Dataset Information

Mobile applications for pain management: an app analysis for clinical usage.

ABSTRACT:

Background

Pain is the most common and distressing symptom for patients in all clinical settings. The dearth of health informatics tools to support acute and chronic pain management may be contributing to the chronic pain and opioid abuse crises. The purpose of this study is to qualitatively evaluate the content and functionality of mobile pain management apps.

Methods

The Apple App Store and the Google Play Store were searched to identify pain management apps. The inclusion criteria were as follows: (1) that apps include a pain diary function allowing users to record pain episodes, (2) are available in either Apple App Store or Google Play Store, and (3) are available in the English language. We excluded apps if they were limited to only specific forms of pain or specific diseases.

Results

A total of 36 apps met the inclusion criteria. Most of the apps served as pain diary tools to record the key characteristics of pain. The pain diary features of the apps were grouped into nine categories: the recordings of pain intensity, pain location, pain quality, pain's impacts on daily life, other features of pain, other related symptoms, medication, patients' habits and basic information, and other miscellaneous functions. The apps displayed various problems in use. The problem of not involving healthcare professionals in app development has not been resolved. Approximately 31% of apps including a pain diary function engaged clinicians in app development. Only 19% involved end-users in development and then only in an ad-hoc way. Only one third of the apps supported the cross-platforms, none of the apps supported clinician access to graphical pain data visualization, none secured HIPAA compliance, and none endorsed the PEG tool for primary care physicians' chronic pain management.

Conclusions

Most of the 36 pain management apps demonstrated various problems including user interface and security. Many apps lacked clinician and end-user involvement in app development impacting the clinical utility of these apps. We could not find any pain apps suitable for clinical usage despite high demand from clinicians due to the US opioid crisis.

SUBMITTER: Zhao P

PROVIDER: S-EPMC6543581 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Publications

Mobile applications for pain management: an app analysis for clinical usage.

Zhao Peng P Yoo Illhoi I Lancey Robert R Varghese Ebby E

BMC medical informatics and decision making 20190530 1

<h4>Background</h4>Pain is the most common and distressing symptom for patients in all clinical settings. The dearth of health informatics tools to support acute and chronic pain management may be contributing to the chronic pain and opioid abuse crises. The purpose of this study is to qualitatively evaluate the content and functionality of mobile pain management apps.<h4>Methods</h4>The Apple App Store and the Google Play Store were searched to identify pain management apps. The inclusion crite ...[more]

PMID: 31146739

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Project description:BackgroundPostfracture acute pain is often inadequately managed in older adults. Mobile health (mHealth) technologies can offer opportunities for self-management of pain; however, insufficient apps exist for acute pain management after a fracture, and none are designed for an older adult population.ObjectiveThis study aims to design, develop, and evaluate an mHealth app prototype using a human-centered design approach to support older adults in the self-management of postfracture acute pain.MethodsThis study used a multidisciplinary and user-centered design approach. Overall, 7 stakeholders (ie, 1 clinician-researcher specialized in internal medicine, 2 user experience designers, 1 computer science researcher, 1 clinical research assistant researcher, and 2 pharmacists) from the project team, together with 355 external stakeholders, were involved throughout our user-centered development process that included surveys, requirement elicitation, participatory design workshops, mobile app design and development, mobile app content development, and usability testing. We completed this study in 3 phases. We analyzed data from prior surveys administered to 305 members of the Canadian Osteoporosis Patient Network and 34 health care professionals to identify requirements for designing a low-fidelity prototype. Next, we facilitated 4 participatory design workshops with 6 participants for feedback on content, presentation, and interaction with our proposed low-fidelity prototype. After analyzing the collected data using thematic analysis, we designed a medium-fidelity prototype. Finally, to evaluate our medium-fidelity prototype, we conducted usability tests with 10 participants. The results informed the design of our high-fidelity prototype. Throughout all the phases of this development study, we incorporated inputs from health professionals to ensure the accuracy and validity of the medical content in our prototypes.ResultsWe identified 3 categories of functionalities necessary to include in the design of our initial low-fidelity prototype: the need for support resources, diary entries, and access to educational materials. We then conducted a thematic analysis of the data collected in the design workshops, which revealed 4 themes: feedback on the user interface design and usability, requests for additional functionalities, feedback on medical guides and educational materials, and suggestions for additional medical content. On the basis of these results, we designed a medium-fidelity prototype. All the participants in the usability evaluation tests found the medium-fidelity prototype useful and easy to use. On the basis of the feedback and difficulties experienced by participants, we adjusted our design in preparation for the high-fidelity prototype.ConclusionsWe designed, developed, and evaluated an mHealth app to support older adults in the self-management of pain after a fracture. The participants found our proposed prototype useful for managing acute pain and easy to interact with and navigate. Assessment of the clinical outcomes and long-term effects of our proposed mHealth app will be evaluated in the future.

Project description:BACKGROUND:Despite the availability of effective medications and clinical guidelines for pain management, pain control is suboptimal in a sizeable proportion of patients with cancer pain. The National Comprehensive Cancer Network guidelines recommend a comprehensive and multimodal approach for management of cancer pain. We developed a mobile phone application, ePAL, based on clinical guidelines to empower patients for cancer pain management by prompting regular pain assessments and coaching for self-management. OBJECTIVE:The objective of this study is to evaluate the effect of a multidimensional mobile phone-based pain management application, ePAL, on controlling cancer pain and improving quality of life in patients with cancer pain being treated at an academic palliative care clinic. METHODS:The study will be implemented as a 2-arm randomized controlled trial with 110 adult patients with CP who own a mobile phone over a follow-up period of two months. Participants will be randomized to either the intervention group receiving ePAL and usual care or to a control group receiving only usual care. The brief pain inventory will be used to assess our primary outcome which is pain intensity. We will also evaluate the effect of the intervention on secondary outcomes which include the effect of the intervention on hospital utilization for pain crisis, quality of life, adherence to analgesic medications, barriers to pain control, anxiety and patient engagement. Instruments that will be used in evaluating secondary outcomes include the Brief Pain Inventory, Morisky Medication Adherence Scale, Barriers Questionnaire-II, Functional Assessment of Cancer Therapy-General, Edmonton Symptom Assessment System, Generalized Anxiety Disorder 7-item scale, and the Functional Assessment of Chronic Illness Therapy-Fatigue. The intention-to-treat approach will be used to evaluate outcomes. Our primary outcome, pain intensity, measured longitudinally over eight weeks, will be assessed by mixed model repeated analysis. Effect sizes will be calculated as mean group differences with standard deviations. RESULTS:The study is still in progress. We hope to have results by the end of 2015. CONCLUSIONS:The multidimensional approach to pain management implemented on a mobile phone application could lead to significant improvements in patient outcomes. TRIAL REGISTRATION:ClinicalTrials.gov NCT02069743; https://clinicaltrials.gov/ct2/show/NCT02069743 (Archived by WebCite at http://www.webcitation.org/6Qb65XGGA).

Project description:BackgroundThe efficacy of digital technology in improving diabetes management has typically been demonstrated through studies such as randomized controlled trials, which have reported a steeper reduction in hemoglobin A1c (HbA1c) values for patients who adopted a digital solution. However, evidence from real-world clinical practice is still limited.ObjectiveThis study aimed to evaluate the effectiveness of digital interventions by tracking HbA1c improvements over 1 year in real-world clinical settings.MethodsPatients used the Health2Sync mobile app to track self-measured outcomes and communicate with health care professionals (HCPs). HCPs used the web-based Patient Management Platform to monitor patient data, view test results from clinical laboratories, and communicate with patients. Patients who have been onboarded for at least 13 months and have consecutive HbA1c findings for 5 quarters were included in the analysis. They were then stratified into 3 groups (high, mid, and low retention) based on their level of use of Health2Sync in the first 6 months of onboarding. A mixed model was built to compare the slopes of the rate of reduction in HbA1c among the groups. In addition, these patients' retention on the app from the seventh to the 12th month was verified through multiple comparisons.ResultsA sample of 2036 users was included in the analysis. With the mixed model coefficient estimates, we found that app users had significant HbA1c percentage reductions as the passed quarter count increased (t=-9.869; P<.001), and that effectiveness increased in the high (t=-5.173) and mid retention (t=-6.620) groups as the interaction effects were significantly negative compared to that in the low retention group (P<.001) in the passed quarter count. The low retention group also had the highest average HbA1c value at the end of 13 months (high: 7.01%, SD 1.02%; mid: 6.99%, SD 1.00%; low: 7.17%, SD 1.14%) (Bonferroni correction: high vs low, P=.07; mid vs low, P=.02; high vs mid, P>.99). The level of use of the app remained consistent in the seventh to the 12th month after onboarding (high: 5.23 [SD 1.37] months, mid: 2.43 [SD 1.68] months, low: 0.41 [SD 0.97] months) (P<.001).ConclusionsOur analysis shows that continuous usage of the diabetes management app is associated with better glycemic control in real-world clinical practice. Further studies are required to reveal the efficacy for specific diabetes types and to observe effects beyond 1 year.

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Dataset Information

Mobile applications for pain management: an app analysis for clinical usage.

Background

Methods

Results

Conclusions

Publications

Mobile applications for pain management: an app analysis for clinical usage.

Similar Datasets

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