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Background: Patient complexity is often operationalized by counting multiple chronic conditions (MCC) without considering contextual factors that can affect patient risk for adverse outcomes.Objective: Our objective was to develop a conceptual model of complexity addressing gaps identified in a review of published conceptual models.Data Sources: We searched for English-language MEDLINE papers published between 1 January 2004 and 16 January 2014. Two reviewers independently evaluated abstracts and all authors contributed to the development of the conceptual model in an iterative process.Results: From 1606 identified abstracts, six conceptual models were selected. One additional model was identified through reference review. Each model had strengths, but several constructs were not fully considered: 1) contextual factors; 2) dynamics of complexity; 3) patients' preferences; 4) acute health shocks; and 5) resilience. Our Cycle of Complexity model illustrates relationships between acute shocks and medical events, healthcare access and utilization, workload and capacity, and patient preferences in the context of interpersonal, organizational, and community factors.Conclusions/implications: This model may inform studies on the etiology of and changes in complexity, the relationship between complexity and patient outcomes, and intervention development to improve modifiable elements of complex patients. [ABSTRACT FROM AUTHOR]

Personal autonomy is widely valued. Recognition of its vulnerability in health care contexts led to the inclusion of respect for autonomy as a key concern in biomedical ethics. The principle of respect for autonomy is usually associated with allowing or enabling patients to make their own decisions about which health care interventions they will or will not receive. In this paper, we suggest that a strong focus on decision situations is problematic, especially when combined with a tendency to stress the importance of patients' independence in choosing. It distracts attention from other important aspects of and challenges to autonomy in health care. Relational understandings of autonomy attempt to explain both the positive and negative implications of social relationships for individuals' autonomy. They suggest that many health care practices can affect autonomy by virtue of their effects not only on patients' treatment preferences and choices, but also on their self-identities, self-evaluations and capabilities for autonomy. Relational understandings de-emphasise independence and facilitate well-nuanced distinctions between forms of clinical communication that support and that undermine patients' autonomy. These understandings support recognition of the value of good patient-professional relationships and can enrich the specification of the principle of respect for autonomy. [ABSTRACT FROM AUTHOR]

A Complex Chronic Disease (CCD) is a condition involving multiple morbidities that requires the attention of multiple health care providers or facilities and possibly community (home)-based care. A patient with CCD presents to the health care system with unique needs, disabilities, or functional limitations. The literature on how to best support self-management efforts in those with CCD is lacking. With this paper, the authors present the case of an individual with diabetes and end-stage renal disease who is having difficulty with self-management. The case is discussed in terms of intervention effectiveness in the areas of prevention, addiction, and self-management of single diseases. Implications for research are discussed. [ABSTRACT FROM AUTHOR]

Widespread health service goals to improve consistency and safety in patient care have prompted considerable investment in the development of evidence-based clinical guidelines. Computerised decision support (CDS) systems have been proposed as a means to implement guidelines in practice. This paper discusses the general concept in oncology and presents an evaluation of a CDS system to support triple assessment (TA) in breast cancer care. Balanced-block crossover experiment and questionnaire study. One stop clinic for symptomatic breast patients. Twenty-four practising breast clinicians from United Kingdom National Health Service hospitals. A web-based CDS system. Clinicians made significantly more deviations from guideline recommendations without decision support (60 out of 120 errors without CDS; 16 out of 120 errors with CDS, P < 0.001). Ignoring minor deviations, 16 potentially critical errors arose in the no-decision-support arm of the trial compared with just one (P = 0.001) when decision support was available. Opinions of participating clinicians towards the CDS tool became more positive after they had used it (P < 0.025). The use of decision support capabilities in TA may yield significant measurable benefits for quality and safety of patient care. This is an important option for improving compliance with evidence-based practice guidelines. [ABSTRACT FROM AUTHOR]

The continued growth in the economic evaluation of healthcare over the past 25 years has led to a shortage of trained health economists globally, leading to a number of universities and/or national governments developing specialised health economics programmes to train more health economists. One of the common problems with many of these training programmes is that they only educate new health economists to the Masters level, and as such they are unable to cover the many skills needed by a successful health economist. Furthermore, government and industry interests have ensured that economic evaluation is a heavily regulated environment that gives little incentive to seek further education. These two related factors (under-education and over-regulation) have lead to a situation where economic evaluation methods may adversely limit innovation of therapeutics and devices in clinical areas that perform badly when evaluated on the cost per QALY scale. The good news, however, is that the tide is turning and theoretically sound adjustments (such as risk adjustments and stated preferences) to the current paradigm are now being considered. This, of cause, is just the tip of the iceberg with other important issues such as time preference and the endogeneity of preference remaining very much under-researched areas in health. This paper concludes that many of these real-world issues, such as patient preferences, can be avoided by using artificial objective functions such as cost per QALY, but this comes at the cost of irrelevance and the misallocation of resources. If we are to meet all of the future challenges in economic evaluation in healthcare then we must focus more on advanced education and far less on the regulation of health economists. [ABSTRACT FROM AUTHOR]