Diagnostic Accuracy of Primary Care Clinicians Across a Statewide System of Autism Evaluation.

OBJECTIVES: To evaluate the diagnostic accuracy of the Early Autism Evaluation (EAE) Hub system, a statewide network that provides specialized training and collaborative support to community primary care providers in the diagnosis of young children at risk for autism spectrum disorder (ASD). METHODS: EAE Hub clinicians referred children, aged 14 to 48 months, to this prospective diagnostic study for blinded follow-up expert evaluation including assessment of developmental level, adaptive behavior, and ASD symptom severity. The primary outcome was agreement on categorical ASD diagnosis between EAE Hub clinician (index diagnosis) and ASD expert (reference standard). RESULTS: Among 126 children (mean age: 2.6 years; 77% male; 14% Latinx; 66% non-Latinx white), 82% (n = 103) had consistent ASD outcomes between the index and reference evaluation. Sensitivity was 81.5%, specificity was 82.4%, positive predictive value was 92.6%, and negative predictive value was 62.2%. There was no difference in accuracy by EAE Hub clinician or site. Across measures of development, there were significant differences between true positive and false negative (FN) cases (all Ps < .001; Cohen's d = 1.1-1.4), with true positive cases evidencing greater impairment. CONCLUSIONS: Community-based primary care clinicians who receive specialty training can make accurate ASD diagnoses in most cases. Diagnostic disagreements were predominately FN cases in which EAE Hub clinicians had difficulty differentiating ASD and global developmental delay. FN cases were associated with a differential diagnostic and phenotypic profile. This research has significant implications for the development of future population health solutions that address ASD diagnostic delays.

Primary healthcare services in the rural Eastern Cape, South Africa: Evaluating a service-support project.

BACKGROUND: In 2012, 38% of the South African population resided in the rural areas of the country. The professional healthcare services are concentrated in the urban areas, resulting in an imbalance between urban and rural healthcare services. AIM: The aim of this study was to evaluate the use of a non-governmental organisation (NGO)-supported mobile healthcare service in a remote area. SETTING: Eastern Cape Province in South Africa. METHODS: The walking distance between the community and the nearest fixed government healthcare service was evaluated and compared with the recommendations of World Health Organization (WHO). Services provided to people visiting the mobile community service were recorded, and descriptive data were analysed and compared with the anonymised patient records of the nearest fixed service clinic. RESULTS: Of the 30 outreach points served by the NGO, 24 points were at a distance more than the WHO-designated walking distance and 11 points were more than twice the WHO-designated distance from the perspective of fixed clinic. The average headcount per annum of the outreach NGO mobile clinics exceeded those of the fixed Department of Health (DoH) clinics by an average of 250 patients per clinic session. The increase in services was also noteworthy, with a mean differential of 1774 services per annum for the same day above that of the DoH clinics. CONCLUSION: Mobile services could make a difference to the utilisation of essential healthcare facilities. The provision of augmented NGO-led mobile clinical outreach services and joint government-NGO partnerships holds possibilities for improving healthcare for those living in remote rural areas.

Primary healthcare services in the rural Eastern Cape, South Africa: evaluating a service-support project

Background: In 2012, 38% of the South African population resided in the rural areas of the country. The professional healthcare services are concentrated in the urban areas, resulting in an imbalance between urban and rural healthcare services. Aim: The aim of this study was to evaluate the use of a non-governmental organisation (NGO)-supported mobile healthcare service in a remote area. Setting: Eastern Cape Province in South Africa. Methods: The walking distance between the community and the nearest fixed government healthcare service was evaluated and compared with the recommendations of World Health Organization (WHO). Services provided to people visiting the mobile community service were recorded, and descriptive data were analysed and compared with the anonymised patient records of the nearest fixed service clinic. Results: Of the 30 outreach points served by the NGO, 24 points were at a distance more than the WHO-designated walking distance and 11 points were more than twice the WHO-designated distance from the perspective of fixed clinic. The average headcount per annum of the outreach NGO mobile clinics exceeded those of the fixed Department of Health (DoH) clinics by an average of 250 patients per clinic session. The increase in services was also noteworthy, with a mean differential of 1774 services per annum for the same day above that of the DoH clinics. Conclusion: Mobile services could make a difference to the utilisation of essential healthcare facilities. The provision of augmented NGO-led mobile clinical outreach services and joint government­NGO partnerships holds possibilities for improving healthcare for those living in remote rural areas

Detection, referral and control of diabetes and hypertension in the rural Eastern Cape Province of South Africa by community health outreach workers in the rural primary healthcare project: Health in Every Hut.

BACKGROUND:  Non-communicable diseases, mainly cardiovascular diseases, diabetes, cancer and chronic respiratory diseases, are responsible for approximately 63% of all deaths occurring worldwide in any given year. The majority of these deaths have occurred in low- and middle-income countries (LMICs). The latest World Health Organization (WHO) report shows that the increase in diabetes is also most pronounced in the LMICs. The South African Labour and Development Research Unit estimated a 9% prevalence within the adult population in 2016. In the Eastern Cape Province, hypertensive heart disease has become the second most common cause of death, followed by diabetes, the third most common cause of death.Aim and setting: The aim of this study was to report on the follow-up of patients in the community with known hypertension or diabetes or who were deemed at-risk (as identified during a prior community-wide survey). METHODS:  Data were collected via a household primary health screening, monitoring and follow-up process, which included taking anthropometric measurements, blood pressure (BP) and blood glucose and referring to clinics for further testing and treatment where necessary. RESULTS:  Of the 1885 participants followed up by the community health outreach workers, 1702 were known to be hypertensive and 183 were deemed at-risk [of these, only 24 (13.2%) had normal or high normal systolic BP readings]. There were 341 participants with diabetes and 34 at-risk of diabetes [of these, 28 (82%) had levels of 11 mmol/l or higher at follow-up]. There was a significant improvement in BP and glucose control over repeated visits. CONCLUSION:  In this rural area of the Eastern Cape, South Africa, the follow-up of patients with hypertension or diabetes as well as those individuals at-risk adds value to hypertension and glucose control.

The noncommunicable disease outcomes of primary healthcare screening in two rural subdistricts of the Eastern Cape Province, South Africa.

BACKGROUND: Middle and lower income countries are challenged with a double burden of disease: while still coping with the onslaught of Human Immunodeficiency Virus (HIV) and increasing levels of tuberculosis (TB), there is a considerable increase in the level of noncommunicable diseases (NCDs). The poor are especially disadvantaged and are at an increased risk for NCDs. Adequate healthcare resources for this environment can only be allocated once the extent and exact nature of the problem is determined.Aim and setting: The aim of this study was to collect demographic and NCD-related data in the poorest community of the poorest province of South Africa in order to determine the extent of the problem and advise on allocation of resources accordingly. METHODS: Data were collected via a household primary health screening process, which included taking anthropometric measurements, blood pressure and blood glucose and referring to clinics for further testing and treatment where necessary. RESULTS: It was found that the population screened was generally older, consisted of women, and had a high incidence of obesity and hypertension. Of note was the fact that in those without known hypertension, close to 40% of individuals had possible newly diagnosed hypertension. This increased with increase in age and body mass index (BMI). The total prevalence of diabetes was close to 5%, but possible new diabetes was considerably lower at approximately 1%. CONCLUSION: In this rural area of the Eastern Cape, South Africa, undiagnosed hypertension is a major concern and renewed efforts at detection and control are warranted.