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Healthcare Data

Physician Leakage & Using Data to Prevent Outward Migration

healthcare data security, healthcare patient privacy, healthcare cybersecurity

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.

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