REAL-WORLD INSIGHTS INTO OBESITY PATHWAYS, PRESCRIBING, PATIENT COMPLEXITY, AND CARE GAPS THROUGH PRIMARY CARE DATABASES

Author(s)

Kim Summers, BSc, MSc, PhD1, Elango Vijaykuma, MBBS2, Orlando Agrippa, BSc, MBA3;
1Sanius Health, Senior Research Consultant, London, United Kingdom, 2Modality Partnership, Surrey, United Kingdom, 3Sanius Health, London, United Kingdom
OBJECTIVES: While obesity is largely managed in primary care (PC), evidence surrounding coding and uptake of core therapies in routine practice remains limited. This work utilised PC records to characterise obesity identification, coding completeness, body mass index (BMI), treatment patterns, and service use.
METHODS: Retrospective analysis using routinely collected UK PC data (2014-2024) was conducted in adults (≥18years) with a recorded BMI≥30 and/or obesity-linked diagnosis code, indexed at first evidence. Post-index outcomes included coding overlap, obesity-linked therapy exposure and persistence (≥180-day gaps; >1 regimen), longitudinal BMI, comorbidities, blood markers, and completed appointments.
RESULTS: 71,686 adults (median age: 57) met the obesity definition, 70,947 (99%) identified via BMI and 739 (1%) coding alone. Among BMI-defined patients, only 5,010 (7%) also had an obesity-linked code.
Post-index, 1,579 (2%) had any obesity-linked therapy record. Median time-to-first treatment was 928 days, and 30% initiated ≥12 months. First recorded regimens were semaglutide (n=732), orlistat (n=627), liraglutide (n=198), and tirzepatide (n=22). ≥180-day gaps occurred in 39% and switching (>1 regimen) in 5%.
At ≤1-year post-index, median BMI was higher in coded than uncoded patients, both obesity therapy-treated (39 vs. 35) and untreated (35 vs. 31). Untreated patients showed modest increases from 0-1y to 5+years post-index, whereas treated-patient BMIs remained relatively stable.
Median finished appointments were 4 per patient-year, and higher in treated than untreated patients (9 vs. 4). 41% had ≥1 mapped comorbidities, most commonly hypertension (16%), osteoarthritis (9%), and depression (8%). Median HbA1c was higher in treated vs. untreated patients (69 vs. 53mmol/mol).
CONCLUSIONS: Obesity was found to be commonly identified through BMI, in contrast to specific coding in PC. Obesity-linked therapy records appeared infrequent, delayed, and concentrated in higher-severity patients. These data highlight the potential for longitudinal and real-world monitoring of prescribing, utilisation, and outcomes aligned to key cardiometabolic endpoints in therapy evaluation and future care pathway optimisation.

Conference/Value in Health Info

2026-05, ISPOR 2026, Philadelphia, PA, USA

Value in Health, Volume 29, Issue S6

Code

RWD113

Topic

Real World Data & Information Systems

Topic Subcategory

Health & Insurance Records Systems

Disease

SDC: Diabetes/Endocrine/Metabolic Disorders (including obesity)

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