Dataset Information

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

ABSTRACT:

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.

SUBMITTER: Radcliffe K

PROVIDER: S-EPMC6688241 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Publications

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

Radcliffe Kate K Lyson Helena C HC Barr-Walker Jill J Sarkar Urmimala U

BMC medical informatics and decision making 20190809 1

<h4>Background</h4>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 descri ...[more]

PMID: 31399099

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Project description:ObjectivesCognitive and other biases can influence the quality of healthcare decision making. While substantial research has explored how biases can lead to diagnostic or other errors in medicine, fewer studies have examined how they impact the decision making of other healthcare professionals. This scoping review aimed to identify and synthesise a broad range of research investigating whether decisions made by allied health professionals are influenced by cognitive, affective or other biases.Materials and methodsA systematic literature search was conducted in five electronic databases. Title, abstract and full text screening was undertaken in duplicate, using prespecified eligibility criteria designed to identify studies attempting to demonstrate the presence of bias when allied healthcare professionals make decisions. A narrative synthesis was undertaken, focussing on the type of allied health profession, type of decision, and type of bias reported within the included studies.ResultsThe search strategy identified 149 studies. Of these, 119 studies came from the field of psychology, with substantially fewer from social work, physical and occupational therapy, speech pathology, audiology and genetic counselling. Diagnostic and assessment decisions were the most common decision types, with fewer studies assessing treatment, prognostic or other clinical decisions. Studies investigated the presence of over 30 cognitive, affective and other decision making biases, including stereotyping biases, anchoring, and confirmation bias. Overall, 77% of the studies reported at least one outcome that represented the presence of a bias.ConclusionThis scoping review provides an overview of studies investigating whether decisions made by allied health professionals are influenced by cognitive, affective or other biases. Biases have the potential to seriously impact the quality, consistency and accuracy of decision making in allied health practice. The findings highlight a need for further research particularly in professional disciplines outside of psychology, using methods that reflect real life healthcare decision making.

Project description:BackgroundThe contribution of patients' non-medical characteristics to individual physicians' decision-making has attracted considerable attention, but little information is available on this topic in the context of collective decision-making. Medical decision-making at cancer centres is currently carried out using a collective approach, at MultiDisciplinary Team (MDT) meetings. The aim of this study was to determine how patients' non-medical characteristics are presented at MDT meetings and how this information may affect the team's final medical decisions.DesignObservations were conducted at a French Cancer Centre during MDT meetings at which non-standard cases involving some uncertainty were discussed from March to May 2014. Physicians' verbal statements and predefined contextual parameters were collected with a non-participant observational approach. Non numerical data collected in the form of open notes were then coded for quantitative analysis. Univariate and multivariate statistical analyses were performed.ResultsIn the final sample of patients' records included and discussed (N = 290), non-medical characteristics were mentioned in 32.8% (n = 95) of the cases. These characteristics corresponded to demographics in 22.8% (n = 66) of the cases, psychological data in 11.7% (n = 34), and relational data in 6.2% (n = 18). The patient's age and his/her "likeability" were the most frequently mentioned characteristics. In 17.9% of the cases discussed, the final decision was deferred: this outcome was positively associated with the patients' non-medical characteristics and with uncertainty about the outcome of the therapeutic options available.LimitationsThe design of the study made it difficult to draw definite cause-and-effect conclusions.ConclusionThe Social Representations approach suggests that patients' non-medical characteristics constitute a kind of tacit professional knowledge that may be frequently mobilised in physicians' everyday professional practice. The links observed between patients' attributes and the medical decisions made at these meetings show that these attributes should be taken into account in order to understand how medical decisions are reached in difficult situations of this kind.

Project description:BackgroundPublic health decision-making structures in England have transformed since the implementation of reforms in 2013, with responsibility for public health services and planning having shifted from the "health" boundary to local authority (LA; local government) control. This transformation may have interrupted flows of research evidence use in decision-making and introduced a new political element to public health decision-making. For generators of research evidence, understanding and responding to this new landscape and decision-makers' evidence needs is essential.MethodsWe conducted a systematic scoping review of the literature, drawing upon four databases and undertaking manual searching and citation tracking. Included studies were English-based, published in 2010 onwards, and were focused on public health decision-making, including the utilisation or underutilisation of research evidence use, in local (regional or sub-regional) areas. All studies presented empirical findings collected through primary research methods or through the reanalysis of existing primary data.ResultsFrom a total of 903 records, 23 papers from 21 studies were deemed to be eligible and were included for further data extraction. Three clear trends in evidence use were identified: (i) the primacy of local evidence, (ii) the important role of local experts in providing evidence and knowledge, and (iii) the high value placed on local evaluation evidence despite the varying methodological rigour. Barriers to the use of research evidence included issues around access and availability of applicable research evidence, and indications that the use of evidence could be perceived as a bureaucratic process. Two new factors resulting from reforms to public health structures were identified that potentially changed existing patterns of research evidence use and decision-making requirements: (i) greater emphasis among public health practitioners on the perceived uniqueness of LA areas and structures following devolution of public health into LAs and (ii) challenges introduced in responding to higher levels of local political accountability.ConclusionsThere is a need to better understand and respond to the evidence needs of decision-makers working in public health and to work more collaboratively in developing solutions to the underutilisation of research evidence in decision-making.

Project description:BACKGROUND:A range of evidence informs decision-making on innovation in health care, including formal research findings, local data and professional opinion. However, cultural and organisational factors often prevent the translation of evidence for innovations into practice. In addition to the characteristics of evidence, it is known that processes at the individual level influence its impact on decision-making. Less is known about the ways in which processes at the professional, organisational and local system level shape evidence use and its role in decisions to adopt innovations. METHODS:A systematic scoping review was used to review the health literature on innovations within acute and primary care and map processes at the professional, organisational and local system levels which influence how evidence informs decision-making on innovation. Stakeholder feedback on the themes identified was collected via focus groups to test and develop the findings. RESULTS:Following database and manual searches, 31 studies reporting primary qualitative data met the inclusion criteria: 24 were of sufficient methodological quality to be included in the thematic analysis. Evidence use in decision-making on innovation is influenced by multi-level processes (professional, organisational, local system) and interactions across these levels. Preferences for evidence vary by professional group and health service setting. Organisations can shape professional behaviour by requiring particular forms of evidence to inform decision-making. Pan-regional organisations shape innovation decision-making at lower levels. Political processes at all levels shape the selection and use of evidence in decision-making. CONCLUSIONS:The synthesis of results from primary qualitative studies found that evidence use in decision-making on innovation is influenced by processes at multiple levels. Interactions between different levels shape evidence use in decision-making (e.g. professional groups and organisations can use local systems to validate evidence and legitimise innovations, while local systems can tailor or frame evidence to influence activity at lower levels). Organisational leaders need to consider whether the environment in which decisions are made values diverse evidence and stakeholder perspectives. Further qualitative research on decision-making practices that highlights how and why different types of evidence come to count during decisions, and tracks the political aspects of decisions about innovation, is needed.

Dataset Information

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

Background

Methods

Results

Discussion

Publications

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

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