Otolaryngic Allergy Patient Journey Mapping: A Framework for Allergy Immunotherapy Adherence

医学 逻辑回归 脱敏(药物) 观察研究 变应原免疫治疗 过敏 儿科 过敏原 内科学 免疫学 受体
作者
David E. Melon,Harold C. Pillsbury,Willard C. Harrill
出处
期刊:Laryngoscope [Wiley]
卷期号:134 (S11)
标识
DOI:10.1002/lary.31690
摘要

Objectives Allergen‐specific immunotherapy (AIT) is an effective treatment for allergic disease but requires long treatment duration and premature cessation is of significant concern. Drivers of premature cessation remain poorly understood and no predictive models currently exist. We hypothesized that a novel patient journey map and de novo real‐time patient electronic health status instruments (eHSIs) could effectively capture patient perceived cost, commitment, and treatment benefit to identify individual patients at risk for premature AIT cessation. Study Type Cross‐Sectional Observational Study. Methods A single Otolaryngology allergy immunotherapy (AIT) program was studied over 5 years. Instances of premature cessation were classified. An Otolaryngic Allergy Patient Journey Map was developed to identify and target automated, real‐time, patient‐reported, electronic health status instrument responses. Results Data capture was robust, with 61,406 data points collected and an eHSI survey completion rate of 81.3%. However, based on correlation analysis and logistic regression alone, real‐time eHSI responses were not predictive of individual patient premature AIT cessation. A total of 597 AIT patients discontinued treatment prematurely: 64.4% stopping within the first year. Specifically, 74.0%–76.3% of subcutaneous AIT patients and 88.5%–100% of sublingual AIT patients did not complete the minimum recommended treatment duration of 3 years. Conclusion Patient journey mapping can aid in the design of longitudinal care models and patient engagement strategies. Yet, eHSI patient responses of perception of AIT cost, benefit, and convenience did not correlate with the likelihood of premature treatment cessation. Our imperfect clinical intuition may not account for the dynamic drivers of premature AIT discontinuation. Future development of predictive tools feed by large patient‐centric data sets may be incorporated into routine practice resulting in delivery of a more streamlined and personalized approach with reduced premature AIT cessation, improved outcomes, and reduced health care expenditures. Level of Evidence NA Laryngoscope , 134:S1–S14, 2024
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