Primary care practitioners' priorities for improving the timeliness of cancer diagnosis in primary care: a European cluster-based analysis.

Neves, Ana Luisa; Esteva, Magdalena; Hoffman, Robert; Harris, Michael (2023). Primary care practitioners' priorities for improving the timeliness of cancer diagnosis in primary care: a European cluster-based analysis. BMC health services research, 23(1), p. 997. BioMed Central 10.1186/s12913-023-09891-w

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BACKGROUND

Diagnosing cancer at an early stage increases the likelihood of survival, and more advanced cancers are more difficult to treat successfully. Primary care practitioners (PCPs) play a key role in timely diagnosis of cancer. PCPs' knowledge of their own patient populations and health systems could help improve the planning of more effective approaches to earlier cancer recognition and referral. How PCPs act when faced with patients who may have cancer is likely to depend on how their health systems are organised, and this may be one explanation for the wide variation on cancer survival rates across Europe.

OBJECTIVES

To identify and characterise clusters of countries whose PCPs perceive the same factors as being important in improving the timeliness of cancer diagnosis.

METHODS

A cluster analysis of qualitative data from an online survey was carried out. PCPs answered an open-ended survey question on how the speed of diagnosis of cancer in primary care could be improved. Following coding and thematic analysis, we identified the number of times per country that an item in a theme was mentioned. k-means clustering identified clusters of countries whose PCPs perceived the same themes as most important. Post-hoc testing explored differences between these clusters.

SETTING

Twenty-five primary care centres in 20 European countries. Each centre was asked to recruit at least 50 participants.

PARTICIPANTS

Primary care practitioners of each country.

RESULTS

In all, 1,351 PCPs gave free-text answers. We identified eighteen themes organising the content of the responses. Based on the frequency of the themes, k-means clustering identified three groups of countries. There were significant differences between clusters regarding the importance of: access to tests (p = 0.010); access to specialists (p = 0.014), screening (p < 0.001); and finances, quotas & limits (p < 0.001).

CONCLUSIONS

Our study identified three distinct clusters of European countries within which PCPs had similar views on the factors that would improve the timeliness of cancer diagnosis. Further work is needed to understand what it is about the clusters that have produced these patterns, allowing healthcare systems to share best practice and to reduce disparities.

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