Private individual ambulatory health care providers in Madhya Pradesh province, India

Background: Ambulatory health care services are a major contributor to the large and inequitable health financing burdens (largely out-of-pocket) faced by households in India. The private sector has a virtual monopoly over ambulatory curative services in rural and urban India. Despite this, there is little knowledge about who these providers are, their numbers, distribution, and activities. Aim: This study describes the numbers, gender, distribution, and characteristics of private individual ambulatory care providers in Madhya Pradesh (60.4 million people), one of India’s largest provinces. It discusses the suitability of this provider mix to deal with maternal and child health, a major health priority in the province. Method: A survey enlisting all health care providers was conducted in the 52,117 villages and 394 towns of the province. Results: There were 14,046 private qualified physicians (12.5% women), 57,684 qualified paramedics (3.4% women), and 89,090 unqualified providers (10% women) providing ambulatory services in individual setups. In addition, 55,393 traditional birth attendants provided home-based intranatal care. The macro organization of these providers in this setting is presented. Given the high levels of maternal and child mortality in the province, excessive reliance is placed on less than competent providers as these present lower access barriers. Conclusion: Given the public health priorities in this province (maternal and child health), the provider mix is not optimally suited to the populations’ needs. There is a lack of competent qualified care required to deal with the major causes of morbidity and mortality, particularly in rural areas. Access to qualified women providers is low. The lack of a cadre of qualified midwives possibly contributes to some of the high maternal mortality observed in this province

Psychosomatic complaints and sense of coherence among adolescents in a county in Sweden: a cross-sectional school survey

<p>Abstract</p> <p>Background</p> <p>Over the last five to ten years there has been an increase in psychosomatic complaints (PSC) in Swedish children. The objective of the study was to examine the relation between PSC and sense of coherence (SOC).</p> <p>Methods</p> <p>A cross-sectional school survey in the county of Västmanland, Sweden. All 16- and 19-year old adolescents present at school on the day of the survey were asked to complete a questionnaire in their classrooms during a one-lesson hour session under the supervision of their teachers. Totally 3,998 students in both private and public schools, studying in ninth grade elementary school or third grade secondary school participated.</p> <p>Results</p> <p>The results from our study show that there is a statistically significant relation between PSC and SOC among adolescents. It also shows that adolescents with a weak SOC score have more symptoms of PSC.</p> <p>Conclusion</p> <p>Our study indicates that SOC can help the adolescents to choose a coping strategy that is appropriate for the situation and thereby may prevent them from developing PSC. However, additional studies are needed to confirm our findings.</p

Measuring costs of data collection at village clinics by village doctors for a syndromic surveillance system-a cross sectional survey from China

Background: Studies into the costs of syndromic surveillance systems are rare, especially for estimating the direct costs involved in implementing and maintaining these systems. An Integrated Surveillance System in rural China (ISSC project), with the aim of providing an early warning system for outbreaks, was implemented; village clinics were the main surveillance units. Village doctors expressed their willingness to join in the surveillance if a proper subsidy was provided. This study aims to measure the costs of data collection by village clinics to provide a reference regarding the subsidy level required for village clinics to participate in data collection. Methods: We conducted a cross-sectional survey with a village clinic questionnaire and a staff questionnaire using a purposive sampling strategy. We tracked reported events using the ISSC internal database. Cost data included staff time, and the annual depreciation and opportunity costs of computers. We measured the village doctors’ time costs for data collection by multiplying the number of full time employment equivalents devoted to the surveillance by the village doctors’ annual salaries and benefits, which equaled their net incomes. We estimated the depreciation and opportunity costs of computers by calculating the equivalent annual computer cost and then allocating this to the surveillance based on the percentage usage. Results: The estimated total annual cost of collecting data was 1,423 Chinese Renminbi (RMB) in 2012 (P25 = 857, P75 = 3284), including 1,250 RMB (P25 = 656, P75 = 3000) staff time costs and 134 RMB (P25 = 101, P75 = 335) depreciation and opportunity costs of computers. Conclusions: The total costs of collecting data from the village clinics for the syndromic surveillance system was calculated to be low compared with the individual net income in County A

Detection of breast cancer lymph node metastases in frozen sections with a point-of care low-cost microscope scanner

Background Detection of lymph node metastases is essential in breast cancer diagnostics and staging, affecting treatment and prognosis. lntraoperative microscopy analysis of sentinel lymph node frozen sections is standard for detection of axillary metastases but requires access to a pathologist for sample analysis. Remote analysis of digitized samples is an alternative solution but is limited by the requirement for high-end slide scanning equipment. Objective To determine whether the image quality achievable with a low-cost, miniature digital microscope scanner is sufficient for detection of metastases in breast cancer lymph node frozen sections. Methods Lymph node frozen sections from 79 breast cancer patients were digitized using a prototype miniature microscope scanner and a high-end slide scanner. Images were independently reviewed by two pathologists and results compared between devices with conventional light microscopy analysis as ground truth. Results Detection of metastases in the images acquired with the miniature scanner yielded an overall sensitivity of 91% and specificity of 99% and showed strong agreement when compared to light microscopy (k = 0.91). Strong agreement was also observed when results were compared to results from the high-end slide scanner (k = 0.94). A majority of discrepant cases were micrometastases and sections of which no anticytokeratin staining was available. Conclusion Accuracy of detection of metastatic cells in breast cancer sentinel lymph node frozen sections by visual analysis of samples digitized using low-cost, point-of-care microscopy is comparable to analysis of digital samples scanned using a high-end, whole slide scanner. This technique could potentially provide a workflow for digital diagnostics in resource-limited settings, facilitate sample analysis at the point-of-care and reduce the need for trained experts on-site during surgical procedures.Peer reviewe

Design of a randomized trial to evaluate the influence of mobile phone reminders on adherence to first line antiretroviral treatment in South India - the HIVIND study protocol

Poor adherence to antiretroviral treatment has been a public health challenge associated with the treatment of HIV. Although different adherence-supporting interventions have been reported, their long term feasibility in low income settings remains uncertain. Thus, there is a need to explore sustainable contextual adherence aids in such settings, and to test these using rigorous scientific designs. The current ubiquity of mobile phones in many resource-constrained settings, make it a contextually appropriate and relatively low cost means of supporting adherence. In India, mobile phones have wide usage and acceptability and are potentially feasible tools for enhancing adherence to medications. This paper presents the study protocol for a trial, to evaluate the influence of mobile phone reminders on adherence to first-line antiretroviral treatment in South India. Methods/Design: 600 treatment naive patients eligible for first-line treatment as per the national antiretroviral treatment guidelines will be recruited into the trial at two clinics in South India. Patients will be randomized into control and intervention arms. The control arm will receive the standard of care; the intervention arm will receive the standard of care plus mobile phone reminders. Each reminder will take the form of an automated call and a picture message. Reminders will be delivered once a week, at a time chosen by the patient. Patients will be followed up for 24 months or till the primary outcome i.e. virological failure, is reached, whichever is earlier. Self-reported adherence is a secondary outcome. Analysis is by intention-to-treat. A cost-effectiveness study of the intervention will also be carried out. Stepping up telecommunications technology in resource-limited healthcare settings is a priority of the World Health Organization. The trial will evaluate if the use of mobile phone reminders can influence adherence to first-line antiretrovirals in an Indian context.EU/HIVIN

Point-of-care mobile digital microscopy and deep learning for the detection of soil-transmitted helminths and Schistosoma haematobium

Background: Microscopy remains the gold standard in the diagnosis of neglected tropical diseases. As resource limited, rural areas often lack laboratory equipment and trained personnel, new diagnostic techniques are needed. Low-cost, point-of-care imaging devices show potential in the diagnosis of these diseases. Novel, digital image analysis algorithms can be utilized to automate sample analysis. Objective: Evaluation of the imaging performance of a miniature digital microscopy scanner for the diagnosis of soil-transmitted helminths and Schistosoma haematobium, and training of a deep learning-based image analysis algorithm for automated detection of soil-transmitted helminths in the captured images. Methods: A total of 13 iodine-stained stool samples containing Ascaris lumbricoides, Trichuris trichiura and hookworm eggs and 4 urine samples containing Schistosoma haematobium were digitized using a reference whole slide-scanner and the mobile microscopy scanner. Parasites in the images were identified by visual examination and by analysis with a deep learning-based image analysis algorithm in the stool samples. Results were compared between the digital and visual analysis of the images showing helminth eggs. Results: Parasite identification by visual analysis of digital slides captured with the mobile microscope was feasible for all analyzed parasites. Although the spatial resolution of the reference slide-scanner is higher, the resolution of the mobile microscope is sufficient for reliable identification and classification of all parasites studied. Digital image analysis of stool sample images captured with the mobile microscope showed high sensitivity for detection of all helminths studied (range of sensitivity = 83.3-100%) in the test set (n = 217) of manually labeled helminth eggs. Conclusions: In this proof-of-concept study, the imaging performance of a mobile, digital microscope was sufficient for visual detection of soil-transmitted helminths and Schistosoma haematobium. Furthermore, we show that deep learning-based image analysis can be utilized for the automated detection and classification of helminths in the captured images.Peer reviewe

Quantification of Estrogen Receptor-Alpha Expression in Human Breast Carcinomas With a Miniaturized, Low-Cost Digital Microscope : A Comparison with a High-End Whole Slide- Scanner

Introduction: A significant barrier to medical diagnostics in low-resource environments is the lack of medical care and equipment. Here we present a low-cost, cloud-connected digital microscope for applications at the point-of-care. We evaluate the performance of the device in the digital assessment of estrogen receptor-alpha (ER) expression in breast cancer samples. Studies suggest computer-assisted analysis of tumor samples digitized with whole slide-scanners may be comparable to manual scoring, here we study whether similar results can be obtained with the device presented. Materials and methods: A total of 170 samples of human breast carcinoma, immunostained for ER expression, were digitized with a high-end slide-scanner and the point-of-care microscope. Corresponding regions from the samples were extracted, and ER status was determined visually and digitally. Samples were classified as ER negative (<1% ER positivity) or positive, and further into weakly (1-10% positivity) and strongly positive. Interobserver agreement (Cohen's kappa) was measured and correlation coefficients (Pearson's product-momentum) were calculated for comparison of the methods. Results: Correlation and interobserver agreement (r = 0.98, p < 0.001, kappa = 0.84, CI95% = 0.75-0.94) were strong in the results from both devices. Concordance of the point-of-care microscope and the manual scoring was good (r = 0.94, p < 0.001, kappa = 0.71, CI95% = 0.61-0.80), and comparable to the concordance between the slide scanner and manual scoring (r = 0.93, p < 0.001, kappa = 0.69, CI95% = 0.60-0.78). Fourteen (8%) discrepant cases between manual and device-based scoring were present with the slide scanner, and 16 (9%) with the point-of-care microscope, all representing samples of low ER expression. Conclusions: Tumor ER status can be accurately quantified with a low-cost imaging device and digital image-analysis, with results comparable to conventional computer-assisted or manual scoring. This technology could potentially be expanded for other histopathological applications at the point-of-care

A novel deep learning-based point-of-care diagnostic method for detecting Plasmodium falciparum with fluorescence digital microscopy

Background Malaria remains a major global health problem with a need for improved field-usable diagnostic tests. We have developed a portable, low-cost digital microscope scanner, capable of both brightfield and fluorescence imaging. Here, we used the instrument to digitize blood smears, and applied deep learning (DL) algorithms to detect Plasmodium falciparum parasites. Methods Thin blood smears (n = 125) were collected from patients with microscopy-confirmed P. falciparum infections in rural Tanzania, prior to and after initiation of artemisinin-based combination therapy. The samples were stained using the 4′,6-diamidino-2-phenylindole fluorogen and digitized using the prototype microscope scanner. Two DL algorithms were trained to detect malaria parasites in the samples, and results compared to the visual assessment of both the digitized samples, and the Giemsa-stained thick smears. Results Detection of P. falciparum parasites in the digitized thin blood smears was possible both by visual assessment and by DL-based analysis with a strong correlation in results (r = 0.99, p <0.01). A moderately strong correlation was observed between the DL-based thin smear analysis and the visual thick smear-analysis (r = 0.74, p <0.01). Low levels of parasites were detected by DL-based analysis on day three following treatment initiation, but a small number of fluorescent signals were detected also in microscopy-negative samples. Conclusion Quantification of P. falciparum parasites in DAPI-stained thin smears is feasible using DL-supported, point-of-care digital microscopy, with a high correlation to visual assessment of samples. Fluorescent signals from artefacts in samples with low infection levels represented the main challenge for the digital analysis, thus highlighting the importance of minimizing sample contaminations. The proposed method could support malaria diagnostics and monitoring of treatment response through automated quantification of parasitaemia and is likely to be applicable also for diagnostics of other Plasmodium species and other infectious diseases.Peer reviewe

A Malaria Diagnostic Tool Based on Computer Vision Screening and Visualization of Plasmodium falciparum Candidate Areas in Digitized Blood Smears

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On-Chip Imaging of Schistosoma haematobium Eggs in Urine for Diagnosis by Computer Vision

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