Integrated disease surveillance and response implementation in Liberia, findings from a data quality audit, 2017

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.

Evaluation of Ebola virus disease surveillance system capability to promptly detect a new outbreak in Liberia

INTRODUCTION

Liberia was heavily affected by the 2014-2016 Ebola virus disease (EVD) outbreak. With substantial investments in interventions to combat future outbreaks, it is hoped that Liberia is well prepared for a new incursion. We assessed the performance of the current EVD surveillance system in Liberia, focusing on its ability to promptly detect a new EVD outbreak.

METHODS

We integrated WHO and US Centers for Disease Control and Prevention guidelines for public health surveillance system evaluation and used standardised indicators to measure system performance. We conducted 23 key informant interviews, 150 health facility assessment surveys and a standardised patient (SP) study (19 visits) from January 2020 to January 2021. Data were summarised and a gap analysis conducted.

RESULTS

We found basic competencies of case detection and reporting necessary for a functional surveillance system were in place. At the higher (national, county and district) levels, we found performance gaps in 2 of 6 indicators relating to surveillance system structure, 3 of 14 indicators related to core functions, 1 of 5 quality indicators and 2 of 8 indicators related to support functions. The health facility assessment found performance gaps in 9 of 10 indicators related to core functions, 5 of 6 indicators related to support functions and 3 of 7 indicators related to quality. The SP simulations revealed large gaps between expected and actual practice in managing a patient warranting investigation for EVD. Major challenges affecting the system's operations across all levels included limited access to resources to support surveillance activities, persistent stock out of sample collection materials and attrition of trained staff.

CONCLUSION

The EVD surveillance system in Liberia may fail to promptly detect a new EVD outbreak. Specific improvements are required, and regular evaluations recommended. SP studies could be crucial in evaluating surveillance systems for rarely occurring diseases that are important to detect early.

Barriers to conducting independent quantitative research in low-income countries: A cross-sectional study of public health graduate students in Liberia

INTRODUCTION

During recent disease outbreaks, quantitative research has been used to investigate intervention scenarios while accounting for local epidemiological, social, and clinical context. Despite the value of such work, few documented research efforts have been observed to originate from low-income countries. This study aimed to assess barriers that may be limiting the awareness and conduct of quantitative research among Liberian public health graduate students.

METHODS

A semi-structured questionnaire was administered September-November 2021 to Master's in Public Health (MPH) students in Liberia. Potential barriers around technology access, understanding of quantitative science, and availability of mentorship were interrogated. Associations between barriers and self-reported likelihood of conducting quantitative research within six months of the investigation period were evaluated using ordinal logistic regression.

RESULTS

Among 120 participating MPH students, 86% reported owning a personal computer, but 18.4% and 39.4% had machines with malfunctioning hardware and/or with battery power lasting ≤2 hours, respectively. On average, students reported having poor internet network 3.4 days weekly. 47% reported never using any computer software for analysis, and 46% reported no specific knowledge on statistical analysis. Students indicated spending a median 30 minutes per week reading scientific articles. Moreover, 50% had no access to quantitative research mentors. Despite barriers, 59% indicated they were very likely to undertake quantitative research in the next 6 months; only 7% indicated they were not at all likely. Computer ownership was found to be statistically significantly associated with higher likelihood of conducting quantitative research in the multivariable analysis (aOR: 4.90,95% CI: 1.54-16.3).

CONCLUSION

The high likelihood of conducting quantitative research among MPH students contrasts with limitations around computing capacity, awareness of research tools/methods, and access to mentorship. To promote rigorous analytical research in Liberia, there is a need for systematic measures to enhance capacity for diverse quantitative methods through efforts sensitive to the local research environment.

Routine use of DHIS2 data: a scoping review

Background

In regard to health service planning and delivery, the use of information at different levels in the health system is vital, ranging from the influencing of policy to the programming of action to the ensuring of evidence-informed practices. However, neither ownership of, nor access to, good quality data guarantees actual use of these data. For information to be used, relevant data need to be collected, processed and analysed in an accessible format. This problem of underused data, and indeed the absence of data use entirely, is widespread and has been evident for decades.

The DHIS2 software platform supports routine health management for an estimated 2.4 billion people, in over 70 countries worldwide. It is by far the largest and most widespread software for this purpose and adopts a holistic, socio-technical approach to development and implementation. Given this approach, and the rapid and extensive scaling of DHIS2, we questioned whether or not there has been a parallel increase in the scaling of improved information use. To date, there has been no rigorous review of the documentation on how exactly DHIS2 data is routinely being used for decision-making and subsequent programming of action. This scoping review addresses this review gap.

Methods

The five-stage approach of Arksey and O’Malley progressed by Levac et al. and Peters was followed. Three databases (PubMed, Web of Science and Embase) were searched, along with relevant conference proceedings and postgraduate theses. In total, over 500 documents were reviewed and data from 19 documents were extracted.

Results

Overall, DHIS2 data are being used but there are few detailed descriptions of this usage in peer reviewed or grey literature. We find that, commonly, there exists a centralised versus decentralised pattern of use in terms of access to data and the reporting of data ‘up’ in the system. We also find that the different conceptualisations of data use and how data use is conceptualised are not made explicit.

Conclusions

We conclude with some suggestions for a way forward, namely: i) the need to document in more detail and share how data are being used, ii) the need to investigate how data were created and who uses such data, iii) the need to design systems based on work practices, and in tandem develop and promote forums in which ‘conversations’ around data can take place.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08598-8.

Quality of National Disease Surveillance Reporting before and during COVID-19: A Mixed-Method Study in Indonesia

Background: Global COVID-19 outbreaks in early 2020 have burdened health workers, among them surveillance workers who have the responsibility to undertake routine disease surveillance activities. The aim of this study was to describe the quality of the implementation of Indonesia’s Early Warning and Response Alert System (EWARS) for disease surveillance and to measure the burden of disease surveillance reporting quality before and during the COVID-19 epidemic in Indonesia. Methods: A mixed-method approach was used. A total of 38 informants from regional health offices participated in Focus Group Discussion (FGD) and In-Depth Interview (IDI) for informants from Ministry of Health. The FGD and IDI were conducted using online video communication. Yearly completeness and timeliness of reporting of 34 provinces were collected from the application. Qualitative data were analyzed thematically, and quantitative data were analyzed descriptively. Results: Major implementation gaps were found in poorly distributed human resources and regional infrastructure inequity. National reporting from 2017–2019 showed an increasing trend of completeness (55%, 64%, and 75%, respectively) and timeliness (55%, 64%, and 75%, respectively). However, the quality of the reporting dropped to 53% and 34% in 2020 concomitant with the SARS-CoV2 epidemic. Conclusions: Report completeness and timeliness are likely related to regional infrastructure inequity and the COVID-19 epidemic. It is recommended to increase report capacities with an automatic EWARS application linked systems in hospitals and laboratories.

Twenty years of integrated disease surveillance and response in Sub-Saharan Africa: challenges and opportunities for effective management of infectious disease epidemics

INTRODUCTION

This systematic review aimed to analyse the performance of the Integrated Disease Surveillance and Response (IDSR) strategy in Sub-Saharan Africa (SSA) and how its implementation has embraced advancement in information technology, big data analytics techniques and wealth of data sources.

METHODS

HINARI, PubMed, and advanced Google Scholar databases were searched for eligible articles. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols.

RESULTS

A total of 1,809 articles were identified and screened at two stages. Forty-five studies met the inclusion criteria, of which 35 were country-specific, seven covered the SSA region, and three covered 3-4 countries. Twenty-six studies assessed the IDSR core functions, 43 the support functions, while 24 addressed both functions. Most of the studies involved Tanzania (9), Ghana (6) and Uganda (5). The routine Health Management Information System (HMIS), which collects data from health care facilities, has remained the primary source of IDSR data. However, the system is characterised by inadequate data completeness, timeliness, quality, analysis and utilisation, and lack of integration of data from other sources. Under-use of advanced and big data analytical technologies in performing disease surveillance and relating multiple indicators minimises the optimisation of clinical and practice evidence-based decision-making.

CONCLUSIONS

This review indicates that most countries in SSA rely mainly on traditional indicator-based disease surveillance utilising data from healthcare facilities with limited use of data from other sources. It is high time that SSA countries consider and adopt multi-sectoral, multi-disease and multi-indicator platforms that integrate other sources of health information to provide support to effective detection and prompt response to public health threats.

Systematic review of Integrated Disease Surveillance and Response (IDSR) implementation in the African region

Background

The WHO African region frequently experiences outbreaks and epidemics of infectious diseases often exacerbated by weak health systems and infrastructure, late detection, and ineffective outbreak response. To address this, the WHO Regional Office for Africa developed and began implementing the Integrated Disease Surveillance and Response strategy in 1998.

Objectives

This systematic review aims to document the identified successes and challenges surrounding the implementation of IDSR in the region available in published literature to highlight areas for prioritization, further research, and to inform further strengthening of IDSR implementation.

Methods

A systematic review of peer-reviewed literature published in English and French from 1 July 2012 to 13 November 2019 was conducted using PubMed and Web of Science. Included articles focused on the WHO African region and discussed the use of IDSR strategies and implementation, assessment of IDSR strategies, or surveillance of diseases covered in the IDSR framework. Data were analyzed descriptively using Microsoft Excel and Tableau Desktop 2019.

Results

The number of peer-reviewed articles discussing IDSR remained low, with 47 included articles focused on 17 countries and regional level systems. Most commonly discussed topics were data reporting (n = 39) and challenges with IDSR implementation (n = 38). Barriers to effective implementation were identified across all IDSR core and support functions assessed in this review: priority disease detection; data reporting, management, and analysis; information dissemination; laboratory functionality; and staff training. Successful implementation was noted where existing surveillance systems and infrastructure were utilized and streamlined with efforts to increase access to healthcare.

Conclusions and implications of findings

These findings highlighted areas where IDSR is performing well and where implementation remains weak. While challenges related to IDSR implementation since the first edition of the technical guidelines were released are not novel, adequately addressing them requires sustained investments in stronger national public health capabilities, infrastructure, and surveillance processes.

Improving dog bite victim survey and estimation of annual human deaths due to suspected rabies cases in three selected Liberian cities and environs, 2008-2017

Rabies remains a public health challenge of unknown magnitude in Liberia in spite of the goal of ensuring that no human in the country dies of rabies by 2030. The annual prevalence of Dog Bite Victims (DBVs) and true load of Annual Human Deaths (AHDs) due to rabies were not known. We investigated three selected cities of Liberia for annual prevalence of DBVs and true load of AHD due to suspected rabies, using 10-year retrospective record, 2008-2017 obtained from Buchanan, Gbarnga, and Voinjama, three socio-economically important cities in post-conflict Liberia. Data were sourced at County Reference Hospitals and at the Liberia National Institute of Health for these cities and their local environs. In addition, household questionnaire survey was used to identify and audit data quality for unreported DBVs, and treatment received from traditional caregivers. The proportion was used to audit the 10-year data on unreported DBVs in the cities. Descriptive statistics was used to summarize annual DBVs over the 10-year period in the three cities, respectively. A standardized clinical decision tree model was used to estimate AHDs due to suspected rabies. Based on questionnaire survey, 140/365, 148/375 and 146/350 DBVs did not visit any orthodox health facility in Buchanan, Gbarnga and Voinjama cities, respectively in 2014. An estimated total of 559 DBVs died of suspected rabies in the three cities and their environs during the 10-year period. Mean yearly prevalence of DBVs was 179±106.82, 393±257.85 and 76.9±38.11 per 100,000 population, while mean AHDs due to suspected rabies was 14.3±8.47, 35.5±23.25, and 6.1±3.21 per 100,000 population in Buchanan, Gbarnga, and Voinjama cities, respectively. The present findings provide annual prevalence of suspected rabies cases, corrected for under-reporting in three selected cities of Liberia. The findings would be useful in planning for stepwise actions towards rabies elimination, ensuring that no human dies of rabies in Liberia by 2030.