Value-based care is complicating provider revenue cycles
Sharp Healthcare and other providers are applying more analytics and IT expertise to keep dollars flowing.
In accounts receivable, cash has always been king. Now so is data.
Value- and quality-based reimbursement contracts are becoming more common, making the revenue cycle ever-more complex and potentially squeezing margins. In response, revenue cycle managers are loading up on data to try to improve every facet of the revenue cycle and squeeze more cash flow out of operations.
To do so they are aggregating and analyzing information to drive workflow changes throughout the revenue cycle—from appointment scheduling to denials management. They are also automating routine workflows, such as processing claims and preventing payer denials.
Ultimately, they’d like to utilize artificial intelligence and predictive analytics for their efforts. However, those tools are not on the short-term radar of most revenue cycle operations.
First things first: To glean really useful insights, revenue cycle managers need to work with aggregated data from disparate information systems deployed in both the financial and clinical realms. But many hospitals and health systems have not reached that level of integration. As they merge and buy physician practices and other healthcare entities, the number of disparate information systems they manage is rising. Incorporating data from outside sources—such as health information exchanges—also contributes to interoperability challenges.
“The inability to get a complete holistic view of a patient record—including the patient billing cycle, the financial picture of the patient—makes it very difficult to perform large-scale analytics,” says Blain Newton, executive vice president of HIMSS Analytics. “It is really across many platforms.”
RCM mishmash
And lots of different types of data is being pushed through a mishmash of revenue system technologies. Many organizations use multiple software products even within the revenue cycle area, according to a 2018 survey of 95 hospital and health system leaders conducted by HIMSS Analytics. A total of 29.5 percent of survey respondents reported using an electronic health record with three or more other systems; 18.9 percent relied solely on an EHR vendor’s business modules to manage the revenue cycle.
Meanwhile, other organizations reported using multiple solutions from non-EHR vendors in revenue cycle management: 13.7 percent used three or more vendor products, 6.3 percent used two or more products, and 13.7 percent used a single solution.
Given the number of information systems both inside and outside of the revenue cycle area, it is not surprising that survey respondents cited interoperability (75.8 percent) and data stuck in silos (66.7 percent) as the key challenges they face.
Sharp HealthCare, for one, would like to automatically feed data from a commercial coding product to its enterprisewide data warehouse. So far, the vendor of the coding product has not complied with the health system’s request. Instead, Sharp uses the vendor’s proprietary report writer to pull data and then join it with data from other information systems, such as payroll, for specific projects—evaluating coders’ productivity, for example.
“It makes us jump through extra hoops,” says Melanie Betancourt, director of system integration for revenue cycle operations at Sharp HealthCare. She did not disclose the name of the vendor.
Lack of control
Another challenge to corralling all the data is inadequate control over the data and dashboards necessary for revenue cycle management, limiting managers’ flexibility to respond to problems quickly, contends Jerica Hopkins, research director for Healthcare Business Insights, a research and training organization, which is part of Decision Resources Group, a research firm. “Revenue cycle leaders actually want to access the data in real time, so they need to have more access or more ownership over the data.”
In a 2018 survey, Healthcare Business Insights found that most respondents had set up a formal structure to dedicate personnel with data expertise to revenue cycle operations. Many embedded analysts in the revenue cycle department; others assigned analysts from the IT department to revenue cycle projects.
But respondents used a variety of reporting structures. Some analysts reported to both IT and revenue cycle managers, while others reported only to managers in one of these areas or the other.
Analytics efforts
Messy data and reporting structures aside, revenue cycle managers are making headway in their efforts to analyze and act on increasingly large data sets.
For example, Betancourt and others at Sharp HealthCare analyzed how much it costs the health system to code each claim. This enabled Sharp to assess the relative productivity of each coder and led the health system to develop standardized coding procedures.
The University of Pittsburgh Medical Center also analyzed staffing issues and made changes to improve performance. Staff in its central scheduling operation have been organized into pods based on medical specialties, which has streamlined end-to-end operations. “This allows us to more effectively handle patient demand as the schedulers become highly efficient in their assigned pod while also allowing the management and analytics teams to better manage results,” says Lucas Foust, senior director of revenue cycle system development.
Foust, who reports to the vice president of revenue cycle at UPMC, said the total number of calls these staff members handle per day increased 53 percent from April 2017 to April this year.
The University of Iowa Hospitals and Clinics is using analytics to track reimbursement from payers and patients, process claims faster, and reduce and manage denials.
Chris Voss, revenue cycle manager in patient financial services at University of Iowa Health Care, which includes University of Iowa Hospitals and Clinics, and others in the department are using electronic dashboards to pinpoint trends and help automate the process of tracking accounts.
The dashboards display metrics related to outstanding accounts receivable, payments, transactions and denials. The health system pulls data directly from Epic’s billing system, writes queries using SQL, and creates the dashboard visualization using Tableau.
In self-pay accounts specifically, Voss and his team use the information reported in the dashboards to improve how they manage patient balances.
For example, the team identifies patient balances that occur when an insurer denies a claim because it doesn’t know if it is the primary payer on an account. In addition to denials, the self-pay team also focused on aging accounts and those with large balances.
The combination of these strategies has led to significant performance improvements. Voss predicts the effort will have reduced days in accounts receivable for self-pay accounts by half a day for the current fiscal year, which ends June 30. He also expects the number of accounts sent to collection agencies to be down by 10 percent.
Dealing with denial
As is the case for University of Iowa Health Care, denials are a priority for many health systems’ analytics efforts. In the HIMSS study on revenue cycle management, 73 percent of respondents said coping with denials is the biggest challenge for their operations.
Denials certainly are a priority at Sharp HealthCare, where staff in revenue cycle management have automated the coding and billing process to decrease the number of denials and increase the number of clean claims.
Sharp programmed rules around the claims-processing requirements for each payer into a series of software tools that staff use to create claims. The software tools alert staff to situations where the information entered from staff members earlier in the revenue cycle process does not follow the rules. Examples of these types of situations include an enrollee identification number that doesn’t conform to an insurer’s standard numbering system or a missing diagnostic code or modifier. Staff members then fix the issues highlighted by the software before the claim is transmitted to a payer, reducing the risk of a denial.
Gerilynn Sevenikar, vice president of revenue cycle management at Sharp HealthCare, says the health system is continually updating its software as payers add new requirements to the coding and billing process. “Every time we talk about something that has caused a delay in the transmission of a claim, our first question is: Can we build a rule?”
Sharp is revising the software to prevent staff members from overriding exceptions. The software “really lends itself to standardized work and highly reliable outcomes,” notes Betancourt, the director of system integration for revenue cycle operations.
Value- and quality-based reimbursement contracts are becoming more common, making the revenue cycle ever-more complex and potentially squeezing margins. In response, revenue cycle managers are loading up on data to try to improve every facet of the revenue cycle and squeeze more cash flow out of operations.
To do so they are aggregating and analyzing information to drive workflow changes throughout the revenue cycle—from appointment scheduling to denials management. They are also automating routine workflows, such as processing claims and preventing payer denials.
Ultimately, they’d like to utilize artificial intelligence and predictive analytics for their efforts. However, those tools are not on the short-term radar of most revenue cycle operations.
First things first: To glean really useful insights, revenue cycle managers need to work with aggregated data from disparate information systems deployed in both the financial and clinical realms. But many hospitals and health systems have not reached that level of integration. As they merge and buy physician practices and other healthcare entities, the number of disparate information systems they manage is rising. Incorporating data from outside sources—such as health information exchanges—also contributes to interoperability challenges.
“The inability to get a complete holistic view of a patient record—including the patient billing cycle, the financial picture of the patient—makes it very difficult to perform large-scale analytics,” says Blain Newton, executive vice president of HIMSS Analytics. “It is really across many platforms.”
RCM mishmash
And lots of different types of data is being pushed through a mishmash of revenue system technologies. Many organizations use multiple software products even within the revenue cycle area, according to a 2018 survey of 95 hospital and health system leaders conducted by HIMSS Analytics. A total of 29.5 percent of survey respondents reported using an electronic health record with three or more other systems; 18.9 percent relied solely on an EHR vendor’s business modules to manage the revenue cycle.
Meanwhile, other organizations reported using multiple solutions from non-EHR vendors in revenue cycle management: 13.7 percent used three or more vendor products, 6.3 percent used two or more products, and 13.7 percent used a single solution.
Given the number of information systems both inside and outside of the revenue cycle area, it is not surprising that survey respondents cited interoperability (75.8 percent) and data stuck in silos (66.7 percent) as the key challenges they face.
Sharp HealthCare, for one, would like to automatically feed data from a commercial coding product to its enterprisewide data warehouse. So far, the vendor of the coding product has not complied with the health system’s request. Instead, Sharp uses the vendor’s proprietary report writer to pull data and then join it with data from other information systems, such as payroll, for specific projects—evaluating coders’ productivity, for example.
“It makes us jump through extra hoops,” says Melanie Betancourt, director of system integration for revenue cycle operations at Sharp HealthCare. She did not disclose the name of the vendor.
Lack of controlAnother challenge to corralling all the data is inadequate control over the data and dashboards necessary for revenue cycle management, limiting managers’ flexibility to respond to problems quickly, contends Jerica Hopkins, research director for Healthcare Business Insights, a research and training organization, which is part of Decision Resources Group, a research firm. “Revenue cycle leaders actually want to access the data in real time, so they need to have more access or more ownership over the data.”
In a 2018 survey, Healthcare Business Insights found that most respondents had set up a formal structure to dedicate personnel with data expertise to revenue cycle operations. Many embedded analysts in the revenue cycle department; others assigned analysts from the IT department to revenue cycle projects.
But respondents used a variety of reporting structures. Some analysts reported to both IT and revenue cycle managers, while others reported only to managers in one of these areas or the other.
Analytics efforts
Messy data and reporting structures aside, revenue cycle managers are making headway in their efforts to analyze and act on increasingly large data sets.
For example, Betancourt and others at Sharp HealthCare analyzed how much it costs the health system to code each claim. This enabled Sharp to assess the relative productivity of each coder and led the health system to develop standardized coding procedures.
The University of Pittsburgh Medical Center also analyzed staffing issues and made changes to improve performance. Staff in its central scheduling operation have been organized into pods based on medical specialties, which has streamlined end-to-end operations. “This allows us to more effectively handle patient demand as the schedulers become highly efficient in their assigned pod while also allowing the management and analytics teams to better manage results,” says Lucas Foust, senior director of revenue cycle system development.
Foust, who reports to the vice president of revenue cycle at UPMC, said the total number of calls these staff members handle per day increased 53 percent from April 2017 to April this year.
The University of Iowa Hospitals and Clinics is using analytics to track reimbursement from payers and patients, process claims faster, and reduce and manage denials.
Chris Voss, revenue cycle manager in patient financial services at University of Iowa Health Care, which includes University of Iowa Hospitals and Clinics, and others in the department are using electronic dashboards to pinpoint trends and help automate the process of tracking accounts.
The dashboards display metrics related to outstanding accounts receivable, payments, transactions and denials. The health system pulls data directly from Epic’s billing system, writes queries using SQL, and creates the dashboard visualization using Tableau.
In self-pay accounts specifically, Voss and his team use the information reported in the dashboards to improve how they manage patient balances.
For example, the team identifies patient balances that occur when an insurer denies a claim because it doesn’t know if it is the primary payer on an account. In addition to denials, the self-pay team also focused on aging accounts and those with large balances.
The combination of these strategies has led to significant performance improvements. Voss predicts the effort will have reduced days in accounts receivable for self-pay accounts by half a day for the current fiscal year, which ends June 30. He also expects the number of accounts sent to collection agencies to be down by 10 percent.
Dealing with denial
As is the case for University of Iowa Health Care, denials are a priority for many health systems’ analytics efforts. In the HIMSS study on revenue cycle management, 73 percent of respondents said coping with denials is the biggest challenge for their operations.
Denials certainly are a priority at Sharp HealthCare, where staff in revenue cycle management have automated the coding and billing process to decrease the number of denials and increase the number of clean claims.
Sharp programmed rules around the claims-processing requirements for each payer into a series of software tools that staff use to create claims. The software tools alert staff to situations where the information entered from staff members earlier in the revenue cycle process does not follow the rules. Examples of these types of situations include an enrollee identification number that doesn’t conform to an insurer’s standard numbering system or a missing diagnostic code or modifier. Staff members then fix the issues highlighted by the software before the claim is transmitted to a payer, reducing the risk of a denial.
Gerilynn Sevenikar, vice president of revenue cycle management at Sharp HealthCare, says the health system is continually updating its software as payers add new requirements to the coding and billing process. “Every time we talk about something that has caused a delay in the transmission of a claim, our first question is: Can we build a rule?”
Sharp is revising the software to prevent staff members from overriding exceptions. The software “really lends itself to standardized work and highly reliable outcomes,” notes Betancourt, the director of system integration for revenue cycle operations.
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