Hospital mortality statistics in Tanzania: availability, accessibility, and quality 2006-2015

Patterns and trends of in-hospital mortality due to non-communicable diseases and injuries in Tanzania, 2006-2015

BACKGROUND

Globally, non-communicable diseases (NCD) kill about 40 million people annually, with about three-quarters of the deaths occurring in low- and middle-income countries. This study was carried out to determine the patterns, trends, and causes of in-hospital non-communicable disease (NCD) and injury deaths in Tanzania from 2006-2015.

METHODS

This retrospective study involved primary, secondary, tertiary, and specialized hospitals. Death statistics were extracted from inpatient department registers, death registers, and International Classification of Diseases (ICD) report forms. The ICD-10 coding system was used to assign each death to its underlying cause. The analysis determined leading causes by age, sex, annual trend and calculate hospital-based mortality rates.

RESULTS

Thirty-nine hospitals were involved in this study. A total of 247,976 deaths (all causes) were reported during the 10-year period. Of the total deaths, 67,711 (27.3%) were due to NCD and injuries. The most (53.4%) affected age group was 15-59 years. Cardio-circulatory diseases (31.9%), cancers (18.6%), chronic respiratory diseases (18.4%), and injuries (17.9%) accounted for the largest proportion (86.8%) of NCD and injuries deaths. The overall 10-year hospital-based age-standardized mortality rate (ASMR) for all NCDs and injuries was 559.9 per 100,000 population. It was higher for males (638.8/100,000) than for females (444.6/100,000). The hospital-based annual ASMR significantly increased from 11.0 in 2006 to 62.8 per 100,000 populations in 2015.

CONCLUSIONS

There was a substantial increase in hospital-based ASMR due to NCDs and injuries in Tanzania from 2006 to 2015. Most of the deaths affected the productive young adult group. This burden indicates that families, communities, and the nation at large suffer from premature deaths. The government of Tanzania should invest in early detection and timely management of NCDs and injuries to reduce premature deaths. This should go hand-in-hand with continuous efforts to improve the quality of health data and its utilization.

Improving disease surveillance data analysis, interpretation, and use at the district level in Tanzania

An effective disease surveillance system is critical for early detection and response to disease epidemics. This study aimed to assess the capacity to manage and utilize disease surveillance data and implement an intervention to improve data analysis and use at the district level in Tanzania. Mapping, in-depth interview and desk review were employed for data collection in Ilala and Kinondoni districts in Tanzania. Interviews were conducted with members of the council health management teams (CHMT) to assess attitudes, motivation and practices related to surveillance data analysis and use. Based on identified gaps, an intervention package was developed on basic data analysis, interpretation and use. The effectiveness of the intervention package was assessed using pre-and post-intervention tests. Individual interviews involved 21 CHMT members (females = 10; males = 11) with an overall median age of 44.5 years (IQR = 37, 53). Over half of the participants regarded their data analytical capacities and skills as excellent. Analytical capacity was higher in Kinondoni (61%) than Ilala (52%). Agreement on the availability of the opportunities to enhance capacity and skills was reported by 68% and 91% of the participants from Ilala and Kinondoni, respectively. Reported challenges in disease surveillance included data incompleteness and difficulties in storage and accessibility. Training related to enhancement of data management was reported to be infrequently done. In terms of data interpretation and use, despite reporting of incidence of viral haemorrhagic fevers for five years, no actions were taken to either investigate or mitigate, indicating poor use of surveillance data in monitoring disease occurrence. The overall percentage increase on surveillance knowledge between pre-and post-training was 37.6% for Ilala and 20.4% for Kinondoni indicating a positive impact on of the training. Most of CHMT members had limited skills and practices on data analysis, interpretation and use. The training in data analysis and interpretation significantly improved skills of the participants.

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

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.

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

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.

Data utilisation and factors influencing the performance of the health management information system in Tanzania

BACKGROUND

Health Management Information System (HMIS) is a set of data regularly collected at health care facilities to meet the needs of statistics on health services. This study aimed to determine the utilisation of HMIS data and factors influencing the health system's performance at the district and primary health care facility levels in Tanzania.

METHODS

This cross-sectional study was carried out in 11 districts and involved 115 health care facilities in Tanzania. Data were collected using a semi-structured questionnaire administered to health workers at facility and district levels and documented using an observational checklist. Thematic content analysis approach was used to synthesise and triangulate the responses and observations to extract essential information.

RESULTS

A total of 93 healthcare facility workers and 13 district officials were interviewed. About two-thirds (60%) of the facility respondents reported using the HMIS data, while only five out of 13 district respondents (38.5%) reported analysing HMIS data routinely. The HMIS data were mainly used for comparing performance in terms of services coverage (53%), monitoring of disease trends over time (50%), and providing evidence for community health education and promotion programmes (55%). The majority (41.4%) of the facility's personnel had not received any training on data management related to HMIS during the past 12 months prior to the survey. Less than half (42%) of the health facilities had received supervisory visits from the district office 3 months before this assessment. Nine district respondents (69.2%) reported systematically receiving feedback on the quality of their reports monthly and quarterly from higher authorities. Patient load was described to affect staff performance on data collection and management frequently.

CONCLUSION

Inadequate analysis and poor data utilisation practices were common in most districts and health facilities in Tanzania. Inadequate human and financial resources, lack of incentives and supervision, and lack of standard operating procedures on data management were the significant challenges affecting the HMIS performance in Tanzania.

Making every death count: institutional mortality accuracy at Ola During Children's Hospital, Sierra Leone

Introduction

health care data accuracy feeds the development of sound healthcare policy and the prioritisation of interventions in scarce resource environments. We designed a retrospective study at the sole paediatric government hospital in Sierra Leone to examine mortality statistics, specifically: the accuracy of mortality data collected in 2017; and the quality of cause of death (CoD) reporting for 2017.

Methods

the retrospective audit included all available mortality statistics collected at the hospital during the 2017 calendar year. For the purpose of calculating a mortality rate, admission data was additionally gathered. Four different hospital entities were identified that collected mortality data (the Monitoring and Evaluation (M&E) office; the nurse ledgers; the office of births and deaths; and the mortuary). Data from each hospital entity were used for the comparative analysis.

Results

striking differences were found in the rate of hospital mortality reported by different entities. The M&E office (responsible for providing data to the ministry of health and sanitation) reported a hospital mortality rate of 2.94% in 2017. Mortuary and nursing admissions records showed a hospital mortality rate of 18.7%. Discrepancies and issues of quality in CoD reporting between hospital entities were identified.

Conclusion

significant variations were found in the generation of official hospital mortality data. Mortality data informs health service prioritisation, resource distribution, outcome measures and epidemiological surveillance. Resources to support quality improvement initiatives are needed in the creation of an in-hospital system that reports accurate data with a process for real-time institutional data feedback.

Data quality of the routine health management information system at the primary healthcare facility and district levels in Tanzania

BACKGROUND

Effective planning for disease prevention and control requires accurate, adequately-analysed, interpreted and communicated data. In recent years, efforts have been put in strengthening health management information systems (HMIS) in Sub-Saharan Africa to improve data accessibility to decision-makers. This study assessed the quality of routine HMIS data at primary healthcare facility (HF) and district levels in Tanzania.

METHODS

This cross-sectional study involved reviews of documents, information systems and databases, and collection of primary data from facility-level registers, tally sheets and monthly summary reports. Thirty-four indicators from Outpatient, Inpatient, Antenatal care, Family Planning, Post-natal care, Labour and Delivery, and Provider-Initiated Testing and Counselling service areas were assessed. Indicator records were tracked and compared across the process of data collection, compilation and submission to the district office. Copies of monthly report forms submitted by facilities to the district were also reviewed. The availability and utilization of HMIS tools were assessed, while completeness and data accuracy levels were quantified for each phase of the reporting system.

RESULTS

A total of 115 HFs (including hospitals, health centres, dispensaries) in 11 districts were involved. Registers (availability rate = 91.1%; interquartile range (IQR) 66.7-100%) and report forms (86.9%; IQR 62.2-100%) were the most utilized tools. There was a limited use of tally-sheets (77.8%; IQR 35.6-100%). Tools availability at the dispensary was 91.1%, health centre 82.2% and hospital 77.8%, and was low in urban districts. The availability rate at the district level was 65% (IQR 48-75%). Wrongly filled or empty cells in registers and poor adherence to the coding procedures were observed. Reports were highly over-represented in comparison to registers' records, with large differences observed at the HF phase of the reporting system. The OPD and IPD areas indicated the highest levels of mismatch between data source and district office. Indicators with large number of clients, multiple variables, disease categorization, or those linked with dispensing medicine performed poorly.

CONCLUSION

There are high variations in the tool utilisation and data accuracy at facility and district levels. The routine HMIS is weak and data at district level inaccurately reflects what is available at the source. These results highlight the need to design tailored and inter-service strategies for improving data quality.

Years of potential life lost and productivity costs due to premature mortality from six priority diseases in Tanzania, 2006-2015

Background

Mortality statistics are traditionally used to quantify the burden of disease and to determine the relative importance of the various causes of death. Some of the most frequently used indices to quantify the burden of disease are the years of potential life lost (YPLL) and years of potential productive life lost (YPPLL). These two measures reflect the mortality trends in younger age groups and they provide a more accurate picture of premature mortality. This study was carried out to determine YPLL, YPPLL and cost of productivity lost (CPL) due to premature mortality caused by selected causes of deaths in Tanzania.

Methods and findings

Malaria, respiratory diseases, HIV/AIDS, tuberculosis, cancers and injuries were selected for this analysis. The number of deaths by sex and age groups were obtained from hospital death registers and ICD-10 reporting forms in 39 public hospitals in Tanzania, covering a period of 2006–2015. The life expectancy method and human capital approach were used to estimate the YPLL, YPPLL and CPL due to premature mortality. During 2006–2015, malaria, HIV/AIDS, tuberculosis, respiratory diseases, HIV+tuberculosis, cancer and injury were responsible for a total of 96,834 hospital deaths, of which 46.4% (n = 57,508) were among individuals in the productive age groups (15–64 years). The reported deaths contributed to 2,850,928 YPLL (female = 1,326,724; male = 1,524,205) with an average of 29 years per death. The average YPLL among females (32) was higher than among males (28). Malaria (YPLL = 38 per death) accounted for over one-third (35%) of the total YPLL. There was a significant increase in YPLL due to the selected underlying causes of death over the 10-year period. Deaths from the selected causes resulted into 1,207,499 YPPLL (average = 21 per death). Overall, HIV/AIDS contributed to the highest YPPLL (323,704), followed by malaria (243,490) and injuries (196,505). While there was a general decrease in YPPLL due to malaria, there was an increase of YPPLL due to HIV/AIDS, respiratory diseases, cancer and injuries during the 10-year period. The total CPL due to the six diseases was US$ 148,430,009 for 10 years. The overall CPL was higher among males than females by 29.1%. Over half (58%) of the losses were due to deaths among males. HIV/AIDS accounted for the largest (29.2%) CPL followed by malaria (17.8%) and respiratory diseases (14.6%). The CPL increased from US$11.4 million in 2006 to US$17.9 million in 2016.

Conclusions

The YPLL, YPPLL and CPL due to premature death associated with the six diseases in Tanzania are substantially high. While malaria accounted for highest YPLL, HIV/AIDS accounted for highest YPPLL and CPL. The overall CPL was higher among males than among females. Setting resource allocation priorities to malaria, HIV/AIDS and respiratory diseases that are responsible for the majority of premature deaths could potentially reduce the costs of productivity loss in Tanzania.

Mortality Patterns of Toxoplasmosis and Its Comorbidities in Tanzania: A 10-Year Retrospective Hospital-Based Survey

Introduction: Toxoplasmosis is a parasitic zoonosis and an important cause of abortions, mental retardation, encephalitis, blindness, and death worldwide. Few studies have quantified toxoplasmosis mortality and associated medical conditions in Sub-Saharan Africa. This retrospective hospital-based study aimed to determine the mortality patterns of toxoplasmosis and its comorbidities among in-patients in Tanzania. Methods: Data on causes of death were collected using customized paper-based collection tools. Sources of data included death registers, inpatient registers, and International Classification of Diseases report forms. All death events from January 2006 to December 2015 were collected. Data used in this study is a subset of deaths where the underlying cause of death was toxoplasmosis. Data was analyzed by STATA programme version 13. Results: Thirty-seven public hospitals were involved in the study. A total of 188 deaths due to toxoplasmosis were reported during the 10-years period. Toxoplasmosis deaths accounted for 0.08% (188/247,976) of the total deaths recorded. The age-standardized mortality rate per 100,000 population increased from 0.11 in 2006 to 0.79 in 2015. Most deaths due to toxoplasmosis affected the adult age category. Of the 188 deaths, males accounted for 51.1% while females for 48.9% of the deaths. Dar es Salaam, Mbeya, Pwani, Tanga, and Mwanza contributed to over half (59.05%) of all deaths due to Toxoplasmosis. Of the total deaths due to toxoplasmosis, 70.7% were associated with other medical conditions; which included HIV/AIDS (52.6%), HIV/AIDS+Cryptococcal meningitis (18.8%) and HIV+Pneumocystis pneumonia (6.8%). Conclusion: The age-standardized mortality rate due to toxoplasmosis has been increasing substantially between 2006 and 2015. Most deaths due to toxoplasmosis affected the adult age category and were highly associated with HIV/AIDS. Appropriate interventions are needed to alleviate the burden of toxoplasmosis in Tanzania.