Diagnostic Decision Making in Oncology: Creating Shared Knowledge and Managing Complexity

Alby, Francesca; Zucchermaglio, Cristina; Baruzzo, Mattia

doi:10.1080/10749039.2014.981642

Cited by 17 publications

(22 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Final analysis included 15 studies, as indicated by the PRISMA chart (Fig. 1) [22–36]. Characteristics of the included studies are presented below (Table 1).…”

Section: Resultsmentioning

confidence: 99%

“…Aggregation of these individual responses may require information technology to generate a collective intelligence, or may require manual efforts, such as “counting votes,” from the study team to synthesize a collective decision or output. Among the included studies, eight used group processes [22, 23, 25, 30–32, 35, 36], six used individual processes [24, 27–29, 33, 34], and one compared the two [26].…”

Section: Resultsmentioning

confidence: 99%

“…Activities such as case conferences or morning rounds that require participants to be present and discuss a case employ in-person synthesis. Of the eight studies that used group processes to generate collective intelligence, the majority (5/8) used in-person synthesis to generate a collective intelligence [22, 23, 25, 31, 32]. One study of the eight using group processes compared in-person and IT-enabled collective intelligence [30].…”

Section: Resultsmentioning

confidence: 99%

“…The final collective output has the potential to inform patient care decisions when it is available to participating individuals for review. For example, in group processes of collective intelligence (8 studies) [22, 23, 25, 30–32, 35, 36], the contributing group members are aware of the final results of consensus as they have participated in the consensus-making. On the other hand, through individual processes, the contributors may not be aware of the final decision-making output.…”

Section: Resultsmentioning

confidence: 99%

See 3 more Smart Citations

Collective intelligence in medical decision-making: a systematic scoping review

Radcliffe

Lyson

Barr‐Walker

et al. 2019

BMC Med Inform Decis Mak

View full text Add to dashboard Cite

Background Collective intelligence, facilitated by information technology or manual techniques, refers to the collective insight of groups working on a task and has the potential to generate more accurate information or decisions than individuals can make alone. This concept is gaining traction in healthcare and has potential in enhancing diagnostic accuracy. We aim to characterize the current state of research with respect to collective intelligence in medical decision-making and describe a framework for diverse studies in this topic. Methods For this systematic scoping review, we conducted a systematic search for published literature using PubMed, Embase, Web of Science, and CINAHL on August 8, 2017. We included studies that combined the insights of two or more medical experts to make decisions related to patient care. Studies that examined medical decisions such as diagnosis, treatment, and management in the context of an actual or theoretical patient case were included. We include studies of complex medical decision-making rather than identification of a visual finding, as in radiology or pathology. We differentiate between medical decisions, in which synthesis of multiple types of information is required over time, and studies of radiological scans or pathological specimens, in which objective identification of a visual finding is performed. Two reviewers performed article screening, data extraction, and final inclusion for analysis. Results Of 3303 original articles, 15 were included. Each study examined the medical decisions of two or more individuals; however, studies were heterogeneous in their methods and outcomes. We present a framework to characterize these diverse studies, and future investigations, based on how they operationalize collective intelligence for medical decision-making: 1) how the initial decision task was completed (group vs. individual), 2) how opinions were synthesized (information technology vs. manual vs. in-person), and 3) the availability of collective intelligence to participants. Discussion Collective intelligence in medical decision-making is gaining popularity to advance medical decision-making and holds promise to improve patient outcomes. However, heterogeneous methods and outcomes make it difficult to assess the utility of collective intelligence approaches across settings and studies. A better understanding of collective intelligence and its applications to medicine may improve medical decision-making. Electronic supplementary material The online version of this article (10.1186/s12911-019-0882-0) contains supplementary material, which is available to authorized users.

show abstract

“…Final analysis included 15 studies, as indicated by the PRISMA chart (Fig. 1) [22–36]. Characteristics of the included studies are presented below (Table 1).…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

Collective intelligence in medical decision-making: a systematic scoping review

Radcliffe

Lyson

Barr‐Walker

et al. 2019

BMC Med Inform Decis Mak

View full text Add to dashboard Cite

show abstract

“…If this can be seen as evidence of medical dominance and paternalistic approach adopting certain healthcare ethical frameworks, some authors hypothesise that it could be an intrinsic feature of the medical enterprise and of the doctor‐patient institutional interaction, since the ongoing activities in the consultation necessarily rely on expert medical knowledge (Alby et al . , Pilnick and Dingwall , ten Have , Zucchermaglio and Alby ).…”

Section: Patients’ Participation In Treatment Recommendationmentioning

confidence: 98%

Managing risk and patient involvement in choosing treatment for cancer: an analysis of two communication practices

Alby

Fatigante

Zucchermaglio

2017

Sociology Health & Illness

Self Cite

View full text Add to dashboard Cite

Drawing on conversation analyses of oncology consultations collected in Italy, the article examines the communication practices used to recommend treatments. We found that the oncologist formulates the treatment recommendation (TR) for high-risk patients in terms of a 'mandatory' choice and for low-risk patients as an 'optional' type of decision. In the first case the doctor presses to reach a decision during the visit while in the second case leaves the decision open-ended. Results show that high-risk patients have less time to decide, are pressured towards choosing an option, but have more opportunities for involvement in TR during the visit. Low-risk patients instead have more time and autonomy to make a choice, but they are also less involved in the decision-making in the visit time. Moreover, we document that TR is organised through sequential activities in which the oncologist informs the patient of alternative therapeutic options while at the same time building a case for the kind of treatment she/he believes to be best for the patient's health. We suggest that in this field risk plays a key role in decision-making which should be better understood with further studies and taken into account in the debate on shared decision-making and patient-centred communication.

show abstract