APPLICATION OF LOT QUALITY
ASSURANCE SAMPLING FOR
ASSESSING DISEASE CONTROL
PROGRAMMES - EXAMINATION OF
SOME METHODOLOGICAL ISSUES
T. R. RAMESH RAO
Department of Mathematics, B. S. Abdur Rahman University, Chennai 600 048, Tamil Nadu, India
Abstract :
Lot Quality Assurance Sampling (LQAS), a statistical tool in industrial setup, has been in use since 1980 for monitoring and evaluation of programs on disease control / immunization status among children / health workers performance in health system. While conducting LQAS in the field, there are occasions, even after due care of design, there are practical and methodological issues to be addressed before it is recommended for implementation and intervention. LQAS is applied under the assumption that the items produced in the industry are homogeneous in nature and randomly distributed. In the health field, the assumption of randomness on occurrence of cases (disease condition), unimmunized children (defectives) etc., may not follow strictly random (parametric) distribution. Besides, there are several important practical statistical issues, seem to be simple, yet complex, need to be addressed and examined while applying LQAS for assessing various health programmes.
This paper is an attempt in that direction to address some of the practical and methodological issues to be addressed before it could be generalized and recommended for use by the public health administrators. Key words: Lot Quality Assurance Sampling, Monitoring and Evaluation Disease Control Programmes, Binomial, Poisson, Hyper geometric Distributions.
1. Introduction
There is a need for a systematic and standardized approach for monitoring and evaluating decease control programmes under National Health Policy in developing countries, including India. Further, areas (states, provinces, regions/zones, districts) with high decease prevalence need to be identified and targeted for necessary strengthening of the program. Decease conditions such as leprosy, Polio, are at the elimination stage. i.e., the prevalence of such decease is very low, may be at the level of 1 per 10,000. Guinea worm and tuberculosis are some of the diseases that have been targeted for eradication or elimination. To monitor such decease control programmes, the available procedures for assessment to date are conventional sampling survey methods. The conventional sample survey methods to monitor the above decease control programmes are expensive, time consuming and need a great deal of resources. In addition, there may be non-sampling errors. The health administrators/ policy makers are interested to have quick results with limited resources. Therefore, there is a need for rapid assessment procedures, for future planning, in identifying disaggregated areas, such as states / provinces / regions / zones / districts with high disease prevalence and also understand its trends while monitoring decease control programmes. In this context, Lot Quality Assurance Sampling (LQAS) technique which has been tried successfully for monitoring and evaluating immunization programmes, leprosy, tuberculosis, sleeping sickness etc., control programmes, can be explored. LQAS assures that the accepted lots meet quality control standards in the lots and the accepted lots contain relatively less number of defectives.
In the health field a lot may be a cluster of villages such as a taluk (mandal), a block, a group of districts, representing a zone, a region as a part of the state/whole state for health care delivery area.
determined statistically to ensure high probability of accepting the lot. The manufacturer of an industry does not want to produce a lot with more than a predetermined percentage of defectives. Similarly, a health administrator does not want to conclude that a community has acceptably low disease prevalence (when the disease prevalence is actually high) above which the community should be targeted for intervention.
A simple random sample of items is taken from each lot for inspection to identify the number of defectives, if any. If the number of defectives in the selected items is less than or equal to a specified or pre-assigned critical (acceptable) number or a critical value (d) then the lot is accepted. On the other hand, if the number of defectives is more than the critical value (d) even before the completion of examination of all the sample items, the lot is rejected and further inspection of sample items becomes redundant.
2. Literature search
Interest in applying LQAS to health assessments has been growing and gaining popularity since the mid-1980s. In September 2006, the World Health Organization (WHO) and the World Bank undertook a global review of the use of LQAS methodology and found more than 800 applications worldwide, thus providing an ample view on the current status of LQAS.
In Bangladesh, ICCDR/B explored the validity of this methodology by carrying out a survey using LQAS in the Matlab catchment area (2007) and found no difference between the LQAS survey information and that obtained through ICCDR/B’s census-based system. The ICCDR/B concluded that the LQAS method “… for many practical purposes, [with] a sample size of 19 should serve the purpose for programme managers.” This result is particularly important since it is the first time that LQAS has been compared with a census and therefore establishes the validity of the results.
With respect to LQAS costs, the most comprehensive study was carried out by Christophe Grundmann in 2002 under a contract financed by USAID. His work compared a cluster sample with multiple LQAS applications. His first conclusion was that LQAS costs should not be compared with other surveys without first emphasizing that LQAS results also support program management. Therefore, while the costs of other surveys typically are for M&E only, LQAS has a management function, so some of its costs should not be attributed to M&E but instead should be attributed to program management.
Grundmann (2002) also showed that once LQAS is used recurrently, economies of scale begin to take hold and the costs decrease considerably. It is reported that classic LQAS is well proven and recommended as an effective, feasible, and affordable approach to data collection that can provide very useful information to both USAID Missions and other engaged agencies.
Megan Deitchler et al (2007) in their article on ‘A field test of three LQAS designs to assess the prevalence of malnutrition’ reported that three Lot Quality Assurance Sampling (LQAS) designs (33 X 6, 67 X 3 and Sequential design) were developed to provide alternatives to implementing the 30 by 30 cluster- survey for assessment of acute malnutrition in emergency settings.
3. Discussion
The number of health care parameters assessed in the surveys varied and some surveys assessed more than one health parameter. 320 surveys dealt with risk factors for HIV/AIDS, 268 surveys assessed immunization coverage, 224 surveys examined women's health issues such as family planning and antenatal care, 136 surveys assessed ORT use, 26 surveys assessed disease burden, 5 surveys evaluated health worker performance and 13 surveys used to assess decease control programmes.
3.1 Application of LQAS method to measure immunization coverage
All the 268 surveys examined / assessed immunization coverage, as the variable of interest for children in the age group 12-23 months. The variable of interest follows binomial distribution. However, the authors did not examine whether the variable follows binomial distribution. None of the studies has addressed methodological issues as well as practical considerations of LQAS before it was used for assessment in the field.
3.2 Application of LQAS for women's health services assessments
The review included receipt of tetanus toxoid, prenatal vitamin A supplementation, breastfeeding of their infants, and knowledge of safe motherhood as variables of interest in their studies. These variables basically followed binomial distribution. However, none of the authors have examined whether the variable follows binomial distribution. They have also not examined other practical considerations for its application in the field. 3.3 Application of LQAS method for ORT assessments
The review for ORT assessments included, “the amount of liquids administered to the children having diarrhea, the knowledge and use of ORT as the parameters of interest. However, the authors did not examine whether the variable follows binomial distribution. The authors have not addressed other practical considerations before the application of LQAS in the field.
3.4 Application of LQAS method for HIV/AIDS
Several studies on this topic done mostly in Africa included sexual behaviour and risk factors for HIV and for other sexually transmitted infections. One LQAS survey assessed performance of nurse midwives in providing education to patients about sexually transmitted infections. All the above variables except the last one follow binomial distribution. The authors did not mention about methodological issues for the application of LQAS in the field. Though the last variable follows hepergeometric distribution, the authors have not examined its goodness of fit. Further, the authors did not discuss other practical considerations for its application in the field.
3.5 Application of LQAS method for disease surveillance
The authors employed level of tetanus toxoid coverage of women, neonatal tetanus mortality rates, prevalence of diarrheal diseases, and responsible children to a chloroquine treatment for prevention of malaria as variables of assessment. Though, some variables follow Poisson distribution the authors, never considered the original distribution for selecting necessary sampling plan for the application of LQAS in the field. In all the surveys the authors never addressed methodological issues and other practical considerations for its application in the field. 3.6 Application of LQAS method for health worker supervision
The authors used health worker performance related to nutrition programs, injection safety techniques and use of ORT as the variables of interest for assessment. In these surveys the target population is very limited and therefore, the authors need to examine whether the variable of interest follows hepergeometric distribution through goodness of fit. The authors have not addressed other practical considerations for its application in the field.
3.7 Application of LQAS method for nutrition programmes
3.8 Application of LQAS method for Leprosy elimination programmes
The authors employed prevalence of leprosy as the variable of interest for monitoring the Leprosy elimination program. The authors rightly examined the goodness-of-fit of the Poisson distribution to the variable of interest. Thus, they examined the randomness of leprosy cases. Besides, they employed two-stage cluster sampling procedure rather than conventional single sampling plan to assess the disease control programs. The authors, accordingly, modified the sample size needed for the survey. They also discussed some practical issues regarding suitability of LQAS for monitoring leprosy elimination programmes.
4. Conclusion
In almost all the LQAS surveys done so far, there was no discussion on methodological and practical considerations in the application of LQAS for monitoring disease control programmes. However, in some LQAS surveys, critical factors such as geographical distribution of cases and adoption of cluster sampling design instead of simple random sampling design before applying LQAS were considered and recommended for monitoring leprosy elimination programme in India.
Hence, there is a need to address certain methodological and practical issues before recommending Lot Quality Assurance Sampling for its application in assessing programmes on disease control / immunization status in children / health workers performance in organization.
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