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Abstract: Introduction: Our aim was to develop a reference functional model for electric health record systems (RFM). Such a RFM is built from functions using functional descriptive elements (FDEs) and represents the static relationships between them. This paper presents a new format for describing electric health record (EHR) system functions. Methods: Questionnaire and field interview survey was conducted in five hospitals in Japan and one in the USA, to collect data on EHR system functions. Based on survey results, a reference functional list (RFL) was created, in which each EHR system function was listed and divided into 13 FDE types. By analyzing the RFL, we built the meta-functional model and the functional model using UML class diagrams. The former defines language for expressing the functional model, while the latter represents functions, FDEs and their static relationships. Results: A total of 385 functions were represented in the RFL. Six patterns were found for the relationships between functions. The meta-functional model was created as a new format for describing functions. Examples of the functional model, which included the six patterns in the relationships between functions and 11 verbs, were created. Discussions: We present the meta-functional model, which is a new description format for the functional structure and relationships. Although a more detailed description is required to apply the RFM to the semiautomatic generation of functional specification documents, our RFM can visualize functional structures and functional relationships, classify functions using multiple axes and identify the similarities and differences between functions. The RFM will promote not only the standardization of EHR systems, but also communications between system developers and healthcare providers in the EHR system-design processes. [Copyright &y& Elsevier]

Summary: Administering and monitoring therapy is crucial to the battle against HIV/AIDS in sub-Saharan Africa. Electronic medical records (EMRs) can aid in documenting care, monitoring drug adherence and response to therapy, and providing data for quality improvement and research. Faculty at Moi University in Kenya and Indiana and University in the USA opened adult and pediatric HIV clinics in a national referral hospital, a district hospital, and six rural health centers in western Kenya using a newly developed EMR to support comprehensive outpatient HIV/AIDS care. Demographic, clinical, and HIV risk data, diagnostic test results, and treatment information are recorded on paper encounter forms and hand-entered into a central database that prints summary flowsheets and reminders for appropriate testing and treatment. There are separate modules for monitoring the Antenatal Clinic and Pharmacy. The EMR was designed with input from clinicians who understand the local community and constraints of providing care in resource poor settings. To date, the EMR contains more than 30,000 visit records for more than 4000 patients, almost half taking antiretroviral drugs. We describe the development and structure of this EMR and plans for future development that include wireless connections, tablet computers, and migration to a Web-based platform. [Copyright &y& Elsevier]

Objective: A deficit is suspected in the manual documentation of adverse events in quality assurance programs in anesthesiology. In order to verify and quantify this, we retrospectively compared the incidence of manually recorded perioperative adverse events with automatically detected events.Methods: In 1998, data of all anesthetic procedures, including the data set for quality assurance of the German Society of Anaesthesiology and Intensive Care Medicine (DGAI), was recorded online with the Anesthesia Information Management System (AIMS) NarkoData4 (Imeso GmbH). SQL (Structured Query Language) queries based on medical data were defined for the automatic detection of common adverse events. The definition of the SQL statements had to be in accordance with the definition of the DGAI for perioperative adverse events: A potentially harmful change of parameters led to therapeutic interventions by an anesthesiologist.Results: During 16,019 surgical procedures, anesthesiologists recorded 911 (5.7%) adverse events manually, whereas 2966 (18.7%) events from the same database were detected automatically. With the exception of hypoxemia, the incidence of automatically detected events was considerably higher than that of manually recorded events. Fourteen and a half percent (435) of all automatically detected events were recorded manually.Conclusion: Using automatic detection, we were able to prove a considerable deficit in the documentation of adverse events according to the guidelines of the German quality assurance program in anesthesiology. Based on the data from manual recording, the results of the quality assurance of our department match those of other comparable German departments. Thus, we are of the opinion that manual incident reporting seriously underestimates the true occurrence rate of incidents. This brings into question the validity of quality assurance comparisons based on manually recorded data. [ABSTRACT FROM AUTHOR]

Background: The Royal College of General Practitioners Research and Surveillance Centre comprises more than 150 general practices, with a combined population of more than 1.5 million, contributing to UK and European public health surveillance and research. Objective: The aim of this paper was to report gender differences in the presentation of infectious and respiratory conditions in children and young adults. Methods: Disease incidence data were used to test the hypothesis that boys up to puberty present more with lower respiratory tract infection (LRTI) and asthma. Incidence rates were reported for infectious conditions in children and young adults by gender. We controlled for ethnicity, deprivation, and consultation rates. We report odds ratios (OR) with 95% CI, P values, and probability of presenting. Results: Boys presented more with LRTI, largely due to acute bronchitis. The OR of males consulting was greater across the youngest 3 age bands (OR 1.59, 95% CI 1.35-1.87; OR 1.13, 95% CI 1.05-1.21; OR 1.20, 95% CI 1.09-1.32). Allergic rhinitis and asthma had a higher OR of presenting in boys aged 5 to 14 years (OR 1.52, 95% CI 1.37-1.68; OR 1.31, 95% CI 1.17-1.48). Upper respiratory tract infection (URTI) and urinary tract infection (UTI) had lower odds of presenting in boys, especially those older than 15 years. The probability of presenting showed different patterns for LRTI, URTI, and atopic conditions. Conclusions: Boys younger than 15 years have greater odds of presenting with LRTI and atopic conditions, whereas girls may present more with URTI and UTI. These differences may provide insights into disease mechanisms and for health service planning. [ABSTRACT FROM AUTHOR]