Cost-effectiveness of a universal strategy of brief dietary intervention for primary prevention in primary care: population-based cohort study and Markov model

Cost Effectiveness and Resource Allocation

Caroline Rudisill²  Judith Charlton¹  Nawaraj Bhattarai¹  Martin C Gulliford¹ 

[1] King’s College London, Department of Primary Care and Public Health Sciences, Capital House, 42 Weston St, London SE1 3QD, UK;Department of Social Policy, London School of Economics and Political Science, London, UK

关键词: Depression;    Colorectal cancer;    Stroke;    Coronary heart disease;    Diabetes;    Outcomes;    Cost effectiveness;    Markov model;    Primary care;    Dietary intervention;   

Others  :  809742
DOI  :  10.1186/1478-7547-12-4

 received in 2013-08-14, accepted in 2014-01-29,  发布年份 2014

【 摘 要 】

Background

A healthy diet is associated with reduced risk of diabetes, cardiovascular disease and cancer. The study aimed to evaluate the cost-effectiveness of a universal strategy to promote healthy diet through brief intervention in primary care.

Methods

The research was informed by a systematic review of randomised trials which found that brief interventions in primary care may be associated with a 0.5 portion per day increase in fruit and vegetable consumption. A Markov model that included five long-term conditions (diabetes, coronary heart disease, stroke, colorectal cancer and depression) was developed. Empirical data from a large cohort of United Kingdom-based participants sampled from the Clinical Practice Research Datalink populated the model. Simulations compared an intervention promoting healthy diet over 5 years in healthy adults, and standard care in which there was no intervention. The annual cost of intervention, in the base case, was one family practice consultation per participant year. Health service costs were included and the model adopted a lifetime perspective. The primary outcome was net health benefit in quality adjusted life years (QALYs).

Results

A cohort of 262,704 healthy participants entered the model. Intervention was associated with an increase in life years lived free from physical disease of 41.9 (95% confidence interval -17.4 to 101.0) per 1,000 participants entering the model (probability of increase 88.0%). New incidences of disease states were reduced by 28.4 (18.7 to 75.8) per 1,000, probability reduced 84.6%. Discounted incremental QALYs were 4.3 (-8.8 to 18.0) per 1,000, while incremental costs were £139,755 (£60,466 to 220,059) per 1,000. Net health benefits at £30,000 per QALY were -0.32 (-13.8 to 13.5) QALYs per 1,000 participants (probability cost-effective 47.9%). When the intervention was restricted to adults aged 50 to 74 years, net health benefits were 2.94 (-21.3 to 26.4) QALYs per 1000, probability increased 59.0%.

Conclusions

A universal strategy to promote healthy diet through brief intervention in primary care is unlikely to be cost-effective, even when delivered at low unit cost. A targeted strategy aimed at older individuals at higher risk of disease might be more cost-effective. More effective dietary change interventions are needed.

【 授权许可】

   
2014 Gulliford et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

【 参考文献 】

• [1]Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, Amann M, Anderson HR, Andrews KG, Aryee M, et al.: A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012, 380:2224-2260.
• [2]World Cancer Research Fund: Food, Nutrition, Physical Activity, and the Prevention of Cancer: A Global Perspective. Second Expert Report. Washington DC: World Cancer Research Fund; 2007.
• [3]World Health Organization: Diet, Nutrition and the Prevention of Chronic Diseases: Report of a Joint WHO/FAO Expert Consultation. Geneva: World Health Organization (Technical Report Series 916); 2003.
• [4]Lock K, Pomerleau J, Causer L, Altmann DR, McKee M: The global burden of disease attributable to low consumption of fruit and vegetables: implications for the global strategy on diet. Bull World Health Organ 2005, 83:100-108.
• [5]Department of Health and Human Services. Office of Health Promotion and Disease Prevention: Dietary Guidelines for Americans. 7th edition. Washington DC: Department of Health and Human Services; 2011.
• [6]Wanless D: Securing Good Health for the Whole Population. Final Report. London: HMSO; 2004.
• [7]Takahashi Y, Sasaki S, Okubo S, Hayashi M, Tsugane S: Blood pressure change in a free-living population-based dietary modification study in Japan. J Hypertens 2006, 24:451-458.
• [8]Coates RJ, Bowen DJ, Kristal AR, Feng Z, Oberman A, Hall WD, George V, Lewis CE, Kestin M, Davis M, et al.: The women’s health trial feasibility study in minority populations: changes in dietary intakes. Am J Epidemiol 1999, 149:1104-1112.
• [9]Roderick P, Ruddock V, Hunt P, Miller G: A randomized trial to evaluate the effectiveness of dietary advice by practice nurses in lowering diet related coronary heart disease risk. Br J Gen Pract 1997, 47:7-12.
• [10]Sacerdote C, Fiorini L, Rosato R, Audenino M, Valpreda M, Vineis P: Randomized controlled trial: effect of nutritional counselling in general practice. Int J Epidemiol 2006, 35:409-415.
• [11]Stevens VJ, Glasgow RE, Toobert DJ, Karanja N, Smith KS: One-year results from a brief, computer-assisted intervention to decrease consumption of fat and increase consumption of fruits and vegetables. Prev Med 2003, 36:594-600.
• [12]Kristal AR, Curry SJ, Shattuck AL, Feng Z, Li S: A randomized trial of a tailored, self-help dietary intervention: the puget sound eating patterns study. Prev Med 2000, 31:380-389.
• [13]Baron JA, Gleason R, Crowe B, Mann JI: Preliminary trial of the effect of general practice based nutritional advice. Br J Gen Pract 1990, 40:137-141.
• [14]Fries E, Edinboro P, McClish D, Manion L, Bowen D, Beresford SAA, Ripley J: Randomized trial of a low-intensity dietary intervention in rural residents: the rural physician cancer prevention project. Am J Prev Med 2005, 28:162-168.
• [15]Beresford SAA, Curry SJ, Kristal AR, Lazovich D, Feng Z, Wagner EH: A dietary intervention in primary care practice: the eating patterns study. Am J Public Health 1997, 87:610-616.
• [16]Gann PH, Chatterton RT, Gapstur SM, Liu K, Garside D, Giovanazzi S, Thedford K, Van Horn L: The effects of a low-fat/high-fiber diet on sex hormone levels and menstrual cycling in premenopausal women. Cancer 2003, 98:1870-1879.
• [17]Bhattarai N, Prevost AT, Wright AJ, Charlton J, Rudisill C, Gulliford MC: Effectiveness of interventions to promote healthy diet in primary care: systematic review and meta-analysis of randomised controlled trials. BMC Public Health 2013, 13:1203. BioMed Central Full Text
• [18]Rees K, Dyakova M, Ward K, Thorogood M, Brunner E: Dietary advice for reducing cardiovascular risk. Cochrane Database Syst Rev 2013., (3) Art. No.: CD002128. doi:10.1002/14651858.CD002128.pub4
• [19]Gulliford MC, Charlton J, Bhattarai N, Charlton C, Rudisill C: Impact and cost-effectiveness of a universal strategy to promote physical activity in primary care: population-based Cohort study and Markov model. Eur J Health Econ 2013. Epub ahead of print
• [20]McEwen LN, Coelho RB, Baumann LM, Bilik D, Nota-Kirby B, Herman WH: The cost, quality of life impact, and cost-utility of bariatric surgery in a managed care population. Obes Surg 2010, 20:919-928.
• [21]Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B: Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet 2012, 380:37-43.
• [22]Bhattarai N, Charlton J, Rudisill C, Gulliford M: Prevalence of depression and utilization of health care in single and multiple morbidity: a population-based cohort study. Psychol Med 2013, 43(7):1423-1431.
• [23]Curtis L: Personal Social Service Research Unit (P S S R U): Unit Costs of Health and Social Care. Canterbury: University of Kent; 2010.
• [24]First Data Bank Europe: FDBE Multilex Drug Data File. First Data Bank Europe: Exeter; 2011.
• [25]Sullivan PW, Slejko JF, Sculpher MJ, Ghushchyan V: Catalogue of EQ-5D Scores for the United Kingdom. Med Decis Making 2011, 31:800-804.
• [26]R Program: R: A language and environment for statistical computing. R Foundation for statistical computing: Vienna, Austria; 2010.
• [27]Hoch JS, Briggs AH, Willan AR: Something old, something new, something borrowed, something blue: a framework for the marriage of health econometrics and cost-effectiveness analysis. Health Econ 2002, 11:415-430.
• [28]Briggs A, Claxton K, Sculpher M: Decision Modelling for Health Economic Evaluation. Oxford: Oxford University Press; 2006.
• [29]Charlton J, Latinovic R, Gulliford MC: Explaining the decline in early mortality in men and women with type 2 diabetes. Population-based cohort study. Diabetes Care 2008, 31(9):1761-1766. dc08-0137
• [30]Gulliford MC, Charlton J, Ashworth M, Rudd AG, Toschke AM: Selection of medical diagnostic codes for analysis of electronic patient records. application to stroke in a primary care database. PLoS One 2009, 4(9):e7168.
• [31]Bhattarai N, Charlton J, Rudisill C, Gulliford MC: Coding, recording and incidence of different forms of coronary heart disease in primary care. PLoS One 2012, 7:e29776.
• [32]Cobiac LJ, Vos T, Veerman JL: Cost-effectiveness of interventions to promote fruit and vegetable consumption. PLoS One 2010, 5(11):e14148. doi:10.1371/journal.pone.0014148
• [33]Pomerleau J, Lock K, Knai C, McKee M: Interventions designed to increase adult fruit and vegetable intake Can Be effective: a systematic review of the literature. J Nutr 2005, 135:2486-2495.
• [34]Gibson A, Edgar JD, Neville CE, Gilchrist SE, McKinley MC, Patterson CC, Young IS, Woodside JV: Effect of fruit and vegetable consumption on immune function in older people: a randomized controlled trial. Am J Clin Nutr 2012, 96:1429-1436.
• [35]Naimark DM, Bott M, Krahn M: The half-cycle correction explained: two alternative pedagogical approaches. Med Decis Making 2008, 28:706-712.
• [36]Barendregt JJ: The half-cycle correction: banish rather than explain It. Med Decis Making 2009, 29:500-502.
• [37]Dakin HDN, Feng Y, Rice N, O’Neill P, Parkin D: The Influence of Cost-Effectiveness and Other Factors in NICE Decisions. Oxford: Health Economics Research Centre, University of Oxford; 2013.