Winning and Surviving

Winning at Survivor

If you’ve ever seen the reality show, Survivor, hospitals could learn a thing or two.

The show features teams of contestants ‘marooned’ to a remote location. They have to work together to collect food and water, build fires, and construct shelters all while competing in challenges for rewards.

The contestants vote to eliminate someone each week until a single “Sole-Survivor” remains and wins the grand prize. If a contestant displayed less than stellar utility to the group in behavior or performance, if they let their team mates do most of the heavy lifting, if they don’t share, or if they sleep too late, they can be eliminated.

Can hospitals learn from Survivor? They certainly are in a contest vying for some rather large stakes and elimination is a real possibility. 2017 net patient revenues for US hospitals were around $2 trillion with only around a 3.9 percent margin on EBITDA and more than 2,400 out of 3,969 hospitals total booking a loss. Since 2010 more than 220 non-federal, short-stay, acute care hospitals have closed. And more are expected to close, as reimbursement and revenues continue to tighten.

Seven information utility questions you should ask regularly:

  1. Is your hospital’s information set imbalanced?
  2. Have you got a data/information/governance plan?
  3. Have you done a data/information SWOT?
  4. Is information shared, and shared with the right people?
  5. Is it timely and useful?
  6. Is information flow restricted?
  7. Do you regularly assess the utility of your information and adjust as changing circumstances dictate?

We’ll dedicate a separate blog post to each.

Information Imbalance

What an amazing insight from one of the weak competitors who totally flipped the tables with one comment about being “Information Imbalanced.”

What does this term “Information Imbalanced” really mean, anyway? I believe it has two meanings.

  1. What you don’t know will substantially weaken your market position.
  2. You have information, but you can’t or don’t know how to use it strategically.

I run into these scenarios almost daily in the healthcare industry. The world of data is evolving rapidly. Does your organization have the flexibility to evolve with the market? If you are using a strategy from the 90’s, then there is a good chance you have already lost the battle and about to be voted off the proverbial island. Margins are slim. You need to grow revenue now, quickly. What are you going to do today to get back your information balance?

Source: Winning and Surviving

Market Map Search on

Market Map Search on

I love our platform. It’s the best in the industry and the reason is simple: it’s easy to use. And that’s by design.

We built TEAM so that anyone in the healthcare industry can log in to our software and immediately recognize value. Minutes after looking at a hospital in our platform, you’ll be able to identify millions of dollars in opportunity.

TEAM empowers you to prioritize service lines and understand physician volumes and loyalty metrics for not just your physicians, but every physician that shares a patient with you.

We have a saying here at Perception Health and it’s called “Three Clicks to Strategy” — In TEAM, you are never more than three clicks away from the information used to create strategic plans and set priorities for your hospital.

They say pictures are worth a thousand words, and in your case, the data charts and graphs in TEAM may be worth thousands of patients and tens of millions of dollars to your hospital.

Our graphs allow you to visualize your local area network at a glance, quickly identifying the areas that need addressing immediately.

And one of my favorite TEAM features is the Market Map – it’s dead easy to use and incredibly powerful. We have a teaser version of the Market Map here on so that you can try it for yourself!

Try it out below and let us know if you want to see more! We’ve love to schedule a personal demo and show you what we’ve built.

try it now


Source: Market Map Search on

The Rural Care Network Revenue Problem

The Rural Care Network Revenue Problem

Many Americans want to have access to quality care close to where they live.  However, many healthcare providers in rural and exurban America are struggling to keep their doors open and are wrestling with a rural care network revenue problem: declining patient volumes, decreased reimbursements, and a looming transition of their business model from fee for service to value-based care.  To add to the list problems facing them, these systems also have to overcome the perception that local care is objectively worse than what is offered in urban centers1.  

In order to reverse this declining trend, we believe that these health systems can engage their local community and build a care network that provides high quality care to local patients and help stymie the flow of patients to urban centers.  To illustrate this idea, we’ll use our TEAM platform to investigate an exurban market and provide insights about what this local system can do to strengthen their local network and keep patients in their network.

Primary care providers are rightfully the quarterbacks of care for their patients and should be the starting point in any system wide analysis for a facility.  A thorough understanding of a facility’s primary care market can provide tremendous downstream revenue if taken advantage of by a facilities’ physician liaisons.

TEAM provides this information at a quick glance using an asset based visualization we call the market map where physician boxes are sized by total volume of patients they see and are colored based on hospital preference.

We classify the physicians into categories based on their patient volumes that end up at our selected facility.  For instance, we classify Loyalists as physicians who keep more than 75% of their patients in our facility.  These are typically our hospital based or employed physicians and we want to keep them on in our network. However, the greater opportunity to drive patient volume to our facility lies in Splitters which have between 25% and 75% of their patients that end up in acute care and are being seen at our facility.

These are the physicians that we want to have a conversation with around quality, cost, access, and branding at our facility to drive downstream volume.

Note: physician names have been redacted for privacy

(Figure 2. Internal Medicine (Non-Specialist) “Splitters” to our hospital- TEAM)

Here we see two physicians that should be potential targets to increase downstream patient volume to our hospital.  Both of these physicians have high patient volumes, are practicing in the same city as the hospital, and while a good portion of their hospital bound patients end up at our facility, a majority end up at other facilities.

For the sake of brevity, we will focus here on the top physician:

Note: physician and network names have been redacted for privacy

 competing rural care networks

(Figure 4. Our physician’s hospital relationships – TEAM.  The grey lines are sized by patient volumes)

This physician has two main hospitals where his patients end up: Hospital 1 (our hospital) and Hospital 2, a rural hospital to the northeast of our facility.  There are also a number of tertiary hospitals, mainly based in the city and its suburbs, that also treat the physicians patients.

From a growth perspective it’s necessary to understand the reasons behind these relationships.  Perhaps our physician splits his time between office locations at Hospital 1 and Hospital 2 or many of his patients are located closer to Hospital 2 which would explain the trend seen above.  Also it is important to discuss the urban hospitals where our physicians patients are receiving care and the reasons why.  For example:

  • Are there access issues around certain service lines at our facility which are driving patients elsewhere?
  • Is there a perception issue around quality of services patients are receiving in urban facilities that are also offered at our facility?
  • Are patient’s health plans directing them to physicians at other facilities?
  1.  Rieber GM, Benzie D, McMahon S. Why patients bypass rural health care centers. Minn Med. 1996;76(46-50).

Perception Health is a technology company focused on driving revenue to health networks, hospitals, and physicians.

Our TEAM platform is the largest, freshest, most comprehensive All-Payer Database in Healthcare.

Source: The Rural Care Network Revenue Problem

Quantifying the Volume Revenue Relationship

Quantifying the Volume Revenue Relationship

Our phTEAM product allows users a full view of their local healthcare network, from pre-acute episodes, through a hospital stay, all the way to post-acute care such as SNF’s and PM&R groups. A deep understanding of this network allows healthcare facilities and physician practices to align themselves with providers who offer quality care to a large patient volume.  While phTEAM can paint a clear picture of patient volume moving through a market, we wanted to see if there was a direct correlation between the patient volume seen in phTEAM and a hospitals net income.  We combined income data from 2014 HCRIS reports to 2014 medicare teaming data from phTEAM for 1,579 acute care facilities across the country to see what effect shared patient visits had on a hospital’s net income.

phTEAM aggregates data using a 30 day window when a patient is seen between two providers.  We capture the shared treatment visits (all clinical treatments), unique patients, and same day visits shared between the two providers. To help quantify the relationship between volume and revenue, we combined Net Income from the 2014 Healthcare Cost Report Information System (HCRIS), and 2014 shared visits, unique patients, and same day visits from phTEAM by hospital, where the hospital was the second provider to see the patient.

Once the data was aggregated, we were left with a sample size of 1,579 hospitals that had net income reported in HCRIS and a significant amount of pre-acute shared visits, unique patients, and same day visits.  We used R to analyze the data and after checking for normality, a Pearson-R correlation was employed to quantify correlations between unique patients, same day visits, shared treatment visits, and net income.  The result was a positive correlation with all three variables. A 28% positive correlation was found in Net Income and Shared Visits (r=.2716, n=1579, p <0.05), Net Income and Unique patients had a 32% correlation (r=.3173, n=1579, p <0.05), and Net Income and Same Day Visits had a correlation of 24% (r=.2350, n=1579, p <0.05) which are all statistically significant. These results suggest that a significant relationship does exists between patient volumes seen in phTEAM and a hospital’s net income.


–Luke Wylie, Data Scientist, Perception Health



* Thanks to Nick Enko for excellent data processing on this study

The post Quantifying the Volume Revenue Relationship appeared first on Perception Health.

Source: Perception

Understanding Geographic Variability in Healthcare

Understanding Geographic Variability in Healthcare

Understanding reimbursement patterns is critical to any healthcare provider who accepts Medicare patients.  Fortunately, a wealth of data is released by CMS that helps shed light on the Medicare system.  One of the most interesting files released is the Hospital Service Area File (HSAF), which breaks down Medicare inpatient claims and charges across a calendar year by ZIP code.  The geographic nature of this data set makes maps an obvious choice to help understand how these charges vary across the country.  The first way of looking at this data is to visualize total Medicare Inpatient Charges by ZIP Code.


This map follows a pattern one would expect when looking at a trend across the continental United States. Areas of higher population, like New York, Chicago, and Los Angeles have more patients and thus a higher total amount of Medicare charges.  Florida has an extremely high amount of total Medicare charges throughout the entire state (not just the state’s population centers), most likely attributed to the state’s high number of 65+ Medicare recipients.

The second and most meaningful way to visualize this data is to normalize it by dividing the total charges by inpatient cases per zip code.  This removes the focus on major population centers and instead paints a more interesting picture about where charges per case are the highest.


Here we see a shift in the story.  Instead of hotbeds in New York, Los Angeles, and western Arizona, we see several regions of the county that have much higher averages charges per case than others.  States like California, Colorado, and New Jersey show much higher charges per case than states like Michigan, the Dakotas, or Minnesota.  This brings to light interesting questions for physicians and healthcare managers in these states.  For instance, are there more expensive procedures being performed in these states, do certain states see higher acuity patients, or do hospitals and physicians bill more for the same procedures?

Additionally, from a retiree point of view, should you plan to retire in an area with a low average charge per case?

With CMS predicting our National Health Expenditure to reach $5,000,000,000,000  by 2022 (available here), these are questions healthcare professionals and policy-makers should not take lightly.


–Luke Wylie, Data Scientist, Perception Health

The post Understanding Geographic Variability in Healthcare appeared first on Perception Health.

Source: Perception

Pareto lives in healthcare

Pareto lives in healthcare

8020ruleVilfredo Pareto hypothesized the 80/20 rule which became known as the Pareto Principle.  In his study, he found 80% of the land in Italy was owned by 20% of the people.

Using the same basis, we hypothesized that 80% of healthcare’s spend is consumed by 20% of the patients.  As luck (or more appropriately science) would have it, we were not far off.  Using our 3.5 billion claims in 2015 and 2016, we found that 80% of the spend is consumed by 17.8% of the patients.  In healthcare, like land ownership in Italy, a large portion of our expenditures as an industry is being consumed by a small percentage of users.  Most of this phenomenon in healthcare is driven by multiple chronic diseases which affects a disproportionately growing number of Americans.

Today, we are merely understanding how utilization translates into different care options for patients.  What if we could lower healthcare costs by 20% by just getting the right patients to the right providers?  We will dig into this more at a later date.


The post Pareto lives in healthcare appeared first on Perception Health.

Source: Perception