Community social valuation: use of nominal group technique in ranking of health conditions from two communities in Temeke and Moshi Districts in Tanzania

This study used the nominal group technique to explore societal value preferences in the ranking of health conditions from two communities in Temeke and Moshi districts in Tanzania. The nominal group technique was applied to a community of lay people including patients and community leaders. In this study we found a relatively high stability of ranking values across sites and informant groups. The nominal group technique was easy for lay people to understand and less time consuming compared to other methods used in health state valuation. The findings indicate that the nominal group technique can be used in the valuation process with a population of lay people to obtain societal preferences as a basis for priority setting in health. This study was limited to using criteria as a guide in the voting exercise, which may have framed respondent's final voting judgement. Further studies are needed to assess informant's responses and test validity and reliability of this method with larger sample size in different sites and informant groups. In conclusion, the nominal group technique may be considered to obtain societal preferences to compliment the current burden of disease data for priority setting. Tanzania Health Research Bulletin Vol.6(2) 2004: 42-5

Designing verbal autopsy studies

<p>Abstract</p> <p>Background</p> <p>Verbal autopsy analyses are widely used for estimating cause-specific mortality rates (CSMR) in the vast majority of the world without high-quality medical death registration. Verbal autopsies -- survey interviews with the caretakers of imminent decedents -- stand in for medical examinations or physical autopsies, which are infeasible or culturally prohibited.</p> <p>Methods and Findings</p> <p>We introduce methods, simulations, and interpretations that can improve the design of automated, data-derived estimates of CSMRs, building on a new approach by King and Lu (2008). Our results generate advice for choosing symptom questions and sample sizes that is easier to satisfy than existing practices. For example, most prior effort has been devoted to searching for symptoms with high sensitivity and specificity, which has rarely if ever succeeded with multiple causes of death. In contrast, our approach makes this search irrelevant because it can produce unbiased estimates even with symptoms that have very low sensitivity and specificity. In addition, the new method is optimized for survey questions caretakers can easily answer rather than questions physicians would ask themselves. We also offer an automated method of weeding out biased symptom questions and advice on how to choose the number of causes of death, symptom questions to ask, and observations to collect, among others.</p> <p>Conclusions</p> <p>With the advice offered here, researchers should be able to design verbal autopsy surveys and conduct analyses with greatly reduced statistical biases and research costs.</p

Rural to Urban Migration and Changes in Cardiovascular risk Factors in Tanzania: A Prospective Cohort Study.

High levels of rural to urban migration are a feature of most African countries. Our aim was to investigate changes, and their determinants, in cardiovascular risk factors on rural to urban migration in Tanzania. Men and women (15 to 59 years) intending to migrate from Morogoro rural region to Dar es Salaam for at least 6 months were identified. Measurements were made at least one week but no more than one month prior to migration, and 1 to 3 monthly after migration. Outcome measures included body mass index, blood pressure, fasting lipids, and self reported physical activity and diet. One hundred and three men, 106 women, mean age 29 years, were recruited and 132 (63.2%) followed to 12 months. All the figures presented here refer to the difference between baseline and 12 months in these 132 individuals. Vigorous physical activity declined (79.4% to 26.5% in men, 37.8% to 15.6% in women, p < 0.001), and weight increased (2.30 kg men, 2.35 kg women, p < 0.001). Intake of red meat increased, but so did the intake of fresh fruit and vegetables. HDL cholesterol increased in men and women (0.24, 0.25 mmoll-1 respectively, p < 0.001); and in men, not women, total cholesterol increased (0.42 mmoll-1, p = 0.01), and triglycerides fell (0.31 mmoll-1, p = 0.034). Blood pressure appeared to fall in both men and women. For example, in men systolic blood pressure fell by 5.4 mmHg, p = 0.007, and in women by 8.6 mmHg, p = 0.001. The lower level of physical activity and increasing weight will increase the risk of diabetes and cardiovascular disease. However, changes in diet were mixed, and may have contributed to mixed changes in lipid profiles and a lack of rise in blood pressure. A better understanding of the changes occurring on rural to urban migration is needed to guide preventive measures

Cause-of-death ascertainment for deaths that occur outside hospitals in Thailand: application of verbal autopsy methods

Background: Ascertainment of cause for deaths that occur in the absence of medical attention is a significant problem in many countries, including Thailand, where more than 50% of such deaths are registered with ill-defined causes. Routine implementation of standardized, rigorous verbal autopsy methods is a potential solution. This paper reports findings from field research conducted to develop, test, and validate the use of verbal autopsy (VA) methods in Thailand.Methods: International verbal autopsy methods were first adapted to the Thai context and then implemented to ascertain causes of death for a nationally representative sample of 11,984 deaths that occurred in Thailand in 2005. Causes of death were derived from completed VA questionnaires by physicians trained in ICD-based cause-of-death certification. VA diagnoses were validated in the sample of hospital deaths for which reference diagnoses were available from medical record review. Validated study findings were used to adjust VA-based causes of death derived for deaths in the study sample that had occurred outside hospitals. Results were used to estimate cause-specific mortality patterns for deaths outside hospitals in Thailand in 2005.Results: VA-based causes of death were derived for 6,328 out of 7,340 deaths in the study sample that had occurred outside hospitals, constituting the verification arm of the study. The use of VA resulted in large-scale reassignment of deaths from ill-defined categories to specific causes of death. The validation study identified that VA tends to overdiagnose important causes such as diabetes, liver cancer, and tuberculosis, while undercounting deaths from HIV/AIDS, liver diseases, genitourinary (essential renal), and digestive system disorders.Conclusions: The use of standard VA methods adapted to Thailand enabled a plausible assessment of cause-specific mortality patterns and a substantial reduction of ill-defined diagnoses. Validation studies enhance the utility of findings from the application of verbal autopsy. Regular implementation of VA in Thailand could accelerate development of the quality and utility of vital registration data for deaths outside hospitals

Mortality Measurement Matters: Improving Data Collection and Estimation Methods for Child and Adult Mortality

Colin Mathers and Ties Boerma discuss three research articles in PLoS Medicine that address the measurement and analysis of child and adult mortality data collected through death registration, censuses, and household surveys

Revising the WHO verbal autopsy instrument to facilitate routine cause-of-death monitoring.

OBJECTIVE: Verbal autopsy (VA) is a systematic approach for determining causes of death (CoD) in populations without routine medical certification. It has mainly been used in research contexts and involved relatively lengthy interviews. Our objective here is to describe the process used to shorten, simplify, and standardise the VA process to make it feasible for application on a larger scale such as in routine civil registration and vital statistics (CRVS) systems. METHODS: A literature review of existing VA instruments was undertaken. The World Health Organization (WHO) then facilitated an international consultation process to review experiences with existing VA instruments, including those from WHO, the Demographic Evaluation of Populations and their Health in Developing Countries (INDEPTH) Network, InterVA, and the Population Health Metrics Research Consortium (PHMRC). In an expert meeting, consideration was given to formulating a workable VA CoD list [with mapping to the International Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) CoD] and to the viability and utility of existing VA interview questions, with a view to undertaking systematic simplification. FINDINGS: A revised VA CoD list was compiled enabling mapping of all ICD-10 CoD onto 62 VA cause categories, chosen on the grounds of public health significance as well as potential for ascertainment from VA. A set of 221 indicators for inclusion in the revised VA instrument was developed on the basis of accumulated experience, with appropriate skip patterns for various population sub-groups. The duration of a VA interview was reduced by about 40% with this new approach. CONCLUSIONS: The revised VA instrument resulting from this consultation process is presented here as a means of making it available for widespread use and evaluation. It is envisaged that this will be used in conjunction with automated models for assigning CoD from VA data, rather than involving physicians

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

Performance of InterVA for assigning causes of death to verbal autopsies: multisite validation study using clinical diagnostic gold standards

Background: InterVA is a widely disseminated tool for cause of death attribution using information from verbal autopsies. Several studies have attempted to validate the concordance and accuracy of the tool, but the main limitation of these studies is that they compare cause of death as ascertained through hospital record review or hospital discharge diagnosis with the results of InterVA. This study provides a unique opportunity to assess the performance of InterVA compared to physician-certified verbal autopsies (PCVA) and alternative automated methods for analysis.Methods: Using clinical diagnostic gold standards to select 12,542 verbal autopsy cases, we assessed the performance of InterVA on both an individual and population level and compared the results to PCVA, conducting analyses separately for adults, children, and neonates. Following the recommendation of Murray et al., we randomly varied the cause composition over 500 test datasets to understand the performance of the tool in different settings. We also contrasted InterVA with an alternative Bayesian method, Simplified Symptom Pattern (SSP), to understand the strengths and weaknesses of the tool.Results: Across all age groups, InterVA performs worse than PCVA, both on an individual and population level. On an individual level, InterVA achieved a chance-corrected concordance of 24.2% for adults, 24.9% for children, and 6.3% for neonates (excluding free text, considering one cause selection). On a population level, InterVA achieved a cause-specific mortality fraction accuracy of 0.546 for adults, 0.504 for children, and 0.404 for neonates. The comparison to SSP revealed four specific characteristics that lead to superior performance of SSP. Increases in chance-corrected concordance are attained by developing cause-by-cause models (2%), using all items as opposed to only the ones that mapped to InterVA items (7%), assigning probabilities to clusters of symptoms (6%), and using empirical as opposed to expert probabilities (up to 8%).Conclusions: Given the widespread use of verbal autopsy for understanding the burden of disease and for setting health intervention priorities in areas that lack reliable vital registrations systems, accurate analysis of verbal autopsies is essential. While InterVA is an affordable and available mechanism for assigning causes of death using verbal autopsies, users should be aware of its suboptimal performance relative to other methods

Factors Associated with Physician Agreement on Verbal Autopsy of over 11500 Injury Deaths in India

Worldwide, injuries account for 9.8% of all deaths. The majority of these deaths occur in low- and middle-income countries where vital registration systems are often inadequate. Verbal autopsy (VA) is a tool used to ascertain cause of death in such settings. Validation studies for VA using hospital diagnosed causes of death as comparisons have shown that injury deaths can be reliably diagnosed by VA. However, no study has assessed the factors that may affect physicians' abilities to code specific causes of injury death using VA.This study used data from over 11 500 verbal autopsies of injury deaths from the Million Death Study (MDS) in which 6.3 million people in India were monitored from 2001–2003 for vital events. Deaths that occurred in the MDS were coded by two independent physicians. This study focused on whether physician agreement on the classification of injury deaths was affected by characteristics of the deceased and respondent. Agreement was analyzed using three primary methods: 1) kappa statistic; 2) sensitivity and specificity analysis using the final VA diagnosed category of injury death as gold standard; and 3) multivariate logistic regression using a conceptual hierarchical model. The overall agreement for all injury deaths was 77.9% with a kappa of 0.74 (99% CI 0.74–0.75). Deaths in the injury categories of “transport”, “falls”, “drowning” and “other unintentional injury” occurring outside the home were associated with greater physician agreement than those occurring at home. In contrast, self-inflicted injury deaths that occurred outside the home were associated with lower physician agreement.With few exceptions, most characteristics of the deceased and the respondent did not influence physician agreement on the classification of injury deaths. Physician training and continued adaptation of the VA tool should focus on the reasons these factors influenced physician agreement

Effects on the estimated cause-specific mortality fraction of providing physician reviewers with different formats of verbal autopsy data

Background: The process of data collection and the methods used to assign the cause of death vary significantly among different verbal autopsy protocols, but there are few data to describe the consequences of the choices made. The aim of this study was to objectively define the impact of the format of data presented to physician reviewers on the cause-specific mortality fractions defined by a verbal autopsy-based mortality-surveillance system.Methods: Verbal autopsies were done by primary health care workers for all deaths between October 2006 and September 2007 in a community in rural Andhra Pradesh, India (total population about 180,162). Each questionnaire had a structured section, composed of a series of check boxes, and a free-text section, in which a narrative description of the events leading to death was recorded. For each death, a physician coder was presented first with one section and then the other in random order with a 20- to 40-day interval between. A cause of death was recorded for each data format at the level of ICD 10 chapter headings or else the death was documented as unclassified. After another 20- to 40-day interval, both the structured and free-text sections of the questionnaire were presented together and an index cause of death was assigned.Results: In all, 1,407 verbal autopsies were available for analysis, representing 94% of all deaths recorded in the population that year. An index cause of death was assigned using the combined data for 1,190 with the other 217 remaining unclassified. The observed cause-specific mortality fractions were the same regardless of whether the structured, free-text or combined data sources were used. At the individual level, the assignments made using the structured format matched the index in 1,012 (72%) of cases with a kappa statistic of 0.66. For the free-text format, the corresponding figures were 989 (70%) and 0.64.Conclusions: The format of the verbal autopsy data used to assign a cause of death did not substantively influence the pattern of mortality estimated. Substantially abbreviated and simplified verbal autopsy questionnaires might provide robust information about high-level mortality patterns. © 2011 Joshi et al; licensee BioMed Central Ltd