Skip to main content

“Magnitude of community-based health insurance utilization and associated factors in Bassona Worena District, North Shoa Zone, Ethiopia: a community-based cross-sectional study”

Abstract

Introduction

The health insurance system has been proven to offer effective and efficient health care for the community, particularly community-based health insurance is expected to ensure health care access for people with low economic status and vulnerable groups. Despite the significance of evidence-based systems and implementation, there is a limited report about the magnitude of CBHI utilization. Therefore, this study was done to assess factors associated with community-based health insurance utilization in Basona Worena District, North Shewa Zone, Ethiopia.

Method

A community-based cross-sectional study was employed. We have included 530 households from 6 randomly selected kebeles. The data was entered using Epi-Data V 3.1 and exported to SPSS version 20.0 for statistical analysis. Bi-variable and multivariable logistic regression analyses were computed to determine factors associated with community-based health insurance utilization.

Result

The study finding shows that 58.6% of the respondents were members of community-based health insurance. Respondents who had primary and secondary education levels were 2 times more likely to be members than those who had no formal education. As compared to those who had awareness, respondents who had no awareness about CBHI were 0.27 times less likely to be insured. Respondents who did not experience illness were 0.27 times less likely to be members than respondents who experienced illness.

Conclusion

Educational status, awareness about CBHI, perception of CBHI scheme and illness experience of family influence CBHI utilization. There is a need to strengthen awareness creation to improve the CBHI utilization.

Peer Review reports

Introduction

According to the World Health Organization (WHO), despite the wide variation in per capita health expenditure between and within countries of the world, over 100 million people are driven into poverty because of the catastrophic health spending. It is conceivable that the majority live in most middle-income countries and low-income countries (LMIC) which have poor health service system and weak health insurance scheme [1, 2].

This financial gap in LMIC leads to user fees for the health services they get that result in high out of pocket (OOP) expenditure. The high OOP expenditure because of user fees result financial risk and increases lack of fairness in access to essential health services [3]. High OOP payment for essential health services is the main risk factor of poverty that shows the need for improving economic security to minimize high health expenditure and reduce poverty [4]. In most LMIC, only a few people have access to health insurance scheme, peoples face health expenditure catastrophe because of absence of health financial risk protection [5].

In Ethiopia, the sources of health care financing are government, OOP, donors and other sources like health insurance [6]. Majority (more than 80%) of finance source in private health institution is OOP at the time of service delivery that indicates the poor health system structure of private health care expenditure. It is anticipated that CBHI scheme will strengthen the health system and help to stabilize the health care financing [7].

Health insurance provides financial risk protection and reduces poverty by risk pooling and it has also good possibility of ensuring universal health care coverage. Yet, launching such type of scheme in resource limited countries has been found challenging due to the exclusion of poor individuals in these areas and the majority are informal sectors employee and rural resident [3, 4]. Thus community based health insurance (CBHI) initiated in response to financial risk protection in health service and it is promising alternative for risk pooling health care financing system improves health services utilization and reduces poverty [8].

CBHI scheme has been implemented in developing countries and other parts of world. Recently in Ethiopia two type of health insurance scheme introduced which are social health insurance and CBHI. In social health insurance enroll the formal sector while CBHI involves informal sector of the economy. The social health insurance and CBHI scheme differ by premium collection system and the economy sector they enroll. CBHI system ensure the financial risk protection of poor individuals from health catastrophic expenditure through risk pooling and sharing and help health institutions to efficiently utilize resources and reduce financial risk [9].

WHO review report regarding health insurance enrollment of informal employee people shows that the utilization of non-profit health insurance system is very poor and only few members are enrolled [10]. There is also evidence that the implementation of CBHI in most LMICs continued to be challenged by poor enrollment of the community and sustainability concerns [11].

For instance, a community based cross-sectional study in South India that assessed determinants of CBHI utilization rural population reported 53.1% of the study participants were insured [12]. From African countries, the implementation of CBHI scheme ranged from about 2% in Kenya and Cameroon to 31% and 44% in Nigeria and Uganda respectively [13]. According to a cross-sectional study that was conducted to assess determinants of rural households willingness to participate in CBHI in Nigeria founds that only 31% of the study respondents were members of CBHI [14]. On another study done on determinants of CBHI enrollment and renewing among households in rural South-Western Uganda, they have found out that around 44% of the study respondents were member of CBHI scheme [15].

In Western Ethiopia, a cross-sectional descriptive study was conducted on CBHI utilization and its associated factors among informal workers in GIda Ayanan Ditrict, Oromia Region and it has found that founds that only 27.5% of the study participants enrolled in CBHI [16]. Another similar study conducted in West Gojjam Zone, Northwest Ethiopia revealed that 58.0% the study respondents were CBHI members [17]. Similar finding reported from studies conducted Dimibitchu and Damboya districts which found 67.0% and 62.0% respectively [9].

In Ethiopia, regardless of the benefit of evidence based study for policy and decision makers, there is limited amount of studies that are done on magnitude of CBHI utilization at district and country level [18]. To the best of the author’s knowledge, there is also no study or comprehensive studies that were conducted in Bassona Worenea district, North Shewa Zone, Ethiopia. Therefore, the current study aimed to determine the utilization of CBHI and its associated factors in Bassona Worenna District.Findings and recommendations from this study may provide information to policy makers and other concerned stakeholders at different level to design targeted and evidence based strategies that will help to increase the number of people utilize CBHI and it will also serve as a baseline for future studies in the area.

Methods

Study setting

This study was done in Bassona Worana district which is one of 24 districts in North Shoa Zone, Amhara Region, Ethiopia. The district is located in Northern part of Ethiopia and at 130 km distance far from Addis Ababa. It has large population size in North Shoa Zone with population number of 145,281 (in 2016). The district covers 786.5 km² areas and there are 31 kebeles and 35 health facilities.

Study design and period

A community based cross sectional study design was employed from June 1 to 30, 2020.

Sample size and sampling procedure

For this study, The actual sample was calculated using Epi-info statistical software by taking the proportion of CBHI utilization which is 94% from the national survey in Northwest Gojjam zone, Northwest Ethiopia. By considering design effect of two and 10% non-response rate a total of 530 representative households were selected. From the total 31 kebeles that are found in the district, six kebeles were selected using lottery method so Wayu, Debele, Saria, Nas, Kasima and Adisge were selected. The total sample size was allocated proportionally to each selected kebeles based on the number of households. Systematic random sampling technique was used to select study every 9th households using the administrative kebele household register.

Eligibility criteria

Permanent resident in the district ( for more than six months), household head aged 18 years old and above were qualified to be included in this study. Whereas, household heads who are a formal sector employees and who are unable to communicate due to being sick or other reasons were not included in the study.

Study variables

In this study CBHI utilization was our dependent variable and CBHI utilizers are operationalized as a households who are a member of community based health insurance who are confirmed by their new membership card.

whereas Socio-demographic factors such as age, sex, religion, ethnicity, marital status, educational level and monthly income, individual factors like awareness and perception about CBHI, health system related factors like distance from health facility, waiting time, availability of drugs, satisfaction with services and household’s health status were our independent variables.

Data collection tools and procedures

A structured questionnaire was developed based on the objectives of the study after reviewing previous literatures. The questionnaire includes information about respondent socio-demographic characteristics, their awareness and perception regarding CBHI, and questions about health-related factors. Four data collectors (health extension workers) and two supervisors (clinical nurses) were trained about the aim of the study the actual data collection.

Data quality control

The questionnaire was first prepared in the English language, then it is translated to the local language and to check the consistency of translation, the language expert translated it back to English. To check the uniformity of responses and understandability of the questions, the questionnaire was pre-tested in randomly selected 41 households at DebreSina District, North Shoa zone. Principal investigator and supervisors daily supervised the well trained data collection process, and they checked for completeness and uniformity of responses.

Data management and analysis

Data was entered using EPi-data version 3.3 and exported into SPSS version 20.0 for analysis. Different frequency tables, graphs and descriptive summaries were used to describe the study variables.

Bivariable logistic regression analysis was used to see significance of association between dependent and independent variable. In the bivariable analysis if the p-value ˂ 0.20 it was transferred to the multivariable logistic regression analysis, which help to control confounders. Odds ratioand 95% confidence interval are computed to measure the strength of the association between the outcome and the explanatory variables. P-value ˂0.05 considered as a statistical significant.

Results

Socio-demographic characteristics

In this study, 503 respondents took part with a 95.0% response rate. Around, 65.0% (327) respondents were male and 40.4% (203) of respondents were in the age group of 30 to 39 years while the median age being 35 years old. The majorities (85.7% (431)) of respondents’ religious belief were Orthodox and 66.4% (334) were Amhara in their ethnic group. Around 76.1% (383) of respondents were married and 40.0% (201) had no formal education. Regarding monthly income, 239 (47.5%) households earned over 2000 birr per month (Table 1).

Table 1 Socio-demographic characteristics of respondents, BassonaWorenaWoreda, Ethiopia 2020 (n= 503)

Concerning the health status of the respondents and their family members, 46.7% (235) of them said their family health status was good and 2.4% (12) believed their family has very poor health status. Around 45.3% (228) said as their family fallen ill in the last six months.

Respondent’s awareness and perception on community based health insurance

Regarding respondent awareness about CBHI, 86.5% (435) of them heard about CBHI and they are classified as aware group. Respondents who ever heard about CBHI scheme were asked about their source of information and 15.3% (77) of them heard about CBHI from neighbors or friends, 55.9% (281) heard from CBHI officials.

Concerning perception towards CBHI scheme, only 37.5% (352) of respondents said CBHI enrollment should not be only for those who are sick. Around 72.2% (363) of them agreed only very poor who cannot afford to pay for health care need to join the CBHI scheme. About 44.6% (362) respondents agreed under CBHI program, people pay money to finance future health care needs (Table 2).

Table 2 Respondent’s perception about CBHI, BassonaWorenaWoreda, Ethiopia 2020

CBHI utilization

Among the total 503 respondents, 58.6% (295) of them reported as they were member of CBHI scheme. From the insured respondents 70.2% (207) visited health facility for illness. Among those who didn’t visit health facility about 58.0% (51) of them said it was not necessary. Among respondent who visited health facility for illness felt in the last six months, about half 49.3% of them were satisfied by the services given, 49.3% (102) of respondents said the waiting time to get services were less than thirty minutes and 37.2% (77) of them replied as drugs were usually available in the health facility, around 71.5% (211) of CBHI members used the scheme to cover the cost for the health services they got. For 65.5% (55) of the respondents, the major reason for not being a CBHI member was that no household member has visited health facilities which were reported by.

From the total insured CBHI members, 20.3% (60) mentioned that they will not renew their membership and absence of household member that has visited health facilities were a reason mentioned by 60.0% (36) of the respondents. Around 16.7% (10) of them said its due to limited availability and poor quality of health services, 13.3% (8) of them assumed that the quality of service for CBHI members is not as good as for non-CBHI members and 10.0% (6) of them said the registration fee and premiums are not affordable (Table 3).

Table 3 Respondents CBHI utilization, BassonaWorenaWoreda, Ethiopia 2020

Factors associated with community based health insurance utilization

In bivariate analysis, variables that showed significant association with CBHI utilization with p value < 0.2 were included in the multiple logistic regression analysis (Table 4). Based on the analysis output, socio-demographic characteristics (such as age, sex, religion, ethnicity, marital status, educational level and monthly income,) and awareness about CBHI, perception towards CBHI, health status and illness experiences of family were significantly associated with CBHI utilization.

Table 4 Factors associated with CBHI utilization, BassonaWorenaWoreda, Ethiopia 2020 (n= 503)

In multivariable logistic regression analysis level of educational, awareness about CBHI, perception towards CBHI and illness experience of family showed a significant association with CBHI utilization. Respondents who had primary and secondary educational level were 2 times more likely to be CBHI member than those who didn’t have formal education (AOR = 2.336; 95% CI=: 1.168, 4.673). Respondents who had no awareness about CBHI were 0.27 times less likely to become CBHI members compared to those who had awareness about the scheme (AOR = 0.270; 95% CI=: 0.113, 0.648). Likewise, respondents who do not perceived CBHI scheme meets their household requirement were 0.188 times less likely to utilize CBHI than those who had perceived the CBHI benefit package meets their household requirement (AOR = 0.188; 95% CI=: 00.085, 0.412). Furthermore, utilization of CBHI among respondents who did not experience illness was 0.27 times less likely to utilize CBHI than who experienced illness in the last six months (AOR = 0.272; 95% CI=: 0.164, 0.451).

Discussion

The main purpose of this study was to assess CBHI utilization in BassonaWorena Woreda, North Shoa Zone, Ethiopia. This study also identified factors that associated with CBHI utilization. The result of this study revealed that only 58.6% of respondents were CBHI member. This finding is in line with study conducted in West Gojjam Zone, Northwest Ethiopia in which 58.0% of the study respondents were CBHI members [17]. But, different from a descriptive study in Gida Ayanan Ditrict, Oromia Region, West Ethiopia (27.5%) [16]. on a study done on determinants of CBHI enrollment and renewing among households in rural Southwestern Uganda (44%) [15]. The possible cause of the discrepancy could be due to the variation in access to information regarding CBHI.

In this study one of factors that affected CBHI utilization was respondent educational level. This study found out that respondents who had primary and secondary educational level were 2 times more likely to be CBHI member than those who hadn’t joined a formal education. Similar finding reported from study conducted in South India where higher education showed statistically significant positive association with CBHI scheme utilization [19]. Several studies also revealed that educational status was factor that showed statistically significant association with decision to enroll in CBHI [20, 21].  Individuals who have higher educational level might know the importance and method of risk sharing in CBHI which can lead them to become a member [16].

Majority (86.5) of this study respondent had awareness about CBHI. This result is higher than CBHI utilization reported from study that examined dropping out of Ethiopians CBHI scheme where 69% of CBHI uptake found [22]. The difference seen could be due to extensive awareness creation campaign done by CBHI officials in recent time. The result of this study further showed that respondents who ever heard about CBHI scheme were asked about their source of information and majority, 55.9% of them heard from CBHI officials.

In addition, this study finding showed that respondents who had no awareness about CBHI were less likely to be CBHI member compared to those who had awareness about the scheme. Similarly, a community based cross-sectional study conducted in Kenya reported that awareness about CBHI scheme had significant association with decision to enroll in CBHI [23]. The possible explanation might be knowing the benefits of enrolling in the CBHI scheme changes their health seeking practice [16].

Positive perception and understanding the CBHI benefit packages facilitate utilization of the scheme. In this study respondents who do not perceived CBHI scheme meets their household requirement were less likely to utilize CBHI than those who had perceived the CBHI benefit package meets their household requirement. Study done in Edo state of Nigeria revealed that perception of CBHI scheme meets household requirement had negative association with CBHI utilization [24].

Even though, no particular illness specified in this study respondents who had history of familiar illness in the last six months were more likely to be CBHI member. Nevertheless, respondents who did not experience illness were less likely to be CBHI member. This result is similar with study conducted in Cameroon which reported family with history of illness had more tendencies to uptake CBHI scheme [25]. This could be due to if there is familiar history of illness there might be higher health care expenses that increases the likelihood to enroll in CBHI.

From the total insured CBHI members, about 20.3% of them would not renew their membership for the following year and their reason to did not renew their membership were no one in my HH has visited health facilities, limited availability and poor quality of health services and the quality of service for CBHI members is not as good as for non-CBHI members. This result is supported by study conducted in Burkina Faso [26].

Conclusion and recommendation

This study found that even though most of respondents have awareness about CBHI, the utilization of is low. Educational status, awareness about CBHI, perception towards CBHI scheme and illness experience of family, influence CBHI utilization. Furthermore, limited availability of drugs, poor quality of services and the quality of the services for CBHI members are not as good as for non-member are the important reasons for CBHI member to do not renew their membership in the following year. In order to improve the CBHI utilization, there should be a strong monitoring evaluation system to ensure the quality of services and availability of drugs for CBHI members, local level information dissemination regarding the benefit of CBHI scheme, the amount of premium paid and the period of payment for renewal should be strengthened. This study can be used as baseline information for further studies on this topic to explore reasons for low utilization of CBHI scheme by assessing challenges and opportunities.

Availability of data and materials

The datasets generated during the current study are not publicly available due to participants have not agreed to make this dataset publically available. But it will be available from the corresponding author on reasonable request after making adjustments to hide anonymity of the participants.

Abbreviations

AOR:

Adjusted Odds Ratio

CBHI:

Community Based Health Insurance

COR:

Crude Odds Ratio

OOP:

Out of Pocket

LMIC:

Low and Middle Income Countries

SPSS:

Statistical Package for the Social Sciences

WHO:

World Health Organization

References

  1. WHO. Recommendations action: international conference on social insurance in developing countries. In: Extending Social Protection in Health: Developing Countries’ Experiences, Lessons Learnt and Recommendations. Berlin: ILO, GTZ and WHO; 2017. p. 168–75.

    Google Scholar 

  2. McIntyre D. Learning from experience: Health care financing in low-and middle-income countries. Switzerland: Global Forum for Health Research Geneva; 2007.

  3. Preker AS, Carrin G. Health financing for poor people: Resource mobilization and risk sharing. Washington, DC: World Bank; 2014.

  4. Carrin G. Community based health insurance schemes in developing countries: Facts, problems and perspectives. 2013.

    Google Scholar 

  5. Adebayo EF, Uthman OA, Wiysonge CS, Stern EA, Lamont KT, Ataguba JE. A systematic review of factors that affect uptake of community-based health insurance in low-income and middle-income countries. BMC Health Serv Res. 2015;15:543.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Guy C. Community based health insurance in developing countries: facts, problem & perspectives World helath organization. World health organization conference. Geneva: World Health Organization; 2013.

    Google Scholar 

  7. MLI ML. Reducing financial barriers to reproductive health care: Ethiopia Spoty Light. Addis Ababa: Aspen Global Health & health development; 2013.

    Google Scholar 

  8. WHO. The world health report: health systems financing: the path to Universal coverage. http://www.who.int/whr/2010/en/index.html (Accessed 23 Feb 2020).

  9. EHIA. Evaluation of Community Based Health Insurance Pilot Schemes in Ethiopia Final Report. Addis Ababa: EHIA; 2015.

    Google Scholar 

  10. World Health Organization (WHO). Tracking universal health caverage: 2017 global monitoring report. 2017.

    Book  Google Scholar 

  11. Fadlallah R, El-Jardali F, Hemadi N, Morsi RZ, Abou Samra CA, Ahmad A, et al. Barriers and facilitators to implementation, uptake and sustainability of community-based health insurance schemes in low- and middle-income countries: a systematic review. Int J Equity Health. 2018;17(1):13.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Sudhir Chaitra M, Deepa K. Determinants of Health Insurance in rural population of South India. Indian J forensic community Med. 2015;2(3):172–5.

    Google Scholar 

  13. Soors W, Devadasan N, Durairaj V, Criel B. Community Health Insurance and Universal Coverage: Multiple Paths, Many Rivers to Cross. World Health Report. http://www.who.int/healthsys-tems/topics/financing/. Accessed on 12 Mar 2020.

  14. Onwujekwe O, Onoka C, Uzochukwu B, Okoli C, Obikeze E, Eze S. Is community-based health insurance an equitable strategy for paying for health care? Experiences from South-East Nigeria. Health Policy. 2009;92(1):96–102.

    Article  PubMed  Google Scholar 

  15. Nshakira-Rukundo E, Mussa EC, Nshakira N, Gerber N, von Braun J. Determinants of enrolment and renewing of community-based health insurance in households with under-5 children in rural south-western Uganda. Int J Health Policy Manag. 2019;8(10):593–606. doi:https://doi.org/10.15171/ijhpm.2019.49.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Negash B, Dessie Y, Gobena T. Community Based Health Insurance Utilization and Associated Factors among Informal Workers in Gida Ayana District, Oromia Region, West Ethiopia. East Afr J Health Biomedical Sci. 2019;3(2):13–22.

    Google Scholar 

  17. Hagos TM, Debalkie GD, Andargie GB. Determinants of community-based health insurance implementation in west Gojjam zone, Northwest Ethiopia: a community based cross sectional study design. BMC Health Serv Res. 2019;19:544. https://doi.org/10.1186/s12913-019-4363-z.

    Article  Google Scholar 

  18. Mebratie AD, Sparrow R, Yilma Z, Alemu G, Bedi AS. Enrollment in Ethiopia’s community-based health insurance scheme. World Development. 2015;74:58–76.

  19. Maina JM, Kithuka P, Tororie S. Percep-tions and uptake of health insurance for maternal care in rural Kenya: a cross sectional study. Pan Afr Med J. 2016;34(1):15.

    Google Scholar 

  20. Kebede A, Gebreslassie M, Yitayal M. Willingness to pay for community based health insurance among households in the rural community of Fogera District, north West Ethiopia. Int J Econ Finance Manag Sci. 2014;2(4):263–9.

    Google Scholar 

  21. Bendig M, Thankom A. Enrolment in micro life and health insurance:. evidences from Sri Lanka. 2011.

    Google Scholar 

  22. Mebratie AD, Sparrow R, Yilma Z, Alemu G, Bedi AS. Dropping out of Ethiopia’s community based health insurance scheme. Health Policy Plann. 2015 Dec;30(10):1296–306. PubMed PMID: 25616670. Epub 2015/01/27. eng.

  23. Kimani JK, Ettarh R, Kyobuntungi C, Mberu B, Muindi K. Determinants for participation in health insurance program among residents of urban slum of Kenya, Nairobi, results from cross sectional survey. BMC Health Serv Res. 2012;2012(12):66.

    Article  Google Scholar 

  24. Oriakhi HO, Onemolease EA. Determinants of Rural Household’s Willingness to Participate in Community Based Health Insurance Scheme in Edo State Nigeria. Stud Ethno-Medicine. 2012;6(2):95–102.

    Article  Google Scholar 

  25. Adebayo EFUO, Wiysonge CS, Stern EA, Lamont KT, Ataguba JE. A systematic review of factors that affect uptake of community-based health insurance in low-income and middle-income countries. BMC Health Serv Res. 2015;15:543 PubMed PMID: 26645355. Pubmed Central PMCID: PMC4673712. Epub 2015/12/10. eng.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Dong HDAM, Gnawali D, Souares A, Sauerborn R. Drop-out analysis of community-based health insurance membership at Nouna, Burkina Faso. Health Policy (Amsterdam, Netherlands). 2009;92(2–3):174–9 PubMed PMID: 19394105. Epub 2009/04/28. eng.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

I would like to thank Debre Berhan University, College of Health Science, and Department of Public Health for permitting the execution of this study. I would also like to express my appreciation for the head and staff of BassonaWorena District health bureau.

Funding

This study was funded by Debre Berhan University, College of Health Science, and Department of Public Health. The funder had no role in the study design, in data collection and analysis, in the interpretation or write-up process.

Author information

Authors and Affiliations

Authors

Contributions

TG and LT conceived, developed the study. Regulatory approvals were secured by MH, YA, TG and HG. Data were obtained by LT and HG. The study was monitored and supervised by HG, YA and MH, MH and LT wrote the article, which was revised by TG, LT, YA and HG, it was commented on by all authors. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Mizan Habtemichael.

Ethics declarations

Ethics approval and consent to participate

Letter of ethical clearance and approval were obtained from the Debre Berhan University Institutional Review Board (IRB). Support letter was requested from Debre Berhan University to the North Shoa Zone health department and Bassona Worena district health bureau. Permission to conduct and letter of support were obtained from the North Shoa zone health department and district health bureau. The objective and purpose of the study were explained to the participants. Subsequently, individual written consent was taken from all participants. In order to make sure confidentiality of the information, names of participants were not included in the questionnaire. All methods were performed in accordance with the relevant guidelines and regulations such as Declaration of Helsinki.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Getahun, T., Teklesilassie, L., Habtemichael, M. et al. “Magnitude of community-based health insurance utilization and associated factors in Bassona Worena District, North Shoa Zone, Ethiopia: a community-based cross-sectional study”. BMC Health Serv Res 22, 1405 (2022). https://doi.org/10.1186/s12913-022-08794-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12913-022-08794-6

Keywords