Highlights
- •One-year postoperative patient & clinic reported weights show high agreement.
- •Patient and clinic reported diabetes & hypertension status show high agreement.
- •Patient report options can increase postoperative long-term follow-up rates.
- •Response rates differ by demographics & response method, limiting generalizability
Abstract
Background
Development of patient-reported outcomes (PROs) to include traditionally clinic-reported
data has the potential to decrease the data-collection burden for patients and clinicians
and increase follow-up rates. However, replacing clinic report by patient report requires
that the data reasonably agree.
Objective
To assess agreement between PROs and clinical registry data at 1 year after bariatric
surgery.
Setting
Not-for-profit organization, bariatric surgery data registry, PROs platform.
Methods
Patient- and clinic-reported 1-year postoperative weight and co-morbidities were compared
for matched PROs and registry records. The co-morbidities evaluated were diabetes,
sleep apnea, hypertension, gastroesophageal reflux disease, and hyperlipidemia. Weight
difference in pounds and nominal groupings (binary, 4-level) for co-morbidities were
assessed for agreement between data sources using descriptive statistics, Bland–Altman
plots, multiple regression, and kappa coefficients. Sensitivity analyses and follow-up
by response method were examined.
Results
Among 1130 patients with both 1-year PROs and registry weights, 95% of patient-reported
weights were within 13 lb of the registry-recorded weight, and patients underreported
their weight by ∼2 lb, on average. Percent agreement and kappa coefficients were highest
for diabetes (n = 999; binary: 94%, κ = .72; 4-level: 86%, κ = .71) and lowest for
gastroesophageal reflux disease (n = 1032; binary: 75%, κ = .40; 4-level: 57%, κ =
.35). Of patients eligible for both PROs and registry 1-year follow-up, 21% had PROs
only.
Conclusions
One-year patient- and clinic-reported weights and disease status for patients with
diabetes and hypertension showed high agreement. The degree of bias from patient report
was low. Patient report is a viable alternative to clinic report for certain objective
measurements and may increase follow-up.
Keywords
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References
- Patient-reported outcomes (PROs) and patient-reported outcome measures (PROMs).Health Serv Insights. 2013; 6: 61-68
- A comparison of measured versus self-reported anthropometrics for assessing obesity in adults: a literature review.Scand J Public Health. 2018; 46: 565-579
- A comparison of direct vs. self-report measures for assessing height, weight and body mass index: a systematic review.Obes Rev. 2007; 8: 307-326
- Validity of self-reported weights following bariatric surgery.JAMA. 2013; 310: 2454-2456
- Validity of diabetes self-reports in the Women’s Health Initiative.Menopause. 2014; 21: 861-868
- Ascertainment of chronic diseases using population health data: a comparison of health administrative data and patient self-report.BMC Public Health. 2013; 13: 16
- Measuring morbidity: self-report or health care records?.Fam Pract. 2010; 27: 25-30
- No evidence for marked ethnic differences in accuracy of self-reported diabetes, hypertension, and hypercholesterolemia.J Clin Epidemiol. 2007; 60: 1271-1279
- Agreement of self-reported comorbid conditions with medical and physician reports varied by disease among end-stage renal disease patients.J Clin Epidemiol. 2007; 60: 634-642
- An overview of obesity-specific quality of life questionnaires.Obes Rev. 2006; 7: 347-360
- Development of physical and mental health summary scores from the patient-reported outcomes measurement information system (PROMIS) global items.Qual Life Res. 2009; 18: 873-880
- Performance of two self-report measures for evaluating obesity and weight loss.Obes Res. 2004; 12: 48-57
- Common pitfalls in statistical analysis: measures of agreement.Perspect Clin Res. 2017; 8: 187-191
- Method agreement analysis: a review of correct methodology.Theriogenology. 2010; 73: 1167-1179
- Estimating predicted probabilities from logistic regression: different methods correspond to different target populations.Int J Epidemiol. 2014; 43: 962-970
- Is weight fluctuation normal? How much daily weight fluctuation you should expect.(Verywell Fit [Internet]. 2022 Sep [cited 2021]:[about 6 p.]. Available from:)
- Review: what do we mean by GERD?—definition and diagnosis.Aliment Pharmacol Ther. 2005; 22: 2-10
- Presentation and epidemiology of gastroesophageal reflux disease.Gastroenterology. 2018; 154: 267-276
- Telemedicine, the current COVID-19 pandemic and the future: a narrative review and perspectives moving forward in the USA.Fam Med Commun Health. 2020; 8e000530
- Common method biases in behavioral research: a critical review of the literature and recommended remedies.J Appl Psychol. 2003; 88: 879-903
- ASA physical status classification system. American Society of Anesthesiologists.([Internet]. 2014 Oct [updated 2020 Dec 13; cited 2021]:[about 4 p.]. Available from:)
Article info
Publication history
Published online: October 10, 2022
Accepted:
October 3,
2022
Received:
April 7,
2022
Publication stage
In Press Journal Pre-ProofIdentification
Copyright
© 2022 American Society for Metabolic and Bariatric Surgery. Published by Elsevier Inc. All rights reserved.