# Content Validation of an Electronic Health Record–Based Diabetes Self-Management Support Tool for Older Adults With Type 2 Diabetes: Qualitative Study

**Authors:** Ploypun Narindrarangkura, Siroj Dejhansathit, Uzma Khan, Margaret Day, Suzanne A Boren, Eduardo J Simoes, Min Soon Kim

PMC · DOI: 10.2196/83448 · JMIR Diabetes · 2026-02-06

## TL;DR

Researchers developed and validated a tool to help older adults with diabetes understand and manage their care through clearer electronic health record notes.

## Contribution

The study validates a patient-centered diabetes self-management tool integrated into EHRs, aligned with established self-care frameworks.

## Key findings

- Patients found the SEE-Diabetes statements clear and relevant, using plain language to support self-care understanding.
- Clinicians viewed the content as concise, clinically appropriate, and aligned with patient self-management goals.
- Both patients and clinicians identified potential for the tool to improve patient engagement and communication, with suggestions for refining medication-related content.

## Abstract

Older adults with diabetes frequently access their electronic health record (EHR) notes but often report difficulty understanding medical jargon and nonspecific self-care instructions. To address this communication gap, we developed Support-Engage-Empower-Diabetes (SEE-Diabetes), a patient-centered, EHR-integrated diabetes self-management support tool designed to embed tailored educational statements within the assessment and plan section of clinical notes.

This study aimed to validate the clarity, relevance, and alignment of SEE-Diabetes content with the Association of Diabetes Care & Education Specialists 7 Self-Care Behaviors framework from the perspectives of older adults and clinicians.

An interdisciplinary team conducted expert reviews and qualitative interviews with 11 older adults with diabetes and 8 clinicians practicing in primary care (family medicine) and specialty diabetes care settings at a Midwestern academic health center. Patients evaluated the readability and relevance of the content, while clinicians assessed clarity, sufficiency, and potential clinical utility. Interview data were analyzed using inductive thematic analysis, and descriptive statistics were used to summarize participant characteristics.

Patients (mean age 72, SD 4.9 y; mean diabetes duration 26, SD 15 y) reported that the SEE-Diabetes statements were clear, relevant, and written in plain language that supported understanding of self-care recommendations. Clinicians (mean 13, SD 9.5 y of diabetes care experience) viewed the content as concise, clinically appropriate, and well aligned with patient self-management goals and the Association of Diabetes Care & Education Specialists 7 Self-Care Behaviors framework. Both groups identified the tool’s potential to enhance patient engagement and patient-clinician communication, while noting opportunities to improve the specificity of language, particularly within medication-related content.

SEE-Diabetes demonstrated content validity as a practical, patient-centered digital health tool for supporting diabetes self-management communication within EHR clinical notes. The findings support its use as a complementary approach to reinforce self-care communication in routine clinical practice and highlight areas for refinement to enhance personalization.

## Linked entities

- **Diseases:** diabetes (MONDO:0005015), Type 2 Diabetes (MONDO:0005148)

## Full-text entities

- **Genes:** SIK1 (salt inducible kinase 1) [NCBI Gene 150094] {aka DEE30, MSK, SIK, SIK-1, SIK1B, SNF1LK}
- **Diseases:** hypertension (MESH:D006973), mental illness (MESH:D001523), cataract (MESH:D002386), hypoglycemic (MESH:C000721848), retinopathy (MESH:D058437), hyperglycemia (MESH:D006943), vomiting (MESH:D014839), hyperlipidemia (MESH:D006949), stroke (MESH:D020521), Obesity (MESH:D009765), Diabetes and Digestive and Kidney Disorders (MESH:D003928), hypoglycemia (MESH:D007003), osteoporosis (MESH:D010024), neuropathy (MESH:D009422), SD (MESH:D012735), PN (MESH:C565820), Type 2 Diabetes (MESH:D003924), foot ulcers (MESH:D016523), fatigue (MESH:D005221), chest pain (MESH:D002637), weight loss (MESH:D015431), abdominal pain (MESH:D015746), cognitive decline (MESH:D003072), prediabetes (MESH:D011236), cough (MESH:D003371), COVID infection (MESH:D000086382), numbness (MESH:D006987), Diabetes (MESH:D003920), nausea (MESH:D009325), chronic disease (MESH:D002908), diarrhea (MESH:D003967), weight gain (MESH:D015430), tingling (MESH:D010292), palpitations (MESH:D006331), kidney damage (MESH:D007674), arthritis (MESH:D001168), fever (MESH:D005334), heart attack (MESH:D009203), UCD (MESH:D008224)
- **Chemicals:** sugar (MESH:D000073893), pioglitazone (MESH:D000077205), microalbumin (-), Metformin (MESH:D008687), amlodipine (MESH:D017311), glipizide (MESH:D005913), ASA (MESH:D001241), losartan (MESH:D019808), glimepiride (MESH:C057619), pravastatin (MESH:D017035), alcohol (MESH:D000438), triamterene (MESH:D014223), lead (MESH:D007854), insulin (MESH:D007328), cholesterol (MESH:D002784), HCTZ (MESH:D006852), Blood glucose (MESH:D001786)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

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## References

25 references — full list in the complete paper: https://tomesphere.com/paper/PMC12880848/full.md

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Source: https://tomesphere.com/paper/PMC12880848