Modeling Chronic Disease and Mental Health with Integrated Tools

Modeling a Chronic Disease Model and a Mental Health Model Using the Same Modeling Tools Jacob Barhak Freelancer Austin, Texas H. Stephen Leff Harvard Medical School Cambridge, Massachusetts

The Story in One Slide Process CHD CHD Death No CHD MI Survive MI Chronic Disease Model Process Stroke Death Survive Stroke Stroke Death No Stroke Stroke Process Competing Mortality Other Death Alive Python Based Modeling Framework Wait FL1 FL2 FL3 FL4 FL5 FL6 FL7 Unknown Death Mental Health Model

Why it is Important? Currently Physical and Mental Health are modeled separately Physical and Mental Health interact and influence each other Integrated physical and mental health care called for in the Affordable Care Act Model Implementations currently use different environments Implementing both models in the same environment is a first step towards: Merging both models Improved modeling capabilities Modeling interactions between processes

The Reference Model - Chronic Disease Process CHD CHD Death No CHD MI Survive MI Process Stroke Death Stroke Death No Stroke Stroke Survive Stroke Process Competing Mortality Other Death Alive Prototype demonstrating Technology Built from literature references and hence the name: The Reference Model Designed to serve as a reference for new equations and populations A League / Consumers Report for disease models

The Reference Model Key Features Simple - Low Resolution Based on secondary data: Published Risk Equations Published Clinical Trials, i.e. no real individual data Other publications Relies on computing power/techniques Parallel processing / High Performance Computing Competition among alternative equation/hypothesis combinations Cross validation - One click validation Ranks results according to fitness - Fitness Engine Accumulates knowledge

The Reference Model: How Does it Work? 1 2 Process CHD Pop 3 4 3 CHD Death No CHD MI Survive MI Pop 2 Pop 1 1 2 Process Stroke Death 4 3 Stroke Death No Stroke Stroke Survive Stroke Eq 1 1 1 1 1 Eq 2 1 4 2 6 3 2 4 1 Pop 1 Process Competing Mortality 2 4 6 1 Other Death Pop 2 Alive 2 3 9 2 Pop 3 Fitness Matrix Loop through Risk Equation/Hypothesis combinations Loop through populations Calculate fitness of simulation outcomes to observed phenomena

The Reference Model: Results Without Treatment Hypothesis With Treatment Hypothesis Best Model Overall Without Biomarker Hypothesis With Biomarker Hypothesis A1c changes BMI changes BP changes Lipid change Smoke changes MI Equation # Stroke Equation # CHD Death Equation # Stroke Death Equation # Treatment Improvement Correction FITNESS: LOW SCORE = GOOD FITNESS UKPDS33 Conventional UKPDS33 Intensive UKPDS33 Full ASPEN All Placebo ASPEN All Atorvastatin ASPEN Primary Placebo ASPEN Primary Atorvastatin ASPEN Secondary Placebo ASPEN Secondary Atorvastatin ASPEN Full ADVANCE Standard ADVANCE Intensive ADVANCE Asia Standard ADVANCE Asia Intensive ADVANCE EME Standard ADVANCE EME Intensive ADVANCE Eastern Europe Standard ADVANCE Eastern Europe Intensive ADVANCE Full ACCORD BP Standard Therapy ACCORD BP Intensive Therapy ACCORD BP Full 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 1 2 1 1 0 0 0 0 0 0 1 2 1 1 1 0 0 0 0 0 1 3 1 1 0 0 0 0 0 0 1 3 1 1 1 0 0 0 0 0 1 4 1 1 0 0 0 0 0 0 1 4 1 1 1 0 0 0 0 0 2 1 1 1 0 0 0 0 0 0 2 1 1 1 1 0 0 0 0 0 2 2 1 1 0 0 0 0 0 0 2 2 1 1 1 0 0 0 0 0 2 3 1 1 0 0 0 0 0 0 2 3 1 1 1 0 0 0 0 0 2 4 1 1 0 0 0 0 0 0 2 4 1 1 1 0 0 0 0 0 3 1 1 1 0 0 0 0 0 0 3 1 1 1 1 0 0 0 0 0 3 2 1 1 0 0 0 0 0 0 3 2 1 1 1 0 0 0 0 0 3 3 1 1 0 0 0 0 0 0 3 3 1 1 1 0 0 0 0 0 3 4 1 1 0 0 0 0 0 0 3 4 1 1 1 0 0 0 0 0 4 1 1 1 0 0 0 0 0 0 4 1 1 1 1 0 0 0 0 0 4 2 1 1 0 0 0 0 0 0 4 2 1 1 1 0 0 0 0 0 4 3 1 1 0 0 0 0 0 0 4 3 1 1 1 0 0 0 0 0 4 4 1 1 0 0 0 0 0 0 4 4 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 0 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 3 1 1 0 1 1 1 1 1 1 3 1 1 1 1 1 1 1 1 1 4 1 1 0 1 1 1 1 1 1 4 1 1 1 1 1 1 1 1 2 1 1 1 0 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 2 2 1 1 0 1 1 1 1 1 2 2 1 1 1 1 1 1 1 1 2 3 1 1 0 1 1 1 1 1 2 3 1 1 1 1 1 1 1 1 2 4 1 1 0 1 1 1 1 1 2 4 1 1 1 1 1 1 1 1 3 1 1 1 0 1 1 1 1 1 3 1 1 1 1 1 1 1 1 1 3 2 1 1 0 1 1 1 1 1 3 2 1 1 1 1 1 1 1 1 3 3 1 1 0 1 1 1 1 1 3 3 1 1 1 1 1 1 1 1 3 4 1 1 0 1 1 1 1 1 3 4 1 1 1 1 1 1 1 1 4 1 1 1 0 1 1 1 1 1 4 1 1 1 1 1 1 1 1 1 4 2 1 1 0 1 1 1 1 1 4 2 1 1 1 1 1 1 1 1 4 3 1 1 0 1 1 1 1 1 4 3 1 1 1 1 1 1 1 1 4 4 1 1 0 1 1 1 1 1 4 4 1 1 1 Models 27.0 24.6 21.5 14.3 18.5 23.3 21.7 23.2 16.2 8.3 67.3 67.3 66.7 72.6 84.8 91.2 75.9 78.5 57.3 46.8 42.5 43.9 24.1 24.6 22.5 21.4 23.0 21.3 10.2 13.8 9.4 20.5 9.5 23.1 13.1 24.3 37.6 21.2 18.8 10.3 11.8 9.9 54.0 12.1 59.3 18.9 58.4 21.2 64.4 14.0 80.4 21.6 83.0 15.7 71.0 10.8 69.2 12.7 54.9 30.4 48.0 27.9 46.7 27.9 45.4 31.7 26.7 26.3 9.7 10.2 11.1 11.4 39.7 20.9 13.4 10.4 12.8 17.0 17.5 20.4 27.4 19.5 17.5 14.6 27.9 28.6 29.2 24.6 24.6 22.4 10.2 17.6 22.3 21.7 21.9 12.2 7.6 60.1 62.7 64.5 71.2 79.7 82.4 69.1 73.6 55.4 54.3 49.8 53.0 33.1 30.1 29.9 10.2 11.3 9.0 10.3 40.4 29.0 13.1 16.0 14.8 12.2 18.0 26.4 30.3 21.5 19.6 18.3 35.1 32.7 34.0 26.9 24.2 23.6 15.1 15.8 20.6 22.9 21.0 11.6 8.2 62.7 60.3 70.9 79.4 81.1 87.1 70.8 75.8 57.0 53.0 48.9 51.8 31.2 26.5 29.5 10.6 8.0 9.0 11.9 37.3 20.7 9.7 12.8 14.5 13.2 17.3 22.4 28.3 17.1 16.2 12.7 32.0 29.2 29.3 43.0 37.0 35.1 15.9 22.7 19.7 25.0 22.7 14.8 9.8 36.6 42.7 35.2 32.8 75.6 82.3 65.6 66.3 52.7 41.5 43.5 44.3 24.6 31.9 29.5 21.9 28.4 31.5 32.1 6.2 18.5 17.3 24.1 23.6 21.5 24.5 49.2 45.7 41.2 44.2 38.8 21.5 15.1 17.7 42.5 34.1 34.5 13.5 22.6 25.4 23.0 19.0 13.1 10.3 27.5 34.5 26.8 32.7 67.9 74.9 59.7 61.1 52.5 44.7 41.6 43.2 32.7 35.2 39.4 22.0 28.5 26.7 32.7 11.6 20.7 17.9 22.8 27.2 20.5 23.2 51.7 57.0 48.0 47.7 44.8 24.1 24.2 25.3 36.3 35.6 35.1 17.8 18.7 24.6 24.2 20.5 15.3 9.4 31.0 36.4 29.2 37.8 65.9 70.5 58.1 56.1 53.9 50.6 48.4 49.1 35.8 38.2 37.3 18.1 30.0 31.3 31.2 17.7 27.5 19.5 27.2 27.2 25.3 23.9 52.9 58.5 48.7 49.2 48.1 34.7 31.7 34.8 39.2 34.2 34.3 19.0 21.6 23.0 25.5 18.1 13.2 9.0 32.9 37.6 32.6 37.3 65.1 75.3 55.9 59.3 53.3 49.5 43.4 50.1 33.4 34.0 33.8 22.1 29.9 27.8 31.6 11.9 23.6 20.1 25.0 28.9 19.9 26.7 49.7 56.0 42.8 45.1 46.6 29.0 29.0 28.2 39.7 32.2 31.5 12.5 16.8 15.5 17.2 18.4 25.9 9.4 54.1 59.1 53.0 58.9 79.4 79.0 62.9 69.5 53.1 62.6 54.4 58.9 29.4 40.8 37.1 23.5 26.0 23.8 25.2 15.7 40.1 16.6 39.4 47.0 43.5 49.5 55.1 57.2 44.9 51.9 50.2 32.3 35.3 33.6 39.7 32.5 32.0 12.6 15.4 14.3 15.6 13.6 23.0 5.6 48.0 51.3 48.3 53.9 66.9 76.3 57.1 57.8 56.4 63.3 55.9 60.4 36.9 43.3 42.4 18.7 25.2 22.6 25.7 15.4 39.2 15.7 42.2 48.9 43.6 52.4 57.7 66.0 56.7 53.2 51.7 39.1 36.5 41.2 39.6 34.3 33.6 10.9 16.6 16.0 17.4 14.6 24.3 7.6 50.1 53.4 52.4 56.5 70.0 72.9 51.4 55.0 52.5 66.3 63.6 64.3 46.2 45.7 45.9 18.2 29.5 21.7 26.2 24.4 46.6 13.7 52.4 53.5 47.4 54.1 59.0 63.8 51.2 57.0 54.9 49.3 47.7 47.7 35.9 29.6 34.2 12.1 13.9 15.8 16.5 12.8 24.2 8.0 49.9 56.2 53.1 57.5 72.4 73.9 51.6 54.4 54.3 63.5 60.3 63.3 38.1 41.8 42.5 19.3 28.2 21.7 25.7 16.2 42.7 17.4 43.4 50.8 47.0 52.9 61.4 65.4 100.6 50.0 49.3 55.1 42.4 39.8 41.1 34.6 42.4 43.8 23.2 28.8 33.3 34.7 20.9 20.8 18.9 65.4 73.2 67.2 79.7 89.0 22.7 21.6 21.9 12.5 9.8 9.8 13.1 45.7 26.2 14.8 12.9 9.8 23.3 16.9 16.9 16.0 23.8 16.2 13.8 37.0 33.8 35.1 35.8 41.4 39.7 22.4 25.1 31.3 31.4 13.8 19.3 18.8 60.5 63.5 63.9 70.7 82.2 86.4 72.2 72.7 61.4 49.4 44.3 48.2 27.8 25.6 27.9 13.4 11.8 10.2 10.5 47.3 26.4 16.3 10.1 8.5 21.0 14.3 19.8 17.1 22.2 19.1 12.8 36.2 32.2 34.4 33.7 43.7 42.6 22.9 28.9 29.9 32.2 19.4 19.3 17.3 67.6 67.9 67.1 74.4 87.3 92.6 76.2 78.8 64.5 54.4 56.8 51.8 30.4 30.6 32.3 13.5 12.1 9.0 10.0 50.7 33.1 16.2 12.3 11.6 12.2 7.6 24.5 20.6 20.8 21.0 13.1 38.3 37.6 37.6 34.4 41.4 41.7 25.1 29.0 32.7 32.7 16.6 20.6 19.7 60.2 70.2 66.7 75.2 81.5 89.3 70.2 68.4 66.2 52.5 52.0 56.2 29.8 29.5 28.7 13.4 10.1 9.3 10.4 48.1 26.0 15.3 11.0 11.6 11.7 7.7 20.8 18.1 22.5 16.7 13.6 36.2 34.9 36.0 23.6 22.8 23.7 15.5 15.0 23.4 17.0 22.7 12.0 8.2 45.9 40.4 54.4 45.3 64.3 61.4 54.0 43.5 39.6 46.5 36.7 43.5 24.7 22.7 21.6 10.3 9.4 8.7 11.3 37.9 21.9 11.9 10.6 9.8 21.2 18.7 11.1 11.9 20.4 19.3 15.8 30.0 28.7 28.4 25.0 22.4 22.5 14.5 12.8 21.3 15.7 21.1 7.6 10.1 40.1 37.6 42.2 42.6 58.7 54.7 47.9 39.9 35.5 47.7 37.2 42.2 29.2 29.0 28.1 9.0 10.6 9.8 10.7 36.3 24.7 13.7 7.2 7.1 19.3 15.3 17.7 19.5 17.6 16.8 11.6 28.5 29.2 30.1 25.5 22.4 21.9 12.3 12.8 20.8 16.5 19.5 12.5 10.4 43.5 39.2 47.3 42.2 64.6 57.3 48.5 40.9 38.2 46.9 43.6 48.0 33.0 28.6 29.6 9.3 11.3 9.0 9.8 39.7 28.3 13.7 9.1 8.4 12.4 10.7 21.5 18.2 19.0 15.1 10.9 34.8 31.4 34.2 26.7 22.0 23.0 14.5 9.1 22.4 16.0 20.2 14.2 9.3 44.0 41.8 48.7 41.8 62.0 56.0 56.1 38.0 37.6 50.9 41.3 46.2 33.1 29.0 27.6 9.9 8.7 9.1 12.0 38.7 25.9 12.4 9.6 8.8 11.1 9.7 19.1 19.5 16.6 14.2 7.2 31.9 32.3 30.3 40.4 34.6 35.6 13.7 17.1 23.4 21.6 24.8 10.3 11.0 27.7 30.3 22.3 29.9 64.2 70.2 52.6 52.9 45.3 42.2 36.1 39.6 24.7 33.7 30.0 21.1 22.3 30.1 24.9 7.9 13.0 19.8 18.1 20.2 22.7 21.9 41.8 40.1 34.9 36.1 36.6 20.0 13.9 16.9 39.9 31.6 33.8 17.5 17.8 24.3 21.4 19.2 7.3 10.2 24.6 25.7 23.8 25.8 60.7 66.8 46.0 51.6 47.3 41.7 36.9 40.6 30.3 32.6 34.5 25.7 26.9 30.5 26.7 10.2 11.8 17.3 19.6 18.8 20.2 20.4 45.8 46.7 39.7 37.8 40.6 23.1 20.8 22.3 40.3 32.0 36.3 14.6 15.8 23.5 22.0 20.9 11.2 9.0 26.9 31.1 24.0 25.5 62.4 61.0 45.7 48.0 45.0 49.3 40.6 46.0 34.2 38.3 37.4 21.1 24.9 29.5 26.8 18.2 21.7 17.3 23.7 23.1 20.2 19.1 50.2 47.1 43.8 39.1 42.1 31.7 28.4 31.1 38.6 33.2 37.5 16.7 16.0 26.5 24.0 18.3 11.7 8.9 29.6 28.7 24.2 28.8 59.7 64.4 46.3 44.5 48.7 48.3 45.1 44.4 30.4 36.1 34.5 22.5 23.1 31.1 28.6 11.5 16.8 16.6 23.2 24.8 22.2 21.5 43.4 48.7 40.5 43.0 40.2 28.8 28.7 27.1 37.7 34.0 34.1 13.7 14.9 14.6 15.6 18.7 21.3 7.6 45.2 40.2 42.5 47.0 65.6 62.3 49.9 47.6 44.0 58.3 44.2 52.4 33.7 39.4 37.7 21.6 24.6 25.1 22.0 16.0 30.5 16.0 37.6 31.6 37.7 35.1 46.9 43.9 36.0 35.2 37.7 28.8 25.5 30.5 36.0 34.2 33.9 11.4 13.3 16.1 15.9 13.8 18.1 7.2 34.7 34.3 39.1 39.1 59.1 54.0 46.9 44.7 45.7 56.0 46.9 51.7 35.0 45.7 44.8 24.3 23.8 25.1 23.8 18.2 31.8 13.4 33.6 38.7 41.4 37.7 49.7 46.0 44.6 37.9 46.6 39.6 31.9 34.9 40.2 32.9 36.4 12.3 14.5 15.0 13.3 14.9 22.3 8.0 40.9 36.5 44.5 38.5 57.2 56.3 48.9 38.8 47.4 63.1 53.3 57.5 41.1 47.1 47.3 19.1 21.2 21.5 23.5 25.8 37.0 15.7 40.5 40.7 34.8 38.6 53.7 49.1 45.3 35.7 45.3 45.7 35.9 39.2 38.6 32.3 34.3 14.5 15.6 17.3 15.1 13.6 20.9 10.1 41.6 39.1 41.0 45.3 61.1 58.7 42.1 43.6 44.7 60.7 54.6 57.5 37.6 45.0 41.0 23.4 21.3 24.3 24.4 18.3 35.7 16.3 37.7 37.2 35.4 40.1 55.1 49.9 41.7 41.1 46.5 43.0 34.9 38.6 35.8 43.4 42.6 22.0 17.0 29.4 23.1 23.2 11.7 18.7 50.7 52.0 48.5 50.8 74.1 68.8 60.6 62.4 46.5 45.9 30.7 37.4 22.3 21.9 23.3 14.6 11.8 9.4 11.8 46.9 29.9 16.7 19.9 12.8 25.8 22.5 19.0 17.1 29.1 25.2 19.0 38.9 38.3 40.0 38.4 42.9 40.5 24.0 16.5 31.1 25.4 14.9 6.1 14.2 40.7 45.8 48.0 49.4 67.9 60.4 56.2 52.2 44.8 47.0 37.8 37.6 29.3 27.4 28.3 13.3 12.8 10.2 10.3 49.7 29.3 18.2 15.5 12.6 21.9 19.9 21.0 20.6 27.2 21.5 13.2 37.2 35.7 37.5 34.3 44.1 45.1 20.8 18.4 32.7 23.2 17.3 9.2 17.9 50.2 47.7 51.4 56.6 70.0 63.5 57.1 55.8 48.3 52.5 41.2 44.2 33.2 31.2 28.7 12.8 11.9 8.8 8.7 48.1 34.8 16.0 14.4 11.5 17.5 9.7 20.5 16.8 26.0 20.7 13.3 38.6 39.2 40.3 34.3 43.7 41.2 20.9 17.9 32.2 22.0 18.0 10.2 16.8 45.1 46.6 55.2 56.6 64.4 64.7 53.9 54.5 51.9 54.0 40.8 47.9 31.0 27.5 27.4 13.9 11.8 7.9 8.5 47.4 32.9 15.7 13.7 12.4 14.7 11.9 19.0 17.9 26.1 24.1 13.6 38.1 39.0 39.3 FITNESS SCORE 7.9 81.8 79.0 64.6 52.8 47.5 49.9 OVERALL MODEL RANKING RESULTS Method_A1c Method_BMI Method_BP Method_Lipids Method_Smoke Method_MI Method_Stroke Method_DeathCHD Method_DeathStroke Method_TimeImprove Weighted Mean MODELS 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 0 0 0 0 0 4 1 1 1 1 1 1 1 1 1 1 4 1 1 1 0 0 0 0 0 4 2 1 1 1 1 1 1 1 1 1 3 1 1 1 0 0 0 0 0 1 2 1 1 1 0 0 0 0 0 1 4 1 1 1 0 0 0 0 0 4 4 1 1 1 1 1 1 1 1 4 1 1 1 1 1 1 1 1 1 4 4 1 1 1 0 0 0 0 0 4 3 1 1 1 1 1 1 1 1 4 2 1 1 1 1 1 1 1 1 4 3 1 1 1 0 0 0 0 0 1 3 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 2 2 1 1 1 0 0 0 0 0 2 1 1 1 1 1 1 1 1 1 2 4 1 1 1 0 0 0 0 0 2 2 1 1 1 1 1 1 1 1 2 3 1 1 1 0 0 0 0 0 2 4 1 1 1 1 1 1 1 1 2 2 1 1 0 1 1 1 1 1 3 1 1 1 1 1 1 1 1 1 1 2 1 1 0 0 0 0 0 0 2 3 1 1 1 1 1 1 1 1 2 3 1 1 0 1 1 1 1 1 2 1 1 1 0 1 1 1 1 1 1 3 1 1 0 1 1 1 1 1 2 4 1 1 0 1 1 1 1 1 1 4 1 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 3 2 1 1 0 1 1 1 1 1 3 2 1 1 1 0 0 0 0 0 2 2 1 1 0 1 1 1 1 1 3 4 1 1 1 0 0 0 0 0 3 1 1 1 1 0 0 0 0 0 2 3 1 1 0 0 0 0 0 0 2 4 1 1 0 1 1 1 1 1 3 3 1 1 0 1 1 1 1 1 3 3 1 1 1 1 1 1 1 1 3 4 1 1 0 1 1 1 1 1 3 1 1 1 0 0 0 0 0 0 2 1 1 1 0 0 0 0 0 0 3 2 1 1 1 1 1 1 1 1 4 2 1 1 0 0 0 0 0 0 3 4 1 1 1 0 0 0 0 0 1 2 1 1 0 1 1 1 1 1 4 4 1 1 0 1 1 1 1 1 4 1 1 1 0 0 0 0 0 0 3 2 1 1 0 1 1 1 1 1 4 3 1 1 0 0 0 0 0 0 3 4 1 1 0 0 0 0 0 0 1 3 1 1 0 0 0 0 0 0 3 3 1 1 0 0 0 0 0 0 3 3 1 1 1 0 0 0 0 0 1 4 1 1 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 3 1 1 1 0 0 0 0 0 0 4 2 1 1 0 0 0 0 0 0 4 4 1 1 0 0 0 0 0 0 4 3 1 1 0 0 0 0 0 0 4 1 1 1 0 RANK 18.51 18.92 19.78 20.04 20.51 20.72 20.73 20.92 21.48 21.66 22.5 22.63 22.88 23.2 23.57 23.77 25.67 27.65 27.91 30.56 31.15 31.41 32.09 33.88 33.89 34.14 34.43 35.32 35.69 35.7 36.1 36.12 36.34 37.7 37.9 38.1 38.96 39.15 39.45 39.65 39.92 40.18 40.52 40.76 41.61 42.15 42.85 43.02 43.71 44.55 44.57 44.99 45.38 45.46 46.3 46.87 47.07 47.24 47.62 47.7 51.37 53.41 55.47 55.58 Best Model Overall Rows Represent Different Populations

Mental Health Model Disappear from System Not Yet In FL# = Functional Level with decreasing hazard Acute Dependent Recovering Dangerous Mortality Residual Vulnerable Independent Wait FL1 FL2 FL3 FL4 FL5 FL6 FL7 Unknown Death Markov Model Special Transitions that release N new individuals into each FL each month

Mental Health Model: Markov Model The Markov Model transitions probabilities used FL1 FL2 FL3 FL4 FL5 FL6 FL7 Unknown Death 0.624 0.118 0.05 0.154 0.007 0.005 0 0.005 0.037 FL1 0.099 0.624 0.129 0.037 0.068 0.002 0 0.004 0.037 FL2 0.006 0.031 0.716 0.184 0.022 0.001 0 0.003 0.037 FL3 0.014 0.019 0.069 0.734 0.111 0.013 0 0.003 0.037 FL4 0.004 0.007 0.015 0.073 0.747 0.103 0.013 0.002 0.036 FL5 0 0.008 0 0.008 0.05 0.879 0.017 0.001 0.037 FL6 0 0 0 0 0 0 1 0 0 FL7 0 0 0 0 0 0 0 1 0 Unknown 0 0 0 0 0 0 0 0 1 Death Transition probabilities out of wait state are conditional if statements: 0 if Time < Arrival Time for all FL 1 if Time < Arrival Time and Individual ID corresponds to FL# 9

Mental Health Model: Reimplementation This Mental Health Model was previously published: Leff H.S., Dada M., Graves S.C. (1986), An LP planning model for a mental health community support system. Management Science 32(2) 139-155 Leff, H. S., Hughes, D., Chow, C., Noyes, S., & Ostrow, L. (2009). A Mental Health Allocation and Planning Simulation Model: A Mental Health Planner's Perspective. In Y. Yuehwern (Ed.), Handbook of Healthcare Delivery Systems. The implementation reports: Number of individuals in each state each month Monthly service costs & Total costs Number of transitions forward = improvement Number of transitions backwards = regression Number of individuals staying in the same state 10

Mental Health Model: Reimplementation The Reimplementation using the Python based Modeling Framework has the following advantages: Micro-Simulation: Each individual is modeled separately Potential to add individual characteristics Sensitivity Analysis: Multiple Scenarios were executed Perturbation as added to transition probabilities Future benefits: The Reference Model can be augmented with a mental health process 11

Mental Health Model: Results Percentage in Functional Level each month Shows high rate of disappearance from system FL3 Unknown FL6 FL5 FL4 FL2 FL1 FL7 Death Months 12

Mental Health Model: Results Transitions Shows more improvement than regression (roughly x2) No Transition Transitions Forwards = Improvement Transitions Backwards = Regression Months 13

Mental Health Model: Results Sensitivity Analysis shows minor variation Second Order Monte Carlo: Uncertainty used: Per Markov P -3SD<Normal(SD)<3SD Where: SD ~ Bernoulli(P) Repeated N=1000 times SD = Sqrt(P*(1-P)/N) No Transition Transitions Forwards = Improvement Transitions Backwards = Regression Months 14

Quality Control Models are prone to human error. The following techniques were used to improve quality: Equations were implemented twice separately Test scripts were written to test implementation Versioning Documentation Human inspection of code and results 15

Summary & Future Work 1st step towards merging Mental & Physical Health models Future modeling work : Bridge Yearly / Monthly Time Scale gap Merge Models into one model with different processes Model interactions between processes Enhancing Mental Health beyond Markov = Individualized Multiple Populations/Trials comparison 16

Summary & Future Work The Modeling Framework itself is being renovated From IEST (Indirect Estimation and Simulation Tool): Combines estimation and simulation capabilities Supports legacy requirements To MIST (MIcro Simulation Tool): Simplified Optimized for simulation Intended to use recent technological advances 17

Acknowledgments The GPL modeling framework described above was supported by the Biostatistics and Economic Modeling Core of the MDRTC (P60DK020572) and by the Methods and Measurement Core of the MCDTR (P30DK092926), both funded by the National Institute of Diabetes and Digestive and Kidney Diseases. The modeling framework was initially defined as GPL and was funded by Chronic Disease Modeling for Clinical Research Innovations grant (R21DK075077) from the same institute. The Reference Model was developed independently without financial support. The Mental Health Model development was initially supported by National Institute of Mental Health Grant No. IR01-MH33581-02. Since then it has been supported by funds from various State and County planning projects. The reimplementation of the model described in this paper was not supported financially. 18