Validation of a risk screening toot for pediatric type 1 diabetes patients: a predictor of increased acute health care utilization

被引:1
作者
Glick, Bethany A. [1 ]
Hong, K. Ming Chan [1 ]
Buckingham, Don [2 ]
Moore-Clingenpeel, Melissa [3 ]
Salvator, Ann [3 ]
Kamboj, Manmohan K. [4 ]
机构
[1] Nationwide Childrens Hosp, Pediat Endocrinol, 700 Childrens Dr, Columbus, OH 43205 USA
[2] Nationwide Childrens Hosp, Serv Line Qual Improvement, Columbus, OH USA
[3] Nationwide Childrens Hosp, Biostat Core & Crit Care Med, Columbus, OH USA
[4] Ohio State Univ, Nationwide Childrens Hosp, Pediat Endocrinol, Columbus, OH 43210 USA
关键词
acute health care utilization; hemoglobin A(1c); psychosocial risk; type; 1; diabetes; QUALITY-OF-LIFE; GLYCEMIC CONTROL; YOUNG-ADULTS; FOLLOW-UP; CHILDREN; ADOLESCENTS; MELLITUS; ADHERENCE; PARENTS; HYPOGLYCEMIA;
D O I
10.1515/jpem-2019-0156
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background: Both psychosocial and socioeconomic risk factors contribute to poor glycemic control (GC). Previous research has identified that diabetes care behaviors are generally 'set' by late childhood, further highlighting the importance of psychosocial screening and intervention in the early course of disease management. The purpose of the current study was to determine whether this brief risk assessment tool is associated with GC and acute health care (HC) utilization, and to evaluate the discriminatory utility of the tool for predicting poor outcomes. Methods: This was a retrospective cohort design in which we compared risk assessment scores with health outcomes at 6, 12, and 18 months after new-onset type 1 diabetes diagnosis for 158 patients between 2015 and 2017. The two primary outcome variables were GC and acute HC utilization. Results: Our data demonstrate that the greatest utility of the tool is for predicting increased acute !IC utilization. It was most useful in differentiating between patients with vs. without any acute HC utilization, with excellent discriminatory ability (area under the receiver operator characteristic curve [AUC] = 0.93), sensitivity (90%), and specificity (97%). Conclusions: Knowledge of the risk category in addition to identification of individual risk factors within each domain allows for not only clear treatment pathways but also individualized interventions. The risk assessment tool was less effective at differentiating patients with poor GC; however, the tool did have high specificity (83%) for predicting poor GC at 18 months which suggests that the tool may also be useful for predicting patients at risk for poor GC.
引用
收藏
页码:1155 / 1162
页数:8
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