A total of 97 individuals participated in 14 focus group discussions, of which 49 were insurance enrollees and the remaining 48 were non-enrollees. Most focus group participants were female and had an education below high school. The mean age of participants was 45 years for enrollees and 37 years for non-enrollees. The proportion of respondents who were Dalits (a historically marginalized ethnic group in Nepal), had higher annual income, and used private health facilities explicitly were higher among the non-enrollee group. In contrast, the proportion of those with chronic illness in the family or a history of catastrophic illness in the family was higher among the enrollee group. See Table 2. for demographic and health-related characteristics of focus group participants.
Among the 23 key informants, most (n = 17) were males. The largest percentage of informants were affiliated with hospitals (55%), followed by PHCCs (25%) and HI province/district offices (20%). The informants have been in service with the Nepal government for an average of 11 years (Range: 1–25 years). The mean years of experience with the HI program was 3 (Range 1-4.5 years).
Key Informants and focus group participants described various factors affecting enrollment and renewal in the NHIP, those associated with providing quality healthcare services, as well as with subsequent increases in access and utilization. Rather than being discrete, these factors were found to be overlapping and intricately connected. The interaction between these factors was varying, with some factors being mutually dependent while the others being a consequence of each other. We have tried to capture the intricate relationship between various demand and supply-side factors in health insurance enrollment and health service utilization using a Fishbone diagram (See Fig. 3). The details are described below.
The unavailability of medicine was the primary cause of discontent among insurance enrollees and a primary reason for non-renewal. Beneficiaries of the health facilities with an abundant supply of medicines expressed higher satisfaction with the insurance program and the health facility despite shortcomings in other resources. This sentiment is illustrated by the following statement “My husband has had heart surgery. Previously my son had to send medicine from India. Now, I can get it from here. I am delighted.”
Key informants outlined various reasons for the unavailability of medicine. These reasons included a tedious procurement system, delays in reimbursement from HIB, difficulties in timely convening Health Facility Management Committee (HFMC) meetings, frequent absence of medical officers required for purchase approval, and shortage of essential medicines under free health services (which are not covered by HIB).
A significant number of insurance enrollees reported feeling discriminated against. One enrollee stated, “They provide different medicine for non-enrollees and cheap, low-quality medicine for us. Even if medicine is available, they withhold it once we show our insurance card.”
Many service providers confirmed that they maintained different sets of medicine, offering the cheapest available medicine to enrollees, as HIB encourages the use of generic drugs and has a specific fixed payment rate for the medicine. This situation has led to trust issues with the medicines available under the insurance program. Mistrust has escalated as the doctors often prescribe medicine using brand names which does not match the name of medicine people receive from pharmacies. Doctors attributed this practice to the lack of information about prescribing with generic names. Few physicians were also wary of writing the generic name, claiming differences in the efficacies of medicines depending on the brand.
Similarly, the lack of diagnostic facilities significantly influenced referral requirements, as people were reluctant to spend time navigating multiple health facilities in search of appropriate treatment. Most participants voiced concerns regarding the lack of diagnostic services in public facilities. While a few facilities reported acquiring diagnostic equipment through NHIP or community support, they lamented the lack of skilled workforce to utilize these resources effectively. Others attributed their inability to utilize these resources to an increased workload, which does not allow time to use these resources.
Availability of service providers and their behavior
Many focus group participants mentioned the unavailability of skilled health workers and their unpleasant behavior as their prime reason for avoiding public health facilities. One participant expressed frustration, stating, “We rarely see doctors, and we are not even talking about specialties... we never receive prior notice about their leave. We wait in line for hours and then find out the doctor is on leave.”
Service providers from public facilities complained of not having a concomitant increase in staff and infrastructure as per increased patient flow and administrative workload. PHCCs typically have only one sanctioned doctor’s position, which often remains vacant. Some PHCCs with strong HFMCs have advocated to Village Councils to hire new staff and provide training to existing staff. Certain PHCCs have utilized personal connections to temporarily assign health service providers from the Nepal government. While the contractual assignment of doctors somewhat addressed the issue of physician scarcity in rural areas, the practice of rotating doctors every 2–3 years has led to frequent training and onboarding needs for new personnel. This process has resulted in the doctors being away from the health facility for extended periods. Additionally, issues have also arisen due to staff transfers and a lack of sanctioned positions, such as pharmacist or administrative assistants, needed to meet NHIP requirements. The high turnover rate among staff has created a gap in orientation and training on NHIP components.
A few respondents, particularly the front-line service providers, expressed their frustration in dealing with beneficiaries’ misconceptions and expectations. Some reported facing numerous “unreasonable” demands, including requests for fruits juices, unnecessary referrals to higher centers, and transportation costs from insurance enrollees. One service provider voiced their concern, saying, “We are already overwhelmed by increased patient flow and do not have time to address the misunderstandings. When people start complaining and arguing, it becomes very difficult to maintain a calm demeanor.”
Wait time
Participants reported long wait times as a significant deterrent to choosing public health facilities. Wait times were already an issue in public health facilities, and they worsened with an increased patient flow and constricted time for patient care caused by administrative burdens.
The NHIP’s requirement for establishing a primary contact point and need for referral has amplified the patient flow in public health facilities. Furthermore, the referral card remains valid for only 7 days, necessitating patients to obtain a new referral for follow-up visits after being discharged from referral centers. Patients must be physically present to receive a referral, as service providers claimed they cannot process claims without examining patients. One participant shared, “It took me over seven days to arrange and secure an appointment at the tertiary health center and my referral card expired by then. Since I had to return to village to obtain another referral card, which I couldn’t manage, I couldn’t use my insurance card.” Although the patient flow has significantly increased in public facilities, particularly PHCCs, the number of individuals actually receiving services remains relatively low. As one informant explained, “Lately we don’t have doctors. So, we mostly have referral cases. We refer 15–20 patients in a day.” Additionally, patients often request referrals specifically for private facilities, as private facilities can only take referral or emergency cases.
The new reporting requirement of IMIS and the lack of interconnectedness between IMIS and other existing reporting systems, such as DHIS-2 and hospital servers, have heightened the administrative burden on staff. Rural facilities also complained about poor internet coverage in the area, which slows down the reporting process. Moreover, many informants found the claim system confusing. Several participants raised concerns about issues when claiming multiple diagnoses, providing services due to unforeseen complications, and problems in writing diagnoses, especially for symptomatic management.
Private facilities did not have issues with lack of service providers or medicine availability, and wait times. However, they charged insurance enrollees the difference (gap amount) between NHIP coverage and hospital’s rate. A representative from a private hospital stated, “the rate provided by HIB is too low. We either offer inadequate care or face financial difficulties. Providing subpar care would harm our reputation, so we charge patients to cover the cost difference.” Unfortunately, this situation has led to misunderstandings about NHIP, as patients were initially promised no copayments and coinsurance within the insurance program.
Choice of health facilities depended on the perceived quality of health services, geographic accessibility, and ability of the health facilities to cater the needs of special populations, such as children, the elderly, and individuals with disabilities. People often favored private facilities or sought treatment in India (in the case of border districts). This has reduced the demand for NHIP since only select private facilities accept insurance. Factors such as the distance to primary service point, lack of transportation options, the higher opportunity cost of seeking treatment from government facilities with long wait time (including the cost of living in city, loss of productivity, and childcare concerns), and service providers behavior were some major reasons for enrollees to opt for services from private facilities.
Lack of awareness about NHIP was another significant factor influencing enrollment. Mass media information did not appear to be sufficient, as many non-enrollees had not even heard about the program. Many EAs, who were supposed to conduct door-to-door visits, tended to avoid targeting the uneducated, lower income, and hard to reach population due to the time it took to persuade them to enroll in the program. Furthermore, many people did not trust EAs, perceiving them as “insurance agents.” Health care providers, who are usually a trusted source, neither possessed sufficient knowledge nor had time to provide information. The absence of insurance registration services at health facilities further compounded the issue.
Among insurance enrollees, health insurance literacy played a significant role in the renewal process. The lack of comprehensive information resulted in misunderstandings, leading to discontentment with the program. One participant explained “When enrolling us, they assured that everything would be covered. But the health facility denied reimbursements. So, I did not renew the insurance anymore..” This discontentment not only impacted renewal rates but also triggered negative word-of-mouth, dissuading potential new people from getting insured as one participant mentioned “No one has shared a positive experience. Even the insured people do not recommend that we enroll”.
Ability to pay for premiums
Despite the policy provision to subsidize premiums for the poor, individuals with low-income status exhibited low enrollment rates, primarily due to the absence of an effective mechanism for means-testing. The current poverty list, established from a survey conducted a few years ago, does not accurately reflect the reality. One participant shared “The actual poor are not on that poverty list. We do not know how they compiled that poverty list when no one visited our village.”
Furthermore, the process of identifying poverty has not been fully completed, leading to a significant proportion of impoverished individuals remaining uninsured. Participants also emphasized that EAs had not reached out to poor people. Conversely, EAs expressed apprehension about using the poverty list, as one explained, “I witnessed a community dispute arising from the poverty list and I don’t want to entangle with that.”
The perceived risk of getting ill played a significant role in enrollment. Primarily, individuals with chronic illnesses and those requiring regular medications were inclined to enroll in the program. However, enrollment was often dependent on the availability of medicine at the primary service center. Families with more than five members typically refrained from enrolling those who were less likely to get sick, usually the youngest members.
Interestingly, the possibility of catastrophic illness or accidents did not motivate people to enroll in the program, likely due to reported poor service quality of public health facilities. As one participant elucidated, “Although I am insured, I might not use it during acute events like accidents or emergencies due to the significant delays in receiving service at government facilities.”
Perceived usefulness of health insurance
Both KIs and focus group participants appreciated the concept of insurance, but many did not perceive it as useful. People claimed they did not need insurance for minor illnesses. A concurrent free health service program and other alternative financing mechanisms (such as a separate health care system for public service employees and uniformed service employees, private insurance schemes for private-sector employees) reduced the necessity of NHIP’s safety net. The absence of major tertiary referral centers and private hospitals within the list of service providers also diminished the program’s usefulness. As one participant explained, “We receive free check-ups and basic medicines from our nearest health posts. Even with insurance, we won’t get medicines and need to visit private hospitals regardless. So, there is no point in getting insurance.” The service lag time (ranging between 1 to 4 months), especially applied for service reactivation if enrollment were to expire, was another significant factor.
As many focus group participants complained of overcrowding, and Key informants reported a substantial increase in patient visits- approximately between 20–70%- after adopting NHIP, we examined the treatment effect of policy on patient visits between intervention and comparator districts using the DID method. The findings (summarized in table 3) suggested an increase in the average number of total and new client visits by 4,729 and 2,7,21, respectively, in overall health facilities of intervention districts compared to comparator districts, due to policy’s effect. Similarly, the average number of referral outs increased by 163 in intervention districts. However, only referral outs were statistically significant at 5%. In subgroup analysis, we found a statistically significant increase in clients visits and referrals for PHCCs but not for hospitals. Nonetheless, the findings indicated an increase in client visits by an average of 9 clients per day in PHCCs and 32 clients per day in hospitals.
Table 3: Difference in Difference estimation
Variable | Interaction co-eff | 95% CI | p-value |
All health facilities | | | | |
Total client visits | 4729 | -3801 | 13259 | 0.28 |
New client visits | 2721 | -4207 | 9649 | 0.44 |
Total referral outs | 163 | 58 | 268 | 0.01* |
Sub-group analysis | | | | |
Hospitals | | | | |
Total client visits | 10072 | -20527 | 40671 | 0.52 |
New client visits | 5065 | -20363 | 30493 | 0.69 |
Total referral outs | 39 | -212 | 290 | 0.76 |
PHCCs | | | | |
Total client visits | 3051 | -731 | 6833 | 0.1** |
New client visits | 2031 | -306 | 4368 | 0.09** |
Total referral outs | 192 | 88 | 296 | < 0.001* |
H 0 : the means are not different. *P < 0.05: reject null hypothesis at 5%. **P < 0.1: reject null hypothesis at 10%.