Quality of Health Management Information System for Maternal & Child Health Care in Haryana State, India

Quality of routine health facility data for monitoring maternal, newborn and child health indicators: A desk review of DHIS2 data in Lumbini Province, Nepal

INTRODUCTION

Health-facility data serves as a primary source for monitoring service provision and guiding the attainment of health targets. District Health Information Software (DHIS2) is a free open software predominantly used in low and middle-income countries to manage the facility-based data and monitor program wise service delivery. Evidence suggests the lack of quality in the routine maternal and child health information, however there is no robust analysis to evaluate the extent of its inaccuracy. We aim to bridge this gap by accessing the quality of DHIS2 data reported by health facilities to monitor priority maternal, newborn and child health indicators in Lumbini Province, Nepal.

METHODS

A facility-based descriptive study design involving desk review of Maternal, Neonatal and Child Health (MNCH) data was used. In 2021/22, DHIS2 contained a total of 12873 reports in safe motherhood, 12182 reports in immunization, 12673 reports in nutrition and 12568 reports in IMNCI program in Lumbini Province. Of those, monthly aggregated DHIS2 data were downloaded at one time and included 23 priority maternal and child health related data items. Of these 23 items, nine were chosen to assess consistency over time and identify outliers in reference years. Twelve items were selected to examine consistency between related data, while five items were chosen to assess the external consistency of coverage rates. We reviewed the completeness, timeliness and consistency of these data items and considered the prospects for improvement.

RESULTS

The overall completeness of facility reporting was found within 98% to 100% while timeliness of facility reporting ranged from 94% to 96% in each Maternal, Newborn and Child Health (MNCH) datasets. DHIS2 reported data for all 9 MNCH data items are consistent over time in 4 of 12 districts as all the selected data items are within ±33% difference from the provincial ratio. Of the eight MNCH data items assessed, four districts reported ≥5% monthly values that were moderate outliers in a reference year with no extreme outliers in any districts. Consistency between six-pairs of data items that are expected to show similar patterns are compared and found that three pairs are within ±10% of each other in all 12 districts. Comparison between the coverage rates of selected tracer indicators fall within ±33% of the DHS survey result.

CONCLUSION

Given the WHO data quality guidance and national benchmark, facilities in the Lumbini province well maintained the completeness and timeliness of MNCH datasets. Nevertheless, there is room for improvement in maintaining consistency over time, plausibility and predicted relationship of reported data. Encouraging the promotion of data review through the data management committee, strengthening the system inbuilt data validation mechanism in DHIS2, and promoting routine data quality assessment systems should be greatly encouraged.

Impact of COVID-19 on utilization of maternal and child health services in India: Health management information system data analysis

Background/Objectives

Studies globally have documented the impact of COVID 19 on maternal and newborn health services. This study assesses the impact of COVID-19 on essential maternal and child health (MCH) services in India based on the national Health Management Information System (HMIS).

Methods

Present retrospective study used secondary data analysis upon the routinely collected data accessed from Health Management Information System. Microdata on maternal and newborn indicators was extracted for all states between April and June during 2019, 2020 and 2021. Relative change for each indicator were taken into consideration for the year 2020 and 2021; with respect to the outcomes in 2019.

Results

Compared to 2019, antenatal care registrations saw a decline in all states for both periods in 2020 and 2021 except for Sikkim, Telangana, Maharashtra and Andhra Pradesh. Similarly, the relative changes in 2019 pertaining to the proportion of pregnant women provided with emergency obstetric care for pregnancy complications registered a decline in all states except for Himachal Pradesh, Telangana and Arunachal Pradesh. There was a decreasing trend noted in institutional deliveries in 2020 and 2021 among all major states. However, an increasing trend was seen in the number of immunization sessions held among all major states.

Conclusion

The study demonstrates a disruption in service delivery during the lockdown period in the first wave and the peak of the second wave. Further qualitative studies need to be undertaken to generate evidence for maintaining continuum of care during a pandemic situation.

CHSI costing study-Challenges and solutions for cost data collection in private hospitals in India

INTRODUCTION

Ayushman Bharat Pradhan Mantri Jan Aarogya Yojana (AB PM-JAY) has enabled the Government of India to become a strategic purchaser of health care services from private providers. To generate base cost evidence for evidence-based policymaking the Costing of Health Services in India (CHSI) study was commissioned in 2018 for the price setting of health benefit packages. This paper reports the findings of a process evaluation of the cost data collection in the private hospitals.

METHODS

The process evaluation of health system costing in private hospitals was an exploratory survey with mixed methods (quantitative and qualitative). We used three approaches-an online survey using a semi-structured questionnaire, in-depth interviews, and a review of monitoring data. The process of data collection was assessed in terms of time taken for different aspects, resources used, level and nature of difficulty encountered, challenges and solutions.

RESULTS

The mean time taken for data collection in a private hospital was 9.31 (± 1.0) person months including time for obtaining permissions, actual data collection and entry, and addressing queries for data completeness and quality. The longest time was taken to collect data on human resources (30%), while it took the least time for collecting information on building and space (5%). On a scale of 1 (lowest) to 10 (highest) difficulty levels, the data on human resources was the most difficult to collect. This included data on salaries (8), time allocation (5.5) and leaves (5).

DISCUSSION

Cost data from private hospitals is crucial for mixed health systems. Developing formal mechanisms of cost accounting data and data sharing as pre-requisites for empanelment under a national insurance scheme can significantly ease the process of cost data collection.

Survey implementation process and interviewer effects on skipping sequence of maternal and child health indicators from National Family Health Survey: An application of cross-classified multilevel model

Implementing a large-scale survey involves a string of intricate procedures exposed to numerous types of survey errors. Uniform and systematic training protocols, comprehensive survey manuals, and multilayer supervision during survey implementation help reduce survey errors, providing a consistent fieldwork environment that should not result in any variation in the quality of data collected across interviewers and teams. With this background, the present study attempts to delineate the effect of field investigator (FI) teams and survey implementation design on the selected outcomes. Data on four of the bigger Empowered Action Group (EAG) states of India, namely Uttar Pradesh, Madhya Pradesh, Bihar, and Rajasthan, were obtained from the fourth round of the National Family Health Survey (NFHS-4) for analysis. A fixed-effect binary logistic regression model was used to assess the effect of FI teams and survey implementation design on the selected outcomes. To study the variation in the outcome variables at the interviewer level, a cross-classified multilevel model was used. Since one interviewer had worked in more than one primary sampling unit (PSU) & district and did not follow a perfect hierarchical structure, the cross-classified multilevel model was deemed suitable. In addition, since NFHS-4 used a two-stage stratified sampling design, two-level weights were adjusted for the models to compute unbiased estimates. This study demonstrated the presence of interviewer-level variation in the selected outcomes at both inter- and intra-field agencies across the selected states. The interviewer-level intra-class correlation coefficient (ICC) for women who had not availed antenatal care (ANC) was the highest for eastern Madhya Pradesh (0.23) and central Uttar Pradesh (0.20). For ‘immunisation card not seen’, Rajasthan (0.16) and western Uttar Pradesh (0.13) had higher interviewer-level ICC. Interviewer-level variations were insignificant for women who gave birth at home across all regions of Uttar Pradesh. Eastern Madhya Pradesh, Rajasthan, and Bihar showed higher interviewer-level variation across the selected outcomes, underlining the critical role of agencies and skilled interviewers in different survey implementation designs. The analysis highlights non-uniform adherence to survey protocols, which implies that not all interviewers and agencies performed in a similar manner in the field. This study recommends a refined mechanism for field implementation and supervision, including focused training on the challenges faced by FIs, random vigilance, and morale building. In addition, examining interviewer-level characteristics, field challenges, and field agency effects may also highlight the roots of interviewer-level variation in the data. However, based on the interviewer's performance in the field, the present study offers an intriguing insight into interviewer-level variations in the quality of data.

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With uniform survey implementation strategies, the interviewer should not have any effect in explaining the maternal and child health variables.

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Skipping of selected maternal and child health indicators curtails informativeness of the survey. Results confirms that information on vaccination card, antenatal care, maternal policy information, delivery cost and postnatal checkups have been skipped with negative response to opening questions.

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Cross-classified multilevel model confirms the presence of interviewer-level variation. The interviewer-level intra-class correlation coefficient (ICC) for ‘immunization card not seen’ was found to be highest in Rajasthan and western Uttar Pradesh.

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Interviewer-level variations were found to be not significant for women who gave birth at home across all the regions of Uttar Pradesh whereas the interviewer-level variations for women who had not availed ANC was found to be highest for eastern Madhya Pradesh central Uttar Pradesh. Results emphasizes that not all interviewers and agencies performed in a similar manner in the field.

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The study recommends a refined mechanism for field implementation and supervision, including focused training on challenges faced by field investigators, random vigilance, and morale building.

Development and Testing Requirements for an Integrated Maternal and Child Health Information System in Iran: A Design Thinking Case Study

BACKGROUND

 Management of child health care can be negatively affected by incomplete recording, low data quality, and lack of data integration of health management information systems to support decision making and public health program needs. Given the importance of identifying key determinants of child health via capturing and integrating accurate and high-quality information, we aim to address this gap through the development and testing requirements for an integrated child health information system.

SUBJECTS AND METHODS

 A five-phase design thinking approach including empathizing, defining, ideation, prototyping, and testing was applied. We employed observations and interviews with the health workers at the primary health care network to identify end-users' challenges and needs using tools in human-centered design and focus group discussion. Then, a potential solution to the identified problems was developed as an integrated maternal and child health information system (IMCHIS) prototype and tested using Software Quality Requirements and Evaluation Model (SQuaRE) ISO/IEC 25000.

RESULTS

 IMCHIS was developed as a web-based system with 74 data elements and seven maternal and child health care requirements. The requirements of "child disease" with weight (0.26), "child nutrition" with weight (0.20), and "prenatal care" with weight (0.16) acquired the maximum weight coefficient. In the testing phase, the highest score with the weight coefficient of 0.48 and 0.73 was attributed to efficiency and functionality characteristics, focusing on software capability to fulfill the tasks that meet users' needs.

CONCLUSION

 Implementing a successful child health care system integrates both maternal and child health care information systems to track the effect of maternal conditions on child health and support managing performance and optimizing service delivery. The highest quality score of IMCHIS in efficiency and functionality characteristics confirms that it owns the capability to identify key determinants of child health.

Can administrative health data be used to estimate population level birth and child mortality estimates? A comparison of India's Health Information Management System data with nationally representative survey data

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HMIS covers a large proportion of births, but a smaller fraction of child deaths compared to estimates from surveys.

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Birth and death coverage in HMIS, while incomplete, has been improving nationally and for many states.

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States that have improved HMIS reporting, should be studied for replicating best practices.

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HMIS can provide signals for real time policy decisions, if used with due consideration of its limitations.

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Including patient socioeconomic and demographic traits in HMIS, could further bolster its utility in population health.

How COVID-19 lockdown has impacted the sanitary pads distribution among adolescent girls and women in India

This paper empirically explores the impact of COVID-19 pandemic and its accompanying lockdown on adolescent girls' and women's access to sanitary pads in India. We have used the National Health Mission's Health Management Information System (NHM-HMIS) data for the study, which provides data on pads' distribution on a district level. The empirical strategy used in the study exploits the variation of districts into red, orange, and green zones as announced by the Indian Government. To understand how lockdown severity impacts access to sanitary pads, we used a difference-in-difference (DID) empirical strategy to study sanitary pads' access in red and orange zones compared to green zones. We find clear evidence of the impact of lockdown intensity on the provision of sanitary pads, with districts with the strictest lockdown restrictions suffering the most. Our study highlights how sanitary pads distribution was overlooked during the pandemic, leaving girls and women vulnerable to managing their menstrual needs. Thus, there is a requirement for strong policy to focus on the need to keep sanitary pads as part of the essential goods to ensure the needs of the girls and women are met even in the midst of a pandemic, central to an inclusive response.

Quality of routine health facility data used for newborn indicators in low- and middle-income countries: A systematic review

Background

High-quality data are fundamental for effective monitoring of newborn morbidity and mortality, particularly in high burden low- and middle-income countries (LMIC).

Methods

We conducted a systematic review on the quality of routine health facility data used for newborn indicators in LMIC, including measures employed. Five databases were searched from inception to February 2021 for relevant observational studies (excluding case-control studies, case series, and case reports) and baseline or control group data from interventional studies, with no language limits. An adapted version (19-point scale) of the Critical Appraisal Tool to assess the Quality of Cross-Sectional Studies (AXIS) was used to assess methodological quality, and results were synthesized using descriptive analysis.

Results

From the 19 572 records retrieved, 34 studies in 16 LMIC countries were included. Methodological quality was high (>14/19) in 32 studies and moderate (10-14/19) in two. Studies were mostly from African (n = 30, 88.2%) and South-East Asian (n = 24, 70.6%) World Health Organization (WHO) regions, with very few from Eastern Mediterranean (n = 2, 5.9%) and Western Pacific (n = 1, 2.9%) ones. We found that only data elements used to calculate neonatal indicators had been assessed, not the indicators themselves. 41 data elements were assessed, most frequently birth outcome. 20 measures of data quality were used, most along three dimensions: 1) completeness and timeliness, 2) internal consistency, and 3) external consistency. Data completeness was very heterogeneous across 26 studies, ranging from 0%-100% in routine facility registers, 0%-100% in patient case notes, and 20%-68% in aggregate reports. One study reported on the timeliness of aggregate reports. Internal consistency ranged from 0% to 96.2% in four studies. External consistency (21 studies) varied widely in measurement and findings, with specificity (6.4%-100%), sensitivity (23.6%-97.6%), and percent agreement (24.6%-99.4%) most frequently reported.

Conclusions

This systematic review highlights a gap in the published literature on the quality of routine LMIC health facility data for newborn indicators. Robust evidence is crucial in driving data quality initiatives at national and international levels. The findings of this review indicate that good quality data collection is achievable even in high-burden LMIC settings, but more efforts are needed to ensure uniformly high data quality for neonatal indicators.

Association between vaccine preventable diseases in children and improved sanitation following a nationwide sanitation campaign in India: an ecological analysis

OBJECTIVE

Persistent exposure to faecal pathogens due to open defecation may cause environmental enteropathy that, in turn, may lead to undernutrition and vaccine failure in under 5-year-old (u5) children. The Swachh Bharat Mission (SBM) programme in India, launched in 2014, aimed to construct toilets for every household nationwide and reduce open defecation. This programme, if successful, had the potential to reduce the burden of four vaccine preventable diseases (VPDs): diphtheria, pertussis, tetanus and measles. We examine whether increased household toilet availability in Indian districts following SBM corresponds with a reduction in diphtheria, pertussis, tetanus and measles in u5 children.

DESIGN

Observational, ecological study.

SETTING

532 districts in 28 Indian states, from 2013 to 2016.

PRIMARY OUTCOME AND EXPOSURE

We retrieved data on district-level change in the annual incidence (per 1000 u5 children) of four VPDs, from 2013 (pre-SBM) to 2016 (post-SBM). We obtained data on our exposure, the change in the percentage of households with toilets (per district), from three large national surveys conducted in 2013 and 2016. We used linear regression analysis, which controlled for change over time in socioeconomic factors, health system-related covariates and pre-SBM annual incidence of VPDs.

RESULTS

A one percentage point increase in households with toilets corresponds with 0.33 fewer measle cases per 1000 u5 children in a district (coefficient: -0.33, 95% CI -0.0641 to -0.014; p<0.05). About 12% of this association is mediated by a reduction in u5 stunting. We observe no relation of the exposure with diphtheria, pertussis or tetanus. Findings remain robust to sensitivity analyses.

CONCLUSION

Rapid improvements in ambient sanitation through increased toilet availability correspond with a reduction in the annual incidence of measles in u5 children. We encourage replication of findings and further research to identify potential pathways by which SBM may reduce measle burden in u5 children.

The effects of India's COVID-19 lockdown on critical non-COVID health care and outcomes: Evidence from dialysis patients

India's COVID-19 lockdown, one of the most severe in the world, is widely believed to have disrupted critical non-COVID health services. However, linking these disruptions to effects on health outcomes has been difficult due to the lack of reliable, up-to-date health outcomes data. We identified all dialysis patients under a statewide health insurance program in Rajasthan, India (N = 2110), and conducted surveys to examine the effects of the lockdown on non-COVID care access and health outcomes. Post-lockdown mortality was our primary outcome and morbidity and hospitalization were secondary outcomes. 63% of patients experienced a disruption to their care. Transport barriers, hospital service disruptions, and difficulty obtaining medicines were the most common causes. We compared monthly mortality in the four months after the lockdown with pre-lockdown mortality trends, as well as with mortality trends for a similar cohort in the previous year. Mortality in May 2020, after a month of exposure to the lockdown, was 1.70 percentage points (95% CI 0.01–0.03) or 64% higher than in March 2020 and total excess mortality between April and July was estimated to be 22%. A 1SD increase in an index of care disruptions was associated with a 0.17SD (95% CI 0.13–0.22) increase in a morbidity index, a 3.1 percentage point (95% CI 0.012–0.051) increase in hospitalization, and a 2.1 percentage point (95% CI 0.00–0.04) increase in probability of death between May and July. Females, socioeconomically disadvantaged groups, and patients living far from the health system faced worse outcomes. The results highlight the unintended consequences of the lockdown on critical, life-saving non-COVID health services that must be taken into account in the implementation of future policy efforts to control the spread of pandemics.

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India's nationwide COVID-19 lockdown severely disrupted critical chronic care.

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Non-COVID-19 morbidity and mortality increased sharply in the subsequent months.

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Socioeconomically disadvantaged patients were worst affected.

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Indirect health effects increase the toll of pandemics and worsen health inequality.

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Pandemic control policies must ensure critical health services continue.

Mapping Healthcare Data Sources in India

Healthcare data sources collect and report various kinds of health data related to routine service delivery, patient-based care, resources related to infrastructure, human resources and finance. Typically, in developing countries, multiple sources are used for the provision of healthcare data, and these include national health surveys, census and civil registration systems, and routine reporting systems. In addition, rapid infusion of information technology has increased adoption of management information systems in public health programs. During the last decade, India has witnessed a sharp rise in the number of healthcare data sources as identified in this review. These sources have increased data availability in multiple data deficient areas. However, the careful appraisal indicates data gaps in numerous important areas. These sources also suffer from inherent quality, coverage and standardisation issues. To overcome these challenges, remedial measures include the development of a national healthcare data plan, a survey calendar, designation of a nodal survey agency, adoption of indicator dictionary, adequate capacity building, and increased coordination among stakeholders.

A Novel Approach to Promote Evidence-Based Development of District Maternal and Newborn Health Plans in Two States in India

Background:

Maternal and child health implementation plan development in districts of India lacks systematic process and capacity resulting in suboptimal health improvements. There is ineffective and limited participation and lack of autonomy to effect changes in district priorities.

Objectives:

Primary objective was to demonstrate a systematic planning approach to develop evidence-based district implementation plans for mothers and children.

Methods:

A planning tool named RAASTA (RMNCH + A Action Agenda using Strategic Approach for evidence-based district work plans) adapted from WHO (World Health Organization) program review tools was used in the states of Uttarakhand and Jharkhand. The tool was implemented in the two states for the development of implementation plans in a 6-step process by prioritizing district health goals; reviewing maternal, neonatal, child, and family planning intervention coverage; and linking them with activity implementation status; assessing strengths, and weaknesses of previous implementation plans and developing solutions based on current gaps in intervention coverage's.

Results:

Tool was used for capacity building of 59 participants and also identification of prioritized activities based on their available data. Several newer activities were identified. The districts mainstreamed them as action plans, many of which were incorporated in the state Program Implementation Plan for budgetary provisions under state NHM (National Health Mission) funds.

Conclusion:

The use of a tool facilitated the systematic development of evidence-based district implementation plans.

Putting the local back into planning-experiences and perceptions of state and district health functionaries of seven aspirational districts in India on an innovative planning capacity building approach

District functionaries have ostensibly a major responsibility to develop evidence based plans. However, this responsibility is not commensurate with skills and expertise among functionaries in many Indian states. Vriddhi project-technical partner of the government, developed a planning tool for maternal and neonatal health programmes, called RMNCH + A Action Agenda using Strategic Approach (RAASTA), which was introduced in a workshop format in two states and attended by program officers. Qualitative feedback was obtained from selected participants to understand their experience of the workshop and of the planning tool. It emerged that previous planning process had little application of local evidence based solutions. Participants appreciated the alternative approach as RAASTA equipped them to use local evidence. Several action plans derived at the workshop were included in the state plan. At the same time, apprehension was expressed by participants about translating their learnings to practical application as planning was not a central priority in their scheme of duties and tasks. Enhanced support from states in refreshing district planners' skills would be an important step. One state government has scaled up the RAASTA tool while an electronic version is being developed for future use as it demonstrates great potential to equip and aid district officials in developing evidence based plans.

Public finance management and data availability for nutrition financing in India

For investments to translate into improved public service delivery, having a strong public finance management (PFM) system that lays out the rules, institutions and processes by which public funds are managed is critical. To enable a better understanding of the nutrition financial landscape, this paper seeks to determine whether the current PFM system in India allows for capturing required nutrition data. It does this by mapping the availability and comparability of data for a set of key nutrition-specific interventions through the budget cycle: from budget formulation, to execution, and finally, evaluation. The study finds significant gaps in data availability including absence of financial data by level of governance, geography and intervention components. These challenges relate to gaps in PFM design in India from weak planning processes, line-item budgeting, unavailability of time costs, inefficient fund release processes, difficulties in estimating target populations and the lack of output costing. These gaps in the PFM system and consequent data issues have several implications which may lead to strained delivery. This in turn impacts quality and the possibility of course correction. Some of these challenges can be overcome by ensuring planning processes are enforced, expanding existing data systems, making more data available in the public domain, using existing research better and using assumptions carefully to cover data gaps.

Improving quality and use of routine health information system data in low- and middle-income countries: A scoping review

BACKGROUND

A routine health information system is one of the essential components of a health system. Interventions to improve routine health information system data quality and use for decision-making in low- and middle-income countries differ in design, methods, and scope. There have been limited efforts to synthesise the knowledge across the currently available intervention studies. Thus, this scoping review synthesised published results from interventions that aimed at improving data quality and use in routine health information systems in low- and middle-income countries.

METHOD

We included articles on intervention studies that aimed to improve data quality and use within routine health information systems in low- and middle-income countries, published in English from January 2008 to February 2020. We searched the literature in the databases Medline/PubMed, Web of Science, Embase, and Global Health. After a meticulous screening, we identified 20 articles on data quality and 16 on data use. We prepared and presented the results as a narrative.

RESULTS

Most of the studies were from Sub-Saharan Africa and designed as case studies. Interventions enhancing the quality of data targeted health facilities and staff within districts, and district health managers for improved data use. Combinations of technology enhancement along with capacity building activities, and data quality assessment and feedback system were found useful in improving data quality. Interventions facilitating data availability combined with technology enhancement increased the use of data for planning.

CONCLUSION

The studies in this scoping review showed that a combination of interventions, addressing both behavioural and technical factors, improved data quality and use. Interventions addressing organisational factors were non-existent, but these factors were reported to pose challenges to the implementation and performance of reported interventions.

The challenges of nursing information systems: a narrative review of the literature

Nursing information systems, where quality indicators are integrated, focus on the standardization of health records and the consequent visibility of the provided care. Despite the acknowledged importance of the contributions of information systems, their implementation has been characterized by several challenges, so we propose to reflect on them. To identify the evidence available in the literature on these same challenges, a narrative review of the literature was developed, with the analysis of relevant articles and reports on this issue. It is clear in the literature the importance of information systems for obtaining quality indicators that are sensitive to nursing care, with a positive impact on the quality of care, allowing for measurable quality in interventions, as well as facilitating inter and intra-institutional comparability, in real-time or in a retrospective analysis. The challenges encountered and which urgently needs to be resolved in clinical practice are related to the difficulty for professionals to perceive the impact of computer records, the visibility of nursing indicators and the time that is allocated in the context of providing care to carry out these records.

Geographic Inequities in Coverage of Maternal and Child health Services in Haryana State of India

Introduction India aims to achieve universal health coverage, with a focus on equitable delivery of services. There is significant evidence on extent of inequities by income status, gender and caste. In this paper, we report geographic inequities in coverage of reproductive, maternal and child health (MCH) services in Haryana state of India. Methods Cross-sectional data on utilization of maternal, child health and family planning services were collected from 12,191 women who had delivered a child in the last one year, 10314 women with 12-23 months old child, and 45864 eligible couples across all districts in Haryana state. Service coverage was assessed based on eight indicators - 6 for maternal health, one for child health and one for family planning. Inter- and intra-district inequalities were compared based on four and three indicators respectively. Results Difference in coverage of full ante-natal care, full immunization and contraceptive prevalence rate between districts performing best and worst was found to be 54%, 65% and 63% respectively. More than one-thirds of the sub-centres (SCs) in Panchkula, Ambala, Gurgaon and Mewat districts had their ante-natal care coverage less than 50% of the respective district average. Similarly, a significant proportion of SCs in Mewat, Panipat and Hisar districts had full immunization rate below 50% of the district average. Conclusion Widespread inter- and intra-district inequities in utilization of MCH services exist. A comprehensive geographical targeting to identify poor performing districts, community development blocks and SCs could result in significant equity gains, besides contributing to quick achievement of sustainable development goals.

Under-reporting of TB cases and associated factors: a case study in China

Background

Tuberculosis is a leading cause of death worldwide and has become a high global health priority. Accurate country level surveillance is critical to ending the pandemic. Effective routine reporting systems which track the course of the epidemic are vital in addressing TB. China, which has the third largest TB epidemic in the world and has developed a reporting system to help with the control and prevention of TB, this study examined its effectiveness in Eastern China.

Methods

The number of TB cases reported internally in two hospitals in Eastern China were compared to the number TB cases reported by these same hospitals in the national reporting systems in order to assess the accuracy of reporting. Qualitative data from interviews with key health officials and researcher experience using the TB reporting systems were used to identify factors affecting the accuracy of TB cases being reported in the national systems.

Results

This study found that over a quarter of TB cases recorded in the internal hospital records were not entered into the national TB reporting systems, leading to an under representation of national TB cases. Factors associated with underreporting included unqualified and overworked health personnel, poor supervision and accountability at local and national levels, and a complicated incohesive health information management system.

Conclusions

This study demonstrates that TB in Eastern China is being underreported. Given that Eastern China is a developed province, one could assume similar problems may be found in other parts of China with fewer resources as well as many low- and middle-income countries. Having an accurate account of the number of national TB cases is essential to understanding the national and global burden of the disease and in managing TB prevention and control efforts. As such, factors associated with underreporting need to be addressed in order to reduce underreporting.

Comprehensive measurement of health system performance at district level in India: Generation of a composite index

There have been limited attempts at measurement of health system performance at decentralized levels in low- and middle-income countries. This study was undertaken to develop a composite indicator to measure health system performance at district level in India. Primary data were collected from 377 public health facilities in 21 districts of Haryana state in India using health facility surveys. In addition, 1700 health care providers and 800 clients visiting health facilities were interviewed. Routine health management information system data at district and state level were also analyzed. These data were used for computing 67 input and process indicators covering six health system building blocks. Indicators were normalized and aggregated to generate domain-specific and overall composite health system performance index (HSPI) for each district. Several sensitivity analyses were performed to assess robustness of results. Overall, Panchkula and Ambala districts were found to be the best performing in the state (with HSPI scores of 0.64 and 0.62 out of 1), while Mewat, Faridabad, and Palwal districts had the poorest performance (with HSPI scores of 0.46, 0.49, and 0.48 out of 1). Significant variation in performance was observed for each health system building block. Sensitivity analyses results showed that study findings were robust to variations in methods of aggregation of indicators. Our study provides a framework and methods to measure health system performance at district level in a comprehensive manner. The composite indicator provides a summary snapshot to benchmark performance, while building block and domain scores provide critical information for programmatic action.

Effect of Kangaroo Mother Care on hospital management indicators: A systematic review and meta-analysis of randomized controlled trials

Results of previous studies about the effect of Kangaroo Mother Care (KMC) on hospital management indicators (HMIs) (length of stay [LOS], readmission to hospital, parent satisfaction, and parent's preference for same postdelivery care) had high confusions. The aim of this study was to conduct a systematic review and meta-analysis of randomized controlled trials on the effect of KMC on HMI in comparison with the conventional neonatal care (CNC). In this systematic review and meta-analysis study, required data were collected by searching the following keywords: "length of stay," "readmission to hospital," satisfaction," same post-delivery," "hospital management," indicators, "skin-to-skin," "Kangaroo Mother Care," randomized trial. The following databases were searched: Google Scholar, PubMed, EMBASE, Scopus, and Cochrane. To estimate the hospital management indicators, computer software Comprehensive Meta-Analysis 2 was used. Finally, 18 articles were included to analysis. The overall LOS standard different between groups (KMC vs. CNC) was - 0.91 days (95% confidence interval [CI], -2.14-0.32, Q = 25.6, df = 10, P = 0.004, I ² = 60.98). The overall readmission to hospital standard different between groups was - 1.78% (95% CI, -1.21%-0.86%, Q = 0.024, df = 1, P = 0.87, I ² = 0.00). The overall parent satisfaction standard different between groups was 5.3% (95% CI, -32.4%-43%, Q = 0.052, df = 2, P = 0.97, I ² = 0.00). The overall standard different between groups was 16.2% (95% CI, -24.7%-57.1%, Q = 0.040, df = 1, P = 0.84, I ² = 0.00). KMC improves HMI but not significantly. According to the current study result and other studies that report positive effect of KMC on health status of the newborns and parents, implemented of KMC in low- and middle-income countries recommended.

A quality assessment of Health Management Information System (HMIS) data for maternal and child health in Jimma Zone, Ethiopia

Health management information system (HMIS) data are important for guiding the attainment of health targets in low- and middle-income countries. However, the quality of HMIS data is often poor. High-quality information is especially important for populations experiencing high burdens of disease and mortality, such as pregnant women, newborns, and children. The purpose of this study was to assess the quality of maternal and child health (MCH) data collected through the Ethiopian Ministry of Health’s HMIS in three districts of Jimma Zone, Oromiya Region, Ethiopia over a 12-month period from July 2014 to June 2015. Considering data quality constructs from the World Health Organization’s data quality report card, we appraised the completeness, timeliness, and internal consistency of eight key MCH indicators collected for all the primary health care units (PHCUs) located within three districts of Jimma Zone (Gomma, Kersa and Seka Chekorsa). We further evaluated the agreement between MCH service coverage estimates from the HMIS and estimates obtained from a population-based cross-sectional survey conducted with 3,784 women who were pregnant in the year preceding the survey, using Pearson correlation coefficients, intraclass correlation coefficients (ICC), and Bland-Altman plots. We found that the completeness and timeliness of facility reporting were highest in Gomma (75% and 70%, respectively) and lowest in Kersa (34% and 32%, respectively), and observed very few zero/missing values and moderate/extreme outliers for each MCH indicator. We found that the reporting of MCH indicators improved over time for all PHCUs, however the internal consistency between MCH indicators was low for several PHCUs. We found poor agreement between MCH estimates obtained from the HMIS and the survey, indicating that the HMIS may over-report the coverage of key MCH services, namely, antenatal care, skilled birth attendance and postnatal care. The quality of MCH data within the HMIS at the zonal level in Jimma, Ethiopia, could be improved to inform MCH research and programmatic efforts.

Mental health information systems in resource-challenged countries: experiences from India

Mental health information systems are increasingly being used to measure the effectiveness of mental health interventions. Little or no data is available for mental health service availability and service uptake in low- and middle-income countries. Through a narrative review, this paper illustrates the importance of routine monitoring data and suggests methods for developing, implementing and evaluating mental health indicators in low- and middle-income countries with a primary focus on India.