August 17 2016 | 0 Comments | 175 reads Average Rating: 3

Health Reform: Will it Really Affect Whether or Not Patients Undergo Surgery?

by Dr. Kevin Keck in Health Analytics

Under fee-for-service payment models, making the decision to move forward with many surgeries – such as total knee replacements – was not a difficult one to make.

Here’s an example of how it would commonly unfold: A patient experiences knee pain. The patient receives a prescription for painkillers. The condition deteriorates, and MRI is obtained and eventually the patient undergoes the total knee replacement as a matter of course. Because such surgeries were profitable for hospitals and orthopedists under the long-held fee-for-service model, no one bats an eye.

But that’s changing. Under value based care, healthcare organizations are now rewarded for keeping patients well and achieving the best outcomes – so surgeries need to be done with highest quality including scrutiny of the indication to operate.

As a result, providers are being called on to use predictive analytics to transform their decision-making approach, especially when it comes to “preference sensitive” surgeries (such as knee replacements) — where there are no definitive guidelines for proceeding with a surgical intervention and when multiple treatment options exist.

Instead of just forging ahead with surgery, healthcare providers can now use analytics to:

1. Pinpoint patients that might not really need the surgery. Advanced predictive analytics can help providers accurately predict which patients might or might not require surgery during a specified timeframe. Armed with this information, they can leverage non-surgical interventions to help patients improve their health without the need for expensive and invasive surgical options, lowering the cost of care while increasing quality and patient satisfaction.

2. Intervene with alternatives. With predictive analytics, providers can get a handle on the costs associated with various treatment options. With such information, they (along with their patients) can discuss the pros and cons of pursuing earlier non-surgical interventions. It is particularly useful for patients where there is high risk due to other conditions. A knee replacement that would be a good choice for a patient who is strong overall may not be the best choice for one who is more fragile. Shoe inserts, physical therapy and some weight loss can offer similar pain relief – and spare some patients the pain, expense and long road to recovery associated with surgery.

3. Identify cases were surgery might not be provide good enough. Analytics can also be leveraged to determine if the results will be good enough. In many cases, surgery might not be enough to restore patients to a sufficiently high quality of life, potentially adding to the overall burden of sick care. For example, preference- sensitive procedures on patients who are chronically ill frequently are not enough to help improve overall health.

The approach to surgical decisions is just one thing that is poised to change under value based care. Can you think of any other decisions that might be made differently?

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Author
Dr. Kevin Keck
Chief Medical Officer

Dr. Keck is SCIO’s Chief Medical Officer and leads the Clinical Analytics development team. His responsibilities include assessing the leakage and the impact of quality and cost in Provider Analytics.

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