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

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.

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Probability and loss: two sides of the risk assessment coin

The Psychiatrist ◽

10.1192/pb.bp.110.033910 ◽

2011 ◽

Vol 35 (11) ◽

pp. 413-418 ◽

Cited By ~ 11

Author(s):

Matthew M. Large ◽

Olav B. Nielssen

Keyword(s):

Mental Health ◽

Risk Assessment ◽

Decision Making ◽

Clinical Decision Making ◽

Clinical Decision ◽

The Other ◽

Current Form ◽

Mental Health Settings ◽

Future Harm ◽

Two Sides

SummaryRisk assessment has been widely adopted in mental health settings in the hope of preventing harms such as violence to others and suicide. However, risk assessment in its current form is mainly concerned with the probability of adverse events, and does not address the other component of risk – the extent of the resulting loss. Although assessments of the probability of future harm based on actuarial instruments are generally more accurate than the categorisations made by clinicians, actuarial instruments are of little assistance in clinical decision-making because there is no instrument that can estimate the probability of all the harms associated with mental illness, or estimate the extent of the resulting losses. The inability of instruments to distinguish between the risk of common but less serious harms and comparatively rare catastrophic events is a particular limitation of the value of risk categorisations. We should admit that our ability to assess risk is severely limited, and make clinical decisions in a similar way to those in other areas of medicine – by informed consideration of the potential consequences of treatment and non-treatment.

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Genomic screening and genomic diagnostic testing—two very different kettles of fish

Genome Medicine ◽

10.1186/s13073-019-0696-9 ◽

2019 ◽

Vol 11 (1) ◽

Cited By ~ 2

Author(s):

Leslie G. Biesecker

Keyword(s):

Decision Making ◽

Clinical Decision Making ◽

Diagnostic Testing ◽

Clinical Decision ◽

Bayes Theorem ◽

Genomic Testing ◽

Test Results ◽

Correct Interpretation ◽

Genomic Test ◽

Genomic Screening

AbstractGenomic testing can be misunderstood as being determinative, when in reality it is the same as all other tests and context is essential for its correct interpretation. Two hypothetical cases of testing for Marfan syndrome demonstrate how clinicians should contextualize genomic test results and the implementation of Bayes theorem in clinical decision-making.

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Health record systems that meet clinical needs

Italian Journal of Medicine ◽

10.4081/itjm.2012.248 ◽

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.

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Integration of germline multigene panel testing into breast and gynecologic oncology clinics.

Journal of Clinical Oncology ◽

10.1200/jco.2020.39.28_suppl.164 ◽

2021 ◽

Vol 39 (28_suppl) ◽

pp. 164-164

Author(s):

Mariella Tejada ◽

June YiJuan Hou ◽

Katherine D. Crew ◽

Melissa Kate Accordino ◽

Kevin Kalinsky ◽

...

Keyword(s):

Breast Cancer ◽

Decision Making ◽

Genetic Testing ◽

Clinical Decision Making ◽

Genetic Test ◽

Gynecologic Oncology ◽

Clinical Decision ◽

Test Results ◽

Panel Testing ◽

Genetic Test Results

164 Background: Germline genetic testing plays an important role in informing cancer screening and risk-reducing strategies, as well as treatment decisions with PARP inhibitors for BRCA-associated malignancies. Referrals to clinical genetics for pre-test counseling and results disclosure can be delayed due to financial and logistical barriers, which may ultimately delay clinical decision-making. Our study objective was to understand patient attitudes, knowledge, and anxiety/distress with point-of-care (POC) genetic testing in breast and gynecologic oncology clinics. Methods: We enrolled patients with early-stage breast cancer undergoing neoadjuvant treatment, metastatic breast cancer, ovarian cancer, or endometrial cancer undergoing POC multigene panel testing with their primary oncologist, rather than a genetic counselor. Pre-test counseling came from discussion with their primary oncologist. Participants completed a survey at time of genetic testing and one after return of genetic test results. Validated measures of genetic testing knowledge, cancer-related distress, and attitudes towards genetic testing were included. Descriptive statistics were generated for all data collected and paired t-tests were conducted for baseline and follow-up comparisons. Results: We enrolled 106 subjects, of which 97 completed the baseline survey. All participants were female with a mean age of 61.5 years (SD 13.5). The cohort consisted of participants with the following tumor types: 80 breast, 2 ovarian, and 16 endometrial. Almost 44% of women identified as Hispanic/Latina, 55% had highest level of education of community/technical college or less, and 51.2% reported annual incomes of less than $50,000. Forty-seven percent of participants had adequate baseline genetic testing knowledge scores (defined as at least 50% correct responses). A majority of participants (86.6%) had positive attitudes toward undergoing genetic testing. Results of genetic testing revealed 11 participants (11.3%) with pathogenic or likely pathogenic variants (of which 36.3% were in BRCA1/2), 25 (25.8%) with variants of unknown significance (VUS), and 61 (62.9%) with benign or likely benign results. The mean cancer-related distress score (scale from 15 to 60, higher score indicates higher levels of distress) was 32.78 (SD 9.74) at baseline and 26.5 (SD 8.9) after receiving genetic testing results (p = 0.002). Genetic test results informed cancer treatment decisions regarding medications and surgery in 15% and 13% of patients, respectively, the majority of which were breast cancer patients. Conclusions: As genetic testing is more frequently used for clinical decision-making it is important to develop ways to efficiently integrate POC testing in the oncology clinics. We demonstrated that POC genetic testing for breast and gynecologic cancers is feasible and can inform clinical decision-making.

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Dedicated Education Unit: Improving graduating nursing students’ preparedness for practice

Journal of Nursing Education and Practice ◽

10.5430/jnep.v11n1p59 ◽

2020 ◽

Vol 11 (1) ◽

pp. 59

Author(s):

Persephone Vargas ◽

Kimberly Dimino ◽

Spencer Mullen

Keyword(s):

Decision Making ◽

Nursing Students ◽

Test Scores ◽

Clinical Decision Making ◽

Clinical Decision ◽

Test Results ◽

Dedicated Education Unit ◽

Self Confidence ◽

Post Test ◽

Readiness For Practice

Background and Objective: Majority of new graduate nurses are not adequately prepared to assume the dynamic and complex role of today’s professional nurse. The Dedicated Education Unit (DEU) is a clinical teaching model developed in response to the limitations of traditional clinical model (TCM). The aim of the study is to examine the readiness for practice and level of confidence in clinical decision making among graduating nursing students in the DEU and compare it with the students in the TCM.Methods: A pre-test/post-test design was used. The Casey-Fink Readiness for Practice was utilized in the pre and post-test surveys and the Nursing Anxiety and Self-Confidence in Clinical Decision-Making was used in the post test. Data were analyzed in aggregate and pre-test scores were compared to post-test scores at the cohort level using t-test.Results: The pre-test results showed no significant difference between the DEU and TCM groups. However, the post-test results showed higher levels of readiness for practice and higher self-confidence and lower anxiety in clinical decision making among the DEU students.Conclusions: The study provides evidence on the impact of the DEU in providing graduating nursing students with high quality clinical education to better prepare them for practice.

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

BMJ Simulation and Technology Enhanced Learning ◽

10.1136/bmjstel-2017-000217 ◽

2017 ◽

Vol 4 (2) ◽

pp. 92-94 ◽

Cited By ~ 1

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.

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Modelling in Clinical Practice with Web Services and BPEL

E-Business Models, Services and Communications ◽

10.4018/978-1-59904-831-4.ch010 ◽

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.

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TPGen: Prescription Generation Using Knowledge-guided Translator

10.21203/rs.3.rs-453032/v1 ◽

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

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A stepwise approach to implementing pharmacogenetic testing in the primary care setting

Pharmacogenomics ◽

10.2217/pgs-2019-0053 ◽

2019 ◽

Vol 20 (15) ◽

pp. 1103-1112 ◽

Cited By ~ 3

Author(s):

Kristin Wiisanen Weitzel ◽

Benjamin Q Duong ◽

Meghan J Arwood ◽

Aniwaa Owusu-Obeng ◽

Noura S Abul-Husn ◽

...

Keyword(s):

Primary Care ◽

Decision Making ◽

Clinical Decision Making ◽

Clinical Decision ◽

Primary Care Providers ◽

Test Results ◽

Implementation Barriers ◽

Pharmacogenetic Testing ◽

Stepwise Approach ◽

Test Ordering

Pharmacogenetic testing can help identify primary care patients at increased risk for medication toxicity, poor response or treatment failure and inform drug therapy. While testing availability is increasing, providers are unprepared to routinely use pharmacogenetic testing for clinical decision-making. Practice-based resources are needed to overcome implementation barriers for pharmacogenetic testing in primary care.The NHGRI’s IGNITE I Network (Implementing GeNomics In pracTicE; www.ignite-genomics.org ) explored practice models, challenges and implementation barriers for clinical pharmacogenomics. Based on these experiences, we present a stepwise approach pharmacogenetic testing in primary care: patient identification; pharmacogenetic test ordering; interpretation and application of test results, and patient education. We present clinical factors to consider, test-ordering processes and resources, and provide guidance to apply test results and counsel patients. Practice-based resources such as this stepwise approach to clinical decision-making are important resources to equip primary care providers to use pharmacogenetic testing.

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