clinical decision support and toolsets, and to include opioid stewardship capabilities in population health management.


This is smart approach: personal health record vendor HealthLynked publishes a plug-in that allows embedding its appointment-booking function in any of the 60 million websites that run WordPress. The screenshots suggest areas of needed improvement, however, since the dates run together and displaying appointment times down to the second seems silly.


A Reaction Data report says that only 15 percent of radiology departments still use dictation and transcription, with speech recognition dominating (although not growing) and 81 percent of respondents using Nuance and basically none of them thinking about switching to another vendor. Just over half of respondents say their speech recognition is integrated with PACS, but integration with RIS and EHR is much lower even though user satisfaction with the integration of all three is high.


Hospital grading organization Leapfrog Group will launch safety and quality surveys of the country’s 5,600 outpatient surgery centers, noting the need as evidenced by the Kaiser Health News/USA Today Network investigation that revealed poor oversight and substandard clinical practices. Let’s hope they call out the likely majority of those centers that refuse to participate (since until competitors start publicizing their good results, there’s no incentive). The organization issues grades for 2,000 US hospitals, just over one-third of the total.


A hospital in eastern China goes live with facial recognition check-in on a system developed by Alibaba’s healthcare group. Anyone with health insurance and a mobile payment account can register without their ID cards or phones once they have linked their accounts to the Alipay mobile payment app. The system’s 3-D cameras link to Alipay’s biometrics and the Ministry of Public Security’s photo database, which is also used by police to identify the faces of fugitives in large crowds. 

A Philips study finds that the US healthcare system captures a lot of data compared to other countries, but suffers from lack of a universal health record and low consumer satisfaction and trust.

Government and Politics


Telemedicine vendor HealthRight and its CEO Scott Roix plead guilty to healthcare fraud and fraudulent marketing of dietary supplements, skin creams, and testosterone that its doctors prescribed without realizing how massively the company was marking up the prices. A total of four men and seven compounding pharmacies were named in charges of running a billion-dollar telemedicine fraud scheme.


Another healthcare information challenge – a person’s genetic test results could change from “normal” to “abnormal” or vice versa based on new research findings, but nobody has thought about the challenges in contacting those patients or their doctors to let them know or to have them retested. A recent study found that of 1.45 million patients tested from 2006 to 2016, reclassification of mutations would have changed the reports of 60,000 of them.


UMass Memorial Health Care lays off 17 IT employees two weeks after going live with its $700 million Epic implementation. 


MIT will spend $1 billion to create an artificial intelligence college that will begin instruction in the fall of 2019. MIT says the intentionally used term “college” reinforces that the new organization will work across all five of its existing schools (architecture, engineering, humanities, management, and science) rather than being a school itself. It adds that the college will emphasize ethical guidelines of how AI can be used for human good.


Amazon posts job listings for data scientists with health benefits experience to work with partners – “including the new healthcare venture” – to create healthcare and population health management solutions. Most interesting is the responsibility to “leverage big data to explore and introduce areas of healthcare analytics and technologies” and preferred experience that includes working with claims, EHR, and patient-reported data. I have a strong feeling that if Amazon ever meets high expectations for healthcare disruption that this Atul Gawande-led group won’t be its weapon of choice – while the company will learn a lot about how healthcare works, the goal is to reduce its own costs, with no guarantee that those efforts will extend outside its four walls. The company’s real disruption opportunity likely lies elsewhere and that are more easily penetrated, such as in supply chain management.


A jarringly moving obituary written by the parents of a 30-year-old mother who died of a drug overdose last week provides a sad reminder of the toll of drug addiction on families. Some excerpts (but you should read the whole thing):

It is impossible to capture a person in an obituary, and especially someone whose adult life was largely defined by drug addiction. To some, Maddie was just a junkie — when they saw her addiction, they stopped seeing her. And what a loss for them … During the past two years especially, her disease brought her to places of incredible darkness, and this darkness compounded on itself, as each unspeakable thing that happened to her and each horrible thing she did in the name of her disease exponentially increased her pain and shame. For 12 days this summer, she was home, and for most of that time she was sober. For those 12 wonderful days, full of swimming and Disney movies and family dinners, we believed as we always did that she would overcome her disease and make the life for herself we knew she deserved. We believed this until the moment she took her last breath. But her addiction stalked her and stole her once again. Though we would have paid any ransom to have her back, any price in the world, this disease would not let her go until she was gone.

If you are reading this with judgment, educate yourself about this disease, because that is what it is. It is not a choice or a weakness. And chances are very good that someone you know is struggling with it, and that person needs and deserves your empathy and support. If you work in one of the many institutions through which addicts often pass — rehabs, hospitals, jails, courts — and treat them with the compassion and respect they deserve, thank you. If instead you see a junkie or thief or liar in front of you rather than a human being in need of help, consider a new profession.

Bizarre: Sacramento police can’t figure out what charges to file against two high school students who handed out cookies at school that contained a secret ingredient – the cremation ashes of one of their grandparents.

Weird News Andy call’s “Rocky’s Revenge” as a New York State hunter dies of a brain disorder after eating the brain of a squirrel he shot. WNA says the incidence of the variant of Creutzfeldt-Jakob disease is high around Rochester, NY, which is a long way from Frostbite Falls, MN.

Sponsor Updates

  • AdvancedMD will exhibit at the American Medical Billing Association National Conference October 18-19 in Las Vegas.
  • CompuGroup Medical will exhibit at the Arizona MGMA Annual Conference October 17-19 in Chandler.
  • Collective Medical partners with the Kentucky Hospital Association.
  • Imprivata’s Mobile Device Access completes validation for use with select Zebra devices.
  • CoverMyMeds will exhibit at the CBI Real-Time Benefit Check and ePrior Authorization Summit October 17-18 in San Francisco.
  • CTG will exhibit at the 2018 Northwest Arkansas Technology Summit October 22-23 in Rogers.
  • Cumberland Consulting Group will exhibit at the CBI Value-Based Oncology Management Forum October 23-24 in Scottsdale, AZ.
  • Direct Consulting Associates will exhibit at the Western PA Healthcare Summit October 19 in Cranberry Township.
  • Dimensional Insight will exhibit at the Value-Based Care Summit October 17 in Boston.
  • DocuTap is accepting nominations for its student scholarship program.
  • Redox will host its Healthcare Interoperability Summit November 13-14 in Denver.

Blog Posts


Mr. H, Lorre, Jenn, Dr. Jayne.
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Contact us.


Morning Headlines 10/16/18

October 15, 2018 Headlines No Comments

Anthem Pays OCR $16 Million in Record HIPAA Settlement Following Largest U.S. Health Data Breach in History

Anthem will pay the HHS Office of Civil Rights $16 million to settle HIPAA violations from a 2015 data breach that impacted 79 million people.

Four Men and Seven Companies Indicted for Billion-Dollar Telemedicine Fraud Conspiracy, Telemedicine Company and CEO Plead Guilty in Two Fraud Schemes

HealthRight President Scott Roix pleads guilty to felony conspiracy charges related to a telemedicine scheme that bilked payers out of nearly $1 billion.

Varian Expands Cancer Care Portfolio with Noona Healthcare Acquisition

Cancer care technology company Varian Medical Systems acquires Noona Healthcare, a developer of oncology patient-reported outcomes software.

Dell Medical School Professor Joins Prestigious National Academy of Medicine

Dell Medical School Professor and former ONC head Karen DeSalvo, MD becomes a member of the National Academy of Medicine.

UMass Memorial Health Care lays off 17 workers

Faced with a $22 million operations shortfall, UMass Memorial Health Care lays off 17 IT staff as part of system-wide downsizing efforts that have included the closure of several facilities.

Curbside Consult with Dr. Jayne 10/15/18

October 15, 2018 Dr. Jayne No Comments

As an urgent care physician, I enjoy the satisfaction of being able to make a bad day better for many of my patients. Although I live in a major metropolitan area, there is a relative shortage of primary care physicians (at least ones taking new patients). For those patients who have primary physicians, there’s a shortage of same-day and after-hours appointments that mesh with patients’ busy schedules and their desire for convenience.

I’m happy we can meet our patients’ needs, but I’m often conflicted about the fact that delivering what is essentially primary care in an urgent care setting often contributes to the fragmentation of care. That’s in addition to the cost contribution, because a visit with us typically costs more than a visit to a primary care physician due to negotiated contract rates with payers and higher co-pays for patients.

The fragmentation could potentially be reduced through better technology, particularly better interoperability. Our EHR allegedly has all the interoperability bells and whistles, but local hospitals and their owned physician groups aren’t too keen on sharing data with competitors despite our desire to deliver better patient care. Our state HIE’s provider-centric pricing model makes it cost prohibitive for us to connect, given that the majority of our providers are part time. Even if it were more economical, our HIE is largely read-only, which doesn’t do a lot for the efficiency or accuracy of being able to bring patient data to life in the chart.

A good chunk of our patient volume happens before 9 a.m. and after 5 p.m., which is a testament to the fact that patients want to receive care at a time that is convenient for them, even if it might be more expensive. They also like being able to get care same day and not have to wait for 3-5 days for an appointment for straightforward medical problems. Many of our patients are hourly workers who don’t have paid sick time, and even those who have sick days may be challenged to find two or three hours to visit their primary physician during the work day.

I often think of the reasons behind why people choose to get their care when and where they do, so this Kaiser Health News article caught my attention.

The article covers the idea that millennials are at the forefront of wanting convenience when selecting their care and tend to choose urgent care, telemedicine, and retail clinic options. A poll of 1,200 adults found that younger patients were less likely to have a primary physician, ranging from 45 percent of patients ages 18 to 29 and declining to 12 percent for those age 65 and older. We see that play out in practice, whether it’s strictly due to the convenience angle or whether it’s due to a lack of available primary care capacity.

However, I’m seeing more patients in the Baby Boomer demographic who may have a primary physician, but choose to come to urgent care because they’re busy in their retirement and don’t want their schedules upset by needing to seek medical care.

I have several friends who are dabbling in telemedicine as an adjunct to their regular primary care practices. They report that patients have discussed their desire to handle medical issues at the time and place of their choosing, whether they actually get to interact with the physician face to face or not. Patients are used to transacting the business of their lives online, whether it’s banking or retail, and since healthcare has become a commodity, it’s no different.

One colleague notes that while the patients are glad she’s offering the service, many of them would be just as happy seeing any other physician and not specifically her. We’ve moved into a generation where patients no longer have a primary care physician for life. They may have one for three or four years and then have to change because their employer selected a different network, or they may change due to relocation and the more fluid lives that people tend to live now.

There are concerns that moving away from that continuity where physicians know their patients not only drives up costs, but also leads to inappropriate antibiotic use or misdiagnosis. We see patients who come in specifically because “my primary wouldn’t call me out a Z-pack” and spend a lot of time educating them about viral illnesses. At least we can send them home with medications to help with their symptoms, which makes them feel like they’ve done something to get better even if it’s not an antibiotic. There’s a powerful psychology in that.

We also see patients who have been to their primary care physician and also a subspecialist, but feel like their problem isn’t being addressed so they come to us “for another opinion.” It’s difficult to explain that we’re not experts and if they’ve been to a subspecialist at one of the local academic medical centers and there’s not an answer, that we’re unlikely to find one at the urgent care with our limited testing and radiology capabilities.

I’m particularly interested in the concept of delivering regular primary care via telemedicine, rather than just care for urgent and acute issues. Virtual visits have the power to revolutionize what we do, adding convenience for both patients and providers. In order to be successful, though, we have to get payers and policies aligned to pay for them so that physicians will be more likely to offer them. We also have to get technology aligned, including robust patient portals, the ability for patients to upload their own health data and documents, and better understanding from mid-career physicians that telemedicine isn’t going to suck away their evening and weekend hours.

I think about all the hours that my practice spent trying to track down patients and get them to come in for appointments back when I was in the primary care trenches. I would bet that at least half just disliked the process of going to the doctor and would have been game to do a virtual visit.

I’m excited about projects that pair community health workers with physicians to deliver a combination of in-home contacts with virtual physician visits, particularly in rural areas. A friend of mine recently received a grant in that regard, and I can’t wait to hear how it plays out in real life. I know she is having some challenges figuring out how to actually deliver the services, whether to try to integrate something with her EHR or to use a third-party telemedicine solution. It sounds like the options among vendors vary dramatically, so she is going to keep me posted on her progress.

Are you a physician who regularly incorporates virtual visits into care, or a healthcare IT person who supports one? I’d love to hear from you. Leave a comment or email me.

Email Dr. Jayne.

Readers Write: Hurricanes Michael and Florence Remind Us Why We Need a Data Backup Plan

October 15, 2018 Readers Write No Comments

Hurricanes Michael and Florence Remind Us Why We Need a Data Backup Plan
By Marty Puranik


Marty Puranik is president and CEO of Atlantic.Net of Orlando, FL.

The immense flooding of Hurricanes Michael and Florence across the Florida Panhandle and southeastern areas of the Carolinas, respectively, is yet another business reminder of the omnipotent power of natural disasters. The devastating chaos and aftermath of the massive storms bring into sharper focus a humbling affirmation of the critical need to safeguard health data.

The data backup plan is a mandatory stage of HIPAA compliance requiring healthcare organizations to create, implement, and maintain a set of rules and procedures to follow when managing the backup and restore requirements of electronic protected health information (ePHI).

The data backup plan encompasses wider contingency planning processes that include your chosen business associate (BA) or managed service provider (MSP). The company engaged to remotely or on-site manage your plan must demonstrate a compliant backup service capable of backing up and restoring exact copies of ePHI. 

In choosing a backup service for business continuity and HIPAA compliance, it is critically important to understand the HIPAA Security Rule requirements. This rule demands a backup solution that adheres to the following criteria:

  • Use of data encryption. Backup data is expected to be encrypted at rest and in transmission. This encryption is achievable by using a storage hardware or operating system-level encryption techniques.
  • User authentication safeguards. Applying unique multi-factor password protection is accomplished using Active Directory and a token-based security key such as PKI.
  • Role-based access rules. Users are restricted access on a need-to-know basis following a least-privileged design. These measures help prevent access to backup data by unauthorized personnel.
  • Offsite storage capabilities. Backups must be stored in a separate location to production services.
  • Secure data center facilities. This measure applies to the facility security processes such as SSAE 16 SOC1 and SOC2 standards.
  • Detailed monitoring and reporting functions. Backups must be reported upon and alerts generated in the event of failure.

Moreover, leaving any best-laid plan involving patient data to chance opens to the door to security risks. Proactively test your data backup plan to ensure the MSP’s systems work harmoniously in any unexpected situation. Testing procedures can include:

  • File-level restore. A file-level restore involves one or several files restored to the file system. This can be set up on the original server or to a different location.
  • VM-level restore. If the MSP deploys virtualization technology, a full virtual machine restore can be performed. The server then can be tested for functionality.
  • Application-level restore. A common application restore is a database from inside a Microsoft SQL server instance or a mailbox from Microsoft Exchange. This test guarantees data integrity and verifies that correct permissions and security configuration are recovered.

I often recommend to providers to delegate the backup and restore responsibilities to a compliant cloud or backup-as-a-service (BaaS) offering. The MSP determines the type of backup media to use, which is usually disk-based storage. Once successful backups are achieved, the next step is the restore process for testing to validate the data’s integrity. The testing also assures the backup engineer’s ability to restore data in tandem with the precise speed of timing to complete the process.

Integration within a wider contingency plan is also essential as a failsafe for the data protection. Most MSPs offer disaster recovery technology capable of failing over data and services to a secondary location almost instantaneously. However, be aware that backups are often considered the last line of defense in the event of a catastrophic system failure. The contingency plan authorizes instant data restoration capability in the worst possible case scenarios.

To meet HIPAA security rule requirements, the BaaS platform incorporates offsite backup technology that will offload entirely the ePHI healthcare infrastructure to an external location. The offloading is most frequently performed through site-to-site replication technology or even by shipping backup tape media to a compliant external location. Since backup data is transferred externally over a network, determining the network security being provided by the MSP is imperative to prevent breaches.

Hurricanes Michael and Florence clearly bring into focus the need for emergency preparedness to protect the security of patient data. Indisputably, losing data has huge consequences for healthcare providers who routinely handle sensitive and private ePHI. For example, if access to a critical pharmacy, lab or EHR system is severed, a medical practice struggles to recover and continue its business operations. Reputations are damaged. More importantly, patient lives are put at risk.

Like insurance plans, a data backup plan is there when you most need it as an integral part of your overall business strategy. Before the next natural disaster strikes, what is your backup plan?

Readers Write: The Compliance Difficulties of Medical Device Connectivity

October 15, 2018 Readers Write No Comments

The Compliance Difficulties of Medical Device Connectivity
By Abbas Dhilawala


Abbas Dhilawala, MS is CTO of Galen Data of Houston, TX.

There are numerous challenges facing the global healthcare ecosystem today, including aging populations that require more healthcare products and services; rising costs across the industry (shared among consumers, insurance carriers, healthcare providers, and taxpayers); growing wait times for medical services; and a growing demand for convenient and personalized care.

To address these challenges, medical device companies are beginning to produce medical devices with cloud connective capabilities that promote the digitization of healthcare and promote better physician-patient engagement while driving down costs. The global market for connected medical devices is expected to increase from $21 billion in 2018 to $63 billion by 2023, an annual growth rate in excess of 25 percent, according to one report.

Still, the path forward for medical device companies that want to design the connected medical devices of the future and get them to market isn’t always clear and direct. Medical device manufacturers are subject to extensive regulations and compliance requirements for the medical devices that they produce. A recent survey of 237 medical technology employees by Deloitte found something important: 67 percent believe that the current regulatory framework will not catch up with what we can do with medical device technology today for another five years.

Medical device companies today face a fractured compliance landscape that can stifle innovation and lead to heavy expenditures in compliance activities at the expense of research and development. Medical device companies that wish to sell their devices in the United States must comply with the quality regulations set forth by the United States Food and Drug Administration (FDA) in Chapter 21 of the Federal Code of Regulations, Part 820. The regulations include guidelines for ensuring the safety and effectiveness of medical devices, including the establishment of detailed design control documentation, the creation and maintenance of processes for corrective and preventive actions when non-conforming products are discovered, and requirements for document control and approval.

Quality system regulations exist around the world in different forms. Canada uses the Canadian Medical Devices Regulations (CMDR), while medical devices sold in Europe must obtain a CE Marking through compliance with ISO 13485, the international standard for medical device quality. Each time a medical device company enters a new market, it must demonstrate compliance with the corresponding local quality system regulations. Sometimes this means conducting a gap analysis and addressing compliance issues internally, but it could also mean hiring a Notified Body to conduct an expensive and time-consuming third-party compliance audit.

To help ease the path to compliance for medical device companies and reduce the cost burden of compliance activities, regulators worldwide are working towards a Medical Device Single Audit Program (MDSAP) that can establish medical device compliance for global markets based on a single audit. While this measure should reduce compliance costs for medical device companies, it remains to be seen how connected medical devices will be regulated under a new system.

As healthcare innovators continue to develop connected medical devices, privacy is a growing concern for regulators and industry professionals. Imagine a future where in-home care is increasingly common and where patients use wearable and implantable medical devices that deliver patient data electronically in real time to a central repository of electronic medical records.

Such a future might not be far off. The EHR mandate already requires hospitals and medical clinics across the United States to use electronic medical records to track patient data, and connected devices with data transmission capabilities already exist. What doesn’t exist yet is a common framework that promotes interoperability between connected devices and patient databases or any kind of privacy and security regulations that would safeguard such a system against malicious attacks that could compromise patient data.

The final compliance issue faced by manufacturers of connected medical devices has to do with changing payment models throughout the healthcare industry. As the industry shifts towards a model that compensates healthcare providers based on the effectiveness of treatments and patient care outcomes, government regulators and payers are increasingly asking for objective evidence that medical devices are positively impacting patient outcomes. Manufacturers of connected medical devices may face additional compliance obstacles when required to demonstrate that their devices actually improve patient engagement, satisfaction, and outcomes.

Despite the compliance difficulties faced by the industry, medical device manufacturers are meeting the challenge head on by innovating new ways of doing business, including funding models that offer data as a service, the adoption of value-based pricing, and the use of real-world patient data to drive business decisions. The medical device companies of today are ready to advance healthcare into the future. Now it’s up to healthcare providers and regulators to keep up.

Morning Headlines 10/15/18

October 14, 2018 Headlines No Comments

Cloud-Based Digital Pathology Startup Deep Lens Exits Stealth Mode With $3.2 Million Seed Financing

Pathology image detection support system vendor Deep Lens announces $3.2 million in seed funding and availability of its free VIPER service for pathologists.

Athenahealth has multiple bidders for sale of the company

Sources suggest that four private equity firms and activist investor Elliott Management are considering placing a bid to acquire Athenahealth.

Sloan Kettering Researchers Correct the Record by Revealing Company Ties

Several prominent Memorial Sloan Kettering Cancer Center researchers update their conflict-of-interest disclosures in previously published journal articles, adding previously undisclosed financial ties to drug companies.

Theranos Criminal Case Is Broader Than Publicly Disclosed, Prosecutors Say

A judge rejects a bid by former Theranos executives Elizabeth Holmes and Ramesh Balwani to block prosecutors from accessing over 200,000 company documents, alluding to a broader investigation that may extend beyond the two defendants.

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