Implementation of point-of-care diagnostics leads to variable uptake of syphilis, anemia and CD4+ T-Cell count testing in rural maternal and child health clinics

listen audio

Study Justification:
– Anemia, syphilis, and HIV are high burden diseases among pregnant women in sub-Saharan Africa.
– The study aimed to evaluate the effect of point-of-care technologies for testing and treatment coverage of these diseases in rural maternal and child health clinics in Mozambique.
– The study also assessed the acceptability of these technologies by health workers.
Highlights:
– Implementation of point-of-care CD4+ T-cell enumeration resulted in a decreased time to initiation of antiretroviral therapy among treatment eligible women.
– Overall hemoglobin and syphilis screening increased after the implementation of point-of-care testing.
– However, there was no significant change in the uptake of overall hemoglobin screening, syphilis screening, and CD4+ T-cell testing.
– The variability in results indicates the potential for detrimental effects in some settings.
Recommendations:
– Local context needs to be considered when implementing point-of-care technologies in order to improve service delivery to expectant mothers.
– Services should be restructured to accommodate innovative technologies.
– Further research is needed to understand the reasons for the variability in results and to identify strategies for improving testing and treatment coverage.
Key Role Players:
– Health facility staff (MCH nurses, laboratory staff, medical director)
– Ministry of Health officials
– Researchers and scientists
– Policy makers
Cost Items for Planning Recommendations:
– Training of health facility staff on the use of point-of-care technologies
– Procurement of point-of-care testing equipment (Hemocue 201+, Bioline 3.0 syphilis, Alere PIMA)
– Infrastructure improvements to accommodate the new technologies
– Monitoring and evaluation activities
– Research and data analysis
– Communication and dissemination of findings

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong, but there are some areas for improvement. The study design is quasi-experimental, which provides some level of evidence. The study includes data from four health facilities and compares outcomes before and after the implementation of point-of-care testing. The study also includes acceptability assessments from health workers. However, the abstract does not provide information on the sample size or the statistical methods used for analysis. Additionally, the abstract does not provide specific details on the results of the study, such as the magnitude of the changes in testing coverage. To improve the evidence, the authors could provide more details on the sample size, statistical methods, and specific results in the abstract.

Introduction Anemia, syphilis and HIV are high burden diseases among pregnant women in sub-Saharan Africa. A quasi-experimental study was conducted in four health facilities in Southern Mozambique to evaluate the effect of point-of-care technologies for hemoglobin quantification, syphilis testing and CD4+ T-cell enumeration performed within maternal and child health services on testing and treatment coverage, and assessing acceptability by health workers. Methods Demographic and testing data on women attending first antenatal care services were extracted from existing records, before (2011; n = 865) and after (2012; n = 808) introduction of point-of-care testing. Study outcomes per health facility were compared using z-tests (categorical variables) and Wilcoxon rank-sum test (continuous variables), while inverse variance weights were used to adjust for possible cluster effects in the pooled analysis. A structured acceptability-assessment interview was conducted with health workers before (n= 22) and after (n = 19). Results After implementation of point-of-care testing, there was no significant change in uptake of overall hemoglobin screening (67.9% to 83.0%; p = 0.229), syphilis screening (80.8% to 87.0%; p = 0.282) and CD4+ T-cell testing (84.9% to 83.5%; p = 0.930). Initiation of antiretroviral therapy for treatment eligible women was similar in the weighted analysis before and after, with variability among the sites. Time from HIV diagnosis to treatment initiation decreased (median of 44 days to 17 days; p<0.0001). A generally good acceptability for point-of-care testing was seen among health workers. Conclusions Point-of-care CD4+ T-cell enumeration resulted in a decreased time to initiation of antiretroviral therapy among treatment eligible women, without significant increase in testing coverage. Overall hemoglobin and syphilis screening increased. Despite the perception that point-of-care technologies increase access to health services, the variability in results indicate the potential for detrimental effects in some settings. Local context needs to be considered and services restructured to accommodate innovative technologies in order to improve service delivery to expectant mothers.

A quasi-experimental operational research study was conducted in four rural public health facilities in two provinces (Maputo and Gaza) in southern Mozambique. The sites (Moamba, Macia, Magude and Marracuene) were purposively selected due to the high volume of antenatal patients seeking MCH services and high prevalence of HIV, and for being health facilities supported by the Elizabeth Glaser Pediatric AIDS Foundation at the time of the study approval. Data were extracted from existing clinical charts and registers for two groups of women; the first group attended ANC before introduction of POC technologies for CD4+ T cell enumeration, hemoglobin and syphilis screening, and the second group after implementation of POC testing. Before introduction of POC testing, hemoglobin and syphilis testing were performed at the laboratory associated with the health facility using Lovibond (Orbeco-Hellige, Florida, US) and Rapid Plasma Reagin (RPR) (Biotec Lab, Suffolk, UK), respectively. Laboratories at these health facilities possessed very basic infrastructure and equipment, were staffed by 3–4 professionals and had relatively inefficient linkages to the corresponding referral laboratory. Nurses at the antenatal consultation gave a test request to pregnant women, who then queued at the laboratory, located in a different part of the same health facility, for blood collection. Once blood was collected, pregnant women waited for their results at the laboratory. After results were returned to the pregnant women by laboratory staff, women went back to the antenatal consultation where they would wait until seen by the nurse. Although the result for hemoglobin and syphilis was available on the same day prior to this study, the inefficient flow was burdensome and time-consuming for the client. In addition, pregnant women had to provide a separate specimen for CD4 counting as described below. Blood samples for CD4+ T cell enumeration were sent weekly to the referral laboratory, where testing was performed using the FACsCalibur (Becton Dickinson, San Jose, CA, USA). Nurses made an appointment for blood collection for CD4 counting on a fixed day, in general requiring therefore an extra visit. On the specimen collection day, women queued at the MCH clinic usually at very early hours of the day. The result on the CD4 counting would only be available on yet a different day, requiring an additional visit to the health facility. Antiretroviral therapy was initiated if CD4+ T-cell count was below 350cells/μL, the standard national policy at the time of the study. Initiation was done at the ANC clinic as soon as possible after determination of eligibility. The POC technologies introduced in January 2012 were: 1) Hemocue 201+ (Hemocue AB, Angelholm, Sweden) for hemoglobin measurement; 2) Bioline 3.0 syphilis (Standard Diagnostics Inc., South-Korea) rapid test for syphilis diagnosis; and 3) Alere PIMA (Alere Inc., Waltham, Massachusetts, USA) for CD4+ T cell enumeration. All these technologies were placed within the MCH services. At each health facility, MCH staff, laboratory staff and the medical director of the health facility were trained on the study objectives and procedures. The change in patient flow due to the implementation of POC technologies was discussed and arranged with clinic staff input within the protocol training. Two nurses within each health facility were trained to perform the tests for routine care within their MCH services. In one HF (Macia), a clinical officer had been trained for CD4+ T-cell enumeration prior to the study and continued supporting that service. After the training, the three POC tests were exclusively performed by the MCH nurses at the clinic. Women who attended their first ANC visit between January and December 2011 for the pre-POC evaluation, and between January and June 2012 for the post-POC evaluation, were eligible for the study. HIV-positive women were excluded from the analysis on coverage of CD4+ T-cell count enumeration and ART initiation if they were on ART at first ANC visit. The sample size for HIV-positive women was calculated separately for each of the health facilities based on a hypothesized 25% increase in ART uptake, using an 80% power and an adjustment for incompleteness of 5%. As data on uptake of hemoglobin and syphilis testing was limited at the time of protocol development, the study estimated to include an equal number of HIV-negative women. For the pre-POC period, files were randomly selected for review using systematic sampling. For the short post-POC evaluation, all files of the HIV-positive women were included in order to reach the desired sample size while for HIV-negative women files were randomly selected using systematic sampling. Data were extracted from antenatal care cards, PMTCT register books and laboratory register books. HIV patient files were used to cross-check laboratory results and ART initiation. Test coverage was defined as a test result being available in either of 3 places: laboratory registry, clinic registry or antenatal cards. Time from HIV diagnosis and each step of the laboratory services up to ART initiation was measured: i) Diagnosis of HIV as written on the antenatal cards; ii) Registration of CD4 analysis request at the MCH clinic; iii) Registration of blood collection at the MCH clinic; iv) Registration of the analysis at the laboratory as written on the CD4 result printout; v) Registration of the results at the clinic as written on the PMTCT book; vi) Registration of results in patient file at the MCH clinic. Structured interviews were conducted with MCH nurses and laboratory technicians to evaluate perceived and then actual acceptability of MCH nurses performing POC technologies, before and after introduction, respectively. The MCH nurses and laboratory technicians were informed about the study by the study team and interviews were conducted with those who provided consent. Data were extracted onto data extraction forms and entered into a Microsoft Access database. Data were analyzed using STATA Version SE/11.1 (Stata Corp, Texas, US). Study outcomes were laboratory testing and treatment uptake for syphilis for all pregnant women, testing uptake for anemia for all pregnant women, uptake of immunological staging for HIV positive pregnant women and uptake of ART treatment for eligible women. As the study was a retrospective routine data review, being screened was defined as having a test result documented in the patient file. Eligibility for ART for the purpose of the study was defined as having a CD4+ T cell count below 351 cells/μL. Anemia is defined as having a hemoglobin <8mg/dl. For each health facility, we estimated the proportion with test before and after introduction of POC technologies and compared two proportions using z-tests. In the pooled analysis, we estimated the overall proportions before and after introduction by pooling across health facilities using an inverse-variance weighted estimate. The overall effect of the POC was estimated by pooling the health facility specific effects using inverse variance weights, a technique based on the random effects model used in meta-analysis. The random effects model accounts for potential intra-cluster (health facility) correlation in the estimation of robust standard errors. The protocol was approved by the National Committee for Health Bioethics of the Ministry of Health, Mozambique and by the Ethics Committee of the George Washington University, Washington DC, US. Signed informed consent was obtained from all health worker interviewees. A waiver of signed consent was obtained from the Ethics Committees for performing chart reviews of participating pregnant women. Patient information was anonymized and de-identified prior to analysis.

N/A

Based on the provided information, here are some potential innovations that could be recommended to improve access to maternal health:

1. Mobile Point-of-Care Testing: Implementing mobile point-of-care testing devices for hemoglobin quantification, syphilis testing, and CD4+ T-cell count in rural maternal and child health clinics. This would eliminate the need for pregnant women to travel to separate laboratories for testing, reducing the burden and time-consuming nature of the current process.

2. Telemedicine Consultations: Introducing telemedicine consultations for pregnant women in rural areas, allowing them to receive medical advice and guidance remotely. This would improve access to healthcare professionals and reduce the need for multiple visits to health facilities.

3. Community Health Worker Training: Providing training and resources to community health workers to perform basic maternal health tests, such as hemoglobin screening and syphilis testing, in remote areas. This would bring healthcare services closer to pregnant women and increase testing coverage.

4. Integration of Services: Integrating maternal health services with existing HIV/AIDS programs to streamline testing and treatment processes. This would ensure that pregnant women receive comprehensive care and reduce the need for multiple visits to different healthcare facilities.

5. Improved Supply Chain Management: Implementing efficient supply chain management systems to ensure a steady and reliable supply of testing kits and medications for maternal health services. This would prevent stockouts and ensure that pregnant women have access to necessary tests and treatments.

6. Health Education and Awareness: Conducting health education campaigns to raise awareness about the importance of maternal health testing and treatment. This would help overcome barriers to access, such as stigma and misconceptions, and encourage more pregnant women to seek care.

7. Strengthening Referral Systems: Improving the coordination and communication between rural health facilities and referral laboratories to ensure timely and accurate test results. This would reduce the waiting time for pregnant women and enable prompt initiation of treatment when necessary.

It’s important to note that these recommendations are based on the specific context provided in the study and may need to be adapted to suit the local conditions and resources available in other settings.
AI Innovations Description
The recommendation that can be developed into an innovation to improve access to maternal health based on the study is the implementation of point-of-care diagnostics in rural maternal and child health clinics. This innovation involves using technologies such as Hemocue 201+ for hemoglobin measurement, Bioline 3.0 syphilis rapid test for syphilis diagnosis, and Alere PIMA for CD4+ T cell enumeration. These technologies would be placed within the maternal and child health services, allowing for immediate testing and results without the need for separate laboratory visits.

By implementing point-of-care diagnostics, pregnant women would no longer have to wait for their test results at the laboratory or make additional visits for CD4 counting. This would significantly reduce the time and burden for pregnant women, improving access to timely and efficient testing. The study showed that point-of-care CD4+ T cell enumeration resulted in a decreased time to initiation of antiretroviral therapy among treatment eligible women.

However, it is important to note that the study also highlighted the variability in results among different health facilities. Therefore, it is crucial to consider the local context and restructure services to accommodate these innovative technologies in order to improve service delivery to expectant mothers.
AI Innovations Methodology
Based on the provided description, here are some potential recommendations for improving access to maternal health:

1. Strengthening Laboratory Infrastructure: Improve the infrastructure and equipment at health facilities to ensure efficient and accurate testing for hemoglobin, syphilis, and CD4+ T-cell count. This could include providing necessary resources, training laboratory staff, and establishing better linkages with referral laboratories.

2. Integration of Point-of-Care Technologies: Expand the use of point-of-care technologies, such as Hemocue for hemoglobin measurement, Bioline 3.0 syphilis rapid test, and Alere PIMA for CD4+ T-cell enumeration. These technologies should be integrated within the maternal and child health services to streamline the testing process and reduce the need for multiple visits.

3. Training and Capacity Building: Provide comprehensive training to MCH nurses and laboratory technicians on the use of point-of-care technologies and ensure they are equipped with the necessary skills to perform the tests accurately. This will help improve the acceptability and uptake of these technologies.

4. Streamlining Patient Flow: Restructure the patient flow within health facilities to minimize waiting times and improve efficiency. This could involve optimizing the process of blood collection, result delivery, and consultation to reduce the burden on pregnant women and improve their overall experience.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Define Key Indicators: Identify key indicators to measure the impact of the recommendations, such as testing coverage for hemoglobin, syphilis, and CD4+ T-cell count, time from diagnosis to treatment initiation, and acceptability among health workers.

2. Data Collection: Collect data on the selected indicators before and after the implementation of the recommendations. This could involve reviewing existing clinical charts and registers, conducting structured interviews with health workers, and extracting data from antenatal care cards, PMTCT register books, and laboratory register books.

3. Data Analysis: Analyze the collected data using appropriate statistical methods. Compare the indicators before and after the implementation of the recommendations to assess the impact on improving access to maternal health. This could involve calculating proportions, conducting z-tests for comparing proportions, and using inverse-variance weighted estimates for pooled analysis.

4. Interpretation of Results: Interpret the results of the data analysis to understand the effectiveness of the recommendations in improving access to maternal health. Identify any significant changes in testing coverage, time to treatment initiation, and acceptability among health workers.

5. Recommendations and Action Plan: Based on the findings, make recommendations for further improvements and develop an action plan to implement the identified strategies. This could involve scaling up successful interventions, addressing any challenges or barriers identified, and continuously monitoring and evaluating the impact of the implemented recommendations.

By following this methodology, it would be possible to simulate the impact of the recommendations on improving access to maternal health and make evidence-based decisions for further improvements in the healthcare system.

Share this:
Facebook
Twitter
LinkedIn
WhatsApp
Email