DOI: 10.5061/dryad.nk98sf7sw
title: Effect of specificity of health expenditure questions in the measurement of out-of-pocket health expenditure: Evidence from field experimental study in Ghana

description: Background: The effect of number of health items on OOPs has been
 identified as a source of bias in measuring OOPs. Evidence comes mostly
 from cross-sectional comparison of different survey instruments to collect
 data on OOPs. Very few studies have attempted to validate these
 questionnaires, or distinguish bias arising from the comprehensiveness of
 the OOPs list versus specificity of OOPs questions. Objectives: This study
 aims to estimate biases arising from the specificity of OOPs questions by
 comparing provider and household’s information. Methods: A generic
 questionnaire to collect data on household’s OOPs was developed following
 the nomenclature proposed in division 6 of the COICOP2018. The four
 categories within such division are used to set the comprehensiveness of
 the OOPs list, the specificity within each category was tailored to the
 design of the nationally representative living standard survey in Ghana
 where a field experiment was conducted to test the validity of different
 versions. Households were randomized to 11, 44 or 56 health items. Using
 data from provider records as the gold standard, we compared the mean
 positive OOPs, and estimated the mean ratio and variability in the ratio
 of household expenditures to provider data for the individual households
 using the Bland-Altman method of assessing agreement. Findings: We found
 evidence of a difference in the overall mean ratio in the specificity for
 OOPs in inpatient care and medications. Within each of these two
 categories, a more detailed disaggregation yielded lower OOPs estimates
 than less detailed ones. The level of agreement between household and
 provider OOPs also decreased with increasing specificity of health items.
 Conclusion: Our findings suggest that, for inpatient care and medications,
 systematically decomposing OOPs categories into finer sub-classes tend to
 produce lower OOPs estimates. Less detailed items produced more accurate
 and reliable OOPs estimates in the context of a rural setting.
description: This study uses health provider records as the ‘gold standard’ to
 compare to household reported OOPs, recognizing that the provider records
 are not a perfect gold standard in the absence of a pre-existing formal
 recording system in place. Two sets of data were collected in this study.
 The first set of data was captured from households in a cross-sectional
 field survey conducted between May 2017 and December 2017 and the second
 set of data was obtained from health provider records within the same
 period. Households were randomized to one of three
 versions of a household questionnaire on consumption expenditure for
 face-to-face interview. All three versions of the questionnaire were
 fielded during the same time period and included questions on
 out-of-pocket health spending for inpatient care services, preventive care
 services, other outpatient care services, other health services, medicines
 and health products. They however differed in the level of specificity
 within each one of these main OOPs categories. The versions were labeled;
 version-1 for the questionnaire with 11 items covering the 6 health
 categories previously mentioned version-2 and 3 for the questionnaire
 versions with a maximum of 44 and 56 items respectively. All three
 versions of the instrument used similar recall periods of 4 weeks for
 items listed under the categories medicines, other outpatient services,
 other health services; 12 months for inpatient care services and other
 health products; and 6 months for OOPs related to preventive care
 services.  We created a database of provider records to
 validate the household reported OOPs. Both private and public health care
 providers within the study area were engaged by the project team to
 extract records covering a 13 month period which in some cases (mostly for
 private providers) also required improving the recording of provider
 records.  Health expenditures reported by any member of the household were
 tracked and a corresponding health provider record obtained to create a
 matched sample for validation. A detailed description of the matching
 procedure can be seen in Supplementary material one under the section
 Matching. Matched sample in this study refers to one-on-one paired records
 households reported OOPs to heath provider recorded OOPs for the same
 reason of incurring the health cost. Unmatched households in this study
 also refers to all OOPs reported by households without pairing such
 expenditures to corresponding health provider records.  Household heads
 were the most common respondents for the household survey but in some
 cases, other individuals within the household were nominated by the
 household head to provide responses.
description: Instrument Design
 We developed new health care
 utilization and expenditure modules using WHOs 2018 revised COICOP list.
 The revised versions have 5 to 7 levels of disaggregation of health
 expenditure and offers the opportunity to further disaggregate the
 previous version into finer decomposition of health expenditures in
 surveys. We developed new 3 modules using these finer decomposed health
 items for validation. Each of these modules is characterized by a finer
 decomposition level of health expenditure list drawn from the revised
 COICOP list. ‘Version-1’ is the old Classification of the Individual
 Consumption according to Purpose (COICOP) and has been used extensively at
 different level of details in the Ghana living standards survey and in
 different countries. The new modules (Version-2 and 3)’ were derived from
 ‘Version-1’. In ‘Version-1’, health consumption is coded (06) in the
 COICOP list. Within this division, there are three major groups -
 <b>medical products, appliances and equipment</b> coded as
 061; <b>outpatient services</b> coded as 062, and
 <b>hospital services</b> coded as 063. Health expenditures
 coded as 061 and 062 are further disaggregated into 3 classes using a
 4-digit code. Health expenditure list coded 063 is not further
 disaggregated. Following the decomposition of the expenditure list,
 ‘Version-1’ has 11 health expenditure items, ‘Version-2’ has 44 health
 expenditure items and ‘Version-3’ has 66 health expenditure items. These
 new decomposed classes use 5 or 7 digits codes that are consistent with
 official COICOP codes but that have been created for this hierarchy of
 classification for the new modules in this study. The suggested additional
 sub-classes either draw on the definition of each group or class given by
 United Nations Statistics Division (UNSTAT) or on the 2011 System of
 Health Accounts framework. For the disaggregation of medical products and
 medicaments in particular, other sources such as the Standard
 International Trade classification as well as the WHO essential medicine
 list were also considered. These new modules in incorporated into the
 GLSS6 survey tool to create a new section on health care utilization and
 expenditure. All other sections on the GLSS6 tool remain unchanged. The
 recall period for the health expenditure items remained the same for the 3
 new models.