DOI: 10.5061/dryad.dz08kps5m
title: Research data on health facility-level factors that contribute to delayed diagnosis of cervical cancer

description: 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.
description: 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.
description: # Research data on Health Facility-Level Factors that Contribute to
 Delayed Diagnosis of Cervical Cancer
 [https://doi.org/10.5061/dryad.dz08kps5m](https://doi.org/10.5061/dryad.dz08kps5m) ## 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 &lt;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 &lt;2 weeks 2 2 weeks - 1 month 3 &gt; 1 month Time taken for Diagnostic Results Required 1 &lt;2 weeks 2 2 weeks - 1 month 3 &gt; 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