Development of novel composite data quality scores to evaluate facility-level data quality in electronic data in Kenya: a nationwide retrospective cohort study.

BACKGROUND: In this evaluation, we aim to strengthen Routine Health Information Systems (RHIS) through the digitization of data quality assessment (DQA) processes. We leverage electronic data from the Kenya Health Information System (KHIS) which is based on the District Health Information System version 2 (DHIS2) to perform DQAs at scale. We provide a systematic guide to developing composite data quality scores and use these scores to assess data quality in Kenya. METHODS: We evaluated 187 HIV care facilities with electronic medical records across Kenya. Using quarterly, longitudinal KHIS data from January 2011 to June 2018 (total N = 30 quarters), we extracted indicators encompassing general HIV services including services to prevent mother-to-child transmission (PMTCT). We assessed the accuracy (the extent to which data were correct and free of error) of these data using three data-driven composite scores: 1) completeness score; 2) consistency score; and 3) discrepancy score. Completeness refers to the presence of the appropriate amount of data. Consistency refers to uniformity of data across multiple indicators. Discrepancy (measured on a Z-scale) refers to the degree of alignment (or lack thereof) of data with rules that defined the possible valid values for the data. RESULTS: A total of 5,610 unique facility-quarters were extracted from KHIS. The mean completeness score was 61.1% [standard deviation (SD) = 27%]. The mean consistency score was 80% (SD = 16.4%). The mean discrepancy score was 0.07 (SD = 0.22). A strong and positive correlation was identified between the consistency score and discrepancy score (correlation coefficient = 0.77), whereas the correlation of either score with the completeness score was low with a correlation coefficient of -0.12 (with consistency score) and -0.36 (with discrepancy score). General HIV indicators were more complete, but less consistent, and less plausible than PMTCT indicators. CONCLUSION: We observed a lack of correlation between the completeness score and the other two scores. As such, for a holistic DQA, completeness assessment should be paired with the measurement of either consistency or discrepancy to reflect distinct dimensions of data quality. Given the complexity of the discrepancy score, we recommend the simpler consistency score, since they were highly correlated. Routine use of composite scores on KHIS data could enhance efficiencies in DQA at scale as digitization of health information expands and could be applied to other health sectors beyondHIV clinics.

The indirect impact of COVID-19 pandemic on inpatient admissions in 204 Kenyan hospitals: An interrupted time series analysis.

The first case of severe acute respiratory coronavirus 2 (SARS-CoV-2) was identified in March 2020 in Kenya resulting in the implementation of public health measures (PHM) to prevent large-scale epidemics. We aimed to quantify the impact of COVID-19 confinement measures on access to inpatient services using data from 204 Kenyan hospitals. Data on monthly admissions and deliveries from the District Health Information Software version 2 (DHIS 2) were extracted for the period January 2018 to March 2021 stratified by hospital ownership (public or private) and adjusting for missing data using multiple imputation (MI). We used the COVID-19 event as a natural experiment to examine the impact of COVID-19 and associated PHM on use of health services by hospital ownership. We estimated the impact of COVID-19 using two approaches; Statistical process control (SPC) charts to visualize and detect changes and Interrupted time series (ITS) analysis using negative-binomial segmented regression models to quantify the changes after March 2020. Sensitivity analysis was undertaken to test robustness of estimates using Generalised Estimating Equations (GEE) and impact of national health workers strike on observed trends. SPC charts showed reductions in most inpatient services starting April 2020. ITS modelling showed significant drops in April 2020 in monthly volumes of live-births (11%), over-fives admissions for medical (29%) and surgical care (25%) with the greatest declines in the under-five's admissions (59%) in public hospitals. Similar declines were apparent in private hospitals. Health worker strikes had a significant impact on post-COVID-19 trends for total deliveries, live-births and caesarean section rate in private hospitals. COVID-19 has disrupted utilization of inpatient services in Kenyan hospitals. This might have increased avoidable morbidity and mortality due to non-COVID-19-related illnesses. The declines have been sustained. Recent data suggests a reversal in trends with services appearing to be going back to pre- COVID levels.

Assessing bed net use and non-use after long-lasting insecticidal net distribution: a simple framework to guide programmatic strategies.

BACKGROUND: Insecticide-treated nets (ITNs) are becoming increasingly available to vulnerable populations at risk for malaria. Their appropriate and consistent use is essential to preventing malaria, but ITN use often lags behind ITN ownership. In order to increase ITN use, it is necessary to devise strategies that accurately identify, differentiate, and target the reasons and types of non-use. METHODS: A simple method based on the end-user as the denominator was employed to classify each individual into one of four ITN use categories: 1) living in households not owning an ITN; 2) living in households owning, but not hanging an ITN; 3) living in households owning and hanging an ITN, but who are not sleeping under one; and 4) sleeping under an ITN. This framework was applied to survey data designed to evaluate long-lasting insecticidal nets (LLINs) distributions following integrated campaigns in five countries: Togo, Sierra Leone, Madagascar, Kenya and Niger. RESULTS: The percentage of children <5 years of age sleeping under an ITN ranged from 51.5% in Kenya to 81.1% in Madagascar. Among the three categories of non-use, children living in households without an ITN make up largest group (range: 9.4%-30.0%), despite the efforts of the integrated child health campaigns. The percentage of children who live in households that own but do not hang an ITN ranged from 5.1% to 16.1%. The percentage of children living in households where an ITN was suspended, but who were not sleeping under it ranged from 4.3% to 16.4%. Use by all household members in Sierra Leone (39.9%) and Madagascar (60.4%) indicate that integrated campaigns reach beyond their desired target populations. CONCLUSIONS: The framework outlined in this paper provides a helpful tool to examine the deficiencies in ITN use. Monitoring and evaluation strategies designed to assess ITN ownership and use can easily incorporate this approach using existing data collection instruments that measure the standard indicators.

Bed net ownership in Kenya: the impact of 3.4 million free bed nets.

BACKGROUND: In July and September 2006, 3.4 million long-lasting insecticide-treated bed nets (LLINs) were distributed free in a campaign targeting children 0-59 months old (CU5s) in the 46 districts with malaria in Kenya. A survey was conducted one month after the distribution to evaluate who received campaign LLINs, who owned insecticide-treated bed nets and other bed nets received through other channels, and how these nets were being used. The feasibility of a distribution strategy aimed at a high-risk target group to meet bed net ownership and usage targets is evaluated. METHODS: A stratified, two-stage cluster survey sampled districts and enumeration areas with probability proportional to size. Handheld computers (PDAs) with attached global positioning systems (GPS) were used to develop the sampling frame, guide interviewers back to chosen households, and collect survey data. RESULTS: In targeted areas, 67.5% (95% CI: 64.6, 70.3%) of all households with CU5s received campaign LLINs. Including previously owned nets, 74.4% (95% CI: 71.8, 77.0%) of all households with CU5s had an ITN. Over half of CU5s (51.7%, 95% CI: 48.8, 54.7%) slept under an ITN during the previous evening. Nearly forty percent (39.1%) of all households received a campaign net, elevating overall household ownership of ITNs to 50.7% (95% CI: 48.4, 52.9%). CONCLUSIONS: The campaign was successful in reaching the target population, families with CU5s, the risk group most vulnerable to malaria. Targeted distribution strategies will help Kenya approach indicator targets, but will need to be combined with other strategies to achieve desired population coverage levels.

The epidemiology of hospitalized pneumonia in rural Kenya: the potential of surveillance data in setting public health priorities.

INTRODUCTION: Surveillance data from inpatient health facilities can be useful for prioritization of public health initiatives, but often are not collected or analyzed in developing countries. We evaluated data on hospitalized patients diagnosed with pneumonia in rural western Kenya to characterize pneumonia epidemiology and mortality. METHODS: Data were obtained from admission registers of all inpatient facilities from 2001 to 2003 in Bondo District (estimated 2003 population: 255901), which is holoendemic for malaria and has high HIV rates. Inpatients with diagnoses compatible with acute pneumonia were included, and census data (1999) were used to calculate incidence rates by age, sex, season, and residence. RESULTS: From 2001 to 2003, a total of 2466 patients diagnosed with pneumonia were hospitalized with 282 deaths (11.4%). Incidence peaked at 698 per 100,000 person-years among children <5 years of age. A second peak occurred among 20-29 year-olds at 356 per 100,000 person-years; rates were twice as high in women as men in this age group (p<0.001). The incidence in persons >65 years was 121 per 100,000 person-years. Pneumonia incidence peaked during the twice-yearly high malaria seasons, 1-2 months after peak rainfall. Rates of pneumonia decreased with increasing distance of residence from the district hospital (p<0.0001). DISCUSSION: In Bondo District, the pneumonia burden is greatest among young children and middle-aged adults, the latter peak reflecting the area's HIV epidemic. Access to care likely influenced hospital utilization and thus pneumonia rates, particularly among the elderly. Our findings show that hospital-based data can provide useful information for public health priority setting, such as the introduction of new pneumonia vaccines for children and accelerating the introduction of antiretroviral medications.

The epidemiology of hospitalization with diarrhea in rural Kenya: the utility of existing health facility data in developing countries.

OBJECTIVES: In developing countries where prospective surveillance is resource-intensive, existing hospital data can define incidence, mortality, and risk factors that can help target interventions and track trends in disease burden. METHODS: We reviewed hospitalizations from 2001 to 2003 at all inpatient facilities in Bondo District, Kenya. RESULTS: Diarrhea was responsible for 11.2% (n=2158) of hospitalizations. The annual incidence was 550 and 216 per 100,000 persons aged <5 and > or =5 years, respectively. The incidence was highest in infants (1138 per 100,000 persons), decreased in older children, peaked again among 20-29-year-olds (341 per 100,000), and declined among those > or =65 years (157 per 100,000). Female adults had higher incidence than males (rate ratio=1.84, 95% CI 1.61-2.10). Incidence decreased with distance from the district referral hospital (4.5% per kilometer, p<0.0001) and from the nearest inpatient facility (6.6% per kilometer, p=0.012). Case-fatality was high (8.0%), and was higher among adults than young children. Co-diagnosis with malaria, pneumonia, HIV, and tuberculosis was common. Peak diarrhea incidence fell one to two months after heavy rains. CONCLUSIONS: The trends revealed here provide useful data for public health priority setting and planning, including preventative interventions. The utility of such data justifies renewed efforts to establish and strengthen health management information systems in developing countries.