How To Take Charge Of Your Transformed Data

By:  David M. Kashmer MD MBA MBB (@DavidKashmer)


No Need To Tell You About The Importance Of Data Again…

You will see many posts on here that describe why it’s important to manage ourselves and our systems with data. You have likely also read about other techniques utilized to make improvement including Kotter’s eight steps to culture change, tools like SIPOC diagrams, and even project charters. If you’ve opened an entry like this, odds are there is no need to tell you of how much more useful it is to utilize good data than more typical way we do process improvement in healthcare such as only reviewing individual cases.  You likely already understand all the reasons why what we do with data has many advantages over those alternatives.  No need to beat that horse again!


Now take a moment to focus on a finer, and more interesting point about managing systems with data. Specifically, this entry touches on points regarding non-normal data and the meaning behind transformed data.  Here, let’s wrestle with some of the interesting things that happen when we start to examine healthcare systems with data and wind up with seemingly odd things to manage.  For example, what happens if we transform data and end up having to manage something counterintuitive as a result?


What does it mean to the team, exactly, when you wind up having to manage some variable like time squared?


Ut-oh, I Used Data & Found A Non-normal Distribution

Have you ever measured a system only to find out that the data are not normally distributed? In fact, we have talked about this issue earlier here. As you may remember, we have several options for treating non-normal data. One is distribution fitting. We can try to find what distribution, if any, the data follow. Many tools for this exist including Minitab and Sigma XL. Nowadays, good quality improvement often requires software and knowledge of how to use it. For more, look here.


What about situations where the data don’t fit some non-normal distribution? In those cases, you may opt to transform the data. More on data transforms here. One of the available data transforms most commonly used is the Box-Cox transformation.



Box Cox Can Create Some Things To Measure That Feel Strange


This transformation tries to find a function that changes the data set into a normally distributed data set by raising the each data point to some power. Let me say that again, the data are changed to fit the normal distribution according to some power function that the system discovers. Usually, a program will then test the new data set (with the Anderson Darling test) to make sure these data now do follow the normal distribution.  (More here.)


So, for example, imagine you are measuring time in a certain scenario such as response of trauma providers to the trauma bay. Let’s say the data are not normally distributed and do not fit any of the typical distributions. What now? Let’s say you’ve opted for data transformation. The Box-Cox transformation tells you that although the data regarding time are not normally distributed the square of the time variable is normally distributed.


Okay, now what? What does it mean to manage time squared? After all, it’s hard to feel time squared and so time squared may not have a great deal of meaning intuitively.  All those instances where a provider responds to the trauma bay are measured in minutes and seconds. So, what exactly does it mean to measure time squared and how does the team go about paying attention to it?  This is an interesting philosophic question with which I have struggled in project teams. Let me share how we usually resolve this…


“Transform” Is A Bad Word…It Can Make It Sound Like Cheating


One step involves the utilization of the word “transform”. It’s important for the team to know that the data aren’t somehow subverted or cheated when they become transformed. The use of the word “transform” just means that the tool determines what function makes the variable under study (such as time) into a normal distribution with that aforementioned power function.


In fact, it seems that the word “transform” itself seems to make people feel, at times, that the data are no longer what they were. However, I try to impress upon the team (when we utilize data transforms) that transforming the data simply allows us to make the data into a form which allows use of routine statistical tests. That’s the whole point of the transform:  we get to use tests that are comfortable and straightforward.  If you remember, from earlier entries here, that many of the typical statistical tests we use assume the data are normally distributed. Therefore, when we have data that are not normally distributed, we cannot use typical tests. For more on tests which do and don’t require normal data look here.


Therefore, when we are in a situation where the data are non-normal yet don’t follow any typical distribution, one of the only options left to make the data set workable is a power transform such as the Box-Cox transformation. We try to focus users on the fact that we’ll be comparing variables such as time squared to the same apples (time squared again) that we collect post changes in the system. We will be comparing time squared to time squared.  Apples to apples.


Obviously, the longer it takes to get to the trauma bay, the longer the time is and thus the longer the time squared value will be. Importantly, we try to impress on users this more intuitive way of thinking about variables like time. Does it really matter if we are talking about time or time squared if when one is longer so is the other?  We see that same logic with many transformed process variables.


Keeping The Team Aligned With Reassurance Is The Key


In the end, we find that the typical issues with managing system variables like time squared after power transformation evaporate when we focus the group and educate them regarding what these variables indicate in the system. It’s an interesting philosophic question, but is one that rarely changes what we do or outcomes of quality improvement projects. As mentioned, however, it is key to know whether data are normally distributed or not and how to utilize power transforms effectively for working with non-normal data. Keeping the team aligned is important when we run up against challenging concepts like data-transforms that create unusual variables to manage such as time squared.

Warning: You May Be Asking The Wrong Questions About Quality

By:  David Kashmer, MD MBA FACS (@DavidKashmer, LinkedIn profile here.)


A recent blog entry by a colleague of mine (see it here) focuses on the importance of taking care of critically ill patients at difficult hours in challenging situations. This struck a real chord with me, as my focus is on how to construct healthcare services for high quality outcomes. Building a service for high quality means, in part, that service needs to perform similarly under often varying conditions. It needs to be both resilient and robust.  Why is it that many hospital services aren’t constructed to be able to perform at this level, as our colleague asked? What does it take to create a robust service that performs well twenty four hours each day rather than just during the easier times? This entry contends that how and which questions we ask about quality can set our systems up for erratic performance down the line.


It’s No Easy Task To Design For Quality


First, it’s important to realize that creating a service that performs at difficult hours is very challenging. My colleague’s entry gave me a reason to write up some tips and techniques to make the job easier.


One of the biggest keys is actually data collection. That is, first, the team must focus on its data rather its gut or how it feels things are. Remember, this is because most service industries perform at a rate of one defect in every thousand opportunities. My claim is that level of defect, well known to pervade service industries, is very challenging to feel on a day to day basis. Staff often think things are going great (or at least very well) because 999 times out of 1000 things do, in fact, go fairly well. It lulls one to sleep.  However, in high stakes fields like healthcare, we’ve demonstrated that a defect level of 1 in 1000 opportunities is completely unacceptable. For more on the reasons why, look here.


How Data Are Collected And When They Are Collected Is Key


Just as important as being willing to look at (and respond to) data is making sure that the data are being collected in a way that’s non-pejorative. One of the barriers in healthcare, as we’ve previously discussed (here and also here), is that we often equate data collection with an out-to-get-you mentality. (Maybe it’s related to tort law and malpractice issues–who knows.) It’s important that the data be collected regarding the team as a whole and not be personally assignable in any way. This key to the process improvement system creates a process that is non-pejorative, and lessens the chance that the process improvement system will be used as a weapon by one provider or staffer against another. It helps ensure that people will participate and be willing to collect, review, and respond to data.


Another important idea concerns collecting data from the entirety of the system. Often, when we see process improvement done, it’s focused on the hours from which it’s easy to get data. Those are the good ol’ nine to five hours. However, as my colleague points out here, trauma (for example) is “a disease of nights and weekends”. So, for high stakes, challenging services lines like trauma, it’s even more important to sample performance during nights, weekends, and other times from which it is generally more difficult to get data.  Those are often the key times!


It is important to realize how the answers we get to questions about quality are often framed by the nature of the data we collect. Let me say it again:  in healthcare, we need to collect data from those hard-to-get times because that’s when issues line up and the bad things have a higher risk of occurrence.  Remember the advice to collect data directly from the process whenever possible rather than sampling cleaned data from hospital databases–prospective data taken right from the action is often a lot more valuable.


Design In A Way To Respond To Surges In Volume


Next, for services like trauma, acute care surgery, and hospitalist medicine, one of the important concepts is surge capacity. How well does the system absorb large influxes of patients? Sometimes patients come in as multiple trauma activations at once. Three to four patients (or more) may show up at one time followed by long stretches in between of one patient arrival at time. Therefore, the ability to flex up to provide the same level of care when three or four patients come in together is every bit as key as performing well when one patient at a time enters the system. The capacity to be resilient and robust must be consciously designed into the system.  Usually a failure mode effects analysis (more on that FMEA technique here) will reveal how focus should be placed directly on events such as multiple trauma activations.


The Questions We Ask Determine The Systems We Build


So, at the end of the day, my colleague’s question about why things aren’t designed in healthcare to run consistently over 24 hours is based, in large part, on the nature of the questions we pose to our systems. The questions we ask with data, and how we ask them, leads us to design systems that are more apt to work well from 9AM to 5PM.  The first of these counts is we often don’t collect data or respond to it for fear of personal reprisals. Second, if we do collect data, we often don’t collect the data to completely embody the robustness of the system. A third major challenge is that our data often don’t reflect the surge capacity in these high stakes situations where multiple patients may enter the system at once. Concentrating on each of these important ideas allows us to create a high quality, robust system that has a better chance of humming along consistently for 24 hours a day.


Knowing Obligates Us To Act


Once we know these important facts, if we are serious about quality and robustness in our system, we become obligated to progressively improve our care during those times when weaknesses in our system line up–especially nights and weekends.  We’ve learned to avoid framing certain questions about quality in the wrong way.  When we collect data from the full house of the system, we become obligated to respond to it, as a team, in a meaningful way for the good of our patients.

Do We Deliver Great Care Even At Midnight?


By:  The Generation Y Surgeon (@GenYSurgeon)


Sick Patients Highlight The Issue


It was 1:00am, and I was at bedside with a complicated post operative patient in the ICU who had recently presented with upper gastrointestinal bleeding.  The resident surgeon and I (I’m a fellow now) were on the phone trying to get in touch with nuclear medicine, with GI, and with interventional radiology…and none of them were answering.  Ten minutes passed.  Then twenty.  I timed it because when patients are as sick as this guy, every minute feels like an hour, especially when you’re waiting for a call back.  I was curious how long it would take them to return a call.  Any of them. Why had all of our consultants turned into pumpkins after midnight?  This patient needed their help–and he was sick.


Two Hats & Misalignment


I can sympathize with providers who are forced to wear two hats: the elective, daytime hat and the emergency responder, middle-of-the-night hat.  The gastroenterologist I call doesn’t just have to get out of bed in the middle of the night, they also have to face a full day of elective cases and clinic patients in the morning.  The interventionist calls in an entire staff and is often left to struggle through elective procedures with a skeleton crew the following day.  The aftermath of responding to midnight consults must be a terrible deterrent for them.  Sympathies aside, many midnight consults cannot wait to be seen in the morning and patient welfare is at stake.


Oh, by the way, many docs are reimbursed related to the number of cases they do (and RVUs they produce).  Would it make sense for them to struggle for a few extra RVUs that are hard to get when it’s 2AM and the patient is critically ill only to struggle more to do the rapid turnover, elective cases the next day?  God forbid you’re so tired from the midnight work for that patient that you have to cancel some elective cases for the next day.  Does it make sense to them to work hard at 2AM with this patient and phone call, or instead just to sleep and focus on the elective “daytime hat” cases that their contract incentivizes them to do?  Could those same docs be faulted if they adopted the “they wouldn’t have survived anyway” mentality that I so commonly see providers use to make themselves feel ok about the difficult situation they’re in?  Yes, some people will pass away no matter what.  However, in one system in which I’ve worked, even people who “wouldn’t have survived anyway” did survive–and it was because the system was setup properly.


Hospitals really need to make sure they are incentivizing the kind of behavior that leads to the best (yet often labor intense) outcomes for critically ill patients–because, now, sometimes they don’t.


A Lesson From Taco Bell That We Should Learn


Did you ever notice that (if you need gas or a snack) there’s always a gas station open?  If you feel the need to harden your arteries at 3am, there’s usually even a Taco Bell that’s both waiting and willing to help you.  Walmart’s doors are open 24/7 (and holidays too!) for electronics, groceries, household items or people watching.  You can even get photos developed.  Why aren’t hospitals that provide care for critically ill patients 24/7 entities as well?  People need healthcare around the clock, emergencies don’t wait.  Maybe it doesn’t need to be all hospitals, but the ones that take care of sick people need to get this right.


By the way, did you know trauma tends to be “a disease of nights and weekends”? If you look at many trauma programs (that care for critically injured patients when time is short), there’s often an influx of patients at night time and on weeknights.  Those are the busy times.  And when are those programs the most short-staffed?  You got it:  those same nights and weekends.


Here’s an exercise: knowing what you know now as a provider (and assuming you had all the power and influence you would need) think about how you would run a hospital?  How would you schedule your physicians and staff?  What would the hospital look like at 8am, at noon, at 4am, or on Sundays?  Obviously, things need to change.


One System To Help Them All


Changes in a hospital system are tough to perform (there are some useful steps described here on the blog); however the Acute Care Surgery model (ACS) is an excellent example of positive change.  ACS is more of a system than a specialty.  Hospital with well-run programs are able to provide consistent access to surgeons for both patients and for consulting teams.  ACS also serves a sort of triage service for acutely ill patients, taking much of the brunt for their daytime colleagues and even for the consultants.  It turns out that general surgeons actually end up doing more cases when they aren’t burdened with emergencies that interrupt their flow and consume resources.  Having a fully-equipped surgeon who specializes in emergency care (and knows when and why to call in consultants) as part of a system is much more effective than other processes of dealing with critically injured or ill patients.  Having a provider like an ACS surgeon in-house takes a huge burden off the system, and the entire system grows in terms of cases performed even as the overall quality improves.  It’s the only real 24-hour specialty outside of emergency medicine.


Now You Know, So You Must Act


Our patients need us 24/7, so shouldn’t we be adequately staffed to provide care 24/7?  Shouldn’t the hospital be more like a Wawa (or Sheetz) than a bank?  In a perfect world, it would be….with the hum of the hospital sounding exactly the same, regardless of the hour or the day  or day of the week.  We should aim to get great outcomes for everyone all the time and now we face a choice because we know what it takes.  And so now we are obligated to act on what we know.

The Shocking Truth About Business Plans In Healthcare

By:  David Kashmer, MD MBA (@DavidKashmer)


Have you ever had to start some new service for your hospital, or even a whole new business?  There’s lots of planning and preparing, right?  At some point, whether you’ve been an innopreneur within your healthcare system or an entrepreneur starting your own business, you’ve probably been called on to write a business plan.  Those plans are often long, specific…and they just plain don’t work.  Now let me share with you the more modern tool to plan your startup:  the business model canvas.  Read on to find out why the business model canvas is a better alternative than the business plans of days gone by.


We Know Business Plans Don’t Work


Here’s a personal favorite quote from the world of startups, and it’s from that little-known philosopher Mike Tyson:  “Everyone has a plan until they get punched in the face.” That’s just how it is with starting up a new service for your hospital or a new business from scratch.  You think you know how it will look (or at least how you want it to look) and you make an elaborate plan (the business plan) that doesn’t survive first contact with the real world.  Let me say it again:  business plans are known to rarely survive first contact with the real world.  Isn’t there something better we can use?


A Better Tool To Plan Your Startup


Here's what a canvas looks like.
Here’s what a canvas looks like.


What’s better about the business model canvas?  First, it’s flexible.  It didn’t take an investment of a week of your life to write, and it makes it crystal clear exactly what (and how) your business will do what it does.  When an opportunity comes up, or it’s time to change how you do things, you’ll see how new avenues fit in much more easily.


Next, it’s brief.  It’s your business or new hospital service in one page.  It hits all the important parts, and makes what you do very easy to explain to others.


Third, it serves as a visual record of your business.  Many users of this technique recommend reviewing the canvas early in your startup and often.  When you have to make changes, you can review old canvases.  These serve as a history of where your business is and where it has been.  Much better than re-writing your business plan every time you may want to make a change or do a new projection.


Next, it’s collaborative.  The business model canvas is usually made by the startup team as a group.  It originated as, literally, a canvas with post-it notes to satisfy each element on the board.  Business model canvases reflect a much more decentralized attitude than the “I wrote this business plan at midnight here it is” that we’ve often seen before.  Nowadays, there are even ways to make a collaborative canvas online.  (The easel, paper, and post-it notes are going digital.) Visit to create one for your next project.  (It’s free, except you do need to give an email address.)


Tools & Tips For The Canvas


We’ve previously discussed important elements of the business model canvas here.  Take a look if you have a moment.  For this discussion, let me share a few useful tips that I’ve found are good ideas to use in conjunction with the technique.


Cost load the canvas.  Make sure, when you calculate the monthly costs and startup costs, to exaggerate the costs involved when there is any doubt.  Don’t fall short and make sure the margin on what you’ll be doing looks ok.


Calculate the costs and revenues on a monthly basis.  Doing things on this scale seems to help make sure that cash flow through the startup will be ok.


Plan for the worst-case revenue.  One of the problems we have in applying the canvas to new services in healthcare is that the revenue side can be fairly difficult to assess.  Usually, I recommend taking the worst case reimbursement to run the model’s numbers the first time.  That means I’ll look to the worst payor in the payor-mix (exclude self pay) and choose the lowest reimbursement possible based on what the model is supposed to do.  Then, I’ll calculate the break even number of those events to see if the model’s costs are covered.  (For example, how many lap appendectomies would have to be done to cover the costs of this new general surgery service if the only payor was such-and-such third party payor?)


If the numbers look bleak or are borderline bleak, we’ll recalculate with the specific payor mix and volume we expect to confirm whether we really want to do this startup.


If you’re creating a new business as a stand alone entity, plan to fund with at least a 4-5 month “runway”.  If you’ve never heard of runway, healthcare colleagues, the runway is the amount of time you have until your business must take off and fly on its own without external support.  Cash burn rate is the speed at which your startup consumes / uses funds owing to its costs.  You should calculate how much funds are required to give your startup approximately a 4-5 month runway (as a rule of thumb) based on its monthly costs (cash burn rate) before it takes in any revenue.


Use The Canvas In Healthcare


If you’re in healthcare, you probably haven’t heard of the business model canvas.  Is it new?  Untried?  No.  The canvas has been used by many startups across many industries.  We just haven’t used it much in healthcare.  Like many more modern business tools, it’s new to us.


Why bother using this technique in healthcare?  It’s flexible, useful, and easier to achieve.  It’s more modern and reflects a collaborative view of startups.  Just as importantly, it recognizes that business plans often don’t survive the first punch in the face when they contact the real world.


Remember:  failing to plan is planning to fail.  How we plan matters, and the useful business model canvas helps us plan the right way for the future’s twists and turns.  Hope you find the business model canvas useful, and let’s take a moment to thank Alex Osterwalder for creating such a useful tool.


Agree, disagree, have some thoughts to share?  Let me know beneath.





Lean & Six Sigma For Healthcare In The News

By:  David M. Kashmer, MD MBA (@DavidKashmer)


Wanted to share some recent examples of Lean & Six Sigma for Healthcare in the news.  This was from a press release based on an interview I recently completed for Business Innovators magazine.  The content was picked up by several TV stations around the country.


For example, look at this version of the release from San Diego:












Click here for the entire release.  Good to get the word out about Lean and Six Sigma in Healthcare.


Have you seen any recent examples of Lean or Six Sigma in the news for Healthcare?  Let me know beneath.



How To Decide Which Quality Project To Do First

By:  David M. Kashmer, MD MBA (@DavidKashmer.  Linked profile here.)


Once you start down the pathway of quality improvement, you may start to see potential projects everywhere.  Problems with prolonged patient times in the Emergency Department?  Maybe you’ll start with that project first.  Trouble with supplying or re-setting the trauma bay?  There’s another potential project.  And what about operating room turnover time?  There’s another.  Hmmm…each of these seems very different and very important.  Which one do we address first?


Read on, because this blog entry is about a useful tool to help prioritize each potential issue in order to decide where to turn first.


It’s Not Just About Which Feels Worse


Sometimes, there may be that one project that we just really want to do.  It could be because we are mostly in the operating room, and an issue with turnover time affects us each day.  Or, perhaps, it’s because we are in the Emergency Department a great deal and that project with patient time in the department is so obvious to us that it just has to be done right this minute.


Well, this is a situation where spending some time thinking about which project to do first may help you a lot later on.  Let’s look in on a useful tool to help decide where to go first.


Look At The FMEA


The FMEA, or Failure Mode Effects Analysis, is a tool designed to prioritize potential projects–and it does so based on some interesting criteria.  For example, the FMEA ranks potential failure modes of a system according to severity.


That criterion is clear enough:  the worse the outcome could be, the higher the severity score from 1-10.  That criterion seems fairly obvious.  If a situation could give a worse outcome, that situation (or the project to repair it) receives a higher severity score.


The FMEA also ranks failure modes using their probability of occurrence.  More common occurrences receive a higher score on the 1-10 scale.  We tend to think of the typical failure rate in service industries, with 1 defect in 1000 opportunities (1 sigma), as approximately a 5 on the 10 point scale.  That said, it is the next criterion that the FMEA uses which interests me most.


If A Defect Happens In The Forest, And There’s No One There…


What if you had a system that made a defect that it was impossible to find before it made it to the patient?  Think about it for a moment.  You may have met someone at the quality meeting who says “Well it’s just very difficult to detect this particular issue before it gets to the patient.  And even if it does they do ok.  I see no bad outcomes.  In other words, there’s no way to know.” The implication may be that the defect just doesn’t matter.


Well, in terms of ability to detect a defect, if it’s difficult to detect the defect then the defect matters even more.  Said differently, if there’s no known way to figure out that there’s a defect before it gets to the patient it is more important to prioritize that failure mode on the FMEA.  Impossible to find the defect before it gets to the patient?  That, my friend, is a 10 on the FMEA’s detection scale parameter.


Here’s The Most Useful Part


The next useful step is to multiply the severity (S) index by the probability of occurrence (O) and the probability of detection (D).  This S x O x D gives the Risk Priority Number, or RPN.  Find the failure mode with the highest RPN, and the project associated with that failure mode is often the one to address first.


In the end, the FMEA allows us to rank each potential failure (usually named as the project that would repair it) on the FMEA grid.  Just as importantly, it allows us to bring the team onto the same page about which issue to address first.  It even highlights how events that are more difficult to detect may be the more important ones to address earlier.


Hope you find this quality tool as useful as I do!  For more information on the FMEA process, click here.


And here is an Excel workbook, tabs at the bottom for each step, for your very own next FMEA:




Questions or comments?  Let me know.

3 Things To Know About Licensing Your Intellectual Property (IP)

By:  James Kashmer (LinkedIn profile here.)


Going the license route is a “no brainer” right? You get lots of money up front and still get to sit back and collect all those future royalty checks over the life of the patent!!!! You do not need to worry about raising money, hiring employees etc etc…….not a bad way to go right?


I wrote previously “there is NOT a shortage of new ideas or inventions that warrant licensing and development”. Visit any web site where you can find available IP from Government and Universities to see and understand this. Try Googling “tech transfer” sometime…..(or just click here–I did the work for you).


The truth is Government and Universities do a great job of licensing technology with revenues in the billions of dollars each year. Unfortunately, only a relatively small percentage of available IP is ever licensed despite their best efforts.


What Are The Potential Markets And Who Are The Leaders In Those Segments?


Chances are you did not create your idea or invention in a vacuum. It’s likely you already knew something about the subject; who the players are in the field; something about their strengths and weaknesses; something about the current offerings that you could make better. Chances are that, as you talk to people, you will learn about additional markets or potential applications. Spending some of your time researching potential markets (including their size and competing companies) is a good idea even if you have no intention of licensing your IP. By doing so you likely will come up with alternative paths on how to proceed.


In the Medical Device Industry as an example, it is not uncommon to enter a market that has fewer FDA regulatory requirements then an initial targeted market. On the other hand if your intention is to develop your IP ONLY for a specific market or industry, the background work will be very useful for you or your “tech transfer office” to target potential licensees outside your interest.


How Do I Get People To Understand What I Have?


Newer “cutting edge” or technically advanced IP is often hard for people to understand (and therefore value). Do not underestimate how big a problem this is and how important it is to find ways to make people “understand” what you have AND how to apply it. It is my strong belief this is a major key to success and the earlier in the process it is done the better even when resources are tight.


What Is My “End Game” Or “Exit Strategy”?


Thinking of an “end game” or “exit strategy” early in the process does not sound like a useful exercise, but I would argue that in fact it is. Managing expectations and measuring results helps to keep the head “screwed on” and focused on the important objective(s). Without thinking about these early on, designing for “manufacturability” can be challenging later on.  If you are strictly planning to only license your IP, you may be able to make your idea more or less attractive by considering what’s coming downstream.


Questions?  Comments?  Thoughts?  Let me know.  Until then, keep the ideas coming.

America: What Part Of The Healthcare Cost Crisis Do You Own?

By:  The Musing Medic (@TheMusingMedic)


Over the past few years, health care expenditure has come to the forefront of American consciousness. Turn to any channel or examine any newspaper headline and you’ll see something pertaining to the rising cost of healthcare. Pundits, regardless of political persuasion, have something to say about the Affordable Care Act, also known pejoratively as “Obamacare”. There is certainly no dearth of opinion on these matters, and numerous entities are blamed for the current “crisis”.  Candidate culprits include big-business insurance companies, bottom-line focused hospitals, and greedy physicians, but…


The Players Didn’t Make Up The Game

While these groups do own some culpability, they are not the catalyst that spurred the issue. Rather they played the game in which they are participants. The adage goes “hate the game, not the player”. So who then is to blame for sparking this wildfire of excessive health care costs?


The general American populous.


That’s right, I said it.


Mr. & Mrs. John Q. Public are to blame for the exorbitant cost of modern health care.  At least partially.  And yes, that’s me and you.


But how?


The Stats Tell Us The Story…

Let’s take a look at some basic statistics:


37.5% of American adults are classified as obese

17% of American children are classified as obese

Source: CDC 2010


18.1% of American adults smoke cigarettes

Source: CDC 2012


80% of American adults do not exercise the recommended amount

Source: CDC 2012


Those are some basic statistics regarding three major components of a health profile. Naturally, all three are related to one another–especially in the cause-effect realm (eg lack of exercise can lead to obesity). There is a myriad of other healthcare issues, such as illicit drug use, poor diet, and so forth. Additionally, there are socioeconomic factors such as income, race, religion, and geography that can affect one’s health and even their access to health care. …however, that is another discussion for another time.  Perhaps I’ll cover those in my next entry.


Does it cost more to take care of an obese smoker?  Absolutely.


This post is all about holding the American public (all of us) accountable for our choices and actions that lead to higher costs.


How about we just take into account the three aforementioned modifiable lifestyle choices? All three can lead to significant health issues such as hypertension, diabetes, coronary disease, stroke, heart failure, renal failure, COPD, and more. Any of these conditions lead to adverse outcomes, disability, and (generally speaking) a significant financial cost.


Yes, we can say that medical errors cost us all a lot.  (And we should try to eliminate errors!) When a healthcare provider makes a mistake, we do all sorts of things like complain, bring suit, etc.  But listen:  when we’re morbidly obese there’s less wiggle room for errors.  Errors are, arguably, more likely when we require many more procedures than we would have otherwise needed owing to our obesity or other comorbidity.  There’d be no error, or at least we’d have less errors, if we weren’t so large that placing central lines or intubating us wasn’t that much harder.  Yes, healthcare providers (like me when I’m in the field) can get it done, but things would go right so much more easily if we, as Americans, helped out a little.


A lot of the trouble is the expectation, from all of us as citizens, that we will be taken care of without any problem despite whatever situation we may have gotten ourselves into.  No matter our size, smoking, or alcohol abuse, we expect healthcare where the procedure that is done to us (for us) simply must go right.


Help us (and yourself) out by avoiding lifestyle choices that paint healthcare providers into a corner when they show up to help.  It would make things easier on you and much safer.


Aren’t Insurance Companies Really To Blame?

It turns out that insurance companies use premiums to pay a large portion of their customers’ health care costs. The more medical conditions a person has, whether by genetics, lifestyle choices, a combination of both, or just dumb luck, the more likely it is that the patient is going to need medical care. And that medical care costs money. So, as the American population continues to go gray (i.e; baby boomers), the greater the need will be for medical care. Add in that there is an ever-rising number of persons under the age of forty-five with cardiac disease, respiratory conditions, and diabetes, and the issue compounds. Insurance companies have been forced to increase premiums to keep up with the needed expenditure. Additionally, hospitals and physicians have needed to raise their prices to keep pace and maintain staffing and proper equipment.


Is the story that simple?  Not really.  But the fact is that a sicker population means more expense.  Maybe insurers would have less of an excuse to raise prices if we all were just a bit healthier…


Imagine if those statistics mentioned previously were halved. What would happen? Would health care costs decrease?


I’m not sure I know that answer. More importantly it’s a moot point. You could hire an actuary to run those numbers along with economists, financial advisors, and health care administrators and still not have a clear cut answer. What is done is done.


…and I am not sure there will be anything but rising costs in the future. Like I mentioned though, this entry is not about finding an answer. It is about pointing a finger at the main offender, the ones who caused this “crisis”. That would be Americans like you and me.  (Hopefully, for your health, not you specifically!) Before citizens blame everyone around them, they should look in the mirror and ask themselves if they have contributed to the cost of health care in a negative or positive way. I doubt many would be pleased with the honest answer.


Agree?  Disagree?  Let me know beneath.


Till next time


The Musing Medic

3 Things To Ask Yourself Before You Start Developing Your Intellectual Property (IP)

By:  James Kashmer (Visit James’ LinkedIn Profile here.)


Why Would Anyone Invest In My Idea Or Me?

If you already have a track record of commercial success you can do pretty much anything you want and command terms that will make you happy that you were born (or live) in the good ole USA!!!!

Short of proven commercial success, if you are a surgeon and are considered a leader among your peers, most likely you also can do pretty much anything you want under very favorable terms.

The point I am making is that investors look to minimize risk, and the lower your credentials are on the “food chain” the harder it will be for you to get them to invest in your idea. So, unless you have significant credible endorsements that are also early investors, recognize that raising money will be difficult.


How Comfortable Am I With The Information That I Have?

Everyone makes assumptions in their plans. It is important to remember these “assumptions” at some point need to be replaced by “facts”. The sooner that this can be done the better so that you (and investors) can attempt to quantify and minimize risk going forward. Even though it is well known that some startup companies have successfully “pivoted” to avoid extinction, I think they all would agree that firming up your business plan “assumptions” sooner rather than later is the way to go.  This idea of rapidly and progressively eliminating unknowns is part of the modern technique of the lean startup.


What Are My Options?

I am in the business of developing “options” and have been for the last 20 plus years. Sad to say:  it’s tough to do anything of consequence out there, and it’s getting tougher all the time.

For those of you who do not already have a track record of commercial success, if you have an idea or patent that is applicable to many markets consider licensing your IP to a company that already dominates a particular segment and don’t be a “hog” about it!!! (Borrowed from the expression “Pigs get fat, hogs get slaughtered”.)

Another option is to try to go as far as you can on the “cheap”. By this I mean do your homework to eliminate as many unknowns (and risk) as you can BEFORE approaching potential investors (or licensees). With the ability today to produce mockups and even working models (prototypes) using 3D Printing, never has it been so easy to go so far on so little.

Until next time: keep on developing your ideas, and get in touch with any questions or comments!