Mobile health technology for remote home monitoring after surgery: a meta-analysis

Abstract

Background Mobile health (mHealth) technology has been proposed as a method of improving post-discharge surveillance. Little is known about how mHealth has been used to track patients after surgery and whether its use is associated with differences in postoperative recovery. Methods Three databases (PubMed, MEDLINE and the Cochrane Central Registry of Controlled Trials) were searched to identify studies published between January 1999 and February 2021. Mobile health was defined as any smartphone or tablet computer capable of electronically capturing health-related patient information and transmitting these data to the clinical team. Comparable outcomes were pooled via meta-analysis with additional studies compiled via narrative review. The quality of each study was assessed based on Grading of Recommendations Assessment, Development, and Evaluation (GRADE) criteria. Results Forty-five articles met inclusion criteria. While the majority of devices were designed to capture general health information, others were specifically adapted to the expected outcomes or potential complications of the index procedure. Exposure to mHealth was associated with fewer emergency department visits (odds ratio 0.42, 95 per cent c.i. 0.23 to 0.79) and readmissions (odds ratio 0.47, 95 per cent c.i. 0.29 to 0.77) as well as accelerated improvements in quality of life after surgery. There were limited data on other postoperative outcomes. Conclusion Remote home monitoring via mHealth is feasible, adaptable, and may even promote more effective postoperative care. Given the rapid expansion of mHealth, physicians and policymakers need to understand these technologies better so that they can be integrated into high-quality clinical care.

Postsurgical Remote Patient Monitoring Outcomes and Perceptions: A Mixed-Methods Assessment

“…A recent meta-analysis analyzed 45 studies in which mobile telemonitoring was performed in patients postsurgery. 4 Although there was no difference in the number of outpatient visits, there was a significant reduction in hospital (odds ratio: 0.47, 95% confidence interval: 0.29-0.79) and ED visits (odds ratio: 0.42, 95% confidence interval: 0.23-0.79) in the pooled analysis; however, there were no differences in complications. Of note, only a few individual studies have found differences in outcomes between groups, including patients who underwent transplant and total knee and hip arthroplasty.…”

“…They reported substantial financial savings, a 75% reduction in clinic appointments, and a 97% patient satisfaction score. Additionally, a recent meta-analysis conducted by Dawes et al 4 including 45 remote monitoring studies focused on mobile telemonitoring, reported broad adherence rates, improved quality of life, and decreased readmissions and emergency department (ED) visits. However, they note limitations, including that only 11 studies identified postoperative outcomes, heterogeneity of outcome measures, and weak study designs.…”

Telemedicine Technologies Selection for the Posthospital Patient Care Process after Total Hip Arthroplasty

“…The users of telemedicine technologies in posthospital patient care process after THA are patients (at every stage of the process), physicians [ 13 , 14 , 23 , 24 , 38 ], physiotherapists [ 15 , 16 , 24 , 25 , 26 ], surgeons, [ 17 , 18 , 25 ], surgeon’s administrative assistants [ 17 ], health care team [ 27 ], and rehabilitation center [ 28 ].…”

“…Remote home monitoring via mHealth is feasible, adaptable, and may even promote more effective postoperative care. Given the rapid expansion of mHealth, physicians and policymakers need to understand these technologies better so that they can be integrated into high-quality clinical care [ 38 ].…”

Gamification for Machine Learning in Surgical Patient Engagement

“…Kane et al found that failure to achieve baseline step counts was associated with risk of readmission in colorectal surgery patients ( 37 ). A meta-analysis of studies in mobile health applications used by postoperative patients demonstrated reduced emergency department visits and hospital admissions ( 38 ). Meanwhile, deep learning has been trained to recognize skin lesions at a degree comparable to board-certified dermatologists ( 39 ).…”