As therapies become increasingly complex and personalized, it is imperative that physicians prescribe the right patient the right treatment at the right time. Trigger programs help with this effort by using real-world data (RWD) and analytics to identify physicians treating patients meeting specific criteria, such as a confirmed lab result in conjunction with specific medication history. An alert is then sent to sales or medical affairs teams, typically through the pharma company’s customer relationship management (CRM) program, with a recommended next-best action.
By implementing a trigger program that informs physician education and outreach efforts, you can:
- Reduce the time to diagnosis and treatment
- Accelerate product adoption
- Drive adherence and therapeutic impact
- Improve sales productivity by focusing time with physicians treating patients meeting the therapy inclusion and exclusion criteria
HealthVerity recently hosted a webinar with our partner Medidata, a leading analytics provider generating evidence and insights for pharmaceutical companies, that discussed the principals to implementing a best-in-class data-driven trigger program. If you missed the webinar, here’s what it covered:
The Right Real-World Data
The more complex or personalized the medication, the more inclusion or exclusion criteria there might be to determine who is an appropriate patient for the therapy. To develop a well-designed trigger program that factors in the varied criterion, RWD is needed from a variety of sources.
For example, medical claims can provide information on the patient’s diagnosis and comorbidities, while lab data informs on the condition severity with test results possibly determining the appropriateness of a given therapy or biomarkers ruling a patient in or out. Pharmacy claims provide insight on prior lines of therapy and may disqualify a patient from taking a complex drug or it may be determined that the individual needs to take another drug first.
Following are key imperatives for ensuring data works for your trigger program:
- Interoperability - All of the data needed to implement a trigger needs to be interoperable, linking at the patient level to provide a comprehensive, HIPAA-compliant view of the patient. If it’s not interoperable you could learn a patient’s lab results, but not know their prescription history or what comorbidities they have or some other insight.
- Coverage - It is also important to make sure the data has adequate coverage to ensure you’re getting the most return on your investment, given the fixed costs of setting up and running these programs. Depending on the disease area, this may require large commercial labs and/or specialized labs (e.g., genomics, pathology).
- Accuracy - If you have false positives, or link patient records for two different individuals, you could have inaccurate correlations that indicate the patient meets your trigger criteria. If you have false negatives that count the same patient as multiple individuals, you will artificially inflate your target population and risk your credibility with the healthcare provider. You will also have a fragmented view of that patient’s journey and valuable insights could be missed.
- Creative Licensing - More data providers are willing to set up a pay-for-performance approach rather than having pharma companies pay up front. Being able to negotiate these types of agreements can help ensure success.
To turn this data into a best-in-class trigger program, you need to apply analytics using machine learning or artificial intelligence. Using these techniques to create micro-segments can provide the most insights.
To develop a micro-segment, you have to first generate a hypothesis of what information the trigger should rely on in order to determine the right patient for treatment. Consider if there are elements of the patient’s medical history that are relevant, such as past diagnoses, if there are necessary lab results, important social determinants of health characteristics, or if it’s more reliant on the payer and formulary access, or the type of treating physician.
Next, ingest relevant data sources needed to inform your hypothesis. The data is then used to perform segmentation and analysis to generate distinct micro-segments for different types of healthcare providers (HCPs), with specific recommendations for each. Once the micro-segments are created, you can begin receiving results, with alerts being sent to the field staff when a potential patient is identified.
Each micro-segment should address the following questions:
- Healthcare Provider - Do they have a high or low patient count, a high or low product market share, how frequently do they perform drug titration
- Patients - Does this provider’s patient population have high or low comorbidities, how severe is the condition of interest
- Payers - Do patients have advantageous access to insurance, are there high or low rejection rates for medications
- Institution - What type of healthcare organization is the physician a part of, large or small, group practice, academia, hospital
- Sales & Marketing Channels - What is the physician’s preferred channel, limited or strong digital engagement
The information for each of these areas will inform what actions are recommended.
Following are key imperatives for ensuring the analytics work for your trigger program:
- Micro-segments - Start with micro-segments instead of using individualized HCP predictions. With an individualized HCP approach, the data can end up being thin and the resulting next-best action doesn’t make sense. Whereas with a micro-segment, the data is aggregated so you get the information you need to appropriately inform recommendations.
- Feedback - It is important to set up a feedback loop so that field teams can let you know if the trigger is working and the alerts are correct. This allows you to make modifications to the algorithm if need be.
- Ease of Access - The generated predictions and recommendations from the trigger program need to be accessible to the field team and presented in a way that is easy for them to understand, such as a dashboard with surface results or routing it through the CRM.
- Field Team Alignment - Make sure you don’t overload your field team with information. Align on a practical cadence for receiving key triggers and don’t provide them with more data than they need.
- Internal Ownership - While providers like Medidata and HealthVerity can set up and implement the trigger program, it should ultimately be run and maintained by an internal team to be efficient.
By enlisting partners like Medidata and HealthVerity, you can successfully implement these key imperatives and unlock optimal trigger programs. Click here to watch a recording of the webinar, Data-Driven Trigger Programs that Accelerate Product Launch and Uptake, or click here to see a demo on how you can curate fit-for-purpose data for your trigger program.