Community perceptions of health insurance and their preferred design features: implications for the design of universal health coverage reforms in Kenya

Abstract

BackgroundHealth insurance is currently being considered as a mechanism for promoting progress to universal health coverage (UHC) in many African countries. The concept of health insurance is relatively new in Africa, it is hardly well understood and remains unclear how it will function in countries where the majority of the population work outside the formal sector. Kenya has been considering introducing a national health insurance scheme (NHIS) since 2004. Progress has been slow, but commitment to achieve UHC through a NHIS remains. This study contributes to this process by exploring communities’ understanding and perceptions of health insurance and their preferred designs features. Communities are the major beneficiaries of UHC reforms. Kenyans should understand the implications of health financing reforms and their preferred design features considered to ensure acceptability and sustainability.MethodsData presented in this paper are part of a study that explored feasibility of health insurance in Kenya. Data collection methods included a cross-sectional household survey (n = 594 households) and focus group discussions (n = 16).ResultsAbout half of the household survey respondents had at least one member in a health insurance scheme. There was high awareness of health insurance schemes but limited knowledge of how health insurance functions as well as understanding of key concepts related to income and risk cross-subsidization. Wide dissatisfaction with the public health system was reported. However, the government was the most preferred and trusted agency for collecting revenue as part of a NHIS. People preferred a comprehensive benefit package that included inpatient and outpatient care with no co-payments. Affordability of premiums, timing of contributions and the extent to which population needs would be met under a contributory scheme were major issues of concern for a NHIS design. Possibilities of funding health care through tax instead of NHIS were raised and preferred by the majority.ConclusionThis study provides important information on community understanding and perceptions of health insurance. As Kenya continues to prepare for UHC, it is important that communities are educated and engaged to ensure that the NHIS is acceptable to the population it serves.

Perception and Motivation of National Health Insurance Program Participation in Bogor

“…According to Sutisna (2001) brand image represents the entire perception of information and past experience to the brand. The results are consistent with research by Mulupi et al (2013) who states that bad perception on the National Health Insurance Program in Kenya happened because of the of poor services provision in health facilities, long waiting times, inadequate benefits and high payments. Therefore, perceptions of information delivered were about National Health Insurance depending on who individual who receives is.…”

Patient costs of hypertension care in public health care facilities in Kenya

“…Kenya is committed towards attaining UHC by 2022 . The Kenyan health sector is funded by different sources including; the government, out‐of‐pocket payments (OOP) and donors . The high level of OOP payments increases the risk of catastrophic health expenditure where households spend a large proportion of their budget on health care, which consequently have negative implications on living standards as they forego other goods and services .…”

Awareness, knowledge, and perception among pharmacists on the National Health Insurance Program in Indonesia

“…[11] The proportion of the result was divided into good and not good perception. [3,9,10] The data are nominal (demographic) and ordinal scale, the distribution is not normal, and the variables are more than two (multivariate); therefore, the non-parametric analysis is structural equation modeling with partial least squares. While for the validity and reliability test, descriptive statistic and Pearson's correlation test were conducted using statistical software RStudio.…”

“…[8] The measurement of the awareness variable consists of five questions with three questions (2, 3, and 4) adopted from Mulupi et al (2013), and two questions (1 and 5) were self-developed with a 1-5 measurement scale from a statement strongly disagree to strongly agree. [9] The measurement of the knowledge variables consists of 20 questions adopted from the NHI socialization handbook by the ministry of health of the Republic of Indonesia with a scale of good knowledge measurement if the answer is true 56-100%, and knowledge is low if the answer is correct ≤55.…”