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Idioms_eoi.pdf

Strategic Research Development Committee
Expression of Interest
Research into Chronic Disease: Unified Systems of Care
1. Application Title
Intranet Diabetes Outcomes Management Systems (IDiOMS)
Unified information delivery for evidence-based practice in a multicultural society
Synopsis of Research Project
The present project aims to provide the Australian health system with an ad hoc, evidence and popu-
lation-based health information system, to support diabetes care and outcomes management on a
continuous basis. The proposed model is a generalisation of modern approaches in disease manage-
ment, suggesting a unified design for information delivery that would support the use of population
data in the practice setting and enhance the possibilities to apply these data directly to patient care.
This project will aim to build improved systems of care for chronic diseases, providing clinical net-
works and consumers with shared information and direct access to patterns of care, trends and varia-
tions. A specialised prototype will be implemented, compliant with current standards for secure
communications and underpinned by rigorous health services and outcomes research methodology.
2. Indicative Budget: 550,000 $
3. Duration of project : 3 years
4. Contact details for the Chief Investigators
Name of Chief Investigator A (CIA): A/Prof Fabrizio Carinci, Director, Centre for Health Systems Research Monash Institute of Health Services Research Locked Bag 29, Monash Medical Centre, Clayton, VIC 3168 Name of Chief Investigator B (CIB): Prof. James Best Head, Department of Medicine, St.Vincent’s Hospital Department of Medicine, St Vincent’s Hospital Melbourne, Name of Chief Investigator C (CIC): A/Prof. Siaw-Teng Liaw, Name of Chief Investigator D(CID): Prof. Kerin O’Dea, Director, Menzies School of Health Research 5. Administering Institute
Monash Institute of Health Services Research Locked Bag 29, Monash Medical Centre, Clayton, VIC 3168 Intranet Diabetes Outcomes Management Systems (IDiOMS) Unified information delivery for evidence-based practice in a multicultural society F.Carinci, J.Best, T.Liaw, K.O’Dea 6. Hypothesis, aims and scope of the research
There is increasing evidence that Disease Management (DM) strategies, supported by innovative methods in Outcomes Research, may improve health outcomes and contain costs of care in popula-tions affected by chronic diseases [1]. DM is frequently represented by a quality improvement cycle, which incorporates changes from emerging best practices and adopts a systematic and comprehensive evaluation model. Research at the international level has shown that well-designed clinical and popu-lation data information can efficiently integrate population data with evidence-based guidelines and promote effective DM, informed clinical practice, high quality health services research, and better health policy [2-4]. Recent initiatives in Australia have paved the way to build solutions around a common terminology and standards for messaging and patient record database (EHR) architecture. Here we propose the development of Intranet Diabetes Outcomes Management Systems (IDiOMS), as a system to unify information delivery for the investigation of diabetes in different populations and
the enhancement of informed clinical practice in different settings of care. The GP Data Model and
the National Health Data Dictionary will provide a central platform around which to design, operate
and evaluate effective clinical and population data information systems to support and enhance
chronic disease management strategies in Australia [5]. IDiOMS will result in specialised software to
automate periodic clinical and population-based reports, along with the clinical guidelines and indica-
tions for their applicability.
7. Outline of the proposed research methods with rationale
Diabetes is a serious and escalating health problem in Australia. The recent AusDiab survey indi- cated that diabetes prevalence in Australia has doubled over the past 20 years, in association with marked increases in overweight and obesity [6]. Two population groups most affected are the elderly (20% of those over 65 have diabetes) and Indigenous Australians, who not only have very high diabe-tes prevalence, but also a 20-30 years earlier age of onset [7]. The AusDiab survey highlighted the burden of undiagnosed diabetes in Australia (a little over half of the diabetes cases were previously undiagnosed). There is therefore a strong case for systems that facilitate the adoption by primary care practitioners of best practice guidelines for the early detection and treatment of diabetes in Australia. The objective of the project is to identify, develop and validate a clinical and population-based in- formation system (CPBIS) that will support the management of diabetes in different settings. IDiOMS will result in the production of software that will link population information to clinical records from different regional areas, generating online reports, customised for the specific clinical problem and di-rectly accessible to the group of participants (intranet). Participating centres will include: a) Hospitals, diabetes centres and specialists; participation will be enlisted by CIB, initially through St Vincent’s and St George’s Hospitals Melbourne, with Gippsland Base Hospital in Sale, Victoria as a rural hospital site. Current links between CIA, CIB and Southern Health will allow involvement of associates at the Monash Medical Centre. For later expansion of hospital site involvement we plan to utilise the FIELD (Fenofibrate Intervention and Event Lowering in Diabetes) study network of 38 Australian specialist diabetes care sites, nearly all of which are in Hospitals, with 17 outside capital cities. CIB is a member of the management committee executive of the FIELD study, which is run by the NHMRC Clinical Trials Centre. b) divisions of general practice; Cis and associate have very close links and collaborative programs with a number of suburban and rural divisions Victoria. c) individual GPs; a large number of GPs are currently involved in the teaching and research pro- grams of The University of Melbourne, Monash University and associates’ centres. d) consumers; to be directly involved in the research program through the participating centres. Software implementation will proceed through the following steps: 1) defining registries, 2) collect- ing existing clinical and population data, 3) linking data on health services utilization, 4) integrating clinical guidelines and 5) presenting specific integrated information to the user to support clinical and population-based decision making. To develop IDiOMS, a multidisciplinary team will design the clinical and information model and scheme for data entry, management and integration, at both indi-vidual and aggregated levels. IDiOMS will provide participating health providers and organisations with online periodical reports that will include accurate information on outcomes in the population Intranet Diabetes Outcomes Management Systems (IDiOMS) Unified information delivery for evidence-based practice in a multicultural society F.Carinci, J.Best, T.Liaw, K.O’Dea with online periodical reports that will include accurate information on outcomes in the population
and the quality and relative performance of health services. Routine patient databases will be left unal-
tered or enhanced to enable data collection at point of care. This will ensure a minimum impact on the
workload of remote operators as well as an overall cost-containment for the project. Secure access to
clinical records will comply with current regulations. Data transfer will be allowed in deidentified
form only. IDiOMS will build on the foundations of previous experiences. In particular, RISS (Report-
ing-by-Intranet Statistical system)
, a project that led to the construction of specialized software [8,9]
and FRAMS (Falls Risk Assessment and Management System), a prototype Internet and Intranet-
based software based on the GP Data Model and Core Data Set and existing Australian standards
[10,11]. RISS adopts a multilevel structure able to generate real time statistical analysis at the systems
level. A basic concept in RISS is accepting the fragmented structure of data, building a statistical
analysis over a distributed database. A desirable property of the system is delivery of reports at remote
and central sites in the form of HTML pages, so that users with minimal IT knowledge may easily
browse them. The FRAMS methodology involves an intensive grounded approach to develop a clini-
cal and information model to underpin a Diabetes Risk Assessment and Management System
(DRAMS) within IDiOMS. It will make best practice guidelines, formalised in the Arden Syntax
[12,13], available via an Internet browser, electronic health record (EHR) and IDiOMS. Such guide-
lines will be derived from the NHMRC National Evidence Based Guidelines for the Management of
Type 2 Diabetes Mellitus, developed with consumer and GP participation and through a process of
public consultation (www.diabetesaustralia.com.au, completion announced for 2002). There has been
strong CI involvement in this process, as CIB chaired the working group on Lipid Management and
CID chaired the working group on Primary Prevention. The clinical implications of the proposed sys-
tem are based on the success of DM programs for diabetes care and prevention, resulting in improved
outcomes [14-16]. Developing a virtual registry from EHRs will allow more accurate investigation of
risk factors and outcomes such as mortality, diabetic complications and general health outcomes. IDi-
OMS will be designed to harmonise the collection of a multidimensional set of risk indicators, build-
ing comprehensive models over a range of outcomes. Modelling diabetes care may represent an im-
portant step in developing a systems approach to the organisational and ecological predictors of out-
comes. Quality improvement cycles in DM imply an accurate economic evaluation and a clear under-
standing of behavioural pathways. Few reports include data on patient-provider interaction, although
there is increasing evidence that this factor plays an important role in determining good self-
management, which is itself related to improved diabetes outcomes. IDiOMS may suggest interven-
tion strategies for subgroups at high risk, in an area where quality of life measures have been shown to
be stronger predictors of premature mortality, relative to traditional biological measurements [17].
IDiOMS will specifically address the impact of socio-economic factors on health outcomes, applying
the methodology to the longitudinal analysis of high risk and disadvantaged strata, in particular: aged
subjects, Indigenous Australians, and people in rural and remote Australia. The analysis of data from
these populations will improve our understanding of the impact of individual and environmental char-
acteristics in relation to other risk factors playing a role in determining poor outcomes. Examples in-
clude poor quality food supply in remote Australia, and depression, which affects at least 15% of pa-
tients with diabetes [18].
8. Indicative budget for the proposal, with brief budget justification
The activity of the project will be organised in three areas: 1) design and evaluation, at the level of the multidisciplinary team of investigators; 2) operational at the level of the statistical core unit 3) op-erational at the level of the clinical users. Allocation to travel and meetings is essential because the design has to be accurately specified to fit the needs of users and solve practical problems. A brief outline of the approximate total expenses is the following: Classification
Overall Cost (AUD)
Principal research fellows (Executive Level 2) Intranet Diabetes Outcomes Management Systems (IDiOMS) Unified information delivery for evidence-based practice in a multicultural society F.Carinci, J.Best, T.Liaw, K.O’Dea Equipment (hardware, software, additional materials) 9. Outline of the anticipated outcomes and their relevance and/or applicability
The production of a multilevel data analysis system will allow real-time control on outcomes and the definition of risk patterns at the population level, as well as interpreting the role of health services
in terms of efficacy and efficiency. The present project will also deliver the prototype, to be used lo-
cally
, as a prototype for the exploration, the estimation and simulation of different strategies for the
prevention and the delivery of health services in chronic diseases, and nationally, as a novel design to
be extended to other areas, and/or added to other clinical networks. The extensive networks of the
Chief Investigators in the areas of General Practice, Diabetes Specialist Centres, Geriatric Medicine,
and Indigenous Health will facilitate the wider dissemination of this system nationally once it has
been thoroughly field tested at the pilot sites which cover the main target groups (aged care, Indige-
nous, rural and remote). An experimental consumer interface will be designed and implemented in the
system.
10. Proposed timeline

The timing for the prototype completion will be three years. The first year will be used for design and development, the second year for beta testing and implementation, the third year for follow-up
and evaluation.
References
1.
Ellrodt G et al., Evidence-based Disease Management, JAMA, 1997; 278:1687-1692 Epstein RS, Sherwood LM, From outcomes research to disease management: guide for the perplexed, Ann Intern Med, 1996;124:832-837 Balas et al., The clinical value of computerized information services: a review of 98 randomised clinical trials, Arch fam Med,1996; 5:271-8 Hunt et al., Effects of computer-based clinical decision support systems on physician performance and patient out-comes. A systematic review, JAMA, 1998; 280:1339-46 National Health Information Management Advisory Council. Setting the Standards. A National Health Information Standards Plan for Australia. Canberra: Department of Health and Aged Care; 2001 Feb 2001. Report No.: 0642 44743 8. Dunstan D, Zimmet P,Welborn T et al, Diabesity and associated disorders in Australia 2000, International Diabetes Institute, Melbourne, 2001 McDermott R, Rowley KG, Lee A, Knight S, O’Dea K. Increase in the prevalence of obesity and diabetes and de-creased plasma cholesterol in a central Australian Aboriginal community. Med J Aust 172: 480-484, 2000. Carinci F, Corrado D, Dettorre A, Pellegrini F, A multilevel approach to health systems analysis using RISS (Report-ing-by-Intranet Stat System), 4th International Conference on the Scientific Basis of Health Services Research, Syd-ney, 22-25 September 2001. Carinci F, RISS Samples, http://www.med.monash.edu.au/healthservices/chsr/software/Samples/veneto_diabete/Reports/RI_Indici_per_Ospedale%5bOSR%5d.HTML, accessed 18 February 2002 10. FRAMS prototype available at http://www.falls.unimelb.edu.au. 11. GP Computing Group, Department of Health and Aged Care. General Practice Data Model and Data Dictionary. 12. HL7 HLS. Arden syntax for medical logic systems. Ann Arbor, MI: American Society for Testing and Materials 13. Hripcsak G. Writing Arden Syntax medical logic modules. Computers in Biology & Medicine 1994;24(5):331-363. 14. Griffin S, Diabetes Care in general practice: meta-analysis of randomised control trials, Br Med J, 1998; 317:390-6 15. Sadur CN et al., Diabetes Management in a Health Maintenance Organization, Diabetes Care, 1999; 22:2011-2017 16. Aubert et al., Nurse case management to improve glycemic control in diabetic patients in a health maintenance or- ganization, Ann Intern Med, 1998; 129:605-612 17. Glasgow RE et al., Behavioural science in diabetes, Diabetes Care, 1999; 22:832-43 18. Peyrot M et al., Levels and risks of depression and anxiety symptomatology among diabetic adults, Diabetes Care, Intranet Diabetes Outcomes Management Systems (IDiOMS) Unified information delivery for evidence-based practice in a multicultural society F.Carinci, J.Best, T.Liaw, K.O’Dea 11. Qualifications, experience, list of publications for the chief investigators

Chief Investigators
A/Prof. Fabrizio Carinci
, MStat, Senior Research Fellow, Monash University, Director, Centre for
Health Systems Research, worked at public health research internationally; expert in statistical meth-
ods for the classification of patients, risk stratification, meta-analysis and health services research.
1. Fresco C, Carinci F et al., Very early assessment of the risk of in-hospital death in 11,483 patients
with acute myocardial infarction, Am Heart J, 1999; 138:1058-64. 2. Nicolucci A, Carinci F et al. Stratifying Patients at Risk of Diabetes Complications: An integrated look at clinical, socio-economic and care-related factors, Diabetes Care, 1998; 21 (9): 1439-1444. 3. Carinci F et al. Role of Interactions between Psychological and Clinical Factors in determining 6- Month Mortality among patients with AMI, Eur Heart J, 1997; 18:835-845. 4. Marchioli R, Marfisi R, Carinci F et al., Meta-Analysis, clinical trials, and transferability of trials results into practice: the case of cholesterol lowering interventions in secondary prevention of coronary heart disease, Archives of Internal Medicine, 1996; 156:1158-1172. 5. Nicolucci A, Carinci F et al., The efficacy of tolrestat in the treatment of diabetic peripheral neu- ropathy: a meta-analysis of individual patient data, Diabetes Care, 1996; 19, 10:1091-1096.
Prof. James Best
, MBBS, MD, FRACP, FRCPath, St Vincent’s Hospital, University of Melbourne.
Over 20 years clinical and research experience in field of diabetes, including development of shared care
diabetes program with General Practitioners. Major interests in cardiovascular risk factors in Type 2 dia-
betes and development of treatment guidelines.
1. O’Neal, D.N., Lewicki, J., Ansari, M.Z., Matthews, P.G. and Best, J.D. Lipid risk factors for periph-
eral vascular disease in NIDDM and in non-diabetic subjects. Atherosclerosis 136:1-8, 1998. 2. Best, J.D. and O’Neal, D.N. Diabetic dyslipidaemia: current treatment recommendations. Drugs 59: 3. Rowley, K.G., Iser, D.M., Best, J.D., O’Dea, K., Leonard, D. and McDermott, R. Albuminuria in Australian Aboriginal people: prevalence and associations with components of the metabolic syn-drome, Diabetologia 43: 1397-1403, 2000. 4. Barter, P., Best, J., Boyden, A., Cooper, C., Sheerin, N., Thompson, P., Tonkin, A. (Core writing group for National Heart Foundation of Australia). Lipid Management Guidelines – 2001. Med J Aust 175: S57-S88, 2001. 5. Vale, M.J., Jelinek, M.V., Best, J.D., Santamaria, J.D. Coaching patients with coronary heart disease to achieve the target cholesterol. A method to bridge the gap between evidence-based medicine and the “real world” – randomized controlled trial. Clin Epidemiol 55: 245-252, 2002.
A/Prof Siaw-Teng Liaw
PhD, FRACGP, Associate Professor of General Practice, University of Mel-
bourne, has research expertise in patient-held health records and use of information and communica-
tion technologies to share information and support online communities to improve evidence-based
care in asthma, mental health, falls prevention, diabetes, and complex cardiovascular disease. Rele-
vant publications include:
1. Liaw ST, Pearce C, Jackson B. Anticoagulant Therapy. Will computer use improve outcomes?
Aust Fam Physician October 2001; 30(10): 964-968 2. Liaw ST, Marty J. Learning to consult with computers. Med Educ 2001; 35(7): 645 3. Liaw ST. Telehealth - convergence for personal health care. Telehealth International 2000; 1(1): 4. Liaw ST, Radford AJ, Maddocks I. The impact of a computer-generated patient-held health re- cord. Aust Fam Physician 1998; 27(Suppl 1): S39-S43. Intranet Diabetes Outcomes Management Systems (IDiOMS) Unified information delivery for evidence-based practice in a multicultural society F.Carinci, J.Best, T.Liaw, K.O’Dea 5. Liaw ST, Lawrence MSTA, Rendell J. The effect of a computer-generated patient-held medical record summary and/or a written personal health record on patients' attitudes, knowledge and be-haviour concerning health promotion. Fam Practice 1996; 13(3): 289-293.
Prof. Kerin O’Dea
, BSc, PhD, Director, Menzies School of Health Research, Darwin. Major interests
in nutrition and population health as applied to preventable chronic diseases. Twenty five years re-
search in Aboriginal health, with a particular focus on type 2 diabetes – epidemiology, and primary
and secondary prevention through diet and lifestyle-based interventions at the community level.
Chaired the Prevention working group for the Type 2 Diabetes Guidelines. The Prevention Guidelines
have been approved by NHMRC. Member of the National Diabetes Strategies Group.
1. O’Dea K. Clinical implications of the ‘thrifty genotype’ hypothesis: Where do we stand now?
Nutr Metab Cardiovsc Dis 7:281-284, 1997. 2. Daniel M, Rowley KG, McDermott R, Mylvaganam A, O’Dea K. Diabetes incidence in an Australian Aboriginal population: eight year follow up study. Diabetes Care 22: 1993-1998, 1999. 3. Daniel M, O’Dea K, Rowley KG, McDermott R, Kelly S. Glycated hemoglobin as an indicator of social environmental stress in indigenous versus westernized populations. Prev Med 29: 405-413, 1999. 4. Rowley KG, Gault A, McDermott R, Knight S, McLeay T, O’Dea K. Reduced prevalence of im- paired glucose tolerance and no change in prevalence of diabetes despite increasing BMI among Aboriginal people from a group of remote homeland communities. Diabetes Care 23: 898-904, 2000 5. Rowley KG, Su Q, Cincotta M, Skinner M, Skinner K, Pindan B, White GA, O’Dea K. Improve- ments in circulating cholesterol, antioxidants, and homocysteine after dietary intervention in an Australian Aboriginal community. Am J Clin Nutr 2001; 74:442-8
Associate Investigators
Prof. Allan Joseph McLean
BSc (Med),MBBS (Hons I), FRACP, PhD, Grad Dip Management
(Technology Mgt), Grad Dip Management , Assoc Fellow Aust College Health Service Executives, is
the Director of the National Ageing Research Institute, Director of Aged Care Services, Melbourne
Health, Director of Geriatric Medical Services, Royal Melbourne Hospital, Professor, Department of
Medicine, University of Melbourne, Professor of Gerontology, University of Canberra, Professor, Di-
vision of Neurosciences, John Curtin School of Medical Research, Australian National University.
Allan McLean has a broad experience in biological research, with a particular focus on liver and age-
ing, an extensive experience in translational research into clinical practice, and large-scale clinical
trial experience. He was an early (1980-1983) innovator in use of online pharmacy record analysis for
quality assurance in medication use and therapeutic policy formation. The National Ageing Research
Institute is the original multidisciplinary Institute in Australia focussing on research into ageing,
health service delivery, public health, preventive medicine and health policy. The Institute has a large
(>600 persons) pool of healthy aged volunteers who have participated in studies ranging from clinical
trials( eg pain research, vaccine trials, paiun research).
Dr John Boffa is a public health medical officer at the Central Australian Aboriginal Congress, Alice
Springs. He is a general practitioner with public health training and experience who has worked in
Aboriginal health services in Central Australia for the past 13 years. He works with senior Aboriginal
management of health policy, program development, planning and evaluation as well as maintaining
two clinical sessions per week. He has a major role in the development of Congress' medical informa-
tion systems and in the development and evaluation of Clinical Quality Assurance Systems.
Intranet Diabetes Outcomes Management Systems (IDiOMS) Unified information delivery for evidence-based practice in a multicultural society F.Carinci, J.Best, T.Liaw, K.O’Dea
Dr. Michael Lowe
is a physician specialising in diabetes and related conditions. He has completed a
fellowship of the Royal Australasian College of Physicians in 1998 and a Graduate Diploma in Clini-
cal Epidemiology through the University of Newcastle Centre for Clinical Epidemiology and Biosta-
tistics in 1996. He has written extensively in the field of ethics and is co-author of the book "Ethics
and Law for the Health Professions" (Social Science Press, 1998). He has worked at Fiji School of
Medicine from 1998-2001, as Senior Lecturer and Associate Professor of Medicine. Currently, he is a
Staff Specialist Physician at the Royal Darwin Hospital, Northern Territory.
Dr Sam Heard is the Director of the General Practice Academic Unit, Northern Territory Clinical
School, Flinders University, Royal Darwin Hospital. He has considerable experience in medical in-
formatics, in particular in modelling with professionals to develop simple, useful and usable compo-
nents for Clinical Information Systems in Primary Care. He is a member of the Electronic Health Re-
cord (EHR) Architecture Working Party, General Practice Computing Group, and Co-Chair, HL7
EHR Special Interest Group. During the last years, he participated to a stream of research projects in
collaboration with partners involved in the GPCG and the EHR. He has undertaken formal training in
general practice in the UK and has extensive experience in teaching and course development, includ-
ing university curriculum development.
Thomas Beale is a system analyst, senior programmer, and the technical lead for the GEHR. He is a
consultant specialising in health and community informatics. His primary interests are standards, re-
quirements, design, and the adoption of modern open source techniques in applications of social rele-
vance.


Source: http://mihsr.med.monash.edu.au/intranet/chsr/FabrizioCarinci/proposals/IDIOMS_EOI.pdf

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