development and validation of automated indicators on the appropriateness of oral anticoagulant prescriptions

Conditions: Healthcare Quality Indicators; Inappropriate Prescribing; Anticoagulant Drugs; Atrial Fibrillation; Venous Thromboembolism; Valvular Heart Disease; Brain Injury

Summary: this research focuses on the development and validation of indicators on the appropriateness of oral anticoagulant prescriptions. the investigators want to propose transferable tools to other healthcare institutions to allow automated construction of indicators as part of a structured approach to improve future practices. the main objective of the study is to develop indicators on the appropriateness of oral anticoagulant prescriptions in adult medicine automated from the hospital information system and to assess their criterion validity.

the appropriateness of oral anticoagulant prescriptions (vitamin k antagonists and direct oral anticoagulants) is a major challenge for improving quality, safety and efficiency of care. the large targeted population, prescription frequency and strong risk of severe adverse events, especially in healthcare institutions, justify the importance of developing indicators on the appropriateness of oral anticoagulant prescriptions and their automated implementation from the hospital information system. there is currently a need to develop and validate such indicators for integrating them into the hospital clinical practice, as part of a structured approach to improve quality and safety of care. as each hospital information system is different, the investigators want to propose transposable tools to other healthcare institutions to allow an automated construction of these indicators. the study will consist of three main steps: 1) identification of indicators on the appropriateness of oral anticoagulant prescriptions and their conditions of appropriateness (literature review), and analysis of their potential utility and operational characteristic (delphi consensus); 2) operational implementation of the selected indicators from the hospital information system, using tools to generalize their implementation to other hospital information systems; 3) evaluation of metrological performance and robustness of the selected indicators. this is an observation of prescriptions after it has occurred without any modification or change of treatment to patients. this study is never interventional. statistical analysis : for each indicator, the criterion validity will be analyzed thanks to prevalence of appropriateness (or not) of oral anticoagulant prescriptions estimated by the hospital information system, sensitivity, specificity, positive and negative predictive values, and area under the roc curve.

Eligibility criteria:
inclusion criteria: * patients aged over 18; * patients hospitalized at the bordeaux university hospital or the georges-pompidou european hospital for a clinical situation that could justify a prescription of oral anticoagulants or for an at risk situation in patients under oral anticoagulants, among targeted frequent clinical situations; * patients hospitalized in medicine-surgery-obstetrics care or rehabilitation care (conventional hospitalization or outpatient) between the 1st of january 2015 and the 31th of december 2017; * patients whose medical and administrative data are available in an electronic format in the hospital information system exclusion criteria: * patients not hospitalized at the bordeaux university hospital or the georges-pompidou european hospital for a clinical situation that could justify a prescription of oral anticoagulants or for an at risk situation in patients under oral anticoagulants, among targeted frequent clinical situations; * patients whose medical and administrative data are not available in an electronic format in the hospital information system; * patients who do not give consent for research data use.

Keywords: quality indicators appropriateness oral anticoagulant prescriptions development and validation hospital information system information storage and retrieval natural language processing