Willingness to join community based health insurance among households in South Wollo, Northeast Ethiopia: A community-based cross-sectional study.

BACKGROUND: Poor health care financing remains a major challenge to health service utilization among the lower socioeconomic society. Consequently, countries have designed different health insurance programs to overcome financial barriers against health services utilization. Similarly, Ethiopia has been implementing community-based health insurance programs since 2011 to improve health care financing system. However, only a small number of people are enrolled which might be attributed to lack of willingness towards the program and the reasons for this remained under reported. This study was intended to examine willingness to join the community-based health insurance program and its associated factors in South Wollo, Northeast Ethiopia.
METHOD: A community-based cross-sectional study was conducted among 421 households. A multistage systematic random sampling technique was employed to recruit the study households. Data were entered into EpiData version 3.1 and was exported into SPSS version 24.0 for analysis. Bivariable and multivariable logistic regression analysis with a backward elimination method was performed to identify the determinants of willingness to join community-based health insurance. Finally, a statistically significant level was declared at a p-value of less than 0.05.
RESULTS: Two hundred and ninety-three [73.6% (95%CI:68.8%-77.9%)] households were willing to join community-based health insurance programs. Being male headed household (AOR:0.2, 95%CI: 0.07-0.58), being a member of Idir (AOR:0.46, 95%CI: 0.25-.84), absence of chronic illness in the household (AOR: 0.31, 95%CI: 0.13-0.77), and family size < 4 (AOR: 0.18, 95% CI:0.08-0.41) were barriers to join community-based health insurance program whereas rural residency (AOR:1.9, 95% CI: 1.09-3.32), perceived quality health services (AOR:2.96, 95%CI:1.4-6.24), and having positive attitude (AOR:4.1, 95%CI:2.32-7.22) and good knowledge to programs (AOR:2.62, 95%CI:1.43-4.8) were enabling factors.
CONCLUSION: Nearly three-fourths of the households were willing to join community-based health insurance programs. However, different household and health service-related factors affected their willingness. The ministry of health with the regional and woreda health offices should work towards improving the quality of health services, conduct program advocacy and community sensitization towards the program, and build trust with the community.

Introduction

Globally, the costs of health care are increasing which causes many people to fall into poverty. The out-of-pocket health care expenditures resulted in massive financial barriers to health care utilization among the lower socioeconomic society [1,2]. Every year, nearly 150 million people globally experience financial catastrophe due to out-of pocket health care expenditures. Evidence had suggested that households spend more than 40% of their income on health care services. The catastrophic nature of health care expenditure is disproportionately very high among the rural households in low-income countries where 80% of the health care service is dependent upon out-of-pocket charges. These high health care expenditures cause short-term health shock and can lead to debt and asset sales which intern brings people into deep poverty [3-6].

The world health organization (WHO) recommends different health care financing strategies to reduce the catastrophic nature of out-of-pocket health care expenditures. Subsequently, countries are designing and implementing different health insurance programs. These include community-based health insurance (CBHI), social health insurance (SHI), and private insurance schemes. These health insurance schemes were aimed to provide financial protection against the cost of illness and increase health service utilization. Studies suggested that insured people were more likely to visit health care institutions than uninsured people when they get sick. This suggested that health insurance programs could help in expanding health service utilization and thereby it could help in achieving universal health coverage [7-10].

Universal health coverage (UHC) is a situation in which all individuals and communities receive health services they need without suffering financial hardship [11,12]. High and middle-income countries have achieved UHC through the implementation of health insurance programs [13]. Similarly, developing countries like Ghana, Rwanda, and Nigeria have achieved rapid utilization of UHC through the national health insurance program [14-16]. However, the UHC strategy confronts the challenges of health care financing in developing countries [13-17]. More than half of the African countries are still relying on out-of-pocket health care services. This out of pocket health care expenditure affect health service utilization among the poor rural communities in low income countries which in turn affects the plan of achieving universal health coverage [18-20].

Ethiopia has planned to achieve universal health coverage by 2035 [21]. However, the health service utilization in the country remained low (34.3%) compared to most of the African countries [12]. Studies showed that poor health care financing is a major contributor for the low health service utilization in the country. Consequently, Ethiopia has designed two policy options; community-based health insurance and social health insurance schemes to improve the health care financing system. Community-based health insurance is a voluntary health insurance program designed to improve financial access to health care services for the informal sectors of rural communities. Whereas, social health insurance is a form of mandatory health insurance to the formal sector employees [22,23].

Although the social health insurance proclamation was ratified in 2010, it is not yet implemented in Ethiopia. However, the country has been implementing community-based health insurance programs since 2011. The objectives of launching CBHI were to improve financial access to health care services; increase resource mobilization; and improve the quality of health care services [22,24]. A national pilot study on the effectiveness of CBHI schemes in Ethiopia showed that CBHI members were using health services 26% more than non-members. Additionally, there was a significant difference in the rate of healthcare utilization between insured (50.5%) and uninsured (29.3%) households [10]. This suggested that scaling up community-based health insurance program in the country could help in expanding health service utilization [25].

The health care system in Ethiopia is guided by a 20-year health sector development strategy which is implemented through a series of five-year health sector development programs. Currently, the country is implementing the fourth health sector development plan which has introduced a three-tier health care delivery system. The primary level consists of health posts (1/5,000), health centers (1/25,000), and primary hospitals (1/100,000). Secondary level services are provided by general hospitals (1/1million) and tertiary services by specialized hospitals (1/5million). These three levels of health care systems are integrated through the referral system and provide service for CBHI members. The communities could get their CBHI membership through the health development army and health extension workers at the nearest health center or hospital [26-28].

The community-based health insurance program is organized at the kebele, woreda, regional, and national levels. The woreda administrator is responsible for `Signing agreements with health care provider’s/health facilities; `Reimbursing health care providers; Administering the fund (keeping financial records; preparing financial statements); Managing the database (which contains data on members, contributions, and utilization). A General Assembly and Board of Directors oversee the governance of CBHI schemes at the woreda level. At the kebele level, the executive body is responsible for registering members, collecting premiums, and channeling funds to each woreda scheme. The communities are directly linked to the program via the leaders of the health development army and the health extension workers [28,29].

The community-based health insurance benefit package includes outpatient and inpatient services, laboratory services, imaging services, supply of drugs, and related services with the exception of eyeglasses, dental implant, dialysis, higher specialized procedures, and aesthetic procedures. All governmental health centers that are situated in the woreda and fulfill the minimum standard of service delivery are contracted to provide services to the members. All pilot woreda has also signed service contracts with their region’s respective referral hospitals. Three regions (Amhara, Oromia, and Tigray) entered contracts to ensure the possibility of interregional referrals [28].

Ethiopia has planned to enroll eighty percent of the households under the CHBI program by the end of 2020. However, only 48% of households are utilizing the program with a higher rate of dropout. As a result, the community-based health insurance utilization in the country had remained one of the lowest in Sub-Sahara African countries. Several factors were responsible for the low achievements of community-based health insurance programs in the country. These factors include educational status, residence, family size of the household, membership in other social supporting systems like Idir, and quality of health service in the catchment area [30,31].

Household willingness is an important determinant for the successful implementation of the CBHI program in the country. However, only a small number (12.8%) of the households were willing to join the program in Ethiopia [32]. Additionally, 36% of the participants who were a member of CBHI are not willing to renew their membership for the next period [29]. This low level of willingness could result in low CBHI utilization and a high dropout rate and which in turn affect the 2035 country plan of achieving universal health coverage [21]. Besides, there was regional variation among studies regarding willingness to join the program and associated factors [33-41]. This study was intended to examine willingness towards the community-based health insurance and associated factors in south wollo zone northeast Ethiopia.

Methods and materials

Study area, design, and period

The Community-Based cross-sectional study was conducted in rural households of WerebBabu district, South Wollo Zone, Northeast Ethiopia from June to July 2020. South Wollo is one of the 12 zones in the Amhara region with 22 districts which is located 401 km northeast of Addis Ababa, the capital city of Ethiopia, and 480 km to the East of Bahirdar, the capital city of the Amhara region. Based on the population projection of the 2007 national census conducted by the Central Statistical Agency of Ethiopia (CSA), South Wollo has a total population of more than 3 million with an area of 17,067.45 square kilometers. South Wollo has a total of 598,447 households resulting in an average of 4.2 persons to a household [42]. In this study, household heads in 8 kebeles were included, however, household heads residing less than six months in the kebele, critically ill or mentally incapable household heads with no other household members greater than 18 years were excluded (Fig 1).

Fig 1

Map of WerebBabu District, South Wollo Zone, Northeast Ethiopia, July 2020 taken from the Woreda administrative office.

Sample size determination

The sample size was determined using a single population proportion formula by considering the 95% confidence interval, margin of error 5% (d = 0.05), proportion (P) = 79% taken from the previous study [31], and 1.5 design effect. The maximum sample size was considered after checking various parameters of measurements from the prevalence and associated factors. Then, the researcher added 10% to compensate for the non-responses and the final sample size for the study was 421.

Where: n = required sample size, Zα/2 = critical value for normal distribution at 95% confidence level (1.96), p = proportion of CBHI among households, d = 0.05 (5% margin of error), and DEFF = design effect to compensate loss of efficient of sample power.

Sampling technique

WerebBabu district was selected purposely from the 22 districts found in South Wollo Zone, Amhara regional state. There are 20 kebeles [i.e. lower administrative unit in Ethiopia] in the district. A two-stage sampling technique was used to obtain the study participants. The first 8 kebeles were selected by using the lottery method from 20 kebeles found in the district. Then the study households were selected by systematic random sampling methods from 8 kebeles. The interval was calculated by dividing the total households found in 8 kebeles by the total sample size (i.e. 2842 households divided by 421, which is 7). After obtaining the interval (7), we have selected the index household leveled 5 by lottery method from the 7 households. Then, the study households in 8 kebeles were selected beginning from the indexed household (leveled 5) by systematic random sampling technique in every 7th interval till the required sample was reached.

Data collection tool and procedures

This questionnaire was adapted from different studies conducted in developing countries [40,43,44] and then modified into contexts. The tool consists of; questions to assess sociodemographic status, questions to assess knowledge of the participants, questions to assess attitude of the participant towards the program, and questions to assess willingness towards the community-based health insurance program. The tool was first prepared in English and was translated to Amharic and then back to English to examine its consistency. Finally, the Amharic version questionnaire was used for data collection.

A total of 38 questions were used to assess knowledge towards community-based health insurance programs. Each question was awarded a score of 1 if it was answered correctly and 0 if not answered. Then the total correct responses of each question were summed to yield the knowledge level of the participants. Participants who scored above 50% for the knowledge questions (19 out of 38) were considered to have good knowledge of the scheme whereas respondents who scored below this cut of point were considered to have poor knowledge.

A 10 items of 5 points Likert scale questionnaire were used to assess the attitude of the study participants towards community-based health insurance programs. This was used to represent attitudes to a topic scored on a 5-point scale, i.e. 1 (Strongly Disagree), 2 (Disagree), 3 (Neutral), 4 (Agree) to 5 (Strongly Agree). Participants who scored above the mean were considered to have a positive attitude and those who scored below the mean were considered to have a negative attitude.

Data were collected through face-to-face interviews with the household representatives in each selected household. A total of 8 data collectors with BSc degrees and 4 supervisors with master’s degrees were involved in the data collection process. Before the data collection period, 5 days of training were given to the data collectors and supervisors. The data collection process was supervised by principal investigators and supervisors. A week before the actual data collection period a pretest was done on 5% of the total sample size in Dessie Zuriya district.

Data quality assurance

In this study, a validated tool was used that was adapted from different studies conducted in developing countries including Ethiopia and we modified the tool into context to apply for our study. Pre-testing of the tool was done on 5% of the sample and some amendments were done based on the findings of the pretest. Besides, training was given for data collectors and supervisors regarding the data collection process. Strict supervision on the data collection procedure was held by the principal investigator and supervisors.

The completeness of the data was checked on a daily basis by the supervisors and principal investigators. Data were entered using EpiData version 3.1 data manager and it was checked for completeness, errors, missing values, and then it was exported into SPSS for analysis. The binary logistic regression model was applied to measure the associations of explanatory variables with the outcome variable because the outcome variable in the study is binary and categorical type. Before doing the analysis, the model fitness was checked using the Hosmer-Lemeshow model fit-ness test. Furthermore, the presence of correlation was checked but no collinearity was found.

Ethics approval and consent to participate

Ethical clearance and approval were obtained from Wollo University. An official letter of cooperation was written to the South Wollo Zone administration and WerebBabu district. Verbal consent was obtained from the study participants after a clear and detailed explanation of the purpose, risks, and benefits of the study.

Data processing and statistical analysis

The data was entered using EpiData version 3.1 and was exported into SPSS 24.0 for analysis. A bivariate logistic regression analysis was done to assess the association between the dependent variable with each independent variable. The sociodemographic and socio-economic-related factors, knowledge, and attitude-related factors were the independent variables included in the bivariate analysis. Independent variables with a p-value less than 0.2 in the bivariate analysis, clinical importance, and absence of multi-collinearity were considered while we select the eligible variables for the final model. Multivariable logistic regression analysis was done to control potential confounders and to identify the factors associated with the outcome variable. Finally, a statistical significance level was declared at a p-value of less than 0.05.

Study variables

Dependent variable

Willingness to join community-based health insurance (no = 0, yes = 1)

Independent variables

Socio-demographic variables: Age, sex, educational status, family size, Household having children, household having a person above 65 years old age. Knowledge (good = greater than mean, poor = less than the mean); attitude (positive = greater than mean, negative = less than mean). Health-related characteristics: Presence of chronic illness, presence of disability, health institution preference, seeking medical treatment, illness in the past three months. Health institution characteristics (health institutions they are served in currently): distance from the household, quality of services, availability of drugs and supplies.

Results

Socio-demographic profile of the study participants

A total of 398 households were included with a response rate of 94.5 percent. The mean age of the participants was 41.85(±3.47 SD) years whereas the minimum and the maximum age of the participants were 25 and 63 years respectively. The majority of the participants (83.4%) were male household heads. Regarding their marital and educational status, 87.4% were married and 50% were illiterates (

Knowledge toward community-based health insurance

Two hundred and ninety-four (73.1%) participants had good knowledge towards community-based health insurance schemes. Out of these 256 (64.3%) of the participants describe community health insurance programs, 332(83.4%) explain the advantage of community-based health insurance and 324 (81.4%) of the respondents know the health care services under the community-based health insurance program.

Attitude towards community-based health insurance

The mean attitude of the respondent was 29.7 (±3.7SD) with the minimum and maximum scores of 13 and 37 respectively. The study revealed that 273 (68.6%) of the respondents had a positive attitude towards the community-based health insurance program.

Willingness to join community-based health insurance

Majority of the households 293 (73.6%) were willing to join community-based health insurance programs. The main reasons for lack of willingness towards the program were lack of interest 19 (18.1%), lack of trust 23 (21.9%), having other means of health care 34 (32.4%), the belief of not getting sick after paying 13 (12.4%), and due to the belief that community-based health insurance causes financial constraints 16 (15.2%).

Factors associated with willingness to join CBHI program

Male-headed households were 80% [AOR: 0.2, 95%CI:0.07, 0.58] less likely to join community-based health insurance programs. Similarly, participants with a positive attitude towards the CBHI scheme were 4.1 [AOR: 4.1, 95%CI:2.32, 7.22] times more likely to join the insurance program and respondents with good knowledge of the scheme were 2.6 [AOR: 2.62, 95%CI:1.43, 4.8] times more likely to join the program. Household heads with a family size of less than 4 were 82% [AOR: 0.18, 95%CI:0.08, 0.41] less likely to join the community-based health insurance scheme and respondents who are members of Idir were 54% [AOR: 0.46, 95%CI:0.25, 0.84] less likely to participate in the program. Households who have no chronic illness in their families were 69%(OR:0.31, 95%CI:0.13,0.77) less likely to join the program. Rural households were almost 2 times (OR:1.9, 95%CI:1.09–3.32) more likely to join CBHI program compared to the urban households (

Discussion

Community-based health insurance program was designed as a means of financial protection against the cost of health care utilization chiefly among the lower socioeconomic societies. However, studies have suggested that small segments of the population are utilizing the program particularly in developing countries like Ethiopia. Additionally, the community’s willingness towards the program is low in Ethiopia compared to most of the African countries and there have been dissimilarity among studies in the country regarding willingness toward the program and associated factors.

This study showed that 73.6% [95%CI:68.8%-77.9%] of the households were willing to join community-based health insurance schemes. The finding was similar to a study in Ethiopia (73%) [45], study in Saudi Arabia (69.6%) [46], and another study in Taiwan (69.5%) [47]. The possible reason might be due to the similarity in the study design or it might be due to similarity in the source populations where both of the studies involve rural households. These low level of community willingness could affect the 2030 plan of achieving universal health coverage.

However, the finding is higher than a study in Malaysia (63.1%) [48], another study in Malaysia (61.1%) [19], and a study in Nigeria (40%) [49]. The possible reason for the discrepancy could be due to the difference in the source populations. The low socioeconomic status of the population in Ethiopia might increase willingness to join community-based health insurance program compared to those higher socioeconomic populations in Malaysia and Nigeria. Besides, differences in sociocultural practice between countries may also explained the discrepancy of the findings.

On the other hand, the finding is lower than studies conducted in Southwest Ethiopia (78%) [44], Northern Ethiopia (79%) [50], northwest Ethiopia, east Gojjam (81.5%) [51], northwest Ethiopia, Fogera district (80%) [39], Nigeria (98%) [14], western Nigeria (82.45%) [52], and urban Bangladesh (86.7%) [53]. This could be due to the differences in program advocacy or community sensitization towards the community-based health insurance scheme among the study participants or the reason might be due to variation in socioeconomic or sociodemographic characteristics of the study participants.

This study revealed that respondents with good knowledge of CBHI were 2.6 times more likely to join the scheme compared to their counterparts. The finding is similar to a study in Siraro District, Ethiopia [45]. The reason could be knowledge on community-based health insurance gives an understanding about the services under community-based health insurance which enables people to join the insurance program. Similarly, participants having a good attitude on CBHI were 4 times more likely to join the program. This finding is similar to a study in Siraro District, Ethiopia [45]. This could be due to the fact that having a positive attitude toward the community-based health insurance program might increase their willingness to join the program.

Respondents who were a member of Idir were 54% less likely to join a community-based health insurance scheme compared to those who were not a member of Idir. This finding was supported by a study in Siraro District, Ethiopia [45]. The reason could be people having other means of social supporting systems like Idir might not need to join the community-based health insurance scheme due to the belief that they might get help from the social supporting systems during illness.

Male-headed households were 80% less likely to join CBHI compared to female-headed households. The finding is similar to the studies conducted in Ethiopia [51], Kenya [54], and Nepal [55]. This could be male household heads might not face financial constrains compared to the female headed households that could restrain from joining and utilizing the program. Respondents having a small family size (<4) were 82% less likely to join the program. The finding is similar to the studies conducted in Northwest Ethiopia [56] and Southern Ethiopia [32]. This might be justified by people with small family size might have financial potential to cover their health care services using out-of-pocket payments. In addition, households with small family size are less likely to pay health care expenditure compared to households with large family size. Thus, they are less likely to join community-based health insurance program.

In the current finding, rural households were 2 times more likely to join a community-based health insurance program compared to urban households. The finding was inconsistent with the study in Kenya where the urban communities were more likely to join the health insurance program compared to the rural communities [54]. This could be due to the wrong of the urban residencies in Ethiopia about health care services in the community-based health insurance programs. Furthermore, the urban community have been relied on private health facilities where CBHI does not refund their costs after they took the treatments.

Households with no chronic illness among family members were 69% less likely to join CBHI program compared to households with chronic illnesses. The finding is similar to studies conducted in Northwest Ethiopia [56], Southern Ethiopia [32], and Malaysia [48]. The possible reason could be people with no chronic illness in their household might not need frequent health care services and hence paying for the community-based health insurance program is considered as a wastage of resources and might not need to join the program.

Households who perceived good health care services in community-based health insurance were almost 3 times more likely to join community-based health insurance compared to their counterparts. The finding was similar to the studies conducted in Northeast Ethiopia [56] and Saudi Arabia [46]. This could be due to the fact that good quality health services satisfy the community and increase their willingness to participate in the community-based health insurance program.

Implication of the study to the households, health system, and policy

In this study, three-fourths (73.6%) of the households are willing to join CBHI program. This level of willingness might affect the 2020 country plan of achieving 80% of enrollment and the 2035 plan of achieving universal health coverage in the country. The study revealed that the community might have concerns about the program like the quality of health services and lack of trust. Therefore, the government should build trust among the community, increase the quality of health services, and address other household and healthcare-related factors to scale up the program.

Limitation of the study

Although the authors had tried to maintain the quality of the study, our finding is not without limitations. The major limitation of the study was the cross-sectional nature of the study which is weak to explore determinants of willingness towards community-based health insurance programs. The other limitation of the study might be social desirability bias as data collectors were health care professionals they might affect the study.

Conclusion

Nearly three fourth of the participants were willing to join a community-based health insurance program. Several household and health service-related factors affected the community’s willingness toward the program. The government the regional and local health offices should improve the quality of health services, perform program advocacy (improve knowledge and attitude), and build trust among the community to scale up the program.

Areas to be explored in the future

The major research areas we recommend for future researchers are; first community willingness with a pure qualitative studies are recommended to explore the deep-rooted barriers for the community to join community based health insurance program. Second, the quality of health care services under community-based health insurance programs should be assessed as well as regular monitoring and evaluation should be done. Thirdly, community awareness creation and community sensitization should be done to improve community willingness toward the program. Additionally, a comparative study on the health service utilization among community-based health insurance members and nonmembers should be conducted.

(SAV)

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26 Jan 2021

PONE-D-20-29657

Willingness to Join Community Based Health Insurance among Households in Worebabo District, South Wollo Zone, Northeast Ethiopia

PLOS ONE

Dear Gebeyaw Bisat

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

General comments: The paper addresses important areas of health system to contribute to sustainable health service delivery.

Introduction : The introduction lacks detail review of literature and policy context of the study country.

Methods: the sample size calculation assumes high rate of enrollment while the result was low which indicates poor review of evidences including the use of estimate from policy document, not peer reviewed paper. This impacts on the power of the study which will not measure the evidence if at all it exists. in addition, the tools used for data collection, how it was developed, pretesting of tools, quality assurance, when data was collected and by who was not clear. the study lacks operational definition for some items like knowledge, attitude etc.

Discussion: the discussion is more of results and the comparison with other studies was random does not consider the similarity among settings and justify why the difference was observed.

Literature review: needs review for more literature and country policy context and provisions. Please find reviewer 's comment included.

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Additional Editor Comments:

General comments: The paper addresses important areas of health system to contribute to sustainable health service delivery.

Introduction : The introduction lacks detail review of literature and policy context of the study country.

Methods: the sample size calculation assumes high rate of enrollment while the result was low which indicates poor review of evidences including the use of estimate from policy document, not peer reviewed paper. This impacts on the power of the study which will not measure the evidence if at all it exists. in addition, the tools used for data collection, how it was developed, pretesting of tools, quality assurance, when data was collected and by who was not clear. the study lacks operational definition for some items like knowledge, attitude etc.

Discussion: the discussion is more of results and the comparison with other studies was random does not consider the similarity among settings and justify why the difference was observed.

Literature review: needs review for more literature and country policy context and provisions.

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5. Thank you for submitting the above manuscript to PLOS ONE. During our internal evaluation of the manuscript, we found significant text overlap between your submission and the following previously published works, some of which you are an author.

-Community-based health insurance and social capital: a review (https://doi.org/10.1186/2191-1991-2-5).

-WILLINGNESS-TO-PAY FOR COMMUNITY BASED HEALTH INSURANCE BY FARMING HOUSEHOLDS: A CASE STUDY OF HYGEIA COMMUNITY HEALTH PLAN IN KWARA STATE, NIGERIA (DOI: 10.15547/tjs.2016.03.014).

-DETERMINANTS OF WILLINGNESS TO JOIN COMMUNITY- BASED HEALTH INSURANCE SCHEME IN A RURAL COMMUNITY OF NORTH-WESTERN NIGERIA (10.35202/AJHE.2015.5103).

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Reviewer #1: Comments

This study assessed willingness to participate in the community-based health insurance and its associated factors in one of the districts in the Northeastern part of Ethiopia. The objective was clearly stated and the authors used quantitative data so as to investigate the issue in question. This shows the study strong.

Despite its good parts the manuscript has many shortcomings.

#1. Similar studies were conducted in different parts of Ethiopia so far. Please follow the following link to access some of them. What the authors brought was not stated in the article.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6337798/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4074337/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6980847/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7493329/

#2. Was CBHI scheme already started in Worebabo district? This issue should be clearly stated in the manuscript. The readers have to read the whole result in reference to the availability/non-availability of the scheme in the district.

#3. The paper has a significant write-up and grammatical problem. Therefore, it needs copy edit by a native English speaker.

Detailed points

Abstract

#1. Better if the authors try to minimize judgmental statements if it is not part of their result. For instance in the first page of the manuscript the authors stated that “Community-based health insurance scheme is the best means of strategy…”

#2. The reason and the conclusion stated in the introduction of the abstract doesn’t seem have a logical relationship. What formation is lacking should be the reason for this kind of studies.

Introduction

#1. The introduction is not strong enough to state the problem and convince the readers. The authors have not given strong justification for the study. Therefore, the authors need to enrich the introduction and show what is really lacking?

You may use the following references:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5797722/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6089309/pdf/bmjopen-2017-019613.pdf

https://pubmed.ncbi.nlm.nih.gov/15315121/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4602341/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4191130/

#2. Some of the information look contradictory with the existing reality in Ethiopia and have not been cited. For instance: “Ethiopia is one of the high burden countries for both communicable and non-communicable diseases in Africa.” “…only practiced by some of the urban communities…”

#3. Evidence indicate that the CBHI scheme in Ethiopia focuses on the rural community rater that the urban (https://link.springer.com/article/10.1007/s10754-005-2333-y). However, in this article the authors stated that the services are being better used by the urban community. It doesn’t seem reasonable argument.

Methods

Study design

#1. The authors need to define what kebele is in its first appearance.

Sample size determination and sampling procedure

#2. The authors taken 80% of power, even though we don’t need powers to calculate samples in a single population proportion formula. Better if the authors indicate the actual formula (at least citation) they have used during sample size determination.

#3. Using a proportion of 79% of enrolment doesn’t seem logical despite we have lots of evidence on willingness to join CBHI. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6337798/; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4074337/; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6980847/; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7493329/.

#4. How 8 kebeles were selected from the 20?

#5. Further explanation on the sampling technique is needed. It cannot be clearly understood how the researcher actually gone through systematic random sampling, for instance; from where they got the list of households, total number of households, the sampling interval, from which household they have started the data collection.

#6. The last sentence “Then the study households were selected by systematic random sampling method from 8 Kebeles after proportional allocation.” S not clear for understanding. Would you please revise it?

Data collection tool and procedures

#7. Please indicate and cite from where the authors adapted the tool.

#8. As indicated by the authors the tool consists of items to assess: sociodemographic status of the participants, knowledge of the participants towards CBHI, and community’s attitude towards the program. However, the main outcome variable (willingness to join) was not listed here. I recommend the authors to submit both versions (English and the translated) of the data collection tool as a supplementary file.

#9. The authors wrote that “It was first prepared in the English language and then translated to Amharic to see for consistency.” But is not clear that how one check consistency of a tool translating into another language.

#10. The authors didn’t say anything about the validation and reliability of data collection tools. These information are paramount important in such kind of scientific investigations.

#11. Even the authors didn’t say anything about pretest of the data collection tools.

#12. The authors need to show what were the variables and their measurement.

Data processing and statistical analysis

#14. The authors shown that, graphs were one method to present the findings of the study. However, there are no graphs throughout the document.

#15. Do the authors have any reason to conduct a simple logistic regression to all the variables and select those with p – value < 0.2 for the multiple logistic regression analysis?

#16. A fitness of good test result is not available in the study. Would you please show how the final model fits?

Results

#1. The calculated sample size were 421, similarly the respondents were 421. Therefore, how the response rate be 94.5 percent?

#2. How can we understand illiterate? Is it to mean those who have net attended formal education?

#3. The statement “Participants knowledge was assessed using 38 knowledge questions with two alternatives coded as 1 for correct answers and 0 for incorrect answers. Respondents who scored above 50% (19 out of 38) were categorized as having good knowledge.” Better be part of the methods.

#4. The statement “Out of these 256 (64.3%) of the participants describe community health insurance program, 332(83.4%) explain the advantage of community-based health insurance and 324 (81.4%) of the respondents know the health care services under the community-based health insurance program.” Are not clear. How the authors brought these information?

#5. This statement “Participant’s attitude towards the CBHI scheme was assessed using the 10 Likert Scale questionnaires. The total response of the participant for these 10 questions was summed which provide a minimum of 10 and a maximum of 50 scores. Respondents who scored above the mean score were categorized having a positive attitude towards CBHI program.” Should be part of methods.

#6. The statement “In this study, willingness to join a Community-Based Health Insurance scheme was determined if all the families were willing to join.” Gives an impression that you interviewed all the family members in the selected households. Was the study conducted that way?

#7. The authors should re-write to clarify and define all the variables listed as reasons for not being willing “The main reasons for unwillingness to join community-based health insurances membership were lack of interest in the program (6.3%), the belief of being a member when needed (7.3%), having other means of health care (10.1%), don’t believe in paying for the sickness (4.5%) and due to the belief community-based health insurance causes financial constraints (5%).”

#8. The authors should also make clear that how the reasons of not being willing to join calculated, what was the denominator. Better if they provide the details in a table.

#9. These statement “Bivariable and multivariable analysis of binary logistic regression model was carried out to identify the factors associated with willingness to join community-based health insurance scheme. Variables with a p-value of less than 0.2 in bivariable analysis was entered to multivariable analysis and those variables with a p-value of less than 0.05 in multivariable analysis was considered statistically significant.” In page 6 is a part of methods section and is repetition in the results section.

#10. Have the authors checked the assumptions of binary logistic regression? For instance, there is a cell value less 5, (table 2 variable: educational level).

Discussion

The discussion should be framed in such a way that you analyze every key finding in the light of findings of earlier researchers. Simply providing others findings and what we found is not helpful to analytically present the findings. Just give a highlight of the findings and give discussion of that finding – its interpretation, implication, comparison with earlier findings. After comparison indicate possible reasons for disparity and/or similarity.

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20 Apr 2021

Point-by-point Responses to the editors

Introduction: The introduction lacks detail review of literature and policy context of the study country.

Response: The authors exhaustively work on the introduction section and we had incorporated all of the concerns raised by the editor in the revised version of the manuscript. Besides, we included the literatures to show the policy context of the country, Ethiopia.

Methods: the sample size calculation assumes high rate of enrollment while the result was low which indicates poor review of evidences including the use of estimate from policy document, not peer reviewed paper. This impacts on the power of the study which will not measure the evidence if at all it exists. in addition, the tools used for data collection, how it was developed, pretesting of tools, quality assurance, when data was collected and by who was not clear. the study lacks operational definition for some items like knowledge, attitude etc.

Responses: The authors have tried to find all the available literatures on willingness to join community-based health insurance program. However, the proportion 79% were used for sample size determination. Because the prevalence reported in this study participants have similar socio economic characteristics with our study communities.

Regarding the tool, data collection procedure, quality assurance, pretesting, and data collector; the authors have revised the comment and incorporated the raised issues in the revised version of the manuscript.

Discussion: the discussion is more of results and the comparison with other studies was random does not consider the similarity among settings and justify why the difference was observed.

Response: The authors have revised the discussion section and incorporated the concerns of the editor in the revised version of the manuscript.

Literature review: needs review for more literature and country policy context and provisions. Please find reviewer 's comment included.

Response: The authors have tried to review more literatures and country policy context and provision

Responses to the Reviewer #1

This study assessed willingness to participate in the community-based health insurance and its associated factors in one of the districts in the Northeastern part of Ethiopia. The objective was clearly stated and the authors used quantitative data so as to investigate the issue in question. This shows the study strong.

Despite its good parts the manuscript has many shortcomings.

#1. Similar studies were conducted in different parts of Ethiopia so far. Please follow the following link to access some of them. What the authors brought was not stated in the article.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6337798/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4074337/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6980847/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7493329/

Response: Sure, there are some studies conducted in Ethiopia but the previous studies were conducted in places where the households live in non-drought affected areas. However, there was no study conducted in South Wollo Zone that were frequently affected by drought. Besides, these part of the zone, Worebabo, is also affected by desert locust. These factors may affect the willingness of the households to join CBHI. Therefore, these were the reasons to conduct this study in south wollo zone.

#2. Was CBHI scheme already started in Worebabo district? This issue should be clearly stated in the manuscript. The readers have to read the whole result in reference to the availability/non-availability of the scheme in the district.

Response: The program was already started in worebabo district but still many households were not joined the CBHI scheme and are not utilizing it.

#3. The paper has a significant write-up and grammatical problem. Therefore, it needs copy edit by a native English speaker.

Response: The authors have corrected the typographical errors in the revised manuscript.

Detailed points:

Abstract

#1. Better if the authors try to minimize judgmental statements if it is not part of their result. For instance, in the first page of the manuscript the authors stated that “Community-based health insurance scheme is the best means of strategy…”

Responses: The authors have corrected such judgmental statements in the revised manuscript.

#2. The reason and the conclusion stated in the introduction of the abstract doesn’t seem have a logical relationship. What formation is lacking should be the reason for this kind of studies.

Introduction

Response: We have corrected it, see the revised manuscript.

#1. The introduction is not strong enough to state the problem and convince the readers. The authors have not given strong justification for the study. Therefore, the authors need to enrich the introduction and show what is really lacking?

Response: The previous studies were conducted in places where the households live in non-drought affected areas. However, there was no study conducted in South Wollo Zone that were frequently affected by drought. Besides, these part of the zone, Worebabo, is also affected by desert locust. These factors may affect the willingness of the households to join CBHI. Therefore, these were the reasons to conduct this study in south wollo zone.

#2. Some of the information look contradictory with the existing reality in Ethiopia and have not been cited. For instance: “Ethiopia is one of the high burden countries for both communicable and non-communicable diseases in Africa.” “…only practiced by some of the urban communities…”

Response: This concern is well addressed in the revised version of the main manuscript.

#3. Evidence indicate that the CBHI scheme in Ethiopia focuses on the rural community rather that the urban (https://link.springer.com/article/10.1007/s10754-005-2333-y) . However, in this article the authors stated that the services are being better used by the urban community. It doesn’t seem reasonable argument.

Response: In our study urban community stands for people who are living in the woreda, kebele, and other small cities in the study area which are also the targets for community based health insurance program. Rural community in this study mean people living in a scattered manner other than the cities mentioned.

Methods

Study design

#1. The authors need to define what kebele is in its first appearance.

Sample size determination and sampling procedure

Response: There are 20 kebeles in the study district, Worebabo woreda, of these kebeles, 8 were selected by lottery method. Then study households were selected using systematic random sampling method after proportional allocation for the 8 selected kebeles. The interval (7) was obtained by dividing the total source population to the sample size (2842/421 = 7). Then the index household was selected by lottery method from 1 to 7 values which was 5, the starting from the fifth household we move on the 7th interval until we reached the required sample size. Here is a schematic presentation of sampling techniques.

THY = total households in yaya, KNSHY = number of sample households in yaya

THG = total households in goha, KNSHG = number of sample households in goha

THB = total households in bokekisa, KNSHB = number of sample households in bokekisa

THb = total households in Bulbulo, KNSHb = number of sample households in Bulbulo

THD = total household’s in Deye, KNSHD = number of sample households in Deye

THE = total households in Ejiressa, KNSHE = number of sample households in Ejiressa

THG = total households in Gerebabo, KNSHG = number of sample house holdes in Gerebabo

THg = total households in gedero, KNSHg = number of sample house holdes in gedero

#2. The authors taken 80% of power, even though we don’t need powers to calculate samples in a single population proportion formula. Better if the authors indicate the actual formula (at least citation) they have used during sample size determination.

Response: The sample size was calculated in two ways one using prevalence and second using the associated factors. Then, the maximum sample size was considered for this study.

Objective 1: prevalence of outcome variable and the sample size was determined using;

(1) a single population proportion formula by considering the assumption Zα/2=critical value for normal distribution at 95% confidence level which equals to 1.96 (z value at α=0.05), P (Estimated proportion) =79% taken from previous study in Kewiot and Efratana Gedem Districts of Amhara Region, Ethiopia and absolute precision or margin of error 5% (d = 0.05). The following formula was used to calculate sample size [43].

n=((Za/2)^2*p(1-p))/d^2

n=((1.96)^2*0.79(0.21))/〖(0.05)〗^2 n = 255

n = 255*1.5) + (382*0.1) = 421

Objective 2: factors associated with the outcome variable and the sample size was determined using double population proportion formula and this was done using Epinfo version7.0.2 with the following basic assumptions

(2) using the assumption Zα/2=critical value for normal distribution at 95%, 80% power of the study, and unexposed to exposed ration of 1 using Epi Info version 7 software. Two variables, knowledge about CBHI and family health status were taken from the previous studies for the sample calculation [39]. Hence power of the study was used while calculating sample size by factors.

Finally, the maximum sample size was used for this study. By default, the prevalence gives the maximum sample size than the factors. But the 80% power was not determined for the prevalence study.

#3. Using a proportion of 79% of enrolment doesn’t seem logical despite we have lots of evidence on willingness to join CBHI. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6337798/; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4074337/; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6980847/; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7493329/.

Response: From the retrieved articles the prevalence 79% was near to the study area and can better represent our population. So we assume that the socio economic status in both setting is similar and hence we used this proportion for sample size calculation.

#4. How 8 kebeles were selected from the 20?

Response: 8 kebeles were selected from the 20 kebeles by lottery method (see the main manuscript).

#5. Further explanation on the sampling technique is needed. It cannot be clearly understood how the researcher actually gone through systematic random sampling, for instance; from where they got the list of households, total number of households, the sampling interval, from which household they have started the data collection.

Response: From a total of 20 kebeles in the district 8 kebeles was selected using lottery methods. The total number of households was retrieved from each the selected kebele administration. Then the total sample size was distributed proportionally to each study kebeles based on the number of households in each kebeles. The total source populations were divided by the total sample size to obtain the interval (k=7). After getting the interval (7) one house hold was selected by lottery method from 1-7 kebeles which was the fifth household. Then starting from the fifth household move on every 7th interval to get the total sample size in each kebeles.

Key

Selected kebeles b = bulbulo kebele, D=deye, G =gedero Y=yaya, g=goha, G=gerbabo,

B = bokekisa, E =ejierssa.

THY–total households in yaya KNSHY-number of sample households in yaya; k=613/76=7

THG-total households in goha KNSHG-number of sample households in goha; k=265/39=7

THB-- total households in bokekisa KNSHB-number of sample households in bokekisa; 220/33=7

THb- total households in Bulbulo, KNSHb-number of sample households in Bulbulo; k=418/62=7

THD- total household’s in Deye, KNSHD-number of sample households in Deye, k=338/50=7

THE- total households in Ejiressa, KNSHE-number of sample households in Ejiressa; k=256/38=7

THG- total households in Gerebabo, KNSHG-number of sample house holdes in Gerebabo; k=466/69=7

THg- total households in gedero, KNSHg-number of sample house holdes in gedero; 367/54=7

Total households of 8 kebeles=2842. Total sample of households of 8 kebele= 421; k=2842/421=7

#6. The last sentence “Then the study households were selected by systematic random sampling method from 8 Kebeles after proportional allocation.” S not clear for understanding. Would you please revise it?

Response: Revised

Data collection tool and procedures

#7. Please indicate and cite from where the authors adapted the tool.

Response: cited (see the revised manuscript).

#8. As indicated by the authors the tool consists of items to assess: sociodemographic status of the participants, knowledge of the participants towards CBHI, and community’s attitude towards the program. However, the main outcome variable (willingness to join) was not listed here. I recommend the authors to submit both versions (English and the translated) of the data collection tool as a supplementary file.

Response: The participants were asked whether they are willing to participate or not in CBHI program after detailed explanation of the aim, payment of the program.

#9. The authors wrote that “It was first prepared in the English language and then translated to Amharic to see for consistency.” But is not clear that how one check consistency of a tool translating into another language.

Response: Translation was made by different scholars and see inconsistencies between translations and made correction to the disagreement.

#10. The authors didn’t say anything about the validation and reliability of data collection tools. This information is paramount important in such kind of scientific investigations.

Response: the tool was adapted from the literatures and no need of validating it but reliability was done via pretest.

#11. Even the authors didn’t say anything about pretest of the data collection tools.

Response: Pretest was done on 5% of the total sample size (22 study participants) in Dessie Zuriya district. Based on the result of pretest, some ambiguous questionnaire was modified to obtain better clarity to participants.

#12. The authors need to show what were the variables and their measurement.

Response: Corrected (see the revised manuscript)

Data processing and statistical analysis

#14. The authors shown that, graphs were one method to present the findings of the study. However, there are no graphs throughout the document.

Response: corrected (see the revised manuscript).

#15. Do the authors have any reason to conduct a simple logistic regression to all the variables and select those with p – value < 0.2 for the multiple logistic regression analysis?

Response: We did not have special reasons but we consider p-value<0.2 to make the model more relaxed and to include more variable for the final model.

#16. A fitness of good test result is not available in the study. Would you please show how the final model fits?

Response: Hosmer and Lemeshow fitness of good test was done which was 0.87 this implies the model is fitted.

Results

#1. The calculated sample size was 421, similarly the respondents were 421. Therefore, how the response rate be 94.5 percent?

Response: The sample size was 421 with 398 participants responded giving a response rate of 94.5%

#2. How can we understand illiterate? Is it to mean those who have net attended formal education?

Response: In this study, illiteracy mean participants who have not attended formal education.

#3. The statement “Participants knowledge was assessed using 38 knowledge questions with two alternatives coded as 1 for correct answers and 0 for incorrect answers. Respondents who scored above 50% (19 out of 38) were categorized as having good knowledge.” Better be part of the methods.

Response: We have moved this part to the method section

#4. The statement “Out of these 256 (64.3%) of the participants describe community health insurance program, 332(83.4%) explain the advantage of community-based health insurance and 324 (81.4%) of the respondents know the health care services under the community-based health insurance program.” Are not clear. How the authors brought these information?

Response: Participants were asked to answer: what is CBHI?, what is the advantage of CBHI?, what are the health care services covered by CBHI? And the response were recorded

#5. This statement “Participant’s attitude towards the CBHI scheme was assessed using the 10 Likert Scale questionnaires. The total response of the participant for these 10 questions was summed which provide a minimum of 10 and a maximum of 50 scores. Respondents who scored above the mean score were categorized having a positive attitude towards CBHI program.” Should be part of methods.

Response: We have moved this part to the method section.

#6. The statement “In this study, willingness to join a Community-Based Health Insurance scheme was determined if all the families were willing to join.” Gives an impression that you interviewed all the family members in the selected households. Was the study conducted that way?

Response: No, we have interviewed the head of the house hold members about the willingness of self, willingness of all family members and willingness of some family members.

#7. The authors should re-write to clarify and define all the variables listed as reasons for not being willing “The main reasons for unwillingness to join community-based health insurances membership were lack of interest in the program (6.3%), the belief of being a member when needed (7.3%), having other means of health care (10.1%), don’t believe in paying for the sickness (4.5%) and due to the belief community-based health insurance causes financial constraints (5%).”

Response: Corrected (See the revised manuscript)

#8. The authors should also make clear that how the reasons of not being willing to join calculated, what was the denominator. Better if they provide the details in a table.

Response: In our study 105(26.4%) of the households were not willing to join the program. The reason for not willingness were calculated among those who were not willing to join the community based health insurance program which was the denominator. The denominator was 105.#9. These statement “Bivariable and multivariable analysis of binary logistic regression model was carried out to identify the factors associated with willingness to join community-based health insurance scheme. Variables with a p-value of less than 0.2 in bivariable analysis was entered to multivariable analysis and those variables with a p-value of less than 0.05 in multivariable analysis was considered statistically significant.” In page 6 is a part of methods section and is repetition in the results section.

Response: We have moved this part to the method section.

#10. Have the authors checked the assumptions of binary logistic regression? For instance, there is a cell value less 5, (table 2 variable: educational level).

Response: The authors have checked the assumption of binary logistic regression

Discussion

The discussion should be framed in such a way that you analyze every key finding in the light of findings of earlier researchers. Simply providing others findings and what we found is not helpful to analytically present the findings. Just give a highlight of the findings and give discussion of that finding – its interpretation, implication, comparison with earlier findings. After comparison indicate possible reasons for disparity and/or similarity.

Response: the authors had revised the whole section of the discussion and incorporated the raised concerns in the revised version of the manuscript.

Thank you all for your constructive comments as well as for suggesting important literatures!

Submitted filename: Response to-editor.docx

Click here for additional data file.

5 May 2021

PONE-D-20-29657R1

Willingness to Join Community Based Health Insurance among Households in Worebabo District, Northeast Ethiopia: A community based study.

PLOS ONE

Dear Gebeyaw Biset

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

1 - the background needs description about UHC and its relation with CBHI in Ethiopia

2 - implication of the study to households, health system and policy makers is not clear

3 - what does high level of willingness mean to the CBHI in Ethiopia and compare with the current practice and use

4 - it is not clear what strategies should be used for different population groups if we have to enhance participation in CBHI

5 - limitation of the study did not address key issues related to data collection and quality assurance. For example some socially desirable questions and their answers might have affected the results

==============================

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15 May 2021

Point by point responses

1 - the background needs description about UHC and its relation with CBHI in Ethiopia

Responses: Universal health coverage (UHC) is a situation in which all individuals and communities receive the health services they need without suffering financial constraints when paying for their health care services. This can be achieved when everyone has access to health care at an affordable cost [11, 12]. However, UHC strategy confronts the challenges of health care financing, resource allocation and protecting people against financial hardship particularly in developing countries [13]. Following this, countries have been implementing different health care financing systems to reduce the cost of health care expenditures and achieving universal health coverage [14-17].

Although Ethiopia has planned to achieve universal health coverage by 2035 [], its UHC has remained low (34.3%) compared to most of the African countries [12]. As a result, the government of Ethiopia has been implementing CBHI program as a means of achieving universal health coverage in the country [21]. A national pilot study on the effectiveness of CBHI schemes in Ethiopia showed that CBHI members are using health services more (26% or more) than the non-members. This implies that universal health coverage can be achieved in the country through the implementation of CBHI program [22]. �  The raised concerns are well addressed in the revised version of the manuscript.

2 - implication of the study to households, health system and policy makers is not clear

Response:

Implication of the study to the households, health system, and policy

In this study, three-fourths (73.6%) of the households are willing to join CBHI program. This level of willingness might affect the 2020 country plan of achieving 80% of enrollment and the 2035 plan of achieving universal health coverage in the country. The study revealed that the community have concerns toward the program like quality of health services and lack of trust to the program. Therefore, the government should build trust among the community, increase the quality of health care system, and address other household and health system related factors to scale up the program.

3 - what does high level of willingness mean to the CBHI in Ethiopia and compare with the current practice and use

Response: Ethiopia has planned to enroll 80% of its population in to the community based health insurance program by 2020. To achieve this plan, more than 80% of the population should be willing to join the CBHI program. Compared to this country plan, studies reported willingness more than 80% were considered high level of willingness and a willingness report below this percent is said to be low level of willingness. But, as we noted from the literature, although there is a regional variation regarding the willingness towards CBHI program, there is a study which revealed only 12.8% of the participants were willing to join the program which was far from the 2020 country plan.

4 - it is not clear what strategies should be used for different population groups if we have to enhance participation in CBHI

Response: In our study we have assessed community’s willingness towards the community based health insurance program in general using similar tool. We have not seen willingness across the different segment of the population. But the finding implies considering the family size, the quality of health services in the catchment area, trust to the program, presence of other social support system in the area should be considered.

5 - limitation of the study did not address key issues related to data collection and quality assurance. For example, some socially desirable questions and their answers might have affected the results.

Response: Corrected (See the revised manuscript)

Submitted filename: Response to Reviewer2.docx

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24 May 2021

PONE-D-20-29657R2

Willingness to Join Community Based Health Insurance among Households in South Wollo, Northeast Ethiopia: A community-based study.

PLOS ONE

Dear Gebeyawu Biset,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

Abstract

In the conclusion, instead of directly linking to health extension program it is better to highlight how this can be done from the current CBHI. Health extension program mainly provides preventive and limited curative service which may require insurance coverage.

Background

Please add few paragraphs about social health insurance before diving into CBHI

Please comment about the willingness to pay as the CHI system is government led which may affect the willingness. Please add some comments to limitation of the study.

Methods

Please add a paragraph or more about data quality assurance from its preparation to analysis.

Discussion

What is those with fewer family size less likely to participate? Is there anything that the CBHI amount is set based on family size?

Is willingness affected by social desirability of the response? Do we lack some information as the country plans future scale up?

Conclusion: Revise the conclusion only based on the study results not the conviction of researchers.

==============================

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Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments (if provided):

Abstract

In the conclusion, instead of directly linking to health extension program it is better to highlight how this can be done from the current CBHI. Health extension program mainly provides preventive and limited curative service which may require insurance coverage.

Background

Please add few paragraphs about social health insurance before diving into CBHI

Please comment about the willingness to pay as the CHI system is government led which may affect the willingness. Please add some comments to limitation of the study.

Methods

Please add a paragraph or more about data quality assurance from its preparation to analysis.

Discussion

What is those with fewer family size less likely to participate? Is there anything that the CBHI amount is set based on family size?

Is willingness affected by social desirability of the response? Do we lack some information as the country plans future scale up?

Conclusion

Revise the conclusion only based on the study results not the conviction of researchers.

[Note: HTML markup is below. Please do not edit.]

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Submitted filename: R2 - Willingness to Join Community Based Health Insurance among Households in South Wollo.docx

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4 Jun 2021

Point by point response

Abstract

#1 In the conclusion, instead of directly linking to health extension program it is better to highlight how this can be done from the current CBHI. Health extension program mainly provides preventive and limited curative service which may require insurance coverage.

Response: In this study, nearly three-fourths of the participants were willing to join a community-based health insurance program. However, different household and health service-related factors were affecting their willingness. Improving the quality of health services, building good knowledge and positive attitude among the community increase the likely of enrollment towards the program. Therefore, the government in collaboration with the regional and woreda health offices should work towards improving the quality of health services and conduct program advocacy via integrating the program with the health extension program. The raised comments are incorporated in the main document.

Background

#2 Please add few paragraphs about social health insurance before diving into CBHI

Response: Poor health care financing remains a major challenge for the health care system in Ethiopia leaving households vulnerable to impoverishment from catastrophic health expenditures. Community based health insurance and social health insurance are the two policy options designed to address the poor health care financing in the country. Community-based health insurance is an alternative to user fees to improve equity in access to medical care particularly to those rural communities and the informal sectors. Whereas social health insurance is a form of mandatory health insurance for formal sector employees, including retirees and pensioners. Community-based health insurance program has been implemented in the country since 2011. Although Ethiopia take initiatives to implement the social health insurance program, the program is not yet started in the country. The raised comments are incorporated in the main document.

#3 Please comment about the willingness to pay as the CHI system is government led which may affect the willingness. Please add some comments to limitation of the study. Subsidize.

Response: The majority of the health service provisions in Ethiopia are government run. This is also good opportunity to apply CBHI scheme as the insurance schemes are not primarily for profit and require high government subsidy at their very start. However, if the community-based health insurance were privatized, it could be primarily for profit organizations which might expose the community for further costs.

Methods

#4 Please add a paragraph or more about data quality assurance from its preparation to analysis.

Response:

Data quality assurance:

A validated tool was adapted from the literature and contextualized into the study area. Prior to the data collection period a pretest was done and based on the result of the pretest some amendments were done. Training was given for data collectors and supervisors regarding the data collection process. The completeness of the data was checked on daily basis by the data collector itself, supervisors and principal investigators. Finally, data was checked for completeness, errors, missing values, and then it was coded entered using EpiData version 3.1 data manager. The binary logistic regression model was selected for analysis because the outcome variable in the study is binary and categorical type. Before doing the analysis, the model fitness was checked using the Hosmer-Lemeshow model fit-ness test which was 0.87. additionally, the correlation between independent variables was checked and there was no correlation between independent variables. The raised comments are incorporated in the main document.

Discussion

#5 What is those with fewer family size less likely to participate? Is there anything that the CBHI amount is set based on family size?

Response: CBHI payment is based on the family size of the household. In our study families with family size of fewer than 4 were less likely to join the program and the finding was supported by other two studies in the country. And we have justified the reason for this as; households with small family size could afford health cost for their small family and might not financial hardship for health care services as a result they might not need to join the program compared to households with larger families.

#6 Is willingness affected by social desirability of the response? Do we lack some information as the country plans future scale up?

Response: Willingness might be affected by the social desirability of the response; people might be voluntary to join the program when an interviewer whom they know asked them about their willingness. As the interviewer were health care professionals, the interviewee might be falsely willing to join because they feel fear the health care professional if they say I am not willing to join the program. But, later on they might not pay the premium because they don’t want to join the program.

#7 Conclusion: Revise the conclusion only based on the study results not the conviction of researchers.

Response: In this study, nearly three fourth of the participants were willing to join a community-based health insurance program. Program. Several household and health service related factors were affecting community’s willingness toward the program. The government should improve the quality of health services and perform program advocacy to scale-up the community based health insurance program (see the revised manuscript).

Submitted filename: Point by point response3.docx

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18 Jun 2021

PONE-D-20-29657R3

Willingness to Join Community Based Health Insurance among Households in South Wollo, Northeast Ethiopia: A community-based study.

PLOS ONE

Dear Gebeyawu,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Thanks for addressing major comments raised are well addressed. However, the paper will benefit from some additions indicated below

Map of the study area

Description of the health system including the community structure

The organization of CBHI and what service it covers, and how it works with the community in terms of participation and use

Add areas to be explored in the future research

Please submit your revised manuscript by July 20, 2021. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see:  http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at  https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols .

We look forward to receiving your revised manuscript.

Kind regards,

Daniel Gemechu Datiko

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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Reviewers' comments:

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

19 Jul 2021

Point by point response

1. Map of the study area

Response: (see the main document)

2. Description of the health system including the community structure

Response:

Ethiopian health system is guided by a 20-year health sector development strategy implemented through a series of five-year health sector development programs (HSDP) with the alignment of international commitments. Currently, the country is implementing the fourth health sector development plan (HSDP IV) which has introduced a three-tier health care delivery system in the country. The primary level consists of health posts (1/5,000 population), health centers (1/25,000), and primary hospitals (1/100,000); secondary level services are provided by general hospitals (1/1million population); and tertiary services by specialized hospitals (1/5million populations). The three health care systems are integrated by the referral system where the community are referred from lower level of health care to a higher level and vis versa. The lower levels of health care (health post, health center and general hospitals) are the first entry point for the community. The community are organized in to health development army and they are integrated with the health extension workers so as to enable the community to take greater responsibility for promoting and maintaining their own health.

3. The organization of CBHI and what service it covers, and how it works with the community in terms of participation and use

Response:

The community based health insurance is organized in to kebele level, district level, regional and national levels by administration. At the woreda level, this body is responsible for: `Signing agreements with health care provider’s/health facilities; `Reimbursing health care providers; Administering the fund (keeping financial records; preparing financial statements); Managing the database (which contains data on members, contributions, and utilization). A General Assembly and Board of Directors oversee the governance of CBHI schemes at the woreda level. At the kebele level, the executive body is responsible for registering members, collecting premiums, and channeling funds to each woreda scheme. the community are directly linked to the service via the health development army and health extension workers.

The CBHI benefit package includes outpatient and inpatient services, laboratory services, imaging services, supply of drugs and related services with the exception of eyeglasses, dental implant, dialysis, etc. All government health centers that are situated in the woreda and fulfill the minimum standard of service delivery are contracted to provide services to members. All pilot woreda have also signed service contracts with their region’s referral hospitals. Three regions (Amhara, Oromia, and Tigray) entered contracts to ensure the possibility of interregional referrals.

4. Add areas to be explored in the future research

Response:

The major research areas we recommend for future researchers are; first community willingness with a qualitative research design need to be under taken in order to get a deeper insights regarding their willingness. Second the researchers need to focus on the health care system including the quality of health care particularly quality of health services under community based health insurances. Additionally, a comparative study regarding health seeking behaviors between community based health insurance utilizers and non-utilizers need to be conducted.

Submitted filename: Point by point response4.docx

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21 Sep 2021

20 Nov 2021

Response to the editor

# 1: The discussion section is more of results and needs detailed discussion of the results

Response: we have corrected the discussion section of the manuscript (see the main manuscript).

#2: The areas of focus for future research are too general and do not clearly indicate what should be done

Response: the authors have tried to clarify the area of focus for future research (see the main manuscript)

The authors have also assessed all the necessary editorial problems and corrected it accordingly.

Submitted filename: Response to the edotor nov20th 2021.docx

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9 Dec 2021

Willingness to Join Community Based Health Insurance among Households in South Wollo, Northeast Ethiopia: A community-based cross-sectional study.

PONE-D-20-29657R5

Dear Gebeyaw Bisnat,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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PLOS ONE

19 Jan 2022

PONE-D-20-29657R5

Willingness to Join Community Based Health Insurance among Households in South Wollo, Northeast Ethiopia: A Community-based Cross-sectional Study

Dear Dr. Biset:

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on behalf of

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PLOS ONE

Table 1

Sociodemographic characteristic of the respondents in WerebBabu district, Northeast Ethiopia, July, 2020.

Variable	Category	Frequency(n = 398)	Percentage
Sex	Male	332	83.4
	Female	66	16.6
Age	20–29	31	7.8
	30–39	116	29.1
	40–49	169	42.5
	>50	82	20.6
Marital status	Single	11	2.8
	Married	348	87.4
	Divorced	25	6.3
	Windowed	14	3.5
Educational status	Illiterate	215	54.0
	read and write	148	37.2
	Primary school	22	5.5
	Secondary school	13	3.3
Residence	Rural	314	78.9
	Urban	84	21.1
Family size	< 3	61	15.3
	4–6	235	59
	> 6	102	25.6
Participation in Idir	Yes	112	28.1
	No	286	71.9
Seek health care while sick	Yes	294	73.9
	No	104	26.1
Chronic illness in the house	Yes	32	8.0
	No	366	92.0
Disability in the house	Yes	6	1.5
	No	392	97.5
Ever borrowed for health services	Yes	133	33.1
	No	265	65.9

Table 2

Factors associated with willingness to join community-based health insurance program among households in WerebBabu district, Northeast Ethiopia July, 2020.

Variables	Category	WTJ		COR(95% CI)	AOR(95% CI)	p-value
		No n(%)	Yes n(%)
Sex	Male	98(93.3)	234(79.9)	0.28(0.13-.64)	0.2(0.07–0.58)*	0.003
	Female	7(6.7)	59(20.1)	1	1	1
Residence	Rural	52(49.5)	191(65.2)	1.91(1.22–3)	1.9(1.09–3.32)*	0.02
	Urban	53(50.5)	102(34.8)	1	1	1
Member of Idir	Yes	40(38.1)	72(24.6)	0.53(0.33–0.85)	0.46(0.25-.84)*	0.01
	No	65(61.9)	221(75.4)	1	1	1
Quality of health service	Good	23(21.9)	84(28.7)	2.16(1.2–3.9)	2.96(1.4–6.24)*	0.004
	Medium	37(35.2)	133(45.4)	2.13(1.27–3.57)	2.37(1.23–4.56)*	0.01
	Poor	45(42.9)	76(25.9)	1	1	1
Chronic illness	No	86(81.9)	280(95.6)	0.21(0.1–0.44)	0.31(0.13–0.77)*	0.01
	Yes	19(18.1)	13(4.4)	1	1	1
Seek health care service	Yes	87(82.9)	207(70.6)	0.5(0.28–0.88)	0.59(0.3–1.17)	0.13
	No	18(17.1)	86(29.4)	1	1	1
Institution to get Rx	Government	100(95.2)	265(90.4)	0.47(0.19–1.26)	0.52(0.16–1.75)	0.29
	Private	5(4.8)	28(9.6)	1	1	1
Educational level	Illiterate	60(57.1)	155(52.9)	0.47(0.1–2.18)	0.6(0.13–2.77)	0.52
	Read/write	35(33.3)	113(38.6)	0.59(0.12–2.78)	1.33(0.28–6.41)	0.72
	Primary	8(7.6)	14(4.8)	0.32(0.06–1.8)	1.21(0.19–7.66)	0.84
	Secondary	2(1.9)	11(3.8)	1	1	1
Family size	1–3	37(35.2)	24(8.2)	0.27(0.14–0.53)	0.18(0.08–0.41)*	<0.0001
	4–6	38(36.2)	198(67.6)	2.2(1.27–3.82)	1.6(0.85–3.1)	0.14
	>6	30(28.6)	71(24.2)	1	1	1
Attitude	Positive	44(41.9)	229(78.2)	4.96(3.08–7.99)	4.1(2.32–7.22)*	<0.0001
	Negative	61(58.1)	64(21.8)	1	1	1
Knowledge	Good	61(20.8)	232(79.2)	2.64(1.63–4.27)	2.62(1.43–4.8)*	0.002
	Poor	43(41.0)	62(59.0)	1	1	1

* = Significantly associated, 1 = reference, COR = Crude odds ratio, AOR = Adjusted odds ratio, Rx = treatment, WTJ = Willingness to join, CI = confident interval.