The Evaluation of Screening Policies for Diabetic Retinopathy using Simulation

Transcription

1 The Evaluation of Screening Policies for Diabetic Retinopathy using Simulation R. Davies 1, S.C. Brailsford 1, P.J. Roderick 2 and C.R.Canning 3 1 School of Management, University of Southampton, UK 2 Wessex Institute of Health Research & Development, University of Southampton, UK 3 Southampton University Hospitals Trust, UK

2 Diabetes mellitus Common disease affecting 1 2% of population of UK Accounts for 4 5% of total health care expenditure in UK Exists in two forms: insulin-dependent (IDDM) and non-insulin-dependent (NIDDM) IDDM (type 1 or acute-onset) usually diagnosed under age 21 NIDDM (type 2 or older-onset) usually diagnosed over age 40 University of Vienna, June 2002 Slide 2

3 IDDM (Type 1) IDDM accounts for 15% of all cases of diabetes Incidence in Europe varies: highest in north (e.g. Finland 43 cases per 100,000 per year) & lowest in south: UK 17 cases per 100,000 per year) Onset is sudden: obvious symptoms (e.g. excessive thirst, tiredness, or even coma) No evidence of higher prevalence in UK ethnic minorities Incidence in children may be increasing University of Vienna, June 2002 Slide 3

4 NIDDM (Type 2) NIDDM accounts for 85% of all cases of diabetes Estimated equal numbers of diagnosed and undiagnosed cases About 2 million cases in the UK (diagnosed and undiagnosed) Prevalence of diagnosed NIDDM in UK estimated between 4 and 9 % Onset is insidious; may already have complications at diagnosis Prevalence of NIDDM is 2 to 4 times higher in Asians and Afro-Caribbeans Overall incidence increasing due to lifestyle changes? University of Vienna, June 2002 Slide 4

5 Diabetic retinopathy One of the most serious complications of both types of diabetes: sight-threatening eye disease DR is the major cause of blindness in the developed countries Retinopathy can be detected before the patient is aware of any symptoms.. and can be successfully treated by laser University of Vienna, June 2002 Slide 5

6 Photograph of the retina, showing patches of retinopathy

7 What is diabetic retinopathy? Raised blood glucose levels cause microvascular damage throughout the body In the eye, some small retinal blood vessels close off and others dilate : called Background Diabetic Retinopathy (BDR) Can lead to two types of disease Diabetic Macular Oedema (DMO) Proliferative Diabetic Retinopathy (PDR) University of Vienna, June 2002 Slide 7

8 Diabetic Macular Oedema Swelling of vessels spreads to macula area where best vision is concentrated Can lead on to Clinically Significant MO (CSMO), when it becomes sight-threatening Most common in elderly: gradual onset, slow deterioration in vision University of Vienna, June 2002 Slide 8

9 Proliferative Retinopathy (PDR) Growth of new vessels off the back of the retina Causes visual loss through bleeding and scar tissue formation Sudden, catastrophic and total sight loss (usually due to a bleed) Most common in IDDM University of Vienna, June 2002 Slide 9

10 Screening for DR: methods Fundoscopy: direct examination of the retina using an ophthalmoscope Photography: with or without mydriasis (eye drops to enlarge the pupil); various types of camera (Polaroid, digital, etc) Visual acuity tests University of Vienna, June 2002 Slide 10

11 Screening for DR: settings In hospital At local doctor s surgery In high-street optometrist shop In mobile van University of Vienna, June 2002 Slide 11

12 Screening for DR: screeners Family doctor (General Practitioner) Diabetic specialist Eye specialist (ophthalmologist) High-street optometrist Trained technician takes photographs, subsequently reviewed by various grades of doctor University of Vienna, June 2002 Slide 12

13 Screening issues By whom? By what technique? Whom to target? How often, and where? Cost-effectiveness Coverage and compliance University of Vienna, June 2002 Slide 13

14 The research project Many different types of screening programme currently in use: no general consensus about form of an ideal screening policy Project funded by UK National Health Service Our task: evaluate and compare range of screening policies, using discrete-event simulation Develop model of the natural history of diabetic retinopathy in a population, incorporating new cases as they are diagnosed Superimpose different screening policies on this baseline model and compare outcomes University of Vienna, June 2002 Slide 14

15 Working with the model Work with clinicians and epidemiologists in collecting and analysing data and designing model Design interface for population, epidemiological and run time data Validate model against published data Derive cost data Perform spreadsheet analysis Experiment with model, summarise and discuss results University of Vienna, June 2002 Slide 15

16 The simulation model(s) Population representing a UK Health District (approx 250,000) People classified by age, sex & ethnicity Simulate 25 years, including new cases Data on incidence, prevalence, progression, mortality, screening and treatment from published literature Investigate different screening policies, with associated costs Key output measure: cost per sight-year saved University of Vienna, June 2002 Slide 16

17 Disease progression No retinopathy NIDDM only Background Diabetic Retinopathy (BDR) Proliferative Diabetic Retinopathy (PDR) Blindness from PDR No retinopathy Diabetic Macular Oedema (DMO) Clinically Significant Macular Oedema (CSMO) Blindness from CSMO

18 Discrete Event Simulation Models individuals moving through a system (queuing network) Characteristics influence progression Random numbers used to sample from distributions Can incorporate delays or interactions Can incorporate constraints University of Vienna, June 2002 Slide 18

19 Advantages of DES Flexible building blocks Can use any distributions Individual variability and uncertainty Takes account of patients characteristics Can take account of limited resource availability Natural structure for costing University of Vienna, June 2002 Slide 19

20 Drawbacks of DES Greedy for computer memory and time consuming (declining problem!) Needs statistical techniques to analyse results Tempting to make models complex Need OR and programming skills for patient flow models University of Vienna, June 2002 Slide 20

21 Modelling Problems Events happen to patients in different orders Groups of events may have different timescales Different processes go on at the same time, and interact, e.g. disease progression, death and screening Need to interrupt and reschedule processes: e.g. resample time of death, since the probability of death may change if the patient changes state University of Vienna, June 2002 Slide 21

22 POST - Patient oriented simulation technique Davies, O Keefe and Davies (1993) Can cope with simultaneous, interacting processes Entities can take part in several activities, and be in several queues, at the same time One event can interrupt and change others University of Vienna, June 2002 Slide 22

23 Three simultaneous processes Policy 1 False +ve Further disease to detect Screening Screen for any retinopathy Detect background retinopathy Visit ophthalmology clinic Detect and treat PDR or CSMO Diagnose diabetes Natural history Background retinopathy PDR DMO PDR + DMO PDR + CSMO Severe vision loss Death from any state CSMO Central vision loss Screening & treatment Disease progression Death University of Vienna, June 2002 Slide 23

24 POST - Patient oriented simulation technique Uses set of procedures and functions in Delphi Patient can be set to take part in more than one event - the earliest one takes precedence over the others Patients can queue while taking part in events Future events can be extracted from the calendar and terminated or changed and returned University of Vienna, June 2002 Slide 24

25 Verification and Validation Does model progress smoothly over time? Do screening and treatment episodes accord with experience? Does prevalence of disease accords with research findings? Problems can arise if there is a mismatch with incidence data. Is it recognisable to the experts? University of Vienna, June 2002 Slide 25

26 Model validation Prevalence of retinopathy Any retinopathy PDR DMO Years from diagnosis Simulation WESDR Proliferative Retinopathy WESDR Any Retinopathy WESDR Macular Oedema University of Vienna, June 2002 Slide 26

27 Screening policies Policy 1: initial screen in primary setting, with follow-up screening in hospital on detection of BDR (or worse) Policy 2: continue to screen in primary setting, i.e. no follow-up screen, until treatable retinopathy detected Investigate different intervals for both University of Vienna, June 2002 Slide 27

28 The screening structure Screening Policy 1 New arrivals No Follow-up screen OP1 Primary screen + + BDR or DMO PDR or CSMO + OP2 + Treatment Treated for both PDR and CSMO? Yes Stop screening + = Positive test result = Negative test result OPi Confirmatory test of positive result

29 Screening policy 2 No New arrivals Screen + OP Treated for both PDR and CSMO? Yes Stop screening + = Positive Positive test test result result = Negative Negative test test result result + Treatment University of Vienna, June 2002 Slide 29

30 Examples of model data (Sensitivity, specificity) (%) Policy Initial screening interval (months) Screening interval after detection of retinopathy Optometrist fundoscopy (73, 93) Diabetologist fundoscopy (81, 95) GP fundoscopy (52, 84) Mobile camera (1 photo, reviewed by diabetologist) (61, 85) Assumed gold standard (ophthalmologist, mydriatic 7-field photography) (98, 100) 1 6 3

31 Costs in Retinopathy study Ophthalmic clinic 53 Other OP clinic 52 Optician visit 29 GP visit 28 Mobile van 16 Treatment session 90 University of Vienna, June 2002 Slide 31

32 Experimentation Need adequate replications: we did 500 Need to cover key scenarios e.g. vary screening interval, screening age, method, compliance etc. Vary more than one together Test with different populations University of Vienna, June 2002 Slide 32

33 Results (i) Average annual results Optometrist (Policy 1) Mobile camera (Policy 2) Gold standard IDDM NIDDM IDDM NIDDM IDDM NIDDM Years of sight saved Patients saved from blindness Visits to primary screener Ophthalmology OP visits Courses of treatment for CSMO Courses of treatment for PDR Total costs ( 000) Costs per year of sight saved Average years of sight lost with no screening was 82 for IDDM and 226 for NIDDM

34 Results (ii) Standard methods of screening save up to 50% of the potential sight years lost. They give up to 85% of the sight years saved by an idealised gold standard programme using mydriatic 7-field photography reported by an ophthalmologist. University of Vienna, June 2002 Slide 34

35 Results (iii) The mobile camera, used for annual screening and six month follow-up after the detection of background retinopathy, had an estimated cost of 449,200 per year with 2,842 per sight year saved. It is less efficient to screen Type 2, rather than Type 1 diabetes mellitus patients, but they contributed to almost three quarters of the sight years saved. University of Vienna, June 2002 Slide 35

36 Years of sight saved per year in a district of 250,000: Policy 1, 12m/6m NIDDM IDDM Optometrist Diabetologist GP Mobile Camera GS Screening method

37 Cost per year of sight saved: Policy 1, 12m/6m 7,000 6,000 5,000 4,000 3,000 IDDM NIDDM 2,000 1,000 - Optometrist Diabetologist GP Mobile Camera GS University of Vienna, June 2002 Screening Method Slide 37

38 The effects of screening sensitivity and patient compliance Years of sight saved per year Policy 1 Policy 2 12m/6m 24m/6m 12m/6m 24m/6m 12m/12m 24m/12m 24m/24m Intervals Sensitivity 80%, Compliance 82% Sensitivity 70%, Compliance 72%

39 Different screening intervals for the two policies 170 Years of sight saved per year % 40% 50% 60% Sensitivity 70% 80% 90% 100% Policy 1, 12m/6m Policy 2, 12m/6m Policy 1, 24m/6m Policy 2, 24m/6m Policy 2, 12m/12m Policy 2, 24m/12m Policy 2, 24m/24m

40 Total costs and years of sight saved for the two policies Costs of programme ('000s) Policy 1 Policy Years of sight saved per year m/6m 24m/6m 12m/6m 24m/6m 12m/12m 24m/12m 24m/24m Intervals

41 Effects of limiting the upper age of screening NIDDM patients in a population of 250,000, using Mobile Van Years of sight saved Costs per year of sight saved (x 10) Upper age for screening

42 Conclusions Simulation models can aid policy-makers Screening is clearly worthwhile Not much difference between methods as long as compliance is high (> 80%) Trade-offs between screening intervals, sensitivity and compliance Important to keep sensitivity > 60% Screening interval should not be > 12m University of Vienna, June 2002 Slide 42

43 Further work Discounted cost-benefit analysis (work currently in progress) Increase in incidence of diabetes due to lifestyle changes (?) New screening methodologies Incorporate other complications of diabetes e.g. neuropathy (some work started) University of Vienna, June 2002 Slide 43

44 References 1. Davies R, O Keefe R M and Davies HTO (1993). Simplifying the modeling of multiple activities, multiple queuing and interruptions: a new low-level data structure. ACM Transactions on Modeling and Computer Simulation 3: Davies R, Sullivan P and Canning CR (1996). Simulation of diabetic eye disease to compare screening policies. British Journal of Ophthalmology 80: Brailsford SC, Davies R, Canning CR and Roderick P (1998). Evaluating screening policies for the early detection of retinopathy in patients with non-insulin-dependent diabetes. Health Care Management Science 1: Brailsford SC, Davies R (1999). University of Southampton Website, Screening for Diabetic Retinopathy Davies R, Brailsford SC, Roderick PJ, Canning C, Crabbe D. (2000) Using simulation modelling for evaluating screening services for diabetic retinopathy. Journal of the Operational Research Society 51: Davies R, Roderick PJ, Canning C, and Brailsford SC, (2002). The evaluation of screening policies for diabetic retinopathy using simulation. Diabetic Medicine (to appear). University of Vienna, June 2002 Slide 44