This article is written by Joseph A. Jackson, Managing Director of Strategic Healthcare Services.
Moneyball is a book written by Michael Lewis and later a movie starring Brad Pitt. The premise of Moneyball is using deep, empirical data to manage the financial resources of an organization, in this case a baseball team, as efficiently as possible. The principle concept in Moneyball says you can't necessarily trust what you see, hear, or what your "gut" tells you. Emotions and group thinking can play tricks on you. One of the best examples given in the book is the difference between a .300 hitter and .275 hitter (in baseball a .300 hitter is considered to be a top performer while a .275 hitter is considered to be average). The difference is minute — the .300 hitter will get one additional hit every two weeks compared to the .275 hitter. One hit. That is the difference between great performance and average performance. The difference is so small you would never notice it with the naked eye. The only way you would know the difference is by looking at the data.
I believe the same argument can be made for managing implant utilization and spend in the OR. If a hospital does not consistently have deep, empirical data, it has a crippling effect on the ability to keep costs for these products under control. Small changes in product utilization can have a huge financial impact. You can't manage what you can't see.
A major objective for many hospital administrators is managing and reducing physician preferred item (PPI) costs. However, this task is not without its challenges. One of those challenges is the human and capital resources available to hospitals. Most hospital budgets don't have much room built in for extra FTEs or a large software solution.
A second, and in many ways a larger problem than the lack of resources is the lack of available usage and cost data for total joint, spine, trauma, sports medicine and cardiology cases. High level information such as total implantable product spend from the month end P & L statements, total OR cases and total spend by manufacturer is generally available. That's good information but much too high level to get an idea of what products are specifically being used in the OR, how the products are used, by which surgeons, and at what unit cost. For most hospitals, detailed reports for PPI usage and spend doesn't exist. If you are not sure if you have good data, ask yourself or your staff the following questions:
• Do you have any ability, on demand, to analyze implant utilization and costs by surgeon, by procedure type and by surgical case?
• Are you certain the capitated (CAP) or system prices set in your implant contracts are still advantageous? If so, how are you certain? Are you being told by someone else or are you able to verify this through data?
• Are there different components being used outside the CAP or system, thus reverting the pricing for all components used during the case to ala carte?
• Are all the products being used in a total joint, trauma, spine, cardiology or sports medicine case under contract?
• Are you able to see if demand matching (if applicable) is being used effectively or at all?
If you receive answers such as: "No", "I don't know", or a person gives you an anecdotal answer as to what they 'think' is occurring — you need hard data.
The relevant data points exist somewhere in your hospital. The trick is finding the data, mining it, and electronically cataloging it so you can conduct a meaningful analysis. Once the data is compiled, you will have an electronic, clean and concise report that you can sort and/or aggregate the relevant data elements by surgeon, by procedure type and by case. Having the data organized in this fashion will present a wealth of insight you didn't previously have.
When you first review your new report, what you find will likely surprise you. In most hospitals there is a disconnect between the products and price structure in the contracts to the products and price structure actually being used in the OR. In my experience, this typically isn't a case of a manufacturer being duplicitous or the hospital being "asleep at the wheel." It has more to do with a lack of good case level product cost and utilization data in combination with the OR being very dynamic. Here are two common examples of what a hospital might find:
1. CAP prices aren’t being utilized. If a surgeon makes a small change in his/her construct preference, it can have a big financial impact. Very often, changes such as this can be considered outside the CAP, thus reverting all components to the standard discount vs. the CAP discount. A lot of money might be left on the table due to small operational changes you simply can't see without this level of data to analyze.
2. A hospital is focusing on the wrong surgeon for cost reduction. Example: Dr. Smith consistently has cases where they are fusing two or three levels of vertebrae. As such, their total costs per case would appear high. Dr. Jones consistently performs single level fusions thus their total costs per case seem competitive. By collecting such a deep level of data to analyze, a hospital might find the price they are paying for Dr. Jones's products is much higher then what they are paying for Dr. Smith's products. If a hospital doesn't have this level of data to analyze, they could be looking in the wrong places for savings and the real opportunity would remain invisible.
Leaks in a hospital's PPI contracts are typically a consequence of not consistently having robust data to analyze — not mismanagement. The initial compilation of this data is a great start but this should not be a one-and-done project. The key to long term success is mining and compiling the usage and cost data each and every month to ensure projected savings turn into actual savings. Remember the "leaks" example above; the OR is a very dynamic place. Things can and will change quickly.
One of the challenges for any organization implementing a new program is consistency over the long term. After the initial push to get the program and reporting established, hospitals need to be careful not to allow competing priorities to slowly pull it in different directions. If a program such as this isn’t given high priority, six months will go by without anyone compiling the data, and a hospital will be back to square one. Considering the various hospital reimbursement reform measures being trialed (Bundled Payments, Accountable Care, etc) this task needs its own focus and speed as it will play a pivotal role in supporting the financial health of hospitals across the country.
About Strategic Healthcare Services
Strategic Healthcare Services (SHS) is a strategic financial consulting firm with a specialization in implant transaction management. Our goal is to create a partnership to ensure your total joint, spine, trauma, and cardiology services lines are as financially strong as possible.
SHS services include Data Enrichment, Contract Compliance and Product Usage Assessment, Cost Benchmarking, and Cost Reduction Strategy and Implementation.
Moneyball is a book written by Michael Lewis and later a movie starring Brad Pitt. The premise of Moneyball is using deep, empirical data to manage the financial resources of an organization, in this case a baseball team, as efficiently as possible. The principle concept in Moneyball says you can't necessarily trust what you see, hear, or what your "gut" tells you. Emotions and group thinking can play tricks on you. One of the best examples given in the book is the difference between a .300 hitter and .275 hitter (in baseball a .300 hitter is considered to be a top performer while a .275 hitter is considered to be average). The difference is minute — the .300 hitter will get one additional hit every two weeks compared to the .275 hitter. One hit. That is the difference between great performance and average performance. The difference is so small you would never notice it with the naked eye. The only way you would know the difference is by looking at the data.
I believe the same argument can be made for managing implant utilization and spend in the OR. If a hospital does not consistently have deep, empirical data, it has a crippling effect on the ability to keep costs for these products under control. Small changes in product utilization can have a huge financial impact. You can't manage what you can't see.
A major objective for many hospital administrators is managing and reducing physician preferred item (PPI) costs. However, this task is not without its challenges. One of those challenges is the human and capital resources available to hospitals. Most hospital budgets don't have much room built in for extra FTEs or a large software solution.
A second, and in many ways a larger problem than the lack of resources is the lack of available usage and cost data for total joint, spine, trauma, sports medicine and cardiology cases. High level information such as total implantable product spend from the month end P & L statements, total OR cases and total spend by manufacturer is generally available. That's good information but much too high level to get an idea of what products are specifically being used in the OR, how the products are used, by which surgeons, and at what unit cost. For most hospitals, detailed reports for PPI usage and spend doesn't exist. If you are not sure if you have good data, ask yourself or your staff the following questions:
• Do you have any ability, on demand, to analyze implant utilization and costs by surgeon, by procedure type and by surgical case?
• Are you certain the capitated (CAP) or system prices set in your implant contracts are still advantageous? If so, how are you certain? Are you being told by someone else or are you able to verify this through data?
• Are there different components being used outside the CAP or system, thus reverting the pricing for all components used during the case to ala carte?
• Are all the products being used in a total joint, trauma, spine, cardiology or sports medicine case under contract?
• Are you able to see if demand matching (if applicable) is being used effectively or at all?
If you receive answers such as: "No", "I don't know", or a person gives you an anecdotal answer as to what they 'think' is occurring — you need hard data.
The relevant data points exist somewhere in your hospital. The trick is finding the data, mining it, and electronically cataloging it so you can conduct a meaningful analysis. Once the data is compiled, you will have an electronic, clean and concise report that you can sort and/or aggregate the relevant data elements by surgeon, by procedure type and by case. Having the data organized in this fashion will present a wealth of insight you didn't previously have.
When you first review your new report, what you find will likely surprise you. In most hospitals there is a disconnect between the products and price structure in the contracts to the products and price structure actually being used in the OR. In my experience, this typically isn't a case of a manufacturer being duplicitous or the hospital being "asleep at the wheel." It has more to do with a lack of good case level product cost and utilization data in combination with the OR being very dynamic. Here are two common examples of what a hospital might find:
1. CAP prices aren’t being utilized. If a surgeon makes a small change in his/her construct preference, it can have a big financial impact. Very often, changes such as this can be considered outside the CAP, thus reverting all components to the standard discount vs. the CAP discount. A lot of money might be left on the table due to small operational changes you simply can't see without this level of data to analyze.
2. A hospital is focusing on the wrong surgeon for cost reduction. Example: Dr. Smith consistently has cases where they are fusing two or three levels of vertebrae. As such, their total costs per case would appear high. Dr. Jones consistently performs single level fusions thus their total costs per case seem competitive. By collecting such a deep level of data to analyze, a hospital might find the price they are paying for Dr. Jones's products is much higher then what they are paying for Dr. Smith's products. If a hospital doesn't have this level of data to analyze, they could be looking in the wrong places for savings and the real opportunity would remain invisible.
Leaks in a hospital's PPI contracts are typically a consequence of not consistently having robust data to analyze — not mismanagement. The initial compilation of this data is a great start but this should not be a one-and-done project. The key to long term success is mining and compiling the usage and cost data each and every month to ensure projected savings turn into actual savings. Remember the "leaks" example above; the OR is a very dynamic place. Things can and will change quickly.
One of the challenges for any organization implementing a new program is consistency over the long term. After the initial push to get the program and reporting established, hospitals need to be careful not to allow competing priorities to slowly pull it in different directions. If a program such as this isn’t given high priority, six months will go by without anyone compiling the data, and a hospital will be back to square one. Considering the various hospital reimbursement reform measures being trialed (Bundled Payments, Accountable Care, etc) this task needs its own focus and speed as it will play a pivotal role in supporting the financial health of hospitals across the country.
About Strategic Healthcare Services
Strategic Healthcare Services (SHS) is a strategic financial consulting firm with a specialization in implant transaction management. Our goal is to create a partnership to ensure your total joint, spine, trauma, and cardiology services lines are as financially strong as possible.
SHS services include Data Enrichment, Contract Compliance and Product Usage Assessment, Cost Benchmarking, and Cost Reduction Strategy and Implementation.