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Record W2594778084 · doi:10.2196/resprot.6314

A Personal Electronic Health Record: Study Protocol of a Feasibility Study on Implementation in a Real-World Health Care Setting

2017· article· en· W2594778084 on OpenAlexvenueno aff
Dominik Ose, Aline Kunz, Sabrina Pohlmann, Helene Hofmann, Markus Qreini, Johannes Krisam, Lorenz Uhlmann, Christian Jacke, Eva C. Winkler, Hans Joachim Salize, Joachim Szécsényi

Bibliographic record

VenueJMIR Research Protocols · 2017
Typearticle
Languageen
FieldHealth Professions
TopicElectronic Health Records Systems
Canadian institutionsnot available
FundersBundesministerium für Bildung und Forschung
KeywordsHealth careElectronic health recordEmpowermentHealth information technologyHealth information exchangeHealth informaticsProtocol (science)NursingChristian ministryeHealthPatient portalMedicineHealth informationAlternative medicinePublic healthPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: A significant potential for patient empowerment is seen in concepts aiming to give patients access to their personal health information (PHI) and to share this PHI across different care settings and health systems. Personal health records (PHRs) and the availability of information through health information exchanges are considered to be key components of effective and efficient health care. With tethered PHRs, as often used in the United States, patients' opportunities to manage their PHI are strongly restricted. Therefore, within the INFOPAT (information technology for patient oriented care) project (2012-2016) in Germany, funded by the Federal Ministry of Education and Research (BMBF), the development of a patient-controlled "personal electronic health record" (PEPA) was based on user requirements right from the beginning. OBJECTIVE: The overall objective of the study is to implement and evaluate a PEPA prototype for patients with colorectal cancer who are treated at the National Center for Tumor Diseases in Heidelberg. To achieve this aim, this study has 2 parts: a pre-implementation study (phase 1) and an implementation study (phase 2). The pre-implementation study will include a usability evaluation of the PEPA approach and the consideration of organizational preconditions for the implementation. With the implementation study, we will evaluate the process of implementation (eg, barriers or facilitators), the need for organizational change (eg, processes of communication), and the impact on outcomes (eg, self-efficacy, involvement in care). METHODS: The pre-implementation study is based on a mixed methods approach and comprises qualitative and quantitative element according to our research aim. We will use a think-aloud method for the usability analysis. Additionally, participants will be asked to evaluate their overall satisfaction based on a standardized questionnaire, the System Usability Scale. For the analysis of preconditions, we will conduct semistructured personal interviews with, for example, patients, medical assistants, and physicians. Within the implementation study the outcome evaluation is planned as a prospective, 3-month, open-label "before and after" trial. Additionally, for the analysis of processes and the need for organizational change, we will conduct interviews with the participants (eg, patients, general practitioners, physicians) of the before and after trial. RESULTS: This project is part of the INFOPAT project, which is funded (2012-2016) by the Federal Ministry of Education and Research (BMBF). The enrolment was completed in July 2016. Data analysis is currently under way and the first results are expected to be submitted for publication at end of 2017. CONCLUSIONS: Existing approaches of PHRs aim to give patients access to their treatment data. With the PEPA approach and this study, we go a step further: patients have access to their PHI and they can give other persons (eg, their general practitioner) access. With this approach, new possibilities for professional collaboration and the engagement of patients can arise.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.040
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.397
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0400.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.456
GPT teacher head0.730
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations24
Published2017
Admission routes1
Has abstractyes

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