Patient Loyalty and Market Share

Predictive AnalyticsBy Sarianne Gruber
Twitter: @subtleimpact

Would you recommend your physician to friend or relative? What would be your reasons for recommending them? Is it because you like the selection of magazines in the waiting room or the self-serve coffee flavors?  In all seriousness, the research team of Press Ganey, an organization with a mission to improve healthcare performance, wanted to know what earns patient loyalty and market share in this highly competitive healthcare market.

Why does customer loyalty and market share matter? In the recently published Press Ganey Research Note: Consumerism: Earning Patient Loyalty and Market Share, there are several factors why retaining patient loyalty is imperative. Notable concerns are:

  • Market share matters – Whether it is fee-for-service or capitation, providers need patients to have a successful and sustainable organization.
  • Due to the economics of today’s choices for coverage, people are questioning more than ever the costs of plans and services, and are willing to change doctors and hospitals that suit their budget.
  • The public is being greatly influenced by health insurance products, various online sources as well as mergers and associations, which are creating new brands across markets. No matter what may challenge a patient’s choice, the drivers for maintaining patient loyalty are “the factors that are within the control of the clinicians at all levels of healthcare – in the hospital, in emergency departments (ED) and in ambulatory offices.”

To understand what drives patient loyalty, Press Ganey analyzed overall ratings of providers in outpatient, inpatient and ED settings to identify the leading factors. The statistical method of choice was recursive partitioning, a non-parametric technique that creates hierarchical subsets to determine the strongest factors first then continues to subset further (like branches of a tree) to next the set of factor. The visual display of this statistical method is called a tree analysis.

Press Ganey set out to study “likelihood to recommend” as a loyalty measure. Quantifying this behavior is basically an extension of how well providers met patients’ needs. The analysis uncovered what behaviors are important in meeting patients’ needs such as peace of mind, compassion, coordinated care and optimal clinical outcomes versus in meeting patients’ expectations.

Summarized Findings:

With a sample of 937,000 patients, the drivers of Likelihood to Recommend for an outpatient setting were:

  • Confidence a patient had in his or her clinician
  • Perception that care team worked well together
  • Perception that caregiver had concern for patient’s worries.

Based on 1.2 million inpatients, the drivers of Likelihood to Recommend for a hospital setting were:

  • Perception that staff worked well together
  • Expectation on cleanliness of hospital rooms
  • Empathy demonstrated by the nurses.

Based on 1.39 million ED patients, the drivers of Likelihood to Recommend for a emergency facility

  • The staff was perceived as caring
  • How well the physician kept the patient informed
  • Information about delays and follow-up care.

A separate analysis between communication and wait time showed communication is what matters. The findings showed that when patients considered information on delays to be excellent, they were highly likely to recommend the ED despite waiting several hours.

Research Takeaways:

Patient loyalty strategies as highlighted from Press Ganey

  • Teamwork and coordination
  • Empathy
  • Communication with other clinicians and patients themselves
  • Courtesy

Press Ganey’s research clearly lays the framework for strategies for the new health care market place.  For a complete review and analysis details, please refer to the study website.