Personal Health Record System Assists Men with Prostate Cancer with Access to Their Electronic Medical Records and eHealth Tools
Notice bibliographique
Résumé
Topic Areas: New models for healthcare delivery, next generation electronic health records. Hypotheses: Personal Health Records (PHR) and the Internet are effective means of providing prostate cancer (PC) patients access to their electronic health records (EHR), health information and e-health tools in a secure and private manner and will assist them to meet their health information needs prior to, during and following prostate cancer treatment. Objectives: Develop and test a PHR accessible over the Internet for PC patients (called PROVIDER). Determine the usage pattern and patient satisfaction with PROVIDER. Background: PC is a disease that fits the chronic disease model in many respects where there can be a role for self-care and self-management. Cancer patients can be highly information seeking and desire access to their medical records. Providing access to medical records in the form of electronic health records (EHR) through the use of Personal Health Records (PHR) and Internet is an innovative means to meet this need in the 21st century. Methods: This was a qualitative, exploratory-type research study. After informed written consent, 22 men with a diagnosis of PC registered at the BC Cancer Agency (BCCA) in Victoria, British Columbia, Canada were given secure and private access to PROVIDER where they could access their up-to-date EHR and e-health tools. E-health tools consisted of decision support, educational, laboratory test monitoring aids and other features. Study patients were given a tutorial prior to PROVIDER use. Patients were given access to PROVIDER for 6 months. They were asked to keep a diary or log of all communications and correspondence with healthcare providers at BCCA and were interviewed at end of 6 months to share their opinions on usability, satisfaction, concerns with PROVIDER. Website activity was electronically recorded to assess usage patterns. Results: Median age of study patients was 64 years. Men were in the following phases of care when they were enrolled in the study: 19 percent initial diagnosis/work-up, 43 percent active treatment, 10 percent follow-up, 29 percent cancer recurrence. The mean number of logins per month was 3.4. Usage was most frequent during the first two months of access but was maintained at a lower rate throughout remainder of the 6 months of access. Seventy seven percent felt their privacy and security was preserved. Twenty nine percent encountered some minor difficulties using PROVIDER. The two most commonly accessed EHR were laboratory tests results and transcribed doctor notes. Ninety-four percent were satisfied to very satisfied with access to their EHR. Sixty-five percent of men said that PHR helped answer all their questions. Seventy-seven percent felt their privacy and confidentiality were preserved. Sixty-five percent felt that using PROVIDER helped them communicate better with their physicians. Eighty-three percent of patients found new and useful information using PROVIDER that they would not have received by talking to their healthcare providers. Discussion: This study demonstrates that men in various phases of care were very satisfied with PHR (i.e. PROVIDER) and would continue to use PROVIDER if it were available. The results of this study strongly suggests that PHR may assist cancer patients with timely access to their health information and medical records, and assist with communication with healthcare providers, knowledge generation, thus empowering patients to take a more active role in their own care.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».