DEVELOPMENT MODEL OF DIGITAL-BASED DENTAL HEALTH RECORDING AND REPORTING SERVICE SYSTEM IN PUBLIC HEALT CENTER

The Puskesmas Information Reporting System (SIP) has been in since 1981. In its implementation, SIP was still limited to data which was the result of interactions between the community and health facilities. Methods used Research and Development (RD). Collecting data by interview, observation, and documentation. The sample contained sample I amounted were 6 people, sample II were 25 people, and sample III were 16 people. Sampling technique with non probability sampling. Data analyswas used univariate and bivariate analyswas. Result that designed and built after being tested by experts, it was feasible to apply the Digital-Based Dental Health Recording and Reporting Service System Development Model. The Development Model of the Digital-Based Dental Health Recording and Reporting Service System after being tested has been proven to be relevant/suitable for use in the implementation of the digital-based dental health recording and reporting service system at the Puskesmas in Boyolali Regency. The Development Model of the Digital-Based Dental Health Recording and Reporting Service System has effective for the substance of the application system and improves the quality of the measurement before and after the development of a dental health recording and reporting service system based at the Puskesmas in Boyolali District with p value = 0.001. Conclusion that Development Model of the Digital-Based Dental Health Recording and Reporting Service System has effective for the substance of the application system and improves the quality dental health recording and reporting service system based at the Puskesmas

Achieving data completeness in electronic medical records: A conceptual model and hypotheses development.

This paper aims at proposing a conceptual model of achieving data completeness in electronic medical records (EMR). For this to happen, firstly, we draw on the model of factors influencing data quality management to construct our conceptual model. Secondly, we develop hypotheses of relationships between influencing factors for data completeness and mediators for achieving data completeness in EMR based on the literature. Our conceptual model extends the prior model for factors influencing data quality management by adding a new factor and exploring the relationships between the influencing factors within the context of data completeness in EMR. The proposed conceptual model and the presented hypotheses once empirically validated will be the basis for the development of tools and techniques for achieving data completeness in EMR.N

The effects of an electronic medical record on the completeness of documentation in the anesthesia record

OBJECTIVES: The purpose of this study is to evaluate the completeness of anesthesia recording before and after the introduction of an electronic anesthesia record. METHODS: The study was conducted in a Korean teaching hospital where the EMR was implemented in October 2008. One hundred paper anesthesia records from July to September 2008 and 150 electronic anesthesia records during the same period in 2009 were randomly sampled. Thirty-four essential items were selected out of all the anesthesia items and grouped into automatically transferred items and manual entry items. 1, .5 and 0 points were given for each item of complete entry, incomplete entry and no entry respectively. The completeness of documentation was defined as the sum of the scores. The influencing factors on the completeness of documentation were evaluated in total and by the groups. RESULTS: The average completeness score of the electronic anesthesia records was 3.15% higher than that of the paper records. A multiple regression model showed the type of the anesthesia record was a significant factor on the completeness of anesthesia records in all items (β=.98, p<.05) and automatically transferred items (β=.56, p<.01). The type of the anesthesia records had no influence on the completeness in manual entry items. CONCLUSIONS: The completeness of an anesthesia record was improved after the implementation of the electronic anesthesia record. The reuse of the data from the EMR was the main contributor to the improved completeness.ope

Contribution à la prévention des risques liés à l’anesthésie par la valorisation des informations hospitalières au sein d’un entrepôt de données

Introduction Hospital Information Systems (HIS) manage and register every day millions of data related to patient care: biological results, vital signs, drugs administrations, care process... These data are stored by operational applications provide remote access and a comprehensive picture of Electronic Health Record. These data may also be used to answer to others purposes as clinical research or public health, particularly when integrated in a data warehouse. Some studies highlighted a statistical link between the compliance of quality indicators related to anesthesia procedure and patient outcome during the hospital stay. In the University Hospital of Lille, the quality indicators, as well as the patient comorbidities during the post-operative period could be assessed with data collected by applications of the HIS. The main objective of the work is to integrate data collected by operational applications in order to realize clinical research studies.Methods First, the data quality of information registered by the operational applications is evaluated with methods … by the literature or developed in this work. Then, data quality problems highlighted by the evaluation are managed during the integration step of the ETL process. New data are computed and aggregated in order to dispose of indicators of quality of care. Finally, two studies bring out the usability of the system.Results Pertinent data from the HIS have been integrated in an anesthesia data warehouse. This system stores data about the hospital stay and interventions (drug administrations, vital signs …) since 2010. Aggregated data have been developed and used in two clinical research studies. The first study highlighted statistical link between the induction and patient outcome. The second study evaluated the compliance of quality indicators of ventilation and the impact on comorbity.Discussion The data warehouse and the cleaning and integration methods developed as part of this work allow performing statistical analysis on more than 200 000 interventions. This system can be implemented with other applications used in the CHRU of Lille but also with Anesthesia Information Management Systems used by other hospitals.Introduction Le Système d'Information Hospitalier (SIH) exploite et enregistre chaque jours des millions d'informations liées à la prise en charge des patients : résultats d'analyses biologiques, mesures de paramètres physiologiques, administrations de médicaments, parcours dans les unités de soins, etc... Ces données sont traitées par des applications opérationnelles dont l'objectif est d'assurer un accès distant et une vision complète du dossier médical des patients au personnel médical. Ces données sont maintenant aussi utilisées pour répondre à d'autres objectifs comme la recherche clinique ou la santé publique, en particulier en les intégrant dans un entrepôt de données. La principale difficulté de ce type de projet est d'exploiter des données dans un autre but que celui pour lequel elles ont été enregistrées. Plusieurs études ont mis en évidence un lien statistique entre le respect d'indicateurs de qualité de prise en charge de l'anesthésie et le devenir du patient au cours du séjour hospitalier. Au CHRU de Lille, ces indicateurs de qualité, ainsi que les comorbidités du patient lors de la période post-opératoire pourraient être calculés grâce aux données recueillies par plusieurs applications du SIH. L'objectif de se travail est d'intégrer les données enregistrées par ces applications opérationnelles afin de pouvoir réaliser des études de recherche clinique.Méthode Dans un premier temps, la qualité des données enregistrées dans les systèmes sources est évaluée grâce aux méthodes présentées par la littérature ou développées dans le cadre ce projet. Puis, les problèmes de qualité mis en évidence sont traités lors de la phase d'intégration dans l'entrepôt de données. De nouvelles données sont calculées et agrégées afin de proposer des indicateurs de qualité de prise en charge. Enfin, deux études de cas permettent de tester l'utilisation du système développée.Résultats Les données pertinentes des applications du SIH ont été intégrées au sein d'un entrepôt de données d'anesthésie. Celui-ci répertorie les informations liées aux séjours hospitaliers et aux interventions réalisées depuis 2010 (médicaments administrées, étapes de l'intervention, mesures, parcours dans les unités de soins, ...) enregistrées par les applications sources. Des données agrégées ont été calculées et ont permis de mener deux études recherche clinique. La première étude a permis de mettre en évidence un lien statistique entre l'hypotension liée à l'induction de l'anesthésie et le devenir du patient. Des facteurs prédictifs de cette hypotension ont également étaient établis. La seconde étude a évalué le respect d'indicateurs de ventilation du patient et l'impact sur les comorbidités du système respiratoire.Discussion The data warehouse L'entrepôt de données développé dans le cadre de ce travail, et les méthodes d'intégration et de nettoyage de données mises en places permettent de conduire des analyses statistiques rétrospectives sur plus de 200 000 interventions. Le système pourra être étendu à d'autres systèmes sources au sein du CHRU de Lille mais également aux feuilles d'anesthésie utilisées par d'autres structures de soins

Issues Concerning the Adoption and Usage of Electronic Medical Records in Ministry of Health Hospitals in Saudi Arabia

Abstract Background:There is a lack of research with regard to understanding the factors that motivate hospitals to proceed with implementing Electronic Medical Record Systems (EMR). The Health Information Management and System Society (HIMSS) outlines eight levels of EMR implementation from 0(no implementation) to 7(full use and implementation of the system). Some hospitals proceed to implement EMR and achieve a high level of implementation, while others stop at a certain level of EMR implementation or may even regress to lower levels. Aims and Methods: This research aimed to develop a framework to understand the motivational and de-motivational factors for proceeding with EMR implementationto uncover which hospitals have implemented EMR, to which levels, and how hospitals perceive EMR. In order to accomplish this,a mixed method design was adopted including a survey and case studies of a sample of hospitals in Eastern Saudi Arabia. The three case study sites were: a large hospital located in the capital city, a medium hospital located in a town, and a small hospital located in an isolated rural area. Results: The study found that 3 out of 29 hospitals in the area had implemented EMR. Contrary to expectations, the largest hospital located in the central city had regressed from level four of EMR implementation to level one, whereas the smallest hospital located in anisolated rural location achieved the highest EMR level. It was found that there were common factors that affected all the case study sites, whileother factors varied among them. Shared factors motivating sites to adopt EMR included a desire to escape from the manual system, whereas shared de-motivational factors included funding and technical problems. As these factors were common across sites at different levels of implementation, it is suggested that they do not sufficiently explain the variance in implementation level. It is argued that factors which varied between sites, however, may shed more light on the main motivators for implementation. For example, although there were technical problems across the sites,the way these technical problems were treated made the difference in terms of the success of the implementation. Additionally, top management commitment, users’ involvement in the EMR development and other factors varying between sites appeared to make the difference in the implementation’s success. Conclusion:The study concluded that all these common and varied factors affectedstaff attitudes toward the system. However, the site-related factors were perceived to be the main driver for the variance in the implementations. Since all site-related factors are controllable by top management, it is recommended that EMR implementation should be managed and supervised by a committee consisting of representatives from among clinical staff and IT staff. Based on this research, it is believed that such a committee is necessary for proceeding with an EMR implementation. However, there is no empirical evidence from this research about that. Therefore, it is advised that future research should find the rules, authorities and compositions of such committees that would make the committee effective