MétaCan
Menu
Back to cohort
Record W3095540521 · doi:10.2196/19093

Beyond Known Barriers—Assessing Physician Perspectives and Attitudes Toward Introducing Open Health Records in Germany: Qualitative Study

2020· article· en· W3095540521 on OpenAlexvenueno aff
Julia Müller, Charlotte Ullrich, Regina Poß-Doering

Bibliographic record

VenueJournal of Participatory Medicine · 2020
Typearticle
Languageen
FieldHealth Professions
TopicElectronic Health Records Systems
Canadian institutionsnot available
Fundersnot available
KeywordsThematic analysisMedical recordWorkloadGermanQualitative researchHealth careHealth literacyMedical educationNursingPsychologyMedicineFamily medicinePolitical scienceSociology

Abstract

fetched live from OpenAlex

BACKGROUND: Giving patients access to their medical records (ie, open health records) can support doctor-patient communication and patient-centered care and can improve quality of care, patients' health literacy, self-care, and treatment adherence. In Germany, patients are entitled by law to have access to their medical records. However, in practice doing so remains an exception in Germany. So far, research has been focused on organizational implementation barriers. Little is known about physicians' attitudes and perspectives toward opening records in German primary care. OBJECTIVE: This qualitative study aims to provide a better understanding of physicians' attitudes toward opening records in primary care in Germany. To expand the knowledge base that future implementation programs could draw from, this study focuses on professional self-conception as an influencing factor regarding the approval for open health records. Perspectives of practicing primary care physicians and advanced medical students were explored. METHODS: Data were collected through semistructured guide-based interviews with general practitioners (GPs) and advanced medical students. Participants were asked to share their perspectives on open health records in German general practices, as well as perceived implications, their expectations for future medical records, and the conditions for a potential implementation. Data were pseudonymized, audiotaped, and transcribed verbatim. Themes and subthemes were identified through thematic analysis. RESULTS: Barriers and potential advantages were reported by 7 GPs and 7 medical students (N=14). The following barriers were identified: (1) data security, (2) increased workload, (3) costs, (4) the patients' limited capabilities, and (5) the physicians' concerns. The following advantages were reported: (1) patient education and empowerment, (2) positive impact on the practice, and (3) improved quality of care. GPs' professional self-conception influenced their approval for open records: GPs considered their aspiration for professional autonomy and freedom from external control to be threatened and their knowledge-based support of patients to be obstructed by open records. Medical students emphasized the chance to achieve shared decision making through open records and expected the implementation to be realistic in the near future. GPs were more hesitant and voiced a strong resistance toward sharing notes on perceptions that go beyond clinical data. Reliable technical conditions, the participants' consent, and a joint development of the implementation project to meet the GPs' interests were requested. CONCLUSIONS: Open health record concepts can be seen as a chance to increase transparency in health care. For a potential future implementation in Germany, thorough consideration regarding the compatibility of GPs' professional values would be warranted. However, the medical students' positive attitude provides an optimistic perspective. Further research and a broad support from decision makers would be crucial to establish open records in Germany.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.013
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0050.006
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.286
GPT teacher head0.584
Teacher spread0.298 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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

Citations8
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Participatory MedicineSame topicElectronic Health Records SystemsFrench-language works237,207