Factors that Empower GPs for Early Cancer Diagnosis. A Delphi Study Protocol

Robert Hoffman, Mette Brekke, George Tzanis, Davorina Petek, Michael Harris, Emmanouil Smyrnakis

Keywords: cancer; empowerment; General Practice; Primary Health Care; Delphi; Diagnosis delay; Decision making


survival rates vary widely in Europe, causing considerable additional mortality in some countries. One possible explanation is the differing levels of empowerment of GPs when faced with patients that could have cancer.

Research questions:

What are the factors that affect GPs’ empowerment in making a timely diagnosis of cancer in their patients?


We will use a Delphi process, which allows easy access to experts who are geographically distant, giving them the opportunity to have their opinions taken into account. Up to 30 Örenäs Research Group countries will be involved in this multi-centre study. Local study leads will recruit 5 panellists from each country. At least 3 panellists will be working GPs and the others will be GP academics. Representation of both genders, rural and urban practice, and working experience, will also be requested.
The project group produced a list of factors that they believe affect GPs’ empowerment in making a timely cancer diagnosis. The list will be used in a 3-round Delphi process, with a 9-point Likert scale for participants to indicate the clinical relevance of each factor in a primary care setting. Factors will be included in the final list if the mean Likert score minus one SD exceeds 5 in Round 3.


In a pilot round, all Örenas Research Group members were invited to study the initial list of 80 factors, score them and suggest additions. After omitting those with the lowest scores and merging those with similar meaning, the research team produced a final list of 52 factors. This list will be the basis of the Delphi survey.


We expect that the results will identify priorities and specific actions to help increase GPs’ empowerment in making a timely diagnosis of cancer in their patients.

Points for discussion:

How can we interpret the results of the study for each individual European country?

How can we use the results of the study to reduce inequalities in cancer survival rates in European countries?