Patient adherence is one of the most difficult changes to healthcare providers. This study models human behavior, both intentional and unintentional, relating to error in patient adherence of diabetes treatment. In a recent study, Penn State-CHOT researchers found that patient adherence was primarily driven by skill-based errors and intentional violations which lent itself to several risk mitigation strategies. This research study indicates that error classifications may be helpful in individualizing treatment interventions. By including device design modification, such as: (1) reduce patient inattention, (2) increase motivation to adhere, and (3) reduce pain barriers for glucometer use, this study demonstrated the feasibility of using an error classification approach in the identification and mitigation of the diabetes patients’ non-adherence with self-monitoring of blood glucose (SMBG).
Vaughn-Cooke, M., Nembhard, H. B., Ulbrecht, J., & Gabbay, R. (2015). Informing Patient Self-Management Technology Design Using a Patient Adherence Error Classification. Engineering Management Journal, 27(3), 124-130.
Harriet Nembhard, PhD