Constructing a clinical decision-making framework for image-guided radiotherapy using a Bayesian Network

A decision-making framework for image-guided radiotherapy (IGRT) is being developed using a Bayesian Network (BN) to graphically describe, and probabilistically quantify, the many interacting factors that are involved in this complex clinical process. Outputs of the BN will provide decision-support for radiation therapists to assist them to make correct inferences relating to the likelihood of treatment delivery accuracy for a given image-guided set-up correction. The framework is being developed as a dynamic object-oriented BN, allowing for complex modelling with specific sub-regions, as well as representation of the sequential decision-making and belief updating associated with IGRT. A prototype graphic structure for the BN was developed by analysing IGRT practices at a local radiotherapy department and incorporating results obtained from a literature review. Clinical stakeholders reviewed the BN to validate its structure. The BN consists of a sub-network for evaluating the accuracy of IGRT practices and technology. The directed acyclic graph (DAG) contains nodes and directional arcs representing the causal relationship between the many interacting factors such as tumour site and its associated critical organs, technology and technique, and inter-user variability. The BN was extended to support on-line and off-line decision-making with respect to treatment plan compliance. Following conceptualisation of the framework, the BN will be quantified. It is anticipated that the finalised decision-making framework will provide a foundation to develop better decision-support strategies and automated correction algorithms for IGRT.

Effective clinical decision-making from practice-based evidence

This is an ongoing research investigating the use of health information technologies (HIT) to improve clinical decision-making processes. Effective and timely clinical decision-making can lead to positive improvements in patient’s health outcome...

Effects of age on aerobic capacity in heart failure patients under beta-blocker therapy: Possible impact in clinical decision-making?

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

ESMO Consensus Guidelines for management of patients with colon and rectal cancer. A personalized approach to clinical decision making

Colorectal cancer (CRC) is the most common tumour type in both sexes combined in Western countries. Although screening programmes including the implementation of faecal occult blood test and colonoscopy might be able to reduce mortality by removing precursor lesions and by making diagnosis at an earlier stage, the burden of disease and mortality is still high. Improvement of diagnostic and treatment options increased staging accuracy, functional outcome for early stages as well as survival. Although high quality surgery is still the mainstay of curative treatment, the management of CRC must be a multi-modal approach performed by an experienced multi-disciplinary expert team. Optimal choice of the individual treatment modality according to disease localization and extent, tumour biology and patient factors is able to maintain quality of life, enables long-term survival and even cure in selected patients by a combination of chemotherapy and surgery. Treatment decisions must be based on the available evidence, which has been the basis for this consensus conference-based guideline delivering a clear proposal for diagnostic and treatment measures in each stage of rectal and colon cancer and the individual clinical situations. This ESMO guideline is recommended to be used as the basis for treatment and management decisions.

The SAKK cancer-specific geriatric assessment (C-SGA): a pilot study of a brief tool for clinical decision-making in older cancer patients

BACKGROUND Recommendations from international task forces on geriatric assessment emphasize the need for research including validation of cancer-specific geriatric assessment (C-SGA) tools in oncological settings. The objective of this study was to evaluate the feasibility of the SAKK Cancer-Specific Geriatric Assessment (C-SGA) in clinical practice. METHODS A cross sectional study of cancer patients >=65 years old (N = 51) with pathologically confirmed cancer presenting for initiation of chemotherapy treatment (07/01/2009-03/31/2011) at two oncology departments in Swiss canton hospitals: Kantonsspital Graubunden (KSGR N = 25), Kantonsspital St. Gallen (KSSG N = 26). Data was collected using three instruments, the SAKK C-SGA plus physician and patient evaluation forms. The SAKK C-SGA includes six measures covering five geriatric assessment domains (comorbidity, function, psychosocial, nutrition, cognition) using a mix of medical record abstraction (MRA) and patient interview. Five individual domains and one overall SAKK C-SGA score were calculated and dichotomized as below/above literature-based cut-offs. The SAKK C-SGA was evaluated by: patient and physician estimated time to complete, ease of completing, and difficult or unanswered questions. RESULTS Time to complete the patient questionnaire was considered acceptable by almost all (>=96%) patients and physicians. Patients reported slightly shorter times to complete the questionnaire than physicians (17.33 +/- 7.34 vs. 20.59 +/- 6.53 minutes, p = 0.02). Both groups rated the patient questionnaire as easy/fairly easy to complete (91% vs. 84% respectively, p = 0.14) with few difficult or unanswered questions. The MRA took on average 8.32 +/- 4.72 minutes to complete. Physicians (100%) considered time to complete MRA acceptable, 96% rated it as easy/fairly easy to complete. Individual study site populations differed on health-related characteristics (excellent/good physician-rated general health KSGR 71% vs. KSSG 32%, p = 0.007). The overall mean C-SGA score was 2.4 +/- 1.12. Patients at KSGR had lower C-SGA scores (2.00 +/- 1.19 vs. 2.81 +/- 0.90, p = 0.009) and a smaller proportion (28% vs.65%, p = 0.008) was above the C-SGA cut-off score compared to KSSG. CONCLUSIONS These results suggest the SAKK C-SGA is a feasible practical tool for use in clinical practice. It demonstrated discriminative ability based on objective geriatric assessment measures, but additional investigations on use for clinical decision-making are warranted. The SAKK C-SGA also provides important usable domain information for intervention to optimize outcomes in older cancer patients.

Clinical decision-making and myocardial viability: current perspectives

Not all myocardium involved in a myocardial infarction is dead or irreversibly damaged. The balance between the amount of scar and live tissue, and the nature of the live tissue, determine the likelihood that contractile function will improve after revascularisation. This improvement (which defines viability) may be predicted with about 80% accuracy using several techniques. This review examines the determinants of functional recovery and how they may be integrated in making decisions regarding revascularisation. (Intern Med J 2005; 35: 118–125)

The influence of patient's age on clinical decision-making about coronary heart disease in the USA and the UK

This paper examines UK and US primary care doctors' decision-making about older (aged 75 years) and midlife (aged 55 years) patients presenting with coronary heart disease (CHD). Using an analytic approach based on conceptualising clinical decision-making as a classification process, it explores the ways in which doctors' cognitive processes contribute to ageism in health-care at three key decision points during consultations. In each country, 56 randomly selected doctors were shown videotaped vignettes of actors portraying patients with CHD. The patients' ages (55 or 75 years), gender, ethnicity and social class were varied systematically. During the interviews, doctors gave free-recall accounts of their decision-making. The results do not establish that there was substantial ageism in the doctors' decisions, but rather suggest that diagnostic processes pay insufficient attention to the significance of older patients' age and its association with the likelihood of co-morbidity and atypical disease presentations. The doctors also demonstrated more limited use of 'knowledge structures' when diagnosing older than midlife patients. With respect to interventions, differences in the national health-care systems rather than patients' age accounted for the differences in doctors' decisions. US doctors were significantly more concerned about the potential for adverse outcomes if important diagnoses were untreated, while UK general practitioners cited greater difficulty in accessing diagnostic tests.

Classifying clinical decision making:a unifying approach

This is the first of two linked papers exploring decision making in nursing which integrate research evidence from different clinical and academic disciplines. Currently there are many decision-making theories, each with their own distinctive concepts and terminology, and there is a tendency for separate disciplines to view their own decision-making processes as unique. Identifying good nursing decisions and where improvements can be made is therefore problematic, and this can undermine clinical and organizational effectiveness, as well as nurses' professional status. Within the unifying framework of psychological classification, the overall aim of the two papers is to clarify and compare terms, concepts and processes identified in a diversity of decision-making theories, and to demonstrate their underlying similarities. It is argued that the range of explanations used across disciplines can usefully be re-conceptualized as classification behaviour. This paper explores problems arising from multiple theories of decision making being applied to separate clinical disciplines. Attention is given to detrimental effects on nursing practice within the context of multidisciplinary health-care organizations and the changing role of nurses. The different theories are outlined and difficulties in applying them to nursing decisions highlighted. An alternative approach based on a general model of classification is then presented in detail to introduce its terminology and the unifying framework for interpreting all types of decisions. The classification model is used to provide the context for relating alternative philosophical approaches and to define decision-making activities common to all clinical domains. This may benefit nurses by improving multidisciplinary collaboration and weakening clinical elitism.

Classifying clinical decision making:interpreting nursing intuition, heuristics and medical diagnosis

This is the second of two linked papers exploring decision making in nursing. The first paper, 'Classifying clinical decision making: a unifying approach' investigated difficulties with applying a range of decision-making theories to nursing practice. This is due to the diversity of terminology and theoretical concepts used, which militate against nurses being able to compare the outcomes of decisions analysed within different frameworks. It is therefore problematic for nurses to assess how good their decisions are, and where improvements can be made. However, despite the range of nomenclature, it was argued that there are underlying similarities between all theories of decision processes and that these should be exposed through integration within a single explanatory framework. A proposed solution was to use a general model of psychological classification to clarify and compare terms, concepts and processes identified across the different theories. The unifying framework of classification was described and this paper operationalizes it to demonstrate how different approaches to clinical decision making can be re-interpreted as classification behaviour. Particular attention is focused on classification in nursing, and on re-evaluating heuristic reasoning, which has been particularly prone to theoretical and terminological confusion. Demonstrating similarities in how different disciplines make decisions should promote improved multidisciplinary collaboration and a weakening of clinical elitism, thereby enhancing organizational effectiveness in health care and nurses' professional status. This is particularly important as nurses' roles continue to expand to embrace elements of managerial, medical and therapeutic work. Analysing nurses' decisions as classification behaviour will also enhance clinical effectiveness, and assist in making nurses' expertise more visible. In addition, the classification framework explodes the myth that intuition, traditionally associated with nurses' decision making, is less rational and scientific than other approaches.