Arthritis of the knee, the most common physical disability in US adults, affects 50% of adults over age 65 and 60% of women of all ages. When arthritis pain and disability advances, total knee replacement (TKR) surgery can effectively eliminate pain and improve function. However, many people do not seek help for their arthritis- related symptoms until symptoms become unbearable. At this stage, TKR surgery may not be as effective as if performed earlier. Literature reports that arthritis patients' unwillingness to consider total joint surgery is often due to misunderstanding of their condition and lack of accurate information about the surgery and its potential outcomes. Knowledge about the surgical treatments and outcomes is critical in the decision to seek help sooner than later. The broad research objective is to create an individualized predictive model based upon PCOR findings and integrate a new patient-centered mHealth tool in clinical practice.
The specific aims are 1) to develop an Android-based smartphone app, TJR-Guru that implements the patient-centered outcome prediction models designed for advanced knee arthritis patients and their surgeons to trend pain and disability and support shared treatment decisions; 2) conduct usability testing with arthritis patients and clinicians in the laboratory, clinic and field until e finalize the app development iterations; and 3) randomize 30 patients with knee arthritis to three conditions: 1) TJR-Guru, 2) office-based patient reported symptom surveys, and 3) No Assessment. Following the office visit, we will interview patients and clinicians about their satisfaction, patient level of engagement in decision-making, and clinician knowledge of patient symptom severity, function, and goals. We hypothesize that the TJR-Guru users will be more engaged and informed as compared to other conditions. The proposed m-Health app will integrate tailored patient-centric prediction models developed from a novel national database with innovative app usability and display features to meet the needs of adults with arthritis facin treatment decisions. Importantly, the translation and dissemination of the patient-centered knowledge from the AHRQ-funded national TKR cohort will advance shared clinician-patient decision-making and engagement.
Arthritis of the knee, the most common physical disability in US adults, affects 50% of adults over age 65. Waiting to seek medical help until symptoms are unbearable has a negative impact on health outcomes. Our proposed smartphone app will inform patients about individualized predicted outcomes to facilitate timely decision making by integrating tailored patient-centric prediction models developed from a novel national database with app display features designed to meet the preferences and needs of aging adults with arthritis faced with treatment decisions.
| Choi, Wonchan; Zheng, Hua; Franklin, Patricia et al. (2017) mHealth technologies for osteoarthritis self-management and treatment: A systematic review. Health Informatics J :1460458217735676 |
