ClickCare Café

Population Health aids Coordinated Care Initiatives

Posted by Lawrence Kerr on Wed, Jul 12, 2017 @ 06:19 AM

samuel-schneider-222889.jpgPopulation health initiatives are nothing new -- but I'll be the first to admit that I was floored by the results that some projects are getting, and this may aid our efforts toward coordinated care. 

As you likely know, population health initiatives are projects that look at the health of a group -- for instance the health of everyone in a state -- including the distribution of those outcomes.

CareOregon is one example -- a nonprofit that increases access to healthcare services for patients on Oregon’s Medicaid programs. As their CEO tells it, their goal is to make hospitals all but unnecessary by limiting the need for that kind of care.

The surprising results? Since it launched in 2011, CareOregon has seen a statewide 23% drop in unnecessary emergency department visits and admissions have decreased as well.

As providers, we may not be population health practitioners in name, but it's our responsibility to look at these determinants of health as well. And we've identified three crucial takeaways from population health that any provider can use.

CareOregon is a great example to look at when it comes to population health. It's broad-based enough to carry takeaways for all kinds of health initiatives. Its results have been substantial in a short period of time. And they've generously shared their initiatives and results so others can learn. 

4 Takeaways from Population Health That Every Provider Can Use:

  • Focus on health, not just healthcare.
    For instance, with CareOregon, a child with severe asthma might be cared for with air conditioners or air filters -- not just medication or even emergency care. This full picture of the "social determinants of health" is something we're passionate about at ClickCare -- and a big reason that the case method of iClickCare is flexible, holistic, multimedia, and includes providers across the continuum of care.

  • Value people -- including the patient and the family -- across the continuum of care.
    CareOregon focus on teams, not events. So whether that means a specialist, an aide, or even a professional outside of medicine, if it will help the patient's overall healthcare, it's part of the picture. As they say, "Sometimes protecting your health means we’ll help you find other agencies that can help you access non-medical support." They also prioritize improving teamwork and communication over advancing specific tactics to improve care. If the team is working well, the results will be good. Finally, they use a “bottom up, top-enabled” approach -- so that the folks who are in most contact with the patient are driving the care (the day-to-day providers), in ways that are enabled at the top (administrators). Valuing people strongly supports our belief that healthcare collaboration and coordinated care are also crucial initiatives -- and telemedicine is one way to make them practical, efficient, and easy.

  • Use simple, inexpensive solutions. 
    This approach is about using technology to work smarter, not harder. Sure, videoconferencing telemedicine systems are fancy (and expensive) -- but we believe that the best medical camera is the one in your pocket already and that the technology should be deeply intuitive. Sophisticated technology doesn't need to be expensive -- and that usually means investing in software, not hardware that is rapidly outdated. 

  • Look at holistic data.
    Fierce Healthcare quotes Karen DeSalvo, M.D., former national coordinator for health information technology at the the Department of Health of Human Services, as saying that we need to break down data "silos that prevent providers from seeing the full picture of a patient's, or community’s, health. Having the full picture allows for a 'system that wraps around people and supports them."  Electronic health records (EMRs and EHRs) are just one piece of the puzzle. All of the other parts of patient data -- that anecdote from a nurse, the self-reported weight changes, etc -- need to be taken into account in systematic ways. Sure, the data in EMRs and EHRs can be codified, but we think that a big reason that CareOregon has seen such dramatic results is because they use the data that helps, even if it's not able to be put into a spreadsheet.

We applaud the pioneers of CareOregon, and the work of every provider who has been courageous enough to try something new as part of it. 

Maybe your medical context is not one where these principles are being used -- but that doesn't mean that you can't apply them, even in small ways, today. 

And if you want a medical collaboration tool like iClickCare as part of that effort, try it for free:

Download iClickCare from the Apple App Store

 

 

Tags: medical collaboration, coordinated care, care coordination, healthcare collaboration, big data

Big Data Moves to Healthcare: A Description. A Warning. A Solution. 2

Posted by Lawrence Kerr on Thu, Oct 25, 2012 @ 03:55 PM

This is Part 2 of a three-part blog post. Emphasis of Big Data acquisition and analysis is supposed to improve healthcare. We emphasize that healthcare collaboration is a way to deal with the massive amounts of data considered to be medical knowledge that has grown beyond mastery of anyone. That said, we also are concerned that attempts to improve quality and profitability remove focus from care and caring. The first post described one source of errors. This second post will show how this error can happen in clinical practice -- with or without healthcare collaboration. The third will suggest a solution. The whole set of the three should bring fair warning to those who hear the sirens of Big Data which is done poorly, and help them look to solutions which are done well.

The past few weeks have brought huge attention to the analysis of data to health care. Much promise has been given to disease detection, epidemiology trends, bioterrorism, and business intelligence. Savings are promised as well as improved care.

iClickCare helps erroneous interpretation by including images, words, discussion andWaiting in line for healtcare collaboration judgment.

EMR and EHRs with financial metrics are the foundations upon which Big Data is being built. They are taking up a considerable part, even a majority, of the day in the life of the provider. What of the rest of the day, a day like this one? To be kind in description, less than user friendly EMR's are being inserted into the office work flow. This process is called “Go Live” which is a stretch of definition of zombie-like software.

All of a sudden four exam rooms are filled and three more patients sit anxiously in the waiting room. The first exam room is occupied by an elderly, somewhat demented, 86 year old with black and blue eyes following a fall. His facial fractures are multiple, and not classic. There are fractures across and within the edentulous maxilla, the nasal bones are involved. There is an extension to the orbit on one side. The zygomatic arch is displaced. With difficulty, they could be classified as LeFort II and a half. Not exactly, but sort of close enough. For patient care, the classification does not matter, the treatment will be the same. We will need to code this visit properly, we know. Why? Because and it will take searching through lists of codes.

The second room corrals a crying 13 month old who has just been sent to the office from the emergency room with a dog bite of the left lower eyelid. She is accompanied by two distraught parents and one distraught grandmother. The next room in line finds a pleasant demanding 54 year old who has body dysmorphic syndrome and is very happy from the scar after the facial basal cell carcinoma that was removed but is also very concerned about her aging body, skin turgor, wrinkles and cheek bones.

healthcare collaboration avoids nurses as butler.jpgThe fourth room has another child with a facial deformity and what his mother describes as moderate to severe autism. He is accompanied on the visit by his brother who shares the same spectrum disorder. There are multiple sharp-edged drawers being opened and slammed closed. The mother’s third child is to be picked up from preschool in just a few minutes. Is surgery to be done?

The fifth room is quiet. Just a calm patient who is thankful for the care, and doesn’t mind waiting. Who would want to keep her waiting? Another form of pressure rests within.

We know that all who care for patients find themselves in similar storms. In part, this exacerbated by patient expectation, such as this Scrubs blog from one our Pinterest followers. In part, it is further caused by the frustration of not doing as smooth a job of healthcare delivery as was possible with less mechanical documentation.

Can you see the potential for error in this scenario? More to follow in Part 3 when we will describe the error and suggest a solution...

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References:

Waiting in line sketch: Jonny Pickton


Tags: healthcare collaboration, EHR, EMR, big data in healthcare, big data

Big Data Moves to Healthcare: A Description. A Warning. A Solution. 1

Posted by Lawrence Kerr on Sun, Oct 21, 2012 @ 01:39 PM

This a three part blog post. Emphasis of Big Data acquisition and analysis is supposed to improve healthcare. We emphasize that healthcare collaboration is a way to deal with the massive amounts of data considered to be medical knowledge that has grown beyond mastery of anyone. That said, we also are concerned that attempts to improve quality and profitabilility remove focus from care and caring. This first post will describe a source of error. The second will show how this error can happen in clinical practice -- with healthcare collaboration or not. The third will suggest a solution. The whole of the three should bring fair warning to those who hear the sirens of Big Data which is done poorly, and look to solutions which are done well.

Here is the problem. Many companies are moving from providing big data services for government to big data services for healthcare.

These companies need to understand what they are getting into.Big data without healthcare collaboration is failure

We, as health care providers, need to realize that we affect the outcome of big data as we provide care alone or as we are part of healthcare collaboration.

Since healthcare collaboration is about taking care of the problem at hand, together, and patient care is about helping another human being either get better, be comfortable, or die peacefully, data entry and codes have no relevance.

On the other hand, we providers are asked to be data input specialists even though we don’t see a benefit for our patients. We have the suspicion that we are working for government -- and thus a boss who regulates; or insurance, and thus a boss who underpays. 

And as happened in the office last week, we are sorely tempted to underperform as data input specialists. Thus, all of you big companies who have migrated from the TSA, CIA and NSA with your Big Data tools should be forewarned. Any of you providers, who see no value in coding precision, should consider the consequences.

Let’s use rounding errors as an example. Then compare the rounding errors to what we sometimes are tempted to (or need to) do as clinicians.

Kees Vuik of the Delft Centre for Computational Science and Engineering clearly and understandably highlights some disasters caused by numerical errors. These range from a Patriot Missile failure which killed 28 soldiers after it missed intercepting a Iraqi Scud missile, to errors on conversion of the Euro. In essence, they all (and there are many other examples) have the same root cause: the magnification of minute inaccuracies of a number by repeated calculation.

iClickCare helps erroneous interpretation by including HIPAA compliant images, words, discussion and judgment. While healthcare collaboration is taking place, accuracy is being increased.Click me

The next post, Part 2,  will describe in detail how simple rounding errors will bring Big Data, Bad Data...

Tags: medical collaboration, HIPAA secure images, healthcare collaboration, big data

EMRs and Cost. Hyperinflation of Big Data. Healthcare Collaboration 2

Posted by Lawrence Kerr on Thu, Oct 04, 2012 @ 04:25 PM

A second thought about Big Data, EMRs and healthcare collaboration.

Another plausible explanation is that the management of Big Data is doing what it is supposed to do. However, the unintended consequence is that billings increased.

giving directionsMaybe what has been discovered is that a whole lot of free care is now being caught in the documentation sieve. Rightful reimbursement is given for work done now, it is just that no one was aware of it before.

Below is a non-medical analogy involving 3 ways to act when a stranger approaches and asks for directions. Assume the stranger is not a native speaker. 

#1. You tell him the directions -- walk one-half block until you see the store with the red front, turn right. You bill for Code ZDP994564.

#2. You quickly and sternly walk him to the corner, a half block away, and point down the street. You bill for the same code, and add the modifier -- 77 because you are completing the EMR form to exactly describe what you did.

#3. Or, you smile, ask him where he is from and how his visit is going, walk him down to the corner, turn right, and walk with him another half a block until he sees what he is seeking. Was there a modifier for that? Was that billable as “public relations," assistance at a higher level, or counseling? 

In either of the 3 ways, you provided a service. If you coded at different levels, isn't that what was asked for? The Garbage-In is just different. Are we as a society getting what we wanted or just getting what we have asked for -- more precise data? And what was free (free as a smile) is accounted and billed for.

iClickCare enables healthcare collaboration by combining words and images with discussion. 

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Tags: healthcare collaboration, EHR, EMR, big data

EMRs and Cost. Hyperinflation of Big Data. Healthcare collaboration.

Posted by Lawrence Kerr on Wed, Sep 26, 2012 @ 10:08 AM

We write a lot about healthcare collaboration. But this is interesting. An editorial in the Wall Street Journal, and report in the NY Times notes that EMRs and EHRs increase healthcare costs.

Design, promote, and sell something which is based on billing and regulations rather than on patient care.

Teach its efficient use over 10 to 20 hours.

Is there a surprise that billings increased? And productivity has decreased? 

Is this hyperinflation of big data?

Sometimes a well aimed gun misfires and explodes backward (the breech). Is this a breech explosion? Really, probably not, the gun may not have been aimed right to begin with. The best aim would be designing better care for the patient that is also cost efficient for the country. EMRs and EHRs are doing what they were designed to do -- bill and regulate.

 

Big Data explodes. Healthcare collaboration should be the target

 

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Tags: healthcare collaboration, EHR, EMR, big data

Big Data and Healthcare Collaboration

Posted by Lawrence Kerr on Thu, Sep 20, 2012 @ 02:00 AM

Big data is a large part of our lives as medical professionals. And the demand for big data is growing. Here are but a few examples that each of us encounters every day. 

  • Usual and customary fees -- their determination
  • Best Hospitals, Best Doctors
  • Length of Stay, Outliers 
  • Meta-analysis studies
  • Prescription surveillance of narcotics
  • Prescribing patterns by big pharma
  • Disease outbreak control
  • Payment and incentives based on percentile of RVUs (relative value units)
  • Free -- something gets measured so somebody else can pay (Nielsen Ratings)
We question, then, how does bad data going in, affect what comes how?
How does that affect us every day?  Healthcare collaboration is affected by Big Data
One approach that industrialists have had toward healthcare collaboration is monetizing Big Data. Hence, we find a plethora of “free” so called collaborative websites. “Free” forums, “Free” references. “Free” consultations. And better than “Free”, honoraria for one’s opinion. While not always needed, pictures and words offer a more accurate communication. But let’s spend a few minutes on “Free”. Chris Anderson has written a book, appropriately enough for this blog, entitled Free. He describes the many forms of free. One that we are all familiar with is free broadcast TV. Free to us, but paid for by a third party, those who pay $3.5 million for 30 second Super Bowl ads. We are willing to watch the ads in exchange for watching football for free. We pay for free later by purchasing what we have been shown. Of course, blogging in general is either filled with ads or offered as a gateway. It is either a lot of posters for the circus, or the barker for the sideshow. It brings new terms to old concepts. Pay Per Click and Organic Search are two of them. Competition for Eyeballs is another.

Another form of free is the free trial. ClickCare offers iClickCare as a free trial with the hope that when familiar with our service you will go ahead and buy it. If you don’t, you still have basic functions for free, and we hope that you will come back and purchase a subscription. This form of free is clear and explicit.

However, there are other forms of free which are less explicit and may be even nefarious. This is where Big Data comes into play. We are all familiar with our paying for our free searches by allowing what we search for, how we searched, and where we came from, to be used by others. Increasingly, we are offered free access to sites offered as a means to enable sharing among professionals. Someone pays for these sites. What do they get in return? Among the returns are aggregated data about what drugs we subscribe, how a marketing campaign worked, or who is a thought leader who can be leveraged/manipulated to increase sales.

This is where Big Data may be hurting us as individuals.

Conversely, as individuals, how do we hurt big data. Really it comes down to the now proverbial -- GIGO -- garbage in / garbage out. In order to satisfy the massive thirst of Big Data, we are asked to reduce our complexity of decision making and care management to CPT and ICD codes. These are unwieldy and time consuming. Imagine that if a patient needs an xray for an injured finger that was just fine before it (inexplicably) struck a wall, then we need an ICD-9 or ICD-10 code. We need to order an xray. We have patients waiting, the EMR is flashing that it has an un-filled field. We know what the film will look like and we know that the finger bone is attached to the hand bone. Knowing all of that, we might  accept that the code for fractured hand is close enough. We will still get to see the fracture. The finger is part of the hand after all, we get the xray, the patient gets the treatment, and Big Data gets the garbage. The Big Data, counting the bits and bytes delivers erroneous:

Usual and customary fees—their determination 

 Fee for treatment

 
 

Best Hospitals, Best Doctors

 

Best outcome because of wrong comparison

 

Length of Stay, Outlier

 

Simpler code for a more complex problem

 

Meta-analysis studies

 

Large numbers of pooled errors

 

Prescription surveillance

of narcotics

 

Narcotic prescribed for less painful injury.

Prescribing patternsby big pharma

Sales representative sits in wrong waiting room 

Disease outbreak control

All of a sudden there are more hand hand than finger fractures

 

Payment and incentives based on percentile of RVUs (relative value units)

Wrong unit, right treatment

Free—something gets measured so something else can pay (Neilsen Ratings)

 

Ask for free data analysis, get the data you pay for. Data gets more accurate information, and qualitative as well as quantitative data as well.

 

 

As the healthcare debate continues, and numbers are described in billions and trillions, we will see more big data. There are a lot of beans to count. As healthcare collaboration feeds more accurate information to big data, the value of analysis is improved. 

Learn more how ClickCare can assure that the data you use is rich, focused and related. 

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References and attribution:

Bean Counter

http://rickmarolt.info/?page_id=276


Tags: healthcare collaboration, big data in healthcare, big data

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