Research data on health facility-level factors that contribute to delayed diagnosis of cervical cancer

In Kenya, cervical cancer is the 2nd commonly diagnosed type of cancer and the top cause of cancer-related deaths among women. Globally, over 50% of cervical cancer diagnoses are made late, with this proportion rising to 80% in developing countries. Poor Health systems can cause delays in diagnosis, thus, this study focused on determining the health facility-level factors that contribute to delayed diagnosis among cervical cancer patients at the Kenyatta National Hospital (KNH). An analytical cross-sectional mixed method study was adopted to collect data on hospital and referral experiences from 139 cervical cancer patients systematically sampled at KNH, using a semi-structured questionnaire. Associations between the stage at diagnosis and hospital and referral experiences were tested using a logistic regression model at 95% Confidence Interval. 86 (61.9%) were diagnosed at advanced stages III and IV. The potential predictors for delayed diagnosis were; More number of hospital referral times (p-value=0.000), Facing referral challenges (p-value=0.041), Longer time taken for diagnosis appointment (p-value=0.059), and Longer time taken for diagnostic results (p-value=0.007) in the bivariate analysis. More number of hospital referral times (p-value=0.001) and longer time taken for diagnostic results (p-value=0.025), were significantly associated with delayed diagnosis of cervical cancer in the multivariate logistic regression test model. Referral challenges included misdiagnosis, cost of diagnosis, and prolonged diagnosis appointments. The study concluded that the cause of delays in diagnosis for most patients is due to poor health and referral systems and inadequate medical personnel and diagnosis equipment. This study recommends improving referral systems and encouraging partnerships to decentralize diagnostic centers and equipment and train more expertise on cervical cancer. Systematic sampling was used to select 139 cervical cancer patients diagnosed and receiving treatment at KNH, aged above 18, and diagnosed within the last one year since time of data collection. The study excluded patients whose medical records did not have clear staging information, those diagnosed with other cancer types, those with recurrent cervical cancer, those in palliative care, those with psychotic health issues, and those who were unwilling to participate in the study. The participants were interviewed using a semi-structured questionnaire, with questions regarding their hospital and referral experiences such as type of medical facility they visited first, number of hospitals visits they made before diagnosis, if they were referred to KNH, number of referral times, referral challenges they faced, and period taken to get diagnosis appointments and results. The key outcome of delayed diagnosis was stage at diagnosis, categorized as either; early (stages IA to IIB) or delayed (IIIA and IVC) diagnosis using the FIGO staging system. The stage at diagnosis was retrieved as stage of malignancy recorded by the doctor in the patients’ files using abstraction forms. Qualitative data was collected from 8 Key Informants including Medical and Radio Oncologists, Nurses, and Social Workers in audio recorded sessions, to provide in depth information. Statistical analysis was done via Stata 14.2. and the association between delayed diagnosis and health facility-level factors was determined by logistic regression test, at 95% Confidence Interval and Odds Ratios and P-Values were reported. Audio recordings for qualitative data were transcribed in verbatim, transcripts verified, then deductive thematic analysis conducted using NVIVO 14. # Research data on Health Facility-Level Factors that Contribute to Delayed Diagnosis of Cervical Cancer [doi.org](doi.org) ## Description of the data and file structure The data consists of 20 variables.  It is structured starting with socio-demographics, dependent variable, and then health facility-related variables.  The data was coded before analysis on Stata. The data also consists of qualitative data on the last two variables, as answered by the participants. Early diagnosis was defined to be stages IA to IIB and decoded as 0. In contrast, the Delayed diagnosis was defined as from stage IIIA  to IVB and was coded as 1 to allow for logistic regression analysis.  The variables were coded as follows; ``` Code Variable Condition Age in years Required 1 <40 2 40-49 3 50-59 4 60-69 5 70 and above Employment Status Required 1 Employed 2 Not employed First Medical Care visit Required 1 Private 2 Public 3 Other Number of Hospital visits Required 1 Once 2 Twice 3 3-4 times 4 5 times and above Referred        Required 1 Yes 2 No Number of Referral times   Not required if Previous answer is No 1 Once 2 Twice and above Referral Challenges Not required if Previous answer is No 1 Yes 2 No Time taken for Diagnosis Appointment Required 1 <2 weeks 2 2 weeks - 1 month 3 > 1 month Time taken for Diagnostic Results Required 1 <2 weeks 2 2 weeks - 1 month 3 > 1 month Hospital Reasons Required In your view, what are the hospital reasons that may contribute to delayed diagnosis? Recommendations Required What would you recommend? ``` ## Sharing/Access information N/A ## Code/Software n/a