An accurate hemoglobin estimation method is lacking at the point of care and may hinder population-based programs for treating anemia. Therefore, we developed a point-of-care method based on pooled capillary blood and an auto-analyzer integrated into a custom software application to categorize the hemoglobin values into different grades of anemia.
Robust point-of-care methods are required to estimate anemia at the population level. The accurate methods are lab-based and cannot be used at the point of care. To address this caveat, a novel method based on pooled capillary blood and a portable autoanalyzer was developed for the estimation of Hb. Additionally, custom software was developed for near-real-time integration of the Hb values from the auto analyzer to the server. Moreover, a decision support tool that can immediately categorize the participants into different stages of anemia was developed. The decision support tool was designed based on the World Health Organization (WHO) cut-off for anemia at the population level and was available for all age and gender groups. This simple and user-friendly tool could easily be used by front-line health workers who have limited technical skills. Overall, the method developed could be used at the point of care and is accurate. This high-throughput method could be used for screening anemia at the population level for all age and gender groups.
Anemia is a major public health problem globally, particularly in India. It is well known that anemia has a detrimental impact on the work productivity of the population and the economic growth of the country1. To leverage the national-level efforts to reduce anemia, the latest public health program initiated in 2018 is the Anemia Mukt Bharat program (AMB). AMB identifies 'testing' followed by tailored 'treatment' as one of the most promising approaches to reducing anemia prevalence in vulnerable age groups2. However, accurate point of care (POC) estimation of hemoglobin (Hb) for diagnosing anemia is needed to implement the 'test and treat' strategy of AMB. Moreover, robust methods are useful for accurately estimating anemia in large-scale community surveys. The current POC methods include non-invasive and minimally invasive devices, and they use capillary blood samples for Hb estimation3. However, several pre-analytical factors, such as variation in finger prick dimensions, the thickness of skin, and the stability of POC devices under environmental conditions, lead to imprecise measurements and result in large differences in prevalence estimates3,4,5. Therefore, there is a need to establish a method of Hb estimation that is mobile, has a short turnaround time (TAT), and is suited for resource-poor settings6. In order to address these needs, a pooled capillary blood collection method was developed using a touch-activated lancet (to ensure uniform prick depth and dimension) to facilitate 6-8 drops of the free-flowing blood sample into potassium ethylenediaminetetraacetic acid (EDTA) microtainer tubes. The Hb in these samples was then measured using a portable auto-analyzer placed in a vehicle at the POC equipped with an uninterrupted power supply or at a nearby center with electricity (Anganwadi, Health clinic, Panchayath, or household). A validation study comparing this method against two gold standard methods (paired venous blood samples and cyanomethamoglobin method) showed high accuracy and precision7,8.
In addition to setting up a valid and reliable POC method, there is a need for rapid decision-making to facilitate the screening and treatment of anemia at the population level. This is not currently feasible where the Hb estimation is done at the health facility, and a medical officer directly supervises the delivery of iron and folic acid (IFA) supplements. Due to the large population catered to by the medical officers at the primary health centers, there is a significant time delay in initiating the intervention. There is a need for technology that can reduce the job burden on the medical officer and empower the front-line health workers to carry out the intervention delivery without the direct involvement of medical personnel. Therefore, the study aimed to develop a custom application (eSTAR app) that can automatically transmit the data from the machine and an in-built algorithm that provides decision support to the front-line workers on the dosage of IFA based on Hb values, age, and gender groups. The software was designed using open source tools such as PHP: hypertext preprocessor (PHP) scripting language and PHP desktop chrome with Visual Studio Code as an integrated development environment. A detailed treatment protocol based on the Anemia Mukt Bharat guidelines has been integrated into the Android application2.
This integrated method addresses the ever-increasing demand to reduce the turnaround time of test results while maintaining accuracy and precision. Further, the ability to provide results within minutes enables rapid decision-making on the initiation of treatment and results in improved intervention delivery9. This integrated method can be adapted for any field-level surveys or intervention programs that include Hb testing. Additionally, it can be used at the health care facility as a job aid for the medical staff to decide on IFA treatment.
The protocol follows the guidelines of the Institutional Review Board of the ICMR-National Institute of Nutrition, Hyderabad, India (IRB. No.08/I/2018).
1. Pooled capillary sample collection for Hb analysis using hematology analyzer10,11
2. Analyses using a hematology analyzer
Testing the validity of the method
The validity of this method was established by comparing it with the gold standard, which was the venous blood autoanalyzer-based method. The validation study has been described in detail elsewhere8. Briefly, 748 apparently healthy volunteers provided a venous sample and a capillary sample consecutively on the same day. The analyses were conducted at the POC. The participants had a wide range of Hb values and belonged to categories of no-anemia, mild, moderate and severe anemia status. To establish the validity of the method, the mean differences and their confidence intervals were calculated. The bias and limits of agreement between different methods were estimated using Bland -Altman analysis.
The difference in the mean Hb values was small for the capillary blood auto-analyzer method and the gold standard venous blood auto-analyzer method, respectively (Table 3). The Bland-Altman plot for comparison between the two methods is presented in Figure 2. The mean difference and limits of agreement were 0.1 g/dL(-1.0 to 0.8).
The prevalence estimate of no anemia differed by 2.2% points between the two methods. The prevalence estimates of different grades of anemia were also very close, establishing the method's validity against the gold standard method (Table 3).
Testing the integrated software and decision support tool
The integrated method was piloted among 68 participants from Buggabai village, Ghatkesar, Narapally. The decision support tool accurately provided the anemia status and IFA doses of these participants, which were manually verified by the field medical officer based on the algorithm (Table 4).
The results show that the integrated POC method is valid and can be used for estimating the prevalence of anemia at the population level. To date, about 16,539 decisions have been generated for different grades of anemia using this method.
Figure 1: Sample collection and auto-analyzer setup. (A,B) Collection of a pooled capillary sample. (C) Auto analyzer setup at the point of care. Please click here to view a larger version of this figure.
Figure 2: Bland Altman plot. The plot compares the mean difference and limits of agreement between the developed (capillary blood-auto-analyzer method) versus the gold standard (venous blood-auto-analyzer method). The mean difference between the two methods was -0.1 (95% CI, -0.2; -0.1). This figure has been modified with permission from Dasi et al.8. Please click here to view a larger version of this figure.
Figure 3: Decision support tool. The tool displays the grade of anemia and treatment dose with iron and folic acid. Please click here to view a larger version of this figure.
Population | Cut-off (g/dL) | Mild and moderate anemia | Severe anemia |
Children 6–59 months | ≥11.0 | ≥7.0–<11.0 | <7.0 |
5–11 years | ≥11.5 | ≥8.0–<11.5 | <8.0 |
12–19 years (Girls) | ≥12 | ≥8.0–<12 | <8.0 |
12–14 y (Boys) | ≥12 | ≥8.0–<12 | <8.0 |
15–19 y (Boys) | ≥13 | ≥8.0–<13 | <8.0 |
Men | ≥13 | ≥8.0–<13 | <8.0 |
NPNL and lactating women | ≥12 | ≥8.0–<12 | <8.0 |
Pregnant | ≥11 | ≥7.0–<11.0 | <7.0 |
Table 1: Criteria to grade participants to different grades of anemia
Population | Per day dose (therapeutic dose) |
Children 6–59 months | 3 mg/kg body weight (Iron syrup containing 20 mg of iron and 100 µg of folic acid) |
5–9 years | 45 mg of iron + 400 µg of folic acid/day (Till the body weight cut off of 18.5 kg, Pink tablet) |
60 mg of iron + 500 µg of folic acid /day (>18.5 kg, blue tablet) | |
10–11 years | 120 mg of iron + 1 mg of folic acid (Blue tablet) |
12–19 years (Girls) | 120 mg of iron + 1 mg of folic acid (Blue tablet) |
12–14 y (Boys) | 120 mg of iron + 1 mg of folic acid (Blue tablet) |
15–19 y (Boys) | 120 mg of iron + 1 mg of folic acid (Blue tablet) |
Men | 120 mg of iron + 1 mg of folic acid (Red tablet) |
NPNL and lactating women | 120 mg of iron + 1 mg of folic acid (Red tablet) |
Pregnant | 120 mg of iron + 1 mg of folic acid (Red tablet) |
Table 2: Treatment protocol. Dosage should be given according to body weight (if the body weight is less compared to age). Severe anemic participants were referred to the local primary health center. For prophylactic doses, 1 IFA tablet per week was followed, except for pregnant women, where 1 tablet per day was given. For children, this was 1 mL biweekly. The treatment was given for 3 months.
Methods | Mean Hb (SD) g/dL | Prevalence of anemia (Overall) (%) | Prevalence of grades of anemia (%) | ||
Mild | Moderate | Severe | |||
Capillary blood auto analyzer method | 11.0 (2.1) | 34.9 | 19.7 | 36.4 | 9.1 |
Venous blood auto analyzer method | 10.9 (2.0) | 32.2 | 20.7 | 37 | 10 |
Table 3: Comparison between Hb estimates obtained by pooled capillary blood and autoanalyzer method against venous blood autoanalyzer method.
Age group | N | Mean Hb | SD | Decisions generated by the integrated system* | ||
Mild | Moderate | Non anemic | ||||
6–59 m | 11 | 9.7 | 1.41 | 4 | 5 | 2 |
5–11 years | 9 | 11.4 | 1.59 | 2 | 2 | 5 |
12–14 y | 4 | 12.4 | 1.56 | 1 | 1 | 2 |
NPNL | 28 | 11.7 | 1.29 | 8 | 6 | 14 |
Men | 16 | 14.7 | 1.34 | 0 | 3 | 13 |
Total | 68 | 11.98 | 1.44 | 15 | 17 | 36 |
*The automated decisions were verified by a field medical officer |
Table 4: Mean Hb values and decisions generated by the integrated system.
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.
The authors have nothing to disclose.
The team acknowledges Mr. J Suresh, Mr. Medappa, Mrs. Madhu, and the entire Kavintech Corporation, Bangalore team, who successfully developed the decision support tool and the software. The authors wish to also acknowledge the Indian Council of Medical Research, Government of India for funding and the Department of public health and family welfare, Telangana for facilitating the study.
ABX Miniclean | Horiba Ltd, Japan | 23-450-004 | Enzymatic solution |
ABX Minidil LMG | Horiba Ltd, Japan | 23-450-008 | Buffered isotonic solution for RBC/PLT dilution, sleeving and cleaning |
ABX Minilyse | Horiba Ltd, Japan | 23-450-006 | Hb measurement; lysing solution |
ABX Minocal | Horiba Ltd, Japan | 2032002 | Calibrator |
ABX Minoclair | Horiba Ltd, Japan | 23-450-003 | Cleaning reagent |
ABX Minotrol 16 – 2H | Horiba Ltd, Japan | 2042209 | Blood control |
ABX Minotrol 16 – 2L | Horiba Ltd, Japan | 2042208 | Blood control |
ABX Minotrol 16 – 2N | Horiba Ltd, Japan | 2042202 | Blood control |
Autoanalyzer | Horiba Ltd, Japan | ABX Micros ES 60 | The FTP port should be functional |
Barcode printer | Technology service corporation, USA | TSC Model TE 244 | 400 Mhz 32 bit RISC processor with 16 MB SDRAM, 8 MB Flash memory |
Barcode Scanner | Retsol | LS-450 | Any company which can provide a scanner with the following specifications: 32 bit CPU fast decode ability, IP 54 rated, Light source – visible laser diode 650 nm, Single scan pattern with scan rate of 100scans/second, Scan width of 200 mm & precision of 4 mil, Scan angle – YAW 65 Deg, Rotation 30 Deg & Pitch 55 Deg, Scan indication – buzzer, light indicator, Scan mode both manual & continue scanning |
BD needles holder | Becton, Dickinson and company Ltd, Dublin, Ireland | 364879 | |
Contact activated lancet | Becton, Dickinson and company Ltd, Dublin, Ireland | 366594, 366593 | For children below 1 year, venous blood sample has been collected. |
Custom software | Kavin Corporation, Bangalore | N/A | |
K2-EDTA Microtainer-5 mL | Becton, Dickinson and company Ltd, Dublin, Ireland | 363706 | EDTA tube for blood profile analysis with 1.0 mg K2 EDTA, dimensions 13 x 75 mm |
Labels | G-Technologies, Secunderabad, telangana | N/A | |
Laptop | Any | N/A | Intel Core I3-1005G1, 8GB DDR4, 1TB HDD, 15.6 FHD LED, WIN 11 HOME and MS OFFICE H&S |