Dataset Information

Using Mobile Phones to Collect Patient Data: Lessons Learned From the SIMPle Study.

ABSTRACT: BACKGROUND:Mobile phones offer new opportunities to efficiently and interactively collect real-time data from patients with acute illnesses, such as urinary tract infections (UTIs). One of the main benefits of using mobile data collection methods is automated data upload, which can reduce the chance of data loss, an issue when using other data collection methods such as paper-based surveys. OBJECTIVE:The aim was to explore differences in collecting data from patients with UTI using text messaging, a mobile phone app (UTI diary), and an online survey. This paper provides lessons learned from integrating mobile data collection into a randomized controlled trial. METHODS:Participants included UTI patients consulting in general practices that were participating in the Supporting the Improvement and Management of UTI (SIMPle) study. SIMPle was designed to improve prescribing antimicrobial therapies for UTI in the community. Patients were invited to reply to questions regarding their UTI either via a prospective text message survey, a mobile phone app (UTI diary), or a retrospective online survey. Data were collected from 329 patients who opted in to the text message survey, 71 UTI patients through the mobile phone UTI symptom diary app, and 91 online survey participants. RESULTS:The age profile of UTI diary app users was younger than that of the text message and online survey users. The largest dropout for both the text message survey respondents and UTI diary app users was after the initial opt-in message; once the participants completed question 1 of the text message survey or day 2 in the UTI diary app, they were more likely to respond to the remaining questions/days. CONCLUSIONS:This feasibility study highlights the potential of using mobile data collection methods to capture patient data. As well as improving the efficiency of data collection, these novel approaches highlight the advantage of collecting data in real time across multiple time points. There was little variation in the number of patients responding between text message survey, UTI diary, and online survey, but more patients participated in the text message survey than the UTI diary app. The choice between designing a text message survey or UTI diary app will depend on the age profile of patients and the type of information the researchers' desire. TRIAL REGISTRATION:ClinicalTrials.gov NCT01913860; https://clinicaltrials.gov/ct2/show/NCT01913860 (Archived by WebCite at http://www.webcitation.org/6pfgCztgT).

SUBMITTER: Duane S

PROVIDER: S-EPMC5424123 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Using Mobile Phones to Collect Patient Data: Lessons Learned From the SIMPle Study.

Duane Sinead S Tandan Meera M Murphy Andrew W AW Vellinga Akke A

JMIR research protocols 20170425 4

<h4>Background</h4>Mobile phones offer new opportunities to efficiently and interactively collect real-time data from patients with acute illnesses, such as urinary tract infections (UTIs). One of the main benefits of using mobile data collection methods is automated data upload, which can reduce the chance of data loss, an issue when using other data collection methods such as paper-based surveys.<h4>Objective</h4>The aim was to explore differences in collecting data from patients with UTI usin ...[more]

PMID: 28442451

Similar Datasets

Project description:BackgroundThe richness of patients? experiences warrants thoughtful and careful examination. While standardized surveys or other structured approaches can be useful when the goal is to count or summarize relatively uncomplicated experiences, they may be less appropriate when the objective is to study sensitive topics, such as medical errors during cancer care. This abstract describes and evaluates a flexible, patient-centered approach to interviewing patients.MethodsUsing a patient-centered telephone interview guide, we interviewed cancer patients who had experienced a problem during their care. Participants were first asked to fully describe their experience; follow-up questions probed for details relevant to the study questions. Question order varied, consistent with a conversational approach. Interviews lasted 60?90 minutes and were digitally recorded. We calculated the percentage of words uttered by participants (compared to the interviewer) as a measure of participant engagement, and noted whether participants corrected the interviewer. Strengths and limitations of this approach are also identified.ResultsSeventy-eight patients were interviewed; 96% (75/78) were female, mean age was 57.7 [SD 10.6]. Overall, participants uttered an average of 77% (6,190/8,001) of the words in the interview. Participants corrected the interviewer at least once in 80% (62/78) of the interviews. Question order was flexible, and probes were used at the discretion of the interviewer. Thus, the interviewer could adapt her questioning to follow the participant?s lead, and sensitively encourage and support participants in sharing details of painful experiences. One benefit of this technique was that it allowed the interviewer to convey interest and respect, which enhanced rapport early in the interview. It also enabled participants to recall details that may otherwise have been forgotten. The drawbacks of this approach include longer interview times; discussion of unrelated topics (by participants) and increased time required for data analyses.ConclusionsPatient-centered conversational interviewing can facilitate investigation of emotionally-charged, personal experiences. This approach appears more effective than standardized interviewing techniques when the goal is to fully understand patients? experiences, such as those of cancer survivors who believe that an error occurred during their cancer care.

Project description:Self-management is critical to achieving diabetes treatment goals. Mobile phones and Bluetooth® can supportself-management and lifestyle changes for chronic diseases such as diabetes. A mobile health (mHealth) research platform--the Few Touch Application (FTA)--is a tool designed to support the self-management of diabetes. The FTA consists of a mobile phone-based diabetes diary, which can be updated both manually from user input and automatically by wireless data transfer, and which provides personalized decision support for the achievement of personal health goals. Studies and applications (apps) based on FTAs have included: (1) automatic transfer of blood glucose (BG) data; (2) short message service (SMS)-based education for type 1diabetes (T1DM); (3) a diabetes diary for type 2 diabetes (T2DM); (4) integrating a patient diabetes diary with health care (HC) providers; (5) a diabetes diary for T1DM; (6) a food picture diary for T1DM; (7) physical activity monitoring for T2DM; (8) nutrition information for T2DM; (9) context sensitivity in mobile self-help tools; and (10) modeling of BG using mobile phones. We have analyzed the performance of these 10 FTA-based apps to identify lessons for designing the most effective mHealth apps. From each of the 10 apps of FTA, respectively, we conclude: (1) automatic BG data transfer is easy to use and provides reassurance; (2) SMS-based education facilitates parent-child communication in T1DM; (3) the T2DM mobile phone diary encourages reflection; (4) the mobile phone diary enhances discussion between patients and HC professionals; (5) the T1DM mobile phone diary is useful and motivational; (6) the T1DM mobile phone picture diary is useful in identifying treatment obstacles; (7) the step counter with automatic data transfer promotes motivation and increases physical activity in T2DM; (8) food information on a phone for T2DM should not be at a detailed level; (9) context sensitivity has good prospects and is possible to implement on today's phones; and (10) BG modeling on mobile phones is promising for motivated T1DM users. We expect that the following elements will be important in future FTA designs: (A) automatic data transfer when possible; (B) motivational and visual user interfaces; (C) apps with considerable health benefits in relation to the effort required; (D) dynamic usage, e.g., both personal and together with HC personnel, long-/short-term perspective; and (E) inclusion of context sensitivity in apps. We conclude that mHealth apps will empower patients to take a more active role in managing their own health.

Project description:BackgroundProviding financial incentives has gained popularity as a strategy to promote weight loss, but questions remain about how best to utilize them. A promising mobile health strategy provides users with near-real-time financial incentives based on both the process of weight loss (behavioral modification) and actual weight loss. To maximize the impact of this strategy, a methodology is needed to close the gap between the desired behavior and the financial incentive. Leveraging mobile health tools-such as mobile phone apps, cellular body weight scales that transmit data to physicians and researchers, and text messaging for instructions and encouragement-has the potential to close this gap.ObjectiveThis study aimed to describe the development of an innovative technology-based solution and lessons learned from a feasibility trial-Log2Lose-that encouraged individuals to lose weight by providing near-real-time financial incentives for weight loss and/or dietary self-monitoring.MethodsWe recruited participants (N=96) with a body mass index greater than or equal to 30 kg/m2 for a 24-week weight loss trial. Participants received a behavioral intervention of biweekly, in-person group sessions and were instructed to log a minimum number of daily calories in MyFitnessPal and to step on the BodyTrace cellular scale at least twice per week. In a 2×2 design, participants were randomized into 4 groups to receive financial incentives for the following: (group 1) weekly weight loss and dietary self-monitoring, (group 2) dietary self-monitoring only, (group 3) weekly weight loss only, or (group 4) no financial incentives. Diet and weight data from the devices were obtained through application programming interfaces. Each week, we applied algorithms to participants' data to determine whether they qualified for a monetary incentive (groups 1-3). A text message notified these participants of whether they met weight loss and/or self-monitoring requirements to earn an incentive and the amount they earned or would have earned. The money was uploaded to a debit card.ResultsOur custom-engineered software platform analyzed data from multiple sources, collated and processed the data to send appropriate text messages automatically, and informed study staff of the appropriate incentives. We present lessons learned from the development of the software system and challenges encountered with technology, data transmission, and participants (eg, lost connections or delayed communication).ConclusionsWith consistent and constant validation checks and a robust beta test run, the process of analyzing data and determining eligibility for weekly incentives can be mostly automated. We were able to accomplish this project within an academic health system, which required significant security and privacy safeguards. Our success demonstrates how this methodology of automated feedback loops can provide health interventions via mobile technology.Trial registrationClinicalTrials.gov NCT02691260; https://clinicaltrials.gov/ct2/show/NCT02691260.

Dataset Information

Using Mobile Phones to Collect Patient Data: Lessons Learned From the SIMPle Study.

Publications

Using Mobile Phones to Collect Patient Data: Lessons Learned From the SIMPle Study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets