Cost-effectiveness of active transport for primary school Children – Walking School Bus program
Critical appraisal
` This article contains a study that was carried out to determine the cost effectiveness of active transport for primary school children program which was used as a prevention measure for obesity among school going children (Kelly et al, 2005). This study is carried out in order to determine whether the program is effective to this specific population or not and whether the program is cost effective. The Walking School Bus (WSB) program was conducted among the school going children in Australia. This program was designed as part of the ACE-Obesity study so that it could help in giving results to the study through the use of the program. This study involved the use of consistent methods and thirteen interventions that were aimed at preventing and reducing obesity among Australian children and adolescents (Kelly et al, 2005).
In this particular study, the target population is clearly stated and the study focuses on this population in the right setting. This is appropriate for the facilitating proper implementation of the program and thus providing the right results (Ogilvie et al, 2011). This helped in knowing whether the program was effective or not based on the outcomes. The competing alternatives in this study are clearly stated in that the program (WSB) is implemented to show the benefits of active physical activity in young children and adolescents as compared to inactivity (Ogilvie et al, 2011). This program provides results that show whether physical activity can reduce and prevent obesity in school going children. This program was aimed at bringing other health benefits in addition to the reduction in obesity. These health benefits include mental health, safety and improving and protecting the environment for both the participating children and the society at large. The research question for this study is well stated in that it is answerable during the study and even after the study (Ogilvie et al, 2011). After getting the results of the study, the researchers are able to determine whether the research question has been answered therefore being able to determine whether the study was effective or not. The research question is what guided the study in both the implementation of the program and also in determining the cost effectiveness of the program (Ogilvie et al, 2011).
The economical study design is not appropriate to the stated objective because the cost effectiveness of the program in relation to the economic status is not emphasized (Coast, Smith, & Lorgelly, 2008). This is one of the factors that made the study not to be effective because in as much as the program helped in reducing and preventing obesity among school going children, it did not reach a wide the WSB program managed to reach a total of 7,840 children between 5 to 7 years at a cost of $AUD22.8M. This number of children involved in the walking program did not increase and this limited the sustainability of the program (Coast, Smith, & Lorgelly, 2008). This cost was also high for the program to be effective and sustainable without any increase in the numbers of school going children involved. The cost benefits were amounted to 3% and this shows that the economic study design could not lead to the achievement of the stated objective (Chalkidou et al, 2008). The time horizon set for this study is not realistic to include relevant costs and consequences. This is because it would be impossible to determine the long term costs and consequences of a program before carrying out a short term analysis of the costs and consequences of the same program (Coast, Smith, & Lorgelly, 2008). The life time or 100 years period of time that was used to determine the consequences of the program and calculate the costs could not work on a program that was being implemented for the first time. This is one of the reasons as to why the program did not succeed because the program could have been analyzed on a short term basis at first so that the researchers can get the chance to improve on the factors that came up as challenges to implementation (Chalkidou et al, 2008). Calculating the costs and analyzing the consequences of the program on a sort term basis helps in predicting the sustainability of a program and giving a chance to improve on the recommendations for the implementation of the program (Barendregt, 2006).
Why it was difficult to design and conduct an economic evaluation of this study to measure and value the health outcomes of the intervention
The actual perspective chosen for this study was appropriate but the plans for implementation were not focused on broader issued that surrounded the issue of cost effectiveness and resource allocation (Barendregt, 2006). Therefore, this study was not as effective as it was intended to be. Conducting an economic evaluation of this study to determine the health benefits of the program was difficult because of the unavailability of data that linked the changes in BMI of the participating children during the active period and the period when they were not active. As a result of this, this study used other existing data about the BMI of the participants to predict the changes that were likely to have occurred (Barendregt, 2006). Lack of the critical information and data in determining the health benefits that were as a result of the implementation of the program made it very difficult to come up with accurate results on how this program improve the health of the participants (Weatherly et al, 2009). The important and relevant costs for each alternative are identified but they are not measured and valued appropriately because there are very high uncertainty rates in the figures provided. The costs cutting measures in this study also did not work out because the fixed amounts of money allocated were not enough to make the obesity prevention cost effective. Due to the lack of some data in this study, not all relevant outcomes for each alternative identified (Weatherly et al, 2009). This is because most of the results of the study are based on assumption other than on real information. In most of the cases, it is very difficult to determine the exact outcomes and only predictions are provided. The outcomes of the program implemented are not measured and valued appropriately because some of the information needed in doing this is not available and some of the available information is not 100% correct (Evers et al, 2005). Most of the outcomes are based on prediction. For example, the incremental costs effectiveness results are not reliable because there was no certainty on the range used on the number of days that the participating children walked per week (Evers et al, 2005).
An incremental analysis of costs and outcomes of alternatives is performed. The incremental costs that were linked to the intervention totaled up to $22.8M and this was an average of $2,900 per child every year and the child walking one day per week to school (Evers et al, 2005). The fixed costs for the program totaled up to 86% of the total amount for the entire program. The future costs and outcomes did not discount appropriately because of the high assumptions that were involved in the program. There was a high rate of ICER uncertainty and this was mainly because of the uncertainty in the number of active physical movements per week. Moreover, the number of active transport estimated was very low as compared to the assumptions. In the sensitivity tests results, allocating a section of the total cost of the prevention program to non-obesity objectives and annuitisation of fixed costs were the main variable considered in the cutting costs of the project (Nemet et al, 2005). However, these variables alone could not lead to cost effectiveness of the program. In order to ensured that cost cutting was carried out, improved capacity utilization measures were added the cost cutting measures to ensure that cost effectiveness was possible. Moreover, this was possible “only under the very optimistic scenario” (Nemet et al, 2005). This means that an increase in the number of children participating in the intervention program would lead to cost effectiveness of the program. Therefore, with the small numbers of children involved in the program, cost-effectiveness was not possible even when strong cost-cutting measures are put into place. The sensitivity analysis provides results based on the variables used and also reflects the uncertain values and the results that would be expected when either the two or the three variables are used (Nemet et al, 2005). Therefore, these results give a condition of optimism when cost effectiveness is possible for the intervention program (Evers et al, 2005).
In this study, the conclusions are drawn from the data reported. The conclusion shows the cost effectiveness of this study and compares it to the current economic situations (Kahn et al, 2002). The intervention program is not cost effective in the fight against obesity but it can be effective if its economic credentials are revised and improved to more realistic ones. The implementation can also be improved to increase effectiveness. Therefore, this intervention program has a very high potential of reducing and preventing obesity but in order for it to achieve this, it needs to be restructured within current infrastructure conditions (Kahn et al, 2002).
The study does not provide generalizabilty of the results to other settings and patient/client groups because the settings may be different and the results may not be the same of the intervention program is restructured in another way (Bravata et al, 2007). Moreover, this intervention has not been approved as an obesity prevention initiative but as strategy that encourages behavior change mostly in schools promoting physical activity. The results may be different in different populations and settings different from the ones in this particular study. This article clearly indicates that there is no conflict of interest of the study (Bravata et al, 2007). This indication is of importance to the readers because they can tell that the information contained in the article if not affected in any way by competing interests of the authors and the funders. The ethical and distribution issues are discussed appropriately in the article thus guiding the leader on how it can be accessed and distributed (Bravata et al, 2007). The article is an open access and it is under unrestricted use and distribution. Reproduction of the article is allowed but the original work must be cited appropriately. The users of the article therefore, know how much freedom they have on the use of its contents (Bravata et al, 2007).
References
Barendregt, J. (2006) Economics and public health: an arranged marriage. European Journal of Public Health. 17(2) p.124.
Bravata, D. M., Smith-Spangler, C., Sundaram, V., Gienger, A. L., Lin, N., Lewis, R., … & Sirard, J. R. (2007). Using pedometers to increase physical activity and improve health. JAMA: the journal of the American Medical Association, 298(19), 2296-2304.
Chalkidou, K., Culyer, A., Naidoo, B. and Littlejohns, P. (2008) Cost-effective public health guidance: asking questions from the decision-maker’s viewpoint. Health Economics. 17(3) pp. 441-448.
Coast, J. Smith, R. Lorgelly, P. (2008) Should the capability approach be applied in health economics? Health Economics, 17: 667-670.
Evers, S., de Vet, H., van Tulder, M. and Ament A. (2005) Criteria list for assessment of methodological quality of economic evaluations: Consensus on Health Economic Criteria, Maastricht University, International Journal of Technology Assessment in Health Care, 21:2 (2005), 240–245.
Kahn, E. B., Ramsey, L. T., Brownson, R. C., Heath, G. W., Howze, E. H., Powell, K. E., … & Corso, P. (2002). The effectiveness of interventions to increase physical activity: A systematic review1, 2 1The names and affiliations of the Task Force members are listed in the front of this supplement and at www. thecommunityguide. org. 2Address correspondence and reprint requests to: Peter A. Briss, MD, Community Guide Branch, Centers for Disease Control and Prevention, 4770 Buford Highway, MS-K73, Atlanta, GA 30341. E-mail: PBriss@ cdc. gov. American journal of preventive medicine, 22(4), 73-107.
Kelly, M., McDaid, D., Ludbrook, A., Powell, J. (2005) Economic appraisal of public health interventions. [online] Health Development Agency. Available from: http://www.cawt.com/Site/11/Documents/Publications/Population%20Health/Economics%20of%20Health%20Improvement/Economic_appraisal_of_public_health_interventions.pdf
Nemet, D., Barkan, S., Epstein, Y., Friedland, O., Kowen, G., & Eliakim, A. (2005). Short-and long-term beneficial effects of a combined dietary–behavioral–physical activity intervention for the treatment of childhood obesity. Pediatrics, 115(4), e443-e449.
Ogilvie, D. Bull, F. Powell, J.E. Cooper, A. Mutrie, N. Preston, J. Rutter, H. (2011) An applied ecological framework for evaluating infrastructure to promote walking and cycling : the iConnect study. American Journal of Public Health. 101: 473-481.
Weatherly, H., Drummond, M., Claxton, K., Cookson, R., Ferguson, B., Godfrey, C., Rice, N., Sculpher, M. and Sowden, A. (2009) Methods for assessing the cost-effectiveness of public health interventions: key challenges and recommendations. Health Policy. 93(2-3) pp.85-92.
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