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Modelling Radiotherapy Tim Cooper National Cancer Action Team.

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Presentation on theme: "Modelling Radiotherapy Tim Cooper National Cancer Action Team."— Presentation transcript:

1 Modelling Radiotherapy Tim Cooper National Cancer Action Team

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3 NRAG Report Deliver 40,000 fractions per mil pop by 2010; and (around) 54,000 fractions by 2016 Deliver 8,300 fractions per Linac by 2010/11; 8,700 per Linac by days wait time standard achieved by December 2010 Robust capital replacement programmes in place. All new & replacement machines capable of image guided IGRT National data collection is fed back to stakeholders at agreed intervals. Development of a workforce strategy that will deliver the required skills mix Implementation of the 4 tier model. Fast track career progression. A business case for a modern proton treatment facility in England Centres offer full service where operate weekends & Bank Holidays Extended days on 50% of machines Set throughput/ efficiency benchmarks. National overview of plans maintained.

4 [NB Prostate has been excluded as survival ‘gap’ is likely to be due to differences in PSA testing rates.] Data derived from Abdel-Rahman et al, BJC Supplement December 2009 Avoidable deaths pa if survival in England matched the best in Europe Breast ~ 2000Myeloma250 Colorectal ~1700Endometrial250 Lung ~1300Leukaemia240 Oesophagogastric ~950Brain225 Kidney ~700Melanoma190 Ovary ~500Cervix180 NHL/HD 370Oral/Larynx170 Bladder 290Pancreas75

5 Radiotherapy as a Treatment for Cancer Ref: IARC/WHO Lyons

6 Key Message – Improving Outcomes Strategy Access to radiotherapy is critical to improving outcomes. To improve outcomes from radiotherapy, there must be equitable access to high quality, safe, timely, protocol-driven quality- controlled services focused around patients’ needs.

7 Issues in Access Variation Missing patients (uptake) Malthus will help address both

8 Variability Variation in prescribing Commissioning for Quality Outcomes –Buy more fractions if the evidence is strong MALTHUS –Modelling –Clinical consensus

9 Attendances per patient - all

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11 Attendances per patient - Breast

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13 Variability Variation in prescribing Commissioning for Quality Outcomes –Buy more fractions if the evidence is strong MALTHUS –Modelling –Clinical consensus –20 th June

14 Issues in Access Variation Missing patients (uptake) Malthus will help address both

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17 What is Malthus? MALTHUS project to –develop an interactive tool for radiotherapy demand modelling in England, –establish consensus for radiotherapy prescribing Builds on the model used for NRAG report (2007) determining national radiotherapy requirements Designed to inform on radiotherapy demand for commissioning and planning purposes

18 MALTHUS Implementation Operates at local (PCT) & national level Models RT fraction demand per 100k population Discrete event simulation model : generates virtual populations of patients matching demographics of local population Use high quality incidence data from cancer registries & direct feeds from NCIN No formal health economics / cost effectiveness modelling

19 MALTHUS Implementation Appropriate rate of radiotherapy is determined from a decision tree Decision tree gives a fraction ‘load’ per patient MALTHUS uses two types of decision tree –Evidence based (revision of CCORE type trees) –Pragmatic (based on expert opinion and current practice)

20 Overview of model Malthus tool downloaded on PC Curated incidence data feeds from NCAT server User select PCT / Region to model Patient generator creates matching virtual population of patients BreastLungH&NUrology # for PCT Evidence based trees Consensus based trees User Customised trees Disease Stage Age Co-morbidity

21 Capacity planning Mandated in Improving Outcomes and the Operating Framework Commissioners must assess the needs of their populations MALTHUS (Local desktop tool) –Revision of NRAG model to take account of: –Cancer incidence –Stage, performance status, comorbidities –Changes in treatment pathway since 2006

22 Deprivation and access Lack of access and deprivation are strongly correlated This may be explained by –Stage at presentation –Performance status –Co-morbidity –Fitness for radical treatment –Willingness to travel –Patient choice Needs individual patient data to test

23 Improving access Review care pathways Facilitate early presentation Patient education Boost participation in MDTs Examine local data Compare to local cancer incidence Concentrate on common cancers and their treatment

24 Malthus project (Monte-Carlo Application for Local Treatment and Healthcare Usage Simulation) High-quality local cancer incidence data Scenario trees –literature review of evidence base –clinical oncologists’ consensus Desktop application User can adjust to local practice Provides a commissioning tool

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