Leveraging your EHR to Support Clinical Research

In December of 2016, the Cures Act was signed into law. It provides an additional $5.8 billion in funding slated specifically for clinical research. Its areas of focus are substance abuse, mental health, brain disorders, and pushing for cancer cures like targeted therapies and immunotherapy. One of the biggest tools at the disposal of large academic research centers is the installed Electronic Health Record (EHR). Leveraging this system for clinical research can have a significant impact on both grants received from this fund, but will also enable your organization to use those dollars more efficiently.

The tasks a EHR can do to improve your research related tasks are:

1. Automated Billing to Research Studies
2. Identification of Study Candidates
3. Conducting New Research

Automated Billing to Research Studies

For Healthcare Research studies; treatment that is standard of care should be billed to the payer directly while treatments that are specific to the study should be paid for by the study’s funds directly. This is the most obvious application of the EHR and the first objective large academic medical research centers reach to overcome. Overall costs are lowered because staff is no longer required to manage work queues – these billing professionals can then be tasked to other needs. Additionally, revenue cycle is improved by having the EHR sort billing requirements.

To redirect these charges automatically, the system needs to understand what research studies exist, what kinds of charges should be sorted between payer and study, and which patients are on studies. This usually takes 0.25 to 1 Full Time Employee (FTE) to maintain – and is usually easy enough to manage that research coordinators could be trained to manage it themselves. Depending on your system build and vendor choices, this information may be automatically updated from your CTMS using an interface.

A Clinical Trials Management System (CTMS) can store information necessary to update your EHR. The best one on the market is Forte’s Oncore, and we highly recommend to use Oncore for your CTMS. This system manages research studies, patient management, investigator management, and regulatory compliance. Your health record system is not designed to be used as a CTMS – however it does manage patients well and holds study information for billing purposes. Using standard HL7 interfaces, these systems can talk to each other well enough that very little manual intervention is necessary. Using an interface can reduce duplicate data entry, removes the need to maintain paper copies of studies, improves research coordinator efficiency, and increases the reliability of the underlying study data.

Identification of Study Candidates

Finding candidates for studies can be difficult – often the specific combination of conditions reduces your cohort to a scant few individuals out of the entire population. Using a medical record system to identify new patients that can be candidates for research studies can speed up the process from weeks to hours. This is best demonstrated through an example.

Let’s say your organization wanted to take advantage of the funding available in President Obama’s Cures Act. Specifically, the $1.8 billion in funding slated for cancer research.

In this example, your organization is researching Trametinib and Dabrafenib; recently FDA approved drugs to fight cancers associated with a mutated B-Raf gene that causes uncontrolled cell growth. If your study was to test the efficacy of these medications then the research coordinators need to find all patients who have the V600E or V600K mutations as detected by the Melanoma, BRAF V600E and V600K Mutation Analysis, THxID test. The coordinators of the study could send out information to all physicians to find these patients which would take weeks of searching for patients and would produce a low response rate. Leveraging the EHR instead would produce larger results in a shorter amount of time.

Research coordinators can proactively find patients through the EHR by:

1. Create a report to find all patients all patients who are diagnosed with the specific Melanoma that could be caused by the BRAF V600E/V600K genes.
2. They could send out a bulk communication to their oncologists to run the test.
3. These patients could also be sent a bulk communication through the patient portal to work with the clinic to take the test.
4. Interested patients from this list could have this test ordered by protocol – reducing the impact to the physician workday.
5. Create another report that shows all patients recently testing positive for this test.
6. Reach out to patients identified in this second report to see if they want to join the study.

Extending this logic – an organization would add clinical decision support tools to alert physicians that their patient is a candidate for a study based on the logic above. This alert would inform the physician to steps to sign the patient up for the study, inform the research coordinator that a new patient is a potential candidate, and set up an appointment with the principal investigator if necessary.

Using these mechanisms, trials can be filled out rapidly with a larger patient base to support study conclusions. Building decision support tools requires 1 FTE that works together with principal investigators for analysis, validation, and testing. Using these tools will enable investigators to find more patients while those patients are in the clinic and already working with their physician.

Conducting New Research

Research on anonymized patient populations could occur directly by your research physicians just by using reporting tools built into, or extended from, your EHR. Much of the data is already categorized into reportable numbers. For example, if your firm implements a new fall prevention policy. Did it work? Being able to plot out the number of fall events that happen prior to the policy, and following the policy is an easy reporting task if this information is captured in discrete fields as it is with many medical record systems today. Kaiser Permentente has been tracking information in this fashion for a decade now and has used this information in both published research studies and in their advertising materials.

Let’s say your information is stored primarily in free-text notes instead of in reliable discrete fields. How can this be used to support research? There are tools which can digest notes using various AI, natural language processing, and data mining techniques. Many of these tools, like Nuance’s Natural Language Processing suite, already interface directly into popular EHRs. Properly setup, these tools can work together to read physician notes and categorize data into reliable and actionable clinical study information. Implementing this properly requires an interface expert as well as someone who can transform the newly created discrete information into actionable reports, outreach campaigns, and clinical decision support tools.

Following the Process

Properly leveraging your electronic health record to support clinical research is challenging – and the process is different for each organization and study. While the barriers lay primarily around interfacing your EHR to other tools, building robust reports surrounding clinical data, and creating the direct clinical support tools within your system; knowing which areas to focus on first can be overwhelming.

How can Serra Health help you tackle these operational challenges?

1. Work with executives to identify the enterprise research goals and existing strategy
2. Health System EHR & CTMS Evaluation to identify gaps between current state and best practice
3. Report Out which includes:
   • Identified gaps – with priority & significance
   • Solutions associated with gaps
   • Implementation costs & long-term support costs associated with each solution
   • Expected ROI with each solution – including details behind numbers
   • Project plan proposal
   • Post-Implementation validation strategy (Evidence of achieved goals)
4. Agree on project parameters, goals, and timelines
5. Execute project plan
6. Validate project success using strategy outlined in the report out

Additionally, Serra Health will produce a Case Study documenting the Health System’s path to success for presentation at trade conferences that the health system participates in.

Following this process will ensure a successful project to improve your ability to leverage your electronic health record system for research studies. To start this evaluation process, you can contact me through LinkedIn or my website.