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Optimal Design of Population-Level Financial Incentives of Influenza Vaccination for the Elderly
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Contents lists available at sciencedirect.com Journal homepage: www.elsevier.com/locate/jval
Optimal Design of Population-Level Financial Incentives of Influenza Vaccination for the Elderly Mu Yue, PhD,1,2 Yi Wang, PhD,2 Chng Kiat Low, BSc,3 Joanne Su-yin Yoong, PhD,4,5 Alex R. Cook, PhD2,3,6,* 1 School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan, China; 2Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore; 3Department of Statistics and Applied Probability, National University of Singapore, Singapore; 4Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA; 5Yong Loo Lin School of Medicine, National University of Singapore, Singapore; 6Duke-NUS Medical School Singapore, Singapore.
A B S T R A C T Objectives: To identify how monetary incentives affect influenza vaccination uptake rate using a randomized control experiment and to subsequently design an optimal incentive program in Singapore, a high-income country with a market-based healthcare system. Methods: 4000 people aged $65 were randomly assigned to 4 treatment groups (1000 each) and were offered a monetary incentive (in shopping vouchers) if they chose to participate. The baseline group was invited to complete a questionnaire with incentives of 10 Singapore dollars (SGD; where 1 SGD z 0.73 USD), whereas the other three groups were invited to complete the questionnaire and be vaccinated against influenza at their own cost of around 32 SGD, in return for incentives of 10, 20, or 30 SGD. Results: Increasing the total incentive for vaccination and reporting from 10 to 20 SGD increased participation in vaccination from 4.5% to 7.5% (P , .001). Increasing the total incentive from 20 to 30 SGD increased the participation rate to 9.2%, but this was not statistically significantly different from a 20-SGD incentive. The group of nonworking elderly were more sensitive to changes in incentives than those who worked. In addition to working status, the effects of increasing incentives on influenza vaccination rates differed by ethnicity, socio-economic status, household size, and a measure of social resilience. There were no significant differential effects by age group, gender, or education, however. The cost of the program per completed vaccination under a 20-SGD incentive is 36.80 SGD, which was the lowest among the three intervention arms. For a hypothetical population-level financial incentive program to promote influenza vaccination among the elderly, accounting for transmission dynamics, an incentive between 10 and 20 SGD minimizes the cost per completed vaccination from both governmental and health system perspectives. Conclusions: Appropriate monetary incentives can boost influenza vaccination rates. Increasing monetary incentives for vaccination from 10 to 20 SGD can improve the influenza vaccination uptake rate, but further increasing the monetary incentive to 30 SGD results in no additional gains. A partial incentive may therefore be considered to improve vaccination coverage in this high-risk group. Keywords: incentivization, influenza, vaccination. VALUE HEALTH. 2019; -(-):-–-
Introduction In the equatorial city-state of Singapore, the health and economic burden of influenza is large. The rate of influenzaassociated hospitalizations in Singapore was 29.6 per 100 000 person-years during 2010 to 2012,1 with death rates at 14.8 per 100 000 person-years.2 Approximately 12% of hospitalizations owing to pneumonia were also attributable to influenza.1 Influenza is a major cause of disease burden among the elderly
(65 years or older), with a study by Chow et al concluding that influenza-associated deaths were 11.3 times higher in this age group compared with the general population.3 Individuals 75 years or older have influenza-related hospitalization rates 47 times higher than those who are between 25 and 44 years old.1 In light of the greater risks of influenza morbidity and mortality among the elderly, studies in temperate settings have demonstrated that vaccinating the aged population against influenza is potentially cost-effective.4,5
* Address correspondence to: Alex R. Cook, PhD, Saw Swee Hock School of Public Health, National University of Singapore, Tahir Foundation Bldg, 12 Science Dr 2, Singapore 117549. Email: [email protected] 1098-3015 - see front matter Copyright ª 2019, ISPOR–The Professional Society for Health Economics and Outcomes Research. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). https://doi.org/10.1016/j.jval.2019.08.006
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In contrast with most other developed countries, there is a lack of obvious seasonality in Singapore. Influenza circulates year-round with 2 periods of slightly elevated transmission from December to February and May to July, but outbreaks may occur between these intervals.6 The absence of winter and the low climatic variability across the year leads to an unusual pattern of quasi-random infectious disease outbreaks,7 making it difficult to predict when these epidemics will actually occur throughout the calendar year. As a result, there is no seasonal cue to go for vaccination, unlike in temperate settings. Thus, although Singapore’s Ministry of Health recommends vaccination against influenza for high-risk groups to prevent severe infections and mortality,8 as in most high-income countries,9,10 the coverage rate is disappointingly low (15% in preschool children and 17% in the elderly 65 or older6,8). Indeed, only about 17% of those 65 years or older reported receiving the seasonal influenza vaccination in the 2013 National Health Surveillance Survey (NHSS) of Singapore,8 an uptake rate that was about the same as that of the uptake rate among the lower risk group of young adults aged between 18 and 29 (16.9%).1 To improve the vaccination coverage rate, since 2014, Singaporeans and permanent residents have been allowed to use balances held in the national medical savings scheme Medisave (a mandatory individual medical savings account) to cover the cost of the influenza vaccination for those 65 or older, 5 or younger, pregnant women, and other at-risk groups, removing the out-of-pocket cost as a potential barrier.1 Despite this policy change, vaccine uptake rates remain low among high-risk groups and new approaches may be needed to afford the elderly the greatest benefits from vaccination. Unlike health interventions where the benefits are restricted to the patient receiving them, vaccination leads to a positive externality—specifically, herd immunity—that benefits society at large.11 This may justify government incentives for vaccination to align societal and individual objectives. Past trials conducted in the United States on interventions using monetary incentives among undergraduates12 or during pandemics have been shown to be effective in increasing the uptake rate of influenza vaccination,13 but the most cost-effective level of incentive for influenza vaccination to improve uptake rates within the elderly population is unclear. To this end, we designed a randomized incentivization experiment, delivered at low cost through the postal system, to model a hypothetical national program. The experimental design involved drawing potential participants from an existing cohort study, randomly assigning them to study arms—which differed in the amount of incentive proffered—and then sending them an invitation to participate. Potential participants were asked to complete a questionnaire and, for the intervention arms, to go receive the influenza vaccine at a clinic of their choice. Those who agreed and returned the questionnaire and, for the intervention arms, returned evidence that they were vaccinated in a fixed period after we wrote to them were rewarded with vouchers with values that depended on the arm. The outcomes of interest in each arm were the participation rates and the characteristics of the participants. Through the experiment, we quantified the trade-off between the costs of increasing incentives of influenza vaccination and the higher participation rates that resulted, identified which population groups were most influenced by such an incentive, and determined an optimal incentive level.
Methods Study Design A randomized experiment was conducted in Singapore from June to August 2018. The experiment was implemented using 4
incentive structures to promote influenza vaccination uptake. The instructions for the study, a questionnaire, a preaddressed stamped envelope, and a brochure describing the costs and benefits of taking the influenza vaccine were sent to potential participants through the post. Invitees who chose to participate provided consent by mailing their completed questionnaire back to the research team. The primary outcome measurement was the return rate in each arm, which was used to assess if greater incentives led to a higher vaccination uptake rate and what the optimal incentive from the government and health system perspectives should be.
Participants, Random Assignment, and Blinding Participants from the Singapore population health study14 who expressed interest in participating in future healthcare-related studies and were 65 or older were identified as potential participants in this study. After assessing their eligibility, we randomly sampled 4000 people to invite to take part. These individuals were randomly assigned to the 4 treatment groups using computer-generated random numbers. Subjects within each treatment group were blinded to the existence of the other treatment groups and made their decision to participate in the questionnaire and vaccination based solely on the information provided to them. Subjects were not blinded to the financial incentive before agreeing to participate. The original number of potential participants in each arm were the same, but the final number of participants was different. Questionnaire data is not available for the invitees who did not consent to participate, although they are known to come from the same pool of potential participants as the other arms. Ethical approval for the use of human subjects in this study was obtained from the Institutional Review Board of the National University of Singapore.
Treatment Groups Invitees who wished to participate were asked to complete their task within 2 months and were rewarded with varying amounts of monetary incentives in the form of shopping vouchers. After verifying the completion, compensation was mailed to the participants. The study initially had 7 arms: arm 1 was invited to complete a questionnaire with an incentive of 10 SGD, whereas arms 2 to 4 were invited to complete the questionnaire and be vaccinated against influenza at their own cost of 32 SGD in return for incentives of 10, 20, and 30 SGD, respectively. Because the incentives we offered were shopping vouchers available in multiples of 10 SGD, we used shopping vouchers with a value 30 SGD to approximate the policy of free vaccines. Arm 5 participants were required to receive the influenza vaccine and complete the questionnaire without incentives; arm 6 were required to receive the influenza vaccine and complete the questionnaire with an incentive of 10 SGD and an additional 10 SGD for each participant they recruited to complete the study; and arm 7, the group referred by the participants in arm 6, were required to receive the influenza vaccine and complete the questionnaire with an incentive of 10 SGD. We tried to send the study instructions to 1000 people for each of the arms 1 to 5 and 500 people for arm 6. Sample sizes were assessed based on a Monte Carlo analysis of the number vaccinated per 1000 SGD, using a permutation test. Arm 5 was removed from further analysis owing to contamination of the sample at the printing stage, and arms 6 and 7 were removed from analysis owing to extremely low participation rates (further details may be found in the Supplemental Materials at https://doi. org/10.1016/j.jval.2019.08.006). Therefore, arms 1 to 4 were left for
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final analysis. Arm 1 served as a proxy for the demographics of those who were willing to consider taking part in the study. Comparing arms 1 and 2 isolated the effect on the return rate of having to be vaccinated, whereas comparing arms 2, 3, and 4 identified how the elderly respond to higher financial incentives.
Questionnaire The questionnaire consisted of 16 questions in 4 sections (a copy may be found in Appendix Section 1 in Supplemental Materials found at https://doi.org/10.1016/j.jval.2019.08.006). The first section contained questions relating to the general information about the participants, such as age, ethnicity, gender, education, housing type, working status, and health-related characteristics. The second section measured sociability and loneliness, using the number of cohabitants and the number of confidants as a proxy for these attributes. The third section assessed their financial situation. The final section contained questions that measured attitude to influenza vaccination by asking the number of times they had been vaccinated in the last two years, their preferred place to get the influenza vaccine, and their attitudes about the efficacy and safety of influenza vaccination. The questionnaire was developed in English, and forward and back translated into simplified Chinese and Malay, the national language. User acceptability testing was performed on 20 colleagues. All materials sent were tested for ease of interpretation and for legibility, using readable fonts, short sentences, and lay terms where possible.
Statistical Analysis All statistical analyses used R.15
Questionnaire data
Missing values in returned questionnaires were ,1% of possible cells. Within each arm, missing values for categorical variables were imputed by the mode of nonmissing cases of those variables and missing values for continuous variables (eg, age) were imputed by the median. Smaller strata that did not have sufficient numbers for analysis were aggregated with similar strata for analysis. Detailed information about the regrouping can be found in Section 2 in Supplemental Materials (found at https://doi.org/10.1016/j.jval.2019.08.006).
Participation rates The main outcome variable was participation in the study within 2 months. For arm 1, this meant returning the questionnaire. For all the other arms, it meant returning both the questionnaire and a vaccination certificate dated within the period of June 22 to August 22, 2018 that indicated the recipient was the person we invited. Participation rates for each arm were calculated by using the number of valid responses divided by the following denominator: the number of elderly invitees whom we tried to mail minus the letters that were returned undelivered and those invitees who replied but had received the influenza vaccination before the study. Those who did not participate but were prompted to go for vaccination because of the information letter are not captured by the study design but are anticipated to be few. We tested whether participation rates were equal among all, or pairs of, treatment groups using Pearson’s chi-square test. Because the demographics and other potential risk factors are not known for individuals who did not participate, it was not possible to relate an individual’s participation to risk factors using standard regression techniques. However, as shown in Section 4.2 in Supplemental Materials (found at https://doi.org/10.1016/j.jval.2 019.08.006), we were able to assess the distribution of risk
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factors among responders in the different arms and thereby test (using a chi-square test) whether the incentivization affected the subgroups equally. We denote pis to be the probability that a subject belonging to stratum s is willing to participate in the study if invited to arm i. Although ps i cannot be estimated for this study . design, the ratio b p is b for arms i and j can be obtained and p js . whether pis p is equal to 1 can be tested. More details on the js derivation of the test can be found in Section 4.3 in Supplemental Materials (found at https://doi.org/10.1016/j.jval.2019.08.006). The methods of using the ratio of the participation rates and using the chi-square test could both answer the question of whether the participation rate in each stratum for any 2 incentive groups are equal (within each subgroup, whether the elderly respond to higher incentives by comparing 10 vs 20 SGD, 10 vs 30 SGD, and 20 vs 30 SGD). Nevertheless, for the chi-square test, the corresponding P value is obtained via exact calculation, whereas for the use of the ratio of the participation rates, the confidence interval (CI) is based on approximation, and thus the corresponding P value is also approximated. To test whether the demographic strata had differences in uptake rates per 10 SGD increment in the vaccination incentive (whether people from each subgroup responded to the higher incentives to the same degree), we fit a Poisson model to the number of respondents, Yis, for intervention i=0,1,2 for arms 2, 3, and 4 respectively, and for stratum s, with mean as 1 bs 3 i. Under this model, which uses a linear model to pool information between arms, bs quantifies the increase in the number of participants in stratum s as the incentive increases by 10 SGD. We tested whether bs is the same for all strata s using the likelihood ratio test. More details on the derivation of the test can be found in Section 4.5 in Supplemental Materials (found at https://doi.org/10.1016/j.jval.2019.08.006).
Cost analysis The costs incurred per eventuated influenza vaccination were derived from the cost of the incentive for those who obtained vaccination and the printing and postage cost for both those who did and did not. We define Ci to be the total cost accrued in incentivizing a single individual in arm i to get the influenza vaccine. Given total printing costs of 1158 SGD and the costs of delivery, that is, in SGD: 1158 1 ðWi 1 0:74Þ 3 Yi 1 0:37 3 Y qi 1 Y pi Ci ¼ Yi where Yi is the number of (valid) responses, Y qi the number of individuals who return a questionnaire but not a vaccination certificate, Yp the number of individuals who return a vaccination certificate for a previous vaccination, and Wi the reimbursement offered to arm i. More details can be found in Section 4.6 in Supplemental Materials (found at https://doi.org/1 0.1016/j.jval.2019.08.006). We used bootstrap with 10 000 resamples, from the numbers of participants, invalid responses, those previously vaccinated, those who had changed their address, and those who declined to respond, to obtain 95% CI for the costs per successful vaccination on each arm. We tested for differences in costs between arms using a bootstrap-based Wald test. Finally, we found the optimal incentive for a population-level vaccination program of the same model as in our study, from both governmental and health systems perspectives, by computing the incremental cost-effectiveness ratio (ICER) of the financial incentive program relative to no program, using output from an individual-based model described elsewhere (Yue et al16).
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The optimal financial incentive is the financial incentive that achieves the smallest ICER, defined as: ICERðxÞ ¼
Costðx; pðxÞÞ 2 Costð0; pð0ÞÞ QALYðpðxÞÞ 2 QALYðpð0ÞÞ
where Cost(x,p(x)) is the total cost of providing financial incentives of x SGD to obtain a fraction p(x) of the population being vaccinated, and QALY(p(x)) is the quality-adjusted life-years (or the life-years saved from not contracting influenza) for the whole Singapore population under the same fraction vaccinated. The cost from the government’s perspective is the financial incentive only and the cost from the health system’s perspective is composed of both the financial incentive and the influenza vaccination cost. The QALYs were derived from mortality, hospitalization, and self-limiting infections. Further details are provided in Section 4 in Supplemental Materials (found at https://doi.org/10.1016/j.jval.2019.08.006).
Results In response to the 4000 letters sent out on June 22, 2018 with a return due date of August 22, 2018, a total of 484 letters were
received, of which 373 were valid (as described in Figure 1). Both trivalent and quadrivalent vaccines are available in Singapore, and most vaccinated participants took the trivalent vaccine. Reasons for invalidity included having recently been vaccinated (ie, sending in evidence of vaccination that predated June 22, 2018), the mail being returned undelivered, or those in arms 2 to 4 returning only a questionnaire but not a vaccination certificate. The overall response rate was therefore 9.3%, and the response rate was highest for arm 1 (who had only to return a questionnaire) at 16.9%. When offering the same amount of monetary compensation (a 10-SGD shopping voucher), requiring participants to also be vaccinated (and to pay for the cost of vaccination by themselves) markedly reduced the participation rate from 16.9% to 4.5% (P , .001). Increasing the total incentive from a 10 SGD to 20 SGD shopping voucher increased the participation rate significantly from 4.5% to 7.5% (P = .006). Further increasing the total incentive from 20 to 30 SGD, however, increased the empirical participation rate by less, from 7.5% to 9.2%, which was not statistically significant. Overall, there was very strong evidence of different response rates among the 4 arms of the study (P , .001). Because many potential participants may have disregarded the study invitation, to approximate the response rate among those
Figure 1. Flow diagram for the experiment, detailing the distribution of responses in each arm. Undelivered indicates number of letters that were undelivered to the potential participants; recent vax, number of letters including previous vaccination certificate to prove that the influenza vaccination had been taken recently; RR, response rate calculated by the ratio of valid responses among the “remaining”; RRR, relative response rate calculated by the ratio of the response rate among the response rate for arm 1.
Prospective participants (N = 4000)
Arm 1 (N = 1000)
Arm 2 (N = 1000)
Arm 3 (N = 1000)
Arm 4 (N = 1000)
Excluded: Undelivered (N = 16) Recent Vax (N = 0)
Excluded: Undelivered (N = 2) Recent Vax (N = 15)
Excluded: Undelivered (N = 15) Recent Vax (N = 17)
Excluded: Undelivered (N = 5) Recent Vax (N = 18)
Remaining: (N = 984)
Remaining: (N = 983)
Remaining: (N = 968)
Remaining: (N = 977)
Valid response: (N = 166) (RR = 16.9%) (RRR = 100.0%)
Valid response: (N = 44) (RR = 4.5%) (RRR = 26.5%)
Valid response: (N = 73) (RR = 7.5%) (RRR = 44.7%)
Valid response: (N = 90) (RR = 9.2%) (RRR = 54.6%)
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who contemplated taking part, we calculated the response rate relative to the baseline group, who were offered 10 SGD for returning a 2-page questionnaire. These were 26.5% (arm 2, 10 SGD), 44.7% (arm 3, 20 SGD), and 54.6% (arm 4, 30 SGD). Demographics of the participants are provided in Table 1, indicating that those who elected to take part were broadly similar to the elderly population as a whole. Most (63%) participants had not received the influenza vaccine in the last 2 years, whereas 21% had been vaccinated once and 16% twice in the last 2 years. Most participants preferred to be vaccinated at a clinic (32% at a general practitioner [GP] clinic and 53% at a public polyclinic). A few favored other places like their home (2%), the hospital (5%), a community center (6%), or a health screening center (2%). Participants had positive perceptions of the safety of vaccination (76% thinking they were safe and only 2% disagreeing), but few perceived themselves as being at risk of infection without being vaccinated (35% agreeing and 22% disagreeing with this proposition).
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The number of participants in each arm by demographic stratum are presented in Figure SI in Supplemental Materials (found at https://doi.org/10.1016/j.jval.2019.08.006). We denote pis to be the probability that a subject belonging to stratum s is willing to participate in the study if invited to arm i. Although pis could not be estimated for this study design, the ratio Pis/pjs for arms i and j could be, which has been tabulated in Table 2 to assess whether the participation rate in each stratum for any 2 incentive groups are equal. The elderly aged 75 or older who were offered a 30-SGD incentive were 4.1 (95% CI 1.3–6.9) times more likely to elect to get vaccinated than when only given 10 SGD, and 3.4 times (95% CI 1.5–8.0) more likely to participate if offered 20 SGD rather than 10 SGD. Although both genders were more likely to participate if offered 30 SGD rather than 10 SGD, only among women was there a statistically significant increase in participation rates when increasing the incentive from 10 SGD to 20 SGD (of 2.0, 95% CI 1.0–3.1). There was evidence that ethnic Chinese responded to increased incentives (Table 2), but
Table 1. Participants’ characteristics. Characteristic
N
%
Population %
Age group
65–69 70–74 75 or older
156 115 102
42 31 27
41* 21* 38*
Ethnicity
Chinese Non-Chinese (of which: Malay Indian Other)
314 59 19 36 4
84 16 5 10 1
84* 16* 9* 6* 1*
Sex
Female Male
170 203
46 54
55* 45*
Education
Below primary education Secondary education Tertiary education
106 213 54
28 57 15
60† 31† 9†
Housing Type
Public housing (small) Public housing (large) Private housing
98 215 60
26 58 16
29† 53† 18†
Number of cohabitants
0–1 2–3 $4
139 165 69
37 44 19
— — —
Working status
Yes No
114 259
31 69
20† 80†
Number of people can confide in
0–2 3–4 $5
160 163 50
43 44 13
— — —
Have health assist card issued by the Community Health Assist Scheme
Yes No Don’t know
196 170 7
52 46 2
— — —
Eligible for the pioneer generation package
Yes No Don’t know
242 117 14
65 31 4
— — —
Have public assistance card
Yes No Don’t know
13 335 25
3 90 7
— — —
Have any diseases
Diabetes Asthma Chronic obstructive pulmonary disease None of the above
97 7 2
28 3 0
— — —
260
69
— †
Population characteristics were derived from the Singapore Yearbook of Statistics 2017* and the General Household Survey 2015 for the resident population aged 65 and older.
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Table 2. Ratios of response rates (ie, pis/pjs) and their 95% confidence intervals. Question
Stratum
Ratio of Response Rates (95% CI) 20 vs 10 SGD
30 vs 20 SGD
30 vs 10 SGD
Age group
65–69 70–74 $75
1.3 (0.6-1.9) 1.8 (0.7-2.9) 3.4 (1.5-8.0)
1.4 (0.7-2.1) 1.1 (0.5-1.7) 1.2 (0.6-1.9)
1.7 (0.9-2.6) 1.9 (0.8-3.1) 4.1 (1.3-6.9)
Ethnicity
Chinese Other
1.6 (1.0-2.2) 3.4 (0.5-6.3)
1.4 (1.0-1.9) 0.5 (0.1-1.0)
2.2 (1.4-3.0) 1.7 (0.1-3.3)
Gender
Male Female
1.6 (0.8-2.3) 2.0 (1.0-3.1)
1.4 (0.9-2.0) 1.1 (0.6-1.5)
2.2 (1.2-3.2) 2.1 (1.0-3.2)
Education
Below primary education Secondary education Tertiary education
1.8 (0.6-3.0) 1.6 (0.9-2.3) 4.5 (0.2-8.9)
1.1 (0.5-1.8) 1.2 (0.8-1.7) 1.6 (0.5-2.8)
2.0 (0.7-3.3) 1.9 (1.1-2.7) 6.7 (0.5-12.9)
Housing type
Public housing (small) Public housing (large) Private housing
2.5 (0.9-4.1) 1.4 (0.7-2.1) 2.2 (0.4-3.9)
0.9 (0.4-1.3) 1.7 (1.0-2.4) 0.8 (0.2-1.4)
2.1 (0.7-3.5) 2.4 (1.3-3.4) 1.6 (0.3-3.0)
Number of cohabitants
0–1 2–3 $4
2.6 (1.1-4.2) 1.4 (0.6-2.2) 1.6 (0.5-2.6)
0.9 (0.5-1.3) 2.2 (1.2-3.2) 0.6 (0.2-1.1)
2.2 (0.9-3.6) 3.0 (1.5-4.4) 0.9 (0.2-1.6)
Working status
Yes No
1.0 (0.4-1.6) 2.3 (1.3-3.4)
1.4 (0.6-2.2) 1.2 (0.8-1.6)
1.3 (0.6-2.1) 2.8 (1.6-4.0)
Number of people can confide in
0–2 3–4 $5
2.5 (1.0-3.9) 1.5 (0.7-2.2) 1.5 (0.3-2.7)
1.2 (0.7-1.8) 1.5 (0.8-2.2) 0.7 (0.1-1.3)
3.0 (1.3-4.7) 2.2 (1.1-3.2) 1.0 (0.1-1.8)
CI indicates confidence interval. The bold values are the 95% CIs cover 0. Information on how these are derived is provided in Section 2 in Supplemental Materials (found at https://doi.org/10.1016/j. jval.2019.08.006).
insufficient numbers of other ethnicities to identify the same pattern held with them. Those who were not working were more sensitive to the amount of incentives, being 2.3 times (95% CI 1.3–3.4) more likely to get vaccinated if offered 20 SGD, and 2.8 times (95% CI 1.6–4.0) if offered 30 SGD rather than 10 SGD.
Differences between the demographic strata in how they responded to different incentive levels are reported in Table 3. The Chinese elderly were more sensitive to the amount of financial incentives than non-Chinese, as were the nonworking elderly compared with the working elderly. Elderly living in different
Table 3. The as, bs and P value from the likelihood ratio test. Question
Stratum
as (95% CI)
bs (95% CI)
Age group
65–69 70–74 $75
21.2 (22.5,44.8) 15.3 (222.5,53.2) 10.0 (246.8,66.8)
7.5 (210.8,25.8) 6.0 (223.3,35.3) 11.0 (233.0,55.0)
.129
Ethnicity
Chinese Other ethnic group
39.5 (25.3,53.7) 7.7 (268.1,83.4)
22.5 (11.5,33.5) 1.0 (257.7,59.7)
.001
Gender
Female Male
21.7 (254.1,97.4) 24.7 (15.2,34.1)
10.0 (248.7,68.7) 14.0 (6.7,21.3)
.616
Education
Below primary education Secondary education Tertiary education
13.2 (220.0,46.3) 30.7 (11.7,49.6) 3.3 (26.1,12.8)
5.5 (220.2,31.2) 12.0 (22.7,26.7) 6.0 (21.3,13.3)
.146
Housing type
Public housing (small) Public housing (large) Private housing
14.3 (280.3,109.0) 23.7 (242.6,89.9) 8.5 (234.1,51.1)
5.0 (268.3,78.3) 17.0 (234.3,68.3) 1.5 (231.5,34.5)
.009
Number of cohabitants
0–1 2–3 $4
16.8 (292.0,125.7) 15.5 (283.9,114.9) 14.3 (251.9,80.6)
7.5 (276.8,91.8) 17.5 (259.5,94.5) 21.0 (252.3,50.3)
,.001
Working status
Working Not working
18.0 (210.4,46.4) 28.5 (270.9,127.9)
3.0 (219.0,25.0) 21.5 (255.5,98.5)
,.001
Number of people can confide in
0–2 3–4 $5
16.0 (240.8,72.8) 20.2 (23.5,43.8) 10.2 (223.0,43.3)
13.0 (231.0,57.0) 11.5 (26.8,29.8) 20.5 (226.2,25.2)
,.001
Detailed information for the regrouping can be found in Section 2 in Supplemental Materials (found at https://doi.org/10.1016/j.jval.2019.08.006).
P value
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types of housing, living with different numbers of people, or having different numbers of confidants also responded differently to different financial incentives.
Cost per Vaccination We derived the realized cost per vaccinated individual for the 3 incentive arms. After accounting for printing and postage, it cost about the same to obtain a single vaccination when offering a 20-SGD incentive as when offering 10 SGD, namely 37.31 SGD (95% CI 31.21–47.32) and 36.80 SGD (95% CI 33.89–41.27). This difference was not statistically significantly differentiable from 0. Offering an incentive of 30 SGD, however, increased the cost to 43.78 SGD (95% CI 41.64–46.81), costing significantly more than an incentive of 20 SGD (P = .003).
Optimal Financial Incentive We identified the population-level optimal financial incentive for the elderly from both governmental and health system perspectives, as presented in Table 4. This assumes that the relationship between the ratio of estimated vaccination rates under incentives of 10, 20, and 30 SGD is maintained and explores different scenarios for the vaccination rate for an incentive of 10 SGD to acknowledge that uptake rates may differ from those in our study if the program were conducted over a longer time period or by a government body. This table shows the optimal financial incentive when population-level influenza vaccination rates for the elderly given the 10-SGD incentive increased from 18% to 30%, the current annual vaccination rate being 17%. The population-level optimal financial incentive decreases as the baseline population-level influenza vaccination uptake rate at 10 SGD monetary incentive increases. If the baseline population-level influenza vaccination uptake rate at a 10-SGD incentive were low (eg, 18%), the incremental rate of vaccination uptake would be smaller as the incentive increased from 0 to 10 SGD and larger for incentives beyond 10 SGD. Thus it would be necessary to have a larger incentive to reach the optimal vaccination rate. Nevertheless, if the baseline population-level influenza vaccination uptake rate at a 10-SGD incentive were higher (eg, 30%), there would be fewer benefits to accrue from increasing the coverage rate further and thus the incentive should be kept low. This result is consistent from both the government and the
7
health system perspectives. If the annual vaccination uptake for a 10-SGD incentive were 20%, the optimal incentive from both perspectives would be 18 SGD, whereas if the program could achieve a 30% uptake rate or above with a 10-SGD incentive, there are no further benefits from offering a higher incentive level.
Discussion Mass vaccination is one of the most important achievements in public health.17 Individuals’ vaccination decisions depend on many factors, from socio-economic status to knowledge and vaccine confidence. In recent years, vaccine confidence has been under unprecedented assault, especially in European and western Pacific regions.18 The perceived, and occasionally real, risks of vaccination may lead to failure to achieve coverage targets set by the Global Vaccine Action Plan 2011 to 2020.19 For vaccines not part of standard pediatric vaccine schedules, it may be harder yet to achieve herd protection, as reflected by the influenza vaccination coverage rates that vary globally from more than 80% to less than 5% among high-risk groups such as the elderly.20 A number of methods have been studied to improve vaccine coverage. These include using electronic medical records to generate automated alerts,21 framing vaccination as avoiding loss (of risk of infection) rather than as a gain (of protection),22 using campaign-like features,23 and providing reminders.24 Specifically for influenza vaccination, a number of strategies have been studied, including home-based delivery,25 highly publicized free vaccination for high-risk groups,26 and opt-out vaccination for healthcare workers.27 The national influenza vaccine policies and subsidies vary between countries. In some, such as the United States, the cost of the influenza vaccine is covered by many health insurance plans as a preventive service.28 With state-provided healthcare, such as in the United Kingdom, influenza vaccination may be free,29 whereas France has given vouchers for influenza vaccine to high-risk groups.30 In Singapore, in contrast, there is no national free influenza vaccine program. Public healthcare in Singapore is founded on the principle of individuals taking responsibility for their own health and healthcare expenditures through a mandatory yet personal savings account (Medisave).31 The account is used largely for inpatient hospitalization expenses, day
Table 4. The optimal financial incentive for the elderly under various scenarios for uptake. Scenario:
S18
S20
S22
S24
S26
S28
S30
Population-level influenza vaccination rate for a10-SGD incentive (%)
18
20
22
24
26
28
30
Modelled population-level influenza vaccination rate for a 20-SGD incentive (%)
30
34
37
40
44
47
51
Modelled population-level influenza vaccination rate for a30-SGD incentive (%)
37
41
45
49
54
58
62
Optimal incentive (SGD)
20
18
15
13
12
10
10
Vaccination rate at optimal incentive (%)
30
31
30
29
30
28
30
Total cost for the government (excluding the vaccination cost) (SGD, in millions)
3.20
2.94
2.34
1.98
1.87
1.48
1.58
Total cost for health system (including the vaccination cost) (SGD, in millions)
7.94
7.78
6.96
6.51
6.50
5.86
6.28
Scenarios show the varying influenza vaccination rate among the elderly for a 10-SGD incentive from 18% to 30% coverage. Strategies are coded. For example, S18 = 18% uptake rate with a 10-SGD incentive. The optimal incentive is the absolute financial incentive that achieves the smallest incremental cost-effectiveness ratio (ICER) under a given scenario for the uptake rate, given a 10-SGD incentive. For example, if the given a 10-SGD incentive achieves an 18% influenza vaccination uptake rate for the elderly, the optimal incentive for the elderly would be 20 SGD. The results are derived from Yue et al.16 For scenarios in which the uptake rate with a 10-SGD subsidy is greater than 30%, the optimal incentive is 10 SGD (not tabulated).
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surgery, and approved medical insurance, and although some outpatient expenses can be paid using Medisave, vaccinations can typically be paid from Medisave only for high-risk groups although the government has recently announced a review of this policy. Thus, although paying out of pocket may act as a disincentive to receiving preventive care such as vaccination, paying from one’s Medisave when possible is preferable to paying using other, more liquid forms of savings. Nevertheless, the differences in payment structures may impact the efficiency of the market and thereby the uptake of vaccination. Unsubsidized vaccination may lead to a suboptimal coverage from a societal perspective, whereas free or subsidized vaccination may allow the positive externalities of individual vaccination, namely the herd immunity of others, to be realized, depending on how sensitive consumers are to the price. A market-based healthcare system like Singapore’s may, therefore, be the ideal place to assess optimal incentive levels. We found that participation rates rose by 67% (from 26.6% of those responding to a questionnaire alone to 44.4%) when the incentive doubled from 10 to 20 SGD, but further increasing the incentive from 20 to 30 SGD (ie, to almost the full price) only increased the participation rate by a nonsignificant 23% (to 54.4%). The response was, however, different for different demographic segments. In particular, those who were still working were not sensitive to the amount of incentive offered, whereas the response rate increased for those no longer in the labor force, suggesting either that time is a barrier to the working elderly or that finances are a barrier for their nonworking peers. The participation rates in arm 1 (baseline group) were higher than arm 4 with incentive of 30 SGD, indicating that some people would need to be paid more than the highest reimbursement we offered to be willing to be vaccinated. Those aged 75 or older were especially more likely to participate when offered a subsidy and, as such, this age group might be a useful starting point for a national program similar to our study. There is an apparent declining marginal response to financial incentives. Although we could not assess this from the study results directly, because the participation rate from a national, presumably government-backed, scheme would differ from that of a university-led research study, we could assess the optimal incentive for different baseline vaccination rates. For all rates considered, the optimal incentive was in the range of 10 20 SGD, that is, still requiring copayment from those being vaccinated. Interestingly, the optimum in each case corresponded to a coverage of around 30%, so a plausible strategy would be to tweak the incentivization using that uptake rate as a target. A limitation of this study is that only one such mechanism was considered, in which we reimbursed participants who first paid upfront (in cash or Medisave) with a shopping voucher, which is not a perfect reflection of how a government or health system campaign might work. Another limitation of the study was the low participation rate. We purposefully approached individuals only once to mimic a one-off vaccination campaign and estimated participation rates relative to a control group who were asked only to complete the questionnaire. Some individuals had already been vaccinated for influenza too recently to warrant repeat vaccination, further reducing the participation rate. Our analysis of optimal policies emerged from a simulation model designed to reproduce the dynamics of nonpandemic influenza in Singapore, a near-aseasonal country located near the equator, and results may not generalize to countries with clear seasonal influenza epidemics; future research may be warranted to generalize to such settings. Demographic data for nonparticipants was not available; although the sample was drawn from individuals who in a larger study (Singapore population health study) had provided consent to be contacted again, those who did not send back questionnaires
did not provide consent for the current study, and thus we could not use the linked information on those participants from the larger study. We were able to partially overcome this using the alternative statistical approaches described in Supplemental Materials (found at https://doi.org/10.1016/j.jval.2019.08.006). Within each arm, the residual confounding effects due to transportation cost, lost leisure time, and differences in spending power cannot be addressed because this information was not captured. This means, for instance, that the observed difference in uptake rates by age group could be due to confounders such as ease of access rather than by age itself.
Conclusion Despite its limitations, this study finds that appropriate monetary incentives to partially or fully subsidize influenza vaccination will boost vaccination rates, especially for nonworking elderly individuals. Free vaccination may not, however, achieve additional gains beyond a partial subsidy with copayment by the vaccinee. In the Singapore context, policy makers may wish to consider setting a partial incentive of 10 to 20 SGD that requires copayment. Other future work could evaluate payment mechanisms—using cash instead of vouchers, subsidizing instead of reimbursing, and using Medisave instead of more liquid forms of money—to see in which circumstances these influenced successful vaccination.
Acknowledgments This study was supported by the Health Services Research (HSRG/NIG) grants NMRC/HSRG/0078/2017 and the Singapore Population Health Improvement Centre (NMRC/CG/C026/2017_NUHS).
Supplemental Material Supplementary data associated with this article can be found in the online version at https://doi.org/10.1016/j.jval.2019.08.006.
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Contents lists available at sciencedirect.com Journal homepage: www.elsevier.com/locate/jval
Optimal Design of Population-Level Financial Incentives of Influenza Vaccination for the Elderly Mu Yue, PhD,1,2 Yi Wang, PhD,2 Chng Kiat Low, BSc,3 Joanne Su-yin Yoong, PhD,4,5 Alex R. Cook, PhD2,3,6,* 1 School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan, China; 2Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore; 3Department of Statistics and Applied Probability, National University of Singapore, Singapore; 4Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA; 5Yong Loo Lin School of Medicine, National University of Singapore, Singapore; 6Duke-NUS Medical School Singapore, Singapore.
A B S T R A C T Objectives: To identify how monetary incentives affect influenza vaccination uptake rate using a randomized control experiment and to subsequently design an optimal incentive program in Singapore, a high-income country with a market-based healthcare system. Methods: 4000 people aged $65 were randomly assigned to 4 treatment groups (1000 each) and were offered a monetary incentive (in shopping vouchers) if they chose to participate. The baseline group was invited to complete a questionnaire with incentives of 10 Singapore dollars (SGD; where 1 SGD z 0.73 USD), whereas the other three groups were invited to complete the questionnaire and be vaccinated against influenza at their own cost of around 32 SGD, in return for incentives of 10, 20, or 30 SGD. Results: Increasing the total incentive for vaccination and reporting from 10 to 20 SGD increased participation in vaccination from 4.5% to 7.5% (P , .001). Increasing the total incentive from 20 to 30 SGD increased the participation rate to 9.2%, but this was not statistically significantly different from a 20-SGD incentive. The group of nonworking elderly were more sensitive to changes in incentives than those who worked. In addition to working status, the effects of increasing incentives on influenza vaccination rates differed by ethnicity, socio-economic status, household size, and a measure of social resilience. There were no significant differential effects by age group, gender, or education, however. The cost of the program per completed vaccination under a 20-SGD incentive is 36.80 SGD, which was the lowest among the three intervention arms. For a hypothetical population-level financial incentive program to promote influenza vaccination among the elderly, accounting for transmission dynamics, an incentive between 10 and 20 SGD minimizes the cost per completed vaccination from both governmental and health system perspectives. Conclusions: Appropriate monetary incentives can boost influenza vaccination rates. Increasing monetary incentives for vaccination from 10 to 20 SGD can improve the influenza vaccination uptake rate, but further increasing the monetary incentive to 30 SGD results in no additional gains. A partial incentive may therefore be considered to improve vaccination coverage in this high-risk group. Keywords: incentivization, influenza, vaccination. VALUE HEALTH. 2019; -(-):-–-
Introduction In the equatorial city-state of Singapore, the health and economic burden of influenza is large. The rate of influenzaassociated hospitalizations in Singapore was 29.6 per 100 000 person-years during 2010 to 2012,1 with death rates at 14.8 per 100 000 person-years.2 Approximately 12% of hospitalizations owing to pneumonia were also attributable to influenza.1 Influenza is a major cause of disease burden among the elderly
(65 years or older), with a study by Chow et al concluding that influenza-associated deaths were 11.3 times higher in this age group compared with the general population.3 Individuals 75 years or older have influenza-related hospitalization rates 47 times higher than those who are between 25 and 44 years old.1 In light of the greater risks of influenza morbidity and mortality among the elderly, studies in temperate settings have demonstrated that vaccinating the aged population against influenza is potentially cost-effective.4,5
* Address correspondence to: Alex R. Cook, PhD, Saw Swee Hock School of Public Health, National University of Singapore, Tahir Foundation Bldg, 12 Science Dr 2, Singapore 117549. Email: [email protected] 1098-3015 - see front matter Copyright ª 2019, ISPOR–The Professional Society for Health Economics and Outcomes Research. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). https://doi.org/10.1016/j.jval.2019.08.006
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In contrast with most other developed countries, there is a lack of obvious seasonality in Singapore. Influenza circulates year-round with 2 periods of slightly elevated transmission from December to February and May to July, but outbreaks may occur between these intervals.6 The absence of winter and the low climatic variability across the year leads to an unusual pattern of quasi-random infectious disease outbreaks,7 making it difficult to predict when these epidemics will actually occur throughout the calendar year. As a result, there is no seasonal cue to go for vaccination, unlike in temperate settings. Thus, although Singapore’s Ministry of Health recommends vaccination against influenza for high-risk groups to prevent severe infections and mortality,8 as in most high-income countries,9,10 the coverage rate is disappointingly low (15% in preschool children and 17% in the elderly 65 or older6,8). Indeed, only about 17% of those 65 years or older reported receiving the seasonal influenza vaccination in the 2013 National Health Surveillance Survey (NHSS) of Singapore,8 an uptake rate that was about the same as that of the uptake rate among the lower risk group of young adults aged between 18 and 29 (16.9%).1 To improve the vaccination coverage rate, since 2014, Singaporeans and permanent residents have been allowed to use balances held in the national medical savings scheme Medisave (a mandatory individual medical savings account) to cover the cost of the influenza vaccination for those 65 or older, 5 or younger, pregnant women, and other at-risk groups, removing the out-of-pocket cost as a potential barrier.1 Despite this policy change, vaccine uptake rates remain low among high-risk groups and new approaches may be needed to afford the elderly the greatest benefits from vaccination. Unlike health interventions where the benefits are restricted to the patient receiving them, vaccination leads to a positive externality—specifically, herd immunity—that benefits society at large.11 This may justify government incentives for vaccination to align societal and individual objectives. Past trials conducted in the United States on interventions using monetary incentives among undergraduates12 or during pandemics have been shown to be effective in increasing the uptake rate of influenza vaccination,13 but the most cost-effective level of incentive for influenza vaccination to improve uptake rates within the elderly population is unclear. To this end, we designed a randomized incentivization experiment, delivered at low cost through the postal system, to model a hypothetical national program. The experimental design involved drawing potential participants from an existing cohort study, randomly assigning them to study arms—which differed in the amount of incentive proffered—and then sending them an invitation to participate. Potential participants were asked to complete a questionnaire and, for the intervention arms, to go receive the influenza vaccine at a clinic of their choice. Those who agreed and returned the questionnaire and, for the intervention arms, returned evidence that they were vaccinated in a fixed period after we wrote to them were rewarded with vouchers with values that depended on the arm. The outcomes of interest in each arm were the participation rates and the characteristics of the participants. Through the experiment, we quantified the trade-off between the costs of increasing incentives of influenza vaccination and the higher participation rates that resulted, identified which population groups were most influenced by such an incentive, and determined an optimal incentive level.
Methods Study Design A randomized experiment was conducted in Singapore from June to August 2018. The experiment was implemented using 4
incentive structures to promote influenza vaccination uptake. The instructions for the study, a questionnaire, a preaddressed stamped envelope, and a brochure describing the costs and benefits of taking the influenza vaccine were sent to potential participants through the post. Invitees who chose to participate provided consent by mailing their completed questionnaire back to the research team. The primary outcome measurement was the return rate in each arm, which was used to assess if greater incentives led to a higher vaccination uptake rate and what the optimal incentive from the government and health system perspectives should be.
Participants, Random Assignment, and Blinding Participants from the Singapore population health study14 who expressed interest in participating in future healthcare-related studies and were 65 or older were identified as potential participants in this study. After assessing their eligibility, we randomly sampled 4000 people to invite to take part. These individuals were randomly assigned to the 4 treatment groups using computer-generated random numbers. Subjects within each treatment group were blinded to the existence of the other treatment groups and made their decision to participate in the questionnaire and vaccination based solely on the information provided to them. Subjects were not blinded to the financial incentive before agreeing to participate. The original number of potential participants in each arm were the same, but the final number of participants was different. Questionnaire data is not available for the invitees who did not consent to participate, although they are known to come from the same pool of potential participants as the other arms. Ethical approval for the use of human subjects in this study was obtained from the Institutional Review Board of the National University of Singapore.
Treatment Groups Invitees who wished to participate were asked to complete their task within 2 months and were rewarded with varying amounts of monetary incentives in the form of shopping vouchers. After verifying the completion, compensation was mailed to the participants. The study initially had 7 arms: arm 1 was invited to complete a questionnaire with an incentive of 10 SGD, whereas arms 2 to 4 were invited to complete the questionnaire and be vaccinated against influenza at their own cost of 32 SGD in return for incentives of 10, 20, and 30 SGD, respectively. Because the incentives we offered were shopping vouchers available in multiples of 10 SGD, we used shopping vouchers with a value 30 SGD to approximate the policy of free vaccines. Arm 5 participants were required to receive the influenza vaccine and complete the questionnaire without incentives; arm 6 were required to receive the influenza vaccine and complete the questionnaire with an incentive of 10 SGD and an additional 10 SGD for each participant they recruited to complete the study; and arm 7, the group referred by the participants in arm 6, were required to receive the influenza vaccine and complete the questionnaire with an incentive of 10 SGD. We tried to send the study instructions to 1000 people for each of the arms 1 to 5 and 500 people for arm 6. Sample sizes were assessed based on a Monte Carlo analysis of the number vaccinated per 1000 SGD, using a permutation test. Arm 5 was removed from further analysis owing to contamination of the sample at the printing stage, and arms 6 and 7 were removed from analysis owing to extremely low participation rates (further details may be found in the Supplemental Materials at https://doi. org/10.1016/j.jval.2019.08.006). Therefore, arms 1 to 4 were left for
--
final analysis. Arm 1 served as a proxy for the demographics of those who were willing to consider taking part in the study. Comparing arms 1 and 2 isolated the effect on the return rate of having to be vaccinated, whereas comparing arms 2, 3, and 4 identified how the elderly respond to higher financial incentives.
Questionnaire The questionnaire consisted of 16 questions in 4 sections (a copy may be found in Appendix Section 1 in Supplemental Materials found at https://doi.org/10.1016/j.jval.2019.08.006). The first section contained questions relating to the general information about the participants, such as age, ethnicity, gender, education, housing type, working status, and health-related characteristics. The second section measured sociability and loneliness, using the number of cohabitants and the number of confidants as a proxy for these attributes. The third section assessed their financial situation. The final section contained questions that measured attitude to influenza vaccination by asking the number of times they had been vaccinated in the last two years, their preferred place to get the influenza vaccine, and their attitudes about the efficacy and safety of influenza vaccination. The questionnaire was developed in English, and forward and back translated into simplified Chinese and Malay, the national language. User acceptability testing was performed on 20 colleagues. All materials sent were tested for ease of interpretation and for legibility, using readable fonts, short sentences, and lay terms where possible.
Statistical Analysis All statistical analyses used R.15
Questionnaire data
Missing values in returned questionnaires were ,1% of possible cells. Within each arm, missing values for categorical variables were imputed by the mode of nonmissing cases of those variables and missing values for continuous variables (eg, age) were imputed by the median. Smaller strata that did not have sufficient numbers for analysis were aggregated with similar strata for analysis. Detailed information about the regrouping can be found in Section 2 in Supplemental Materials (found at https://doi.org/10.1016/j.jval.2019.08.006).
Participation rates The main outcome variable was participation in the study within 2 months. For arm 1, this meant returning the questionnaire. For all the other arms, it meant returning both the questionnaire and a vaccination certificate dated within the period of June 22 to August 22, 2018 that indicated the recipient was the person we invited. Participation rates for each arm were calculated by using the number of valid responses divided by the following denominator: the number of elderly invitees whom we tried to mail minus the letters that were returned undelivered and those invitees who replied but had received the influenza vaccination before the study. Those who did not participate but were prompted to go for vaccination because of the information letter are not captured by the study design but are anticipated to be few. We tested whether participation rates were equal among all, or pairs of, treatment groups using Pearson’s chi-square test. Because the demographics and other potential risk factors are not known for individuals who did not participate, it was not possible to relate an individual’s participation to risk factors using standard regression techniques. However, as shown in Section 4.2 in Supplemental Materials (found at https://doi.org/10.1016/j.jval.2 019.08.006), we were able to assess the distribution of risk
3
factors among responders in the different arms and thereby test (using a chi-square test) whether the incentivization affected the subgroups equally. We denote pis to be the probability that a subject belonging to stratum s is willing to participate in the study if invited to arm i. Although ps i cannot be estimated for this study . design, the ratio b p is b for arms i and j can be obtained and p js . whether pis p is equal to 1 can be tested. More details on the js derivation of the test can be found in Section 4.3 in Supplemental Materials (found at https://doi.org/10.1016/j.jval.2019.08.006). The methods of using the ratio of the participation rates and using the chi-square test could both answer the question of whether the participation rate in each stratum for any 2 incentive groups are equal (within each subgroup, whether the elderly respond to higher incentives by comparing 10 vs 20 SGD, 10 vs 30 SGD, and 20 vs 30 SGD). Nevertheless, for the chi-square test, the corresponding P value is obtained via exact calculation, whereas for the use of the ratio of the participation rates, the confidence interval (CI) is based on approximation, and thus the corresponding P value is also approximated. To test whether the demographic strata had differences in uptake rates per 10 SGD increment in the vaccination incentive (whether people from each subgroup responded to the higher incentives to the same degree), we fit a Poisson model to the number of respondents, Yis, for intervention i=0,1,2 for arms 2, 3, and 4 respectively, and for stratum s, with mean as 1 bs 3 i. Under this model, which uses a linear model to pool information between arms, bs quantifies the increase in the number of participants in stratum s as the incentive increases by 10 SGD. We tested whether bs is the same for all strata s using the likelihood ratio test. More details on the derivation of the test can be found in Section 4.5 in Supplemental Materials (found at https://doi.org/10.1016/j.jval.2019.08.006).
Cost analysis The costs incurred per eventuated influenza vaccination were derived from the cost of the incentive for those who obtained vaccination and the printing and postage cost for both those who did and did not. We define Ci to be the total cost accrued in incentivizing a single individual in arm i to get the influenza vaccine. Given total printing costs of 1158 SGD and the costs of delivery, that is, in SGD: 1158 1 ðWi 1 0:74Þ 3 Yi 1 0:37 3 Y qi 1 Y pi Ci ¼ Yi where Yi is the number of (valid) responses, Y qi the number of individuals who return a questionnaire but not a vaccination certificate, Yp the number of individuals who return a vaccination certificate for a previous vaccination, and Wi the reimbursement offered to arm i. More details can be found in Section 4.6 in Supplemental Materials (found at https://doi.org/1 0.1016/j.jval.2019.08.006). We used bootstrap with 10 000 resamples, from the numbers of participants, invalid responses, those previously vaccinated, those who had changed their address, and those who declined to respond, to obtain 95% CI for the costs per successful vaccination on each arm. We tested for differences in costs between arms using a bootstrap-based Wald test. Finally, we found the optimal incentive for a population-level vaccination program of the same model as in our study, from both governmental and health systems perspectives, by computing the incremental cost-effectiveness ratio (ICER) of the financial incentive program relative to no program, using output from an individual-based model described elsewhere (Yue et al16).
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The optimal financial incentive is the financial incentive that achieves the smallest ICER, defined as: ICERðxÞ ¼
Costðx; pðxÞÞ 2 Costð0; pð0ÞÞ QALYðpðxÞÞ 2 QALYðpð0ÞÞ
where Cost(x,p(x)) is the total cost of providing financial incentives of x SGD to obtain a fraction p(x) of the population being vaccinated, and QALY(p(x)) is the quality-adjusted life-years (or the life-years saved from not contracting influenza) for the whole Singapore population under the same fraction vaccinated. The cost from the government’s perspective is the financial incentive only and the cost from the health system’s perspective is composed of both the financial incentive and the influenza vaccination cost. The QALYs were derived from mortality, hospitalization, and self-limiting infections. Further details are provided in Section 4 in Supplemental Materials (found at https://doi.org/10.1016/j.jval.2019.08.006).
Results In response to the 4000 letters sent out on June 22, 2018 with a return due date of August 22, 2018, a total of 484 letters were
received, of which 373 were valid (as described in Figure 1). Both trivalent and quadrivalent vaccines are available in Singapore, and most vaccinated participants took the trivalent vaccine. Reasons for invalidity included having recently been vaccinated (ie, sending in evidence of vaccination that predated June 22, 2018), the mail being returned undelivered, or those in arms 2 to 4 returning only a questionnaire but not a vaccination certificate. The overall response rate was therefore 9.3%, and the response rate was highest for arm 1 (who had only to return a questionnaire) at 16.9%. When offering the same amount of monetary compensation (a 10-SGD shopping voucher), requiring participants to also be vaccinated (and to pay for the cost of vaccination by themselves) markedly reduced the participation rate from 16.9% to 4.5% (P , .001). Increasing the total incentive from a 10 SGD to 20 SGD shopping voucher increased the participation rate significantly from 4.5% to 7.5% (P = .006). Further increasing the total incentive from 20 to 30 SGD, however, increased the empirical participation rate by less, from 7.5% to 9.2%, which was not statistically significant. Overall, there was very strong evidence of different response rates among the 4 arms of the study (P , .001). Because many potential participants may have disregarded the study invitation, to approximate the response rate among those
Figure 1. Flow diagram for the experiment, detailing the distribution of responses in each arm. Undelivered indicates number of letters that were undelivered to the potential participants; recent vax, number of letters including previous vaccination certificate to prove that the influenza vaccination had been taken recently; RR, response rate calculated by the ratio of valid responses among the “remaining”; RRR, relative response rate calculated by the ratio of the response rate among the response rate for arm 1.
Prospective participants (N = 4000)
Arm 1 (N = 1000)
Arm 2 (N = 1000)
Arm 3 (N = 1000)
Arm 4 (N = 1000)
Excluded: Undelivered (N = 16) Recent Vax (N = 0)
Excluded: Undelivered (N = 2) Recent Vax (N = 15)
Excluded: Undelivered (N = 15) Recent Vax (N = 17)
Excluded: Undelivered (N = 5) Recent Vax (N = 18)
Remaining: (N = 984)
Remaining: (N = 983)
Remaining: (N = 968)
Remaining: (N = 977)
Valid response: (N = 166) (RR = 16.9%) (RRR = 100.0%)
Valid response: (N = 44) (RR = 4.5%) (RRR = 26.5%)
Valid response: (N = 73) (RR = 7.5%) (RRR = 44.7%)
Valid response: (N = 90) (RR = 9.2%) (RRR = 54.6%)
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who contemplated taking part, we calculated the response rate relative to the baseline group, who were offered 10 SGD for returning a 2-page questionnaire. These were 26.5% (arm 2, 10 SGD), 44.7% (arm 3, 20 SGD), and 54.6% (arm 4, 30 SGD). Demographics of the participants are provided in Table 1, indicating that those who elected to take part were broadly similar to the elderly population as a whole. Most (63%) participants had not received the influenza vaccine in the last 2 years, whereas 21% had been vaccinated once and 16% twice in the last 2 years. Most participants preferred to be vaccinated at a clinic (32% at a general practitioner [GP] clinic and 53% at a public polyclinic). A few favored other places like their home (2%), the hospital (5%), a community center (6%), or a health screening center (2%). Participants had positive perceptions of the safety of vaccination (76% thinking they were safe and only 2% disagreeing), but few perceived themselves as being at risk of infection without being vaccinated (35% agreeing and 22% disagreeing with this proposition).
5
The number of participants in each arm by demographic stratum are presented in Figure SI in Supplemental Materials (found at https://doi.org/10.1016/j.jval.2019.08.006). We denote pis to be the probability that a subject belonging to stratum s is willing to participate in the study if invited to arm i. Although pis could not be estimated for this study design, the ratio Pis/pjs for arms i and j could be, which has been tabulated in Table 2 to assess whether the participation rate in each stratum for any 2 incentive groups are equal. The elderly aged 75 or older who were offered a 30-SGD incentive were 4.1 (95% CI 1.3–6.9) times more likely to elect to get vaccinated than when only given 10 SGD, and 3.4 times (95% CI 1.5–8.0) more likely to participate if offered 20 SGD rather than 10 SGD. Although both genders were more likely to participate if offered 30 SGD rather than 10 SGD, only among women was there a statistically significant increase in participation rates when increasing the incentive from 10 SGD to 20 SGD (of 2.0, 95% CI 1.0–3.1). There was evidence that ethnic Chinese responded to increased incentives (Table 2), but
Table 1. Participants’ characteristics. Characteristic
N
%
Population %
Age group
65–69 70–74 75 or older
156 115 102
42 31 27
41* 21* 38*
Ethnicity
Chinese Non-Chinese (of which: Malay Indian Other)
314 59 19 36 4
84 16 5 10 1
84* 16* 9* 6* 1*
Sex
Female Male
170 203
46 54
55* 45*
Education
Below primary education Secondary education Tertiary education
106 213 54
28 57 15
60† 31† 9†
Housing Type
Public housing (small) Public housing (large) Private housing
98 215 60
26 58 16
29† 53† 18†
Number of cohabitants
0–1 2–3 $4
139 165 69
37 44 19
— — —
Working status
Yes No
114 259
31 69
20† 80†
Number of people can confide in
0–2 3–4 $5
160 163 50
43 44 13
— — —
Have health assist card issued by the Community Health Assist Scheme
Yes No Don’t know
196 170 7
52 46 2
— — —
Eligible for the pioneer generation package
Yes No Don’t know
242 117 14
65 31 4
— — —
Have public assistance card
Yes No Don’t know
13 335 25
3 90 7
— — —
Have any diseases
Diabetes Asthma Chronic obstructive pulmonary disease None of the above
97 7 2
28 3 0
— — —
260
69
— †
Population characteristics were derived from the Singapore Yearbook of Statistics 2017* and the General Household Survey 2015 for the resident population aged 65 and older.
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VALUE IN HEALTH
Table 2. Ratios of response rates (ie, pis/pjs) and their 95% confidence intervals. Question
Stratum
Ratio of Response Rates (95% CI) 20 vs 10 SGD
30 vs 20 SGD
30 vs 10 SGD
Age group
65–69 70–74 $75
1.3 (0.6-1.9) 1.8 (0.7-2.9) 3.4 (1.5-8.0)
1.4 (0.7-2.1) 1.1 (0.5-1.7) 1.2 (0.6-1.9)
1.7 (0.9-2.6) 1.9 (0.8-3.1) 4.1 (1.3-6.9)
Ethnicity
Chinese Other
1.6 (1.0-2.2) 3.4 (0.5-6.3)
1.4 (1.0-1.9) 0.5 (0.1-1.0)
2.2 (1.4-3.0) 1.7 (0.1-3.3)
Gender
Male Female
1.6 (0.8-2.3) 2.0 (1.0-3.1)
1.4 (0.9-2.0) 1.1 (0.6-1.5)
2.2 (1.2-3.2) 2.1 (1.0-3.2)
Education
Below primary education Secondary education Tertiary education
1.8 (0.6-3.0) 1.6 (0.9-2.3) 4.5 (0.2-8.9)
1.1 (0.5-1.8) 1.2 (0.8-1.7) 1.6 (0.5-2.8)
2.0 (0.7-3.3) 1.9 (1.1-2.7) 6.7 (0.5-12.9)
Housing type
Public housing (small) Public housing (large) Private housing
2.5 (0.9-4.1) 1.4 (0.7-2.1) 2.2 (0.4-3.9)
0.9 (0.4-1.3) 1.7 (1.0-2.4) 0.8 (0.2-1.4)
2.1 (0.7-3.5) 2.4 (1.3-3.4) 1.6 (0.3-3.0)
Number of cohabitants
0–1 2–3 $4
2.6 (1.1-4.2) 1.4 (0.6-2.2) 1.6 (0.5-2.6)
0.9 (0.5-1.3) 2.2 (1.2-3.2) 0.6 (0.2-1.1)
2.2 (0.9-3.6) 3.0 (1.5-4.4) 0.9 (0.2-1.6)
Working status
Yes No
1.0 (0.4-1.6) 2.3 (1.3-3.4)
1.4 (0.6-2.2) 1.2 (0.8-1.6)
1.3 (0.6-2.1) 2.8 (1.6-4.0)
Number of people can confide in
0–2 3–4 $5
2.5 (1.0-3.9) 1.5 (0.7-2.2) 1.5 (0.3-2.7)
1.2 (0.7-1.8) 1.5 (0.8-2.2) 0.7 (0.1-1.3)
3.0 (1.3-4.7) 2.2 (1.1-3.2) 1.0 (0.1-1.8)
CI indicates confidence interval. The bold values are the 95% CIs cover 0. Information on how these are derived is provided in Section 2 in Supplemental Materials (found at https://doi.org/10.1016/j. jval.2019.08.006).
insufficient numbers of other ethnicities to identify the same pattern held with them. Those who were not working were more sensitive to the amount of incentives, being 2.3 times (95% CI 1.3–3.4) more likely to get vaccinated if offered 20 SGD, and 2.8 times (95% CI 1.6–4.0) if offered 30 SGD rather than 10 SGD.
Differences between the demographic strata in how they responded to different incentive levels are reported in Table 3. The Chinese elderly were more sensitive to the amount of financial incentives than non-Chinese, as were the nonworking elderly compared with the working elderly. Elderly living in different
Table 3. The as, bs and P value from the likelihood ratio test. Question
Stratum
as (95% CI)
bs (95% CI)
Age group
65–69 70–74 $75
21.2 (22.5,44.8) 15.3 (222.5,53.2) 10.0 (246.8,66.8)
7.5 (210.8,25.8) 6.0 (223.3,35.3) 11.0 (233.0,55.0)
.129
Ethnicity
Chinese Other ethnic group
39.5 (25.3,53.7) 7.7 (268.1,83.4)
22.5 (11.5,33.5) 1.0 (257.7,59.7)
.001
Gender
Female Male
21.7 (254.1,97.4) 24.7 (15.2,34.1)
10.0 (248.7,68.7) 14.0 (6.7,21.3)
.616
Education
Below primary education Secondary education Tertiary education
13.2 (220.0,46.3) 30.7 (11.7,49.6) 3.3 (26.1,12.8)
5.5 (220.2,31.2) 12.0 (22.7,26.7) 6.0 (21.3,13.3)
.146
Housing type
Public housing (small) Public housing (large) Private housing
14.3 (280.3,109.0) 23.7 (242.6,89.9) 8.5 (234.1,51.1)
5.0 (268.3,78.3) 17.0 (234.3,68.3) 1.5 (231.5,34.5)
.009
Number of cohabitants
0–1 2–3 $4
16.8 (292.0,125.7) 15.5 (283.9,114.9) 14.3 (251.9,80.6)
7.5 (276.8,91.8) 17.5 (259.5,94.5) 21.0 (252.3,50.3)
,.001
Working status
Working Not working
18.0 (210.4,46.4) 28.5 (270.9,127.9)
3.0 (219.0,25.0) 21.5 (255.5,98.5)
,.001
Number of people can confide in
0–2 3–4 $5
16.0 (240.8,72.8) 20.2 (23.5,43.8) 10.2 (223.0,43.3)
13.0 (231.0,57.0) 11.5 (26.8,29.8) 20.5 (226.2,25.2)
,.001
Detailed information for the regrouping can be found in Section 2 in Supplemental Materials (found at https://doi.org/10.1016/j.jval.2019.08.006).
P value
--
types of housing, living with different numbers of people, or having different numbers of confidants also responded differently to different financial incentives.
Cost per Vaccination We derived the realized cost per vaccinated individual for the 3 incentive arms. After accounting for printing and postage, it cost about the same to obtain a single vaccination when offering a 20-SGD incentive as when offering 10 SGD, namely 37.31 SGD (95% CI 31.21–47.32) and 36.80 SGD (95% CI 33.89–41.27). This difference was not statistically significantly differentiable from 0. Offering an incentive of 30 SGD, however, increased the cost to 43.78 SGD (95% CI 41.64–46.81), costing significantly more than an incentive of 20 SGD (P = .003).
Optimal Financial Incentive We identified the population-level optimal financial incentive for the elderly from both governmental and health system perspectives, as presented in Table 4. This assumes that the relationship between the ratio of estimated vaccination rates under incentives of 10, 20, and 30 SGD is maintained and explores different scenarios for the vaccination rate for an incentive of 10 SGD to acknowledge that uptake rates may differ from those in our study if the program were conducted over a longer time period or by a government body. This table shows the optimal financial incentive when population-level influenza vaccination rates for the elderly given the 10-SGD incentive increased from 18% to 30%, the current annual vaccination rate being 17%. The population-level optimal financial incentive decreases as the baseline population-level influenza vaccination uptake rate at 10 SGD monetary incentive increases. If the baseline population-level influenza vaccination uptake rate at a 10-SGD incentive were low (eg, 18%), the incremental rate of vaccination uptake would be smaller as the incentive increased from 0 to 10 SGD and larger for incentives beyond 10 SGD. Thus it would be necessary to have a larger incentive to reach the optimal vaccination rate. Nevertheless, if the baseline population-level influenza vaccination uptake rate at a 10-SGD incentive were higher (eg, 30%), there would be fewer benefits to accrue from increasing the coverage rate further and thus the incentive should be kept low. This result is consistent from both the government and the
7
health system perspectives. If the annual vaccination uptake for a 10-SGD incentive were 20%, the optimal incentive from both perspectives would be 18 SGD, whereas if the program could achieve a 30% uptake rate or above with a 10-SGD incentive, there are no further benefits from offering a higher incentive level.
Discussion Mass vaccination is one of the most important achievements in public health.17 Individuals’ vaccination decisions depend on many factors, from socio-economic status to knowledge and vaccine confidence. In recent years, vaccine confidence has been under unprecedented assault, especially in European and western Pacific regions.18 The perceived, and occasionally real, risks of vaccination may lead to failure to achieve coverage targets set by the Global Vaccine Action Plan 2011 to 2020.19 For vaccines not part of standard pediatric vaccine schedules, it may be harder yet to achieve herd protection, as reflected by the influenza vaccination coverage rates that vary globally from more than 80% to less than 5% among high-risk groups such as the elderly.20 A number of methods have been studied to improve vaccine coverage. These include using electronic medical records to generate automated alerts,21 framing vaccination as avoiding loss (of risk of infection) rather than as a gain (of protection),22 using campaign-like features,23 and providing reminders.24 Specifically for influenza vaccination, a number of strategies have been studied, including home-based delivery,25 highly publicized free vaccination for high-risk groups,26 and opt-out vaccination for healthcare workers.27 The national influenza vaccine policies and subsidies vary between countries. In some, such as the United States, the cost of the influenza vaccine is covered by many health insurance plans as a preventive service.28 With state-provided healthcare, such as in the United Kingdom, influenza vaccination may be free,29 whereas France has given vouchers for influenza vaccine to high-risk groups.30 In Singapore, in contrast, there is no national free influenza vaccine program. Public healthcare in Singapore is founded on the principle of individuals taking responsibility for their own health and healthcare expenditures through a mandatory yet personal savings account (Medisave).31 The account is used largely for inpatient hospitalization expenses, day
Table 4. The optimal financial incentive for the elderly under various scenarios for uptake. Scenario:
S18
S20
S22
S24
S26
S28
S30
Population-level influenza vaccination rate for a10-SGD incentive (%)
18
20
22
24
26
28
30
Modelled population-level influenza vaccination rate for a 20-SGD incentive (%)
30
34
37
40
44
47
51
Modelled population-level influenza vaccination rate for a30-SGD incentive (%)
37
41
45
49
54
58
62
Optimal incentive (SGD)
20
18
15
13
12
10
10
Vaccination rate at optimal incentive (%)
30
31
30
29
30
28
30
Total cost for the government (excluding the vaccination cost) (SGD, in millions)
3.20
2.94
2.34
1.98
1.87
1.48
1.58
Total cost for health system (including the vaccination cost) (SGD, in millions)
7.94
7.78
6.96
6.51
6.50
5.86
6.28
Scenarios show the varying influenza vaccination rate among the elderly for a 10-SGD incentive from 18% to 30% coverage. Strategies are coded. For example, S18 = 18% uptake rate with a 10-SGD incentive. The optimal incentive is the absolute financial incentive that achieves the smallest incremental cost-effectiveness ratio (ICER) under a given scenario for the uptake rate, given a 10-SGD incentive. For example, if the given a 10-SGD incentive achieves an 18% influenza vaccination uptake rate for the elderly, the optimal incentive for the elderly would be 20 SGD. The results are derived from Yue et al.16 For scenarios in which the uptake rate with a 10-SGD subsidy is greater than 30%, the optimal incentive is 10 SGD (not tabulated).
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VALUE IN HEALTH
surgery, and approved medical insurance, and although some outpatient expenses can be paid using Medisave, vaccinations can typically be paid from Medisave only for high-risk groups although the government has recently announced a review of this policy. Thus, although paying out of pocket may act as a disincentive to receiving preventive care such as vaccination, paying from one’s Medisave when possible is preferable to paying using other, more liquid forms of savings. Nevertheless, the differences in payment structures may impact the efficiency of the market and thereby the uptake of vaccination. Unsubsidized vaccination may lead to a suboptimal coverage from a societal perspective, whereas free or subsidized vaccination may allow the positive externalities of individual vaccination, namely the herd immunity of others, to be realized, depending on how sensitive consumers are to the price. A market-based healthcare system like Singapore’s may, therefore, be the ideal place to assess optimal incentive levels. We found that participation rates rose by 67% (from 26.6% of those responding to a questionnaire alone to 44.4%) when the incentive doubled from 10 to 20 SGD, but further increasing the incentive from 20 to 30 SGD (ie, to almost the full price) only increased the participation rate by a nonsignificant 23% (to 54.4%). The response was, however, different for different demographic segments. In particular, those who were still working were not sensitive to the amount of incentive offered, whereas the response rate increased for those no longer in the labor force, suggesting either that time is a barrier to the working elderly or that finances are a barrier for their nonworking peers. The participation rates in arm 1 (baseline group) were higher than arm 4 with incentive of 30 SGD, indicating that some people would need to be paid more than the highest reimbursement we offered to be willing to be vaccinated. Those aged 75 or older were especially more likely to participate when offered a subsidy and, as such, this age group might be a useful starting point for a national program similar to our study. There is an apparent declining marginal response to financial incentives. Although we could not assess this from the study results directly, because the participation rate from a national, presumably government-backed, scheme would differ from that of a university-led research study, we could assess the optimal incentive for different baseline vaccination rates. For all rates considered, the optimal incentive was in the range of 10 20 SGD, that is, still requiring copayment from those being vaccinated. Interestingly, the optimum in each case corresponded to a coverage of around 30%, so a plausible strategy would be to tweak the incentivization using that uptake rate as a target. A limitation of this study is that only one such mechanism was considered, in which we reimbursed participants who first paid upfront (in cash or Medisave) with a shopping voucher, which is not a perfect reflection of how a government or health system campaign might work. Another limitation of the study was the low participation rate. We purposefully approached individuals only once to mimic a one-off vaccination campaign and estimated participation rates relative to a control group who were asked only to complete the questionnaire. Some individuals had already been vaccinated for influenza too recently to warrant repeat vaccination, further reducing the participation rate. Our analysis of optimal policies emerged from a simulation model designed to reproduce the dynamics of nonpandemic influenza in Singapore, a near-aseasonal country located near the equator, and results may not generalize to countries with clear seasonal influenza epidemics; future research may be warranted to generalize to such settings. Demographic data for nonparticipants was not available; although the sample was drawn from individuals who in a larger study (Singapore population health study) had provided consent to be contacted again, those who did not send back questionnaires
did not provide consent for the current study, and thus we could not use the linked information on those participants from the larger study. We were able to partially overcome this using the alternative statistical approaches described in Supplemental Materials (found at https://doi.org/10.1016/j.jval.2019.08.006). Within each arm, the residual confounding effects due to transportation cost, lost leisure time, and differences in spending power cannot be addressed because this information was not captured. This means, for instance, that the observed difference in uptake rates by age group could be due to confounders such as ease of access rather than by age itself.
Conclusion Despite its limitations, this study finds that appropriate monetary incentives to partially or fully subsidize influenza vaccination will boost vaccination rates, especially for nonworking elderly individuals. Free vaccination may not, however, achieve additional gains beyond a partial subsidy with copayment by the vaccinee. In the Singapore context, policy makers may wish to consider setting a partial incentive of 10 to 20 SGD that requires copayment. Other future work could evaluate payment mechanisms—using cash instead of vouchers, subsidizing instead of reimbursing, and using Medisave instead of more liquid forms of money—to see in which circumstances these influenced successful vaccination.
Acknowledgments This study was supported by the Health Services Research (HSRG/NIG) grants NMRC/HSRG/0078/2017 and the Singapore Population Health Improvement Centre (NMRC/CG/C026/2017_NUHS).
Supplemental Material Supplementary data associated with this article can be found in the online version at https://doi.org/10.1016/j.jval.2019.08.006.
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