%0 Journal Article
%@ 2561-7605
%I 
%V 6
%N 
%P e44037
%T Diabetes Life Expectancy Prediction Model Inputs and Results From Patient Surveys Compared With Electronic Health Record Abstraction: Survey Study
%A Bernstein,Sean
%A Gilson,Sarah
%A Zhu,Mengqi
%A Nathan,Aviva G
%A Cui,Michael
%A Press,Valerie G
%A Shah,Sachin
%A Zarei,Parmida
%A Laiteerapong,Neda
%A Huang,Elbert S
%K diabetes mellitus
%K patient-reported outcome measure
%K life expectancy
%K diabetes
%K diabetic
%K predict
%K model
%K mortality
%K chart review
%K chart abstraction
%K patient chart
%K prediction model
%K patient-reported outcome
%D 2023
%7 9.11.2023
%9 
%J JMIR Aging
%G English
%X Background: Prediction models are being increasingly used in clinical practice, with some requiring patient-reported outcomes (PROs). The optimal approach to collecting the needed inputs is unknown. Objective: Our objective was to compare mortality prediction model inputs and scores based on electronic health record (EHR) abstraction versus patient survey. Methods: Older patients aged ≥65 years with type 2 diabetes at an urban primary care practice in Chicago were recruited to participate in a care management trial. All participants completed a survey via an electronic portal that included items on the presence of comorbid conditions and functional status, which are needed to complete a mortality prediction model. We compared the individual data inputs and the overall model performance based on the data gathered from the survey compared to the chart review. Results: For individual data inputs, we found the largest differences in questions regarding functional status such as pushing/pulling, where 41.4% (31/75) of participants reported difficulties that were not captured in the chart with smaller differences for comorbid conditions. For the overall mortality score, we saw nonsignificant differences (P=.82) when comparing survey and chart-abstracted data. When allocating participants to life expectancy subgroups (<5 years, 5-10 years, >10 years), differences in survey and chart review data resulted in 20% having different subgroup assignments and, therefore, discordant glucose control recommendations. Conclusions: In this small exploratory study, we found that, despite differences in data inputs regarding functional status, the overall performance of a mortality prediction model was similar when using survey and chart-abstracted data. Larger studies comparing patient survey and chart data are needed to assess whether these findings are reproduceable and clinically important. 
%M 37962566
%R 10.2196/44037
%U https://aging.jmir.org/2023/1/e44037
%U https://doi.org/10.2196/44037
%U http://www.ncbi.nlm.nih.gov/pubmed/37962566