A drug administration decision support system

Drug delivery is one of the most common clinical routines in hospitals, and is critical to patients' health and recovery. It includes a decision making process in which a medical doctor decides the amount (dose) and frequency (dose interval) on the basis of a set of available patients' feature data and the doctor's clinical experience (a priori adaptation). This process can be computerized in order to make the prescription procedure in a fast, objective, inexpensive, non-invasive and accurate way. This paper proposes a Drug Administration Decision Support System (DADSS) to help clinicians/patients with the initial dose computing. The system is based on a Support Vector Machine (SVM) algorithm for estimation of the potential drug concentration in the blood of a patient, from which a best combination of dose and dose interval is selected at the level of a DSS. The addition of the RANdom SAmple Consensus (RANSAC) technique enhances the prediction accuracy by selecting inliers for SVM modeling. Experiments are performed for the drug imatinib case study which shows more than 40% improvement in the prediction accuracy compared with previous works. An important extension to the patient features' data is also proposed in this paper.

The EPAGE internet guideline as a decision support tool for determining the appropriateness of colonoscopy

RÉSUMÉ Contexte : Peu d'études ont examiné la façon dont les médecins appréhendent les guidelines, et encore moins celle dont ils perçoivent de tels guidelines disponibles sur Internet. Cette étude évalue l'acceptation par les médecins d'un guideline électronique portant sur l'adéquation de la colonoscopie. Méthode : Des gastroentérologues participant à une étude observationnelle internationale ont consulté un guideline électronique pour une série consécutive de patients adressés pour une colonoscopie. Le guideline a été élaboré par le Panel Européen sur l'Adéquation de l'Endoscopie Gastro-intestinale (EPAGE en version anglaise), utilisant une méthode validée (RAND). Les opinions des médecins sur le guideline, sur le site Internet et sur les perspectives d'utilisation ont été recueillies au moyen de questionnaires. Résultats : 289 patients ont été inclus dans l'étude. Le temps moyen pour consulter le site Internet a été de 1.8 min et 86% des médecins l'ont considéré comme simple à utiliser. Les recommandations ont été facilement localisées pour 82% des patients et les médecins étaient d'accord avec l'adéquation de la colonoscopie dans 86% des cas. Selon les critères EPAGE, la colonoscopie était appropriée, incertaine et inappropriée, respectivement chez 59, 28 et 13% des patients. Conclusions : Le guideline EPAGE a été considéré comme acceptable et simple à utiliser. L'utilisation, l'utilité et la pertinence du site Internet a été jugée comme acceptable. Son utilisation effective dépendra cependant de la levée de certains obstacles au niveau organisationnel et culturel.

Decision-support tools to manage drug incompatibilities: evaluation by nurses

Introduction Preventing drug incompatibilities has a high impact onthe safety of drug therapy. Although there are no internationalguidelines to manage drug incompatibilities, different decision-supporttools such as handbooks, cross-tables and databases are available.In a previous study, two decision-support tools have been pre-selectedby pharmacists as fitting nurses' needs on the wards1. The objective ofthis study was to have these both tools evaluated by nurses todetermine which would be the most suitable for their daily practice.Materials & Methods Evaluated tools were:1. Cross-table of drug pairs (http://files.chuv.ch/internet-docs/pha/medicaments/pha_phatab_compatibilitessip.pdf)2. Colour-table (a colour for each drug according to the pH: red =acid; blue = basic; yellow = neutral; black = to be infused alone)2Tools were assessed by 48 nurses in 5 units (PICU, adult andgeriatric intensive care, surgery, onco-hematology) using a standardizedform1. The scientific accuracy of the tools was evaluated bydetermining the compatibility of five drugs pairs (rate of correctanswers according to the Trissel's Handbook on Injectable Drugs,chi-square test). Their ergonomics, design, reliability and applicabilitywere estimated using visual analogue scales (VAS 0-10; 0 =null, 10 = excellent). Results are expressed as the median and interquartilerange (IQR) for 25% and 75% (Wilcoxon rank sum test).Results The rate of correct answers was above 90% for both tools(cross-table 96.2% vs colour-table 92.5%, p[0.05).The ergonomics and the applicability were higher for the crosstable[7.1 (IQR25 4.0, IQR75 8.0) vs 5.0 (IQR25 2.7, IQR75 7.0), p =0.025 resp. 8.3 (IQR25 7.4, IQR75 9.2) vs 7.6 (IQR25 5.9, IQR75 8.8)p = 0.047].The design of the colour-table was judged better [4.6 (IQR25 2.9,IQR75 7.1) vs 7.1 (IQR25 5.4, IQR75 8.4) p = 0.002].No difference was observed in terms of reliability [7.3 (IQR25 6.5,IQR75 8.4) vs 6.7 (IQR25 5.0, IQR758.6) p[0.05].The cross-table was globally preferred by 65% of the nurses (27%colour-table, 8% undetermined) and 68% would like to have thisdecision-support tool available for their daily practice.Discussion & Conclusion Both tools showed the same accuracy toassess drug compatibility. In terms of ergonomics and applicabilitythe cross-table was better than the colour-table, and was preferred bythe nurses for their daily practice. The cross-table will be implementedin our hospital as decision-support tool to help nurses tomanage drug incompatibilities.

Prototype of a web-based participative decision support platform in natural hazards and risk management

This paper presents the current state and development of a prototype web-GIS (Geographic Information System) decision support platform intended for application in natural hazards and risk management, mainly for floods and landslides. This web platform uses open-source geospatial software and technologies, particularly the Boundless (formerly OpenGeo) framework and its client side software development kit (SDK). The main purpose of the platform is to assist the experts and stakeholders in the decision-making process for evaluation and selection of different risk management strategies through an interactive participation approach, integrating web-GIS interface with decision support tool based on a compromise programming approach. The access rights and functionality of the platform are varied depending on the roles and responsibilities of stakeholders in managing the risk. The application of the prototype platform is demonstrated based on an example case study site: Malborghetto Valbruna municipality of North-Eastern Italy where flash floods and landslides are frequent with major events having occurred in 2003. The preliminary feedback collected from the stakeholders in the region is discussed to understand the perspectives of stakeholders on the proposed prototype platform.

Epidémiologie clinique: définitions, utilités et raisons pour un développement en Suisse. [Clinical epidemiology: definitions, uses and reasons for development in Switzerland].

Clinical epidemiology is the most currently used name for a comparatively new branch of medicine covering a certain number of activities related to the practice of clinical medicine, but using epidemiological techniques and methods. Clinical epidemiology has only just begun to be known in Europe, whereas units are being increasingly developed and expanded in North America, particularly within the clinical departments of hospitals. The methods it offers are valid for both practicing physicians and hospital doctors (or those being trained in hospitals) and serve the purpose of promoting a better quality medical service, especially where a more adequate evaluation of the effectiveness of diagnostic methods, therapy and prognosis in medicine is concerned. Clinical epidemiology proposes a methodology of medical reasoning and of decision-making, as well as techniques intended to facilitate the indispensable task of keeping up with advances in medical knowledge.

A prediction rule to identify low-risk patients with pulmonary embolism.

BACKGROUND: A simple prognostic model could help identify patients with pulmonary embolism who are at low risk of death and are candidates for outpatient treatment. METHODS: We randomly allocated 15,531 retrospectively identified inpatients who had a discharge diagnosis of pulmonary embolism from 186 Pennsylvania hospitals to derivation (67%) and internal validation (33%) samples. We derived our rule to predict 30-day mortality using classification tree analysis and patient data routinely available at initial examination as potential predictor variables. We used data from a European prospective study to externally validate the rule among 221 inpatients with pulmonary embolism. We determined mortality and nonfatal adverse medical outcomes across derivation and validation samples. RESULTS: Our final model consisted of 10 patient factors (age > or = 70 years; history of cancer, heart failure, chronic lung disease, chronic renal disease, and cerebrovascular disease; and clinical variables of pulse rate > or = 110 beats/min, systolic blood pressure < 100 mm Hg, altered mental status, and arterial oxygen saturation < 90%). Patients with none of these factors were defined as low risk. The 30-day mortality rates for low-risk patients were 0.6%, 1.5%, and 0% in the derivation, internal validation, and external validation samples, respectively. The rates of nonfatal adverse medical outcomes were less than 1% among low-risk patients across all study samples. CONCLUSIONS: This simple prediction rule accurately identifies patients with pulmonary embolism who are at low risk of short-term mortality and other adverse medical outcomes. Prospective validation of this rule is important before its implementation as a decision aid for outpatient treatment.

A clinical prognostic model for the identification of low-risk patients with acute symptomatic pulmonary embolism and active cancer.

BACKGROUND: Physicians need a specific risk-stratification tool to facilitate safe and cost-effective approaches to the management of patients with cancer and acute pulmonary embolism (PE). The objective of this study was to develop a simple risk score for predicting 30-day mortality in patients with PE and cancer by using measures readily obtained at the time of PE diagnosis. METHODS: Investigators randomly allocated 1,556 consecutive patients with cancer and acute PE from the international multicenter Registro Informatizado de la Enfermedad TromboEmbólica to derivation (67%) and internal validation (33%) samples. The external validation cohort for this study consisted of 261 patients with cancer and acute PE. Investigators compared 30-day all-cause mortality and nonfatal adverse medical outcomes across the derivation and two validation samples. RESULTS: In the derivation sample, multivariable analyses produced the risk score, which contained six variables: age > 80 years, heart rate ≥ 110/min, systolic BP < 100 mm Hg, body weight < 60 kg, recent immobility, and presence of metastases. In the internal validation cohort (n = 508), the 22.2% of patients (113 of 508) classified as low risk by the prognostic model had a 30-day mortality of 4.4% (95% CI, 0.6%-8.2%) compared with 29.9% (95% CI, 25.4%-34.4%) in the high-risk group. In the external validation cohort, the 18% of patients (47 of 261) classified as low risk by the prognostic model had a 30-day mortality of 0%, compared with 19.6% (95% CI, 14.3%-25.0%) in the high-risk group. CONCLUSIONS: The developed clinical prediction rule accurately identifies low-risk patients with cancer and acute PE.

Développement, implémentation et utilisation pratique d'un score diagnostique [Development, implementation and practical use of a diagnostic score].

In recent years many clinical prediction rules (CPR) have been developed. Before a CPR can be used in clinical practice, different methodical steps are necessary, from the development of the score, the internal and external validation to the impact study. Before using a CPR in daily practice family doctors have to verify how the rules have been developed and whether this has been done in a population similar to the population in which they would use them. The aim of this paper is to describe the development of a CPR, and to discuss advantages and risks related to the use of CPR in order to help family doctors in their choice of scores for use in their daily practice.

Ruling out coronary heart disease in primary care: external validation of a clinical prediction rule.

BACKGROUND: The Marburg Heart Score (MHS) aims to assist GPs in safely ruling out coronary heart disease (CHD) in patients presenting with chest pain, and to guide management decisions. AIM: To investigate the diagnostic accuracy of the MHS in an independent sample and to evaluate the generalisability to new patients. DESIGN AND SETTING: Cross-sectional diagnostic study with delayed-type reference standard in general practice in Hesse, Germany. METHOD: Fifty-six German GPs recruited 844 males and females aged ≥ 35 years, presenting between July 2009 and February 2010 with chest pain. Baseline data included the items of the MHS. Data on the subsequent course of chest pain, investigations, hospitalisations, and medication were collected over 6 months and were reviewed by an independent expert panel. CHD was the reference condition. Measures of diagnostic accuracy included the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, likelihood ratios, and predictive values. RESULTS: The AUC was 0.84 (95% confidence interval [CI] = 0.80 to 0.88). For a cut-off value of 3, the MHS showed a sensitivity of 89.1% (95% CI = 81.1% to 94.0%), a specificity of 63.5% (95% CI = 60.0% to 66.9%), a positive predictive value of 23.3% (95% CI = 19.2% to 28.0%), and a negative predictive value of 97.9% (95% CI = 96.2% to 98.9%). CONCLUSION: Considering the diagnostic accuracy of the MHS, its generalisability, and ease of application, its use in clinical practice is recommended.