Collective Intelligence Increases Diagnostic Accuracy in a General Practice Setting.

Blanchard, Matthew D; Herzog, Stefan M; Kämmer, Juliane E; Zöller, Nikolas; Kostopoulou, Olga; Kurvers, Ralf H J M (2024). Collective Intelligence Increases Diagnostic Accuracy in a General Practice Setting. Medical decision making, 44(4), pp. 451-462. Sage 10.1177/0272989X241241001

[img]
Preview
Text
blanchard-et-al-2024-collective-intelligence-increases-diagnostic-accuracy-in-a-general-practice-setting-.pdf - Published Version
Available under License Creative Commons: Attribution (CC-BY).

Download (2MB) | Preview

BACKGROUND

General practitioners (GPs) work in an ill-defined environment where diagnostic errors are prevalent. Previous research indicates that aggregating independent diagnoses can improve diagnostic accuracy in a range of settings. We examined whether aggregating independent diagnoses can also improve diagnostic accuracy for GP decision making. In addition, we investigated the potential benefit of such an approach in combination with a decision support system (DSS).

METHODS

We simulated virtual groups using data sets from 2 previously published studies. In study 1, 260 GPs independently diagnosed 9 patient cases in a vignette-based study. In study 2, 30 GPs independently diagnosed 12 patient actors in a patient-facing study. In both data sets, GPs provided diagnoses in a control condition and/or DSS condition(s). Each GP's diagnosis, confidence rating, and years of experience were entered into a computer simulation. Virtual groups of varying sizes (range: 3-9) were created, and different collective intelligence rules (plurality, confidence, and seniority) were applied to determine each group's final diagnosis. Diagnostic accuracy was used as the performance measure.

RESULTS

Aggregating independent diagnoses by weighing them equally (i.e., the plurality rule) substantially outperformed average individual accuracy, and this effect increased with increasing group size. Selecting diagnoses based on confidence only led to marginal improvements, while selecting based on seniority reduced accuracy. Combining the plurality rule with a DSS further boosted performance.

DISCUSSION

Combining independent diagnoses may substantially improve a GP's diagnostic accuracy and subsequent patient outcomes. This approach did, however, not improve accuracy in all patient cases. Therefore, future work should focus on uncovering the conditions under which collective intelligence is most beneficial in general practice.

HIGHLIGHTS

We examined whether aggregating independent diagnoses of GPs can improve diagnostic accuracy.Using data sets of 2 previously published studies, we composed virtual groups of GPs and combined their independent diagnoses using 3 collective intelligence rules (plurality, confidence, and seniority).Aggregating independent diagnoses by weighing them equally substantially outperformed average individual GP accuracy, and this effect increased with increasing group size.Combining independent diagnoses may substantially improve GP's diagnostic accuracy and subsequent patient outcomes.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Intensive Care, Emergency Medicine and Anaesthesiology (DINA) > University Emergency Center

UniBE Contributor:

Kämmer, Juliane Eva

Subjects:

600 Technology > 610 Medicine & health

ISSN:

1552-681X

Publisher:

Sage

Language:

English

Submitter:

Pubmed Import

Date Deposited:

12 Apr 2024 15:34

Last Modified:

18 May 2024 00:15

Publisher DOI:

10.1177/0272989X241241001

PubMed ID:

38606597

Uncontrolled Keywords:

collective intelligence decision support systems diagnostic accuracy general practice medical diagnostics wisdom of crowds

BORIS DOI:

10.48350/195923

URI:

https://boris.unibe.ch/id/eprint/195923

Actions (login required)

Edit item Edit item
Provide Feedback