Geographical location of health and laboratory facilities in South Africa.

<p>Map to reveal geographic location of ∼4756 health facilities (as at 2011/2012); including primary care, community centers and hospital-based clinics (black dots) and 260 NHLS routine pathology service laboratories, across nine provinces and the related 52 districts. Insert reveals the proportions of different category of health facilities requesting CD4 testing (also see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0114727#pone-0114727-t001" target="_blank">Table 1</a>).</p

Six-tiered CD4 service framework and ideal proposed service coverage.

<p><b>4a</b> Graphical representation of an integrated, hierarchical ‘parent’, six-tiered CD4 service approach to secure scalable, ‘full-coverage’ across a national programme. From top to base, each band represents an increasing service load from an increasing base of referring health clinics. The proposed hierarchical ‘parent’ spatial support relationship between, and within, service tiers illustrates how higher service tiers can support and interact with lower service tiers, not only in a direct hierarchical fashion, but also how geographical location of different tiers in any given region can enable ‘parent/support’ relationships. <b>4b</b> Reveals existing and ideal proposed service coverage precincts of 5 tiers of service in South Africa, based on an averaged 50–100 km radius ‘coverage-precincts’. In both 4a and 4b, ‘A’ and ‘B’ reveal examples of the envisaged integrated support relationships between lower and upper tiers, specifically how a Tier-3 or Tier-4 level laboratory can supplement and support local Tier-1 and Tier-2 services respectively. Likewise, in addition to the proposed support infrastructure, ‘C’ also reveals how higher tiers can function together within a defined service precinct, to accommodate high service demands and provide infrastructure support in terms of service back-up and disaster recovery.</p

Relationship between CD4 tiers and NDOH Health Care Facilities.

<p>Table showing the integration of the category of Health Care Facility (NDOH ‘Classification of Health Care Facility’ <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0114727#pone.0114727-National8" target="_blank">[20]</a> offering ART) in relation to the proposed tier of CD4 service testing centre required to match and accommodate referred numbers of CD4 tests.</p><p>*testing facility framework and proportion offering ART; <b>^§</b>sample testing capacity per day.</p><p>Relationship between CD4 tiers and NDOH Health Care Facilities.</p

Current CD4 service coverage precincts.

<p>Map to reveal current estimated service precincts based on an averaged 100 km Euclidian radius. Areas without drawn service precincts largely coincide with districts with poorer LTR-TAT (see insert <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0114727#pone-0114727-g002" target="_blank">Fig. 2</a>). Note many health care facilities that fall outside of service precincts that would benefit from implementation of additional Tier-1, 2 and 3 services. Red circles highlight relatively over-subscribed areas with multiple ‘centralised’/metro laboratories in densely populated areas. In such metropolitan areas with high testing demands, amalgamation of services and the formation of a ‘super-laboratory’ could create critical mass, consolidate on technical skills and quality control provided that transport and IT logistics are absolutely optimized.</p

Colour-graded map indicating CD4 test volumes and laboratory-to-result turn-around-time (LTR TAT) in South Africa.

<p>Map to reveal the daily CD4 test service volumes (workload), across 52 districts in South Africa, colour-graded according to volumes of tests requested, averaged over three year from 2009–2012. Higher testing volumes (as red or orange) as well as ‘hard to reach areas’ with low testing needs (yellow, more likely to require POC testing) are revealed. Approximately 3.8 million CD4 samples were referred during 2012 to an annual average of ∼60 designated NHLS CD4 facilities (existing shown as green dots). Insert reveals proportions of reports issued within a TAT of 48-hours, across all districts, averaged over years 2009–2012. The legend here highlights districts (as red) with less than 34% of reports or 35–80% of reports (mustard orange) issued within a 48-hour TAT (see legend on figure).</p

Description of Proposed CD4 Testing Tiers.

<p>Table outlining proposals for CD4 tiers, indicating number of sites, volumes (workload) per day and per annum, the number of clinics serviced, proposed platforms/instruments for testing and estimated costs.</p>§<p>Flow Cytometer systems with automated sample preparation systems accommodating testing volumes; <b>*</b>dependent upon organizational capacity planning and disaster recovery planning; <b>^§§</b>Assuming widespread POC services are used to supplement existing laboratory services (i.e. no extended laboratory services at Tier-2 lab-supported POC-HUBS or Tier-3 community laboratories). **ZAR/USD exchange of R11/USD1 as at November 3^rd, 2014. Abbreviations: BC, Beckman Coulter, USA. BD, BD Biosciences, USA. NA, not applicable.</p><p>Description of Proposed CD4 Testing Tiers.</p

Estimating the cost-per-result of a national reflexed Cryptococcal antigenaemia screening program: Forecasting the impact of potential HIV guideline changes and treatment goals

<div><p>Introduction</p><p>During 2016, the National Health Laboratory Service (NHLS) introduced laboratory-based reflexed Cryptococcal antigen (CrAg) screening to detect early Cryptococcal disease in immunosuppressed HIV+ patients with a confirmed CD4 count of 100 cells/μl or less.</p><p>Objective</p><p>The aim of this study was to assess cost-per-result of a national screening program across different tiers of laboratory service, with variable daily CrAg test volumes. The impact of potential ART treatment guideline and treatment target changes on CrAg volumes, platform choice and laboratory workflow are considered.</p><p>Methods</p><p>CD4 data (with counts < = 100 cells/μl) from the fiscal year 2015/16 were extracted from the NHLS Corporate Date Warehouse and used to project anticipated daily CrAg testing volumes with appropriately-matched CrAg testing platforms allocated at each of 52 NHLS CD4 laboratories. A cost-per-result was calculated for four scenarios, including the existing service status quo (Scenario-I), and three other settings (as Scenarios II-IV) which were based on information from recent antiretroviral (ART) guidelines, District Health Information System (DHIS) data and UNAIDS 90/90/90 HIV/AIDS treatment targets. Scenario-II forecast CD4 testing offered only to new ART initiates recorded at DHIS. Scenario-III projected all patients notified as HIV+, but not yet on ART (recorded at DHIS) and Scenario-IV forecast CrAg screening in 90% of estimated HIV+ patients across South Africa (also DHIS). Stata was used to assess daily CrAg volumes at the 5^th, 10^th, 25^th, 50^th, 75^th, 90^th and 95^th percentiles across 52 CD4-laboratories. Daily volumes were used to determine technical effort/ operator staff costs (% full time equivalent) and cost-per-result for all scenarios.</p><p>Results</p><p>Daily volumes ranged between 3 and 64 samples for Scenario-I at the 5th and 95th percentile. Similarly, daily volumes ranges of 1–12, 2–45 and 5–100 CrAg-directed samples were noted for Scenario’s II, III and IV respectively. A cut-off of 30 CrAg tests per day defined use of either LFA or EIA platform. LFA cost-per-result ranged from $8.24 to$5.44 and EIA cost-per-result between $5.58 and$4.88 across the range of test volumes. The technical effort across scenarios ranged from 3.2–27.6% depending on test volumes and platform used.</p><p>Conclusion</p><p>The study reported the impact of programmatic testing requirements on varying CrAg test volumes that subsequently influenced choice of testing platform, laboratory workflow and cost-per-result. A novel percentiles approach is described that enables an overview of the cost-per-result across a national program. This approach facilitates cross-subsidisation of more expensive lower volume sites with cost-efficient, more centralized higher volume laboratories, mitigating against the risk of costing tests at a single site.</p></div

One-way sensitivity analysis of the cost-per-result.

<p>One-way sensitivity analysis to assess changes in the cost-per-result based on changes to the error rate, reduction/increase in CrAg LFA reagent cost and allocation of a full-time medical technologist at the Tambo Memorial laboratory.</p

Distribution of test volumes.

<p>This figure represents the four test volume scenarios (I-IV) where the x-axis represents the test volumes (fixed across scenarios) and the Y-axis the predicted percentage of laboratories performing these volumes. The red colored lines represent the 50^th percentile, while the blue lines represent the 5^th and 95^th percentiles. The remaining consecutive percentiles are colored green (10^th, 25^th, 75^th, 90^th percentiles).</p

Impact of changes in daily volumes on the cost-per-result.

<p>One-way sensitivity analysis to assess changes in the cost-per-result based on changes in daily CrAg volumes at 10, 20, 30 and 60% increase/decrease in relation to base-line cost-per-result.</p