Health Economic Implications of Complications Associated With Pancreaticoduodenectomy

2019 ◽  
pp. 144-167
Author(s):  
Jason Wang ◽  
Laurence Weinberg
Keyword(s):  
Decision Making ◽  
Health Economic ◽  
Clinical Decision Making ◽  
Clinical Information ◽  
Clinical Decision ◽  
Tertiary Hospital ◽  
Hospital Environment ◽  
Activity Based Costing ◽  
Economic Implications ◽  
High Acuity

Clinical costing is a powerful tool to bridge the disconnect between financial and clinical information, and is an ideal platform to conduct research aimed at informing value-based clinical decision making. This chapter will provide an example of the utility of activity-based costing to elucidate the costs of complications following pancreaticoduodenectomy, a high acuity procedure with high costs. It will show the significance of clear clinical costing in targeting cost containment in a tertiary hospital environment.

scholarly journals Predicting mortality in adults with suspected infection in a Rwandan hospital: an evaluation of the adapted MEWS, qSOFA and UVA scores

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e040361
Author(s):  
Amanda Klinger ◽  
Ariel Mueller ◽  
Tori Sutherland ◽  
Christophe Mpirimbanyi ◽  
Elie Nziyomaze ◽  
...  
Keyword(s):  
Decision Making ◽  
Quality Improvement ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Tertiary Hospital ◽  
Early Warning Score ◽  
Receiver Operating Curve ◽  
Predictive Capacity ◽  
Suspected Infection ◽  
Significant Difference

RationaleMortality prediction scores are increasingly being evaluated in low and middle income countries (LMICs) for research comparisons, quality improvement and clinical decision-making. The modified early warning score (MEWS), quick Sequential (Sepsis-Related) Organ Failure Assessment (qSOFA), and Universal Vital Assessment (UVA) score use variables that are feasible to obtain, and have demonstrated potential to predict mortality in LMIC cohorts.ObjectiveTo determine the predictive capacity of adapted MEWS, qSOFA and UVA in a Rwandan hospital.Design, setting, participants and outcome measuresWe prospectively collected data on all adult patients admitted to a tertiary hospital in Rwanda with suspected infection over 7 months. We calculated an adapted MEWS, qSOFA and UVA score for each participant. The predictive capacity of each score was assessed including sensitivity, specificity, positive and negative predictive value, OR, area under the receiver operating curve (AUROC) and performance by underlying risk quartile.ResultsWe screened 19 178 patient days, and enrolled 647 unique patients. Median age was 35 years, and in-hospital mortality was 18.1%. The proportion of data missing for each variable ranged from 0% to 11.7%. The sensitivities and specificities of the scores were: adapted MEWS >4, 50.4% and 74.9%, respectively; qSOFA >2, 24.8% and 90.4%, respectively; and UVA >4, 28.2% and 91.1%, respectively. The scores as continuous variables demonstrated the following AUROCs: adapted MEWS 0.69 (95% CI 0.64 to 0.74), qSOFA 0.65 (95% CI 0.60 to 0.70), and UVA 0.71 (95% CI 0.66 to 0.76); there was no statistically significant difference between the discriminative capacities of the scores.ConclusionThree scores demonstrated a modest ability to predict mortality in a prospective study of inpatients with suspected infection at a Rwandan tertiary hospital. Careful consideration must be given to their adequacy before using them in research comparisons, quality improvement or clinical decision-making.

Clinical decision-making and its place in paramedic practice

2019 ◽  
Vol 11 (5) ◽  
pp. 1-5
Author(s):  
Samantha Murdoch
Keyword(s):  
Decision Making ◽  
Clinical Outcome ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Hospital Environment ◽  
Decision Making Process ◽  
Clinical Decisions ◽  
Correct Treatment ◽  
Health And Wellbeing

In the pre-hospital environment, paramedics are required to make clinical decisions, often rapidly to ensure correct treatment and care is provided. Decisions made by paramedics majorly impacts on the life, clinical outcome, safety, health and wellbeing of their patients. With the introduction of the Newly Qualified Paramedic Framework, it potentially has never been more pertinent to examine the decision-making process-an integral part of paramedicine. The implementation of the NQP framework has prompted an exploration into clinical decision making and its place in an ever-evolving profession. Through examination of theories and frameworks, this article aims to identify the underpinning evidence that enables a paramedic to reach a competent decision and the barriers experienced in the process.

scholarly journals Health record systems that meet clinical needs

2012 ◽  
Author(s):  
Gabriella Negrini
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Patient Safety ◽  
Health Care Professionals ◽  
Clinical Decision Making ◽  
Clinical Information ◽  
Clinical Decision ◽  
Health Record ◽  
Record System ◽  
Health Records

Introduction Increased attention has recently been focused on health record systems as a result of accreditation programs, a growing emphasis on patient safety, and the increase in lawsuits involving allegations of malpractice. Health-care professionals frequently express dissatisfaction with the health record systems and complain that the data included are neither informative nor useful for clinical decision making. This article reviews the main objectives of a hospital health record system, with emphasis on its roles in communication and exchange among clinicians, patient safety, and continuity of care, and asks whether current systems have responded to the recent changes in the Italian health-care system.Discussion If health records are to meet the expectations of all health professionals, the overall information need must be carefully analyzed, a common data set must be created, and essential specialist contributions must be defined. Working with health-care professionals, the hospital management should define how clinical information is to be displayed and organized, identify a functionally optimal layout, define the characteristics of ongoing patient assessment in terms of who will be responsible for these activities and how often they will be performed. Internet technology can facilitate data retrieval and meet the general requirements of a paper-based health record system, but it must also ensure focus on clinical information, business continuity, integrity, security, and privacy.Conclusions The current health records system needs to be thoroughly revised to increase its accessibility, streamline the work of health-care professionals who consult it, and render it more useful for clinical decision making—a challenging task that will require the active involvement of the many professional classes involved.

scholarly journals Use of EHR-based simulation to diagnose aetiology of information gathering issues in struggling learners: a proof of concept study

2017 ◽  
Vol 4 (2) ◽  
pp. 92-94 ◽  
Author(s):  
Vishnu Mohan ◽  
Gretchen Scholl ◽  
Jeffrey A Gold
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Large Fraction ◽  
Clinical Information ◽  
Clinical Decision ◽  
Information Gathering ◽  
High Fidelity ◽  
Struggling Learners ◽  
Effective Decision Making ◽  
Main Component

Learners who struggle with clinical decision making are often the most challenging to identify and remediate. While for some learners, struggles can be directly traced to a poor knowledge base, for many others, it is more difficult to understand the reason for their struggles. One of the main component of effective decision making is access to accurate and complete clinical information. The electronic health record (EHR) is the main source of clinical information and, with its widespread adoption, has come increased realisation that a large fraction of users have difficulty in effectively gathering and subsequently processing information out of the EHR. We previously documented that high-fidelity EHR-based simulation improves EHR usability and, when combined with eye and screen tracking, generates important measures of usability. We hypothesised that the same simulation exercise could help distinguish whether learners had difficulty in knowledge, information gathering or information processing. We report the results of the first three struggling learners who participated in this exercise. In each case, the simulation was able to ‘diagnose’ the aetiology for the learners’ struggle and assist in formulating an appropriate solution. We suggest that high-fidelity EHR-based simulation can be a powerful tool in the standard approach to understanding struggling learners.

Modelling in Clinical Practice with Web Services and BPEL

2011 ◽  
pp. 208-220
Author(s):  
Iain Morrison ◽  
Bryn Lewis ◽  
Sony Nugrahanto
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Information System ◽  
Clinical Information ◽  
Clinical Decision ◽  
Quality Of Healthcare ◽  
Critical Areas ◽  
Service Modelling ◽  
Tools And Techniques ◽  
Traditional Approaches

The aim of increasing the quality of healthcare has led to the development of a number of ‘guideline’ systems whereby clinicians receive assistance in decision making in a given care context – for example in areas such as prescribing or therapeutics. These guidelines range in complexity and functionality from simple textual references through to executable modules which can subsume some of the clinical decision making process. In the latter case, ensuring consistent and interoperable engagement between the guideline engine, clinical information system and patient record can become problematic. Critical areas include vocabulary and terminology (in differing use contexts) and the interfaces and interaction between different sub-systems where traditional approaches have been focussed on tightly coupling of sub-systems and in the generation of special purpose ‘glue’ languages and logic. In this paper, we briefly describe an approach to clinical, information and service modelling. This approach uses tools and techniques gaining increasing acceptance in the e-Commerce domain, which shares many of the technical and interoperability problems present in e-Health.

scholarly journals Student paramedic anticipation, confidence and fears: Do undergraduate courses prepare student paramedics for the mental health challenges of the profession?

2017 ◽  
Vol 14 (4) ◽  
Author(s):  
Lisa Holmes ◽  
Russell Jones ◽  
Richard Brightwell ◽  
Lynne Cohen
Keyword(s):  
Mental Health ◽  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Skills ◽  
Significant Proportion ◽  
Clinical Decision ◽  
Mental Wellbeing ◽  
Making A Difference ◽  
High Acuity ◽  
Mental Health Challenges

IntroductionThis study explores the preparedness of undergraduate student paramedics for the mental health challenges of the paramedic profession from the perspective of course coordinators and their students. MethodsTwo surveys were developed and administered to course coordinators and students of the 16 undergraduate degree paramedicine courses across Australia and New Zealand. Sixteen course coordinators and 302 students responded. ResultsResults illustrate there was widespread recognition for the need to include preparation for the mental health challenges of the profession within undergraduate courses. Furthermore, most course coordinators and students had a preference for this topic to be taught using multiple teaching modes with particular preference for teaching the topic via discussion and activity based education. Teaching the topic as a standalone unit was supported by more than a third of course coordinators (43%) and a third of students (32%).ConclusionSix themes were identified as positive by anticipants: caring for people, high acuity work, diversity of work and patients, making a difference to patients and their families, using clinical skills and knowledge and engaging with the community. Students were most confident about communicating with patients and using clinical skills and knowledge. Students were least confident about clinical decision making and the most commonly cited fear was making a clinical mistake. A significant proportion of students (16%) feared for their personal mental wellbeing and 14% reported they were least confident about personal mental health within the profession.

scholarly journals TPGen: Prescription Generation Using Knowledge-guided Translator

2021 ◽  
Author(s):  
Chunyang Ruan ◽  
Hua Luo ◽  
Yingpei Wu ◽  
Yun Yang
Keyword(s):  
Decision Making ◽  
Machine Translation ◽  
Language Processing ◽  
Clinical Decision Making ◽  
Clinical Information ◽  
Clinical Decision ◽  
Proposed Model ◽  
Translation Mechanism ◽  
Mining Complex ◽  
Model Improvement

Abstract Background: Prescriptions contain a lot of clinical information and play a pivotal role in the clinical diagnosis of Traditional Chinese Medicine (TCM), which is a combination of herb to treat the symptoms of a patient from decision-making of doctors. In the process of clinical decision-making, a large number of prescriptions have been invented and accumulated based on TCM theories. Mining complex and the regular relationships between symptoms and herbs in the prescriptions are important for both clinical practice and novel prescription development. Previous work used several machine learning methods to discover regularities and generate prescriptions but rarely used TCM knowledge to guide prescription generation and described why each herb is predicted for treating a symptom. Methods: In this work, we employ a machine translation mechanism and propose a novel sequence-to-sequence (seq2seq) architecture termed TPGen to generate prescriptions. TPGen consisting of an encoder and a decoder is a well-known framework for resolving the machine translation problem in the natural language processing (NLP) domain. We use the lite transformer and Bi-directional Gate Recurrent Units(Bi-GRUS) as a fundamental model in TPGen, and integrate TCM clinical knowledge to guide the model improvement termed TPGen+. Results: We conduct extensive experiments on a public TCM dataset and clinical data. The experimental results demonstrate that our proposed model is effective and outperforms other state-of-the-art methods in TCM expert evaluation. The approach will be beneficial for clinical prescription discovery and diagnosis

To report or not to report: a proposal on how to deal with altered test results in hemolytic samples

2017 ◽  
Vol 55 (8) ◽  
pp. 1109-1111 ◽  
Author(s):  
Janne Cadamuro ◽  
Cornelia Mrazek ◽  
Elisabeth Haschke-Becher ◽  
Sverre Sandberg
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Information ◽  
Clinical Decision ◽  
General Information ◽  
The Other ◽  
Test Results ◽  
Scientific Discussion ◽  
Laboratory Values ◽  
Test Result

Abstract Preanalytically altered test results are a challenge every laboratory has to face. The release of such results may be to the harm of the patient by triggering wrong clinical decision making in monitoring or treatment. On the other hand, their deletion also might be to the harm of the patient by delaying the time to decision making as the exact value sometimes is not even necessary but rather an answer to the question “Is it raised or lowered”. Based on this dilemma and forced to produce laboratory values without any clinical information on the respective patient, laboratories have developed their own preferred way on how to deal with preanalytically altered test results. Some release the value with a comment, some reject the value with or without a comment and others again provide only general information about the hemolytic sample. To date there is no guideline or standardization to this postanalytical topic. Therefore, with this opinion paper, we want to start the scientific discussion on this important issue by providing one possible method to overcome the lack of clinical information which the laboratory would need to correctly decide whether or not to release an altered test result. We suggest providing the clinician with all the information on the hemolytic sample and its impact on the respective parameter needed to make his/her own decision on the usage of the respective test result. We believe that reporting a preanalytically altered laboratory value including a respective comment is preferable to not reporting it.

scholarly journals Shades of grey: how and why we make mistakes

2020 ◽  
Vol 24 (3) ◽  
pp. 123-145
Author(s):  
A. A. Uchevatkin ◽  
A. L. Yudin ◽  
N. I. Afanas'yeva ◽  
E. A. Yumatova
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Cognitive Strategies ◽  
Diagnostic Errors ◽  
Clinical Information ◽  
Clinical Decision ◽  
Final Diagnosis ◽  
Negative Consequences ◽  
Pathological Changes ◽  
The Impact

Purpose: to consider the epidemiology and classification of errors in radiologic diagnostics.Materials and methods. The analysis of articles devoted to elucidating the possible causes of diagnostic errors published before 2019 is carried out. A retrospective analysis of the research results revealed the most frequent cognitive biases affecting clinical decision making. Strategies have been developed to combat these distortions, which minimize the likelihood of errors.Discussion. Image analysis by doctors is a complex work based on a combination of psychophysiological and cognitive processes, which in itself is subject to a wide variety of errors, including perception errors (when pathological changes are simply skipped) and cognitive errors (those cases when pathological changes are detected visually but incorrectly interpreted). Although some of the changes in the radiation images may be skipped due to technical or physical limitations of the modality (resolution, signal-to-noise ratio, artifacts, etc.), most diagnostic discrepancies are associated with an incorrect interpretation of the findings by radiologists.Conclusions. Cognitive distortions can significantly affect the process of making diagnostic decisions, and lead to medical errors and negative consequences for patients. Various cognitive strategies and metacognitive practices can help minimize the impact of bias on decision making and reduce the frequency of diagnostic errors. Knowing one’s limitations and possibilities in interpreting radiation research, as well as understanding the role of the radiologist in the formation of the final diagnosis and, accordingly, in the fate of the patient, can lead to a more thoughtful analysis of images and clinical information and improve the quality of the diagnostic decision-making process.

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