Back to Search
Start Over
Characterization of multi-domain postoperative recovery trajectories after cardiac surgery using a digital platform.
- Source :
- NPJ Digital Medicine; 12/24/2022, Vol. 5 Issue 1, p1-8, 8p
- Publication Year :
- 2022
-
Abstract
- Understanding postoperative recovery is critical for guiding efforts to improve post-acute phase care. How recovery evolves during the first 30 days after cardiac surgery is not well-understood. A digital platform may enable granular quantification of recovery by frequently capturing patient-reported outcome measures (PROM) that can be clinically implemented to support recovery. We conduct a prospective cohort study using a digital platform to measure recovery after cardiac surgery using a PROM sent every 3 days for 30 days after surgery to characterize recovery in multiple domains (e.g., pain, sleep, activities of daily living, anxiety) and to identify factors related to the patient's perception of overall recovery. We enroll patients who underwent cardiac surgery at a tertiary center between January 2019 and March 2020 and automatically deliver PROMs and reminders electronically. Of the 10 surveys delivered per patient, 8 (IQR 6–10) are completed. Patients who experienced postoperative complications more commonly belong to the worst overall recovery trajectory. Of the 12 domains modeled, only the worst anxiety trajectory is associated with the worse overall recovery trajectory membership, suggesting that even when patients struggle in the recovery of other domains, the patient may still feel progress in their recovery. We demonstrate that using a digital platform, automated PROM data collection, and characterization of multi-domain recovery trajectories is feasible and likely implementable in clinical practice. Overall recovery may be impacted by complications, while slow progress in constituent domains may still allow for the perception of overall recovery progression. [ABSTRACT FROM AUTHOR]
- Subjects :
- SURGERY & psychology
CARDIAC surgery
PAIN measurement
CONVALESCENCE
DIGITAL technology
HEALTH outcome assessment
PATIENTS
SURGICAL complications
ACTIVITIES of daily living
PATIENTS' attitudes
SLEEP
AUTOMATION
DESCRIPTIVE statistics
QUESTIONNAIRES
ANXIETY
STATISTICAL sampling
LONGITUDINAL method
REHABILITATION
EVALUATION
Subjects
Details
- Language :
- English
- ISSN :
- 23986352
- Volume :
- 5
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- NPJ Digital Medicine
- Publication Type :
- Academic Journal
- Accession number :
- 160956524
- Full Text :
- https://doi.org/10.1038/s41746-022-00736-0