Improving patient engagement, adherence, and satisfaction in lung cancer surgery with implementation of a mobile device platform for patient reported outcomes

Abstract

Background: Active patient engagement may improve their perioperative experience and outcomes. We sought to evaluate the use of a mobile device application (App) for patient engagement and patient reported outcomes (PROs) assessment following robotic lung cancer surgery. Methods: Patients with suspected lung cancer undergoing robotic resection between January-May 2019, were offered the SeamlessMD App, which was customized to meet requirements of the thoracic enhanced recovery pathway. The App guided patients through preoperative preparation, in-hospital recovery, and postop discharge care with personalized reminders, task lists, education, progress tracking, and surveys. Results: Fifty patients participated in the study (22.1%). Of the 50 patients, 20 (40%) patients completed the preoperative compliance survey, and 31 (62%) completed the hospital satisfaction survey. A total of 62 inpatient recovery checks were completed, identifying non-compliance with incentive spirometer use in 2 (3.2%) and patient worries about self-care after discharge in 18 (29%) instances. Postoperative health-checks were completed by 27 (54%) patients with a median of 3 [0-17] completed surveys per patient. Patient reported symptom scores up to 30 days after surgery, demonstrating a significant decrease maximum pain level (P=0.002) and anxiety scores (P<0.001). The App enabled health-checks improved confidence and decreased worries in over 80% of patients. Nine patients (40.9%) reported the health-checks helped avoid 1+ calls and 4 (18.2%) reported the App helped avoid 1+ visits to the hospital. Over 74% of patients reported the App was very or extremely useful in each of the preoperative, inpatient, and post-discharge settings. Conclusions: A mobile device platform may serve as an effective mechanism to record perioperative PROs and satisfaction while facilitating patient-provider engagement in perioperative care.

Additional Value of Patient-Reported Symptom Monitoring in Cancer Care: A Systematic Review of the Literature

“…All the studies were implemented in Europe and North America (ten of them in the United States and Canada). Of the 16 studies identified, eight had a randomized clinical trial design [ 19 , 20 , 21 , 23 , 24 , 25 , 26 , 27 ], six were observational studies [ 28 , 29 , 30 , 31 , 32 , 33 ] and two were economic evaluations [ 22 , 34 ]. Of the clinical trials, five reports [ 20 , 24 , 25 , 26 , 27 ] were randomized controlled trials with a high-quality design, whereas two [ 19 , 23 ] were research letters that communicated brief reports of data.…”

Multilingual Conversational Systems to Drive the Collection of Patient-Reported Outcomes and Integration into Clinical Workflows

“…The other challenge related to the integration of PGHD relate to the patient's perspective; i.e., long-term sustainability and quality of collected information [36,37]. Familiarity, perceived complexity, and trustworthiness represent the main drivers of patient adher-ence [38].…”

“…In the medical domain, particularly in oncology setting, conversational intelligence focuses primarily on (speech-enabled) chatbots [29] to contribute to screening (i.e., iDecide [30]), improving mental health state through managing psychological distress [31][32][33] and lifestyle changes [34]. Overall, chatbots have been proven as an enabler for active patient engagement, adherence and satisfaction increase [35,36]. "The self-reporting aspect delivered with the mobile application provides benefits that might otherwise be difficult to obtain" [36]:6689.…”

“…Overall, chatbots have been proven as an enabler for active patient engagement, adherence and satisfaction increase [35,36]. "The self-reporting aspect delivered with the mobile application provides benefits that might otherwise be difficult to obtain" [36]:6689. However, the chatbots have yet to tackle the long-term adherence with sustainable quality of the reported data [37].…”

“…However, the chatbots have yet to tackle the long-term adherence with sustainable quality of the reported data [37]. In [36], active use of the technology drops after 14 days. Patients' understanding (i.e., familiarity), their ability to remember the details and perceived trustworthiness represent the main factors of patient adherence [38].…”