Search

Your search keyword '"MESH : Drug Prescriptions"' showing total 6 results
Start Over Descriptor "MESH : Drug Prescriptions" Topic business
6 results on '"MESH : Drug Prescriptions"'

1. European survey on principles of prudent antibiotic prescribing teaching in undergraduate students

Author

C. Pulcini, F. Wencker, N. Frimodt-Møller, W.V. Kern, D. Nathwani, J. Rodríguez-Baño, G.S. Simonsen, V. Vlahović-Palčevski, I.C. Gyssens, F. Jacobs, W. Peetermans, I. Francetić, N. Frimodt-Mǿller, N. Høiby, M. Kilian, F. Ader, C. Cazorla, M. Etienne, G. Fätkenheuer, M.W. Pletz, B. Salzberger, B. Cacopardo, M. Mikulska, C. Mussini, G. Orlando, S. Stefani, S.H. Lowe, J.L. Nouwen, J.E. Afset, K. Bergh, F. Müller, B. Carevic, O. Horvat, S. Jankovic, B. Beović, J.R. Gorisek, R. Canton, M.C. Fariñas, F. Gudiol, J.R. Paño Pardo, J. Rodríguez Baño, S. Harbarth, G. Zanetti, G. Barlow, N. Brown, B. Healy, Maladies chroniques, santé perçue, et processus d'adaptation. Approches épidémiologiques et psychologiques. ( APEMAC - EA 4360 ), Université Paris Descartes - Paris 5 ( UPD5 ) -Université de Lorraine ( UL ), Service des Maladies Infectieuses et Tropicales [CHRU Nancy], Centre Hospitalier Régional Universitaire de Nancy ( CHRU Nancy ), Radboud University Medical Center [Nijmegen], Canisius-Wilhelmina Hospital, Rigshospitalet [Copenhagen], Center for Infectious Diseases and Travel Medicine, University Hospital Freiburg, Ninewells Hospital and Medical School [Dundee], Infectious Diseases and Clinical Microbiology Unit, University Hospital Virgen Macarena, Universidad de Sevilla, UNN, University Hospital of North Norway, Tromsoe, Norvège, The Arctic University of Norway ( UiT ), University Hospital Rijeka, University of Rijeka, Hasselt University, Gyssens I, Jacobs F, Peetermans W, Francetić I, Vlahović-Palčevski V, Frimodt-Mǿller N, Høiby N, Kilian M, Ader F, Cazorla C, Etienne M, Pulcini C, Fätkenheuer G, Kern W, Pletz M, Salzberger B, Cacopardo B, Mikulska M, Mussini C, Orlando G, Stefani S, Gyssens I, Lowe S, Nouwen J, Afset J, Bergh K, Müller F, Simonsen G, Carevic B, Horvat O, Jankovic S, Beović B, Gorisek J, Canton R, Fariñas M, Gudiol F, Pardo J, Baño J, Harbarth S, Zanetti G, Barlow G, Brown N, Healy B, Nathwani D., Medical Microbiology & Infectious Diseases, Maladies chroniques, santé perçue, et processus d'adaptation (APEMAC), Université Paris Descartes - Paris 5 (UPD5)-Université de Lorraine (UL), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), Université Paris Diderot - Paris 7 (UPD7), The Arctic University of Norway (UiT), Copenhagen University Hospital, and Hasselt University (UHasselt)

Subjects
Pediatrics, Cross-sectional study, MESH : Drug Prescriptions, lnfectious Diseases and Global Health Radboud Institute for Molecular Life Sciences [Radboudumc 4], curriculum, MESH : Drug Utilization, law.invention, 0302 clinical medicine, MESH : Cross-Sectional Studies, MESH: Drug Prescriptions, law, Surveys and Questionnaires, Medicine, 030212 general & internal medicine, Duration (project management), MESH: Drug Utilization, MESH : Anti-Bacterial Agents, Schools, Medical, Antibiotic stewardship, 0303 health sciences, education, Clinical pharmacology, Schools, Education, Medical, [ SDV.SPEE ] Life Sciences [q-bio]/Santé publique et épidémiologie, General Medicine, BIOMEDICINA I ZDRAVSTVO. Temeljne medicinske znanosti. Farmakologija, antibiotic stewardship, medical student, medical school, questionnaire, 3. Good health, Anti-Bacterial Agents, Europe, Infectious Diseases, ntibiotic stewardship, MESH: Communicable Diseases, MESH : Surveys and Questionnaires, Microbiology (medical), medicine.medical_specialty, MESH : Schools, Medical, MESH: Education, Medical, MESH : Europe, BIOMEDICINE AND HEALTHCARE. Basic Medical Sciences. Pharmacology, Communicable Diseases, Drug Prescriptions, Antibiotic prescribing, 03 medical and health sciences, MESH: Cross-Sectional Studies, SDG 3 - Good Health and Well-being, Antibiotic therapy, Medical, MESH: Anti-Bacterial Agents, Curriculum, Education, Medical school, Medical student, Questionnaire, Cross-Sectional Studies, Drug Utilization, Antibiotic use, medical schoo, MESH: Surveys and Questionnaires, MESH : Education, Medical, ntibiotic stewardship, curriculum, education, medical school, medical student, questionnaire, Medical education, MESH: Schools, Medical, 030306 microbiology, business.industry, MESH : Communicable Diseases, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, MESH: Europe, business
Abstract

We surveyed European medical schools regarding teaching of prudent antibiotic prescribing in the undergraduate curriculum. We performed a cross-sectional survey in 13 European countries (Belgium, Croatia, Denmark, France, Germany, Italy, Netherlands, Norway, Serbia, Slovenia, Spain, Switzerland, United Kingdom) in 2013. Proportional sampling was used, resulting in the selection of two to four medical schools per country. A standardized questionnaire based on literature review and validated by a panel of experts was sent to lecturers in infectious diseases, medical microbiology and clinical pharmacology. In-depth interviews were conducted with four lecturers. Thirty-five of 37 medical schools were included in the study. Prudent antibiotic use principles were taught in all but one medical school, but only four of 13 countries had a national programme. Interactive teaching formats were used less frequently than passive formats. The teaching was mandatory for 53% of the courses and started before clinical training in 71%. We observed wide variations in exposure of students to important principles of prudent antibiotic use among countries and within the same country. Some major principles were poorly covered (e.g. reassessment and duration of antibiotic therapy, communication skills). Whereas 77% of the respondents fully agreed that the teaching of these principles should be prioritized, lack of time, mainly due to rigid curriculum policies, was the main reported barrier to implementation. Given the study design, these are probably optimistic results. Teaching of prudent antibiotic prescribing principles should be improved. National and European programmes for development of specific learning outcomes or competencies are urgently needed. Clinical Microbiology and Infection © 2014 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved

Published
2015

2. An international cross-sectional survey of antimicrobial stewardship programmes in hospitals

Author

Ian M. Gould, Philip Howard, Céline Pulcini, Stéphan Juergen Harbarth, Robert West, G. Levy Hara, Dilip Nathwani, Leeds Teaching Hospitals NHS Trust, Maladies chroniques, santé perçue, et processus d'adaptation (APEMAC), Université Paris Descartes - Paris 5 (UPD5)-Université de Lorraine (UL), Service des Maladies Infectieuses et Tropicales [CHRU Nancy], Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), Hospital Carlos G. Durand, Leeds Institute for Health Sciences (LIHS), Faculty of Medicine and Health [Leeds], University of Leeds-University of Leeds, Aberdeen Royal Infirmary, Prévention et contrôle des infections (PCI ), Hôpitaux Universitaires de Genève (HUG), Ninewells Hospital and Medical School [Dundee], Maladies chroniques, santé perçue, et processus d'adaptation. Approches épidémiologiques et psychologiques. ( APEMAC - EA 4360 ), Université Paris Descartes - Paris 5 ( UPD5 ) -Université de Lorraine ( UL ), Centre Hospitalier Régional Universitaire de Nancy ( CHRU Nancy ), Leeds Institute for Health Sciences ( LIHS ), Prévention et contrôle des infections ( PCI ), and Hôpitaux Universitaires de Genève ( HUG )

Subjects
Cross-sectional study, MESH : Drug Prescriptions, MESH: Global Health, Global Health, MESH : Drug Utilization, antibiotic prescription, 0302 clinical medicine, MESH : Cross-Sectional Studies, MESH: Drug Prescriptions, Antimicrobial stewardship, Pharmacology (medical), 030212 general & internal medicine, MESH : Anti-Bacterial Agents, MESH: Drug Utilization, ddc:616, 0303 health sciences, [ SDV.SPEE ] Life Sciences [q-bio]/Santé publique et épidémiologie, Antimicrobial, MESH: Hospitals, Hospitals, Organizational Policy, Antibiotic prescription, Anti-Bacterial Agents, 3. Good health, MESH : Hospitals, Infectious Diseases, Health Services Research, MESH : Organizational Policy, MESH: Health Services Research, Microbiology (medical), medicine.medical_specialty, MESH : Health Services Research, Drug Prescriptions, 03 medical and health sciences, Pharmacy (field), MESH: Cross-Sectional Studies, Environmental health, Electronic prescribing, MESH: Anti-Bacterial Agents, medicine, Humans, Intensive care medicine, Pharmacology, MESH: Humans, 030306 microbiology, business.industry, MESH : Humans, Drug Utilization, antibiotic policy, Cross-Sectional Studies, MESH : Global Health, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, MESH: Organizational Policy, antibiotic management, business
Abstract

Objectives To report the extent and components of global efforts in antimicrobial stewardship (AMS) in hospitals. Methods An Internet-based survey comprising 43 questions was disseminated worldwide in 2012. Results Responses were received from 660 hospitals in 67 countries: Africa, 44; Asia, 50; Europe, 361; North America, 72; Oceania, 30; and South and Central America, 103. National AMS standards existed in 52% of countries, 4% were planning them and 58% had an AMS programme. The main barriers to implementing AMS programmes were perceived to be a lack of funding or personnel, a lack of information technology and prescriber opposition. In hospitals with an existing AMS programme, AMS rounds existed in 64%; 81% restricted antimicrobials (carbapenems, 74.3%; quinolones, 64%; and cephalosporins, 58%); and 85% reported antimicrobial usage, with 55% linking data to resistance rates and 49% linking data to infection rates. Only 20% had electronic prescribing for all patients. A total of 89% of programmes educated their medical, nursing and pharmacy staff on AMS. Of the hospitals, 38% had formally reviewed their AMS programme: reductions were reported by 96% of hospitals for inappropriate prescribing, 86% for broad-spectrum antibiotic use, 80% for expenditure, 71% for healthcare-acquired infections, 65% for length of stay or mortality and 58% for bacterial resistance. Conclusions The worldwide development and implementation of AMS programmes varies considerably. Our results should inform and encourage the further evaluation of this with a view to promoting a worldwide stewardship framework. The prospective measurement of well-defined outcomes of the impact of these programmes remains a significant challenge.

Published
2015

3. The impact of infectious disease specialists on antibiotic prescribing in hospitals

Author

Stéphan Juergen Harbarth, Oliver J. Dyar, E Botelho-Nevers, Céline Pulcini, Maladies chroniques, santé perçue, et processus d'adaptation. Approches épidémiologiques et psychologiques. ( APEMAC - EA 4360 ), Université Paris Descartes - Paris 5 ( UPD5 ) -Université de Lorraine ( UL ), Service des Maladies Infectieuses et Tropicales [CHRU Nancy], Centre Hospitalier Régional Universitaire de Nancy ( CHRU Nancy ), Service des maladies infectieuses [Saint-Etienne], CHU Saint-Etienne, Groupe Immunité des Muqueuses et Agents Pathogènes ( GIMAP ), Université Jean Monnet [Saint-Étienne] ( UJM ), North Devon District Hospital, Prévention et contrôle des infections ( PCI ), Hôpitaux Universitaires de Genève ( HUG ), Maladies chroniques, santé perçue, et processus d'adaptation (APEMAC), Université Paris Descartes - Paris 5 (UPD5)-Université de Lorraine (UL), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), Groupe Immunité des Muqueuses et Agents Pathogènes (GIMAP), Université Jean Monnet [Saint-Étienne] (UJM), Prévention et contrôle des infections (PCI ), and Hôpitaux Universitaires de Genève (HUG)

Subjects
MESH : Drug Prescriptions, Controlled studies, appropriateness, MESH : Drug Resistance, Bacterial, MESH : Randomized Controlled Trials as Topic, law.invention, 0302 clinical medicine, Randomized controlled trial, MESH: Drug Prescriptions, law, Medicine, Antimicrobial stewardship, MESH: Physicians, 030212 general & internal medicine, MESH : Anti-Bacterial Agents, Practice Patterns, Physicians', Randomized Controlled Trials as Topic, 0303 health sciences, infectious disease physician, [ SDV.SPEE ] Life Sciences [q-bio]/Santé publique et épidémiologie, General Medicine, Bacterial Infections, MESH: Hospitals, Hospitals, 3. Good health, Anti-Bacterial Agents, MESH : Bacterial Infections, MESH : Hospitals, Infectious Diseases, quality, interventional studies, Microbiology (medical), medicine.medical_specialty, MESH: Bacterial Infections, MESH : Physicians, review, antibiotic stewardship, Drug Prescriptions, Antibiotic prescribing, curbside consultation, 03 medical and health sciences, Antibiotic resistance, MESH: Anti-Bacterial Agents, Physicians, MESH: Drug Resistance, Bacterial, Drug Resistance, Bacterial, Humans, Antibiotic use, Medical prescription, Intensive care medicine, MESH: Humans, 030306 microbiology, business.industry, MESH : Humans, MESH: Randomized Controlled Trials as Topic, MESH : Practice Patterns, Physicians', Infectious disease (medical specialty), Emergency medicine, MESH: Practice Patterns, Physicians', antimicrobial, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, business
Abstract

International audience; Given the current bacterial resistance crisis, antimicrobial stewardship programmes are of the utmost importance. We present a narrative review of the impact of infectious disease specialists (IDSs) on the quality and quantity of antibiotic use in acute-care hospitals, and discuss the main factors that could limit the efficacy of IDS recommendations. A total of 31 studies were included in this review, with a wide range of infections, hospital settings, and types of antibiotic prescription. Seven of 31 studies were randomized controlled trials, before/after controlled studies, or before/after uncontrolled studies with interrupted time-series analysis. In almost all studies, IDS intervention was associated with a significant improvement in the appropriateness of antibiotic prescribing as compared with prescriptions without any IDS input, and with decreased antibiotic consumption. Variability in the antibiotic prescribing practices of IDSs, informal (curbside) consultations and the involvement of junior IDSs are among the factors that could have an impact on the efficacy of IDS recommendations and on compliance rates, and deserve further investigation. We also discuss possible drawbacks of IDSs in acute-care hospitals that are rarely reported in the published literature. Overall, IDSs are valuable to antimicrobial stewardship programmes in hospitals, but their impact depends on many human and organizational factors.

Published
2014

4. Impact of a region wide antimicrobial stewardship guideline on urinary tract infection prescription patterns

Author

Danièle Sekri, Xavier Bertrand, C. Slekovec, Nathalie Vernaz-Hegi, Bruno Hoen, Daniel Talon, J. Leroy, Jean-Pierre Faller, Laboratoire Chrono-environnement - CNRS - UBFC (UMR 6249) (LCE), Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Centre Hospitalier Régional Universitaire de Besançon (CHRU Besançon), Service des maladies infectieuses et tropicales, Centre Hospitalier Régional Universitaire de Besançon (CHRU Besançon)-Hôpital Saint-Jacques, Laboratoire Chrono-environnement ( LCE ), Université Bourgogne Franche-Comté ( UBFC ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Franche-Comté ( UFC ), Hôpital Jean Minjoz, Centre Hospitalier Régional Universitaire [Besançon] ( CHRU Besançon ), and Centre Hospitalier Régional Universitaire [Besançon] ( CHRU Besançon ) -Hôpital Saint-Jacques

Subjects
Health Knowledge, Attitudes, Practice, Antibiotics, MESH : Drug Prescriptions, MESH: Health Knowledge, Attitudes, Practice, MESH : Aged, MESH: Urinary Tract Infections, Toxicology, MESH: Regression Analysis, MESH : General Practitioners, MESH : Guideline Adherence, 0302 clinical medicine, MESH : Physician's Practice Patterns, Anti-Infective Agents, MESH : Regression Analysis, Medicine, Pharmacology (medical), MESH : Urinary Tract Infections, Practice Patterns, Physicians', MESH: Drug Utilization, 0303 health sciences, MESH: Program Evaluation, MESH : Education, Medical, Continuing, MESH: Middle Aged, 3. Good health, MESH : Practice Guidelines as Topic, [SDV.MP]Life Sciences [q-bio]/Microbiology and Parasitology, MESH: Young Adult, MESH: Guideline Adherence, MESH : Anti-Infective Agents, Regression Analysis, Education, Medical, Continuing, Guideline Adherence, medicine.medical_specialty, MESH : Fosfomycin, Attitude of Health Personnel, Urinary system, MESH: Attitude of Health Personnel, MESH : Young Adult, Pharmacy, Drug Prescriptions, 03 medical and health sciences, MESH : Adolescent, [ SDV.MHEP ] Life Sciences [q-bio]/Human health and pathology, Humans, MESH : Middle Aged, MESH : Norfloxacin, MESH: Physician's Practice Patterns, Norfloxacin, Aged, Pharmacology, MESH: Adolescent, MESH: Humans, 030306 microbiology, MESH : Humans, MESH: Adult, Guideline, MESH: Education, Medical, Continuing, Nitrofurantoin, MESH: Female, MESH : Attitude of Health Personnel, Pediatrics, Time Factors, MESH : Health Knowledge, Attitudes, Practice, Pharmaceutical Science, MESH : Drug Utilization, MESH: Fosfomycin, MESH: Practice Guidelines as Topic, MESH: Drug Prescriptions, [ SDV.MP ] Life Sciences [q-bio]/Microbiology and Parasitology, Antimicrobial stewardship, MESH : Female, 030212 general & internal medicine, MESH: Aged, MESH : Adult, Middle Aged, MESH: General Practitioners, MESH : Program Evaluation, Practice Guidelines as Topic, Urinary Tract Infections, MESH: Nitrofurantoin, Female, France, medicine.drug, MESH : Time Factors, Adult, MESH: Norfloxacin, Adolescent, medicine.drug_class, MESH: Anti-Infective Agents, Young Adult, Fosfomycin, General Practitioners, Internal medicine, MESH : Nitrofurantoin, Medical prescription, MESH : France, business.industry, MESH: Time Factors, Drug Utilization, MESH: France, business, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, Program Evaluation
Abstract

International audience; BACKGROUND: Fluoroquinolones are frequently prescribed for non complicated urinary tract infection treatments and have a negative ecological impact. We aimed to substitute them by antibiotics with narrower activity spectrum in order to preserve fluoroquinolone activity in complicated hospital infections. OBJECTIVE: To assess the impact of a multi-modal approach that combines the dispatching of antibiotic prescription guidelines and voluntary attendance at educational sessions on general practitioners' (GP) antibiotic prescription habits. SETTING: This study was led in Franche-Comté, a French eastern region, where GPs were given a guideline recommending a restricted use of fluoroquinolones for urinary tract infections. METHOD: Segmented regression analysis of interrupted time series was used to assess changes in antibiotic prescription. MAIN OUTCOME MEASURE: The antibiotic prescription data of nitrofurantoin, fosfomycin-trometamol and fluoroquinolones for women aged 15-65 years were obtained from the regional agency of health insurance. RESULTS: Twenty months after intervention, the number of nitrofurantoin and fosfomycintrometamol prescriptions increased by 36.8% (95% CI: 30.6-42.2) and 28.5% (95% CI: 22.9-35.4), respectively, while that of norfloxacin decreased by 9.1% (95% CI: -15.3 to -3.5). CONCLUSION: This study suggests that the dispatch of the guideline on urinary tract infection had a moderate impact on antibiotic prescriptions.

Published
2012

5. How to translate therapeutic recommendations in clinical practice guidelines into rules for critiquing physician prescriptions? Methods and application to five guidelines

Author

Christine Riou, Christian Simon, Brigitte Séroussi, Jean-Baptiste Lamy, Alain Venot, Stéphane Dubois, Jacques Bouaud, Madeleine Favre, Vahid Ebrahiminia, Antoine Butti, Gérard Simon, Hector Falcoff, Laboratoire d'Informatique Médicale et Ingénierie des Connaissances en e-Santé (LIMICS), Université Paris 13 (UP13)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire d'Informatique Médicale et de BIOinformatique (LIM&BIO), Université Paris 13 (UP13), Département d'information hospitalier, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Henri Mondor-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Modélisation Conceptuelle des Connaissances Biomédicales, Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), UPMC - Département de santé publique, Université Pierre et Marie Curie - Paris 6 (UPMC)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Tenon [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Centre de Recherche des Cordeliers (CRC (UMR_S 872)), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Silk Informatique, Recherches et Etudes en Systèmes Informatiques Professionnels (RESIP), RESIP, Expertise en Système d'Information et de Représentation de l'Information Médicale (ESIRIM), ESIRIM, Société de Formation Thérapeutique du Généraliste (SFTG), We thank the HAS (Haute Autorité de Santé, the French health authority) and the CNAM (Caisse Nationale d'Assurance Maladie, the French health insurance fund for employees) for funding the ASTI project, Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Université Paris Descartes - Paris 5 (UPD5)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), BMC, Ed., Laboratoire d'Informatique Médicale et de BIOinformatique ( LIM&BIO ), Université Paris 13 ( UP13 ), Assistance publique - Hôpitaux de Paris (AP-HP)-Hôpital Henri Mondor-Université Paris-Est Créteil Val-de-Marne - Paris 12 ( UPEC UP12 ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Département de santé publique, Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Assistance publique - Hôpitaux de Paris (AP-HP)-CHU Tenon [APHP], Centre de Recherche des Cordeliers ( CRC (UMR_S 872) ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Recherches et Etudes en Systèmes Informatiques Professionnels ( RESIP ), Expertise en Système d'Information et de Représentation de l'Information Médicale ( ESIRIM ), Société de Formation Thérapeutique du Généraliste ( SFTG ), and Bouaud, Jacques

Subjects
Decision support system, 020205 medical informatics, MESH : Translational Medical Research, MESH : Drug Prescriptions, Alternative medicine, MESH: Translational Medical Research, 02 engineering and technology, Health informatics, law.invention, Task (project management), Translational Research, Biomedical, 0302 clinical medicine, MESH : Physician's Practice Patterns, Randomized controlled trial, MESH : Chronic Disease, MESH: Drug Prescriptions, MESH: Practice Guidelines as Topic, law, 0202 electrical engineering, electronic engineering, information engineering, Medicine, 030212 general & internal medicine, Practice Patterns, Physicians', [ SDV.BIBS ] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], MESH : Algorithms, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM], [SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Health Policy, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], 3. Good health, Computer Science Applications, Test (assessment), MESH : Practice Guidelines as Topic, Practice Guidelines as Topic, lcsh:R858-859.7, Algorithms, Research Article, medicine.medical_specialty, Health Informatics, MESH: Algorithms, lcsh:Computer applications to medicine. Medical informatics, Drug Prescriptions, 03 medical and health sciences, MESH: Drug Therapy, Drug Therapy, [ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM], Humans, Medical prescription, MESH: Physician's Practice Patterns, MESH : Drug Therapy, Medical education, MESH: Humans, business.industry, MESH: Chronic Disease, MESH : Humans, Guideline, Family medicine, Chronic Disease, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], business
Abstract

Background Clinical practice guidelines give recommendations about what to do in various medical situations, including therapeutical recommendations for drug prescription. An effective way to computerize these recommendations is to design critiquing decision support systems, i.e. systems that criticize the physician's prescription when it does not conform to the guidelines. These systems are commonly based on a list of "if conditions then criticism" rules. However, writing these rules from the guidelines is not a trivial task. The objective of this article is to propose methods that (1) simplify the implementation of guidelines' therapeutical recommendations in critiquing systems by automatically translating structured therapeutical recommendations into a list of "if conditions then criticize" rules, and (2) can generate an appropriate textual label to explain to the physician why his/her prescription is not recommended. Methods We worked on the therapeutic recommendations in five clinical practice guidelines concerning chronic diseases related to the management of cardiovascular risk. We evaluated the system using a test base of more than 2000 cases. Results Algorithms for automatically translating therapeutical recommendations into "if conditions then criticize" rules are presented. Eight generic recommendations are also proposed; they are guideline-independent, and can be used as default behaviour for handling various situations that are usually implicit in the guidelines, such as decreasing the dose of a poorly tolerated drug. Finally, we provide models and methods for generating a human-readable textual critique. The system was successfully evaluated on the test base. Conclusion We show that it is possible to criticize physicians' prescriptions starting from a structured clinical guideline, and to provide clear explanations. We are now planning a randomized clinical trial to evaluate the impact of the system on practices.

Published
2010

6. Chronology of prescribing error during the hospital stay and prediction of pharmacist's alerts overriding: a prospective analysis

Author

Vanida Bruni, Florence Gillaizeau, Thibaut Caruba, Brigitte Sabatier, Patrice Prognon, Virginie Korb, Dominique Bégué, Isabelle Colombet, Pierre Durieux, Service de pharmacie, Assistance publique - Hôpitaux de Paris (AP-HP)-Hôpital Européen Georges Pompidou [APHP] ( HEGP ), Laboratoire Interdisciplinaire de Recherche en Economie de Santé, Informatique Hospitalière, Evaluation et Santé Publique, Centre D'investigation Épidémiologique 4, Institut National de la Santé et de la Recherche Médicale ( INSERM ), Centre de Recherche des Cordeliers ( CRC (UMR_S 872) ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Risque Thrombotique et Mecanismes de l'Hemostase ( U765 ), Institut des sciences du Médicament -Toxicologie - Chimie - Environnement ( IFR71 ), Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Ecole Nationale Supérieure de Chimie de Paris- Chimie ParisTech-PSL ( ENSCP ) -Centre National de la Recherche Scientifique ( CNRS ) -Institut de Recherche pour le Développement ( IRD ) -Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Ecole Nationale Supérieure de Chimie de Paris- Chimie ParisTech-PSL ( ENSCP ) -Centre National de la Recherche Scientifique ( CNRS ) -Institut de Recherche pour le Développement ( IRD ) -Université Paris Descartes - Paris 5 ( UPD5 ) -Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Service de pharmacie [CHU HEGP], Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Institut National de la Santé et de la Recherche Médicale (INSERM), Centre de Recherche des Cordeliers (CRC (UMR_S 872)), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Risque Thrombotique et Mécanismes de l'Hémostase (U765), Institut des sciences du Médicament -Toxicologie - Chimie - Environnement (IFR71), Institut de Recherche pour le Développement (IRD)-Ecole Nationale Supérieure de Chimie de Paris - Chimie ParisTech-PSL (ENSCP), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Ecole Nationale Supérieure de Chimie de Paris - Chimie ParisTech-PSL (ENSCP), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Risque Thrombotique et Mecanismes de l'Hemostase (U765), Institut National de la Santé et de la Recherche Médicale (INSERM)-Ecole Nationale Supérieure de Chimie de Paris - Chimie ParisTech-PSL (ENSCP), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Ecole Nationale Supérieure de Chimie de Paris - Chimie ParisTech-PSL (ENSCP), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Paris Descartes - Paris 5 (UPD5)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), and BMC, Ed.

Subjects
MESH: Pharmacists, MESH: Drug Interactions, MESH : Drug Prescriptions, MESH : Prospective Studies, MESH : Pharmacists, MESH: Medication Errors, MESH: Hospitalization, Pharmacists, 030226 pharmacology & pharmacy, Health informatics, MESH: Regression Analysis, MESH: Length of Stay, Health administration, Hospitals, University, 0302 clinical medicine, MESH: Drug Prescriptions, Computerized physician order entry, MESH : Regression Analysis, Medication Errors, Drug Interactions, 030212 general & internal medicine, Prospective Studies, [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, Health Policy, Nursing research, lcsh:Public aspects of medicine, Regression analysis, [SDV.SP]Life Sciences [q-bio]/Pharmaceutical sciences, 3. Good health, MESH: Medical Order Entry Systems, [SDV.SP] Life Sciences [q-bio]/Pharmaceutical sciences, Hospitalization, MESH : Length of Stay, Regression Analysis, MESH : Hospitalization, MESH : Medical Staff, Hospital, France, medicine.medical_specialty, MESH : Interprofessional Relations, MESH : Medication Errors, Interprofessional Relations, Pharmacist, MESH: Medical Staff, Hospital, Drug Prescriptions, Medical Order Entry Systems, 03 medical and health sciences, [ SDV.MHEP ] Life Sciences [q-bio]/Human health and pathology, MESH: Interprofessional Relations, Research article, medicine, Medical Staff, Hospital, Humans, Medical prescription, MESH : France, MESH : Hospitals, University, MESH: Hospitals, University, MESH: Humans, business.industry, MESH : Humans, lcsh:RA1-1270, Length of Stay, MESH: Prospective Studies, MESH : Drug Interactions, MESH: France, MESH : Medical Order Entry Systems, [ SDV.SP ] Life Sciences [q-bio]/Pharmaceutical sciences, Emergency medicine, Prescribing error, business, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract

Background: Drug prescribing errors are frequent in the hospital setting and pharmacists play an important role in detection of these errors. The objectives of this study are (1) to describe the drug prescribing errors rate during the patient’s stay, (2) to find which characteristics for a prescribing error are the most predictive of their reproduction the next day despite pharmacist’s alert (i.e. override the alert). Methods: We prospectively collected all medication order lines and prescribing errors during 18 days in 7 medical wards’ using computerized physician order entry. We described and modelled the errors rate according to the chronology of hospital stay. We performed a classification and regression tree analysis to find which characteristics of alerts were predictive of their overriding (i.e. prescribing error repeated). Results: 12 533 order lines were reviewed, 117 errors (errors rate 0.9%) were observed and 51% of these errors occurred on the first day of the hospital stay. The risk of a prescribing error decreased over time. 52% of the alerts were overridden (i.e error uncorrected by prescribers on the following day. Drug omissions were the most frequently taken into account by prescribers. The classification and regression tree analysis showed that overriding pharmacist’s alerts is first related to the ward of the prescriber and then to either Anatomical Therapeutic Chemical class of the drug or the type of error. Conclusions: Since 51% of prescribing errors occurred on the first day of stay, pharmacist should concentrate his analysis of drug prescriptions on this day. The difference of overriding behavior between wards and according drug Anatomical Therapeutic Chemical class or type of error could also guide the validation tasks and programming of electronic alerts. Background Drug prescribing errors are defined as a prescribing decision or prescription writing process that results in an unintentional, significant reduction in the probability of treatment being timely and effective or increase in the risk of harm, when compared with generally accepted practice. High rates of inpatient prescribing errors have been reported: 1.5-5.3 per 100 drug orders, or 1.4 errors per admission [1,2].

Published
2010

Catalog

Books, media, physical & digital resources
See catalog results