Evaluation of neonatal mortality data completeness and accuracy in Ghana

Background Cause-specific mortality data are required to set interventions to reduce neonatal mortality. However, in many developing countries, these data are either lacking or of low quality. We assessed the completeness and accuracy of cause of death (COD) data for neonates in Ghana to assess their usability for monitoring the effectiveness of health system interventions aimed at improving neonatal survival. Methods A lot quality assurance sampling survey was conducted in 20 hospitals in the public sector across four regions of Ghana. Institutional neonatal deaths (IND) occurring from 2014 through 2017 were divided into lots, defined as neonatal deaths occurring in a selected facility in a calendar year. A total of 52 eligible lots were selected: 10 from Ashanti region, and 14 each from Brong Ahafo, Eastern and Volta region. Nine lots were from 2014, 11 from 2015 and 16 each were from 2016 and 2017. The cause of death (COD) of 20 IND per lot were abstracted from admission and discharge (A&D) registers and validated against the COD recorded in death certificates, clinician’s notes or neonatal death audit reports for consistency. With the error threshold set at 5%, ≥ 17 correctly matched diagnoses in a sample of 20 deaths would make the lot accurate for COD diagnosis. Completeness of COD data was measured by calculating the proportion of IND that had death certificates completed. Results Nineteen out of 52 eligible (36.5%) lots had accurate COD diagnoses recorded in their A&D registers. The regional distribution of lots with accurate COD data is as follows: Ashanti (4, 21.2%), Brong Ahafo (7, 36.8%), Eastern (4, 21.1%) and Volta (4, 21.1%). Majority (9, 47.4%) of lots with accurate data were from 2016, followed by 2015 and 2017 with four (21.1%) lots. Two (10.5%) lots had accurate COD data in 2014. Only 22% (239/1040) of sampled IND had completed death certificates. Conclusion Death certificates were not reliably completed for IND in a sample of health facilities in Ghana from 2014 through 2017. The accuracy of cause-specific mortality data recorded in A&D registers was also below the desired target. Thus, recorded IND data in public sector health facilities in Ghana are not valid enough for decision-making or planning. Periodic data quality assessments can determine the magnitude of the data quality concerns and guide site-specific improvements in mortality data management.

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Assessment of neonatal mortalities and stillbirths data quality in Offinso North District of Ghana

International Journal of Scientific Research and Management ◽

10.18535/ijsrm/v10i01.mp01 ◽

2022 ◽

Vol 10 (01) ◽

pp. 508-518

Author(s):

Richmond Nsiah ◽

Wisdom Takramah ◽

Solomon Anum-Doku ◽

Richard Avagu ◽

Dominic Nyarko

Keyword(s):

Data Quality ◽

Neonatal Mortality ◽

Assessment Tool ◽

Information Management System ◽

Health Facilities ◽

Primary Data ◽

Mortality Data ◽

Neonatal Deaths ◽

Discrepancy Rate

Background: Stillbirths and neonatal deaths when poorly documented or collated, negatively affect the quality of decision and interventions. This study sought to assess the quality of routine neonatal mortalities and stillbirth records in health facilities and propose interventions to improve the data quality gaps. Method: Descriptive cross-sectional study was employed. This study was carried out at three (3) purposively selected health facilities in Offinso North district. Stillbirths and neonatal deaths recorded in registers from 2015 to 2017, were recounted and compared with monthly aggregated data and District Health Information Management System 2 (DHIMS 2) data using a self-developed Excel Data Quality Assessment Tool (DQS). An observational checklist was used to collect primary data on completeness and availability. Accuracy ratio (verification factor), discrepancy rate, percentage availability and completeness of stillbirths and neonatal mortality data were computed using the DQS tool. Findings: The results showed high discrepancy rate of stillbirth data recorded in registers compared with monthly aggregated reports (12.5%), and monthly aggregated reports compared with DHIMS 2 (13.5%). Neonatal mortalities data were under-reported in monthly aggregated reports, but over-reported in DHIMS 2. Overall data completeness was about 84.6%, but only 68.5% of submitted reports were supervised by facility in-charges. Delivery and admission registers availability were 100% and 83.3% respectively. Conclusion: Quality of stillbirths and neonatal mortality data in the district is generally encouraging, but are not reliable for decision-making. Routine data quality audit is needed to reduce high discrepancies in stillbirth and neonatal mortality data in the district.

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Improving quality of medical certification of causes of death in health facilities in Tanzania 2014–2019

BMC Health Services Research ◽

10.1186/s12913-021-06189-7 ◽

2021 ◽

Vol 21 (S1) ◽

Author(s):

Trust Nyondo ◽

Gisbert Msigwa ◽

Daniel Cobos ◽

Gregory Kabadi ◽

Tumaniel Macha ◽

...

Keyword(s):

Quality Improvement ◽

Health Policy ◽

Cause Of Death ◽

Causes Of Death ◽

Health Facilities ◽

Mortality Data ◽

Medical Certification ◽

Specific Mortality ◽

Icd 10

Abstract Background Monitoring medically certified causes of death is essential to shape national health policies, track progress to Sustainable Development Goals, and gauge responses to epidemic and pandemic disease. The combination of electronic health information systems with new methods for data quality monitoring can facilitate quality assessments and help target quality improvement. Since 2015, Tanzania has been upgrading its Civil Registration and Vital Statistics system including efforts to improve the availability and quality of mortality data. Methods We used a computer application (ANACONDA v4.01) to assess the quality of medical certification of cause of death (MCCD) and ICD-10 coding for the underlying cause of death for 155,461 deaths from health facilities from 2014 to 2018. From 2018 to 2019, we continued quality analysis for 2690 deaths in one large administrative region 9 months before, and 9 months following MCCD quality improvement interventions. Interventions addressed governance, training, process, and practice. We assessed changes in the levels, distributions, and nature of unusable and insufficiently specified codes, and how these influenced estimates of the leading causes of death. Results 9.7% of expected annual deaths in Tanzania obtained a medically certified cause of death. Of these, 52% of MCCD ICD-10 codes were usable for health policy and planning, with no significant improvement over 5 years. Of certified deaths, 25% had unusable codes, 17% had insufficiently specified codes, and 6% were undetermined causes. Comparing the before and after intervention periods in one Region, codes usable for public health policy purposes improved from 48 to 65% within 1 year and the resulting distortions in the top twenty cause-specific mortality fractions due to unusable causes reduced from 27.4 to 13.5%. Conclusion Data from less than 5% of annual deaths in Tanzania are usable for informing policy. For deaths with medical certification, errors were prevalent in almost half. This constrains capacity to monitor the 15 SDG indicators that require cause-specific mortality. Sustainable quality assurance mechanisms and interventions can result in rapid improvements in the quality of medically certified causes of death. ANACONDA provides an effective means for evaluation of such changes and helps target interventions to remaining weaknesses.

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Cause of death in under 5 children in a demographic surveillance site in Pakistan

Online Journal of Public Health Informatics ◽

10.5210/ojphi.v9i1.7772 ◽

2017 ◽

Vol 9 (1) ◽

Cited By ~ 1

Author(s):

Muhammad Imran Nisar ◽

Muhammad Ilyas ◽

Komal Naeem ◽

Urooj Fatima ◽

Fyezah Jehan

Keyword(s):

Cause Of Death ◽

Diarrheal Disease ◽

Perinatal Asphyxia ◽

Health Facilities ◽

Childhood Mortality ◽

Neonatal Deaths ◽

Surveillance Site ◽

Birth Complication ◽

Specific Mortality ◽

Cause Of Deaths

ObjectiveTo identify Cause of deaths among children below age of 5yearsfrom a prospective cohort of women in one urban and four peri-urbansettings of Karachi, PakistanIntroductionPakistan ranks 26th in Childhood mortality rates, globally. Pakistan,with other 4 countries is responsible for about half of the deaths ofchildren age under 5. Despite such burden vital registration systemis not well established, health facilities are not easily accessible andmostly deaths occur at home, making identification of cause of death(COD) difficultMethodsFrom Jan 2007-Dec 2012 under-5 mortality was identifiedby CHWs during their 3-monthly visits. A Research Assistantconducted Verbal Autopsies (VA). Each VA form was analyzed by2 physicians, independently, and assigned a cause. VA is analyzedby a third physician in case two physicians do not agree on a cause.Cause Specific Mortality Fractions (CSMF) were calculated for eachidentified COD.Results833(58%) neonatal deaths and 591(42%) Under-5 deaths (excludingneonates) were identified. Among neonates most common CODswere perinatal asphyxia(30.4%), neonatal sepsis/meningitis(28%),pre-term birth complication(11%) and neonatal pneumonia(6%).For Post-neonatal deaths most common CODs were sepsis (19%),diarrheal disease (17%), Pneumonia (17%) and meningitis (8%).ConclusionsWe describe the CSMF for different CODs among neonated andchildren under 5. Strategies for prevention of most common causesand making health facilities easily accessible will decrease thisburden.

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Institutional mortality rate and cause of death at health facilities in Ghana between 2014 and 2018

PLoS ONE ◽

10.1371/journal.pone.0256515 ◽

2021 ◽

Vol 16 (9) ◽

pp. e0256515

Author(s):

Adobea Yaa Owusu ◽

Sandra Boatemaa Kushitor ◽

Anthony Adofo Ofosu ◽

Mawuli Komla Kushitor ◽

Atsu Ayi ◽

...

Keyword(s):

Mortality Rate ◽

Infectious Diseases ◽

Cause Of Death ◽

Information Management System ◽

Health Facilities ◽

World Health ◽

Urban Region ◽

Mortality Data ◽

National Trends ◽

Ghana Health

Background The epidemiological transition, touted as occurring in Ghana, requires research that tracks the changing patterns of diseases in order to capture the trend and improve healthcare delivery. This study examines national trends in mortality rate and cause of death at health facilities in Ghana between 2014 and 2018. Methods Institutional mortality data and cause of death from 2014–2018 were sourced from the Ghana Health Service’s District Health Information Management System. The latter collates healthcare service data routinely from government and non-governmental health institutions in Ghana yearly. The institutional mortality rate was estimated using guidelines from the Ghana Health Service. Percent change in mortality was examined for 2014 and 2018. In addition, cause of death data were available for 2017 and 2018. The World Health Organisation’s 11th International Classification for Diseases (ICD-11) was used to group the cause of death. Results Institutional mortality decreased by 7% nationally over the study period. However, four out of ten regions (Greater Accra, Volta, Upper East, and Upper West) recorded increases in institutional mortality. The Upper East (17%) and Volta regions (13%) recorded the highest increase. Chronic non-communicable diseases (NCDs) were the leading cause of death in 2017 (25%) and 2018 (20%). This was followed by certain infectious and parasitic diseases (15% for both years) and respiratory infections (10% in 2017 and 13% in 2018). Among the NCDs, hypertension was the leading cause of death with 2,243 and 2,472 cases in 2017 and 2018. Other (non-ischemic) heart diseases and diabetes were the second and third leading NCDs. Septicaemia, tuberculosis and pneumonia were the predominant infectious diseases. Regional variations existed in the cause of death. NCDs showed more urban-region bias while infectious diseases presented more rural-region bias. Conclusions This study examined national trends in mortality rate and cause of death at health facilities in Ghana. Ghana recorded a decrease in institutional mortality throughout the study. NCDs and infections were the leading causes of death, giving a double-burden of diseases. There is a need to enhance efforts towards healthcare and health promotion programmes for NCDs and infectious diseases at facility and community levels as outlined in the 2020 National Health Policy of Ghana.

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Trends, patterns and cause-specific neonatal mortality in Tanzania: a hospital-based retrospective survey

International Health ◽

10.1093/inthealth/ihaa070 ◽

2020 ◽

Author(s):

Chacha D Mangu ◽

Susan F Rumisha ◽

Emanuel P Lyimo ◽

Irene R Mremi ◽

Isolide S Massawe ◽

...

Keyword(s):

Respiratory Distress ◽

Neonatal Mortality ◽

Neonatal Death ◽

Birth Asphyxia ◽

International Classification Of Diseases ◽

Mortality Rates ◽

Data Availability ◽

Mortality Data ◽

Neonatal Deaths ◽

Over Time

Abstract Background Globally, large numbers of children die shortly after birth and many of them within the first 4 wk of life. This study aimed to determine the trends, patterns and causes of neonatal mortality in hospitals in Tanzania during 2006–2015. Methods This retrospective study involved 35 hospitals. Mortality data were extracted from inpatient registers, death registers and International Classification of Diseases-10 report forms. Annual specific hospital-based neonatal mortality rates were calculated and discussed. Two periods of 2006–2010 and 2011–2015 were assessed separately to account for data availability and interventions. Results A total of 235 689 deaths were recorded and neonatal deaths accounted for 11.3% (n=26 630) of the deaths. The majority of neonatal deaths (87.5%) occurred in the first week of life. Overall hospital-based neonatal mortality rates increased from 2.6 in 2006 to 10.4 deaths per 1000 live births in 2015, with the early neonates contributing 90% to this rate constantly over time. The neonatal mortality rate was 3.7/1000 during 2006–2010 and 10.4/1000 during 2011–2015, both periods indicating a stagnant trend in the years between. The leading causes of early neonatal death were birth asphyxia (22.3%) and respiratory distress (20.8%), while those of late neonatal death were sepsis (29.1%) and respiratory distress (20.0%). Conclusion The majority of neonatal deaths in Tanzania occur among the early newborns and the trend over time indicates a slow improvement. Most neonatal deaths are preventable, hence there are opportunities to reduce mortality rates with improvements in service delivery during the first 7 d and maternal care.

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The effect of an mhealth clinical decision-making support system on neonatal mortality in Ghana

European Journal of Public Health ◽

10.1093/eurpub/ckz185.131 ◽

2019 ◽

Vol 29 (Supplement_4) ◽

Author(s):

H B Amoakoh ◽

K Klipstein-Grobusch ◽

I A Agyepong ◽

P Zuithoff ◽

M Amoakoh-Coleman ◽

...

Keyword(s):

Decision Making ◽

Neonatal Mortality ◽

Neonatal Death ◽

Clinical Decision Making ◽

Clinical Decision ◽

Mortality Data ◽

Eastern Region ◽

Intervention Period ◽

Neonatal Deaths ◽

Decision Making Support

Abstract Background Mhealth interventions promise to bridge gaps in clinical care but documentation of their effectiveness is limited. We evaluated the utilization and effect of an mhealth clinical decision-making support intervention that aimed to improve neonatal mortality in Ghana by providing access to emergency neonatal protocols for frontline health workers. Methods In the Eastern Region of Ghana, sixteen districts were randomized into two study arms (8 intervention and 8 control clusters) in a cluster-randomized controlled trial. Institutional neonatal mortality data were extracted from the District Health Information System-2 during an 18-month intervention period. We performed an intention-to-treat analysis and estimated the effect of the intervention on institutional neonatal mortality (primary outcome measure) using grouped binomial logistic regression with a random intercept per cluster. This trial is registered at ClinicalTrials.gov (NCT02468310). Results There were 65,831 institutional deliveries and 348 institutional neonatal deaths during the study period. Overall, 47·3% of deliveries and 56·9% of neonatal deaths occurred in the intervention arm. During the intervention period, neonatal deaths increased from 4·5 to 6·4 deaths and, from 3·9 to 4·3 deaths per 1,000 deliveries in the intervention arm and control arm respectively. The odds of neonatal death was non-significantly higher in the intervention arm compared to the control arm (odds ratio 2·10; 95% CI (0·77;5·77); p = 0·15). The correlation between the number of protocol requests and the number of deliveries per intervention cluster was 0·71 (p = 0·05). Conclusions Non-significant higher risk of neonatal death observed in intervention clusters may be due to problems with birth and death registration, unmeasured and unadjusted confounding, and unintended use of the intervention. The findings underpin the need for careful and rigorous evaluation of mhealth intervention implementation and effects. Key messages Supposedly effective interventions must be evaluated in context before they are scaled-up. Mechanisms influencing outcomes in context must be considered in the design and evaluation of interventions.

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Using Linked Whole-Of-Population Data to Estimate Education-Related Inequalities in Cause-Specific Mortality in Australia

International Journal for Population Data Science ◽

10.23889/ijpds.v5i5.1555 ◽

2020 ◽

Vol 5 (5) ◽

Author(s):

Jennifer Welsh ◽

Grace Joshy ◽

Lauren Moran ◽

Kay Soga ◽

Hsei Di Law ◽

...

Keyword(s):

Cause Of Death ◽

Brain Cancer ◽

Negative Binomial ◽

Health Behaviours ◽

Negative Binomial Regression ◽

Population Data ◽

Medical Intervention ◽

Mortality Data ◽

Registration Data ◽

Specific Mortality

IntroductionOfficial Australian estimates of socioeconomic inequalities in cause-specific mortality have been based on area-level socioeconomic measures. Using area-level measures is known to underestimate inequalities. Objectives and ApproachUsing recently released census linked to mortality data, we estimate education-related inequalities in cause-specific mortality for Australia. We used 2016 Australian Census and Death Registration data (2016-17) linked via a Person Linkage Spine (linkage rates: 92% and 97%, respectively) from the Multi-Agency Data Integration Project (MADIP). Education, from the Census, was categorised as low (no secondary school graduation or other qualification), intermediate (secondary graduation with/without other non-tertiary qualifications) and high (tertiary qualification). Cause of death was coded according to the underlying cause of death using the ICD-10. We used negative binomial regression to estimate relative rates (RR) for cause-specific mortality at ages 25-84 years, in the 12-months following Census, comparing low vs high education, separately by sex and 20-year age group, adjusting for age. Results80,317 deaths occurred among 13,856,202 people. For those aged 25-44 years, relative inequalities were large for causes related to injury and smaller for lesspreventable deaths (e.g. for men, suicide RR=5.6, 95%CI: 4.1-7.5 and brain cancer RR=1.3, 0.6-3.1). For those aged 45-64, inequalities were large for causes related to health behaviours and amenable to medical intervention, e.g. lung cancer (men RR= 6.4, 4.7-8.8) and ischaemic heart disease (women RR=5.0, 3.2-7.7), and were small for less preventable causes e.g. brain cancer (women RR=0.9, 0.6-1.3). Patterns among those aged 65-84years were similar to those aged 45-64 years. Conclusion / ImplicationsIn Australia, inequalities in mortality are substantial. Our findings highlight the health burden from inequalities, opportunities for prevention and provide insights on targets to effectively reduce them.

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Quality of cause-of-death data in Brazil: Garbage codes among registered deaths in 2000 and 2015

Revista Brasileira de Epidemiologia ◽

10.1590/1980-549720190002.supl.3 ◽

2019 ◽

Vol 22 (suppl 3) ◽

Cited By ~ 1

Author(s):

Renato Azeredo Teixeira ◽

Mohsen Naghavi ◽

Mark Drew Crosland Guimarães ◽

Lenice Harumi Ishitani ◽

Elizabeth Barboza França

Keyword(s):

Data Quality ◽

Cause Of Death ◽

Age Groups ◽

Health Assessment ◽

Mortality Data ◽

Laboratory Findings ◽

Northern Regions ◽

Icd 10 ◽

Death Data

ABSTRACT Introduction: reliability of mortality data is essential for health assessment and planning. In Brazil, a high proportion of deaths is attributed to causes that should not be considered as underlying causes of deaths, named garbage codes (GC). To tackle this issue, in 2005, the Brazilian Ministry of Health (MoH) implements the investigation of GC-R codes (codes from chapter 18 “Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified, ICD-10”) to improve the quality of cause-of-death data. This study analyzes the GC cause of death, considered as the indicator of data quality, in Brazil, regions, states and municipalities in 2000 and 2015. Methods: death records from the Brazilian Mortality Information System (SIM) were used. Analysis was performed for two GC groups: R codes and non-R codes, such as J18.0-J18.9 (Pneumonia unspecified). Crude and age-standardized rates, number of deaths and proportions were considered. Results: an overall improvement in the quality of mortality data in 2015 was detected, with variations among regions, age groups and size of municipalities. The improvement in the quality of mortality data in the Northeastern and Northern regions for GC-R codes is emphasized. Higher GC rates were observed among the older adults (60+ years old). The differences among the areas observed in 2015 were smaller. Conclusion: the efforts of the MoH in implementing the investigation of GC-R codes have contributed to the progress of data quality. Investment is still necessary to improve the quality of cause-of-death statistics.

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Is newborn survival influenced by place of delivery? A comparison of home, public sector and private sector deliveries in India

Journal of Biosocial Science ◽

10.1017/s0021932021000080 ◽

2021 ◽

pp. 1-15

Author(s):

Asmita Verma ◽

John Cleland

Keyword(s):

Public Sector ◽

Private Sector ◽

Neonatal Mortality ◽

Neonatal Period ◽

Uttar Pradesh ◽

Health Facilities ◽

Place Of Delivery ◽

Early Neonatal Mortality ◽

Early Neonatal Period ◽

Home Deliveries

Abstract In 2005 and again in 2011, the Government of India launched schemes to encourage institutional delivery among poor women, with the aim of improving maternal and newborn health outcomes. Partly as a result of these initiatives, the proportion of children born in a health facility rose steeply from 42% in 2000–2005 to 81% a decade later. In this context, the objective of this paper was to determine the association between place of delivery (public sector, private sector, home) and early neonatal mortality, defined as death in the first 7 days after birth. The focus was on early neonatal mortality because over half of all under-five deaths occur in his period and because the protective effect of an institutional place of birth should be strongest in those few early days. Both bivariate methods and multivariate logistic regression analysis were applied to data from the fourth round of the National Family Health Survey conducted in 2015–16. For the country as a whole, it was found that the adjusted odds of death in the early neonatal period were lower for deliveries in public health facilities than for home deliveries (OR 0.833 p<0.01), but no significant difference was found between deliveries in private health facilities and at home. Adjusted odds of death were higher for deliveries in private than public sector facilities (OR 1.41 p<0.01). On further investigation, for the poor in Bihar and Uttar Pradesh, it was found that the risks of dying in the early neonatal period were even higher for babies delivered in private health facilities than for home deliveries with adjusted odds of over 2.0. These results raise serious questions about quality of care in the private sector in India. In the context of increased emphasis on public–private partnerships in health services provision in the country, it becomes imperative to enforce better inspection, licensing and quality control of private sector facilities, especially in the states of Bihar and Uttar Pradesh.

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Modal lifespan and disparity at older ages by leading causes of death: a Canada-U.S. comparison

Journal of Population Research ◽

10.1007/s12546-020-09247-9 ◽

2020 ◽

Vol 37 (4) ◽

pp. 323-344

Author(s):

Viorela Diaconu ◽

Nadine Ouellette ◽

Robert Bourbeau

Keyword(s):

Old Age ◽

Cause Of Death ◽

Causes Of Death ◽

Heart Diseases ◽

Cerebrovascular Diseases ◽

Mortality Data ◽

Age At Death ◽

Specific Mortality ◽

The U.S ◽

Country Specific

AbstractThe U.S. elderly experience shorter lifespans and greater variability in age at death than their Canadian peers. In order to gain insight on the underlying factors responsible for the Canada-U.S. old-age mortality disparities, we propose a cause-of-death analysis. Accordingly, the objective of this paper is to compare levels and trends in cause-specific modal age at death (M) and standard deviation above the mode (SD(M +)) between Canada and the U.S. since the 1970s. We focus on six broad leading causes of death, namely cerebrovascular diseases, heart diseases, and four types of cancers. Country-specific M and SD(M +) estimates for each leading cause of death are calculated from P-spline smooth age-at-death distributions obtained from detailed population and cause-specific mortality data. Our results reveal similar levels and trends in M and SD(M +) for most causes in the two countries, except for breast cancer (females) and lung cancer (males), where differences are the most noticeable. In both of these instances, modal lifespans are shorter in the U.S. than in Canada and U.S. old-age mortality inequalities are greater. These differences are explained in part by the higher stratification along socioeconomic lines in the U.S. than in Canada regarding the adoption of health risk behaviours and access to medical services.

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