Developing and validation of a smartphone app for post-discharge early follow-up after colorectal cancer surgeries

被引:0
|
作者
Kupper, Bruna Elisa Catin [1 ]
Bernardon, Elaine Cordeiro [2 ]
Antunes, Camila Forni [2 ]
Martos, Natalia Martinez [2 ]
Sacomani, Carlos Alberto Ricetto [3 ]
Azevedo, Mauricio [4 ]
Adolfi Junior, Mario Sergio [5 ]
Bezerra, Tiago Santoro [1 ]
Marques, Tomas Mansur Duarte de Miranda [1 ]
Stevanato Filho, Paulo Roberto [1 ]
Takahashi, Renata Mayumi [1 ]
Nakagawa, Wilson Toshihiko [1 ]
Lopes, Ademar [1 ]
Aguiar Jr, Samuel [1 ]
机构
[1] AC Camargo Canc Ctr, Colorectal Canc Reference Ctr, Sao Paulo, Brazil
[2] AC Camargo Canc Ctr, Value Based Off, Sao Paulo, Brazil
[3] AC Camargo Canc Ctr, Innovat & Technol Dept, Sao Paulo, Brazil
[4] Johnson & Johnson MedTech, Sao Paulo, Brazil
[5] Kidopi, Sao Paulo, Brazil
来源
DIGITAL HEALTH | 2024年 / 10卷
关键词
Mobile app; mobile health; telemedicine; transitional care; readmissions; health services research; PATIENT-REPORTED OUTCOMES; SURGICAL COMPLICATIONS; PERFORMANCE-MEASURES; READMISSION; INDICATORS;
D O I
10.1177/20552076241292389
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background Colorectal surgeries are complex procedures associated with high rates of complications and hospital readmission.Objective This study aimed to develop an electronic post-discharge follow-up plan to remotely monitor patients' symptoms in the postoperative period of colorectal surgeries and evaluate the outcomes of emergency department visits and the rate of severe complications within 15 days after hospital discharge.Design We developed a digital tool capable of remotely assessing symptoms that could indicate complications related to colorectal surgical procedures and directing early management. This project was divided into two stages. The first was platform development with an algorithm for identifying symptoms and directing conduct, and the second was clinical validation of the program and evaluation of patient's experience. Patients who underwent elective oncological colorectal surgery were invited to participate in this study. We used commercial software (CleverCare) that was adjusted according to the clinical algorithm developed in this study, predicting complications and directing conduct with minimal human intervention using a Chatbot with Natural Language Processing (NPL) and artificial intelligence.Results We planned three Interim Analyses to evaluate the outcomes of complications, referrals to the Emergency Department (ED), ED visits, adherence, and patient satisfaction. After each analysis, specialists validated the changes before implementation. A total of 92 eligible participants agreed to participate in the study. The ability to detect complications increased with each adjustment phase, and after the third and last phase, the digital solution identified 3(4.8%) real complications, with a sensitivity of 75%, specificity of 83%, accuracy of 82%, positive predictive value of 27%, and negative predictive value of 97%. Complete adherence to the monitoring program was 83.7% with an NPS score of 94 in the last evaluation phase.Conclusion The digital platform is safe with high adherence rates and good patient acceptance.
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页数:11
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