Shifting reasons for older men remaining uncircumcised: Findings from a pre- and post-demand creation intervention among men aged 25-39 years in western Kenya.

Voluntary medical male circumcision (VMMC) reduces men's risk of acquiring Human immunodeficiency virus (HIV) through vaginal sex. However, VMMC uptake remains lowest among Kenyan men ages 25-39 years among whom the impact on reducing population-level HIV incidence was estimated to be greatest at the start of the study in 2014. We conducted a pre- and post-intervention survey as part of a cluster randomized controlled trial to determine the effect of two interventions (interpersonal communication (IPC) and dedicated service outlets (DSO), delivered individually or together) on improving VMMC uptake among men ages 25-39 years in western Kenya between 2014 and 2016. The study had three intervention arms and a control arm. In arm one, an IPC toolkit was used to address barriers to VMMC. In arm two, men were referred to DSO that were modified to address their preferences. Arm three combined the IPC and DSO. The control arm had standard of care. At baseline, uncircumcised men ranked the top three reasons for remaining uncircumcised. An IPC demand creation toolkit was used to address the identified barriers and men were referred for VMMC at study-designated facilities. At follow-up, those who remained uncircumcised were again asked to rank the top three reasons for not getting circumcised. There was inconsistency in ranking of reported barriers at pre- and post- intervention: 'time/venue not convenient' was ranked third at baseline and seventh at follow-up; 'too busy to go for circumcision' was tenth at baseline but second at follow-up, and concern about 'what I/family will eat' was ranked first at both baseline and follow-up, but the proportion reduced from 62% to 28%. Men ages 25-39 years cited a variety of logistical and psychosocial barriers to receiving VMMC. After exposure to IPC, most of these barriers shifted while some remained the same. Additional innovative interventions to address on-going and shifting barriers may help improve VMMC uptake among older men.

Pairwise fitting of piecewise mixed models for the joint modeling of multivariate longitudinal outcomes, in a randomized crossover trial.

Many statistical models have been proposed in the literature for the analysis of longitudinal data. One may propose to model two or more correlated longitudinal processes simultaneously, with a goal of understanding their association over time. Joint modeling is then required to carefully study the association structure among the outcomes as well as drawing joint inferences about the different outcomes. In this study, we sought to model the associations among six nutrition outcomes while circumventing the computational challenge posed by their clustered and high-dimensional nature. We analyzed data from a 2 × $\times$ 2 randomized crossover trial conducted in Kenya, to compare the effect of high-dose and low-dose iodine in household salt on systolic blood pressure (SBP) and diastolic blood pressure (DBP) in women of reproductive age and their household matching pair of school-aged children. Two additional outcomes, namely, urinary iodine concentration (UIC) in women and children were measured repeatedly to monitor the amount of iodine excreted through urine. We extended the model proposed by Mwangi et al. (2021, Communications in Statistics: Case Studies, Data Analysis and Applications, 7(3), 413-431) allowing flexible piecewise joint models for six outcomes to depend on separate random effects, which are themselves correlated. This entailed fitting 15 bivariate general linear mixed models and deriving inference for the joint model using pseudo-likelihood theory. We analyzed the outcomes separately and jointly using piecewise linear mixed-effects (PLME) model and further validated the results using current state-of-the-art Jones and Kenward methodology (JKME model) used for analyzing randomized crossover trials. The results indicate that high-dose iodine in salt significantly reduced blood pressure (BP) compared to low-dose iodine in salt. Estimates for the random effects and residual error components showed that SBP and DBP had strong positive correlation, with effect of the random slope indicating that significantly related outcomes are strongly associated in their evolution. There was a moderately strong inverse relationship between evolutions of UIC and BP both in women and children. These findings confirmed the original hypothesis that high-dose iodine salt has significant lowering effect on BP. We further sought to evaluate the performance of our proposed PLME model against the widely used JKME model, within the multivariate joint modeling framework through a simulation study mimicking a 2 × 2 $2\times 2$ crossover design. From our findings, the multivariate joint PLME model performed exceptionally well both in estimation of random-effects matrix (G) and Hessian matrix (H), allowing satisfactory model convergence during estimation. It allowed a more complex fit to the data with both random intercepts and slopes effects compared to the multivariate joint JKME model that allowed for random intercepts only. When a hierarchical viewpoint is adopted, in the sense that outcomes are specified conditionally upon random effects, the variance-covariance matrix of the random effects must be positive definite. In some cases, additional random effects could explain much variability in the data, thus improving precision in estimation of the estimands (effect size) parameters. The key highlight in this evaluation shows that multivariate joint JKME model is a powerful tool especially while fitting mixed models with random intercepts only, in crossover design settings. Addition of random slopes may lead to model complexities in most cases, resulting in unsatisfactory model convergence during estimation. To circumvent convergence pitfalls, extention of JKME model to PLME model allows a more flexible fit to the data (generated from crossover design settings), especially in the multivariate joint modeling framework.

Uptake and continuation of HIV pre-exposure prophylaxis among women of reproductive age in two health facilities in Kisumu County, Kenya.

INTRODUCTION: In 2020, Kenya had 19,000 new HIV infections among women aged 15+ years. Studies have shown sub-optimal oral pre-exposure prophylaxis (PrEP) use among sub-populations of women. We assessed the uptake and continuation of oral PrEP among women 15-49 years in two health facilities in Kisumu County, Kenya. METHODS: A retrospective cohort of 262 women aged 15-49 years, initiated into oral PrEP between 12 November 2019 and 31 March 2021, was identified from two health facilities in the urban setting of Kisumu County, Kenya. Data on baseline characteristics and oral PrEP continuation at months 1, 3 and 6 were abstracted from patient records and summarized using descriptive statistics. Missing data in the predictor variables were imputed within the joint modelling multiple imputation framework. Using logistic regression, we evaluated factors associated with the discontinuation of oral PrEP at month 1. RESULTS: Of the 66,054 women screened, 320 (0.5%) were eligible and 262 (82%) were initiated on oral PrEP. Uptake was higher among women 25-29 years as compared to those 15-24 years (77% vs. 33%). Oral PrEP continuation declined significantly with increasing duration of follow-up; 37% at month 1, 21% at month 3 and 12% at month 6 (p<0.05). In the adjusted analysis, women 15-24 years had lower adjusted odds of continuing at month 1 than women ≥25 years (adjusted odds ratio [aOR]: 0.41, 95% CI: 0.21-0.82). There was no association between being sero-discordant and continuation of oral PrEP at month 1 (aOR; 1.21, 95% CI 0.59-2.50). Women from the sub-county hospital were more likely to continue at month 1 of follow-up compared to women enrolled in the county referral hospital (aOR 5.11; 95% CI 2.24-11.70). CONCLUSIONS: The low eligibility for oral PrEP observed among women 15-49 years in an urban setting with high HIV prevalence calls for a review of the screening process to validate the sensitivity of the screening tool and its proper application. The low uptake and continuation among adolescent girls and young women underscores the need to identify and address specific patient- and facility-level barriers affecting different sub-populations at risk for HIV acquisition.

Handling missing data in a composite outcome with partially observed components: simulation study based on clustered paediatric routine data.

Composite scores are useful in providing insights and trends about complex and multidimensional quality of care processes. However, missing data in subcomponents may hinder the overall reliability of a composite measure. In this study, strategies for handling missing data in Paediatric Admission Quality of Care (PAQC) score, an ordinal composite outcome, were explored through a simulation study. Specifically, the implications of the conventional method employed in addressing missing PAQC score subcomponents, consisting of scoring missing PAQC score components with a zero, and a multiple imputation (MI)-based strategy, were assessed. The latent normal joint modelling MI approach was used for the latter. Across simulation scenarios, MI of missing PAQC score elements at item level produced minimally biased estimates compared to the conventional method. Moreover, regression coefficients were more prone to bias compared to standards errors. Magnitude of bias was dependent on the proportion of missingness and the missing data generating mechanism. Therefore, incomplete composite outcome subcomponents should be handled carefully to alleviate potential for biased estimates and misleading inferences. Further research on other strategies of imputing at the component and composite outcome level and imputing compatibly with the substantive model in this setting, is needed.

Pairwise joint modeling of clustered and high-dimensional outcomes with covariate missingness in pediatric pneumonia care.

Multiple outcomes reflecting different aspects of routine care are a common phenomenon in health care research. A common approach of handling such outcomes is multiple univariate analyses, an approach which does not allow for answering research questions pertaining to joint inference. In this study, we sought to study associations among nine pediatric pneumonia care outcomes spanning assessment, diagnosis and treatment domains of care, while circumventing the computational challenge posed by their clustered and high-dimensional nature and incompletely recorded covariates. We analyzed data from a cluster randomized trial conducted in 12 Kenyan hospitals. There were varying degrees of missingness in the covariates of interest, and these were multiply imputed using latent normal joint modeling. We used the pairwise joint modeling strategy to fit a correlated random effects joint model for the nine outcomes. This entailed fitting 36 bivariate generalized linear mixed models and deriving inference for the joint model using pseudo-likelihood theory. We also analyzed the nine outcomes separately before and after multiple imputation. We observed joint effects of patient-, clinician- and hospital-level factors on pneumonia care indicators before and after multiple imputation of missing covariates. In both pairwise joint modeling and separate univariate analysis methods, enhanced audit and feedback improved documentation and adherence to recommended clinical guidelines over time in six and five pneumonia care indicators, respectively. Additionally, multiple imputation improved precision of parameter estimates compared to complete case analysis. The strength and direction of association among pneumonia outcomes varied within and across the three domains of pneumonia care.

Excess Mortality by Multimorbidity, Socioeconomic, and Healthcare Factors, amongst Patients Diagnosed with Diffuse Large B-Cell or Follicular Lymphoma in England.

(1) Background: Socioeconomic inequalities of survival in patients with lymphoma persist, which may be explained by patients' comorbidities. We aimed to assess the association between comorbidities and the survival of patients diagnosed with diffuse large B-cell (DLBCL) or follicular lymphoma (FL) in England accounting for other socio-demographic characteristics. (2) Methods: Population-based cancer registry data were linked to Hospital Episode Statistics. We used a flexible multilevel excess hazard model to estimate excess mortality and net survival by patient's comorbidity status, adjusted for sociodemographic, economic, and healthcare factors, and accounting for the patient's area of residence. We used the latent normal joint modelling multiple imputation approach for missing data. (3) Results: Overall, 15,516 and 29,898 patients were diagnosed with FL and DLBCL in England between 2005 and 2013, respectively. Amongst DLBCL and FL patients, respectively, those in the most deprived areas showed 1.22 (95% confidence interval (CI): 1.18-1.27) and 1.45 (95% CI: 1.30-1.62) times higher excess mortality hazard compared to those in the least deprived areas, adjusted for comorbidity status, age at diagnosis, sex, ethnicity, and route to diagnosis. (4) Conclusions: Deprivation is consistently associated with poorer survival among patients diagnosed with DLBCL or FL, after adjusting for co/multimorbidities. Comorbidities and multimorbidities need to be considered when planning public health interventions targeting haematological malignancies in England.

Handling missing data in modelling quality of clinician-prescribed routine care: Sensitivity analysis of departure from missing at random assumption.

Missing information is a major drawback in analyzing data collected in many routine health care settings. Multiple imputation assuming a missing at random mechanism is a popular method to handle missing data. The missing at random assumption cannot be confirmed from the observed data alone, hence the need for sensitivity analysis to assess robustness of inference. However, sensitivity analysis is rarely conducted and reported in practice. We analyzed routine paediatric data collected during a cluster randomized trial conducted in Kenyan hospitals. We imputed missing patient and clinician-level variables assuming the missing at random mechanism. We also imputed missing clinician-level variables assuming a missing not at random mechanism. We incorporated opinions from 15 clinical experts in the form of prior distributions and shift parameters in the delta adjustment method. An interaction between trial intervention arm and follow-up time, hospital, clinician and patient-level factors were included in a proportional odds random-effects analysis model. We performed these analyses using R functions derived from the jomo package. Parameter estimates from multiple imputation under the missing at random mechanism were similar to multiple imputation estimates assuming the missing not at random mechanism. Our inferences were insensitive to departures from the missing at random assumption using either the prior distributions or shift parameters sensitivity analysis approach.

Analysis of Hierarchical Routine Data With Covariate Missingness: Effects of Audit & Feedback on Clinicians' Prescribed Pediatric Pneumonia Care in Kenyan Hospitals.

Background: Routine clinical data are widely used in many countries to monitor quality of care. A limitation of routine data is missing information which occurs due to lack of documentation of care processes by health care providers, poor record keeping, or limited health care technology at facility level. Our objective was to address missing covariates while properly accounting for hierarchical structure in routine pediatric pneumonia care. Methods: We analyzed routine data collected during a cluster randomized trial to investigating the effect of audit and feedback (A&F) over time on inpatient pneumonia care among children admitted in 12 Kenyan hospitals between March and November 2016. Six hospitals in the intervention arm received enhance A&F on classification and treatment of pneumonia cases in addition to a standard A&F report on general inpatient pediatric care. The remaining six in control arm received standard A&F alone. We derived and analyzed a composite outcome known as Pediatric Admission Quality of Care (PAQC) score. In our analysis, we adjusted for patients, clinician and hospital level factors. Missing data occurred in patient and clinician level variables. We did multiple imputation of missing covariates within the joint model imputation framework. We fitted proportion odds random effects model and generalized estimating equation (GEE) models to the data before and after multilevel multiple imputation. Results: Overall, 2,299 children aged 2 to 59 months were admitted with childhood pneumonia in 12 hospitals during the trial period. 2,127 (92%) of the children (level 1) were admitted by 378 clinicians across the 12 hospitals. Enhanced A&F led to improved inpatient pediatric pneumonia care over time compared to standard A&F. Female clinicians and hospitals with low admission workload were associated with higher uptake of the new pneumonia guidelines during the trial period. In both random effects and marginal model, parameter estimates were biased and inefficient under complete case analysis. Conclusions: Enhanced A&F improved the uptake of WHO recommended pediatric pneumonia guidelines over time compared to standard audit and feedback. When imputing missing data, it is important to account for the hierarchical structure to ensure compatibility with analysis models of interest to alleviate bias.

Prevalence, outcome and quality of care among children hospitalized with severe acute malnutrition in Kenyan hospitals: A multi-site observational study.

BACKGROUND: Severe acute malnutrition (SAM) remains a major cause of admission and inpatient mortality worldwide in children aged less than 5 years. In this study, we explored SAM prevalence and outcomes in children admitted in 13 Kenyan hospitals participating in a Clinical Information Network (CIN). We also describe their immediate in-patient management. METHODS: We analyzed data for children aged 1-59 months collected retrospectively from medical records after discharge. Mean, median and ranges were used to summarize pooled and age-specific prevalence and mortality associated with SAM. Documentation of key signs and symptoms (S/S) and performance of indicators of quality of care for selected aspects of the WHO management steps were assessed. Logistic regression models were used to evaluate associations between documented S/S and mortality among SAM patients aged 6-59 months. Loess curves were used to explore performance change over time for indicators of selected SAM management steps. RESULTS: 5306/54140 (9.8%) children aged 1-59 months admitted with medical conditions in CIN hospitals between December 2013 and November 2016 had SAM. SAM prevalence identified by clinicians and case fatality varied widely across hospitals with median proportion (range) of 10.1% (4.6-18.2%) and 14.8% (6.0-28.6%) respectively. Seventeen variables were associated with increased mortality. Performance change over time of management steps varied across hospitals and across selected indicators but suggests some effect of regular audit and feedback. CONCLUSION: Identification of SAM patients, their mortality and adherence to in-patient management recommendations varied across hospitals. An important group of SAM patients are aged less than 6 months. Continued efforts are required to improve management of SAM in routine settings as part of efforts to reduce inpatient mortality.

Does audit and feedback improve the adoption of recommended practices? Evidence from a longitudinal observational study of an emerging clinical network in Kenya.

Background: Audit and feedback (A&F) is widely used in healthcare but there are few examples of how to deploy it at scale in low-income countries. Establishing the Clinical Information Network (CIN) in Kenya provided an opportunity to examine the effect of A&F delivered as part of a wider set of activities to promote paediatric guideline adherence. Methods: We analysed data collected from medical records on discharge for children aged 2-59 months from 14 Kenyan hospitals in the CIN. Hospitals joined CIN in phases and for each we analysed their initial 25 months of participation that occurred between December 2013 and March 2016. A total of 34 indicators of adherence to recommendations were selected for evaluation each classified by form of feedback (passive, active and none) and type of task (simple or difficult documentation and those requiring cognitive work). Performance change was explored graphically and using generalised linear mixed models with attention given to the effects of time and use of a standardised paediatric admission record (PAR) form. Results: Data from 60 214 admissions were eligible for analysis. Adherence to recommendations across hospitals significantly improved for 24/34 indicators. Improvements were not obviously related to nature of feedback, may be related to task type and were related to PAR use in the case of documentation indicators. There was, however, marked variability in adoption and adherence to recommended practices across sites and indicators. Hospital-specific factors, low baseline performance and specific contextual changes appeared to influence the magnitude of change in specific cases. Conclusion: Our observational data suggest some change in multiple indicators of adherence to recommendations (aspects of quality of care) can be achieved in low-resource hospitals using A&F and simple job aides in the context of a wider network approach.

Inappropriate prescription of cough remedies among children hospitalised with respiratory illness over the period 2002-2015 in Kenya.

OBJECTIVE: To examine trends in prescription of cough medicines over the period 2002-2015 in children aged 1 month to 12 years admitted to Kenyan hospitals with cough, difficulty breathing or diagnosed with a respiratory tract infection. METHODS: We reviewed hospitalisation records of children included in four studies providing cross-sectional prevalence estimates from government hospitals for six time periods between 2002 and 2015. Children with an atopic illness were excluded. Amongst eligible children, we determined the proportion prescribed any adjuvant medication for cough. Active ingredients in these medicines were often multiple and were classified into five categories: antihistamines, antitussives, mucolytics/expectorants, decongestants and bronchodilators. From late 2006, guidelines discouraging cough medicine use have been widely disseminated and in 2009 national directives to decrease cough medicine use were issued. RESULTS: Across the studies, 17 963 children were eligible. Their median age and length of hospital stay were comparable. The proportion of children who received cough medicines shrank across the surveys: approximately 6% [95% CI: 5.4, 6.6] of children had a prescription in 2015 vs. 40% [95% CI: 35.5, 45.6] in 2002. The most common active ingredients were antihistamines and bronchodilators. The relative proportion that included antihistamines has increased over time. CONCLUSIONS: There has been an overall decline in the use of cough medicines among hospitalised children over time. This decline has been associated with educational, policy and mass media interventions.

Blood Transfusion Delay and Outcome in County Hospitals in Kenya.

Severe anemia is a leading indication for blood transfusion and a major cause of hospital admission and mortality in African children. Failure to initiate blood transfusion rapidly enough contributes to anemia deaths in sub-Saharan Africa. This article examines delays in accessing blood and outcomes in transfused children in Kenyan hospitals. Children admitted with nonsurgical conditions in 10 Kenyan county hospitals participating in the Clinical Information Network who had blood transfusion ordered from September 2013 to March 2016 were studied. The delay in blood transfusion was calculated from the date when blood transfusion was prescribed to date of actual transfusion. Five percent (2,875/53,174) of admissions had blood transfusion ordered. Approximately half (45%, 1,295/2,875) of children who had blood transfusion ordered at admission had a documented hemoglobin < 5 g/dl and 36% (2,232/6,198) of all children admitted with a diagnosis of anemia were reported to have hemoglobin < 5 g/dL. Of all the ordered transfusions, 82% were administered and documented in clinical records, and three-quarters of these (75%, 1,760/2,352) were given on the same day as ordered but these proportions varied from 71% to 100% across the 10 hospitals. Children who had a transfusion ordered but did not receive the prescribed transfusion had a mortality of 20%, compared with 12% among those transfused. Malaria-associated anemia remains the leading indication for blood transfusion in acute childhood illness admissions. Delays in transfusion are common and associated with poor outcomes. Variance in delay across hospitals may be a useful indicator of health system performance.

Improving documentation of clinical care within a clinical information network: an essential initial step in efforts to understand and improve care in Kenyan hospitals.

In many low income countries health information systems are poorly equipped to provide detailed information on hospital care and outcomes. Information is thus rarely used to support practice improvement. We describe efforts to tackle this challenge and to foster learning concerning collection and use of information. This could improve hospital services in Kenya. We are developing a Clinical Information Network, a collaboration spanning 14 hospitals, policy makers and researchers with the goal of improving information available on the quality of inpatient paediatric care across common childhood illnesses in Kenya. Standardised data from hospitals' paediatric wards are collected using non-commercial and open source tools. We have implemented procedures for promoting data quality which are performed prior to a process of semi-automated analysis and routine report generation for hospitals in the network. In the first phase of the Clinical Information Network, we collected data on over 65 000 admission episodes. Despite clinicians' initial unfamiliarity with routine performance reporting, we found that, as an initial focus, both engaging with each hospital and providing them information helped improve the quality of data and therefore reports. The process has involved mutual learning and building of trust in the data and should provide the basis for collaborative efforts to improve care, to understand patient outcome, and to evaluate interventions through shared learning. We have found that hospitals are willing to support the development of a clinically focused but geographically dispersed Clinical Information Network in a low-income setting. Such networks show considerable promise as platforms for collaborative efforts to improve care, to provide better information for decision making, and to enable locally relevant research.