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Bryn Mawr 2008
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Bryn Mawr 2008

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This copyrighted presentation was made at the Bryn Mawr Innovation Systems Biology Conference, October 14, 2008.

This copyrighted presentation was made at the Bryn Mawr Innovation Systems Biology Conference, October 14, 2008.

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  • This presentation focuses on the key role human health technologies will play in determining leadership in the healthcare space. More importantly, it focuses on the vital role these technologies will play in enabling Pfizer to continue its leadership by developing new business models for delivering superior healthcare value.
  • Transcript

    • 1. ITHW, Inc. Innovative Technologies in Health and Wellness David S. Lester, Ph.D. President, ITHW, Inc. Executive VP, Gene Express, Inc. October, 2008 A Systems Approach to Identifying Technology Interventions Based on Patient-Centered Outcomes
    • 2. REPORT CARD How well are we doing? <ul><li>“ Well, at least until last night. In the past, as I have gotten more fit, my insulin needs would decrease fairly quickly. Well, 3 weeks into my new exercise regimen, and I&apos;m already starting to see the difference. Especially on the day I work out with my trainer. Which was yesterday. I thought I had it all figured out. Hm. Not so much, it turns out. I ate before, tested afterward, ate a snack, went low anyway, covered the low, rebounded, went too high, made the mistake of correcting the high and wham, it&apos;s the middle of the night and I&apos;m jolted from a dream, wicked low, pounding headache, sweaty all over, grasping for food. This was a hard core low. Really intense, really physical” </li></ul>Blog source ITHW, Inc. Innovative Technologies in Health and Wellness
    • 3. How well are we doing? <ul><li>“… .. the episode turned out to be better than it sounds, but still is prompting an appointment with an endocrinologist to address my struggling control of my blood sugars of late. The worst part though was showing up at Flower Festival the next morning looking like I&apos;d been beaten up in a bar fight.” </li></ul>Blog source <ul><li>“ By the way, few meters accurately measure very low readings. ……… I wish there was a consistent pattern to this, but there isn&apos;t .... one reason why living with DM is such a headache!” </li></ul>ITHW, Inc. Innovative Technologies in Health and Wellness
    • 4. Healthcare Comment <ul><li>“ People have craved a different sort of experience. People are willing to pay for individualized care and individualized wellness.” </li></ul><ul><li>Eric Hedges, Duke Executive Health Program. (HealthlLeaders, August 2007, p.15) </li></ul>ITHW, Inc. Innovative Technologies in Health and Wellness
    • 5. The Key Is Identifying and Integrating Patient-Centric Technology Strategies to Prove Value to Multiple Stakeholders Payers Suppliers Employers Providers Patients Regulators Caregivers The Perception of Value Depends on Stakeholder Perspective Pharma ITHW, Inc. Innovative Technologies in Health and Wellness
    • 6. The Healthcare System of Today: Which iPod do I trust? Regulators Pharmaceutical Companies Payers Providers Suppliers Caregivers Device Manufacturers Employers ITHW, Inc. Innovative Technologies in Health and Wellness
    • 7. The Patient of Today – The iPod: What accessory do I choose? Eastern Medicines /Treatments Generics Pharmaceuticals Supplements Regulated Devices Non-Regulated Devices Nutraceuticals Physical Activities ITHW, Inc. Innovative Technologies in Health and Wellness
    • 8. Developing Patient-Centric Technology Strategies Adding Value by Optimizing Key Points of Patient Impact Expanding Opportunities Across the Cycle of Patient Care Diagnosis Intervention Adherence Control Improved Outcomes Redefining &amp; Identifying Diseases for Product Development Redefining Performance &amp; Execution of Clinical Value Product Superiority/ Inferiority Novel Information Individualized Monitoring Pricing ITHW, Inc. Innovative Technologies in Health and Wellness
    • 9. Our Proof-of-Principle (PoP) model focuses on integrating diabetes with its associated complications and comorbidities (C&amp;Cs) to better inform how Pfizer and its peers can improve patient health Depression* Stroke* Dementia* Alzheimer’s disease* Endocrine disorders Foot ulceration Respiratory distress Hypertension* Atherosclerosis* Hyper-/Hypoglycemia* Hyper-/Hypoinsulinemia* Dyslipidemia/ Hypercholesterolemia* Metabolic syndrome* Neuropathy* Compressed nerves* Immune suppression Focal neuropathy Intermittent claudication Bone disorders Cancer Gangrene Nephropathy* Obesity* <ul><li>Diabetes has a profound impact beyond the disease itself </li></ul><ul><li>Its comorbidities coincide with many Pfizer priorities </li></ul>Retinopathy Diabetic Macular Edema* Vitreous hemorrhage Glaucoma* Cataracts Coronary heart disease* Myocardial Infarction Angina Sudden death Heart failure* Transient ischemic attacks Erectile dysfunction* Retrograde ejaculation Decreased vaginal lubrication* Neurogenic bladder Urinary Tract Infections Gastroparesis Diabetes and its complications account for approximately 15% of total healthcare expenditures even though diabetes is present in only approximately 6% of the population Project Rationale &amp; Goals . . . ITHW, Inc. Innovative Technologies in Health and Wellness
    • 10. Systems Dynamics Modeling of the Diabetic Patient Outcomes ITHW, Inc. Innovative Technologies in Health and Wellness
    • 11. We are utilizing a proven method that enables us to integrate a wide range of dynamics and stakeholders Introduction to System Dynamics . . . ITHW, Inc. Innovative Technologies in Health and Wellness
    • 12. MIT research shows that beyond three interacting feedback loops, intuition and conventional analysis break down Debt &amp; Equity Passengers Flown Physical Capacity Service Capacity Product Attractiveness Shareholder Value Cause-effect relationships close in on themselves to form feedback loops – interacting feedback loops generate performance over time Introduction to System Dynamics . . . ITHW, Inc. Innovative Technologies in Health and Wellness ? ? Earnings Revenue (Unit Sales) Service Quality Customers Ability To Raise Capital Ability to Attract &amp; Hire Employees
    • 13. The complexity of diabetes and its C&amp;Cs is reflected in their extensive interacting feedback loops Introduction to System Dynamics . . . ITHW, Inc. Innovative Technologies in Health and Wellness Atherosclerosis Obesity Stroke CHD Diabetes Depression Dyslipidemia Retinopathy Neuropathy Nephropathy Hypertension
    • 14. Our second step was to organize diabetes and its complications and comorbidities into ten groups for the PoP effort Fasting Plasma Glucose (FPG) levels at presentation Type 2 Diabetes Diabetic FPG 126-299 mg/dL Non-diabetic FPG &lt;100 mg/dL Pre-diabetic FPG 100-125 mg/dL Severe State Moderate State Non-state Pre-state Complication or comorbidity Specific classification index Obesity Coronary Heart Disease Stroke Atherosclerosis Dyslipidemia Hypertension Depression Nephropathy Neuropathy Adult 45-64 Adult 20-44 Adult 65+ Retinopathy When we distinguish three age groups, the number of groups triples from 120 potential patient pools to 360 potential patient pools Clinical landscape inventory . . . ITHW, Inc. Innovative Technologies in Health and Wellness
    • 15. Our second step was to cluster related technologies and determine a manageable number for the PoP Identifi-cation of existing diabetes tech-nologies Grouped according to technologies’ function in diabetes care <ul><ul><li>Technologies grouped according to mode of administration or mechanism of action whenever feasible </li></ul></ul><ul><ul><ul><li>Examples: All non-invasive glucose monitoring devices, all emerging oral insulins </li></ul></ul></ul><ul><ul><li>The clustering enabled us to identify the most highly-leveraged and synergistic technology categories for this PoP effort </li></ul></ul><ul><ul><li>We focused on diabetes technologies only for the PoP (C&amp;C technologies were excluded) </li></ul></ul><ul><ul><li>Sources of information included Pharmaprojects, company and patient group websites, industry reports and journal reviews </li></ul></ul><ul><ul><li>Only emerging technologies with a predicated 2-7 year launch were included based upon clinical trial phase and Technology Readiness Levels (technologies ranked on a scale to assess maturity of evolving technologies) </li></ul></ul>Identification of emerging diabetes technologies Characterization according to clinical trial phase, technology readiness level, and launch date Technology landscape inventory . . . ITHW, Inc. Innovative Technologies in Health and Wellness
    • 16. Example of a complication of diabetes: Nephropathy Nephropathy * National Kidney Foundation/Kidney Disease Outcome Quality Initiative (NKF/KDOQI) classification system Complication/Comorbidity Clinical landscape inventory . . . Further details are provided in the supporting C&amp;Cs Appendix ITHW, Inc. Innovative Technologies in Health and Wellness Demographics/Epidemiology Contributing factors Diagnostic Disease State Classification* Downstream Outcomes Sample Outcome Approximately 25-50 % of Type II DM patients will develop kidney disease, although do not present with symptoms until 5-10 years post onset of disease. Patients from an Asian or Afro-Caribbean origin are twice as likely to develop diabetic kidney disease. Diabetic nephrology accounts for approximately 40% of all cases of new end stage renal disease (ESRD). Hypertension, Atherosclerosis, Neuropathy. Severity of condition depends upon comorbidities of patient. Hyperglycemia and exposure to a high protein diet are important risks for development of proteinuria. Albumin (urine sample, first passing of day), creatinine (blood sample) Microalbumin-uria (marker of development of nephrology) -albumin levels over 30mg in 24h. Macroalbumin-uria (marker for progression to Stage V: ESRD)- albumin levels above 300mg. Serum creatinine levels outside normal range 0.8-1.3mg/dL indicates major kidney functional loss. Assessment of findings provide clues to stage of renal disease: Stage I: Time of diagnosis. Kidney size is increased. Glomerular Filtration Rate (GFR) is &gt;90ml/min/1.73m 2 . Reversible by blood glucose control. Stage II: 2-3 yrs post-diagnosis. Glomerular basement membrane thickens and decline in renal function initiated. Scar tissue formation occurs. GFR 60-89ml/min/1.73m 2 Stage III: 7-15 yrs post-diagnosis. Microalbuminuria first appears. Glomerular damage has progressed and hypertension may be present. Patients are asymptomatic. GFR 30-59ml/min/1.73m 2 Stage IV: Overt, or dipstick positive, diabetes. Almost all patients have hypertension. Suboptimal glucose control. GFR 15-29ml/min/1.73m 2 Stage V: ESRD; GFR &lt;15ml/min/1.73m 2 Renal replacement required. Coronary heart disease (due to macroalbu-minuria), Kidney failure
    • 17. Uniform ‘care cycles’ are built onto the backbone to reflect the relationships among patient care variables <ul><li>We have included structure related to: </li></ul><ul><li>Undiagnosed disease </li></ul><ul><li>Access to care (intervention) </li></ul><ul><li>Adherence to care </li></ul><ul><li>Efficacy of care (control) </li></ul>Generic care cycle: Model structure . . . Progression Improvement Backbone: ITHW, Inc. Innovative Technologies in Health and Wellness
    • 18. The standardization of the impact of health care system variables in the model enabled consistent use of technologies related to the care cycle Generic care cycle Non-intervention 2 Non-diagnosis 1 Non-adherence 3 Non-control of condition 4 *The language of these parameters is established such that a reduction in the parameter is always beneficial to the population: “ up is bad, down is good” Model structure . . . <ul><ul><li>Non-diagnosis: the fraction of people with a condition who have not yet been diagnosed </li></ul></ul><ul><ul><li>Non-intervention: the fraction of diagnosed patients who do not start and/or continue their care plan due to a variety of reasons related to access to care including reimbursement issues, lack of insurance, ‘physical’ access to care, providers not adequately following practice guidelines, etc. </li></ul></ul><ul><ul><li>Non-adherence: the fraction of diagnosed patients who do not adhere to their care plan, thus falling short of achieving its full intended benefit </li></ul></ul><ul><ul><li>Non-control: the fraction of diagnosed patients who receive and adhere to their care plan without achieving the efficacy benefit according to the technologies ‘label’ </li></ul></ul>ITHW, Inc. Innovative Technologies in Health and Wellness
    • 19. We also included the structure for three performance measures (“simulation outcomes”) <ul><ul><li>Non-diagnosis: the fraction of people with a condition who have not yet been diagnosed </li></ul></ul><ul><ul><li>Non-intervention: the fraction of diagnosed patients who do not start and/or continue their care plan due to a variety of reasons related to access to care including reimbursement issues, lack of insurance, ‘physical’ access to care, providers not adequately following practice guidelines, etc. </li></ul></ul><ul><ul><li>Non-adherence: the fraction of diagnosed patients who do not adhere to their care plan, thus falling short of achieving its full intended benefit </li></ul></ul><ul><ul><li>Non-control: the fraction of diagnosed patients who receive and adhere to their care plan without achieving the efficacy benefit according to the technologies ‘label’ </li></ul></ul><ul><ul><li>Progression/improvement: the movement from one disease severity to another </li></ul></ul><ul><ul><li>Mortality: death due to diabetes or its C&amp;Cs </li></ul></ul><ul><ul><li>Non-Quality of Life (Non-QoL): eg, bad days, as measured by validated instruments for measuring quality of life (out of scope for Phase 1b) </li></ul></ul>Generic care cycle Non-intervention 2 Non-diagnosis 1 Non-adherence 3 Non-control of condition 4 Progression / Improvement 5 Mortality 6 NQoL 7 Model structure . . . *The language of these parameters is established such that a reduction in the parameter is always beneficial to the population: “ up is bad, down is good” ITHW, Inc. Innovative Technologies in Health and Wellness
    • 20. Addition of technology impact points for all the diabetes populations and one C&amp;C (obesity) expands the complexity OBESITY DIABETES Model structure . . . ITHW, Inc. Innovative Technologies in Health and Wellness NQOL, e.g. “ bad days ” Non - intervention Non - diagnosis Non - adherence Noncontrol of condition Progression Mortality NQOL, e.g. “ bad days ” Non - intervention Non - diagnosis Non - adherence Noncontrol of condition Progression Mortality NQOL, e.g. “ bad days ” Non - intervention Non - diagnosis Non - adherence Noncontrol of condition Progression Mortality NQOL, e.g. “ bad days ” Non - intervention Non - diagnosis Non - adherence Noncontrol of condition Progression Mortality NQOL, e.g. “ bad days ” Non - intervention Non - diagnosis Non - adherence Noncontrol of condition Progression Mortality NQOL, e.g. “ bad days ” Non - intervention Non - diagnosis Non - adherence Noncontrol of condition Progression Mortality NQOL, e.g. “ bad days ” Non - intervention Non - diagnosis Non - adherence Noncontrol of condition Progression Mortality NQOL, e.g. “ bad days ” Non - intervention Non - diagnosis Non - adherence Noncontrol of condition Progression Mortality NQOL, e.g. “ bad days ” Non - intervention Non - diagnosis Non - adherence Noncontrol of condition Progression Mortality NQOL, e.g. “ bad days ” Non - intervention Non - diagnosis Non - adherence Noncontrol of condition Progression Mortality NQOL, e.g. “ bad days ” Non - intervention Non - diagnosis Non - adherence Noncontrol of condition Progression Mortality NQOL, e.g. “ bad days ” Non - intervention Non - diagnosis Non - adherence Noncontrol of condition Progression Mortality NQOL, e.g. “ bad days ” Non - intervention Non - diagnosis Non - adherence Noncontrol of condition Progression Mortality NQOL, e.g. “ bad days ” Non - intervention Non - diagnosis Non - adherence Noncontrol of condition Progression Mortality NQOL, e.g. “ bad days ” Non - intervention Non - diagnosis Non - adherence Noncontrol of condition Progression Mortality NQOL, e.g. “ bad days ” Non - intervention Non - diagnosis Non - adherence Noncontrol of condition Progression Mortality NQOL, e.g. “ bad days ” Non - intervention Non - diagnosis Non - adherence Noncontrol of condition Progression Mortality NQOL, e.g. “ bad days ” Non - intervention Non - diagnosis Non - adherence Noncontrol of condition Progression Mortality
    • 21. The complexity is further enriched when the other C&amp;Cs are added Model structure . . . ITHW, Inc. Innovative Technologies in Health and Wellness
    • 22. We quantified a total of 50 Diabetes technologies in the proof-of-principle phase <ul><li>6 types of Diagnostic Tests </li></ul><ul><li>5 types of Glucose Monitoring Devices </li></ul><ul><li>3 types of Insulin Types </li></ul><ul><li>5 types of Insulin Delivery Methods </li></ul><ul><li>8 types of Oral Hyperglycemic Agents </li></ul><ul><li>1 related to Lifestyle Changes </li></ul><ul><li>2 related to Overall Management </li></ul>Existing Diabetes Technology Categories <ul><li>3 types of Continuous Glucose Monitoring Devices </li></ul><ul><li>4 types of Insulin Delivery Methods </li></ul><ul><li>10 types of Hyperglycemic Agents </li></ul><ul><li>1 related to Cellular Therapies </li></ul><ul><li>1 related to Telemedicine Technologies </li></ul><ul><li>1 related to Electronic Health Records </li></ul>Emerging Diabetes Technology Categories 30 Existing Diabetes Technologies 20 Emerging Diabetes Technologies * We have identified an additional 29 technology categories with market impact beyond 7years (out of the scope of Phase 1b) Model quantification . . . Further details are provided in the supporting Technologies Appendix ITHW, Inc. Innovative Technologies in Health and Wellness
    • 23. The technologies have a broad range of effects on deaths and retinopathy cases averted, but there is little synergy among tested DM TLs. Technologies which impact the largest fraction of the population have a higher impact e.g. adherence programs Technologies which improve control AND adherence (through fewer adverse side effects) also have a large impact e.g. PPARgAgnst Deaths Averted from Single Technologies Generally, the TLs with the most impact affect wider populations, and effect populations behaviorally as well as medically Which technologies have the biggest impact? Reference Point: 500k deaths averted represents about 1% of the 50 million total deaths in the base case from 2008-2025. ILLUSTRATIVE RESULTS ONLY Deaths Averted from Pairs of Technologies Metric = Deaths averted compared to base case from 2008-2025 <ul><li>Synergy between technologies can occur when they act on the same populations but on different impact points, increasing the impact of each individual technology. </li></ul><ul><li>Likewise, technologies can “cannibalize” the effects of one another if they act in the same places on the same population. </li></ul><ul><li>Not surprisingly, there is little synergy among the technlogy paris tested, as the act in the same few areas. However, these results are illustrative of how synergies or cannibalization can be analyzed. </li></ul>Model results . . . ITHW, Inc. Innovative Technologies in Health and Wellness The difference is the impact of synergistic effects.
    • 24. When the simulation combines medical and epidemiological facts, interesting potential insights emerge For each impact point, the difference between the base case and an ideal situation (ie, no progress, no control problems, total adherence) was reduced by 50%. Here only the most influential half of impact points are shown. Technologies acting on which impact points would have the most influence*? Metric = Deaths averted compared to base case from 2008-2025 Not surprisingly, progression has the biggest impact on mortality. Due to the fact that even Pre-Diabeties significantly increases the risk of death in Older Adults, and that many pre diabetics become diabetics, preventing the onset of Pre-Diabeties has an even bigger impact than preventing the onset of full blown diabetes Keeping Non-diabetics from progressing to Pre-diabetics in general has more of an impact than keep Pre-diabetics from progressing to Diabetes because of the relatively larger Non-diabetic population, because Pre-diabetics exhibit some of the problems Diabetics Exhibit, and cutting down on Pre-diabetic development ultimately also decreases diabetes. Following Progression, Control and Adherence have the biggest impacts. While Progression of Non-diabetics to Diabetics has a larger impact than the progression of Pre-Diabetics to Diabetics, glucose control of diabetics has a larger impact than control of Pre-diabetics. Reference Point: 1 million deaths averted represents about 2% of the 50M total US deaths in the base case from 2008-2025. ILLUSTRATIVE RESULTS ONLY Model results . . . * “Progression, Non Diabetic, Older Adult” represents the progression of older, non-diabetic adults to older, pre-diabetic adults ITHW, Inc. Innovative Technologies in Health and Wellness
    • 25. Adding Additional Patient Subgroups ITHW, Inc. Innovative Technologies in Health and Wellness
    • 26. Preliminary categorization has identified several high-priority sub-groups for incorporation into the model e.g., Particular obesity treatments are not suitable for children e.g., Treatment efficacy might be influenced by sex hormones e.g., An anti-smoking treatment will not affect non-smokers * For additional information, see Appendix A: Supporting details for sub-group classification ** Priority ranking: 1 = highest 1 2 Considerations . . . ITHW, Inc. Innovative Technologies in Health and Wellness Smokers Age Gender Time with diabetes Alcohol consumers Ethnicity Genetic pre-disposition For how many C&amp;Cs are the sub-groups relevant? 8 6 5 3 7 8 6 Is the prevalence of diabetes &amp; its associated C&amp;Cs altered among the different sub-groups of the classification? Yes Yes Yes Yes Yes Yes Yes Do differences exist in the Relative Risks (RRs) among the different sub-groups of the classification? Yes Yes Yes Yes Unclear Unclear No Suggested priority 1 1 1 1 2 2 3 Is a difference in technology impact among the different sub-groups of the classification likely to be observed? Yes Yes Yes Yes Unlikely No Unlikely Revised priority with consideration of the technology impact consideration 1 1 1 1 2 3 3
    • 27. While expanding further patient sub-groups adds granularity to the model, the increased complexity must be managed Obesity Coronary Heart Disease Stroke Atherosclerosis Dyslipidemia Hypertension Depression Nephropathy Neuropathy Retinopathy Diabetic Non-diabetic Pre-diabetic Severe State Moderate State Non-state Pre-state Adult 45-64 Adult 20-44 Adult 65+ Adding only 2 further sub-group classifications across all C&amp;Cs, each with 4 sub-groups, significantly increases complexity 4x3x3x10 = 360 “slices” in the model 4x3x3x10x(4x4) = 5760 “slices” in the model PoP (v1.0) Model PoP (v1.1) Model Considerations . . . ITHW, Inc. Innovative Technologies in Health and Wellness Obesity Coronary Heart Disease Stroke Atherosclerosis Dyslipidemia Hypertension Depression Nephropathy Neuropathy Retinopathy Diabetic Non-diabetic Pre-diabetic Severe State Moderate State Non-state Pre-state Adult 45-64 Adult 20-44 Adult 65+
    • 28. Addition of Adherence Factors ITHW, Inc. Innovative Technologies in Health and Wellness
    • 29. A number of factors have been identified that influence an individual’s adherence to his/her treatment program* * Adapted from Vlasnik 2005 and expanded by PA Features of the Disease <ul><ul><li>Severity </li></ul></ul>Side Effects Fears of undesirable side effects Long term benefits vs. acute side effects Fears of long term safety of drugs Threat of mortality Chronicity <ul><li>Morbidity </li></ul>Perception of risk <ul><ul><li>Misunderstanding of prescribing instructions </li></ul></ul><ul><ul><li>Frequent changes to drug regimens </li></ul></ul>Concern about taking drugs, incl. fear of addiction/dependency Medication taste Problems swallowing tablets Difficulty in opening drug containers Difficulty in handling small/large tablets Inability to distinguish colors or identifying markings on medications Ease of administration of medication Interactions with drug rehabilitation Treatment Regimen <ul><li>Multiple physicians or health care providers prescribing medications </li></ul>Limited faith in the medication or the provider Physicians providing clear explanations, encouragement, reassurance, and follow-up Provider Insurance and reimbursement variables Flexible clinic hours Access to Healthcare Location/ Physical environment/ Transportation Dependent care issues Language/ communication barriers Patient Household/ family dynamics Limited social or family support Broader problems requiring assistance in the home Support Patient Physical difficulties limiting access to or use of medication packaging Denial of the illness or its significance/ anger about the illness Burden of taking regular medication Limited education about the illness or the need for medication Past noncompliance with regimens Reduction, disappearance, or fluctuation of symptoms <ul><ul><li>Age </li></ul></ul><ul><ul><li>Income/homelessness </li></ul></ul><ul><ul><li>Cost of medication </li></ul></ul>Inability to read written instructions <ul><ul><li>Forgetfulness or confusion </li></ul></ul><ul><ul><li>Concurrent substance abuse </li></ul></ul><ul><ul><li>Cultural/religious/political beliefs </li></ul></ul><ul><ul><li>Apathy </li></ul></ul><ul><ul><li>Mental status/depression/stress </li></ul></ul><ul><ul><li>Agoraphobia </li></ul></ul><ul><ul><li>Incarceration </li></ul></ul>Adherence Burden of food/meal interactions Drivers of adherence . . . ITHW, Inc. Innovative Technologies in Health and Wellness
    • 30. For the purpose of this illustration, we’ve simplified the many potential sub-groups and drivers into an illustrative model Adherence Risk of non-adherence due to lack of access to care Baseline Adherence Risk of non-adherence Risk of non-adherence due to impact of Risk of due to complexity Risk of non-adherence due to lack of readiness Distance to access Time to access Cost of coverage e.g., premiums Cost of treatments e.g., co-pays Actual side Available education on side effects Number of concurrent treatments Frequency of doses Availability of emotional support Frequency of personal reminders Risk of non-adherence due to inconvenience of care due to cost of care of treatment regimen side effects on lifestyle of patients for treatment Time demand of treatment <ul><li>The population is divided into eight categories based on three classifications: </li></ul><ul><ul><li>Insurance Status (covered v. not covered) </li></ul></ul><ul><ul><li>Discipline to follow treatment (high discipline v. low discipline) </li></ul></ul><ul><ul><li>Level of family and personal obligation (high responsibility v. low responsibility) </li></ul></ul>ILLUSTRATIVE RESULTS Identifying cause and effect . . . effects non-adherence ITHW, Inc. Innovative Technologies in Health and Wellness
    • 31. The two sample technologies appeal to the different sub-groups because of the interventions’ relative appeal on different drivers Adherence Risk of non-adherence due to lack of access to care Baseline Adherence Risk of non-adherence Risk of non-adherence due to impact of Risk of due to complexity Risk of non-adherence due to lack of readiness Distance to access Time to access Cost of coverage e.g., premiums Cost of treatments e.g., co-pays Actual side Available education on side effects Number of concurrent treatments Frequency of doses Availability of emotional support Frequency of personal reminders Risk of non-adherence due to inconvenience of care due to cost of care of treatment regimen side effects on lifestyle of patients for treatment Time demand of treatment ILLUSTRATIVE RESULTS Identifying cause and effect . . . effects non-adherence <ul><ul><li>The diet pill significantly lowers the time demand of treatment, helping all groups but especially helping those with low discipline </li></ul></ul><ul><ul><li>The high cost of the E-coach program discourages use among all groups, but especially those without insurance coverage </li></ul></ul><ul><ul><li>The E-coach also increases reminders and personal support, especially aiding those with low discipline </li></ul></ul><ul><ul><li>The side effect of fatigue from the diet pill is unpleasant to all, but increases the risk of non-adherence much more for those with high family responsibility </li></ul></ul>ITHW, Inc. Innovative Technologies in Health and Wellness
    • 32. These drivers of adherence interact in complex ways, as seen from the perspective of patients, providers, treatments and the healthcare system Disease &amp; Treatment Provider Health care system <ul><li>Patient barriers to adherence, e.g.: </li></ul><ul><ul><li>Patient limitations in medication knowledge </li></ul></ul><ul><ul><li>Patient unwillingness to change behavior </li></ul></ul><ul><li>Physicians barriers to adherence, e.g.: </li></ul><ul><ul><li>Failure to explain benefits and side effects </li></ul></ul><ul><ul><li>No consideration of cost or lifestyle of patient </li></ul></ul><ul><li>Health care systems barriers to adherence, e.g.: </li></ul><ul><ul><li>Limited access to health care </li></ul></ul><ul><ul><li>Use of restricted formulary/switching to different formulary </li></ul></ul><ul><ul><li>Lack of continuity of care </li></ul></ul><ul><li>Disease and treatment barriers to adherence, e.g.: </li></ul><ul><ul><li>High medication costs </li></ul></ul><ul><ul><li>Unpleasant or unwanted side effects </li></ul></ul>Drivers of adherence . . . ITHW, Inc. Innovative Technologies in Health and Wellness Patient
    • 33. Total Population very closely matches historical estimates Younger Adults Middle Aged Adults Older Adults Simulation Historical Data Step #1: Historical Calibration… ITHW, Inc. Innovative Technologies in Health and Wellness Total Population by Age Group 1995.0 1996.8 1998.6 2000.4 2002.2 2004.0 20,000,000 40,000,000 60,000,000 80,000,000 100,000,000 120,000,000
    • 34. THANK YOU Partners: PA Consulting Joe Alexander, Pfizer Human Health Technologies ITHW, Inc. Innovative Technologies in Health and Wellness

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