A major urban health system in the Northeast was losing millions to referral leakage. Nearby health systems of comparable scale and prestige offered patients multiple options for receiving care. The market also contained numerous affiliated providers who could direct services to multiple systems.
Health systems nationwide face similar challenges in referral management, losing significant revenue annually to leakage.1 These challenges are exacerbated by a lack of effective data and analytics capabilities. Although data and analytics are critical to effective referral management, health systems often lack easy access to usable data, strategic focus for their analyses, or operational levers to translate insight into action.
This article is the second in a series that discusses how to impact key drivers of physician referrals, drawing on Chartis’ work with health systems and WebMD Ignite’s analytics and insights on referrals. This article examines how health systems can effectively apply analytics to focus their referral management strategies on the right opportunities, following the journey of this Northeast health system.
Market analytics bring focus to referral management strategies
Developing and implementing enterprise referral management strategies is complex. Patient and provider preferences arise from the experiences and expectations of multiple groups of consumers: referring providers, receiving providers, and patients. Managing these expectations and strengthening relationships with patients and providers requires dedicated time and effort. Health systems must also maintain these relationships in the face of shifting market forces.
Effective analytics help identify which patient and provider relationships require the most attention. For example, a health system may leverage claims data to identify service lines in need of development, based on uncaptured market share. Combining claims and encounter data can allow a health system to identify out-of-network referrals and specific areas of patient leakage. Monitoring market share and out-of-network referrals over time can reveal whether referral management operational processes are effective.
With the right insights at the right time, health systems can ensure their referral management strategies and resources make a real impact.
Three steps to drive impactful analysis and action
Applying analytics to referral management involves more than pulling up a report or dashboard. Following are three broad steps health systems must first consider:
1. Determine what insights the organization needs
Before diving into the data, health systems should clearly identify the questions they want to ask and the decisions they want to drive. This will inform subsequent decisions about required data and analyses.
At minimum, health systems should align their data and analytics needs with their strategic priorities. For example, health systems concerned about market competitiveness should assess their market share against key competitors, segmenting their analyses by diagnosis, demographics, and service line to highlight specific areas of action. To understand changes in market share over time, health systems might then prioritize data points related to the care experience, such as patient feedback, provider referral patterns, and quality ratings.
The Northeast health system in our case study wanted to drive targeted relationships with providers in priority service lines such as cardiology and neurology. Leaders identified a broad range of insights required to drive this effort, such as the economic opportunity of each service line, service line market share, and referral patterns by individual provider.
2. Set up the right data and analyses
Health systems should guide their data and analytics needs based on the insights they need, likely requiring multiple data points for a complete picture. For example, projections of service line financials would require reimbursement, claims, and demographic data to determine market size and growth opportunity.
Certain insights may require especially sophisticated analyses. For example, claims and encounter data can reveal individual referral patterns, but only after extensive data cleaning and advanced analytics. In these cases, health systems should also consider whether it is more practical to develop needed capabilities internally or to contract through a vendor.
The Northeast health system wanted to examine individual provider interactions. For more rapid insights, they contracted a vendor with expertise in claims data and referral analytics. By diving deep into their data, the health system validated which competitors and providers were most responsible for leaking referrals to or rendering services in out-of-network facilities. These specific insights also informed targeted strategies to counteract prevailing trends at the provider and facility level.
3. Develop analytics strategies for short- and long-term actions
In the short-term, health systems should respond appropriately to any identified patterns and insights. Qualitative data based on conversations with service line leadership can provide critical context to quantitative trends. Focus groups and experience surveys can help integrate the patient perspective. Based on these findings, health systems can implement appropriate operational improvements to solve for referral management challenges. Open communication with patients and providers will help reveal whether new processes are truly effective.
In the long run, referral management strategy development, execution, and optimization require persistent and consistent analytics. Health systems must build and sustain a formal program structure over referral optimization—and related analytics—to ensure consistent executive attention, resourcing, and progress.
Based on their findings, leaders at the Northeast health system were able to align on service lines of concern, as well as immediate hiring strategies for staffing gaps. In the process, this health system also identified the requirements for developing broader programmatic efforts that will drive consistent referral strategy and management across the organization.
Use the right analytics to improve referral management strategies
Analytic insights can help health systems target the right service lines and patient populations for further referral management efforts. Health systems will find the most value from their data and analytics by being clear on the insights they wish to pursue, bringing the right data and analyses to bear, and ensuring they can act on the insights they uncover. Doing so will allow health systems to focus on the most critical opportunities for bringing services in network.
WebMD Ignite’s companion article offers a deeper dive into considerations for claims data analytics and how this Northeastern health system identified the greatest areas of patient leakage.
In the third installment of this series, we will dive into best practices for implementing operational improvements in referral management at an enterprise level.
Sources
1 “Patient referral leakage FAQ,” WebMD Ignite, Feb. 7, 2023, https://webmdignite.com/faq/patient-referral-leakage.
