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Observational Study
. 2024 Sep;15(9):1306-1316.
doi: 10.1111/jdi.14228. Epub 2024 Jun 5.

Patient-reported outcomes and treatment adherence in type 2 diabetes using natural language processing: Wave 8 of the Observational International Diabetes Management Practices Study

Affiliations
Observational Study

Patient-reported outcomes and treatment adherence in type 2 diabetes using natural language processing: Wave 8 of the Observational International Diabetes Management Practices Study

Juliana Cn Chan et al. J Diabetes Investig. 2024 Sep.

Abstract

Aims/introduction: We analyzed patient-reported outcomes of people with type 2 diabetes to better understand perceptions and experiences contributing to treatment adherence.

Materials and methods: In the ongoing International Diabetes Management Practices Study, we collected patient-reported outcomes data from structured questionnaires (chronic treatment acceptance questionnaire and Diabetes Self-Management Questionnaire) and free-text answers to open-ended questions to assess perceptions of treatment value and side-effects, as well as barriers to, and enablers for, adherence and self-management. Free-text answers were analyzed by natural language processing.

Results: In 2018-2020, we recruited 2,475 patients with type 2 diabetes (43.3% insulin-treated, glycated hemoglobin (HbA1c) 8.0 ± 1.8%; 30.9% with HbA1c <7%) from 13 countries across Africa, the Middle East, Europe, Latin America and Asia. Mean ± standard deviation scores of chronic treatment acceptance questionnaire (acceptance of medication, rated out of 100) and Diabetes Self-Management Questionnaire (self-management, rated out of 10) were 87.8 ± 24.5 and 3.3 ± 0.9, respectively. Based on free-text analysis and coded responses, one in three patients reported treatment non-adherence. Overall, although most patients accepted treatment values and side-effects, self-management was suboptimal. Treatment duration, regimen complexity and disruption of daily routines were major barriers to adherence, whereas habit formation was a key enabler. Treatment-adherent patients were older (60 ± 11.6 vs 55 ± 11.7 years, P < 0.001), and more likely to have longer disease duration (12 ± 8.6 vs 10 ± 7.7 years, P < 0.001), exposure to diabetes education (73.1% vs 67.8%, P < 0.05), lower HbA1c (7.9 ± 1.8% vs 8.3 ± 1.9%, P < 0.001) and attainment of HbA1c <7% (29.7% vs 23.3%, P < 0.01).

Conclusions: Patient perceptions/experiences influence treatment adherence and self-management. Patient-centered education and support programs that consider patient-reported outcomes aimed at promoting empowerment and developing new routines might improve glycemic control.

Keywords: Clincal; Glycemic control; Patient‐reported outcomes; Treatment - Education; Type 2 diabetes.

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Conflict of interest statement

JCNC, JJG, HI, AR, JCM, MS and PA are all members of the IDMPS steering committee, and have received honoraria for travel grants and speakers' fees from Sanofi. JCNC has also received research grants and/or honoraria for consultancy or giving lectures from Applied Therapeutics, AstraZeneca, Bayer, Boehringer Ingelheim, Eli Lilly, Merck Serono, Merck Sharp & Dohme, Novartis, Pfizer, Servier, Sanofi and Viatris. PA has served as a consultant for and received speaker fees from AstraZeneca, Boehringer Ingelheim, Eli Lilly, Merck Sharp & Dohme, Novo Nordisk and Sanofi; and has served on an advisory board for Merck Sharp & Dohme and Sanofi. MR and LD are employees of Quinten, contracted by Sanofi. LMM is an employee of IVIDATA Life Sciences, contracted by Sanofi. JMC is an employee of Sanofi and may hold Sanofi stocks/shares.

Approval of the research protocol: The protocol for this research project has been approved by a suitably constituted Ethics Committee of the institution, and it conforms to the provisions of the Declaration of Helsinki.

Informed consent: Informed consent was obtained from each study participant.

Registry and the registration no. of the study/trial: N/A.

Animal studies: N/A.

Figures

Figure 1
Figure 1
Medication in general: three questions on medication advantages/disadvantages, acceptance and long‐term worth of taking the medication. Effectiveness: three questions on perceived medication effectiveness. Side‐effects: five questions on occurrence of side‐effects, their severity and impact on medication adherence. Numerous medications: one question on number of medications. Regimen constraints: five questions on whether patients consider collecting, taking and remembering to take medication to be constraining. Length of treatment: three questions on past and future length of treatment and medication routine. Medication inconvenience: five questions on the perceived inconvenience of medication preparation, administration, form, storage and discretion. Glucose management: five questions on blood glucose management, medication and dietary control. Dietary control: four questions on food choices, eating habits, and doctor recommendations. Physical activity: three questions on physical activity regularity and occurrence. Healthcare use: three questions on medical appointment related to frequency and attendance.
Figure 2
Figure 2
Patient adherence: natural language processing. (a) Reasons for non‐adherence. (b) Reasons for adherence. Natural language processing and clustering methods were used to analyze responses to three questions: Q1: If you tend to forget or skip your diabetes medication, could you explain the reasons why? Q2: If you do not always take your diabetes medication as prescribed, could you explain the reasons why? Q3: If you always take your medication as prescribed, could you explain why it is important for you to always take your diabetes medication and how you make sure not to forget it? Patients could report more than one reason per question. Q1 and Q2 responses were merged as reasons for ‘omission’. Respondents with an eligible answer to Q1 or Q2: n = 661; responders with an eligible answer to Q3: n = 865.

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