Published as:
Schulz, D.N., Smit, E.S.,Stanczyk, N.E., Kremers, S.P.J., de Vries, H., Evers, S.M.A.A. (2014) Economic evaluation of a web-based tailored lifestyle intervention for adults: findings regarding cost-effectiveness and cost-utility from a randomized controlled trial, Journal of Medical Internet Research, 16(3): e91. DOI: 10.2196/jmir.3159
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Title:
Economic evaluation of a web-based tailored lifestyle intervention for adults: findings regardingcost-effectiveness and cost-utility from a randomized controlled trial
Authors:
Daniela N. Schulz, MSc 1; Eline S. Smit, PhD 1,2; Nicola E. Stanczyk, MSc 1; Stef P. J. Kremers, PhD 3; Hein de Vries, PhD 1; Silvia M.A.A. Evers, PhD4
1 Maastricht University
Faculty of Health, Medicine and Life Sciences
CAPHRI School for Public Health and Primary Care
Department of Health Promotion
P.O. Box 616, 6200 MD Maastricht
The Netherlands
2University of Amsterdam
Department of Communication Science
Amsterdam School of Communication Research/ASCoR
Kloveniersburgwal 48, 1012 CX Amsterdam
The Netherlands
3 Maastricht University
Faculty of Health, Medicine and Life Sciences
Nutrition and Toxicology Research Institute Maastricht (NUTRIM)
Department of Health Promotion
P.O. Box 616, 6200 MD Maastricht
The Netherlands
4 Maastricht University
Faculty of Health, Medicine and Life Sciences
CAPHRI School for Public Health and Primary Care
Department of Health Services Research
P.O. Box 616, 6200 MD Maastricht
The Netherlands
Corresponding author:
Schulz, Daniela N.
Phone: +31 43 388 2832 / Fax: +31 43 367 1032
Email:
Address: P.O. Box 616, 6200 MD Maastricht, The Netherlands
Keywords:randomized controlled trial; economic evaluation; cost-effectiveness; cost-utility; lifestyle behaviours; internet interventions; web-based; computer-tailoring
Abstract
Background. Whereas different studies have reported the effectiveness of web-based computer-tailored lifestyle interventions, economic evaluations of these interventions are scarce.
Objective. To assess the cost-effectiveness and cost-utilityof a sequential and a simultaneous web-based computer-tailored lifestyle intervention for adults, compared to a control group.
Methods. The economic evaluation, conducted from a societal perspective, was part of a 2-year randomized controlled trial including three study groups. All groups received personalized health risk appraisals based on the guidelines for physical activity, fruit intake, vegetable intake, alcohol consumption, and smoking. Additionally, respondents in the sequential condition received personal advice about one lifestyle behaviour in the first year and regarding a second behaviour in the second year; respondents in the simultaneous condition received personal advice about all unhealthy behaviours in both years. During a period of 24 months, health care use, medication use, absenteeism from work and quality of life (EQ-5D-3L) were assessed every three months using web-based questionnaires. Demographics were assessed at baseline, and lifestyle behaviours both at baseline and after 24 months. Cost-effectiveness and cost-utility analyses were performed based on the outcome measures lifestyle factor (the number of guidelines respondents adhered to) and quality of life, respectively. We accountedfor uncertainty using bootstrapping techniques and sensitivity analyses.
Results. A total of 1,733 respondents were included in the analyses. From a willingness to pay of €4,594 per one additional guideline met, the sequential intervention (n = 552) was likely to be the most cost-effective, whereas from a willingness to pay of €10,850, the simultaneous intervention (n = 517) was likely to be most cost-effective. The control condition (n = 664), on the other hand, was probably preferred with regard to quality of life.
Conclusion. Both the sequential and the simultaneous lifestyle interventions were likely to be cost-effective where it concerned the lifestyle factor, whereas the control condition was when it concerned quality of life. However, there is no accepted cut-off point for the willingness to pay per gain in lifestyle behaviours, making it impossible to draw firm conclusions. Further economic evaluations of lifestyle interventions are needed.
Trial registration.NTR2168
Background
Non-communicable chronic diseases are associated with various modifiable health risk behaviours, such as physical inactivity, bad nutrition, excessive drinking, and smoking [1]. An unhealthy lifestyle and the consequences involved are related to a reduced quality of life [2] as well as substantial health care costs [3,4].Stimulating a healthy lifestyle is important to improve health and prevent illness on the one hand, and to reduce health care costs on the other, especially with current budget cuts in the Netherlands and other countries [5,6].
Computer-tailoring can be used successfully as an intervention to promote behaviours associated with a healthy lifestyle [7]. When applying computer-tailoring, personalised feedback is generated by a computer programme based on an individual assessment[8]. Earlier studies have demonstrated that tailored information is perceived as more relevant than non-tailored information [9].Moreover, computer-tailored interventions have proven to be effective in stimulating a healthier lifestyle, e.g. inreaching smoking cessation [10], preventing smoking relapse [11], encouraging healthy nutrition [12], lowering alcohol intake [13], and increasing physical activity [14]. Previous research has also indicated that changing multiple lifestyle related behavioursis likely to be more effective than changing only a single behaviour [15]. A recent study has shown that tailored interventions which aim to reducing multiple health risk behavioursare not only successful in reducing unhealthy behavioursbut also in simultaneously enhancing the overall well-being of the individual [16]. The delivery of computer-tailored interventions targeting multiple health risk behaviours through the internet hasvarious benefits: these programmes can be applied in privacy and at a time and place the respondent findsconvenient; many people can be reached at relatively low intervention cost, since more than 90% of the Dutch population has internet access nowadays [17]; and since the system is computerized it can be easily combined with, and/or integrated in other programmes or interventions.
Some economic evaluations of web-based and/or computer-tailored programmes have been conducted to date [e.g., 18-23]. In general, these studies have given a first indication that these interventions – most were single behaviour change interventions – canindeed becost-effective. To our knowledge, however, so far no economic evaluation of a web-based computer-tailored intervention targeting multiple health risk behaviourshas been conducted.
Web-based computer-tailored lifestyle interventions are an interesting and promising option to make the healthcare system more sustainable, because of their proven clinical effectiveness and their potential cost-effectiveness due to relatively low intervention costs and wide reach. Thus, information regarding the cost-effectiveness of web-based computer-tailored intervention programmesis crucial for health care decision makers and the government, inmaking evidence-based decisions regarding large-scale implementation of such programmes [24]. The aim of the present study, therefore, is to assess from a societal perspective the cost-effectiveness and cost-utility of two different versions (sequential and simultaneous) of a web-based computer-tailored lifestyle intervention for adults, compared to a control group that received only a minimal intervention.
Methods
Study design and participants
The economic evaluation was embedded in a 2-year single-blind randomized controlled trial, including three study groups.The study was approved by the Medical Ethics Committee of Maastricht University and the University Hospital Maastricht (MEC 09-3-016/NL27235.068.09) and registered by the Dutch Trial Register (NTR2168).
In October 2009, the Dutch Regional Health Authorities of North-Brabant and Zeeland conducted the quadrennial ‘Adult Health Monitor 2009’ among inhabitants of these two provinces.This questionnaire could be completed online viathe internet or on paper. Respondents who completed theonline version of the questionnaire were invited to take part in the present study. The Monitor was interconnected with and integrated into our web-based lifestyle intervention.The study website was also open to the general public, which means that it was also possible to register for participation in the trial directly on the study website without having completed theMonitor.
The inclusion period for this study was from November 2009 up to and including July 2010.The following inclusion criteria were used: being between 18 and 65 years old; having a computer with internet access and basic internet literacy; and having a valid e-mail address. Participants were randomized into one of the two experimental groups (sequential condition (SeqC) or simultaneous condition (SimC)) or into the control condition (CC), with an equal probability of being assigned to any of the three groups.Randomization took place at the individual level by means of a computer software randomization system. Figure 1 shows the CONSORT flow diagram.
Figure 1.Flow diagram of the economic study
Intervention
The intervention was a web-basedcomputer-tailored multi-session programme targeting adults. The main aim of this lifestyle intervention was to motivate participants to be sufficiently physically active, to eatenough fruit and vegetables, to drink less alcohol and to quit smoking. The intervention was based on the I-Change model, an integration of social cognitive models [25,26], and previously developed programmes which have proven to be effective in increasing the level of physical activity [27], promoting the intake of fruit and vegetables [28], reducing the consumption of alcohol [29], and smoking cessation [30]. The respondents received feedback texts on their computer screens which were aimed to motivate them to adopt the recommended health behaviours. All respondents received a health risk appraisal (HRA) indicating whether they adhered to the following public health guidelines: being moderately physically active for 30 minutes at least five days a week [31]; eating 200 grams of vegetables per day [32]; eating two pieces of fruit per day [32]; not drinking more than one (women) or two (men) glasses of alcohol a day [32]; and not smoking [33]. For all health risk behaviours, they received a traffic light indicating whether they met (green), almost met (orange) or failed to meet (red) the guideline. Subsequently, the experimental groups received personalized advice provided in four steps based on questions about different psychosocial determinants of the I-Change model [25,26]: (1) attitude; (2) social influence; (3) preparatory planning; and (4) self-efficacy and coping planning. At the end of every step, personal advice was given. At baseline, respondents in the sequential condition could select one module concerning one of the lifestyle behaviours for which they did not meet the public health guidelines and thus received a red or orange traffic light in their HRA; on completing this module, they received personalized feedback regarding this particular behaviour. After 12 months, a second assessment took place and respondents had the opportunity to choose a second module and to receive feedback on a second lifestyle behaviourfor which they did not meet the public health guidelines. At baseline and after 12 months, respondents of the simultaneous condition received feedback on all behaviours for which they did not meet the public health guideline simultaneously.In both conditions, an overview of all received pieces of advice was available (via a link which was also sent by email) for the respondent at the end of the sessions. The control group received the HRA at baseline and after 24 months, but no additional personal advice. Figure 2 presents the design of the study, including allall parts of the intervention. A detailed description of the study protocol has been published elsewhere [34].
Figure 2. Design of the study
Identification, measurement and valuation of costs and effects
The economic evaluation was conducted from a societal perspective which means that all relevant costs (i.e., intervention costs, health care costs and respondent costs) and effects (Quality Adjusted Life Years (QALYs) and lifestyle factor score (LFS)) were taken into account [35].
Costs
Intervention costs consisted of hosting costs for the website, including costs for technical assistance and required updates. Costs for the development of the intervention programme and research specific costs were excluded, because these are once-only costs which are not necessary again when implementing the programme. The intervention costs were the same for all study groups since all groups received tailored advice that was integrated in the study website.
Health care costs included use of medication, medical consultations, inpatient and outpatient specialist care, hospital admissions, and other care (e.g. professional home care). Health care costs were assessed using a three-month retrospective questionnaire consisting of multiple choice and open-ended questions. This online questionnaire was taken quarterly during the 24 months. The updated Dutch Manual for Cost Analysis in Health Care was used to valuate costs [36]. If cost-prices were not available, other sources were used. For instance, the website [37] was used to calculate medication costs.The costs of medications were calculated based on the dose described by the respondent. Hence, costs per tablet, gram or millilitre were used to calculate total medication costs for each respondent.Costs for health care services, which could not be found in the Dutch Manual for Cost Analysis in Health Care, were looked up on theinternet (e.g., via the websites of health care services). If possible, three costs for each health care service were looked up, to ultimately calculate a mean cost prize for this service. Cost price details can be found in Appendix 1.
Productivity costs included costs due to sickness absenteeism from work. They were calculated via the human capital method using mean costs for the Dutch population corrected for gender and age [36].
Respondent costs(also known as patient and family costs) included the time respondents spent on the website for participation, and costs for travelling to health care services.For the time spent on the website, we used the mean time that was necessary to complete the programme within the three study groups. The time lost due to participation in the Adult Health Monitor was also taken into account, but we only added the time people needed to fill out the partsof the Adult Health Monitorregarding the five lifestylebehaviours. We made this decisionfortwo reasons: firstly, it wasnot necessary to combine the interventions and the entire Monitor of the Regional Health Authorities; secondly, respondents who participated in the Adult Health Monitor skipped these parts on our website, whereas people who did not take part in the Adult Health Monitor completed these questions on our website (i.e., in the end, all respondents completed the same number of questions).Ultimately, we used an average time of 70 minutes for the sequential condition; 100 minutes for the simultaneous condition; and 20 minutes for the control condition. To determine the cost of time spent on the website, we valued the time by applying the labour time using the mean costs of the Dutch population corrected for gender and age[36]. Costs for travelling tohealth care services were also valued in monetary terms.These costs were assessed based on average travel distances to health care services in the Netherlands [38] and the mean costs per km [36].
Effects
For the cost-effectiveness analysis (CEA), the primary outcome measure was thetotal LFS. The following questionnaires were used to assess the five lifestyle behaviours: the Short QUestionnaire to ASsess Health-enhancing physical activity (SQUASH) [39,40], a four-item Food Frequency Questionnaire (FFQ) assessing weekly fruit and fruit juice intake [39], a four-item FFQ assessing the weekly consumption of boiled or baked vegetables, as well as salads or raw vegetables [39], the five-item Dutch Quantity-Frequency-Variability (QFV) questionnaire to assess alcohol intake [39,41], and questions asking participants if they smoked, what they smoked (cigarettes, cigars, or pipe tobacco) and how much they smoked per day (cigarettes) or per week (cigars or pipe tobacco) [39]. Based on the guidelines for physical activity, fruit intake, vegetable intake, alcohol consumption, and smoking, we calculated this LFS by summing up all healthy behaviours (i.e., complying with the guideline in question) – a similar method (Prudence score) was applied by Parekh et al. [42] – atbaseline and after 24 months; the value of the LFS could thus range from 0 (adhering to no guidelines) to 5 (adhering to all guidelines).Moreover, alifestyle factor change index (LFCI) was calculated by subtracting the LFS at baseline from the LFS at 24 months[43]. The value for this index could range from -5 to +5 on a continuous 10-point scale; positive scoresindicated an increase, while negative scores indicated a decrease in the number of healthy behaviours.
For the cost-utility analysis (CUA), the primary outcome measure was utilities based on a health-related quality of life instrument. The Euro-Qol (EQ-5D-3L) [44] was used to assess health-related quality of life. The EQ-5D-3L, which was completed by respondents every three months, consisted of the following five health dimensions: mobility, self-care, daily activity, pain/discomfort, and anxiety/depression. On a three-point Likert scale, respondents had to indicate their own state of health (no complaints=1; some complaints=2; many complaints=3). A utility score was calculated for each measurement point,using the Dutch tariff [45]. This score could range from -0.33 (death) to 1 (perfect health). This utility score, in turn, was used to calculate theQuality Adjusted Life Years (QALYs)gained or lost during the two yearstudy period by making use of the “area under the curve” method. The area under the curve stands for the duration of the health state (x-axis, 24 months) multiplied by the quality weight for the health state (y-axis; utility score).