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

<p>Abstract</p> <p>Background</p> <p>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, <it>i.e</it>. 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.</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p

Use of the C4.5 machine learning algorithm to test a clinical guideline-based decision support system.

International audienceWell-designed medical decision support system (DSS) have been shown to improve health care quality. However, before they can be used in real clinical situations, these systems must be extensively tested, to ensure that they conform to the clinical guidelines (CG) on which they are based. Existing methods cannot be used for the systematic testing of all possible test cases. We describe here a new exhaustive dynamic verification method. In this method, the DSS is considered to be a black box, and the Quinlan C4.5 algorithm is used to build a decision tree from an exhaustive set of DSS input vectors and outputs. This method was successfully used for the testing of a medical DSS relating to chronic diseases: the ASTI critiquing module for type 2 diabetes

An Interoperable Clinical Cardiology Electronic Health Record System - a standards based approach for Clinical Practice and Research with Data Reuse

Currently in hospitals, several information systems manage, very often autonomously, the patient’s personal, clinical and diagnostic data. This originates a clinical information management system consisting of a myriad of independent subsystems which, although efficient in their specific purpose, make the integration of the whole system very difficult and limit the use of clinical data, especially as regards the reuse of these data for research purposes. Mainly for these reasons, the management of the Genoese ASL3 decided to commission the University of Genoa to set up a medical record system that could be easily integrated with the rest of the information system already present, but which offered solid interoperability features, and which could support the research skills of hospital health workers. My PhD work aimed to develop an electronic health record system for a cardiology ward, obtaining a prototype which is functional and usable in a hospital ward. The choice of cardiology was due to the wide availability of the staff of the cardiology department to support me in the development and in the test phase. The resulting medical record system has been designed “ab initio” to be fully integrated into the hospital information system and to exchange data with the regional health information infrastructure. In order to achieve interoperability the system is based on the Health Level Seven standards for exchanging information between medical information systems. These standards are widely deployed and allow for the exchange of information in several functional domains. Specific decision support sections for particular aspects of the clinical life were also included. The data collected by this system were the basis for examples of secondary use for the development of two models based on machine learning algorithms. The first model allows to predict mortality in patients with heart failure within 6 months from their admission, and the second is focused on the discrimination between heart failure versus chronic ischemic heart disease in the elderly population, which is the widest population section served by the cardiological ward

Progress Notes

https://scholarlyworks.lvhn.org/progress_notes/1296/thumbnail.jp

Phenomenological Assessment of Integrative Medicine Decision-making and the Utility of Predictive and Prescriptive Analytics Tools

The U.S. Healthcare system is struggling to manage the burden of chronic disease, racial and socio-economic disparities, and the debilitating impact of the current global pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). More patients need alternatives to allopathic or “Western” medicine focused on fighting disease with mechanism, pharmaceuticals, and invasive measures. They are seeking Integrative Medicine which focuses on health and healing, emphasizing the centrality of the patient-physician relationship. In addition to providing the best conventional care, IM focuses on preventive maintenance, wellness, improved behaviors, and a holistic care plan. This qualitative research assessed whether predictive and prescriptive analytics (artificial intelligence tools that predict patient outcomes and recommend treatments, interventions, and medications) supports the decision-making processes of IM practitioners who treat patients suffering from chronic pain. PPA was used in a few U.S. hospitals but was not widely available for IM practitioners at the time of this research. Phenomenological interviews showed doctors benefit from technology that aggregates data, providing a clear patient snapshot. PPA exposed historical information that doctors often miss. However, current systems lacked the design to manage individualized, holistic care focused on the mind, body, and spirit. Using the Future-Focused Task-Technology Fit theory, the research suggested PPA could actually do more harm than good in its current state. Future technology must be patient-focused and designed with a better understanding of the IM task and group characteristics (e.g., the unique way providers practice medicine) to reduce algorithm aversion and increase adoption. In the ideal future state, PPA will surface healthcare Big Data from multiple sources, support communication and collaboration across the patient’s support system and community of care, and track the various objective and subjective factors contributing to the path to wellness

How can pharmacists contribute to anaemia management? A review of literature and exploratory study on pharmacists' role in anaemia

Background Iron deficiency anaemia (IDA) is the leading cause of anaemia globally, most frequently found in children and pregnant women. With their increasing role in the healthcare system, pharmacists may contribute to the management of anaemia. Through the International Pharmaceutical Federation (FIP) Multinational Needs Assessment Programme, the FIP explored the contribution of pharmacists in anaemia, specifically IDA, focusing on five countries: India, Indonesia, Malaysia, Philippines and Singapore. Objective To explore information on pharmacists' roles in a variety of settings related to 1) IDA management; 2) education and training needed to support the roles; and 3) barriers and enablers to expanding or developing the roles. Methods This study involved a literature review and a focus group discussion with twelve participants selected purposively and nominated by national professional leadership bodies across five countries. A literature search was conducted using PubMed Database. A focus group discussion explored pharmacists' roles, education and training needs, as well as barriers and enablers to support their roles in anaemia management, specifically in IDA. A codebook thematic analysis approach was conducted according to the study objectives. Results Sixteen articles were included in the analysis. The pharmacists' roles in anaemia identified from literature ranged from patient management and monitoring, collaboration with other healthcare professionals and involvement in guideline development, in which the roles vary according to the workplace. Twelve participants attended the focus group discussion. Participants highlighted pharmacists' roles in screening and detection, medication therapeutic management, patient counselling and patient monitoring. Participants emphasised a need for guidelines or toolkits with subsequent training or workshops to support their competency development in anaemia. Monitoring the success of pharmacist delivered anaemia programmes was recommended to support advocating for active pharmacist roles. Conclusion Pharmacists have a growing opportunity to contribute to achieving the global targets on anaemia through their involvement in screening and managing anaemia and increasing anaemia awareness among the patients and community

A national clinical decision support infrastructure to enable the widespread and consistent practice of genomic and personalized medicine

<p>Abstract</p> <p>Background</p> <p>In recent years, the completion of the Human Genome Project and other rapid advances in genomics have led to increasing anticipation of an era of genomic and personalized medicine, in which an individual's health is optimized through the use of all available patient data, including data on the individual's genome and its downstream products. Genomic and personalized medicine could transform healthcare systems and catalyze significant reductions in morbidity, mortality, and overall healthcare costs.</p> <p>Discussion</p> <p>Critical to the achievement of more efficient and effective healthcare enabled by genomics is the establishment of a robust, nationwide clinical decision support infrastructure that assists clinicians in their use of genomic assays to guide disease prevention, diagnosis, and therapy. Requisite components of this infrastructure include the standardized representation of genomic and non-genomic patient data across health information systems; centrally managed repositories of computer-processable medical knowledge; and standardized approaches for applying these knowledge resources against patient data to generate and deliver patient-specific care recommendations. Here, we provide recommendations for establishing a national decision support infrastructure for genomic and personalized medicine that fulfills these needs, leverages existing resources, and is aligned with the <it>Roadmap for National Action on Clinical Decision Support </it>commissioned by the U.S. Office of the National Coordinator for Health Information Technology. Critical to the establishment of this infrastructure will be strong leadership and substantial funding from the federal government.</p> <p>Summary</p> <p>A national clinical decision support infrastructure will be required for reaping the full benefits of genomic and personalized medicine. Essential components of this infrastructure include standards for data representation; centrally managed knowledge repositories; and standardized approaches for leveraging these knowledge repositories to generate patient-specific care recommendations at the point of care.</p

Estudio para la calculadora de edad vascular como herramienta para reducir el riesgo cardiovascular de la farmacia comunitaria

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Farmacia, leída el 29-11-2021Background: Cardiovascular disease (CVD) is one of the leading causes of morbidity and mortality in Spain. According to the World Health Organization (WHO), 80% of these premature deaths are avoidable by reducing the modifiable risk factors of CVD. Research indicates that patients better understand their true risk when information is presented to them in vascular age (VA). Community pharmacists (CP) are well situated to assess patientsVA, provide professional educational advice, and implement interventions for reducing cardiovascular risk (CVR).Aim: The explicit objective of this thesis was to create a patient-centred, accurate and accessible tool that allows the CPs in Spain to estimate the VA and design a personalized intervention aimed at reducing the patient’s VA.Method: A website was created and included an original questionnaire, the vascular age calculator (VAC), detailed protocols for the pharmacist’s intervention and the patient’s information leaflets on CVR factors. The webpage user’s perceptions were analysed via a 26-item self-completion online survey distributed among CPs using a Google forum. Informed consent was taken from the CPs to participate in the study. The responses to the survey were collected anonymously. Open and closed questions were used to gain a wide range of replies and an in-depth understanding. The questionnaire from the pilot study was available online from the 1st August 2020 to the 31st of February 2021. The results were analysed using the STATA package version 12.0 (StataCorp LP, College Station, TX, USA). The NVivo software was used for assessing the descriptive findings...Antecedentes: La enfermedad cardiovascular (ECV) es una de las principales causas de morbilidad y mortalidad en España. Según la Organización Mundial de la Salud, el 80% de estas muertes prematuras se podrían evitar reduciendo los factores de riesgo cardiovascular modificables. Diversos estudios indican que los pacientes entienden mejor su riesgo real cuando se les presenta la información en forma de edad vascular. Los farmacéuticoscomunitarios (FC) están bien posicionados para evaluar la edad vascular de los pacientes, proporcionar asesoramiento educativo profesional y aplicar intervenciones para reducir el riesgo cardiovascular (RCV).Objetivo: El objetivo explícito de esta tesis fue crear una herramienta centrada en el paciente, precisa y accesible que permita a los FC de España estimar la edad vascular y diseñar un plan de intervención personalizado encaminado a reducirla. Método: Se creó una página web que incluía un cuestionario original, la calculadora de la edad vascular, protocolos detallados para la intervención del farmacéutico y folletos informativos para el paciente sobre factores de RCV. Se analizó la percepción de los usuarios sobre la página web a través de una encuesta online de veintiséis preguntas distribuida entre los FC mediante un formulario de Google. Se obtuvo el consentimiento informado de los FC para participar en el estudio. Las respuestas a la encuesta se recogieron de forma anónima. Se utilizaron preguntas abiertas y cerradas para obtener una amplia gama de respuestas y de mayor profundidad. El cuestionario del estudio piloto estuvo disponible en línea desde el 1de agosto de 2020 hasta el 31 de febrero de 2021. Los resultados se analizaron con el paquete STATA versión 12.0 (StataCorp LP, College Station, TX, USA). Para evaluar los resultados descriptivos se utilizó el programa informático NVivo...Fac. de FarmaciaTRUEunpu

Implementation of case management to reduce cardiovascular disease risk in the Stanford and San Mateo Heart to Heart randomized controlled trial: study protocol and baseline characteristics

BACKGROUND: Case management has emerged as a promising alternative approach to supplement traditional one-on-one sessions between patients and doctors for improving the quality of care in chronic diseases such as coronary heart disease (CHD). However, data are lacking in terms of its efficacy and cost-effectiveness when implemented in ethnic and low-income populations. METHODS: The Stanford and San Mateo Heart to Heart (HTH) project is a randomized controlled clinical trial designed to rigorously evaluate the efficacy and cost-effectiveness of a multi-risk cardiovascular case management program in low-income, primarily ethnic minority patients served by a local county health care system in California. Randomization occurred at the patient level. The primary outcome measure is the absolute CHD risk over 10 years. Secondary outcome measures include adherence to guidelines on CHD prevention practice. We documented the study design, methodology, and baseline sociodemographic, clinical and lifestyle characteristics of 419 participants. RESULTS: We achieved equal distributions of the sociodemographic, biophysical and lifestyle characteristics between the two randomization groups. HTH participants had a mean age of 56 years, 63% were Latinos/Hispanics, 65% female, 61% less educated, and 62% were not employed. Twenty percent of participants reported having a prior cardiovascular event. 10-year CHD risk averaged 18% in men and 13% in women despite a modest low-density lipoprotein cholesterol level and a high on-treatment percentage at baseline. Sixty-three percent of participants were diagnosed with diabetes and an additional 22% had metabolic syndrome. In addition, many participants had depressed high-density lipoprotein (HDL) cholesterol levels and elevated values of total cholesterol-to-HDL ratio, triglycerides, triglyceride-to-HDL ratio, and blood pressure. Furthermore, nearly 70% of participants were obese, 45% had a family history of CHD or stroke, and 16% were current smokers. CONCLUSION: We have recruited an ethnically diverse, low-income cohort in which to implement a case management approach and test its efficacy and cost-effectiveness. HTH will advance the scientific understanding of better strategies for CHD prevention among these priority subpopulations and aid in guiding future practice that will reduce health disparities