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The effect of clustering on lot quality assurance sampling: a probabilistic model to calculate sample sizes for quality assessments.

ABSTRACT:

Background

Traditional Lot Quality Assurance Sampling (LQAS) designs assume observations are collected using simple random sampling. Alternatively, randomly sampling clusters of observations and then individuals within clusters reduces costs but decreases the precision of the classifications. In this paper, we develop a general framework for designing the cluster(C)-LQAS system and illustrate the method with the design of data quality assessments for the community health worker program in Rwanda.

Results

To determine sample size and decision rules for C-LQAS, we use the beta-binomial distribution to account for inflated risk of errors introduced by sampling clusters at the first stage. We present general theory and code for sample size calculations.The C-LQAS sample sizes provided in this paper constrain misclassification risks below user-specified limits. Multiple C-LQAS systems meet the specified risk requirements, but numerous considerations, including per-cluster versus per-individual sampling costs, help identify optimal systems for distinct applications.

Conclusions

We show the utility of C-LQAS for data quality assessments, but the method generalizes to numerous applications. This paper provides the necessary technical detail and supplemental code to support the design of C-LQAS for specific programs.

SUBMITTER: Hedt-Gauthier BL

PROVIDER: S-EPMC3819670 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

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The effect of clustering on lot quality assurance sampling: a probabilistic model to calculate sample sizes for quality assessments.

Hedt-Gauthier Bethany L BL Mitsunaga Tisha T Hund Lauren L Olives Casey C Pagano Marcello M

Emerging themes in epidemiology 20131026 1

<h4>Background</h4>Traditional Lot Quality Assurance Sampling (LQAS) designs assume observations are collected using simple random sampling. Alternatively, randomly sampling clusters of observations and then individuals within clusters reduces costs but decreases the precision of the classifications. In this paper, we develop a general framework for designing the cluster(C)-LQAS system and illustrate the method with the design of data quality assessments for the community health worker program i ...[more]

PMID: 24160725

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Project description:BACKGROUND:Cardiovascular diseases (CVDs) are the leading cause of mortality in India. India has rolled out Comprehensive Primary Health Care (CPHC) reforms including population based screening for hypertension and diabetes, facilitated by frontline health workers. Our study assessed blood pressure and blood sugar coverage achieved by frontline workers using Lot Quality Assurance Sampling (LQAS). METHODS:LQAS Supervision Areas were defined as catchments covered by frontline workers in primary health centres in two districts each of Uttar Pradesh and Delhi. In each Area, 19 households for each of four sampling universes (males, females, Above Poverty Line (APL) and Below Poverty Line (BPL)) were visited using probability proportional to size sampling. Following written informed consent procedures, a short questionnaire was administered to individuals aged 30 or older using tablets related to screening for diabetes and hypertension. Using the LQAS hand tally method, coverage across Supervision Areas was determined. RESULTS:A sample of 2052 individuals was surveyed, median ages ranging from 42 to 45?years. Caste affiliation, education levels, and occupation varied by location; the sample was largely married and Hindu. Awareness of and interaction with frontline health workers was reported in Uttar Pradesh and mixed in Delhi. Greater coverage of CVD risk factor screening (especially blood pressure) was seen among females, as compared to males. No clear pattern of inequality was seen by poverty status; some SAs did not have adequate BPL samples. Overall, blood pressure and blood sugar screening coverage by frontline health workers fell short of targeted coverage levels at the aggregate level, but in all sites, at least one area was crossing this threshold level. CONCLUSION:CVD screening coverage levels at this early stage are low. More emphasis may be needed on reaching males. Sex and poverty related inequalities must be addressed by more closely studying the local context and models of service delivery where the threshold of screening is being met. LQAS is a pragmatic method for measuring program inequalities, in resource-constrained settings, although possibly not for spatially segregated population sub-groups.

Project description:BackgroundThe Better Health Outcomes through Mentoring and Assessment (BHOMA) project is a cluster randomized controlled trial aimed at reducing age-standardized mortality rates in three rural districts through involvement of Community Health Workers (CHWs), Traditional Birth Attendants (TBAs), and Neighborhood Health Committees (NHCs). CHWs conduct quarterly surveys on all households using a questionnaire that captures key health events occurring within their catchment population. In order to validate contact with households, we utilize the Lot Quality Assurance Sampling (LQAS) methodology. In this study, we report experiences of applying the LQAS approach to monitor performance of CHWs in Luangwa District.MethodsBetween April 2011 and December 2013, seven health facilities in Luangwa district were enrolled into the BHOMA project. The health facility catchment areas were divided into 33 geographic zones. Quality assurance was performed each quarter by randomly selecting zones representing about 90% of enrolled catchment areas from which 19 households per zone where also randomly identified. The surveys were conducted by CHW supervisors who had been trained on using the LQAS questionnaire. Information collected included household identity number (ID), whether the CHW visited the household, duration of the most recent visit, and what health information was discussed during the CHW visit. The threshold for success was set at 75% household outreach by CHWs in each zone.ResultsThere are 4,616 total households in the 33 zones. This yielded a target of 32,212 household visits by community health workers during the 7 survey rounds. Based on the set cutoff point for passing the surveys (at least 75% households confirmed as visited), only one team of CHWs at Luangwa high school failed to reach the target during round 1 of the surveys; all the teams otherwise registered successful visits in all the surveys.ConclusionsWe have employed the LQAS methodology for assurance that quarterly surveys were successfully done. This methodology proved helpful in identifying poorly performing CHWs and could be useful for evaluating CHW performance in other areas.Trial registrationIdentifier: NCT01942278 . Date of Registration: September 2013.

Dataset Information

The effect of clustering on lot quality assurance sampling: a probabilistic model to calculate sample sizes for quality assessments.

Background

Results

Conclusions

Publications

The effect of clustering on lot quality assurance sampling: a probabilistic model to calculate sample sizes for quality assessments.

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