Dr Alison Hayes

Senior Research Fellow
Public Health, School of Public Health

Telephone +61 2 9036 7138
Fax +61 2 9351 7420

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Biographical details

Alison Hayes is a Senior Research Fellow in health economics at the School of Public Health, University of Sydney, with a specialisation in health economic modelling of chronic disease. More specifically her work takes a life-course approach to projecting the consequences of chronic disease, with a strong emphasis on modelling the epidemiology of disease and its associated long term costs and quality of life outcomes. The models combine techniques of patient-level simulation with decision analysis for evaluating the cost-effectiveness of interventions. Alison is passionate about using models as translational tools to bridge the gap between cost-effectiveness evidence and policy decisions in public health.

Research interests

Alison Hayes’ research interests include the health economics of diabetes, obesity and cardiovascular disease; she also had an interest in maternal and infant health in low income populations, both in Australia and overseas. Her methodological interests include modelling methods for health economic evaluation, patient-level simulation, risk modelling, quality of life, the measurement of health inequalities and analysis of linked data.

Teaching and supervision

Alison Hayes contributes to the face to face teaching of health economics within the Masters programmes in the School of Public Health. These include Health Economic Evaluation (PUB 5302), Advanced Health Economic Evaluation (PUB 5307) and Making Decisions in Public Health (PUBH 5032). She also contributes to teaching of health economics outside of the university. Dr Hayes is currently associate supervisor for 2 PhD candidates.

Current projects

Alison Hayes’ current research interests include:

  • Health economic modelling of type 2 diabetes progression. Alison has been part of a long term collaboration with researchers and clinicians at the University of Oxford in the development of a health economic and policy model for type 2 diabetes, based on 30 years of data from the United Kingdom Prospective Diabetes Study (UKPDS). A commercial version of this software (UKPDS Outcomes Model v2) is currently being developed by the Diabetes Trial Unit, University of Oxford. Current research includes adaptation of the model to the Australian healthcare setting and in the future, to calibrate the model for China;
  • Economic evaluation of obesity prevention, including early intervention with first-time mothers (the Healthy Beginnings Trial);
  • Economic evaluation of maternal and infant health programmes in low income settings, including the Mirpur Shushi Pushti Trial – a peer counselling intervention to reduce undernutrition in urban Bangladesh, Shonjibon a trial of iron/folic acid supplementation to reduce neonatal mortality in rural Bangladesh and programmes to reduce maternal and child malnutrition in Indonesia (GAIN) ;
  • Economic evaluation of polypill (Kanyini GAP);
  • Population level modelling of obesity progression for long term evaluation and cost-effectiveness analysis of successful preventive health interventions;
  • Prediction of cardiovascular risk;
  • Methodological research in health economic modelling;
  • Quality of life in people with type 2 diabetes;

These studies are being undertaken with a range of collaborators at Sydney University, the George Institute, University of Melbourne, The Baker Institute and the University of Oxford, UK.

Associations

Guest discussant, Economics Sub Committee of Pharmaceutical Benefits Advisory Committee, October 2013.

Member of Expert Advisory Group for the Post-market Review of Products used for the Treatment of Diabetes, since November 2012.

Awards and honours

Honorary Associate, NHMRC Clinical trials Centre, since 2007.

International links

United Kingdom

(Health Economics Research Centre University of Oxford Oxford) Since 2009 I have been part of a multi-disciplinary team of health economists, epidemiologists and clinicians to develop and validate a computer simulation model for modelling the progression of type 2 diabetes, based on a 30-year longitudinal dataset.

Selected grants

2014

  • Effectiveness of an integrated program to reduce maternal and child nutrition in Indonesia; Dibley M, Li M, Hayes A, Alam A, Ferguson E, Titaley C, Ariawan I; The Global Alliance For Improved Nutrition/Research Support.
  • Does the impact of peer counselling for appropriate infant feeding last till the child is five years of age? Extended follow up of children from a community-based trial in urban Bangladesh; Dibley M, Rasheed S, Hamadani J, Agho K, Mihrshahi S, Hayes A; National Health and Medical Research Council (NHMRC)/Project Grants.

2012

  • Can we achieve better clinical and economic outcomes for chronic disease management in primary care asthma and hypertension?; Armour C, Bajorek B, Krass I, Hayes A, Roberts C; Heart Foundation of Australia/Grants-in-Aid.

2011

  • Effectiveness of an early intervention trial to prevent obesity - Phase 2: Follow-up and cost effectiveness analysis; Wen L, Baur L, Rissel C, Flood V, Simpson J, Hayes A, Hardy L; National Health and Medical Research Council (NHMRC)/Project Grants.

Selected publications

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Journals

  • Hayes, A., Davis, W., Davis, T., Clarke, P. (2013). Adapting and validating diabetes simulation models across settings: Accounting for mortality differences using administrative data. Journal of Diabetes and Its Complications, 27(4), 351-356. [More Information]
  • Lung, T., Clarke, P., Hayes, A., Stevens, R., Farmer, A. (2013). Simulating lifetime outcomes associated with complications for people with type 1 diabetes. PharmacoEconomics, 31(6), 509-518. [More Information]
  • Leal, J., Hayes, A., Gray, A., Holman, R., Clarke, P. (2013). Temporal Validation of the UKPDS Outcomes Model Using 10-Year Posttrial Monitoring Data. Diabetes Care, 36(6), 1541-1546. [More Information]
  • Hayes, A., Leal, J., Gray, A., Holman, R., Clarke, P. (2013). UKPDS Outcomes Model 2: a new version of a model to simulate lifetime health outcomes of patients with type 2 diabetes mellitus using data from the 30 year United Kingdom Prospective Diabetes Study: UKPDS 82. Diabetologia: clinical and experimental diabetes and metabolism, 56(9), 1925-1933. [More Information]
  • Wen, L., Baur, L., Rissel, C., Flood, V., Simpson, J., Hayes, A., Hardy, L., Wardle, K. (2012). Healthy Beginnings Trial Phase 2 study: Follow-up and cost-effectiveness analysis. Contemporary Clinical Trials, 33(2), 396-401. [More Information]
  • Lung, T., Hayes, A., Hayen, A., Farmer, A., Clarke, P. (2011). A meta-analysis of health state valuations for people with diabetes: explaining the variation across methods and implications for economic evaluation. Quality of Life Research, 20(10), 1669-1678. [More Information]
  • Hayes, A., Clarke, P., Lung, T. (2011). Change in bias in self-reported body mass index in Australia between 1995 and 2008 and the evaluation of correction equations. Population Health Metrics, 9(25), 53-(9pp). [More Information]
  • Hayes, A., Leal, J., Kelman, C., Clarke, P. (2011). Risk Equations to Predict Life Expectancy of People with Type 2 Diabetes Mellitus Following Major Complications: A Study from Western Australia. Diabetic Medicine, 28(4), 428-435. [More Information]
  • Hayes, A., Clarke, P., Voysey, M., Keech, A. (2011). Simulation of Quality-Adjusted Survival in Chronic Diseases: An Application in Type 2 Diabetes. Medical Decision Making: an international journal, 31(4), 559-570. [More Information]
  • Gerdtham, U., Clarke, P., Hayes, A., Gudbjornsdottir, S. (2009). Estimating the cost of diabetes mellitus-related events from inpatient admissions in Sweden using administrative hospitalization data. PharmacoEconomics, 27(1), 81-90. [More Information]
  • Clarke, P., Hayes, A. (2009). Measuring achievement: Changes in risk factors for cardiovascular disease in Australia. Social Science and Medicine, 68(3), 552-561. [More Information]
  • Clarke, P., Hayes, A., Glasziou, P., Scott, R., Simes, R., Keech, A. (2009). Using the EQ-5D index score as a predictor of outcomes in patients with type 2 diabetes. Medical Care, 47(1), 61-68. [More Information]
  • Hayes, A., Clarke, P., Glasziou, P., Simes, R., Drury, P., Keech, A. (2008). Can self-rated health scores be used for risk prediction in patients with type 2 diabetes? Diabetes Care, 31(4), 795-797. [More Information]
  • Hayes, A., Kortt, M., Clarke, P., Brandrup, J. (2008). Estimating equations to correct self-reported height and weight: implications for prevalence of overweight and obesity in Australia. Australian and New Zealand Journal of Public Health, 32(6), 542-545. [More Information]

2013

  • Hayes, A., Davis, W., Davis, T., Clarke, P. (2013). Adapting and validating diabetes simulation models across settings: Accounting for mortality differences using administrative data. Journal of Diabetes and Its Complications, 27(4), 351-356. [More Information]
  • Lung, T., Clarke, P., Hayes, A., Stevens, R., Farmer, A. (2013). Simulating lifetime outcomes associated with complications for people with type 1 diabetes. PharmacoEconomics, 31(6), 509-518. [More Information]
  • Leal, J., Hayes, A., Gray, A., Holman, R., Clarke, P. (2013). Temporal Validation of the UKPDS Outcomes Model Using 10-Year Posttrial Monitoring Data. Diabetes Care, 36(6), 1541-1546. [More Information]
  • Hayes, A., Leal, J., Gray, A., Holman, R., Clarke, P. (2013). UKPDS Outcomes Model 2: a new version of a model to simulate lifetime health outcomes of patients with type 2 diabetes mellitus using data from the 30 year United Kingdom Prospective Diabetes Study: UKPDS 82. Diabetologia: clinical and experimental diabetes and metabolism, 56(9), 1925-1933. [More Information]

2012

  • Wen, L., Baur, L., Rissel, C., Flood, V., Simpson, J., Hayes, A., Hardy, L., Wardle, K. (2012). Healthy Beginnings Trial Phase 2 study: Follow-up and cost-effectiveness analysis. Contemporary Clinical Trials, 33(2), 396-401. [More Information]

2011

  • Lung, T., Hayes, A., Hayen, A., Farmer, A., Clarke, P. (2011). A meta-analysis of health state valuations for people with diabetes: explaining the variation across methods and implications for economic evaluation. Quality of Life Research, 20(10), 1669-1678. [More Information]
  • Hayes, A., Clarke, P., Lung, T. (2011). Change in bias in self-reported body mass index in Australia between 1995 and 2008 and the evaluation of correction equations. Population Health Metrics, 9(25), 53-(9pp). [More Information]
  • Hayes, A., Leal, J., Kelman, C., Clarke, P. (2011). Risk Equations to Predict Life Expectancy of People with Type 2 Diabetes Mellitus Following Major Complications: A Study from Western Australia. Diabetic Medicine, 28(4), 428-435. [More Information]
  • Hayes, A., Clarke, P., Voysey, M., Keech, A. (2011). Simulation of Quality-Adjusted Survival in Chronic Diseases: An Application in Type 2 Diabetes. Medical Decision Making: an international journal, 31(4), 559-570. [More Information]

2009

  • Gerdtham, U., Clarke, P., Hayes, A., Gudbjornsdottir, S. (2009). Estimating the cost of diabetes mellitus-related events from inpatient admissions in Sweden using administrative hospitalization data. PharmacoEconomics, 27(1), 81-90. [More Information]
  • Clarke, P., Hayes, A. (2009). Measuring achievement: Changes in risk factors for cardiovascular disease in Australia. Social Science and Medicine, 68(3), 552-561. [More Information]
  • Clarke, P., Hayes, A., Glasziou, P., Scott, R., Simes, R., Keech, A. (2009). Using the EQ-5D index score as a predictor of outcomes in patients with type 2 diabetes. Medical Care, 47(1), 61-68. [More Information]

2008

  • Hayes, A., Clarke, P., Glasziou, P., Simes, R., Drury, P., Keech, A. (2008). Can self-rated health scores be used for risk prediction in patients with type 2 diabetes? Diabetes Care, 31(4), 795-797. [More Information]
  • Hayes, A., Kortt, M., Clarke, P., Brandrup, J. (2008). Estimating equations to correct self-reported height and weight: implications for prevalence of overweight and obesity in Australia. Australian and New Zealand Journal of Public Health, 32(6), 542-545. [More Information]

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