Semi Quantitative Evaluation of Access and Coverage (SQUEAC) for OPD-SAM Programme Final Report
Lashkar Gah District of Helmand Province, Afghanistan From 10th to 29th March 2018
AFGHANISTAN
Funded by:
SQUEAC Manager: Sayed Rahim RASTKAR
Authors: Sayed Rahim RASTKAR, Celine Soulier & Bijoy Sarker
Action Against Hunger | Action Contre La Faim A non-governmental, non-political and non-religious organization
Acknowledgements
Action Against Hunger (AAH) would like to thank all the parties who were involved either directly or indirectly in the success of the SQUEAC assessment. ACF Helmand provincial office through the project manager for providing logistical support in addition to materials used in training and data collection . The SQUEAC assessment team for a high level of commitment and professionalism throughout the assessment period . All the key informants interviewed during the various stages of the assessment . All the communities residing in the districts surveyed for providing consent and taking part in the assessment . GAC for providing financial support to undertake the assessment.
Abbreviations ACF Action Contre la Faim | Action Against Hunger AYSO Afghan Youth Services Organization BHC Basic Health Center BBQ Booster, Barrier and Questions BPHS Basic package of health services BRAC Building Resources Across Communities (NGO) CHC Comprehensive health center CHS Community health supervisor CHW Community health worker IMAM Integrated management of acute malnutrition DH District Hospital DoPH Directorate of Public Health EPI Expanded Program on Immunization EPHS Emergency package of health services FGD Focused Group Discussion GAM Global Acute Malnutrition HMIS Health Management Information System MAM Moderate Acute Malnutrition MoPH Ministry of Public Health MUAC Mid-upper arm circumference OTP Out Patient Therapeutic Program PLW Pregnant and Lactating Women PNO Provincial Nutrition Officer PPHD Provincial Public Health Directorate RUTF Ready-to-use therapeutic food SAM Severe Acute Malnutrition SMART Standardized Monitoring and Assessment of Relief and Transitions WHO World Health Organization WFP World Food Program SQUEAC Semi-Quantitative Evaluation of Access and Coverage Table of Contents Acknowledgements ...... 2 Abbreviations ...... 3 1.0 Introduction ...... 10 1.1. Objectives ...... 10 1.2. Methodology ...... 10 1.3. SQUEAC investigation team ...... 11 1.5 Context ...... 12 1.5.1 Nutritional Situation ...... 14 * The new IMAM guideline with revised admission and discharge criteria’s is currently in the process of finalization till this report is being written ...... 16 2.0. The SQUEAC Survey - STAGE ONE ...... 16 2.1. Introduction ...... 16 2.2. Identification of areas with low and high coverage ...... 17 2.3. Quantitative data collection and analysis ...... 17 2.3.1 Admissions over time ...... 17 1.3 Admissions per health facility ...... 20 2.3.3 Discharge outcomes ...... 21 2.3.4 Length of stay before cure ...... 24 2.3.5 Defaulting over time ...... 25 2.3.6 Time to default ...... 26 2.4 Qualitative data collection and analysis ...... 27 2.4.1 Introduction ...... 27 2.4.2 Data compilation and analysis ...... 34 Introduction ...... 39 Hypothesis setting and testing: ...... 39 3.2 Prior building ...... 42 3.2.1 Introduction ...... 42 3.2.2 Weighted scores ...... 45 3.2.3 Simple scores ...... 45 3.2.4 Histogram prior ...... 45 3.2.5 Concept Map ...... 46 3.2.6 Mind Map ...... 47 3.2.7 Prior mode ...... 48 4. STAGE THREE: WIDE AREA SURVEY ...... 49 4.1. Minimum sample size of villages for the wide area survey ...... 49 4.2. Wide area survey Methodology ...... 50 4.3. Coverage estimations ...... 50 3.2 Results of the wide-area survey ...... 52 4.4. Measurement data of wide area survey ...... 53 4.5. Reasons for un-covered SAM cases ...... 53 5. Conclusions ...... 54 6. Recommendation and Joint Action Plan ...... 55 7. Annexes ...... 58
Table of Figures Figure 1: Admissions over time at 5 HFs and 2 Mobile clinics from February, 2017 to January, 2018 ...... 18 Figure 2: Total admissions per OPD-SAM site (5 HFs & 2 Mobile clinics) Lashkar Gah district, Helmand province ...... 20 Figure 3: MUAC at admission of 5HFs and 2Mobile clinic_ Lashkar Gah district, Helmand province ...... 21 Figure 4: Discharges over time –from treatment follow up cards of 5 HFs and 2 Mobile clinics from February, 2017 to January, 2018 ...... 22 Figure 5: Discharges over time –from the nutrition report (IMAM database) of 5 HFs and 2 Mobile clinics from February, 2017 to January, 2018_ Lashkar Gah district, Helmand province . 23 Figure 6: Discharge outcomes per OPD-SAM site- 5 HFs and 2 Mobile Clinics_ Lashkar Gah district, Helmand province ...... 24 Figure 7: Weeks in the program before discharge as cured_ from 5 HFs and 2 Mobile Clinics .... 25 Figure 8: Defaulters over time _4HFs and 2Mobile Clinics from February 2017 to January, 2018 Lashkar Gah district, Helmand province ...... 26 Figure 9: Weeks in the program before discharge as defaulter from 5 HFs and 2 Mobile Clinics 27 Figure 10: Bayes plot of OPD SAM prior mode (43.05 %) ...... 49 Figure 11: Measurement data analyzed by MUAC, WHZ, Both (MUAC/WHZ) and Odema ...... 53 Figure 12: Reasons for un-covered SAM cases founded during the wide area survey ...... 54
List of Table Table 3: List of Five health facilities supported by ACF with nutrition program services ...... 13 Table 4: ACF mobile clinic HR composition ...... 14 Table 5: IMAM_OPD SAM Admission and Discharge criteria ...... 16 Table 6: Health facilities list offering nutrition services ...... 16 Table 7: Boosters; sources of qualitative data collection, methods used to obtain this information and location of data collected from...... 29 Table 8: Barriers; sources of qualitative data collection, methods used to obtain this information and location data collected from...... 31 Table 9: Methods, Source and Location symbols list ...... 33 Table 10: The most effective boosters with explanation ...... 34 Table 11: The most potential barriers with explanation ...... 36 Table 12: Small area survey data ...... 41 Table 13: Small area survey result ...... 42 Table 14: Boosters and Barriers simple score and weighted score list ...... 43 Table 15: Prior estimations and prior mode for OPD SAM program ...... 48 Table 16: Shape parameters for OPD SAM program ...... 48 Table 17: Total SAM cases founded during the wide-area survey ...... 52
Executive Summary Action Against Hunger (AAH) in partnership with the BPHS Implementing organization Building Resources Across Communities (BRAC) and Ministry of Public Health (MoPH) conducted SQUEAC (Semi-Quantitative Evaluation of Access and Coverage) assessment in Lashkar Gah district of Helmand province from 10th to 29th March 2018. The assessment intended to provide reliable coverage estimation for the SAM treatment program, to gather information on barriers and boosters to access and to develop recommendations to improve coverage for SAM services. The assessment estimated an overall coverage of 40.3% (31.7% - 49.8%; 95% CI) using the single coverage estimator which was below the SPHERE standard thresholds for rural settings (>50%). SPHERE standards: Minimum Humanitarian Thresholds in Emergencies for IMAM programs coverage based on population settings namely Rural (>50%); Urban (>70%) and Camp (>90%) The SQUEAC methodology employed in the assessment to estimate the OPD-SAM treatment coverage. It applies both qualitative and quantitative techniques and triangulation using various sources and methods. Interviews with key community groups, staff of health facilities in charges, caregivers of SAM cases in program and caregivers of SAM cases not in the program revealed varied positive (boosters) and negative (barriers) factors influencing the OPD-SAM coverage. The positive factors include: Awareness about the nutrition program and Malnutrition illness in the community Positive opinion about the program of people those are receiving the services from the program Screening of under 5 years children at all health facilities and at the target village by Mobile team Screening of under-five years children and referring to health facilities by CHWs in the community Community mobilization and sensitization by ACF community promoters Screening of all under-five years children and treatment of SAM children through ACF mobile team weekly basis visit in Lashkar Gah district ACF doing Formal and on the job training for all staff of 5 health facilities covered by the ACF project in Lashkar Gah District Supervision and Monitoring for HF by BRAC/AYSO, DoPH, ACF and MoPH Most of the HFs staff was trained on IMAM/SOP Availability and use of IEC Material at health facilities supplied by ACF, ACTD and BRAC provincial office The negative factors include: Traditional treatment/Using Formula milk for the treatment of Malnutrition Long distance 1 hour far (2 hours for Female) from the Health Facilities Refer to a private doctor (local pharmacist and qualified medical doctors which have private clinics in the villages and providing health services to the community) for the treatment of malnutrition Long hours waiting at health facilities for services Low awareness of the beneficiary about program procedure Mothers are not allowed to go to Health Facilities for the treatment of her malnourished child without Mahram HF staff distributing RUTF to their relatives/ineligible people Poor economic status of the community (not able to cover transportation costs for/to health facility for proper follow up of treatment) The bad behavior of HF/Mobile team staff with caregivers Availability of RUTF in the marketed (Selling of RUTF by caregivers and HF staff) Migrations Workload on HF staff HF staff’s turnover
Recommendations: Capacity building of Health Facilities staff on accurate reporting and documentation. Improve documentation through regular supportive supervision and monitoring of Health Facilities. Provide the entire necessary update document (Treatment cards, Ration cards, Registers, Report format and Tally sheet) to HFs. Defaulter tracing and follow up system must be strengthen. Strengthen the existing referral systems through provision of adequate training to the Health Facilities staff as well as community based staff (CHSs, CHWs and FHAGs) Expand the scope of referral through engaging and involving key community figures in referral of malnourished children. Set up clear monitoring and follow up mechanisms to identify key challenges with referrals. Extend community mobilization, to create awareness and understanding about the program and malnutrition. Engagement of Key community informants in community mobilization and health education program. Community mobilization should have a formalized planning showing schedules and activities of all actors involved in nutrition program at health facilities and community level. Nutrition education should be the key effort of community mobilization, involving a collaborative effort between CHWs, CHSs and FHAGs. Integration of nutrition activities into other health services and campaigns Nutrition program education through radios or TV channels. Increase the number of staff in the health facilities Good coordination between health facility staff to support the nutrition activities Follow the job description by the new position nutrition counselors which made by PND.
1.0 Introduction Action Against Hunger has been implementing Severe Acute Malnutrition treatment program through Mobile clinic in Lashkar Gah district of Helmand province as well as supporting health facilities, Namely Mukhtar CHC, Safiyan BHC, Karta-e-Lagan CHC, Qala-e-Boost BHC, and B2one BHC since April 2017 up to 31st March 2018 under the F2E project funded by GAC. The project is being implemented with close coordination of BPHS and EPHS implementer (BRAC/AYSO and MSF) and PPHD of Helmand province. The assessment has been conducted to identify the main boosters and barriers to the OPD SAM program access and the single coverage for the Severe Acute Malnutrition (SAM) treatment program and to develop a joint action plan for the improvement of the program access and coverage. Coverage assessment was proposed in the catchment area of Mobile clinics and mentioned health facilities supported by ACF.
1.1. Objectives The overall objective of the assessment is to investigate the OPD SAM program coverage in Lashkar Gah district of Helmand Province in the target area of F2E project and providing contextual recommendations to improve the programme coverage in future.
Specific Objectives: To estimate the treatment coverage of the SAM treatment program. To identify positive and negative factors influencing service uptake of SAM program. To develop, in collaboration with BPHS/EPHS implementers and the government, recommendations and an action plan to improve service uptake. Setting the baseline coverage estimation of F2E project in Lashkar Gah. To improve the capacity of ACF, BPHS, EPHS staff and other partners on the SQUEAC methodology.
1.2. Methodology The SQUEAC assessment methodology used in order to estimate the coverage of the OPD-SAM treatment program in Lashkar Gah district of Helmand province and to provide recommendations to improve coverage. The SQUEAC included the following stages: Stage 1: Review of available program data from the Health facilities (OPD-SAM sites) from the previous 12 months and the collection and analysis of supplementary data from selected 5 health facilities and 2 Mobile clinics. This was combined with the collection and analysis of qualitative information from community members and health facility staff and the identification of negative and positive factors affecting coverage. Stage 2: Development and testing of hypotheses to confirm (or deny) assumptions related to areas of high or low coverage. The findings from these tests were then incorporated into the survey team’s prior mode for the OPD-SAM coverage and then used to calculate the required sample size for Stage 3. Stage 3: A wide-area survey to determine coverage estimates for the OPD-SAM and using Bayesian techniques The assessment took place over the course of 19 days, from 10th March, 2018 to 29th March, 2018 and culminated in a planning and recommendations workshop with the survey team and external participants.
1.3. SQUEAC investigation team The core survey team was composed of one SQUEAC program manager from Action Against Hunger Kabul Main office, one PNO from PPHD for supervision and monitoring of the processes, 5 supervisors from the field team, ( two key nutrition staff from the ACF Ghor office, three officers from BPHS implementing agencies (BRAC/AYSO)), and other 10 enumerators were health facility staff from the HFs of the target area. At first, the SQUEAC program manager delivered a two days training workshop to the 5 supervisors about the Coverage methodology implementation and then 2 days training for all 15 team members for fulfilling of first stage qualitative data from community then provided an explanation of each of the key stages of a SQUEAC. For stage 2, again two days training was conducted for all 15 survey team members. Also for wide area survey again the core team (survey manager and survey supervisors) conducted one day training for all 15 team members in accordance how to collect the data in stage three.
1.5 Context Description of Area and Population Helmand is one of the 34 provinces of Afghanistan, located in the southern part of the Afghanistan. The province is divided into fourteen districts such us Garmseer, Nawa, Nadali, Greshk, Khana shin, Marjah, Naw zad, Sangin, Mosa Qala, Wasir, Kajake, Baghran, Disho and Lashkar Gah is the capital of the province. The total population of the province is about 1,441,7691. Helmand has borders with Kandahar, Nimroz, Farah, Ghor and Daykundi provinces. Predominant tribe is the Pashtun although there are other minority tribes like Baluchi, Tajik and Hazaras. The most commonly spoken language in the province is Pashto. The Helmand Basin region is encompassed entirely by mountains - the Hindu Kush to the North, the East Iranian ridges to the West, and the mountains of Baluchistan Province to the East and South. The lower portion of the Basin is located in the worldwide subtropical dry zone. As a result, the area is arid or hyper arid. The lower Helmand Basin receives less than 75 millimeters (3 inches) of precipitation annually. Because winters are colder than is typical for the subtropical dry zone, the basin more closely resembles the large, continental deserts of Asia than the subtropical deserts found in Northern Africa and the Middle East.
Map 1: Map of Helmand Province
1 https://simple.wikipedia.org/wiki/Helmand_Province Lashkar Gah District Lashkargah is a district in the east of Helmand Province, Afghanistan, surrounding the provincial capital of Lashkargah. Its population is 45% Pashtun and 20% Baluch, with 30% Tajiks, 5% are Hindus and Hazara; the population was estimated at 201,546 2 in 2015. In 2015 ACF implemented emergency WASH programs in Helmand province, assisting people displaced by conflict. Since April 2016, ACF has been implementing integrated WASH and nutrition programs in the vicinity of Lashkar Gah city which is also the capital of Helmand province. The objective of the project is to improve the quality of care and access to health and nutrition services for the treatment of Severe Acute Malnutrition (SAM) and to improve access to water and hygiene and sanitation in the health facilities and communities. One of the activities of the nutrition and health sector is to provide support to BRAC/AYSO BPHS partner through training of health facility staffs and provision of tools to the health facility to improve the quality of SAM treatment in the health facilities. BRAC is an international non-profit non-political organization and AYSO is a national NGO and sub-contractor with BRAC in Helmand being BPHS implementing partner engaged in the health service delivery. ACF has piloted the mobile clinic service to improve the access for the health and nutrition services. In addition, ACF has been implementing treatment of OPD SAM through mobile clinic in the different villages, visiting villages that are outside the outreach areas of the health facilities, conducting active case finding through Screeners and nutrition promoters with close cooperation of Community Health Workers (CHWs) and Family Health Action Groups (FHAG).also disseminating the presence of mobile clinic in the village using speaker and conducting full package of the OPD SAM intervention. ACF mobile clinic visit the selected villages on a weekly basis. The mobile clinic also provides medical treatment for children that are affected by common and basic illness. The water and sanitation component of the project complements the nutrition interventions through the construction and rehabilitation of water points, training or hygiene promotion sessions for the community. ACF has two projects F2E (GAC funded) and D5S (CHF funded) in Helmand Lashkar Gah district in 22 selected areas and supporting five health facilities.
Table 1: List of Five health facilities supported by ACF with nutrition program services
2 https://simple.wikipedia.org/wiki/Helmand_Province Five HFs which are supported by ACF implemented by BRAC/AYSO S/No District HF Name Type OPD-SAM OPD-MAM IYCF Micronutrients 1 Lashkar Gah Mukhtar CHC Yes Yes Yes Yes 2 Lashkar Gah Karta e Lagan CHC Yes Yes Yes Yes 3 Lashkar Gah Safian SHC Yes Yes Yes Yes 4 Lashkar Gah B 2 1 BHC Yes Yes Yes Yes 5 Lashkar Gah Qala e Boost BHC Yes Yes Yes Yes
Table 2: ACF mobile clinic HR composition S/ Team Project Doctor Nurse Screener Promoter Psychosocial NO Counsellor 1 Mobile F2E 1 1 2 1 1 Team A 2 Mobile F2E 1 1 2 1 1 Team B 3 Mobile D5S 1 2 2 3 2 Team D 4 Mobile D5S 1 2 2 3 2 Team E On a weekly basis, they are doing supervision of the mobile sites. They have a specific checklist for supervision, one is for supervision of the mobile clinic OTP/IMCI and there is an exit Interview for U5 children, second for health facilities. They are doing comprehensive supervision two times in the rest of the project once at the start and once in the end of the project. 1.5.1 Nutritional Situation The Rapid Nutrition Assessment was conducted from 7th to 13th December, 2017 in Lashkar Gah and Nawa districts of Helmand province. 563 children aged 0-59 months and 518 children aged 6-59 months were assessed from 227 households out of planned 250 households..
The GAM prevalence based on weight-for-height Z-score was 10.0% (7.6 - 13.2; 95% C.I.) and SAM rate was 1.2% (0.5 - 2.5; 95% CI). GAM prevalence based on MUAC <125 mm was 12.9% (9.4 -17.5; 95% CI) and SAM (<115mm) was 3.1% (1.7 – 5.7; 95% CI) respectively. However, the combined GAM rate was at 16.1% (12.9-19.3:95% CI) and SAM rate of 3.3% (1.8-4.9: 95% CI). According to the WHO threshold classification for acute malnutrition (based on WHZ), this is a serious public health problem. Prevalence of Stunting rate was 53.1% (44.7 - 61.4; 95% C.I.) among children 6-59 months. Based on the survey finding every second child is suffering from chronic malnutrition or stunting. The prevalence of underweight was at 28.3% (23.3 - 33.8; 95% CI); this from of under-nutrition depicts the burden of acute and chronic under-nutrition among under-fives. Further analysis suggests that these rates do not refer to same children. Children classified as wasted based WHZ are not entirely overlapping (35.4%) with those classified wasted based on MUAC. If both criteria are combined, the overall prevalence of children U5 fall in the emergency threshold category defined by WHO in Nawa and Lashkar Gah districts, Helmand province that was found to be 16.1% (95% CI 12.9-19.3). When SAM alone is analyzed using combined WHZ and MUAC then the SAM caseloads is projected at 3.3% (95% CI 1.8-4.9%). Combined rates are recommended to be used for caseload estimation of SAM and MAM management in the assessed health facility coverage areas. IMAM Program Implementation protocol; According to the national IMAM Guidelines, a SAM child by MUAC should be admitted at <11.5cm and must visit every week until cured (having a MUAC of ≥12.5cm or above for 2 consecutive visits). Admissions can also be made through identifying a Weight for Height Z score (WHZ) of <- 3 SD, the child must have a Z score/SD of ≥-2 for two weeks as an outpatient. Admission and discharge criteria are set out in the national IMAM protocol as follows:
Table 3: IMAM_OPD SAM Admission and Discharge criteria ADMISSION CRITERIA
6 TO 59 MONTHS W/H or W/L <-3 Z score (WHO2006 standard unisex table) and/or MUAC <115 mm and/or Presence of bilateral pitting oedema (+ & ++ admission to OPD; +++ admission to IPD) DISCHARGE CRITERIA
6 TO 59 MONTHS W/H or W/L ≥-2 Z score on more than one occasion if
STANDARD OPD-SAM adequate arrangements for follow up have been made (Two days for inpatients, two weeks for outpatients). MUAC >125mm for children No oedema for 14 days * The new IMAM guideline with revised admission and discharge criteria’s is currently in the process of finalization till this report is being written 2.0. The SQUEAC Survey - STAGE ONE 2.1. Introduction Information about the beneficiaries of the SAM program was collected from the beneficiary’s treatment cards with information for the last one year (February 2017 to January 2018). The beneficiary information was collected from 5 health facilities supporting by ACF and from two ACF mobile clinics offering SAM services in the Lashkar Gah district (See Table 6). Table 4: Health facilities list offering nutrition services
Five HFs which are supported by ACF S/No District HF Name Type OPD-SAM OPD-MAM IYCF Micronutrients 1 Lashkar Gah Mukhtar CHC Yes Yes Yes Yes 2 Lashkar Gah Karta e Lagan CHC Yes Yes Yes Yes 3 Lashkar Gah Safian SHC Yes Yes Yes Yes 4 Lashkar Gah B 2 1 BHC Yes Yes Yes Yes
5 Lashkar Gah Qala e Boost BHC Yes Yes Yes Yes 6 Lashkar Gah Team A Mobile Yes Yes Yes Yes 7 Lashkar Gah Team B Mobile Yes Yes Yes Yes
2.2. Identification of areas with low and high coverage Quantitative and qualitative data triangulation by source and method were used to identify areas of low and high coverage areas. Quantitative analysis of routine data involved cross-checking OPD-SAM treatment card, OPD-SAM register card and OPD-SAM monthly reports used. Qualitative data were generated from interviews with key informants at community levels, and health facility staff. 2.3. Quantitative data collection and analysis At this stage, quantitative data about the program was analyzed with all the admission cards to give information on children’s admissions and outcomes. In the community and in the health facilities, meetings were held with persons those directly and indirectly involved in the IMAM program. The following quantitative information was collected for the SAM program:- 1. Admissions over time 2. Admissions per treatment site (health facility) 3. Program exits 4. Stage of admission to the program 5. Defaulting over time 6. Time to default 7. Length of stay in the program The sources of quantitative information include; OPD treatment cards, HMIS system, facility registers and nutrition reporting system. 2.3.1 Admissions over time The analysis of admission data covered a one year from February, 2017 to January, 2018. Data on monthly admissions was collected from the 2204 beneficiary cards from five health facilities and two Mobile Clinics as highlighted in table 1. It’s for this reason; the analysis was based on OPD- SAM treatment cards since the cards are the only proven that indeed OPD-SAM services were offered to the beneficiaries. Confirmation from OPD-SAM treatment cards revealed that MUAC <115 mm is the major criteria used in admissions.
According to the data analysis in the mentioned period, admissions increased when ACF mobile clinics started to work in the target area from July 2017 up to March 2018 but from the month of February ACF mobile clinics stopped the new admissions due to their project was about to end (31st March 2018). And admissions also decreased at the last months of the project starting from the December 2017. Figure 1: Admissions over time at 5 HFs and 2 Mobile clinics from February, 2017 to January, 2018
Admissions over time 400 350 300 250 200 150 100 50 Numberadmission of 0
Month
Total Admissions 1 M3A3
Multi sectorial indicators: FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC JAN FEB
F2E project Insecurity Harvesting (poppy) Seasonal population movements School periods / school expenses Holidays / celebrations Ramadan Donors' activities Financial terms Dry season Droughts Winter season Rainy season Floods Acute malnutrition prevalence Diarrhea Malaria Women activities / workload Harvesting (wheat) Harvesting (fruits vegetables) Labor opportunities Period of F2E project in the target area OPD SAM service implementation by F2E project High rate Low rate Normal or No activity 1.3 Admissions per health facility Analysis of OPD-SAM treatment cards revealed that Karta-e-lagan CHC had the highest number of SAM admissions over time as highlighted in figure 2. This was attributed to the fact that, the facilities had the biggest number of population as well as a higher number of CHWs than other HFs. Mukhtar CHC, Qala-e-Boost BHC and B2one BHC had the lowest SAM admissions because of unavailability of some beneficiary data for analysis for 2017 year. Also shortage of RUTF in multiple months in different periods of time at Qala-e-Boost BHC and Safyian SHC was noted during qualitative data collection. Mobile clinics by having high admissions in the program were high valuable for the people due to easy access to the nutrition program services. Also community requested that to continue nutrition and health services by mobile clinics in their villages for the future. Figure 2: Total admissions per OPD-SAM site (5 HFs & 2 Mobile clinics) Lashkar Gah district, Helmand province
Total admissions per health centre and mobile clinic 800
700
600
500
400
300
200
100
0 Mobile Team Mobile Team Qala-e-Boost Mukhtar CHC B21 BHC Safian BHC Karta-e-Lagan A B Total admissions
2.3.2 MUAC at admission According to IMAM guidelines for Afghanistan, the child should be admitted to OPD SAM treatment with a MUAC <115 mm, WHZ Score <-3SD or confirmed bilateral pitting oedema. Most of the children were admitted to OPD-SAM treatment based on MUAC criteria only, that is 92.4% (2,204 cases). High number of SAM children were admitted with MUAC measurements of 111mm, which is around 47.3% (966 cases) of the total admission based on MUAC revealing early admission of SAM cases to the program. Late admissions to OPD-SAM program was also observed with MUAC measurements as low as 90mm based on the OPD-SAM treatment card records. This lack of adherence to admission criteria coupled with poor documentation depicts that the OPD- SAM programs might appear to be not functioning normally as observed from confirmation of OPD-SAM treatment cards but this might not be the case as illustrated in figure 3. The median MUAC was 110mm illustrating a relatively early treatment of SAM cases to OPD-SAM programs. Figure 3: MUAC at admission of 5HFs and 2Mobile clinic_ Lashkar Gah district, Helmand province
MUAC at admission 300
250
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150
100 Number admissions Number of 50
0
95 99 98 97 96 94 93 92 91
≤90
111 124 123 122 121 120 119 118 117 116 115 114 113 112 110 109 108 107 106 105 104 103 102 101 100 ≥125 MUAC (mm)
2.3.3 Discharge outcomes The discharge outcomes include: cured, default, death and non-response rates which are compared to the SPHERE standards. The SPHERE thresholds for cure rate in OPD SAM is >75%, while death rate and default are <10% and <15% respectively3. It’s important to note that 5 cases were recorded as a death during last one year (Feb, 2017-Jan, 2018) from malnutrition and 14 cases were non response, out of 14 non response cases 12 were from 2 mobile clinics and 2 other were from the B21 BHC clinic. From April to May, 2017 - the program outcome was not good with having high defaulter >15% and low cured rate <75% due to shortage of RUTF. Migration and the season of the year where people are very busy with planting and other field activities in Helmand province. Figure 4: Discharges over time –from treatment follow up cards of 5 HFs and 2 Mobile clinics from February, 2017 to January, 2018
Discharges over time - all health centres 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%
Month Cured Defaulter Death Non-response
To check the quality of the program data and the reporting system of 5 health facilities offering OPD SAM services, we analyzed the second source of the data as well, which was nutrition program monthly reports in the IMAM database4. However, this showed contrary information regarding the outcomes, with a high cure rate being reported by the database. This further shows a gap in the reporting system, and supervision of activities is highly recommended to streamline the reporting system for accuracy.
3 Sphere Handbook , 2011 4 This is the data used by MOPH for planning and evaluation of the program Figure 5: Discharges over time –from the nutrition report (IMAM database) of 5 HFs and 2 Mobile clinics from February, 2017 to January, 2018_ Lashkar Gah district, Helmand province
Discharges over time - all health centres
100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%
Month Cured Defaulter Death Non-response
The discharge outcomes data analysis per health facilities from beneficiaries’ treatment cards for showing the performance of each health facility. According to the data Safian BHC was the worst outcome by having 80% of defaulters after Safian BHC, B21 BHC had 52% defaulters, Mukhtar CHC had 49% defaulters and Qala-e-boost had 30% defaulter from February 2017 to January 2018. However, the two mobile clinics data were very good compare to the SPHERE standards. The cure rate was >75%, while death rate and default are <10% and <15% respectively.
Figure 6: Discharge outcomes per OPD-SAM site- 5 HFs and 2 Mobile Clinics_ Lashkar Gah district, Helmand province
Discharge outcomes per health centre
100% 1%0% 1% 0% 0% 2% 0% 0% 13% 90% 1% 30% 80% 49% 70% 52% 60% 80%
50% 98% 97% Non-response 87% 40% 70% Death 30% 51% Defaulter 20% 44% Cured 10% 20% 0%
2.3.4 Length of stay before cure According to the IMAM guideline, the minimum length of Stay in the program for severely malnourished child is 4 weeks and maximum length of stay is 4 months or 16 weeks in the program. In the below figure median length of stay is 7 weeks, which building good treatment outcome as well as a positive perception of the community about the program. Still there were some cases in the program for 16 or 17 weeks due to the severity of cases, sharing RUTF with other children, not following the program visit properly and poor hygiene practices of their family.
Figure 7: Weeks in the program before discharge as cured_ from 5 HFs and 2 Mobile Clinics
Weeks in programme before discharge cured - all health centres 300
250
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Count 150
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0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Length of stay (weeks)
2.3.5 Defaulting over time Defaulting was identified as a major barrier to the program coverage. Inability to retain the beneficiaries to the program will have a negative effect, as the cases will worsen or even die in the community. So the target beneficiaries of the program will therefore have a negative opinion towards the program. This will have an effect on the enrollment to the program with the community associating the program only to the negative outcomes. Defaulters over time for the OPD-SAM program analyzed in the figure 8, showing that defaulter were present in every month of the year in all health facilities, but the high numbers of the defaulters were in May, June and October, November 2017. Access to the program decreased due to RUTF shortage, Migration and seasonal agricultural activities of the people in the field.
Figure 8: Defaulters over time _4HFs and 2Mobile Clinics from February 2017 to January, 2018 Lashkar Gah district, Helmand province
Defaulters over time 80 70 60 50 40 30 20 10 Numberdefaulters of 0
Month
Total Defaulters M3A3
2.3.6 Time to default A malnourished child who is under treatment with the recommended protocols adhered by both the health service provider and the caregiver shows constant improvement and is likely to stay for a shorter period of time. If such a child`s default after having received a considerable amount of treatment, recovery possibility out of the program is likely to be cured. A child who, however defaults so early from the program (<4 weeks) will have received treatment of little significance and therefore the same episode of malnutrition will possibly escalate again. In figure 9, it seems that early defaulter (less than 4 weeks in the program) is very high in general. Once again, it is the above-mentioned reasons that due to those issues - out of 384 patients almost 55.2% (212 cases) are defaulted in the first 4 weeks of the admission time. Most are early defaulter, which depicts issues around HFs related weakness in services as well as could be due to negative opinion/impression about the program or lack of awareness (health education for how to feed the child with RUTF and importance of treatment in the first place). Figure 9: Weeks in the program before discharge as defaulter from 5 HFs and 2 Mobile Clinics
Weeks in programme before discharged as defaulter - all health centres 70
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2.4 Qualitative data collection and analysis 2.4.1 Introduction The main objective of the qualitative investigation was to validate the results of the quantitative data analysis, to investigate emerging questions and to explore additional information that might be useful in understanding the factors that affects access and coverage of IMAM services. Meetings at the community level were held with different informants, to ascertain the level of community engagement in the programs. These informants included community leaders (Malek, and other elders), Religious leaders (Mullah), mothers in the community, mothers of defaulted children, mothers of malnourished children not in the program, traditional healers and also CHWs from the community. The methods used to collect the data were informal group discussion (administered to members of the community), semi-structured interview (administered to health workers), and in-depth interviews (administered to caregivers) and observed at the service delivery sites. Village selection for qualitative data collection was done, All OPD SAM sites in the target area of F2E project were visited. At each site, a village far and a village near, villages with high admissions and villages with low admissions, villages with high defaulters and villages with low defaulters, villages covered by mobile clinics, villages with high and villages with low cured rate were visited. Key informants were interviewed to ensure that the views of the general community were adequately represented. A total of 10 villages and 5 Health Facilities were visited within the three days allocated for qualitative assessment. The BBQ5 approach was used to organize data. At the end of each day after qualitative data collection, the team returned to base to discuss findings. These were identified and listed as either boosters or barriers to coverage for the OPD SAM program, with questions arising incorporated into the next day’s data collection. Data collection continued until sampling to redundancy was achieved, i.e. no new data were collected. Table 7 shows the sources of qualitative data collection, methods used to obtain this information and location where the data were collected .
5 Barriers Boosters and Questions Table 5: Boosters; sources of qualitative data collection, methods used to obtain this information and location of data collected from.
S/ Boosters Location Sources Methods No of responses No 1 Awareness of Malnutrition QK,LD,HR,TN,K,M B,I,A,G,D SSI,FGD 1,1,1,1,1,1,1,7,1,1,1,1,1,1,1,1,1, -CHC,LK- 7,1,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1, CHC,ABQ,AG,AH, MK 2 No Stigma about Malnourished children QK,HR,K,AHQ,AG B,A,G,I SSI,FGD 1,1,1,1,1,1,7,1,1,4,1,1,1,1,1,1,1,, ,AH,LK,MK 3 People Know about the Supplementary QK,K,KL-CHC,S- A, D,I SSI 1,1,1,1,1,1,1,1,1,1,1, foods for Malnourished children for BHC,AHQ,AH, treatment 4 Positive opinion about the program of LD,HR,K,M- A,I,D,G, SSI,FGD 1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,7, people those are receiving the services from CHC,KL- 1,1,1, 1,1,1,1,1,1,1 the program CHC,HM,B- BHC,QB- CHC,AHQ,AH,LK, 5 Screening of under 5 years children at all HR,K,M-CHC,KL- A, J,D,I SSI 1,1,1,1,1,1,1,1,1,1,1,1, health facilities and at the target village by CHC,AHQ,LK,AH, Mobile team 6 Presence of Health Education plan and HR,K,M-CHC,KL- A, D,I,G SSI 1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 conducting health education sessions at CHC,S-BHC,B- health facilities and Mobile team BHC,QB- BHC,LK,AHQ,AH, MK,AG 7 Awareness about the nutrition program of HR,K,M-CHC,KL- G,I,A,D SSI 1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1, the community CHC,S-BHC,QB- 1,1,1,1,1,1,1,1 BHC,AHQ,AH,LK, MK, 8 Communities referring their children to HR,TN,K,KL- G,I,J,A,D SSI,FGD 1,1,1,7,1,1,1,1,1,1, health facilities for the treatment of CHC,B- malnutrition BHC,AHQ,MK, 9 Presence of 97 health posts in the TN, J SSI 1, catchment area of 5 health facilities for community base activities 10 Good word of mouth in community TN,M-CHC,KL- I,A, SSI,FGD 1,7,1,1,1,1,1, CHC,S-BHC, 11 Screening of under-five children and TN,KL-CHC, M- E,I,D SSI,FGD 1,7,1,1,1,1,1, referring to health facilities by CHWs in the CHC, community 12 Community mobilization and sensitization by TN, KL,B- I,E,A,G SSI,FGD 1,1,1,1,1,1,1,1,1,1,7,4,1,1,1,1,1, ACF community promoter BHC,AHQ, 1,1,1,1, AG,AH,LK,MK, 13 Screening of all under-five years children M- A,I,G SSI,FGD 1,1,1,1,1,1,1,1,7,1,4,1,1,1,1,1,1, and treatment of SAM children through ACF CHC,AHQ,AG,AH, 1,1,1,1,1 mobile team weekly base visit in Lashkar LK,MK, Gah district 14 MAM children referring by the ACF Mobile M- A,I,G SSI 1,4,1,1,1,1 clinic to Health Facility CHC,AHQ,AG,AH, MK 15 Qala-e-Boost/Mukhtar CHC staff M-CHC,QB-BHC D SSI 1,1,1 conducting weekly base mass screening at community according to their schedule 16 ACF doing Formal and on the job training for M-CHC,KL- D SSI 1,1,1,1,1,1,1,1,1,1, all staff of 5 health facilities covered by the CHC,S-BHC,QB- ACF project in Lashkar Gah District BHC 17 Supervision and Monitoring for HF by M-CHC,KL- D SSI 1,1,1,1,1,1,1,1,1,1,1, BRAC/AYSO, DOPH and ACF, MoPH CHC,S-BHC,QB- BHC 18 Most of the HFs staff are trained on M-CHC,KL- D SSI 1,1,1,1,1,1,1,1,1 IMAM/SOP CHC,S-BHC,QB- BHC 19 Having proper defaulter tracing/ follow-up M-CHC,KL- D,A SSI 1,1,1,1,1,1,1,1 system at health facilities and Mobile teams CHC,QB-BHC,LK 20 Presence of IEC Material at health facilities, KL-CHC,M- D SSI 1,1,1,1,1,1,1,1,1, Supply by ACF, ACTD and BRAC provincial CHC,S-BHC,QB- office BHC 21 Qala-e-Boost , Karta-e-Lagan CHC and M-CHC,KL-CHC, D SSI 1,1,1,1,1,1, Mukhtar CHC had a regular supply (No QB-BHC RUTF shortage during 2017 and 2018) 22 Mothers are trained on MUAC by ACF and LK,AHQ,AH,MK,A A,I,G SSI 1,1,1,1,1,1,1,1,1,1,1,1 doing measurement of their children by G them self at home
Table 6: Barriers; sources of qualitative data collection, methods used to obtain this information and location data collected from.
S/No Barriers Location Sources Methods No of responses 1 Traditional treatment QK,HR B,I SSI 1,1,1, 2 Long distance - 1 hour far (2 hour QK,TN,M-CHC,S-BHC,QB- B,I,A,G SSI,FGD 1,1,1,1,1,1,1,1,1,1,4,1, for Female) Health Facilities BHC, AHQ,AG 3 No CHW QK,LD,HR,AHQ,AG, B,A,I SSI,FGD 1,1,1,1,1,1,1,7,1,4,1 4 Refer to the private doctor for the QK,LD, TN,K, S, B,G,I,F SSI 1,1,1,1,1,1,1,1,1 treatment of malnutrition 5 Long hours waiting at health QK,HR,TN,K,KL-CHC,B- A,I,G SSI 1,1,1,1,1,1,1,1,1,1,1 facilities for services BHC,LK 6 Sharing RUTF with other children at QK,AG, A,I,G SSI 1,1,1 home those are not malnourished 7 Low awareness about program QK,LD,K,B-BHC B,I,F SSI 1,1,1,1,1, procedure 8 Poor screening /early case finding QK,LD,HR,TN, B-BHC B,I,G,A SSI,FGD 1,1,4,1,1,1,1,1,1,1,7,1 at health facility outreach catchment area 9 Mothers are not allowed to go to QK,LD,K,S-BHC,B- B,A,I,F,D SSI 1,1,1,1,1,1,1,1,1,1,1,1,1,1,1, Health Facilities for the treatment of BHC,AHQ,AG,AH her malnourished child without Mahram 10 HF staff distributing RUTF to their Qk,LD,TN,AG,LK, B,I,G,A SSI,FGD 1,1,7,,1,4,1 relative/ineligible people 11 Low awareness of about the Qk,LD,K,HM, B,F,I SSI 1,1,1,1,1,1, determinants of Malnutrition 13 Poor economic status of community LD, TN,HM,B-BHC,AG,LK,MK B,I,A SSI,FGS 1,1,1,1,1,1,4,1,1,1,1, (not able to cover transportation costs for/to health facility for proper follow up of treatment ) 14 The bad behavior of HF/Mobile LD,TN,AHQ,AG,LK I,G,A,C FGD,SSI 4,1,1,1,1,7,4,1, team staff with caregivers 16 Availability of RUTF in the market LD, M-CHC,AG,AH I,G, M-CHC FGD,SSI 4,1,1,4,1,1,1 (Selling of RUTF by caregivers and HF staff) 17 Using Formula milk for the LD,TN,MCHC,AHQ,AG B,I,A SSI 1,1,1,1,1,1,1 treatment of Malnutrition 18 Lack of community mobilization QK,LD,HR,TN,M-CHC,B-BHC B,G,I,A SSI 1,1,1,1,1,1,1,1, activities at community 19 Gender base violence K,LK A,G SSI 1,1,1, 20 Insecurity K,KL-CHC E,D SSI 1,1,1, 21 Migrations K, M-CHC,KL-CHC,AH,MK E,D,I,A SSI 1,1,1,1,1,1,1,1,1 22 Workload on HF staff K, M-CHC,KL-CHC,AG,MK G,D SSI 1,1,1,1,1,1,1 23 Less daily working time of Health K G SSI 1, Facility (09:00AM-12:00PM) 24 Poor quality Screening at HF M-CHC, A, SSI 1, (weight, Height, Z-Score and MUAC) 25 HF Staff turn over S-BHC,KL-CHC,M-CHC D SSI 1,1,1,1, 26 People of Abdul haq village was not AHQ,AG B,I SSI 1,1,1,1,1 happy from the ACF mobile team from their bad behavior, selling drugs and other material 27 Mobile Clinic most focusing on AG,AH I, SSI 1,1,1,1 female doesn’t have interest to male 28 Mobile teams coming to the village AH, I SSI 1, so late starting their activities at 10:00AM
Table 7: Methods, Source and Location symbols list
Methods Symbols Sources Symbols Location Symbols
Group Discussion GD Caretaker of malnourished children in the program A Qadir Khan QK Semi-Structured Interview SSI Caretaker of malnourished children not in the program B Laisa-e-Dosti LD Observation Obs Caretaker of defaulter children C Haji Rostam HR Heath Facilities Staff D Talibano Numre TN CHW (M/F) E Khari K Mula F Mukhtar CHC M-CHC Malik G Karta-e-Lagan KL- CHC CHC Teachers H Safian BHC S-BHC Community members I B21 BHC B-BHC Qala-e-Boost QB- BHC Abdul Ahad AH Lalo Khan LK Mula Karim MK Abdul Ghani AG Abdul Haq AHQ
2.4.2 Data compilation and analysis The triangulated findings of the qualitative investigation were arranged in an overall list of barriers and boosters and organized by theme. The key observations are summarize below. Table 8: The most effective boosters with explanation
BOOSTERS EXPLANATION Mothers are trained on MUAC by Mother MUAC training is an approach of ACF organization that implemented in other countries ACF and doing measurement of and now implemented in Afghanistan. Community promoters provided nutrition, health and their children and their neighbor’s hygiene education sessions to mothers about malnutrition signs, consequences and others. children by them self at home Community promoters trained 2981 mothers on MUAC and Odema screening in 11 selected sites in 2017. ACF distributed MUAC tapes to all mothers. They screened their children and referred to mobile clinics for the malnutrition treatment. Community promoters and mobile clinic had a follow up of Mother MUAC screening that mothers did the screening correct or wrong. Community promoters conducted refresher training to those mothers that did the wrong screening. It helps in early case detection (active case finding) of malnutrition and timeline treatment of malnutrition. It prevents from the mortality and morbidity of U5 children.
Having proper defaulter tracing/ For proper follow up of admitted cases, mobile clinic had three tracks. 1: staff of the mobile follow-up system at health clinic calling to the parent of patients when they are not coming to the program for the facilities and Mobile teams treatment. 2: Community promoters followed door by door all SAM admitted children in the program. 3: Mobile clinic Nutrition supervisors sharing the list of all absent children with community leaders for the follow up of SAM children in the program. Supervision and Monitoring for HF BPHS implementer and DoPH used the PND monitoring checklist for all nutrition interventions by BRAC/AYSO, DOPH and ACF, and ACF used own supervisory checklist during mobile team supervision. MoPH ACF doing Formal and on the job First ACF conducted formal training for HFs staff and did on Job training and Follow up of On training for all staff of 5 health Job Training. ACF has a checklist for the following nutrition and MHCP activities: 1: Infant facilities covered by the ACF nutrition focused on 0-6 months. 2: Complementary Feeding and breastfeeding 6-24 project in Lashkar Gah District months. 3: Maternal Nutrition and Mother health (ANC, Safe delivery and PNC visits). 4: IMAM/Screening, Referral. 5: MHCP, Timing for the On Job Training and Follow up of ON job Training was after one month. Screening of all under-five years ACF has two mobile teams and has screened all U5 children by screeners in 11 selected sites. children and treatment of SAM When a child is detected as SAM and then admitted in OPD-SAM program and followed their children through ACF mobile team treatment by weekly base in each site. ACF also provided IMNCI consultations to all U5 weekly base visit in Lashkar Gah children that will have IMNCI problems. district Community mobilization and Community promoters conducted health, nutrition and hygiene session house-by-house visits sensitization by ACF community on daily base. During the community mobilization, they are screening all U5 children and promoter referred to mobile clinics for the SAM treatment and IMNCI consultations. They referred MAM children to close HFs for MAM treatment. They followed all absent children from OPD-SAM program at all selected sites. Presence of Health Education plan Nutrition nurses, community promoters and psychosocial counselors provided health, nutrition, and conducting health education hygiene and psychosocial support sessions at mobile site and at community level for the sessions at health facilities and prevention of Malnutrition of U5 children and pregnant and lactating women. Mobile team Screening of under 5 year children All the children coming to the health facilities they are screening them if the child is at all health facilities and at the malnourished they referring to OPD-SAM or OPD-MAM program for the treatment. And target village by Mobile clinic mobile clinic when they are the village community promoters informing all households to bring their children to the mobile clinic and the mobile clinic screener screening all of them. Awareness about the nutrition Awareness of the program and Malnutrition illness is very effective in disseminating messages program and Malnutrition illness in and urging early treatment-seeking behavior. There is a high awareness in most of the caregivers, the community both in the program and not in the program. Some caregivers reported having learnt of the program from their neighbors. The majority of the mothers could even explain the MUAC cut off points. This normally done through the ACF mobile clinic and health facility staff. Positive opinion about the Benefits of the program were reported across a board, Interviews with caregivers of children in program of people those are the program revealed that they were happy about the program since their children were receiving the services from the recovering from malnutrition and were adding weight. program The availability of free and accessible treatment was considered in high regard by informants, and the clear success in the treatment was reported. They were ready for any kind of possible cooperation in order to improve the program. Most of the HFs staff was trained The staffs of Kart-e-Lagan, Safyan, Mukhtar and Qala-e-Boost were trained in IMAM program. on IMAM/SOP During a visit at health facilities, it is confirmed that they know screening for SAM and MAM children, referral mechanisms and follow-ups, MUAC cut off and complications arising as a result of malnutrition. Screening of under-five children In all focus groups and interview, questions were posed in order to assess the level of CHW and referring to health facilities by activity. The teams were careful to ensure that where a CHW was present, they were also active, CHWs in the community and were active in screening for malnutrition. The CHWs interviewed generally described the screening and referral process well, with an acceptable frequency (every week). They also talked about going to neighboring villages to screen children. Good word of mouth in community Communication within the community, between neighbors, family and villagers is essential for spreading messages about malnutrition, program and treatment. During investigation, it is confirmed that the mentioned messages done remarkable work and made other mothers bring their children to HFs in order to get treated.
Table 9: The most potential barriers with explanation
BARRIERS EXPLANATION Traditional treatment/Using Provision of the perceived nutritious food combined with some local herbs was rampantly Formula milk for the treatment of reported. This is the first measure most of the caregivers took, if it failed, and then the Malnutrition malnourished children were taken for management. This was majorly reported through discussions with caregivers and community elders of villages, which were far from the OPD- SAM sites. Belief in traditional faith healers digs deep into the mindset of the people and is generational. Hence, the children are devoid of clinical treatment or appropriate treatment at the health facility. The traditional faith healers and the Zyarat Pasteur are influential figures or opinion makers, who want to maintain their status quo. This is a potential barrier to accessing the services of the health facility including the OPD-SAM center, Long distance 1hour far(2 hour for Interviews with Doctor in charge and discussions with caretakers of SAM children in the program Female) Health Facilities and caretakers of SAM children not in the program revealed that distance from/to the health facility was too far especially when there is no transportation connection between the village and HF. Access is even more difficult when villages are over 5 km from a health facility, have no CHW, community outreach or mobile clinic, and/or fall in insecure fighting zones. Refer to a private doctor for the The interviews done with various sources from different location showed that there is a treatment of malnutrition practice of taking the children to the private doctors for the treatment of malnutrition. It is because of no awareness about the program or most of the times they assume that due to (insecurity, transportation problems, long waiting time for achieving services at HFs, the bad behavior of HF staff or less believe on the program) they prefer going to private doctors rather than HFs. So, the children are devoid of appropriate treatment of malnutrition at the health facility. This is a potential barrier to accessing the services of the health facility including the OPD-SAM center. Long hours waiting at health Observations of the SQUEAC team were made in most health facilities to report on the facilities for services organization of the program. The HFs serve a big population causing crowding at the sites and mothers waiting for long to be served. And they are coming from far area, according the interview SQUEAC team had with these mother, they mentioned that due to the long waiting at health facility reduces their interest and don’t like to come for next time or visit. Low awareness about program Interviews with community members (men and women), “Malik”, CHWs, vaccinators and procedure caregivers of children not in the program, as well as maleks, mullahs and other community members reported little or no awareness of the program. This was reported especially in many of the far areas. They do not know about MUAC tape, treatment and other information regarding nutrition program procedure. Mothers are not allowed to go to During the data collection, one of the reasons why malnourished children were not in the Health Facilities for the treatment program was the lack of permission to go to the OPD-SAM sites by the family members. of her malnourished child without Interviews with mothers also reported lack of permission as the main reason why mothers with Mahram malnourished children will not have them enrolled in the nutrition program. HF staff distributing RUTF to During the interview at the community with community members (men and women), “Malik”, their relative/ineligible people CHWs, vaccinators and caregivers of children not in the program, as well as maleks, mullahs and other community members reported that health facilities staff distributing RUTF to their relative or ineligible people. Poor economic status of Scattered population across the province is another reason to depress access of the SAM community (not able to cover treatment program, because the distances of villages to the health facilities is far and poor transportation costs for/to health economic status of community, not able to cover transportation costs thus limiting the facility for proper follow up of malnourished children accessing treatment on weekly and regular basis. treatment) The bad behavior of HF/Mobile Interviews with mothers and caregivers point to a very important barrier that most of the time team staff with caregivers RUTF only given familiar beneficiaries not giving to eligible beneficiaries. Long waiting time at the clinic, recurrent visits with no RUTF due to wrong information about next visits, deter beneficiaries from returning to the program. Migrations Interviews were held with caregivers of defaulters, IMAM staff and CHWs interviewed on defaulting reported migrations (due to insecurity and seasonality) as a major cause of absences and defaulting. Defaulters of Zara Malimeen in the program were due to migrations to locations far from the program areas. Workload on HF staff Observations by the SQUEAC team revealed that no specific nutrition staffs were attached at approximately all health facilities to support implementation of IMAM services. Activities such as growth monitoring/anthropometric measurements and supplementation, is quite overwhelming for the in charge or midwife (who is currently responsible) to do routine work plus all mentioned activities. Staff shortage is a major problem in service delivery at HFs. Interviews with clinic staff revealed that at the basic health center, a doctor or midwife works approximately in in (6-7) departments and in this case there are very many patients waiting to receive different services. Sometimes if one of the health worker fails to report to the health center it results to overcrowding of patients and in some occasions they health worker is overwhelmed. There is not a specific staff directly stationed at the nutrition program and thus the same health workers rotates to ensure they provide all services and if not some services are provided intermittently or twice a week.
STAGE TWO Introduction Based on stage-1 data, it is assumed that the coverage is low (below 50% throughout). But the thorough analysis of Quantitative & Qualitative data from stage one revealed that the coverage was uneven in the health facilities and villages and some villages or areas have a higher coverage than other villages where the coverage is low. Therefore Stage 2 was undertaken following two objectives: 1. To test our ideas for areas of potential high and low coverage 2. To confirm that coverage is uniformly low throughout the districts The teams were trained during two days in active and adaptive case-finding as well as MUAC, weight, Height/length and oedema screening. Structured questionnaires to use for both covered and non-covered cases were developed and the teams were trained to use them. The questionnaires were translated from English into Dari and then translated back by a different person in order to verify the quality of the translation. Hypothesis setting and testing: Based stage one data (quantitative data and qualitative data) analysis, the SQUEAC team come with the assumption that the villages that are covered by mobile clinic have high coverage, due to easy access. And low coverage in the catchment area of health facilities both far and near. The hypothesis agreed on with the following justifications; 1. Mobile team going to the selected villages and providing health and nutrition service’s to the vulnerable people, but the services providing by health facilities people need to come from far way to receive the services. 2. Due to culture, mothers are restricted to go to health facility for the treatment of their malnourished children, either they live near to the health facility or far from health facility. 3. Low program awareness in the catchment area of the health facilities and high awareness in the catchment area of mobile clinic, mobile clinic have specific staff for the community mobilization and health education in the community. 4. Caregivers in far areas will need more time, considering travelling time and waiting time at the health facilities, high cost of transportation due to long distance and often damaged roads, which would not be fully accepted by the families.
Part A: Villages covered by Mobile clinic’s the coverage of the nutrition program will be high (more than 50%). Part B: Village or catchment area of the health facilities either near or far and not covered by the mobile clinics, the coverage will be low (less than 50%). 3.2.1 Methodology: As these hypotheses are related to the spatial distribution of coverage, to test these hypotheses, a ‘small-area survey’ was conducted in 5 villages covered by ACF mobile clinics (Haji Mohammad Dawod, Haji Hatam (Qazi), Mula Grghib, Haji Abdul Manan and Abdul Ghafoor) and 5 villages not covered by ACF mobile clinics (Maliman, Abdul Salan, Mula Sardar, Haji Farid Ullah and Shayesta Gul). Active and adaptive case finding was the method used to find all SAM cases in the selected village using MUAC, W/H, Z-score and Oedema measurements. Then when a case was found, the caregiver was interviewed whether the child was already in the program or not. In each village a guide was identified to orient the team, take them around the village and ensure each household with a child aged 6-59 years was surveyed. The LQAS (Lot Quality Assurance Sampling) tool was used to analyze the data. As the sample size in small-area surveys is too small to correctly estimate coverage, the following formula was used to classify coverage accurately and reliably, despite the small sample size, as satisfactory (i.e., coverage meets or exceeds the standard) or unsatisfactory (i.e. Coverage does not meet or exceed the standard): d = Decision rule; n = Sample size; p = Coverage standard
p d = n x 100
In each type of village tested (covered by mobile team or not) a decision rule (d) was calculated based on the total number of cases found (n) and the coverage standard appropriate to the context. The total number of covered cases found in the small-area survey, then compared to d (threshold value). In the suspected high coverage villages, if the number of covered cases found exceeds d, part A was proven. If it equals or is below d, the hypothesis was disproven. In the suspected low coverage villages, the opposite was true.
For this test, 50% was selected as the appropriate coverage standard in rural settings as per the Sphere minimum standard for coverage of OPD-SAM program. Results: During this test, only active SAM cases were included. Therefore, recovering cases were excluded from the results (shown in Table 12). Table 10: Small area survey data
Team Health Distan Date Villag Covere Non Re- Number Facilit ce Team leader e/s Village d Covered Covering y Name to HF Dr. M. Safian Haji M.d 22/03/2018 Mobile team 7 4 2 Sharif BHC Dawod Dr. Mukhta 22/03/2018 Haji Hatam Mobile team 5 2 0 Bismillah r CHC High Dr. Safian 23/03/2018 Mula Grghib Mobile team 5 1 0 Coverag Bismillah BHC Karta- e Area Dr. M. Haji Abdul 23/03/2018 e-Lagan Mobile team 7 1 0 Sharif Manan CHC Haji Sayed Mukhta Abdul 23/03/2018 Mobile team 3 1 3 Ahmad r CHC Ghafoor Total 27 9 5 0 SAM cases
Team Distan Re-
Number ce Covering Health Villag Covere Non
Facility e/s d Covered Team Village leader to HF Name Karta- Haji Sayed 8Km(1.7Hou 22/03/2018 e-Lagan Maliman 0 2 1 Ahmad rs) CHC Dr. Niaz B- 21 22/03/2018 Abdul Salan 5 Km 0 0 1 Mohammad BHC Low Qala-e- Dr. 22/03/2018 Boost Mula Sardar 3Km 1 3 0 Coverag Garibullah e Area BHC Dr. Safian Haji Farid 23/03/2018 1 KM 1 1 0 Garibullah BHC ullah Qala-e- Dr. Niaz Shayesta 23/03/2018 Boost 4Km 1 0 0 Mohammad Gul BHC Total 3 6 2 The test of the hypothesis proved that the survey team’s belief about the coverage was correct for both hypotheses; In the villages covered by ACF mobile teams the coverage is high (more than 50%) and in the villages located far from the health facilities (OPD-SAM program) and not covered by the mobile teams, coverage is low (less than 50%).
Table 11: Small area survey result
High coverage in the Low coverage in villages not villages covered by mobile covered by mobile clinics clinics Total SAM cases (n) 36 9 Decision rule/threshold 18 4.5 value (d) Covered cases found 27 3 Conclusion of test Covered cases are greater Covered cases are less than d. than d. Hypothesis A is proven Hypothesis B is proven The survey teams to the nearest treatment site referred all the children who were SAM and not covered by the treatment program. The primary caregivers of such children interviewed on the reasons why their children not enrolled in a treatment program. The major reasons reported were lack of program awareness, long distance to the health facilities and lack of transportation and finances for the journey cost. 3.2 Prior building 3.2.1 Introduction One important aspect of SQUEAC is the ability to combine the existing information with a small sample to get the estimate. The existing information collected in the survey gave just a feeling of how coverage is likely to be. The Bayesian technique used to be able correctly represent the belief about coverage. The ‘Prior’ (the mode of the probability density) was developed based on findings of Stage 1 and Stage 2, to assume the most likely coverage rate that the OPD-SAM program expects. To develop the prior of Lashkar Gah, Helmand province (F2E project target area) SQUEAC assessment, 5 methods used to ensure triangulation, which is an important principle in SQUEAC methodology. The methods used included having the average of the simple scores, the average of the weighted scores, the average of the Histogram believe, mind map and concept map. The investigation team went through the final list boosters and barriers that have a high effect on OPD SAM program access and coverage (identified during Stage 1) and scored each one according to their relative impact on coverage. A score of between one and five (low and high effect) was allocated to each barrier and booster (100/the maximum list of boosters (19) = 5.2 rounding down the number to 5). This ensured that the prior influenced by the relative importance of each booster/barrier. The process of scoring of boosters and barriers is as shown in the table below: Table 12: Boosters and Barriers simple score and weighted score list
Boosters Simple Weighted Barriers Simple Weighted Score Score Score Score Awareness about the nutrition program and Traditional treatment/Using Formula milk for the Malnutrition illness in the community 5 5 treatment of Malnutrition 5 3
No Stigma about Malnourished children Long distance 1hour far(2 hour for Female)Health 5 2 Facilities 5 5
Positive opinion about the program of people those Refer to a private doctor for the treatment of are receiving the services from the program 5 5 malnutrition 5 2.5
Screening of under 5year children at all health Long hours waiting at health facilities for services facilities and at the target village by Mobile team 5 5 5 3.5
Presence of Health Education plan and conducting Low awareness about program implementation health education sessions at health facilities and procedure (visit Length, number of RUTF, usage 5 3 5 4 Mobile team of RUTF etc.)
Communities referring their children to health Poor screening /early case finding at health facility facilities for the treatment of malnutrition 5 2 outreach catchment area 5 4
Presence of 97 health posts in the catchment area of Mothers are not allowed to go to Health Facilities 5 health facilities for community base activities for the treatment of her malnourished child 5 2 without Mahram 5 5
Good word of mouth in community HF staff distributing RUTF to their 5 3 relative/ineligible people 5 4
Screening of under-five children and referring to Poor economic status of community (not able to health facilities by CHWs in the community cover transportation costs for/to health facility for 5 3 proper follow up of treatment) 5 2.5
Community mobilization and sensitization by ACF The bad behavior of HF/Mobile team staff with community promoter 5 4 caregivers 5 3.5
Screening of all under-five years children and Availability of RUTF in the marketed (Selling of treatment of SAM children through ACF mobile team RUTF by caregivers and HF staff) weekly base visit in Lashkar Gah district 5 5 5 5 Qala-e-Boost/Mukhtar CHC staff conducting weekly Gander base valance base mass screening at community according to their schedule 5 2 5 3.5
ACF doing Formal and on the job training for all staff Migrations of 5 health facilities covered by the ACF project in Lashkar Gah District 5 5 5 2
Supervision and Monitoring for HF by BRAC/AYSO, Workload on HF staff DOPH and ACF, MoPH 5 3 5 5
Most of the HFs staff was trained on IMAM/SOP 5 4 HF Staff turns our 5 4 Having proper defaulter tracing/ follow-up system at Poor quality Screening at HF (weight, Height, Z- health facilities and Mobile teams 5 3 Score and MUAC) 5 5
Presence of IEC Material at health facilities, Supply by Poor Nutrition program documentation at health ACF, ACTD and BRAC provincial office 5 3 facilities 5 5
Qala-e-Boost, Karta-e-Lagan CHC and Mukhtar CHC had a regular supply (No RUTF shortage during 2017 and 2018) 5 4
Mothers are trained on MUAC by ACF and doing measurement of their children by them self at home 5 3
95 66 85 66.5 95 66 15 33.5
To calculate the prior mode, the following below formula used:
3.2.2 Weighted scores The scores given to each factor depended on how much it confirmed by many sources, methods, locations and the potential impact it had on coverage. A factor confirmed by fewer sources and methods with a lesser impact was deemed to be of low significance while those factors confirmed by several sources, methods, locations and with a high potential impact were given a high significance score. Each booster and a barrier were given a score ranging 1-5. The total sum of the boosters was added to the lowest possible coverage (0 + 66) = 66% The total sum of the barriers was subtracted from the highest possible coverage (100 – 66.5) = 33.5% Prior mode; from the weighted boosters and barriers (66% +33.5%)/2 = 49.75%. 3.2.3 Simple scores All the factors were given a score ranging 1-5 with the assumption of the impact that had on coverage. The total sum of the simple boosters was added to the lowest possible coverage (0 + 95) = 95% The total sum of the simple barriers was subtracted from the highest possible coverage (100 – 85) = 15% Prior mode; from the simple boosters and barriers (95% +15%)/2 = 55%. 3.2.4 Histogram prior A histogram prior developed collectively in the classroom as a starting point for the prior development. Each coverage value (x-axis) discussed and a belief of whether coverage is likely to be that value determined (y-axis). A prior mode (most likely value for coverage) was determined at 34% for the OPD SAM program. Team 1 Team 2 Team 3 Team 4 Team 5 25.5 28 34 40 40 Median 34 Histogram Prior
Photo 1: Histogram believes_F2E project Lashkar Gah, Helmand Province
3.2.5 Concept Map Following the finalization of the barrier and booster table, the teams worked together to draw concept maps for barriers and boosters to illustrate the links between factors and how they link to the coverage. Photo 2: Concept map
By counting the links between boosters and barriers, it was possible to calculate another prior estimation; it was possible to identify 26 positive and 40 negative links: (0+26)+(100−40) - Concept map prior estimation for OPD SAM = = ퟒퟑ% 2 3.2.6 Mind Map Another method, which can be used to estimate a prior, is to count the total number of positive and negative factors on the mind map constructed during Stage 1 of the SQUEAC. This includes observations made during the quantitative data analysis and all of the positive and negative factors identified during the qualitative data investigation. A total 65 positive and 98 negative factors identified. (0+65)+(100−98) - Mind map prior estimation for OPD SAM = = ퟑퟑ. ퟓ% 2 3.2.7 Prior mode The average of these prior estimates for the OPD SAM program was calculated in order to produce an average prior mode (see Table 15). Table 13: Prior estimations and prior mode for OPD SAM program
Prior contributing element OPD SAM program Simple barrier and booster prior 55 Weighted barrier and booster prior 49.75 Histogram prior 34 Concept Map prior 43 Mind Map prior 33.5 Average / Prior mode 55+49.75+34+43+33.5/5= 43.05% The prior mode value of 43.05% plotted for the OPD-SAM program using Bayes SQUEAC Coverage Estimate Calculator (version 3.01). To do this the team first needed to apply a range of uncertainty to the prior mode. In Lashkar Gah district, Helmand province this was the second time to conduct the SQUEAC assessment. The team judged that they had high certainty about the prior modes. Therefore, they applied a range of uncertainty + and – 20%. Therefore, for OPD SAM, with a prior mode of 43.05%, the minimum probable value was 23.05% and the maximum probable value 63.05%. The conjugate analysis method used in SQUEAC requires the prior distribution to be summarized by two numbers called shape parameters, αprior and βprior. These were calculated using the mode and the minimum and maximum probable prior values as follows:
Prior Mode 43.05% Input the % value, and the rest will be converted to proportions. Uncertainty 20% Input the % value without + or - signs, and the rest will be converted to proportions. Minimum 0.2305 Maximum Probable Value 0.6305 Probable Value
μ 0.43
σ 0.07
α prior 23.3 β prior 30.8
Table 14: Shape parameters for OPD SAM program
OPD SAM α Prior 23.3 β Prior 30.8 With the Alpha and Beta shape parameters, it was possible to plot the prior distributions on the Bayes calculator. 풎풐풅풆(ퟏ − 풎풐풅풆) 풏 = − (휶 + 휷 − ퟐ)ퟑ (풑풓풆풄풊풔풊풐풏 ÷ ퟏ. ퟗퟔ)ퟐ Figure 10: Bayes plot of OPD SAM prior mode (43.05 %)
The sample sizes required to complete the conjugate analysis were therefore, calculated to be 53 SAM cases for the wide area survey. 4. STAGE THREE: WIDE AREA SURVEY The principal objective of Stage III is to provide an estimate for coverage across the selected area. This firstly requires the development of likelihood, though a wide area survey, and then, using a Bayesian conjugate analysis, combine the prior and the likelihood to produce the posterior coverage estimate. A 2 stage sampling procedure was used to first select the village to sample, then to carry out the survey in the community. It involved calculation of a sample size of villages to be visit for the wide area survey. In the wide area survey screening of children, aged from 6 to 59 months using weight-for-height z-scores, MUAC and oedema criteria through door by door active case finding technique was employed. 4.1. Minimum sample size of villages for the wide area survey The sampling frame used in the survey consisted of the five health facilities and two Mobile team catchment area which covered by F2E project.
The calculation of minimum sample size (villages) were based on the following parameters: n=53 (SAM cases) based on the sample size generated by the Bayes calculator, an average village population of 4876, the percentage of children aged (6 to< 59) months =15%7 and a combine SAM prevalence of 3.3%8. A total of 22 villages was calculated based on equation 1 as illustrated below;
Equation 1: Calculation of villages’ number for wide area survey
푁 푁 푣𝑖푙푙푎푔푒푠 = ⌈ ⌉ % 표푓 푐ℎ𝑖푙푑푟푒푛 6 − 59 푚표푛푡ℎ푠 푃푟푒푣푒푙푎푛푐푒 퐴푣푒푟푎푔푒 푣𝑖푙푙푎푔푒 푝표푝푢푙푎푡𝑖표푛푠 × × 100 100
53 푁 푣𝑖푙푙푎푔푒푠 = ⌈ ⌉ = 22 15 3.3 487 × × 100 100
The villages were selected through systematic random sampling, since there was an updated list provided by the EPI department of BRAC office.
4.2. Wide area survey Methodology The wide area survey data collection took five days in the 22 selected villages. Exhaustive screening of children less than five years of age in all the villages was done through active case finding (door to door). There were five teams composed of one supervisor and two enumerators (one female and one male). Verification of the presence or absence of oedema, MUAC <115mm and WHZ <-3SD was done. All cases found in the survey not covered in the SAM treatment program were referred to the nearest OPD-SAM site with a referral slip. To ascertain the reasons why those children were not in the program, their caregivers were interviewed using a standard questionnaire. 4.3. Coverage estimations A total of 999 children aged below five years were screened and a total of 54 SAM children were found. 18 active SAM cases were identified in the program (which was already in the program). In addition, three cases were found to be recovering SAM cases in a program and 1 recovering case out of the program was found (see below equation 3).
6 Total number of villages in the 5 target HF catchment area was 307 villages with a total population of 149440 persons (derived from EPI micro plan). 7 Source: EPI micro plan 8 Source: Lashkar Gah district Rapid SMART survey, 2018 - SAM prevalence (combine) of 3.3% (95% CI 1.8 – 4.9) The most reliable, and widely suited, coverage estimator currently available is the single coverage estimator9 and should be used for estimating SAM treatment program coverage. The estimator estimates coverage using active SAM cases as well as recovering cases in the program and recovering cases not in the program. The following formula is used where Cin= covered SAM cases,
Cout= uncovered SAM cases, Rin = recovering cases in the program and Rout = recovering cases not in the program: Equation 2: Calculation of single coverage 퐶𝑖푛 + 푅𝑖푛 푆𝑖푛푔푙푒 푐표푣푒푟푎푔푒 = 퐶𝑖푛 + 푅𝑖푛 + 퐶표푢푡 + 푅표푢푡
The Cin, Cout and Rin are all collected during the wide-area survey however Rout must be estimated.
The number of recovering cases not in the program (Rout) is calculated using the formula below. Equation 3: Calculation of Rout cases
Cin + Cout + 1 푅표푢푡 =1 푥 (푅𝑖푛 푋 − 푅𝑖푛) 푘 Cin + 1
The results of the wide area survey and the result of the calculations for Rout are presented in Table 17.
9 For more information see Myatt, M et al, (2015) A single coverage estimator for use in SQUEAC, SLEAC, and other CMAM coverage assessments, p.81 Field Exchange 49. Table 15: Total SAM cases founded during the wide-area survey
Type of case SAM cases
Cases not in the program (Cout) 33
Cases in the program (Cin) 18
Recovering cases in the program (Rin) 3
Recovering cases not in the program (Rout) 1 Total cases 55 3.2 Results of the wide-area survey During the wide area survey a total of 55 SAM cases (including one recovering not in the programme) were identified in the 22 selected villages in Lashkar Gah district of Helmand province. The denominator for the single coverage estimate was, 55 for SAM and the numerator was 21
SAM (Cin + Rin). Using the Bayes calculator, the conjugate analysis was completed with the Prior parameters calculated for the OPD SAM program 40.3% (95% CI: 31.7% - 49.8%) with (p- value=0.6406) and (z-test=0.47). As the final sample size was greater than the suggested sample size (<53 SAM cases), means that the coverage estimate is valid and can be reported as there is no conflict between the prior and the likelihood. This coverage estimate is below the coverage standard for rural contexts (50%) for OPD SAM program.
4.4. Measurement data of wide area survey During the wide area survey 54 SAM cases were identified, out of 54 cases 59% (32 Cases) of them were malnourished by MUAC, 17% (9 Cases) By Z-Score, 22% (12 cases) by Both criteria (MUAC/Z-Score) and 2% (1 case) by Oedema. Figure 11: Measurement data analyzed by MUAC, WHZ, Both (MUAC/WHZ) and Odema
MUAC Z-Score Both Odema
2%
22%
17% 59%
4.5. Reasons for un-covered SAM cases The survey sought to get reasons why some children with SAM were not covered by the program. This was by interviewing all the caregivers of the children not covered by the program on what their reasons were for not being in the program. The most reported reason was Distance and lack of finance for the journey cost, which was common especially in the far villages. Some mothers were not able to identify if their children were malnourished. Culture barriers like mothers were not allowed to go to health facilities without mahram or refusing by their family, less awareness about the malnutrition and nutrition program, supplies and other factors shown in the figure below where the other factors while the children were not admitted into the program.
Figure 12: Reasons for un-covered SAM cases founded during the wide area survey
Reasons for uncovered cases
Too far; Walking distance(>1 hour) Lack of finance for the journey cost Refusal by husband /Family Lack of Transportation Lack of support / Mahram Too busy at home activities Don't Know about the illness of malnutrition Inaccessibility (seasonal flooding, etc.) Don't know how to get child admitted in the program Staff in health facility are rude and not welcoming No one to take care of the other children Difficulty getting to the health facility Do not believe the program will help Caregiver is sick Insecurity A family member is sick Mobile team stop work in their village Migration 0 2 4 6 8 10 12
Reasons for uncovered cases
5. Conclusions Since April 2016, ACF have been implementing integrated WASH and nutrition programs in the vicinity of Lashkar Gah city capital of Helmand province. The objective of the project is to improve the quality of care and access to health and nutrition services for the treatment of Severe Acute Malnutrition (SAM) and to improve access to water and hygiene and sanitation in the health facilities and communities. Coverage assessment was proposed in the catchment area of Mobile clinics and health facilities supported by ACF from April 2017 to 31st March 2018 under the F2E project funded by GAC, The assessment estimated overall coverage of 40.3% (95% CI: 31.7% - 49.8%) using the single coverage estimator. which was below the SPHERE10 thresholds for rural settings (>50%). Comparing the result with latest SQUEAC assessment, which was, conducted in April 2017 11in Lashkar Gah district of Helmand province, 4.7% SAM program coverage improved. Therefore indicates the need to invest in reform to improve the program coverage for the future.
10 Minimum Humanitarian Thresholds in Emergencies for IMAM programs coverage based on population settings namely Rural (>50%); Urban (>70%) and Camp (>90%) 11 Result of 2017 SQUEAC assessment 35.6% (24.0% - 49.3%). 6. Recommendation and Joint Action Plan Level Whe Responsible of Recommendation Findings Actions to be taken n to people priori do it ty Poor documentation at Health Facilities level (Incomplete Capacity building of registers and treatment follow Health Facilities staff up cards on accurate reporting Poor understanding of discharge Supportive supervision & OTJ must be ACF - BPHS and documentation. July High protocols by Health Facilities conducted regularly to all HFs. IP , DoPH
staff Discrepancy between Health Improve documentation Facilities data, Raw data from through regular cards and monthly reports. supportive supervision Reporting HF staff must identify and prepare a list and monitoring of Lack of Distance data in all BPHS & HF of villages with their distance from HF.( JULY High Health Facilities health facilities staff Hour or KM) HFs don’t have properly Groth Provide all the Urgently supply registers to relevant HFs monitoring, Screening, OPD- BPHS& ACF necessary update and OTJ must be conducting in order to July High SAM and OPD-MAM specific and DoPH
Nutrition Program Documentation and and Documentation Program Nutrition document to HFs correct fill the data. register Defaulters were more than 15% Defaulter follow up in the program Defaulters to be identified and closely HF staff & system must be July High Poor follow up system of the followed up by community community strengthened
up and up absent and defaulter cases
- Strengthen the existing Community and HF staff mast be trained referral systems trout on case finding and then closely follow up provision of adequate BPHS IP and CHWs and provide incentive per case for training to the Health Poor active case finding at all other Augus CHW. ACF and other nutrition partners High
referral system system referral Facilities staff as well as community level nutrition t should dedicate their community community based staff stakeholders promoters and community mobilizers, to Defaulter follow Defaulter (CHSs, CHWs and actively participate in this part. FHAGs) Expand the scope of referral through engaging and involving Poor passive screening and key community figures referral in referral of malnourished children Set up clear monitoring and follow up Unmarked Defaulters in Supportive supervision & OTJ must be ACF - BPHS Augus mechanisms to identify treatment cards and also absent High conducted regularly to all HFs. IP , DoPH t key challenges with visits were not marked referrals Extend community mobilization, to create Community awareness sessions mast be BPHS IP/ awareness and Using Family Food for the regularly conducted and providing Augus DoPH and High understanding about treatment of Malnutrition information about the malnutrition t ACF the program and treatment program malnutrition, Engagement of Kay community informants MUAC by Mothers and engagement of Each People don’t know MUAC and in community kay community informants in the active ACF projec High what for MUAC is used mobilization and health case finding process t
education program A Strict culture where some Community MUAC by Mothers and engagement of Each women are not allowed out of mobilization should kay community informants in the active ACF projec High the home to go to Clinics have a formalized case finding process t without Mahram Awareness planning showing preparation of health education schedule schedules and activities on monthly base and conduct nutrition of all actors involved in BPHS IP/ Poor counselling about seasons in the waiting area, during the nutrition program at DoPH and July High Malnutrition at health facilities screening, during the IMCI consultation, health facilities and ACF during vaccination, during ANC/PNC community level visits for all BNFs Nutrition education Community awareness sessions must be should be the key effort regularly conduct by Community network BPHS IP/ Community has lack of of community and radio spot messages must be DoPH and July High knowledge about malnutrition mobilization, involving a broadcasts in order to raise awareness of ACF collaborative effort the community regarding mal nutrition. between CHWs, CHSs and FHAGs Integration of nutrition activities into other Traditional Treatment for health services and Malnutrition campaigns e.g. Increase community awareness and BPHS IP/ Poor awareness and provide basic level training for DoPH and July High Nutrition program understanding of the program community key informants ACF education through Conduct training to private sector and radios or TV channels Referring to Private doctors for refer slip to be distributed and orient DoPH 2019 High Malnutrition treatment them on referral system. Long waiting time for achieving HF staff must triage patients and respect HF staff July High services at HFs working hours. Train nutrition counselors and prepare Poor counselling about BPHS IP and plans based on their TORs and act July High Malnutrition at health facilities ACF accordingly. Sometimes HF Staff don have no Ethical procedures to be undertaken and good manner with the patients behavior change sessions to be BPHS IP and July High Increase the number of and provide wrong information conducted for HF staff. Regularly ACF staff in the health for next or follow up visit conduct supportive supervision. The nutrition consolers was not facilities/Good NC must follow their activities based on Nutrition fully involve in nutrition program July High coordination between their approved ToR. Counsellors health facility staff to implementation Recruit and complete staff based on support the nutrition Workload on the health facilities activities and follow the BPHS guideline and maintain on time BPHS IP July High Staffing staffs job discretion by the supply new position nutrition No CHS in SHCs for sharing information (especially refer BHC and CHC CHSs should regularly visit consolers which made BPHS IP and follow up and defaulter tracking) the catchment area of their relevant SHC July High by PND ACF between Sub Health Centers and and supervise the HPs. communities BPHS IP and High staff turn our at HFs level motivate staff and recruiting local staff ACF July High OTJ mast be provided and build the Poor Nutrition program capacity of HFs staff in terms of proper BPHS IP and July High documentation reporting and timely supply reporting ACF formats. 7. Annexes Annex 1: Survey Implementation plan
SQUEAC
Province Name Helmand
Month / Year : March,2018
Tavel Training Stage 1 Stage 2 Prior Stage 3 Recos/Action Plan Travel Meeting Date 7-Mar 8-Mar 9-Mar 10-Mar 11-Mar 12-Mar 13-Mar 14-Mar 15-Mar 16-Mar 17-Mar 18-Mar 19-Mar 20-Mar 21-Mar 22-Mar 23-Mar 24-Mar 25-Mar 26-Mar 27-Mar 28-Mar 29-Mar 30-Mar 31-Mar 1-Apr 2-Apr 3-Apr 4-Apr
We Th Fr Sa Su Mo Tu We Th Fr Sa Su Mo Tu We Th Fr Sa Su Mo Tu We Th Fr Sa Su Mo Tu We Days
Activity 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
Travel to the province
Meeting with DoPH & BPHS IP BPHS DoPH SQUEAC and Coverage overview + getting to know the programme + BBQ (for Supervisors)
Quantitative Data Analysis (OPD-SAM & OPD-MAM)
Qualitative Research Training/Preparation for Qualitative Data Collection- Role playing(Supervisors and Enumerators)
Qualitative Data Collection and Analysis & BBQ
BBQ+Formulation of Hypothesis + planning for Stage 2 + training of (Supervisors and Enumerators
Stage 2: small area survey
Hypothesis analysis and Formulation of Prior
Preparation for Wide Area Survey (Sample, Log etc.) + training enumerators and Supervisors
Stage 3: Wide area survey
Development of Posterior
Recommandations and Action Plan
Presentation at PPHD/ Partner and others
Travel Back
0 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 0 0 0 Core team
0 0 0 0 0 10 10 10 10 10 10 10 10 10 0 10 10 10 10 10 0 0 0 Number of Extra enumerators (5F= female 5M= Male)
Office Car Office Car 1 1 1 1 1 1 5 5 5 1 1 5 5 1 1 5 5 5 5 Office Car Office Car Office Car Number of Cars Needed
C C C C C C C C F F F C C F F C C F F F F C C C Classroom ( C ) or Field ( F )
SRR SRR SRR SRR SRR SRR SRR SRR SRR SRR SRR SRR SRR SRR SRR SRR SRR SRR SRR SRR SRR SRR SRR SRR SRR Sayed Rahim RASTKAR