Revenue Optimization Clinical Trial Challenges

Headshot of Kelly Willenberg, DBA, RN, CHRC, CHC, CCRP

Kelly Willenberg, DBA, RN, CHRC, CHC, CCRP

Kelly Willenberg & Associates

Abstract: Data is a powerful tool that can be leveraged to drive key decisions for a health system. This article describes various data elements, metrics, and key performance indicators that aid a health system with making key decisions about its research portfolio. Using denials management is one example of leveraging the data to build a robust Coverage Analysis, increasing revenue for the health system. This article also provides information that can be used to develop staffing models and productivity models.

Developing a Risk-based Revenue Compliance Plan Based on Data Elements
There are many finance-based data elements that must be understood in order to conduct risk analysis, including:

  • Vetting and feasibility analysis
  • Coverage analysis and billing plan
  • Budgeting, pricing, and contracting
  • IRB approval
  • Enrollment and informed consent
  • Identification, registration, scheduling, and tracking
  • Authorization and documentation for medical necessity
  • Charge capture
  • Charge segregation
  • Claims submission.

The elements above help a health system clinical research site to better understand their portfolio. Whether trying to decide under a feasibility review or effectively evaluating whether a site has the sufficient patient population to participate in a study, a site needs to analyze whether they have patients to accrue. Once a study is open with no patients, clinical research work begins. Unpaid work on a study includes dealing with monitors and answering emails until patients are accrued after you receive the nonrefundable startup fee.

The coverage analysis is the driving force for revenue optimization in clinical trials. Clinical research sites that are conducting clinical trials without a coverage analysis are not conducting studies in the right way. The coverage analysis must be developed at the beginning, before the budget, contract, and informed consent form are developed, and they should be used to negotiate a budget.

When conducting audits, we validate that the coverage analysis, budget, contract, and informed consent form are consistent. If they are not consistent, the clinical research site may end up in a payback situation. Usually, sites promise things to patients in the informed consent document that they are not doing, and they collect money for items and services that were part of a claim. Sometimes, the sites do not collect money for something that is billable. Many types of problems stem from inconsistencies between the coverage analysis, budget, contract, and informed consent document.

Clinical research sites need a method for appropriate budgeting and pricing, including research discount pricing. Sites should never offer a pharmaceutical sponsor, which is a for-profit entity, prices that are less than the Medicare rate for the region. These prices are available on Medicare’s website. Some sites use the Medicare rate times two or 2.5 as their research rate for industry-sponsored studies.

Considerations under IRB approval are the timing of IRB approval and the need to put patients first when preparing the cost language. The primary concern is to do right by the patients. A patient who has consented to participate in a clinical trial has put his/her trust in the site. Telling the patient how much participating in the study will cost is part of the informed consent process and should not be taken lightly.

Enrollment considerations include when each patient consented and started the study as well as the end of study. Sites must account for the timing and screen failures. Kelly Willenberg & Associates often sees inaccurately-tracked screen failures where the sponsor pays for screening items and services before the patient has been consented  as well as screen failure patients who receive items and services paid for by the sponsor that are only for study participants after screening. Auditors will review when consent was done and when it should have been done in relation to proper submission of claims.

A valid review of revenue requires identifying every subject at every visit in every study. This includes knowing when research participants come to the health system for study items and services and when the health system provides research-related services for physicians outside of the organization, such as an MRI. In order to submit claims correctly, billing staff must know when services are related to research and who the patients are.

Authorization and documentation for medical necessity is crucial. Auditors often see problems with the revenue cycle due to lack of or poor authorization and documentation for medical necessity. In a claim review, every line item for every study that is open should be evaluated for payment or submission for payment to an insurance company. When there are outstanding balances, clinical research sites need to know their payors and how to handle their variances. Sometimes, problems occur because sites fail to get a pre-authorization, and ultimately, the payor will not pay the bill. Clinical research professionals must review each patient’s insurance and obtain any pre-authorizations required for certain tests and procedures.

Another issue is the improper designation of items and services as standard of care. All items and services designated as standard of care must be validated as billable under the National Coverage Decision (NCD) and the appropriate Local Coverage Decision (LCDs). This should be done as part of the coverage analysis.

Considerations under charge capture, charge segregation, and claims submission including knowing who is responsible for tasks such as adding codes and modifiers, releasing claims, and sending bills for drug trials to regular Medicare need to be decided. Claims must contain the right information and be submitted correctly. All of these things can pose risks to the revenue cycle if not done correctly.  

Common Areas of Identified Risk

Table 1 highlights common areas of identified risk, starting with not developing a coverage analysis and a proper budget. We often audit where the clinical research site does not have a properly performed coverage analysis. Going back and retrospectively building a coverage analysis is a huge job, especially if patients are already enrolled in the study and have been treated and the budget and contract have been finalized.

Not identifying, registering, scheduling, or tracking patients using IT tools is another common area of risk to the revenue cycle. Clinical research sites need a system to register study patients and flag or highlight them in the electronic medical records (EMRs). This is necessary in order to track patients and know when they are coming in for a research visit or a clinical visit.

Some studies may find themselves in the hole or find that have excess funds not expensed. A clinical research site may owe money to ancillary departments such as radiology but does not have the money in the study accounts to pay them. Or, the site may have a great deal of money left over and not know why. When this happens, the site should evaluate the funds received and how they were allocated.

Some clients of ours still use paper or a spreadsheet for tracking. There are many clinical trial management systems (CTMSs) available, and these systems can be used to easily track patients and accounting. Entering the data in a timely manner is crucial for billing compliance, accounts receivable, and auditing on the back end after patients receive treatment.

To audit a study, clinical research professionals can pull the last three closed studies and see how many times in the past six months study participants had a Z00.6 code (the secondary diagnosis for research) put on their claim. This can be enlightening as to whether research coding is being utilized on claims. Clinical research sites that conduct many oncology studies should have many Z00.6 codes because these patients have cycles of treatment, therefore necessitating the use of the coding. The accounting department can provide information about codes and possibly help to pull claims and assess research coding usage.

Some sites find that segregating charges can be problematic. In order to segregate charges appropriately, it is necessary to know how to do this and to have access to the coverage analysis. Study coordinators are often contacted with questions about whether services such as an EKG or echocardiogram are study related. They either answer based on what they remember or guess without the information in the coverage analysis. When audits uncover inappropriate claims, the cause can be a study coordinator who did not know or was never told that the sponsor was or was not paying for an item or service. They may not understand the use of a coverage analysis. To document services correctly and ensure proper orders, the study coordinator needs the information in the coverage analysis from the beginning with the intent to bill for all patients.

Enrollment and informed consent can be another common area of risk. It is necessary to know the date of consent, the date of screening, and the date that the patient went on the study. If a patient was consented but was a screen failure, this information must be sent to the people who are handling claims so they understand that the baseline visit was study related but the patient’s other visits should not be on the study account or include the clinical trial codes and modifiers. Working with physician practices that the clinical research site does not own is a challenge in terms of enrollment and informed consent information flow. Coordination and communication of information such as consent dates and screen failures will lead to better success for claims processing.

Medicare Advantage plans do not cover routine costs in a qualifying drug clinical trial. This is another reason why it is important to know the type of insurance that the patient has and to communicate that information. When a patient with Medicare Advantage goes on a study, the study coordinator must know what the schedule of events contains so that the claims for items and services can be sent to regular Medicare when appropriate.

Also, not all parts of a claim go to Medicare. For example, if a patient is on a study involving chemotherapy but also receives a flu shot, the flu shot is not part of the study, therefore, when there is a Medicare Advantage plan involved, there may be three different accounts used for that visit.  Good communication is necessary in order for the necessary information to flow between everyone involved in clinical trial billing.

Medical necessity documentation is necessary because the physician needs to know when an item or service is a routine cost in a qualifying clinical trial and that this has been vetted through the guidelines and can be billed as conventional care per the coverage analysis. The physician must document medical necessity so that the coders can process a claim appropriately.

For example, if a patient comes into the emergency department with a stroke, he/she must be treated quickly. After the emergency treatment, if the physician wants to put the patient on an investigational drug, the physician cannot go back and document that the patient was admitted for a stroke study. This happens frequently. There are very few studies where a patient is admitted in order to participate in a study and all items and services are related to the research, especially in an emergency situation.

In order to do appropriate charge capture and claims submissions, is it necessary to know what happened on each day and whether an item or service is research-related and on the study calendar. The people who are doing this work must have the necessary information and access to the coverage analysis. If a patient who is on a study is admitted to the hospital for a volleyball injury, for example, this should not be billed to research.

Key Performance Indicators for Higher Productivity

Higher productivity will enable clinical research sites to ensure that they are generating the money to cover their costs and submitting claims appropriately. Table 2 outlines indicators for higher productivity. Following the NCD 310.1 and the relevant LCD in a complete coverage analysis or the investigational device guidelines is one indicator of higher productivity. Frequency of tests and procedures are always a question. Some guidelines do not specify, for example, how often a service is recommended. Some guidelines are not as clear for certain populations, such as pediatrics. 

It is necessary to understand what the physician would do if the patient were not part of a study. A service must be provided based on guidelines: the NCD and the LCD. If the information is not in a guideline, the study coordinator must ask the clinical investigator for a relevant journal article or another way to justify the claim. The physician cannot simply say that he/she does this routinely as standard of care, and the coverage analysis also cannot be based on their opinion.  

The NCD and the LCDs are full of items and services that are not billable depending on the Medicare Contractor. For example, an EKG performed when there are no signs and symptoms is not billable, especially considering that sometimes EKGs are screening. Protime and Prothrombin time are limited and billable for certain reasons. Items that are not billable within a certain ICD-10 code will not be submitted on a claim or will be denied. This can lead to a lower financial impact if something should have been paid by the sponsor. It is also necessary to know how and when to stop claims from being submitted. Ancillary departments that provide study services, such as radiology, must be given information about what the sponsor does and does not pay for so that they can bill correctly.

Review of denials is another indicator for productivity. Many denials fall into a black hole, so reviewing all claim denials may increase accounts receivable. Auditors often find that appropriate claims are denied due to a lack of a code or modifier. These claims should be evaluated and re-submitted. If the payer will not pay, the patient is responsible for the bill unless he/she is indigent. It would not be appropriate to allow the sponsor to pay for a particular patient as a result of a denial.

It is important to understand the indicators that can lead to lower revenue such as inadequate financial accounting. By not tracking the funds received, a site may see lower revenue. Other indicators of lower revenue are not identifying research subjects and non-concordance of the protocol, coverage analysis, budget, contract, and informed consent document. A lack of charge capture/billing for research-related services and routine costs, study drugs, and devices can be another indicator of lower revenue and should be addressed.

Not monitoring clinical trial billing inquiries is another indicator of lower revenue. Medicare can and will conduct reviews of clinical trial billing by data mining to identify problems. Medicare has the ability to compare all of the clinical research sites in a study against the other sites participating. Health systems should never bill Medicare for an item or service that other patients receive for free, and Medicare can review items within particular studies retrospectively.

Having an adequate system process for tracking revenue can mean money. Clinical research professionals must have a broad understanding of the health system’s fragmented, disconnected processes and systems, as well as how they interconnect. CTMSs, EMRs, and e-regulatory systems can help with this, and they are deployed in many institutions without the study team knowing which does what within the revenue cycle for research.

An appreciation of the many events that take place before and after billing is necessary. There are three stages: before the study, before the patient goes on the study, and once the patient has study-related procedures per the study calendar. The coverage analysis and all of the other documents should be developed before the patient goes on the study. Everything must be synced-up and documented consistently. A study account should be set up for every study that has funding flowing in and out of the institution. Once a patient enrolls onto a study, clinical research professionals must know what happens with every patient on every visit. This is necessary in order to correctly debit the study account and bill third parties (insurance, patient, etc.).

The four main reasons for incorrect billing and problems with financial compliance and business processes are technological error, human error, lack of training, and lack of awareness. Technological errors can be as simple as not removing research-related items and services from a claim. Human error is sometimes due to lack of training or lack of knowledge about the clinical trial billing process. A high percentage of errors during audits is the result of a lack of training.

Revenue Compliance Review and Using Analytics

Data for revenue compliance review can be used for process improvement if a site tracks it. Data can be extracted from:

  • CTMSs
  • EMRs
  • Hospital billing systems
  • Physician billing systems
  • Denials and appeals

Before reviewing data and using analytics, it is necessary to know who at the facility is responsible for operational billing (registration and billing) and financial management (budgeting, pricing, contracting, and accounts receivable). Then, clinical research professionals can work with other staff to ensure that everyone is informed about what is happening with study patients at each time point on each study.

Audits of clinical trials can cover study-level review, patient-level review, subject identification within various systems, or denials (Table 3). Study-level review can be a sample of studies, items and services that are underbilled or not billed, what happens to claims for subjects that are not flagged, and/or a concordance review of the coverage analysis and other documents.

Data analytics for research billing can include:

  • Sample of studies and subjects to review
  • Determination as to whether payers were charged appropriately
  • Identifying denials on clinical trial claims
  • Identify underbilled or not billed charges
  • Reviewing subject “flagging” or alerts in CTMS or EMR
  • Reviewing claims against the coverage analysis and the study calendar

Document Concordance

Document concordance is ensuring that all of the documents say the same thing. This is an important and complex requirement in research billing. Document concordance refers to the consistency and accuracy of all study-initiation and -continuation documents relevant to billing for protocol-specified clinical services. Without document concordance, accurate billing and revenue optimization is at risk.

The coverage analysis should be developed before the budget and contract are developed. It must drive the development of the other documents.

To do a document concordance review, clinical research professionals can choose an open study and compare the key documents for consistency

  • Contract
  • Budget, internal and external
  • Informed consent form
  • Coverage analysis
  • Protocol.

Table 4 highlights common compliance analytics techniques, including anomaly detection to recognize potential compliance risks. Anomalies include lack of code Z00.6, condition code .30, or Medicare Advantage plan claims being sent to regular Medicare. Clinical research professionals should set up dashboards to perform internal control checks.

Knowledge of the various compliance requirements is the key to success in revenue optimization. Clinical research professionals should define the clinical research site’s risk tolerance. They must know the type of studies that the site conducts and the areas of risk. If the clinical research site does Phase I clinical trials or investigator-initiated clinical trials, the risk is higher and billing compliance issues are broader.

Compliance knowledge can reduce the odds that warning signs are overlooked. Trends can be discovered by inspecting and modeling clinical trial data.

Table 5 provides examples of using compliance knowledge in a CTMS and to integrate EMR data into a CTMS. Clinical research professionals should review revenue and study visits in order to determine whether things match up. They should benchmark studies against each other. For example, a simple study that was conducted properly for revenue optimization can be benchmarked against a complicated study with four arms. Variances in the data will be seen. EMR integration with the CTMS can maximize the revenue.

Successful Compliance Data Analytics

Clinical trial billing compliance is necessary. Armed with the necessary compliance knowledge, a healthcare system can apply analytics to its data. Analytics can use multiple sets of data to identify patterns or anomalies in billing data that do not adhere to defined requirements. There are many ways to collect data and conduct risk reviews based on the type of studies being conducted at the clinical research site. The sources of critical data will be determined by each clinical investigator, department, or institution. Effective risk compliance analytics require reviewing a substantial amount of data.

Analytics should be incorporated throughout the clinical trial revenue continuum, which starts with the coverage analysis and ends with study close-out. Institutional expertise should be leveraged. This can significantly affect the development of an institutional data analytics program and improve performance and innovation. Clinical research professionals should find other people in the institution who have the necessary expertise or, if necessary, outsource it. Developing a data analytics program is not easy, but it can be beneficial financially!


TABLE 1

Common Areas of Identified Risk

  • Not doing a coverage analysis and proper budget
  • Not identifying, registering, scheduling, or tracking patients using IT tools
  • Not segregating charges appropriately
  • Inadequate budgeting, pricing, and contracting
  • IRB consent language not stating the intent for financial liability to the patient
  • Poor or a lack of medical necessity documentation
  • Incorrect charge capture or inaccurate claims submission

TABLE 2

Indicators for Higher Productivity

  • Following the NCD 310.1 in a complete coverage analysis
  • Following the investigational device guidelines
  • Not billing Medicare Advantage for drug trials during claims processing
  • Review of a high denial rate 

TABLE 3

Data to Audit in a Clinical Trial

  • Study-level review:
    • Coverage analysis and document concordance
  • Patient-level review:
    • Reconciliation of patient billing/accounting
    • Validation of coding
  • Subject identification within various systems:
    • Timely data entry prior to claims submission
  • Denials:
    • Awareness of denials and timely filing

TABLE 4

Compliance Analytics Techniques

  • Rules-based monitoring to identify known billing and compliance risks
  • Anomaly detection to recognize potential compliance risks
  • Network analysis to identify potentially worrisome activity
  • Visual analytics/dashboards to summarize actionable results for stakeholders

TABLE 5

Examples of Using Compliance Knowledge

  • CTMS:
    • Document the designation of charges as research-related or paid by research
    • Recording the rationale behind the determinations on a coverage analysis
    • Use as a repository of information exchanged between research groups and the hospital and professional revenue cycle teams
  • EMR integration with CTMS:
    • Communicates if a subject is a research participant
    • Translates routing of charges and drives proper coding
    • Identifies serious adverse events and adverse events when patients are identified correctly and monitored

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