REVIEW AND ANALYSIS OF INDIAN ELECTRONIC HEALTH RECORD (EHR) SYSTEM ALONG WITH DENMARK, CANADA AND AUSTRALIA
Notice bibliographique
Résumé
Cloud-based information technology has a major impact on the improvement of service quality in many sectors, quality of service in health sectors being one of the most important out of these. In the heath sector as well, information technology may play a crucial role to keep the patient record in the digital version to improve the quality of health services, more importantly, emergency health services. Cloud-based secure storage of patients' records and appropriate authentication mechanism not only saves time for access to data, but less storage space will be required removing data redundancy and ambiguities. The cost of cloud-based centrally controlled health records will also be highly cost-effective relatively, as compared to conventional paper-based records or offline digital records. Electronic Health Record (EHR) is the standard terminology used for clouds based storage of health data. So EHR may not only provide easy access to data globally but also access mechanisms may be effectively controlled as per policies drawn by the governments. Electronic Health Records controlled and authenticated by government policies is also reliable for other health providers like medical specialists, physicians, nurses, and doctors, etc. EHR is an electronic record of a patient that reports on an individual's lifetime health. EHR is used to enhance the facility of the health services for a patient by using cloud-based computing applications. So, EHR provides all the information in an integrated care system inexpensively and flexibly along with the security of data that gives the authentic data for a patient. This paper aims to compare and analyze the health architecture of EHR of INDIA with that of to follow Denmark, Canada, and Australia. India is a country heavily populated and low per capita income and consequently, expenditure, has relatively behind in usage of digital technology in the fields of public services, particularly health services. Even on the part policy framework, India needs to improve. Only limited reference EHR guidelines have been framed by the government, however many developed countries including the ones mentioned in the analysis have already functional cloud-based EHR systems in place. The EHR policy framework proposed by the Indian government is also described in this paper. Analysis of policies, framework architecture and working functionality of EHR systems adopted by the mentioned countries may help in the effectively functional implementation of the EHR system in India as well.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».