In this week’s telehealth research studies collection, we present summaries of five insightful studies highlighting the impact and effectiveness of telehealth interventions in various healthcare settings. The studies range from improving medication adherence in patients with type 2 diabetes to enhancing post-heart attack follow-up care and stroke screening in rural hospitals. These studies shed light on the potential of telehealth to overcome barriers and revolutionize healthcare delivery. Explore the findings and implications that pave the way for accessible and patient-centered care in diverse healthcare scenarios.
1) Telehealth Research Studies: The Effectiveness of Telehealth Interventions on Medication Adherence Among Patients with Type 2 Diabetes: A Meta-Analysis
This meta-analysis of telehealth research studies assessed the impact of telehealth interventions on medication adherence in patients with type 2 diabetes mellitus (DM). Eighteen relevant studies were analyzed. The combined results showed that telehealth interventions significantly increased medication adherence in the intervention group. In addition, subgroup analysis revealed that factors such as HbA1c value, mean age, and duration of intervention influenced the study results. The findings highlight the effectiveness of telehealth interventions in improving medication adherence for patients with type 2 DM. In addition, the study suggests that integrating telehealth interventions into clinical practices can enhance disease management for individuals with diabetes.
2) G.B. Grassi Hospital In Rome & Remote Follow–Up of Ischemic Heart Disease After Myocardial Infarction
The second study in this week’s telehealth research studies includes a telehealth study investigating the use of telemedicine for follow-up care of patients discharged after a heart attack. Utilizing a digital platform, a televisit service was established to provide remote consultations. The consultations were conducted by a team consisting of a cardiologist, nurse, and cardiology technician. The patients had different types of heart attacks and were assessed for their cardiovascular events. The events included: adherence to therapy, achievement of treatment goals, and satisfaction levels. A total of 58 patients were followed during the study period.
At the 1-month televisit, five patients reported symptoms, but all of them continued their prescribed antiplatelet therapy. Additionally, the study examined the patient’s achievement of therapeutic targets for LDL cholesterol, blood pressure, and blood sugar levels. Six patients did not reach the target LDL cholesterol level, with three having stopped taking their cholesterol-lowering medication. One patient experienced symptoms of anemia and was found to have colon diverticulosis with bleeding.
The study also conducted a 4-month follow-up for 42 patients, yielding similar results, with no hospital readmissions or deaths reported. Overall, the televisit approach was deemed safe and well-received by the patients. Thus, the results highlighted the importance of establishing a dedicated team and a health coordination center to support patients.
3) Using Remotely Monitored Patient Activity Patterns after Hospital Discharge to Predict 30-day Hospital Readmission: a Randomized Trial
This third component in this week’s telehealth research studies was a telehealth study looking at the prediction of hospital readmissions using remote patient monitoring data and machine learning approaches. First, researchers randomly assigned 500 patients discharged from the hospital. Patients then used a smartphone or a wearable device to collect remote patient monitoring (RPM) data after discharge. Then, they compared different models and techniques to predict hospital readmissions within 30 days of discharge.
The traditional prediction models used data collected until discharge performed similarly to previously published models, with limited accuracy. However, incorporating RPM data after release significantly improved the prediction. In addition, nonparametric machine learning approaches outperformed traditional parametric regression models, such as random forest, gradient boosting, and ensemble models.
The results showed that smartphones and wearables provided a good prediction of 30-day hospital readmission. Wearables slightly outperformed smartphones. Wearables captured additional measures like sleep patterns, while smartphones had higher data transmission rates for physical activity. Nonparametric machine learning models combined with RPM data resulted in the best prediction. The findings suggest that incorporating remote patient monitoring devices into prediction models could help identify patients at the highest risk of hospital readmission.
4) Patient-Centered Outcomes Of Telehealth For The Care Of Rural-Residing Patients With Urologic Cancer
This week’s telehealth research studies collection includes this study on patients residing in rural areas who face significant obstacles in accessing urologic cancer care. A study conducted at the Fred Hutchinson Cancer Center in Seattle, Washington, explored the potential of telehealth as an accessible solution. The telehealth study included 1091 patients, with 28.7% living in rural communities. Results showed that telehealth provided comparable satisfaction levels to in-person appointments for rural patients. Additionally, rural patients with in-person appointments incurred higher financial costs than those using telehealth. These findings highlight telehealth’s affordability and potential benefits in improving urologic cancer care for rural residents.
5) Analysis of Telestroke Usage in Rural Critical Access Emergency Departments
In the final collection of telehealth research studies, the study examined telestroke utilization and the effectiveness of an electronic medical record (EMR)-derived report as a stroke screening tool in rural hospitals. The analysis included 252 out of 12,685 emergency department visits, suggesting potential acute ischemic stroke (AIS) or transient ischemic attack (TIA) cases. The EMR report showed high specificity (98.78%) but lower sensitivity (58.06%) in identifying strokes.
Of the visits, 12.7% met telestroke criteria, with 38.89% receiving telestroke evaluation. Notably, 92.86% of telestroke consultations led to confirmed AIS/TIA diagnoses. However, 61.11% of eligible patients were diagnosed with AIS/TIA at discharge. The findings highlight the need for further telehealth research studies to understand barriers to telestroke utilization and optimize stroke care in rural hospitals.
Weekly Telehealth Research Studies Summary
These telehealth research studies collectively underscore the transformative potential of telehealth in overcoming barriers, patient adherence, improving access to care, and delivering patient-centered healthcare. As telehealth continues to advance and integrate into clinical practices, it holds immense promise in shaping the future of healthcare delivery, making it more accessible, efficient, and patient-centric. Subscribe to Tenovi’s Weekly Research Round Up for new research into RPM device technology, conditions managed by RPM like chronic heart failure, COPD, Long Covid, and myriad other conditions. Simply scroll down now to subscribe.
