January 30 2019 | 0 Comments | 116 reads Average Rating: 3.5
5 Ways a Deep Data Dive Can Lead to Improved Medication Adherence
“Following doctor’s orders.” It’s a phrase that intrinsically implies compliance. However, patients often dismiss doctor’s orders regarding their medication therapy regimens.
And, this non-compliance is resulting in a variety of ill effects. In fact, researchers have identified non-adherence as a major source of waste in U.S. healthcare, totaling approximately $290 billion, which equates to about 13% of total healthcare spending.1 Overall, non-adherence puts a tremendous burden on the healthcare ecosystem as it results in poor clinical outcomes, declining quality of life, skyrocketing costs, and increasing insurance premiums. More specifically, non-adherence can have a negative impact on pharma companies. A report from HealthPrize Technologies and Capgemini Consulting, for instance, shows that pharma loses an estimated $546 per year in global revenues due to patient non-adherence of medications to chronic illnesses.2
The big question then becomes: How do we, as an industry, ensure that patients will actually follow doctor’s orders and take their medications as directed? The follow-up question then becomes: Are healthcare providers today truly armed with the information that will enable them to get their patients to adhere to their medication regimens?
Following in the footsteps of other industries such as banking and retail, which use data to develop a deep understanding of customers, could help address these issues. These industries assess and analyze a tremendous amount of information at the consumer level – and then use it to place consumers into specific population segments, which shed light on their buying behaviors and attitudes.
Pharma could do the same by analyzing multiple layers of data to assess the risk of patients not adhering to their medication regimens. Information on a patient’s behaviors and attitudes, demographics and attribution, clinical factors, cost and quality, and utilization can all add up to an assessment of a patient’s risk or an understanding of where the patient is headed in the next 12 months. The data could also provide insight into how impactable a patient is – or how likely they are to respond to various interventions.
More specifically, an analysis of such data can make it possible for pharma companies to:
1) Identify patient segments and their personas.
2) Understand how different factors might affect their adherence levels – today and tomorrow.
3) Determine which patient segments can be impacted the most and where.
4) Inform healthcare providers of factors affecting patient compliance in their communities.
5) Develop programs and educate patients.
Indeed, when pharma companies use data to gain a better understanding of patients, they can become a more valuable resource for healthcare providers. This could prove especially helpful to pharma reps – as one of the main reasons that providers often do not want to meet with them is because they feel that the reps are not bringing any new information into the meetings. By sharing data-driven insights with providers, however, pharma reps can help clinicians better communicate with their patients. And, when providers really understand their individual patients – and have some insight into “what keeps them up at night,” – they can develop the medication education and communication programs that truly resonate and promote adherence.
Looking to learn more about medication adherence? Check out our recorded webinar entitled, “Making Serious Gains In Adherence.”
1. Philipson, T. Non-Adherence in Health Care: Are Patients or Policy Maker Ill Informed. Forbes, May 8, 2015. https://www.forbes.com/sites/tomasphilipson/2015/05/08/non-adherence-in-health-care-are-patients-or-policy-makers-ill-informed/#2771e9d04c4a
2. HealthPrize and Capgemini Consulting. Estimated Annual Pharmaceutical Revenue Loss Due to Medication Non-Adherence. https://www.capgemini.com/wp-content/uploads/2017/07/Estimated_Annual_Pharmaceutical_Revenue_Loss_Due_to_Medication_Non-Adherence.pdfM