Dataset Information

The Added Value of Log File Analyses of the Use of a Personal Health Record for Patients With Type 2 Diabetes Mellitus: Preliminary Results.

ABSTRACT: The electronic personal health record (PHR) is a promising technology for improving the quality of chronic disease management. Until now, evaluations of such systems have provided only little insight into why a particular outcome occurred. The aim of this study is to gain insight into the navigation process (what functionalities are used, and in what sequence) of e-Vita, a PHR for patients with type 2 diabetes mellitus (T2DM), to increase the efficiency of the system and improve the long-term adherence. Log data of the first visits in the first 6 weeks after the release of a renewed version of e-Vita were analyzed to identify the usage patterns that emerge when users explore a new application. After receiving the invitation, 28% of all registered users visited e-Vita. In total, 70 unique usage patterns could be identified. When users visited the education service first, 93% of all users ended their session. Most users visited either 1 or 5 or more services during their first session, but the distribution of the routes was diffuse. In conclusion, log file analyses can provide valuable prompts for improving the system design of a PHR. In this way, the match between the system and its users and the long-term adherence has the potential to increase.

SUBMITTER: Sieverink F

PROVIDER: S-EPMC4455425 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

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The Added Value of Log File Analyses of the Use of a Personal Health Record for Patients With Type 2 Diabetes Mellitus: Preliminary Results.

Sieverink Floor F Kelders Saskia M SM Braakman-Jansen Louise M A LM van Gemert-Pijnen Julia E W C JE

Journal of diabetes science and technology 20140304 2

The electronic personal health record (PHR) is a promising technology for improving the quality of chronic disease management. Until now, evaluations of such systems have provided only little insight into why a particular outcome occurred. The aim of this study is to gain insight into the navigation process (what functionalities are used, and in what sequence) of e-Vita, a PHR for patients with type 2 diabetes mellitus (T2DM), to increase the efficiency of the system and improve the long-term ad ...[more]

PMID: 24876574

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Project description:BackgroundWeb-based outpatient portals help patients engage in the management of their health by allowing them to access their medical information, schedule appointments, track their medications, and communicate with their physicians and care team members. Initial studies have shown that portal adoption positively affects health outcomes; however, early studies typically relied on survey data. Using data from health portal applications, we conducted systematic assessments of patients' use of an outpatient portal to examine how patients engage with the tool.ObjectiveThis study aimed to document the functionality of an outpatient portal in the context of outpatient care by mining portal usage data and to provide insights into how patients use this tool.MethodsUsing audit log files from the outpatient portal associated with the electronic health record system implemented at a large multihospital academic medical center, we investigated the behavioral traces of a study population of 2607 patients who used the portal between July 2015 and February 2019. Patient portal use was defined as having an active account and having accessed any portal function more than once during the study time frame.ResultsThrough our analysis of audit log file data of the number and type of user interactions, we developed a taxonomy of functions and actions and computed analytic metrics, including frequency and comprehensiveness of use. We additionally documented the computational steps required to diagnose artifactual data and arrive at valid usage metrics. Of the 2607 patients in our sample, 2511 were active users of the patients portal where the median number of sessions was 94 (IQR 207). Function use was comprehensive at the patient level, while each session was instead limited to the use of one specific function. Only 17.45% (78,787/451,762) of the sessions were linked to activities involving more than one portal function.ConclusionsIn discussing the full methodological choices made in our analysis, we hope to promote the replicability of our study at other institutions and contribute to the establishment of best practices that can facilitate the adoption of behavioral metrics that enable the measurement of patient engagement based on the outpatient portal use.

Project description:BACKGROUND:An increasing number of software companies work according to the agile software development method, which is difficult to integrate with user-centered design (UCD) practices. Log file analysis may provide opportunities for integrating UCD practices in the agile process. However, research within health care information technology mostly has a theoretical approach and is often focused on the researcher's interpretation of log file analyses. OBJECTIVE:We aimed to propose a systematic approach to log file analysis in this study and present this to developers to explore how they react and interpret this approach in the context of a real-world health care information system, in an attempt to answer the following question: How may log file analyses contribute to increasing the match between the health care system and its users, within the agile development method, according to agile team members? METHODS:This study comprised 2 phases to answer the research question. In the first phase, log files were collected from a health care information system and subsequently analyzed (summarizing sequential patterns, heat mapping, and clustering). In the second phase, the results of these analyses are presented to agile professionals during a focus group interview. The interpretations of the agile professionals are analyzed by open axial coding. RESULTS:Log file data of 17,924 user sessions and, in total, 176,678 activities were collected. We found that the Patient Timeline is mainly visited, with 23,707 (23,707/176,678; 13.42%) visits in total. The main unique user session occurred in 5.99% (1074/17,924) of all user sessions, and this comprised Insert Measurement Values for Patient and Patient Timeline, followed by the page Patient Settings and, finally, Patient Treatment Plan. In the heat map, we found that users often navigated to the pages Insert Measurement Values and Load Messages Collaborate. Finally, in the cluster analysis, we found 5 clusters, namely, the Information-seeking cluster, the Collaborative cluster, the Mixed cluster, the Administrative cluster, and the Patient-oriented cluster. We found that the interpretations of these results by agile professionals are related to stating hypotheses (n=34), comparing paths (n=31), benchmarking (n=22), and prioritizing (n=17). CONCLUSIONS:We found that analyzing log files provides agile professionals valuable insights into users' behavior. Therefore, we argue that log file analyses should be used within agile development to inform professionals about users' behavior. In this way, further UCD research can be informed by these results, making the methods less labor intensive. Moreover, we argue that these translations to an approach for further UCD research will be carried out by UCD specialists, as they are able to infer which goals the user had when going through these paths when looking at the log data.

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Project description:A model based on a specific phantom, called QuAArC, has been designed for the evaluation of planning and verification systems of complex radiotherapy treatments, such as volumetric modulated arc therapy (VMAT). This model uses the high accuracy provided by the Monte Carlo (MC) simulation of log files and allows the experimental feedback from the high spatial resolution of films hosted in QuAArC. This cylindrical phantom was specifically designed to host films rolled at different radial distances able to take into account the entrance fluence and the 3D dose distribution. Ionization chamber measurements are also included in the feedback process for absolute dose considerations. In this way, automated MC simulation of treatment log files is implemented to calculate the actual delivery geometries, while the monitor units are experimentally adjusted to reconstruct the dose-volume histogram (DVH) on the patient CT. Prostate and head and neck clinical cases, previously planned with Monaco and Pinnacle treatment planning systems and verified with two different commercial systems (Delta4 and COMPASS), were selected in order to test operational feasibility of the proposed model. The proper operation of the feedback procedure was proved through the achieved high agreement between reconstructed dose distributions and the film measurements (global gamma passing rates > 90% for the 2%/2 mm criteria). The necessary discretization level of the log file for dose calculation and the potential mismatching between calculated control points and detection grid in the verification process were discussed. Besides the effect of dose calculation accuracy of the analytic algorithm implemented in treatment planning systems for a dynamic technique, it was discussed the importance of the detection density level and its location in VMAT specific phantom to obtain a more reliable DVH in the patient CT. The proposed model also showed enough robustness and efficiency to be considered as a pre-treatment VMAT verification system.

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Dataset Information

The Added Value of Log File Analyses of the Use of a Personal Health Record for Patients With Type 2 Diabetes Mellitus: Preliminary Results.

Publications

The Added Value of Log File Analyses of the Use of a Personal Health Record for Patients With Type 2 Diabetes Mellitus: Preliminary Results.

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