Tech optimization: Keeping financial IT humming
Financial information systems are an integral part of the healthcare information technology machine. Without them, healthcare does not get paid for.
That’s why it’s important for healthcare CIOs and CFOs to keep these invaluable information systems humming. And humming optimally. There’s always room for improvement, so CIOs, CFOs and other health IT leaders need to know how to optimize these systems so that they are working at peak levels and helping healthcare provider organizations achieve their specific goals.
Here, five healthcare financial information systems experts offer technology optimization best practices to help provider organization leaders get the most out of their financial IT. These experts are from financial IT companies including Availity, HMS, Kaufman Hall Software and VisitPay.
Avoiding hospital readmissions
One financial IT optimization best practice is for healthcare provider organizations to use predictive models to avoid hospital readmissions, said Dr. Gary Call, chief medical officer at HMS, a healthcare financial information technology vendor.
“Hospital readmissions are very costly for payers with implications for health outcomes, quality scores and finances,” he explained. “Providers also are hurt by hospital readmissions due to financial recoupments from payment integrity audits and payer penalties for excessive readmissions; for example, CMS readmission reduction program penalties. Avoiding preventable hospital readmissions helps patients, providers and payers.”
"Use of AI-driven predictive modeling would allow payers and providers to become hyper-focused on care transition resources on the patients most likely to be readmitted."
Dr. Gary Call, HMS
Providers and payers can develop AI-driven predictive models or engage with analytics vendors that can provide AI-driven predictive models that will determine during the first hospital admission, at the point of care, which patients are likely to be readmitted within a short period of time, he continued.
“Providers and payers currently collaborate on post-hospital discharge care transitions programs,” he said. “However, limited resources often make these programs perfunctory and less than optimal. Use of AI-driven predictive modeling would allow payers and providers to become hyper-focused on care transition resources on the patients most likely to be readmitted.”
Patients considered less likely could receive less intensive care transition interventions, which would save resources while still impacting high-risk patients, he added. Reduction of readmissions results in higher quality healthcare outcomes and lower costs to payers and providers, he said.
Leveraging multi-payer portals
As a best practice, provider organizations should take advantage of multi-payer portals to streamline the process of updating and maintaining provider directory information, said Mark Martin, director of the health plan portfolio at Availity, a financial information technology vendor.
“Every year, provider directory maintenance costs physician practices $2.76 billion, or an average of about $1,000 per month per practice, according to a survey conducted by the Council for Affordable Quality Healthcare,” he noted. “Despite this significant allocation of resources, the industry still falls short, as shown by a recent report from CMS that found that nearly 50% of Medicare Advantage provider directory locations showed at least one mistake.”
The most common errors included the wrong location or phone number, or the directory stated that providers were accepting new patients when they were not.
"By using a single platform for providers to update and manage data for all of their contracted health plans, payers and providers can save time and money with streamlined processes and achieve better data quality and accuracy."
Mark Martin, Availity
“For providers, updating directory information can require significant time and effort, as most contract with a dozen or more health plans, and each plan may have its own forms and processes to follow,” Martin explained. “Indeed, many providers’ challenge around updating information stems from each payer’s different questions and unique ways of requesting and accepting data.”
To overcome challenges associated with inaccurate provider directory information, providers should consider taking advantage of multi-payer platforms, which are centralized portals that enable providers and plans to exchange and reconcile provider data, he advised.
“By using a single platform for providers to update and manage data for all of their contracted health plans, payers and providers can save time and money with streamlined processes and achieve better data quality and accuracy,” he stated. “Further, by delivering a substantial boost to providers’ efficiency, multi-payer platforms much more effectively incentivize providers to maintain current directory data.”
Determination at the point of care
Determining proper insurance coverage at the point of care is another way to optimize finance, said Call of HMS.
“Some patients have access to health insurance coverage from several sources; for example, Medicaid and commercial insurance,” he said. “Many times patients are either unaware of or don’t share information on all their coverage, which prevents providers from billing the appropriate insurance payer. Billing the wrong payer as primary can result in costs of re-work to bill appropriately in cases where coordination of benefits activities are necessary.”
In many cases, billing the wrong payer can result in lost revenue from lower reimbursement – such as getting reimbursed from a lower paying Medicaid fee schedule when a patient really has a commercial insurance available.
“Incorrect initial billing also can result in lost revenue from failure to meet prior authorization or formulary requirements of the true primary payer, resulting in diminished or no reimbursement for services provided,” Call said.
Providers should consider engaging with a vendor that has AI-driven eligibility matching logic models and access to large eligibility databases, he suggested.
“These models can rapidly validate the primary insurance presented at the point of care by the patient,” he explained. “Rapid verification or identification of the true primary payer allows providers to bill with confidence knowing they will avoid the re-work costs of corrected billing as well as potential revenue loss from lower fee schedules or failure to meet authorization requirements.”
Advanced tech and prior authorizations
When it comes to financial IT optimization best practices, healthcare provider organizations should leverage advanced technologies to automate the prior authorization process, contended Jeremy Sacks, product director for authorizations and referrals at Availity.
“While prior authorizations are often an important and necessary part of the prescribing process, serving as a tool that supports evidence-based guidance and protecting against excessive medication costs, they often lead to frustration by medical practices due to time-consuming, manual steps,” he stated.
"Because prior authorization does not follow a one-size-fits-all process, and generally involves multiple steps of varying complexity, even the process itself adds to the challenge of automation."
Jeremy Sacks, Availity
However, in recent years, systems that automate the frequently labor-intensive prior authorization process have become available to providers, he noted. This automation offers substantial benefits to medical practices, including reduced costs, greater operational efficiency, greater physician and staff productivity, and, most important, greater patient satisfaction, he contended.
“Because prior authorization does not follow a one-size-fits-all process, and generally involves multiple steps of varying complexity, even the process itself adds to the challenge of automation,” he said.
Following, according to Sacks, are three key areas of functionality that an automated prior authorization system should deliver:
- Verification: Upon integration with a medical practice’s electronic health record, prior authorization technology must have the capability of automatically checking for eligibility and benefits to immediately determine whether authorization is required.
- Submission: Prior authorization technology should automate the administrative work associated with a submission, freeing up staff and physicians to focus only on the most important clinical tasks, and allowing all team members to work at the top of their licenses.
- Status: One of the chief benefits of automated prior authorization technology should be that it should free staff from having to continuously scan the patient portal to see whether a prior authorization request has been approved. Upon approval, the technology should automatically send a notification with key information, such as approval number, valid dates and an archived screen capture of the authorization details. For audit purposes, the system also should automatically attach the documentation to the patient’s record in the EHR.
On another front, in a recent survey, 75% of financial leaders at healthcare organizations said they were planning to invest in technology to help achieve performance improvement and cost transformation goals within the next two years.
“They are feeling that pressure to invest because they recognize the need to dig deeper and deploy more sophisticated analytics and drive cost savings,” said Kermit S. Randa, CEO of Kaufman Hall Software, a vendor of enterprise performance management software and data and management consulting services. “They are right to do so, but reducing costs and improving financial performance is not only a matter of investing in technology – healthcare organizations need to connect and analyze key data to realize significant improvement.”
"With so much data available in one place, it could be a challenge to figure out where to focus and identify top opportunities for improvement – this is where comparison data comes into play."
Kermit S. Randa, Kaufman Hall Software
Data integration makes information available faster and helps build trust in the accuracy of costing data, he said. Seamlessly sharing data across systems also removes the very real risk of human error when information flows securely without manual re-keying, he added.
“To better understand costs across entities, healthcare organizations need to bring together data from various software systems – financial and clinical – as well as across hospitals, clinical medical groups and other associated entities,” he said. “This improves the overall validity of costing data and lays the foundation for analyzing opportunities to reduce costs.”
Once the right data sources are connected, organizations need to adjust costing data based on specialties, he advised.
“To do that, they can use technology to accurately allocate shared costs against different provider settings,” he said. “Of course, with so much data available in one place, it could be a challenge to figure out where to focus and identify top opportunities for improvement – this is where comparison data comes into play.”
Using one’s own data to compare performance can identify the low-hanging fruit of improvement opportunities: broadly applying tactics that are proven efficient and effective.
“For instance, are wait times shorter at one outpatient center than another, or how do costs compare across facilities or departments?” Randa pointed out. “Take a deeper look into what the more efficient facility does and then train others to apply those effective processes across your organization.”
Hospitals and health systems also can compare data to determine which businesses and service lines are cost leaders in the market.
“They then can drive patients to these services while simultaneously developing corrective actions to become leaders in the other services,” he said. “Using data to compare information in this way goes beyond traditional benchmarking by empowering organizations to really understand the ‘why’ behind the ‘what’ – or why they are lagging in a certain area and where to focus their energies.”
The comparative analytics capabilities available today are far superior to traditional benchmarking tools used decades ago because today’s technology provides a more comprehensive view of an organization’s competitive position and health, Randa said. By leveraging machine learning and other advanced data tools, organizations have access to the data-based insights they need to focus on how to improve performance and drive growth, he said.
Actionable data analysis
Randa expounds on another best practice suggestion for optimizing healthcare financial information systems.
“Most healthcare organizations are hyper-focused on cost reduction – it’s the top priority at 85% of organizations, according to one report – but the same data-based processes that help organizations reduce costs can also help drive clinical quality improvement and revenue optimization,” he said. “It’s sort of a three-legged stool of performance improvement all built on actionable data analysis.”
Randa offers a real-world example from among his clients that explains what he means.
“At Franciscan Health in Mishawaka, Indiana, the 14-hospital health system can stratify physician-level performance and identify physicians who consistently perform above or below benchmarks,” he explained. “As part of a quality improvement initiative, the health system assembled a team to review high-risk, large-volume diagnoses – such as heart failure – and identify the top physicians based on four metrics: length of stay, readmissions, risk-adjusted mortality rates and adjusted direct costs.”
The team compared performance against Medicare and system-specific benchmarks. Among low performers, the team took a deeper dive, examining readmission rate, mortality rate and direct cost.
“This analysis uncovered dramatic variances in health outcomes and cost, and the data was leveraged to significantly improve quality of care and reduce costs for four of the health system’s costliest conditions in just five years,” he said.
The data that healthcare organizations have collected for decades is immensely powerful to drive improvement beyond just eliminating waste and reducing spending, he advised.
“Healthcare organizations must balance cost-reduction efforts with revenue optimization and clinical quality improvement by using data to guide action that will have the most profound impact,” he stated.
Dynamic, fit-to-purpose segmentations
Wendy Alexander, vice president of data, analytics and client services at VisitPay, a vendor of patient financial engagement technology, advised that healthcare provider organizations must think beyond one-size-fits-all, off-the-shelf scores to dynamic and fit-to-purpose segmentations.
“As use of scores like propensity-to-pay become more commonplace, it’s important to think about whether you are truly personalizing the experience and whether you are using the right tool for the job,” she cautioned. “Off-the-shelf propensity-to-pay scores often are a single input that fails to account for the health system’s unique market, the consumer’s situation and place in the financial journey and revenue cycle, and the need or action being taken.”
"Segmentation starts with good data sets and good data sets start by knowing what questions you want answers to."
Wendy Alexander, VisitPay
A simple score likely doesn’t consider, for example, if a patient’s billing obligations are due to a singular event, like an unplanned emergency room visit, or a recurrent healthcare situation, like pregnancy, she added.
“Nor can it inform servicing staff how patients will respond to communication about medical costs, payment options and discounts, or how that message should best be delivered; for example, through text messages, portals, call centers or paper,” she said.
Further, provider organizations can apply consumer segmentation to the patient financial experience, Alexander advised.
“Health system leaders should reimagine their patient financial experience strategy, starting with a robust scoring and segmentation solution that applies advanced analytics to the health system’s own data, thereby capturing a more precise – and predictive – picture of where patients are in their lives. Segmentation is a classic cross-industry marketing technique that uses data from multiple sources to identify the preferences and behaviors of groups that share similar qualities.”
Segmentations can uncover insights into how different patients interact with the health system at different times within the health system revenue cycle, including pre-service, post-billing and bad debt, she noted. And different segmentations can be created to understand the patient from many dimensions, both behavioral and financial, she added.
“Segmentation starts with good data sets and good data sets start by knowing what questions you want answers to,” she said. “Data elements are like puzzle pieces in a box. Fit enough of the right pieces together, a picture of the patient emerges.”
In a data-rich environment such as healthcare – with years of financial data stored in various EHR platforms – segmentation, she concluded, can help CFOs reimagine their patient financial experience strategy from the ground up, capturing a more precise and predictive picture of where patients are in their lives.
Technology Optimization Best Practices
Experts from across the health IT field will share insights about everything from AI and cloud computing to telemedicine and population health.