Devarsetty Praveen

Population Health Metrics Research Consortium gold standard verbal autopsy validation study: design, implementation, and development of analysis datasets

BackgroundVerbal autopsy methods are critically important for evaluating the leading causes of death in populations without adequate vital registration systems. With a myriad of analytical and data collection approaches, it is essential to create a high quality validation dataset from different populations to evaluate comparative method performance and make recommendations for future verbal autopsy implementation. This study was undertaken to compile a set of strictly defined gold standard deaths for which verbal autopsies were collected to validate the accuracy of different methods of verbal autopsy cause of death assignment.MethodsData collection was implemented in six sites in four countries: Andhra Pradesh, India; Bohol, Philippines; Dar es Salaam, Tanzania; Mexico City, Mexico; Pemba Island, Tanzania; and Uttar Pradesh, India. The Population Health Metrics Research Consortium (PHMRC) developed stringent diagnostic criteria including laboratory, pathology, and medical imaging findings to identify gold standard deaths in health facilities as well as an enhanced verbal autopsy instrument based on World Health Organization (WHO) standards. A cause list was constructed based on the WHO Global Burden of Disease estimates of the leading causes of death, potential to identify unique signs and symptoms, and the likely existence of sufficient medical technology to ascertain gold standard cases. Blinded verbal autopsies were collected on all gold standard deaths.ResultsOver 12,000 verbal autopsies on deaths with gold standard diagnoses were collected (7,836 adults, 2,075 children, 1,629 neonates, and 1,002 stillbirths). Difficulties in finding sufficient cases to meet gold standard criteria as well as problems with misclassification for certain causes meant that the target list of causes for analysis was reduced to 34 for adults, 21 for children, and 10 for neonates, excluding stillbirths. To ensure strict independence for the validation of methods and assessment of comparative performance, 500 test-train datasets were created from the universe of cases, covering a range of cause-specific compositions.ConclusionsThis unique, robust validation dataset will allow scholars to evaluate the performance of different verbal autopsy analytic methods as well as instrument design. This dataset can be used to inform the implementation of verbal autopsies to more reliably ascertain cause of death in national health information systems.

Using verbal autopsy to measure causes of death: the comparative performance of existing methods

BackgroundMonitoring progress with disease and injury reduction in many populations will require widespread use of verbal autopsy (VA). Multiple methods have been developed for assigning cause of death from a VA but their application is restricted by uncertainty about their reliability.MethodsWe investigated the validity of five automated VA methods for assigning cause of death: InterVA-4, Random Forest (RF), Simplified Symptom Pattern (SSP), Tariff method (Tariff), and King-Lu (KL), in addition to physician review of VA forms (PCVA), based on 12,535 cases from diverse populations for which the true cause of death had been reliably established. For adults, children, neonates and stillbirths, performance was assessed separately for individuals using sensitivity, specificity, Kappa, and chance-corrected concordance (CCC) and for populations using cause specific mortality fraction (CSMF) accuracy, with and without additional diagnostic information from prior contact with health services. A total of 500 train-test splits were used to ensure that results are robust to variation in the underlying cause of death distribution.ResultsThree automated diagnostic methods, Tariff, SSP, and RF, but not InterVA-4, performed better than physician review in all age groups, study sites, and for the majority of causes of death studied. For adults, CSMF accuracy ranged from 0.764 to 0.770, compared with 0.680 for PCVA and 0.625 for InterVA; CCC varied from 49.2% to 54.1%, compared with 42.2% for PCVA, and 23.8% for InterVA. For children, CSMF accuracy was 0.783 for Tariff, 0.678 for PCVA, and 0.520 for InterVA; CCC was 52.5% for Tariff, 44.5% for PCVA, and 30.3% for InterVA. For neonates, CSMF accuracy was 0.817 for Tariff, 0.719 for PCVA, and 0.629 for InterVA; CCC varied from 47.3% to 50.3% for the three automated methods, 29.3% for PCVA, and 19.4% for InterVA. The method with the highest sensitivity for a specific cause varied by cause.ConclusionsPhysician review of verbal autopsy questionnaires is less accurate than automated methods in determining both individual and population causes of death. Overall, Tariff performs as well or better than other methods and should be widely applied in routine mortality surveillance systems with poor cause of death certification practices.

Use of mHealth Systems and Tools for Non-Communicable Diseases in Low- and Middle-Income Countries: a Systematic Review

With the rapid adoption of mobile devices, mobile health (mHealth) offers the potential to transform health care delivery, especially in the world’s poorest regions. We systematically reviewed the literature to determine the impact of mHealth interventions on health care quality for non-communicable diseases in low- and middle-income countries and to identify knowledge gaps in this rapidly evolving field. Overall, we found few high-quality studies. Most studies narrowly focused on text messaging systems for patient behavior change, and few studies examined the health systems strengthening aspects of mHealth. There were limited literature reporting clinical effectiveness, costs, and patient acceptability, and none reporting equity and safety issues. Despite the bold promise of mHealth to improve health care, much remains unknown about whether and how this will be fulfilled. Encouragingly, we identified some registered clinical trial protocols of large-scale, multidimensional mHealth interventions, suggesting that the current limited evidence base will expand in coming years.

SMARTHealth India: Development and Field Evaluation of a Mobile Clinical Decision Support System for Cardiovascular Diseases in Rural India

Background Cardiovascular disease (CVD) is the major cause of premature death and disability in India and yet few people at risk of CVD are able to access best practice health care. Mobile health (mHealth) is a promising solution, but very few mHealth interventions have been subjected to robust evaluation in India. Objective The objectives were to develop a multifaceted, mobile clinical decision support system (CDSS) for CVD management and evaluate it for use by public nonphysician health care workers (NPHWs) and physicians in a rural Indian setting. Methods Plain language clinical rules were developed based on standard guidelines and programmed into a computer tablet app. The algorithm was validated and field-tested in 11 villages in Andhra Pradesh, involving 11 NPHWs and 3 primary health center (PHC) physicians. A mixed method evaluation was conducted comprising clinical and survey data and in-depth patient and staff interviews to understand barriers and enablers to the use of the system. Then this was thematically analyzed using NVivo 10. Results During validation of the algorithm, there was an initial agreement for 70% of the 42 calculated variables between the CDSS and SPSS software outputs. Discrepancies were identified and amendments were made until perfect agreement was achieved. During field testing, NPHWs and PHC physicians used the CDSS to screen 227 and 65 adults, respectively. The NPHWs identified 39% (88/227) of patients for referral with 78% (69/88) of these having a definite indication for blood pressure (BP)-lowering medication. However, only 35% (24/69) attended a clinic within 1 month of referral, with 42% (10/24) of these reporting continuing medications at 3-month follow-up. Physicians identified and recommended 17% (11/65) of patients for BP-lowering medications. Qualitative interviews identified 3 interrelated interview themes: (1) the CDSS had potential to change prevailing health care models, (2) task-shifting to NPHWs was the central driver of change, and (3) despite high acceptability by end users, actual transformation was substantially limited by system-level barriers such as patient access to doctors and medicines. Conclusions A tablet-based CDSS implemented within primary health care systems has the potential to help improve CVD outcomes in India. However, system-level barriers to accessing medical care limit its full impact. These barriers need to be actively addressed for clinical innovations to be successful. Trial Registration Clinical Trials Registry of India: CTRI/2013/06/003753; http://ctri.nic.in/Clinicaltrials/showallp.php?mid1=6259&EncHid=51761.70513&userName=CTRI/2013/06/003753 (Archived by WebCite at http://www.webcitation.org/6UBDlrEuq).

Engineering a mobile health tool for resource-poor settings to assess and manage cardiovascular disease risk: SMARThealth study

BackgroundThe incidence of chronic diseases in low- and middle-income countries is rapidly increasing both in urban and rural regions. A major challenge for health systems globally is to develop innovative solutions for the prevention and control of these diseases. This paper discusses the development and pilot testing of SMARTHealth, a mobile-based, point-of-care Clinical Decision Support (CDS) tool to assess and manage cardiovascular disease (CVD) risk in resource-constrained settings. Through pilot testing, the preliminary acceptability, utility, and efficiency of the CDS tool was obtained.MethodsThe CDS tool was part of an mHealth system comprising a mobile application that consisted of an evidence-based risk prediction and management algorithm, and a server-side electronic medical record system. Through an agile development process and user-centred design approach, key features of the mobile application that fitted the requirements of the end users and environment were obtained. A comprehensive analytics framework facilitated a data-driven approach to investigate four areas, namely, system efficiency, end-user variability, manual data entry errors, and usefulness of point-of-care management recommendations to the healthcare worker. A four-point Likert scale was used at the end of every risk assessment to gauge ease-of-use of the system.ResultsThe system was field-tested with eleven village healthcare workers and three Primary Health Centre doctors, who screened a total of 292 adults aged 40 years and above. 34% of participants screened by health workers were identified by the CDS tool to be high CVD risk and referred to a doctor. In-depth analysis of user interactions found the CDS tool feasible for use and easily integrable into the workflow of healthcare workers. Following completion of the pilot, further technical enhancements were implemented to improve uptake of the mHealth platform. It will then be evaluated for effectiveness and cost-effectiveness in a cluster randomized controlled trial involving 54 southern Indian villages and over 16000 individuals at high CVD risk.ConclusionsAn evidence-based CVD risk prediction and management tool was used to develop an mHealth platform in rural India for CVD screening and management with proper engagement of health care providers and local communities. With over a third of screened participants being high risk, there is a need to demonstrate the clinical impact of the mHealth platform so that it could contribute to improved CVD detection in high risk low resource settings.

Behaviour change strategies for reducing blood pressure-related disease burden: findings from a global implementation research programme

BackgroundThe Global Alliance for Chronic Diseases comprises the majority of the world’s public research funding agencies. It is focussed on implementation research to tackle the burden of chronic diseases in low- and middle-income countries and amongst vulnerable populations in high-income countries. In its inaugural research call, 15 projects were funded, focussing on lowering blood pressure-related disease burden. In this study, we describe a reflexive mapping exercise to identify the behaviour change strategies undertaken in each of these projects.MethodsUsing the Behaviour Change Wheel framework, each team rated the capability, opportunity and motivation of the various actors who were integral to each project (e.g. community members, non-physician health workers and doctors in projects focussed on service delivery). Teams then mapped the interventions they were implementing and determined the principal policy categories in which those interventions were operating. Guidance was provided on the use of Behaviour Change Wheel to support consistency in responses across teams. Ratings were iteratively discussed and refined at several group meetings.ResultsThere was marked variation in the perceived capabilities, opportunities and motivation of the various actors who were being targeted for behaviour change strategies. Despite this variation, there was a high degree of synergy in interventions functions with most teams utilising complex interventions involving education, training, enablement, environmental restructuring and persuasion oriented strategies. Similar policy categories were also targeted across teams particularly in the areas of guidelines, communication/marketing and service provision with few teams focussing on fiscal measures, regulation and legislation.ConclusionsThe large variation in preparedness to change behaviour amongst the principal actors across these projects suggests that the interventions themselves will be variably taken up, despite the similarity in approaches taken. The findings highlight the importance of contextual factors in driving success and failure of research programmes. Forthcoming outcome and process evaluations from each project will build on this exploratory work and provide a greater understanding of factors that might influence scale-up of intervention strategies.

Comparability of HbA1c and lipids measured with dried blood spot versus venous samples: a systematic review and meta-analysis

BackgroundLevels of haemoglobin A1c (HbA1c) and blood lipids are important determinants of risk in patients with diabetes. Standard analysis methods based upon venous blood samples can be logistically challenging in resource-poor settings where much of the diabetes epidemic is occurring. Dried blood spots (DBS) provide a simple alternative method for sample collection but the comparability of data from analyses based on DBS is not well established.MethodsWe conducted a systematic review and meta-analysis to define the association of findings for HbA1c and blood lipids for analyses based upon standard methods compared to DBS. The Cochrane, Embase and Medline databases were searched for relevant reports and summary regression lines were estimated.Results705 abstracts were found by the initial electronic search with 6 further reports identified by manual review of the full papers. 16 studies provided data for one or more outcomes of interest. There was a close agreement between the results for HbA1c assays based on venous and DBS samples (DBS = 0.9858venous + 0.3809), except for assays based upon affinity chromatography. Significant adjustment was required for assays of total cholesterol (DBS = 0.6807venous + 1.151) but results for triglycerides (DBS = 0.9557venous + 0.1427) were directly comparable.ConclusionsFor HbA1c and selected blood lipids, assays based on DBS samples are clearly associated with assays based on standard venous samples. There are, however, significant uncertainties about the nature of these associations and there is a need for standardisation of the sample collection, transportation, storage and analysis methods before the technique can be considered mainstream. This should be a research priority because better elucidation of metabolic risks in resource poor settings, where venous sampling is infeasible, will be key to addressing the global epidemic of cardiovascular diseases.

Mean population salt consumption in India: a systematic review

Background: Member states of the WHO, including India, have adopted a target 30% reduction in mean population salt consumption by 2025 to prevent noncommunicable diseases. Our aim was to support this initiative by summarizing existing data that describe mean salt consumption in India. Method: Electronic databases – MEDLINE via Ovid, EMBASE, CINAHL and the Cochrane Database of Systematic Reviews – were searched up to November 2015 for studies that reported mean or median dietary salt intake in Indian adults aged 19 years and older. Random effects meta-analysis was used to obtain summary estimates of salt intake. Results: Of 1201 abstracts identified, 90 were reviewed in full text and 21 were included: 18 cross-sectional surveys (n = 225 024), two randomized trials (n = 255) and one case–control study (n = 270). Data were collected between 1986 and 2014, and reported mean salt consumption levels were between 5.22 and 42.30 g/day. With an extreme outlier excluded, overall mean weighted salt intake was 10.98 g/day (95% confidence interval 8.57–13.40). There was significant heterogeneity between the estimates for contributing studies (I2 = 99.97%) (P homogeneity ⩽0.001), which was likely attributable to the different measurement methods used and the different populations studied. There was no evidence of a change in intake over time (P trend = 0.08). Conclusion: The available data leave some uncertainty about exact mean salt consumption in India but there is little doubt that population salt consumption far exceeds the WHO-recommended maximum of 5 g per person per day.

Protocol for developing the evidence base for a national salt reduction programme for India

Introduction The scientific evidence base in support of salt reduction is strong but the data required to translate these insights into reduced population salt intake are mostly absent. The aim of this research project is to develop the evidence base required to formulate and implement a national salt reduction programme for India. Methods and analysis The research will comprise three components: a stakeholder analysis involving government, industry, consumers and civil society organisations; a population survey using an age-stratified and sex-stratified random samples drawn from urban (slum and non-slum) and rural areas of North and South India; and a systematic quantitative evaluation of the nutritional components of processed and restaurant foods. The stakeholder interviews will be analysed using qualitative methods to summarise the main themes and define the broad range of factors influencing the food environment in India. The population survey will estimate the mean daily salt consumption through the collection of 24 h urine samples with concurrent dietary surveys identifying the main sources of dietary sodium/salt. The survey of foods will record the nutritional composition of the chief elements of food supply. The findings from this research will be synthesised and proposals for a national salt reduction strategy for India will be developed in collaboration with key stakeholders. Ethics and dissemination This study has been approved by the Human Research Ethics Committees of the University of Sydney and the Centre for Chronic Disease Control in New Delhi, and also by the Indian Health Ministrys Screening Committee. The project began fieldwork in February 2014 and will report the main results in 2016. The findings will be targeted primarily at public health policymakers and advocates, but will be disseminated widely through other mechanisms including conference presentations and peer-reviewed publications, as well as to the participating communities.

Determinants of Inhalant (Whitener) Use Among Street Children in a South Indian City

A cross-sectional study was conducted in the year 2008 among 174 children in observation homes in Hyderabad, India, to estimate the distribution of inhalant (whitener) use among this population. Data were collected using an instrument developed for this purpose. About 61% of the children were boys and their mean age was 12.2 years (range 5–18 years). Whitener use was found in 35% of the children along with concurrent use of other substances. Peer pressure was the commonest cause reported for initiating substance use. The high prevalence is an important concern for the Indian policymakers given the large number of street children in Indian cities.