The underlying structure of the English Cancer Patient Experience Survey: Factor analysis to support survey reporting and design

• Published in: Cancer medicine (Malden, MA) MA), 2022-01, Vol.11 (1), p.3-20
• Main Authors: Gomez‐Cano, Mayam, Lyratzopoulos, Georgios, Campbell, John L., Elliott, Marc, Abel, Gary
• Format: Article
• Language: English
• Subjects: Cancer; Chemotherapy; Clinical Cancer Research; Clinical nursing; Eigenvalues; Employment; Factor analysis; Factor Analysis, Statistical; Health care; health services administration; Humans; indicators; Neoplasms - psychology; Neoplasms - therapy; Nurse specialists; oncology; patient experience; Patient Outcome Assessment; Patients; Performance management; Polls & surveys; psycho‐oncology; Quantitative psychology; Response rates; survey; surveys and questionnaires
• ISSN: 2045-7634; 2045-7634
• DOI: 10.1002/cam4.4325

Background The English Cancer Patient Experience Survey (CPES) is a regularly conducted survey measuring the experience of cancer patients. We studied the survey's underlying structure using factor analysis to identify potential for improvements in reporting or questionnaire design. Methods Cancer Patient Experience Survey 2015 respondents (n = 71,186, response rate 66%) were split into two random subgroups. Using exploratory factor analysis (EFA) on the first subgroup, we identified the survey's latent structure. EFA was then applied to 12 sets of items. A first (“core”) set was formed by questions that applied to all participants. The subsequent sets contained the “core set” plus questions corresponding to specific care pathways/patient groups. We used confirmatory factor analysis (CFA) on the second data subgroup for cross‐validation. Results The EFA suggested that five latent factors underlie the survey's core questions. Analysis on the remaining 11 care pathway/patient group items also indicated the same five latent factors, although additional factors were present for questions applicable to patients with an overnight stay or those accessing specialist nursing. The five factors models had an excellent fit (comparative fit index = 0.95, root mean square error of approximation = 0.045 for core set of questions). Items loading on each factor generally corresponded to a specific section or subsection of the questionnaire. CFA findings were concordant with the EFA patterns. Conclusion The findings suggest five coherent underlying sub‐constructs relating to different aspects of cancer health care. The findings support the construction of evidence‐based composite indicators for different domains of experience and provide options for survey re‐design. The underlying structure of the Cancer Patient experience Survey comprises five major factors. These include shared decisions; care coordination; diagnostic care; timely tests; and aftercare. Our results support the current survey structure, but provide options to guide survey redesign.