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The current paper describes a point-of-care method using a pooled capillary blood sample and an auto-analyzer. The method was integrated with custom software, which could upload the results from the analyzer automatically to the server and generate decisions on anemia. Also, it could provide the treatment doses of IFA as per the protocol of the National program2.
The custom software was designed to integrate barcode printing, hematology data export, and visualization of data. It was designed using an online PHP-based desktop application using PHP scripting language and PHP desktop chrome with visual studio code as an integrated development environment. HTML 5, CSS, and JavaScript were used to design the user interface. Web services were developed using the PHP scripting language. A user could print multiple barcodes using this desktop application through a barcode printer. A barcode scanner was used to access the barcode data and send it to the auto-analyzer. Data was stored locally using SqlLite and on the server using MySql database with MySql workbench as an environment. The hematology reports could also be downloaded in PDF format. A detailed treatment protocol based on the Anemia Mukt Bharat guidelines12 has been integrated into the Android application (Table 1 and Table 2)2. This module calculated the IFA dose (the type and number of IFA tablets) based on the participant's age, sex, physiological status, and Hb level. In the case of young children who will need iron syrup, the dose (in milliliters of syrup) was calculated based on the child's body weight. The components of the Electronic decision support system (EDSS) display included (i) participant's anemia status (grade of anemia or no anemia), (ii) visual depiction of the prescribed IFA package (pink for a 45 mg tablet, blue for a 60 mg tablet for adolescents, and red for a 60 mg tablet for adults), (iii) dose (number of tablets to be delivered for 1 month), (iv) frequency and timing (daily or weekly after the meal) (Figure 3).
The current anemia program in India covers eight age and gender groups. The treatment doses are different, with 5 types of prophylactic doses and 7 types of treatment doses. Due to this, there is a possibility of errors in decision-making by the front-line health workers who have limited education and skills. Using this software, the errors can be eliminated, and the treatment delivery can be faster and more accurate. Therefore, the software has the potential to become a job aid for front-line workers to roll out anemia control programs at the population level. Previous studies have shown that front-line health workers could successfully use digital technologies for data collection and record keeping13. Receiving an electronic job aid would also enhance the perceived self-identity of this important first-line community health contact personnel14.
The basic cost of analysis using this method was about INR 75 per sample and included lancet, microtainer, and reagents. Even though a systematic cost analysis had not been done so far on this method, we believe that the overall cost would be comparable with other commonly used PoC methods like digital hemoglobinometer, which costs about INR 104-177 per sample analysis15. Additionally, considering the important advantages of the auto analyzer wherein markers such as RBC indices could be obtained, the auto analyzer based method could be considered promising for use in population-based surveys.
For optimal use of the integrated method in field settings, there were several critical steps that need to be followed. During blood sample collection, precautions should be taken not to press the fingers. Another critical step was sample mixing. Immediately after collection and before analysis, the sample should be mixed properly to get accurate results. During the sample upload, the firewalls installed on the laptop needed to be switched off. The system was used at the point-of-use with the help of 1 KVA batteries, which sustained the analyzer for about 4 h.
One limitation of the method was its temperature sensitivity. When the ambient temperatures were above 35 °C, the analyzer would work best inside a vehicle with an air conditioner. If the analyzed sample data was uploaded twice, the system automatically displayed the most recent upload, even though all the files would be available at the back end. The decision support tool was accurate in providing decisions. But for its use, front-line health workers needed to be digitally literate. Since the software was bilingual, it would not be difficult for the front-line health worker to understand the display language. However, if the software has to be scaled up for states other than Telangana, the new language needs to be incorporated.
With the help of an algorithm-based decision support tool and a simplified visual output, the front-line health workers will be able to treat anemics and follow them up throughout the treatment period. The integrated method has the potential for scale-up, is completely designed using open-source platforms, and is interoperable. This digital tool will provide a substantial impetus for rolling out the 'screen and treat' interventions for anemia reduction in resource-constrained settings.