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physician leakage, outward migration, healthcare data analytics, big data healthcare

By Ed Willard

Physician Leakage & Using Data to Prevent Outward Migration

Physician Leakage & Using Data to Prevent Outward Migration

Physician referrals are a link between primary and specialty care and are vital to patient management and volume within a healthcare system. In fact, visits to specialists constitute more than half of outpatient physician visits in the United States. Physician leakage refers to the process of physicians referring patients to competing hospitals or providers outside of their network.

A recent article Dropping the Baton: Specialty Referrals in the United States notes the following breakdowns and inefficiencies in all components of the specialty-referral process:

Outward migration affects both patient care and a hospital’s bottom line:

  • Reduced continuity of care
  • Delays in diagnosis and treatment
  • Duplication of services and testing wasting hospital resources
  • The simultaneous use of multiple drugs to treat a single ailment or condition, or polypharmacy
  • Increased risk of malpractice lawsuits
  • Weakened physician-patient relationships

Physician Leakage and Outward Migration

Looking more closely at the financial impact of outward migration, let’s look at this example provided by Lance Fusacchia in an HFMA article:

“Consider for a moment the potential financial losses of referral no-shows in terms of actual dollars. As an example, a typical healthcare system with 200 providers, each serving a panel of 2,000 patients. Of those 400,000 patients, it is fair to estimate that 50 percent visit their physicians and 30 percent of those visits result in a referral. That makes 60,000 potential referral visits. If 30 percent of those referrals don’t happen (the average number of no-shows, as cited previously), that’s approximately 18,000 lost referrals. According to findings in one study, a single no-show costs a provider, on average, $210. Multiplying that amount by 18,000 no-shows results in $3.78 million in lost revenue. If a health system could avert even 25 percent of those lost referrals, it could recover nearly $1 million in lost revenue.”  

The Role of Data in Preventing Outward Migration

Data plays a major role in the prevention of outward migration. Having data alone, however, won’t solve the challenges. Being able to have the data analytics tools to gain key insights from the data will provide the needed information to adjust physician referral management programs and processes.

  • Comparing Past to Present Data – Historical data can allow for a view of events that may be factoring into lost business. A referral drop is a cause for concern to be investigated and resolved.
  • High-Tail & Long-Tail – These are common terms in marketing and should be applied to outward migration data analytics. Basically, high-tail means that 80% of monitored events occur in the first 20% of a population metric. Low-tail comprises the remaining 20% of monitored events, but it can often outweigh the overall high-tail impact. By analyzing where business is coming from on both ends of the tail, you may be surprised that the long-tail is equally, if not more, responsible for driving volume.
  • Where You Stack Up in the Industry – Data analytics can show you where you stack up with your competitors, helping you to establish a baseline to measure performance against.
  • Interoperability – One of the holy grails of healthcare is interoperability both within and outside of a healthcare network. Healthcare systems have long operated private health information exchanges within their networks and the Affordable Care Act has helped to promote public exchanges to share data across systems. The continued advancement of this data sharing effort will progressively close the referral tracking information gap that challenges both physicians and hospital executives.

At Intellimed, we have provided healthcare data analytics solutions to the U.S. hospital marketing for 30 years. Contact us to learn more about leveraging data to prevent outward migration and stop physician leakage.

Ed Willard serves as INTELLIMED’s Executive Director of Business Development and is a member of the INTELLIMED leadership team. In his free time, he enjoys soccer and is involved in several local soccer organizations.

Healthcare big data

By Bill Goodwin

Three Tips to Prevent Big Data From Causing Big Problems

Three Tips to Prevent Big Data From Causing Big Problems

If you are like most leaders in business, you hear the words “Big Data” being used in promotions, internal meetings, vendor presentations and more. Big data – to an increasing extent – has become synonymous with “we can help you find the answers you need and improve profits.”

And, there is some truth in this statement. According to the International Institute for Analytics, businesses that use data will see $430 billion in productivity benefits over their competition not using data. Forrester predicts that real-time streaming insights into big data will be the hallmarks of data winners going forward. Without a doubt, data can help us make better more informed decisions. However, it is possible to over-rely on big data as a panacea for answers to complex healthcare business decisions.

Countless times I have been in meetings with vendors, internal personnel and clients where healthcare big data is mentioned in some form or another as being the solution to helping (better yet telling) them what to do. The competitive pressure in all markets today forces individuals to make decisions faster and more accurately, so the appeal of fresh insights from new clinical data analysis becomes extremely appealing.

In many ways, tapping into healthcare big data analytics can help, but all of us should be extremely careful about placing too much stock in there always being clear, action-oriented and effective go-forward strategies to be found in big data. In fact, I have been in front of many prospective clients over the last few years and they mention, albeit sometimes reluctantly, that they have been burned by previous companies who offer data-driven tools designed to provide answers they had previously been unable to find. So not only has big data in hospitals been marketed as the solution, it has also started to develop a reputation as being overrated.

Big data, more accurately described, is a general, all-inclusive term for a variety of complex data collection, processing and analysis generation that traditional applications are unable to handle. There is no question the accumulation and analysis of new data can be helpful to every organization. However, take ten organizations in the same industry that have the same big data inputs and I guarantee all will come out with different conclusions on what they should do next. Seems logical, yes, but how do you ensure your organization is not one of the ones that makes a critical misstep?

While big data can certainly provide critical insights for healthcare decision makers, we must approach big data cautiously and through a measured perspective. Here are three important considerations with regard to big data to leverage immediately:

  • Be Aware of Personal and Internal Bias
    All analyses have some level of personal or organizational bias. Whether it is how the analyses are set up or how the information is interpreted, it is essential to a) know there will always be bias and b) try to factor that out in the final interpretation. In other words, while there is no way to fully eliminate bias, you can be aware of what it is and modify your interpretation accordingly. Most leaders are aware that there is bias in all analyses, yet some continue to make decisions without taking bias into consideration.
  • Understand Correlation Versus Causation
    I have seen too many leaders make detrimental decisions when they mistake correlation with causation. High positive or high negative correlation does not always mean causation, whether one is looking at two variables or a multi-variable analysis. Be sure to factor this in before any major decisions are made. Dig deeper, look at the problem or opportunity from more angles and get other viewpoints before settling in on the final decision.
  • Tap Into Your Intuition
    In this new data-driven society, we are becoming so data dependent that using intuition is becoming a thing of the past. In fact, I would argue the art of intuition has been lost in many organizations. We have all had situations where the “data” told us to turn left, but our gut told us to turn right. And, how many times did all of us turn left due to an analyses only to find out right was the better direction? Intuition is essential to any decision-making process and simply cannot be excluded. If you don’t have a good feel for the decision you need to make, rely on data more. If your intuition is telling you what decision you should make, pay more attention to it, regardless of what the analysis suggests.

Some data experts predict that we have already begun to move away from the era of big data in favor of “fast data” and “actionable data,” noting that most businesses don’t use a fraction of the data they have access to and should focus on asking the right questions to make the best use of data, big or otherwise. Certainly these data analytics changes will enable us to continue to enhance our insights and subsequent decisions.

With the continual advancement of how we access and perform big data analytics as a service, it’s hard to argue that it’s not a necessary component of healthcare decision making – but it’s not the only factor. Regardless of the direction that big data goes, coupling the knowledge gained from data with our experience and intuition – and knowing when to favor one over the other – will become increasingly important in our complex healthcare landscape.

Bill Goodwin is CEO of INTELLIMED, a leading healthcare analytics company.

physician leakage, outward migration, healthcare data analytics, big data healthcare
Physician Leakage & Using Data to Prevent Outward Migration
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