Compliance to HIV treatment monitoring guidelines can reduce laboratory costs

Background: Panel tests are a predetermined group of tests commonly requested together to provide a comprehensive and conclusive diagnosis, for example, liver function test (LFT). South African HIV antiretroviral treatment (ART) guidelines recommend individual tests for toxicity monitoring over panel tests. In 2008, the National Health Laboratory Services (NHLS) request form was redesigned to list individual tests instead of panel tests and removed the ‘other tests’ box option to facilitate efficient ART laboratory monitoring.Objectives: This study aimed to demonstrate changes in laboratory expenditure, for individual and panel tests, for ART toxicity monitoring.Method: NHLS Corporate Data Warehouse (CDW) data were extracted for HIV conditional grant accounts to assess ART toxicity monitoring laboratory expenditure between 2010/2011 and 2014/2015. Data were classified based on the tests requested, as either panel (LFT or urea and electrolytes) or individual (alanine transaminase or creatinine) tests.Results: Expenditure on panel tests reduced from R340 million in 2010/2011 to R140m by 2014/2015 (reduction of R204m) and individual test expenditure increased from R34m to R76m (twofold increase). A significant reduction in LFT panel expenditure was noted, reducing from R322m in 2010/2011 to R130m in 2014/2015 (60% reduction).Conclusion: Changes in toxicity monitoring guidelines and the re-engineering of the NHLS request form successfully reduced expenditure on panel tests relative to individual tests. The introduction of order entry systems could further reduce unnecessary laboratory expenditure

Analysis of HIV disease burden by calculating the percentages of patients with CD4 counts

Background. South Africa (SA)’s Comprehensive HIV and AIDS Care, Management and Treatment (CCMT) programme has reduced new HIV infections and HIV-related deaths. In spite of progress made, 11.2% of South Africans (4.02 million) were living with HIV in 2015.Objective. The National Health Laboratory Service (NHLS) in SA performs CD4 testing in support of the CCMT programme and collates data through the NHLS Corporate Data Warehouse. The objective of this study was to assess the distribution of CD4 counts <100 cells/µL (defining severely immunosuppressed HIV-positive patients) and >500 cells/µL (as an HIV-positive ‘wellness’ indicator).Methods. CD4 data were extracted for the financial years 2010/11 and 2014/15, according to the district where the test was ordered, for predefined CD4 ranges. National and provincial averages of CD4 counts <100 and >500 cells/µL were calculated. Data were analysed using Stata 12 and mapping was done with ArcGIS software, reporting percentages of CD4 counts <100 and >500 cells/µL by district.Results. The national average percentage of patients with CD4 counts <100 cells/µL showed a marked decrease (by 22%) over the 5-year study period, with a concurrent increase in CD4 counts >500 cells/µL (by 57%). District-by-district analysis showed that in 2010/11, 44/52 districts had >10% of CD4 samples with counts <100 cells/µL, decreasing to only 17/52 districts by 2014/15. Overall, districts in the Western Cape and KwaZulu-Natal had the lowest percentages of CD4 counts <100 cells/µL, as well as the highest percentages of counts >500 cells/µL. In contrast, in 2014/15, the highest percentages of CD4 counts <100 cells/µL were noted in the West Rand (Gauteng), Vhembe (Limpopo) and Nelson Mandela Bay (Eastern Cape) districts, where the lowest percentages of counts >500 cells/µL were also noted.Conclusions. The percentages of CD4 counts <100 cells/µL highlighted here reveal districts with positive change suggestive of programmatic improvements, and also highlight districts requiring local interventions to achieve the UNAIDS/SA National Department of Health 90-90-90 HIV treatment goals. The study further underscores the value of using NHLS laboratory data, an underutilised national resource, to leverage laboratory test data to enable a more comprehensive understanding of programme-specific health indicators.

Using laboratory data to categorise CD4 laboratory turn-around-time performance across a national programme

Background and objective: The National Health Laboratory Service provides CD4 testing through an integrated tiered service delivery model with a target laboratory turn-around time (TAT) of 48 h. Mean TAT provides insight into national CD4 laboratory performance. However, it is not sensitive enough to identify inefficiencies of outlying laboratories or predict the percentage of samples meeting the TAT target. The aim of this study was to describe the use of the median, 75th percentile and percentage within target of laboratory TAT data to categorise laboratory performance.   Methods: Retrospective CD4 laboratory data for 2015–2016 fiscal year were extracted from the corporate data warehouse. The laboratory TAT distribution and percentage of samples within the 48 h target were assessed. A scatter plot was used to categorise laboratory performance into four quadrants using both the percentage within target and 75th percentile TAT. The laboratory performance was labelled good, satisfactory or poor.   Results: TAT data reported a positive skew with a mode of 13 h and a median of 17 h and 75th percentile of 25 h. Overall, 93.2% of CD4 samples had a laboratory TAT of less than 48 h. 48 out of 52 laboratories reported good TAT performance, i.e. percentage within target > 85% and 75th percentile ≤ 48 h, with two categorised as satisfactory (one parameter met), and two as poor performing laboratories (failed both parameters).   Conclusion: This study demonstrated the feasibility of utilising laboratory data to categorise laboratory performance. Using the quadrant approach for TAT data, laboratories that need interventions can be highlighted for root cause analysis assessment

Performance evaluation of the Pima™ point-of-care CD4 analyser using capillary blood sampling in field tests in South Africa

<p>Abstract</p> <p>Background</p> <p>Point-of-care CD4 testing can provide immediate CD4 reporting at HIV-testing sites. This study evaluated performance of capillary blood sampling using the point-of-care Pima™ CD4 device in representative primary health care clinics doing HIV testing.</p> <p>Methods</p> <p>Prior to testing, prescribed capillary-sampling and instrument training was undertaken by suppliers across all sites. Matching venous EDTA samples were drawn throughout for comparison to laboratory predicate methodology (PLG/CD4). In Phase I, Pima™ cartridges were pipette-filled with EDTA venous blood in the laboratory (N = 100). In Phase II (N = 77), Pima™ CD4 with capillary sampling was performed by a single operator in a hospital-based antenatal clinic. During subsequent field testing, Pima™ CD4 with capillary sampling was performed in primary health care clinics on HIV-positive patients by multiple attending nursing personnel in a rural clinic (Phase-IIIA, N = 96) and an inner-city clinic (Phase-IIIB, N = 139).</p> <p>Results</p> <p>Pima™ CD4 compared favourably to predicate/CD4 when cartridges were pipette-filled with venous blood (bias -17.3 ± STDev = 36.7 cells/mm³; precision-to-predicate %CV < 6%). Decreased precision of Pima™ CD4 to predicate/CD4 (varying from 17.6 to 28.8%SIM CV; mean bias = 37.9 ± STDev = 179.5 cells/mm³) was noted during field testing in the hospital antenatal clinic. In the rural clinic field-studies, unacceptable precision-to-predicate and positive bias was noted (mean 28.4%SIM CV; mean bias = +105.7 ± STDev = 225.4 cells/mm³). With additional proactive manufacturer support, reliable performance was noted in the subsequent inner-city clinic field study where acceptable precision-to-predicate (11%SIM CV) and less bias of Pima™ to predicate was shown (BA bias ~11 ± STDev = 69 cells/mm³).</p> <p>Conclusions</p> <p>Variable precision of Pima™ to predicate CD4 across study sites was attributable to variable capillary sampling. Poor precision was noted in the outlying primary health care clinic where the system is most likely to be used. Stringent attention to capillary blood collection technique is therefore imperative if technologies like Pima™ are used with capillary sampling at the POC. Pima™ CD4 analysis with venous blood was shown to be reproducible, but testing at the point of care exposes operators to biohazard risk related to uncapping vacutainer samples and pipetting of blood, and is best placed in smaller laboratories using established principles of Good Clinical Laboratory Practice. The development of capillary sampling quality control methods that assure reliable CD4 counts at the point of care are awaited.</p

Analysis of HIV disease burden by calculating the percentages of patients with CD4 counts <100 cells/µL across 52 districts reveals hot spots for intensified commitment to programmatic support

Background. South Africa (SA)’s Comprehensive HIV and AIDS Care, Management and Treatment (CCMT) programme has reduced new HIV infections and HIV-related deaths. In spite of progress made, 11.2% of South Africans (4.02 million) were living with HIV in 2015. Objective. The National Health Laboratory Service (NHLS) in SA performs CD4 testing in support of the CCMT programme and collates data through the NHLS Corporate Data Warehouse. The objective of this study was to assess the distribution of CD4 counts 500 cells/µL (as an HIV-positive ‘wellness’ indicator). Methods. CD4 data were extracted for the financial years 2010/11 and 2014/15, according to the district where the test was ordered, for predefined CD4 ranges. National and provincial averages of CD4 counts 500 cells/µL were calculated. Data were analysed using Stata 12 and mapping was done with ArcGIS software, reporting percentages of CD4 counts 500 cells/µL by district. Results. The national average percentage of patients with CD4 counts 500 cells/µL (by 57%). District-by-district analysis showed that in 2010/11, 44/52 districts had >10% of CD4 samples with counts 500 cells/µL. In contrast, in 2014/15, the highest percentages of CD4 counts 500 cells/µL were also noted. Conclusions. The percentages of CD4 counts <100 cells/µL highlighted here reveal districts with positive change suggestive of programmatic improvements, and also highlight districts requiring local interventions to achieve the UNAIDS/SA National Department of Health 90-90-90 HIV treatment goals. The study further underscores the value of using NHLS laboratory data, an underutilised national resource, to leverage laboratory test data to enable a more comprehensive understanding of programme-specific health indicators

Observed full blood count and lymphocyte subset values in a cohort of clinically healthy South African children from a semi-informal settlement in Cape Town

Background. The paediatric full blood count and lymphocyte subset reference intervals used by the National Health Laboratory Service (NHLS), South Africa (SA), are taken from two international reference interval publications. Differences in reference intervals suggest that international data sets may not be appropriate for use in SA.Objective. To study immunohaematological values of a group of clinically healthy children from an informal settlement in Cape Town, SA, to assess whether international paediatric reference intervals used by the NHLS are appropriate. Methods. A cross-sectional study of 207 female and 174 male HIV-uninfected children living in an informal settlement in Cape Town was performed. Full blood counts, automated differential counts and lymphocyte subset analysis were done using internationally accepted technologies. Data were categorised by age and reference intervals compiled using medians and 95% confidence intervals (CIs). Gender comparisons were calculated by non-parametric tests. Results. Although median and 95% CI values differed slightly, physiological trends for red cell, platelet, white blood cell differential and lymphocyte subsets were similar to international reference intervals currently in use at the NHLS. Benign ethnic neutropenia was not a significant finding, and gender-specific intervals were not necessary until 12 years of age. Lower overall median values for haemoglobin and haematocrit, and higher median values for mean cell volume and red cell distribution width, were noted. Assessment of haemoglobin, red cell distribution width and calculated Mentzer ratios suggested underlying iron deficiency in 14.2% of participants. Conclusion. Paediatric immunohaematological reference intervals observed in this study are similar to, and support continued use of, international paediatric reference intervals. Underlying iron and related nutritional deficiencies may be contributing to lower haemoglobin levels noted in local children. A larger nationwide study, including all ethnic groups, is recommended.

Siting of HIV/AIDS diagnostic equipment in South Africa: a case study in locational analysis

This paper describes a practical application of locational analysis to the siting of HIV/AIDS diagnostic equipment in laboratories across South Africa. Classical location analytical techniques were extended to ensure that laboratories are sited as close as possible to major centres of demand from hospitals and clinics. A particular advantage of the modified set covering algorithm developed is that choices between laboratory sites are made in a transparent manner. In order to find appropriate numbers and ideal placement of CD4 laboratories, runs were undertaken for various scenarios based on maximum travel time from health facilities to laboratory sites. Results demonstrated to decision makers showed close comparisons with pilot review projects undertaken in four health districts of South Africa. The research has potential to impact health care delivery to HIV sufferers in the poorest rural regions of the country

Programmatic implications of implementing the relational algebraic capacitated location (RACL) algorithm outcomes on the allocation of laboratory sites, test volumes, platform distribution and space requirements

Introduction: CD4 testing in South Africa is based on an integrated tiered service delivery model that matches testing demand with capacity. The National Health Laboratory Service has predominantly implemented laboratory-based CD4 testing. Coverage gaps, over-/under-capacitation and optimal placement of point-of-care (POC) testing sites need investigation. Objectives: We assessed the impact of relational algebraic capacitated location (RACL) algorithm outcomes on the allocation of laboratory and POC testing sites. Methods: The RACL algorithm was developed to allocate laboratories and POC sites to ensure coverage using a set coverage approach for a defined travel time (T). The algorithm was repeated for three scenarios (A: T = 4; B: T = 3; C: T = 2 hours). Drive times for a representative sample of health facility clusters were used to approximate T. Outcomes included allocation of testing sites, Euclidian distances and test volumes. Additional analysis included platform distribution and space requirement assessment. Scenarios were reported as fusion table maps. Results: Scenario A would offer a fully-centralised approach with 15 CD4 laboratories without any POC testing. A significant increase in volumes would result in a four-fold increase at busier laboratories. CD4 laboratories would increase to 41 in scenario B and 61 in scenario C. POC testing would be offered at two sites in scenario B and 20 sites in scenario C. Conclusion: The RACL algorithm provides an objective methodology to address coverage gaps through the allocation of CD4 laboratories and POC sites for a given T. The algorithm outcomes need to be assessed in the context of local conditions

District and sub-district analysis of cryptococcal antigenaemia prevalence and specimen positivity in KwaZulu-Natal, South Africa

Background: Cryptococcal meningitis (CM) is a leading cause of mortality among HIV-positive South Africans. Reflex cryptococcal antigen (CrAg) testing of remnant plasma was offered as a pilot prior to implementation in October 2016 in KwaZulu-Natal province. The national reflex CrAg positivity was 5.4% compared to 7.3% for KwaZulu-Natal. Objectives: The aim of this study was to interrogate CrAg positivity by health levels to identify hotspots. Method: Data for the period October 2016 to June 2017 were analysed. Health district CrAg positivity and prevalence were calculated, with the latter using de-duplicated patient data. The district CrAg positivity and the number of CrAg-positive specimens per health facility were mapped using ArcGIS. For districts with the highest CrAg positivity, a sub-district CrAg positivity analysis was conducted. Results: The provincial CrAg positivity was 7.6%. District CrAg positivity ranged from 5.7% (Ugu) to 9.6% (Umkhanyakude) with prevalence ranging from 5.5% (Ugu) to 9.7% (Umkhanyakude). The highest CrAg positivity was reported for the Umkhanyakude (9.6%) and King Cetswayo (9.5%) districts. In these two districts, CrAg positivity of 10% was noted in the Umhlabuyalingana (10.0%), Jozini (10.2%), uMhlathuze (10.5%) and Nkandla (10.8%) subdistricts. In these subdistricts, 135 CrAg-positive samples were reported for the Ngwelezane hospital followed by 41 and 43 at the Hlabisa and Manguzi hospitals respectively. Conclusion: Cryptococcal antigen positivity was not uniformly distributed at either the district or sub-district levels, with identified facility hotspots in the Umkhanyakude and King Cetswayo districts. This study demonstrates the value of laboratory data to identify hotspots for planning programmatic interventions