The effect of a mobile health app on adherence to physical health treatment

Evaluation of Patient-Facing Mobile Apps to Support Physiotherapy Care: Systematic Review

BACKGROUND

Mobile health interventions delivered through mobile apps are increasingly used in physiotherapy care. This may be because of the potential of apps to facilitate changes in behavior, which is central to the aims of care delivered by physiotherapists. A benefit of using apps is their ability to incorporate behavior change techniques (BCTs) that can optimize the effectiveness of physiotherapeutic interventions. Research continues to suggest that despite their importance, behavior change strategies are often missing in patient management. Evaluating mobile apps that physiotherapists can use to drive behavior change may inform clinical practice and potentially improve patient outcomes. Examining the quality of apps and exploring their key features that can support behavior change and physiotherapy care are important aspects of such an evaluation.

OBJECTIVE

The primary aim of this study was to describe the range of mobile apps in app stores that are intended for use by patients to support physiotherapy care. The secondary aims were to assess app quality, BCTs, and their behavior change potential.

METHODS

A systematic review of mobile apps in app stores was undertaken. The Apple App Store and Google Play were searched using a 2-step search strategy, using terms relevant to the physiotherapy discipline. Strict inclusion and exclusion criteria were applied: apps had to be intended for use by patients and be self-contained (or stand-alone) without the requirement to be used in conjunction with a partner wearable device or another plugin. Included apps were coded for BCTs using the Behavior Change Technique Taxonomy version 1. App quality was assessed using the Mobile App Rating Scale, and the App Behavior Change Scale was used to assess the app's potential to change behavior.

RESULTS

In total, 1240 apps were screened, and 35 were included. Of these 35 apps, 22 (63%) were available on both the Apple App Store and Google Play platforms. In total, 24 (69%) were general in their focus (eg, not condition-specific), with the remaining 11 (31%) being more specific (eg, knee rehabilitation and pelvic floor training). The mean app quality score (Mobile App Rating Scale) was 3.7 (SD 0.4) of 5 (range 2.8-4.5). The mean number of BCTs identified per app was 8.5 (SD 3.6). BCTs most frequently included in the apps were instruction on how to perform a behavior (n=32), action planning (n=30), and self-monitoring of behavior (n=28). The mean behavior change potential score (App Behavior Change Scale) was 8.5 (SD 3.1) of 21 (range 3-15).

CONCLUSIONS

Mobile apps available to support patient care received from a physiotherapist are of variable quality. Although they contain some BCTs, the potential for behavior change varied widely across apps.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/29047.

Amputation Rates and Associated Social Determinants of Health in the Most Populous US Counties

Importance

Social Determinants of Health (SDOH) have been found to be associated with health outcome disparities in patients with peripheral artery disease (PAD). However, the association of specific components of SDOH and amputation has not been well described.

Objective

To evaluate whether individual components of SDOH and race are associated with amputation rates in the most populous counties of the US.

Design, Setting, and Participants

In this population-based cross-sectional study of the 100 most populous US counties, hospital discharge rates for lower extremity amputation in 2017 were assessed using the Healthcare Cost and Utilization Project State Inpatient Database. Those data were matched with publicly available demographic, hospital, and SDOH data. Data were analyzed July 3, 2022, to March 5, 2023.

Main outcome and Measures

Amputation rates were assessed across all counties. Counties were divided into quartiles based on amputation rates, and baseline characteristics were described. Unadjusted linear regression and multivariable regression analyses were performed to assess associations between county-level amputation and SDOH and demographic factors.

Results

Amputation discharge data were available for 76 of the 100 most populous counties in the United States. Within these counties, 15.3% were African American, 8.6% were Asian, 24.0% were Hispanic, and 49.6% were non-Hispanic White; 13.4% of patients were 65 years or older. Amputation rates varied widely, from 5.5 per 100 000 in quartile 1 to 14.5 per 100 000 in quartile 4. Residents of quartile 4 (vs 1) counties were more likely to be African American (27.0% vs 7.9%, P < .001), have diabetes (10.6% vs 7.9%, P < .001), smoke (16.5% vs 12.5%, P < .001), be unemployed (5.8% vs 4.6%, P = .01), be in poverty (15.8% vs 10.0%, P < .001), be in a single-parent household (41.9% vs 28.6%, P < .001), experience food insecurity (16.6% vs 12.9%, P = .04), or be physically inactive (23.1% vs 17.1%, P < .001). In unadjusted linear regression, higher amputation rates were associated with the prevalence of several health problems, including mental distress (β, 5.25 [95% CI, 3.66-6.85]; P < .001), diabetes (β, 1.73 [95% CI, 1.33-2.15], P < .001), and physical distress (β, 1.23 [95% CI, 0.86-1.61]; P < .001) and SDOHs, including unemployment (β, 1.16 [95% CI, 0.59-1.73]; P = .03), physical inactivity (β, 0.74 [95% CI, 0.57-0.90]; P < .001), smoking, (β, 0.69 [95% CI, 0.46-0.92]; P = .002), higher homicide rate (β, 0.61 [95% CI, 0.45-0.77]; P < .001), food insecurity (β, 0.51 [95% CI, 0.30-0.72]; P = .04), and poverty (β, 0.46 [95% CI, 0.32-0.60]; P < .001). Multivariable regression analysis found that county-level rates of physical distress (β, 0.84 [95% CI, 0.16-1.53]; P = .03), Black and White racial segregation (β, 0.12 [95% CI, 0.06-0.17]; P < .001), and population percentage of African American race (β, 0.06 [95% CI, 0.00-0.12]; P = .03) were associated with amputation rate.

Conclusions and Relevance

Social determinants of health provide a framework by which the associations of environmental factors with amputation rates can be quantified and potentially used to guide interventions at the local level.

The effect of a mobile health App on treatment adherence and revenue at physical health clinics: a retrospective record review

BACKGROUND

A significant proportion of patients do not adhere to their prescribed course of physical therapy or self-discharge themselves from care. Adhering to prescribed physical therapy, including attending physical therapy clinic appointments, contribute to patients achieving the goals of therapy including reducing pain and increasing functioning. Online platforms have been demonstrated to be effective means for managing clinical patients with musculoskeletal pain similar to managing them in person. Behavioral change techniques introduced through digital or online platforms can reduce nonadherence with prescribed physical therapy and improve patient outcomes. The literature also indicates that a phone-based App provided to patients that includes a reward incentive gamification to complement their care contributed to a greater number of kept appointments in a physical therapy clinic.

OBJECTIVE

The purpose of this study was to compare the rate of provider-discharge with self-discharge and the number of clinic visits among patients attending a physical health clinic who did and did not choose to adopt a phone-based App to complement their care. A secondary purpose was to compare the revenue generated by patients attending a physical health clinic who did and did not choose to adopt a phone-based App to complement their care.

METHODS

A retrospective analysis of all new outpatient medical records (n=5,328) from a multisite physical health practice were evaluated between January 2018 to December 2019. Patients in the sample self-selected into the 2018 Usual Care Group, the 2019 Usual Care Group and the 2019 Kanvas App Group who downloaded the Kanvas App. Kanvas is a customized private practice App, designed for patient engagement with their specific health care provider. This App included a gamification system that provided rewards to the patient for attending their scheduled clinic appointments. According to their medical record each patient was classified as completing prescribed therapy (Provider-Discharged) or not completing their prescribed therapy (Self-Discharged). Also, extracted from each patient's medical record were the total number of clinic visits each patient attended, the total charges for services and the total payments received by the clinic per patient.

RESULTS

Patients in the 2019 Kanvas App Group exhibited a higher rate of provider-discharge compared to the patients who did not adopt the App. This greater rate of provider-discharges among the patients who adopted the Kanvas App likely contributed to this group attending more clinic visits (13.21+12.09) than the other study groups who did not download the App (10.72+9.80 - 11.35+11.10). This greater number of clinic visits in turn contributed to the patients who adopted the App generating more clinic charges and payments.

CONCLUSIONS

Future investigators need to employ more rigorous methods to confirm these findings and healthcare providers need to weigh the anticipated benefits against the cost and staff involvement in managing the Kanvas App.

CLINICALTRIAL

Effect of electronic reminders on patients' compliance during clear aligner treatment: an interrupted time series study

Patient compliance is relevant to achieving therapeutic goals during clear aligner therapy (CAT). The aim of this study was to evaluate the efficacy of remote electronic (e-)reminders and e-feedback on compliance during CAT using an interrupted time series (ITS) analysis. We used routinely collected mobile application data from a German healthtech company (PlusDental, Berlin). Our primary outcome was self-reported compliance (aligner wear time min. 22 h on 75% of their aligners were classified as fully compliant, min. 22 h on 50–74.9% of their aligners: fairly compliant; min. 22 h on < 50% of their aligners: poorly compliant). E-reminders and e-feedback were introduced in the 1st quarter of 2020. Compliance was assessed at semi-monthly intervals from June-December 2019 (n = 1899) and June-December 2020 (n = 5486), resulting in a pre- and post-intervention group. ITS and segmented regression modelling were used to estimate the effect on the change in levels and trends of poor compliance. Pre-intervention, poor compliance was at 24.47% (95% CI: 22.59% to 26.46%). After the introduction of e-reminders and e-feedback (i.e., post-intervention), the percentage of poorly compliant patients decreased substantially, levelling off at 9.32% (95% CI: 8.31% to 10.45%). E-reminders and e-feedback were effective for increasing compliance in CAT patients.

Clinical Significance: Orthodontists and dentists may consider digital monitoring and e-reminders to improve compliance and increase treatment success.