Patient Participation With a Mobile Phone Application for Objective Activity Assessment Before and After Spinal Fusion

A Scale for Measuring Electronic Patient Engagement Behaviors: Development and Validation

Purpose

Advancements in electronic health (eHealth) technology have profoundly impacted patient engagement. This study aimed to develop and validate the Electronic Patient Engagement Behavior (EPEB) scale to measure the conceptual and underlying framework of patient engagement behaviors in an eHealth context.

Patients and Methods

Initial measurement items were generated based on a literature review and qualitative research. Two rounds of surveys, a pilot survey and validation survey, were conducted to evaluate the psychometric properties of the scale.

Results

The EPEB scale consists of 15 items in four dimensions: disease information search, physician-patient interaction, social interaction between patients, and disease self-monitoring. In the pilot survey, the exploratory factor analysis revealed a four-factor model, explaining 69.411% of variance. In the validation survey, the Cronbach's α coefficient of each sub-scale was 0.865, 0.904, 0.904, and 0.900 respectively. The Spearman-Brown split coefficient of the scale was 0.963. The results of the cross-sex measurement equivalence test indicate that all fit indices met the measurement criteria. The confirmatory factor analysis indicated second-order 4-factor model fit the data well. The EPEB has a good reliability and validity.

Conclusion

The EPEB scale provides a reliable tool for measuring patient engagement behaviors in the eHealth context. The utilization of this scale may yield valuable insights into strategies for enhancing patient engagement and optimizing health outcomes.

The Role of Mobile Health Technology in Perioperative Spinal Care: A Systematic Scoping Review and Narrative Synthesis

Smartphone applications play a crucial role in contemporary healthcare by aiming to enhance patient care through technology. Mobile health (mHealth) applications have proven to have transformative potential in enhancing patients' outcomes in candidates undergoing orthopedic and spinal surgery. In the context of the pervasive use of smartphones and the exponential growth of mHealth apps, totaling over 99,000 in 2021, the applications had a significant impact on lifestyle management, supporting initiatives like smoking cessation with motivational reminders and progress tracking. Patient compliance is significantly enhanced, reducing surgery cancellations and improving outcomes through effective adherence to pre-operative treatments and instructions. Physiotherapy receives a substantial boost as mHealth facilitates video-guided exercises, potentially improving compliance and treatment outcomes. Data collection takes on innovative dimensions, with mHealth apps capturing post-operative metrics like physical activity, offering valuable insights into patient recovery trends. Remote care is streamlined through features like photo uploads and direct messaging, proving especially beneficial in times of crises such as the COVID-19 pandemic. Despite these merits, challenges emerge, including issues related to technological literacy, potential discrimination due to paywalls, and concerns about patient data confidentiality. Overcoming these challenges requires standardized approaches, legislative measures, and ongoing research to refine and optimize mHealth applications for diverse healthcare settings.

Collection of the International Hip Outcome Tool-12 Using a Smartphone Application Format Is Faster and Preferred When Compared With the Paper Version: A Pilot Study of rHip

Purpose

To evaluate the agreeability between the mobile application-based International Hip Outcome Tool-12 (iHOT-12) survey with the paper version, as well as compare the time it takes patients each of the versions, and patient preferences between the two.

Methods

Patients seen with symptomatic femoroacetabular impingement syndrome were prospectively enrolled in February 2019 and completed both the paper and application-based iHOT-12, in randomized order. Outcomes scores and time to completion were recorded for each version, and patients were also asked which they preferred. Intraclass correlation coefficient was calculated to assess for absolute agreement between the 2 versions. Bland–Altman plots were constructed to evaluate the agreeability between paper and application-based iHOT-12 scores. Bland–Altman plots were evaluated to identify systematic bias and data stratification was performed to identify sequence bias between the application and paper-based collection modalities.

Results

Twenty-nine patients (aged15-56 years) completed both the paper and application-based versions of the iHOT-12. Between the application-based and paper versions, the intraclass correlation coefficient was 0.98, and Bland–Altman analysis showed agreement without bias between versions. There was no sequence bias. Accounting for completion order, the application-based iHOT-12 was faster for patients when compared to the paper version (61.4 ± 20.3 vs 71.9 ± 23.6 seconds, P = .02). Twenty-two patients reported a version preference where 19 of 22 (86%) chose application-based (P < .001).

Conclusions

The application-based iHOT-12 demonstrated absolute agreement with the paper iHOT-12, and is faster for patients to complete. Patients preferred using the application-based iHOT-12 over the paper-based version. Application-based PROs allow for collection of patient data at more frequent time points, which may be helpful in tracking the recovery progress of patients and predicting outcomes.

Clinical Relevance

As electronic-based outcome surveys become more common, it is important to know how the results may differ from traditional paper-based surveys.

Using smartphone-based accelerometers to gauge postoperative outcomes in patients with NPH: Implications for ambulatory monitoring

Background

The surgical treatment of normal pressure hydrocephalus (NPH) with shunting remains controversial due to the difficulty in distinguishing such pathology from other neurological conditions that can present similarly. Thus, patients with suspected NPH should be carefully selected for surgical intervention. Historically, clinical improvement has been measured by the use of functional grades, alleviation of symptoms, and/or patient/family-member reported surveys. Such outcome analysis can be subjective, and there is difficulty in quantifying cognition. Thus, a push for a more quantifiable and objective investigation is warranted, especially for patients with idiopathic NPH (INPH), for which the final diagnosis is confirmed with postoperative clinical improvement. We aimed to use Apple Health (Apple Inc., Cupertino, CA) data to approximate physical activity levels before and after shunt placement for NPH as an objective outcome measurement. The patients were contacted and verbally consented to export Apple Health activity data. The patient's physical activity data were then analyzed. A chart review from the patient's EMR was performed to understand and better correlate recovery.

Case Description

Our first patient had short-term improvements in activity levels when compared to his preoperative activity. The patient's activity level subsequently decreased at 6 months and onward. This decline was simultaneous to new-onset lumbar pain. Our second patient experienced sustained improvements in activity levels for 12 months after his operation. His mobility data were in congruence with his subjectively reported improvement in clinical symptoms. He subsequently experienced a late-decline that began at 48-months. His late deterioration was likely confounded by exogenous factors such as further neurodegenerative diseases coupled with old age.

Conclusion

The use of objective activity data offers a number of key benefits in the analysis of shunted patients with NPH/INPH. In this distinctive patient population, detailed functional outcome analysis is imperative because the long-term prognosis can be affected by comorbid factors or life expectancy. The benefits from using smartphone-based accelerometers for objective outcome metrics are abundant and such an application can serve as a clinical aid to better optimize surgical and recovery care.