Cost-Benefit Analysis of Providing Non-Emergency Medical Transportation (2005)

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Chapter 7: Condition-Based Cost-Effectiveness Analysis of NEMT and Health This chapter uses the non-emergency medical transportation cost estimates developed in Chapter 5, and the methods elaborated in Chapter 6, to review and analyze the cost-effectiveness of providing NEMT to those who lack access to it, and who suffer from twelve specific medical conditions. Because the benefits of additional care vary according to medical condition, this analysis essentially produces twelve unique cost- effectiveness results. We analyzed the most important and prevalent conditions faced by the transportation-disadvantaged persons who lack access to NEMT. By analyzing these highly prevalent conditions, we have included the majority of affected individuals, i.e., the project’s target population. Because chronic and preventive conditions require fundamentally different approaches, as discussed in Chapter 6, this chapter is organized into two major sections, one for the conditions using each approach. We begin with the five preventive care conditions. These are followed by the analysis of seven chronic care conditions. A final section discusses how these results may be aggregated into an overall cost-effectiveness analysis for the conditions analyzed, as well as other issues associated with these estimates. 7.1 Cost-Effectiveness of Increased Access to Healthcare for Preventive Care Presentation of the preventive care examples is straightforward in that they are based on existing cost-effectiveness studies found in the literature. The cost of NEMT is added to the cost side of the ratio to determine the cost-effectiveness of the particular preventive service. 7.1.1 Influenza Vaccinations Vaccinations can be critical to health and their cost-effectiveness has been extensively studied. Influenza, or flu, occurs annually and can be deadly, especially to infants and the elderly. This cost-effectiveness analysis relies on data from the Centers for Disease Control based on flu vaccination eligibility for all adults, with the exception of pregnant and nursing women. The steps are as follows. Step 1. Determine the compliance rate. The literature suggests that the compliance rate for preventive care screenings or vaccinations is comparatively low. In the case of the flu vaccine, it is estimated that 18.3% to 40.8% of eligible patients get a flu vaccine (Nichol et al., 2003). This number is closer to 66% for patients over 65 (MMWR, 2003). Among the elderly, immunization programs that increase access have demonstrated vaccination numbers of 84% (Nichol et al., 1998). For the cost- effectiveness of NEMT, compliance with receiving the vaccination is of little interest, since a patient not taking the vaccine is also not likely to incur transportation or medical visit costs. Therefore, no compliance rate is applied in this analysis. Final Report 55

Step 2. Research cost and benefit parameters. Literature on cost-effectiveness of preventive screenings and vaccinations indicates that getting a vaccination is cost- effective. The direct and indirect costs avoided annually for patients with a flu vaccine are estimated to be $49.73 (Nichol et al., 2003). Step 3. Determine the cost for a vaccination visit. The cost to visit a nurse and be vaccinated for flu, estimated in 1998 dollars, is $10 – $36 depending on whether the patient is a child or adult. This includes the cost of the vaccine (Luce et al., 2001). Step 4. Determine the cost of a paratransit trip. As determined in Chapter 5, round trip costs range from $43.86 to $74.86. Step 5. Incorporate the trip cost into the cost-effectiveness calculation. (We are using the term “transit” in this discussion though not all of the transportation services are literally “public transportation”.) As stated in Step 1, compliance factors are not applied for patients who do not get vaccinated, as they are assumed to also not use NEMT. The results are presented in Table 7-1, using the low, intermediate, and high transportation costs shown in Table 5-3. Providing NEMT for flu vaccination is not cost saving, however at the highest cost of $61.13, contracting the flu and the quality of life impacts of having the flu can be avoided. Considering the risk of death for elderly flu patients, the cost of NEMT is negligible. NEMT for flu vaccination is cost-effective. Table 7-1: Cost-Effectiveness Results for Flu Vaccine Transit Cost Scenario Average Round Trip Cost Visit and Vaccine Cost (Low Estimate) Visit and Vaccine Cost (High Estimate) Total Trip Cost (Low) Total Trip Cost (High) Costs Avoided with Flu Vaccine Net Cost Difference (Low) Net Cost Difference (High) Low $43.86 $10 $36.00 $53.86 $79.86 $49.73 ($4.13) ($30.13) Intermediate $44.44 $10 $36.00 $54.44 $80.44 $49.73 ($4.71) ($30.71) High $74.86 $10 $36.00 $84.86 $110.86 $49.73 ($35.13) ($61.13) 7.1.2 Prenatal Care Prenatal care offers an opportunity to both increase infant survival rates and delay pre-term delivery in high-risk pregnancies, through nutritional counseling and screening for various conditions of the mother or fetus (Bonifield, 1998). Additionally, screening programs for maternal diabetes, neural tube deficiencies, HIV, and Downs’s Syndrome have demonstrated effectiveness (USPSTF, 1996; USPSTF, 2005). These screenings often occur during prenatal care visits and the benefits associated suggest that prenatal care is highly cost-effective. This analysis focuses on the cost-effectiveness of prenatal care to prevent premature birth. Step 1. Determine the compliance rates for prenatal care. Low birth weight can be reduced through prenatal care, but not eliminated. The cost-effectiveness studies above take this fact into account. Despite the availability of prenatal services, 16% Final Report 56

of mothers had inadequate prenatal care (Schramm, 1992). In a study of insured patients, 8% of women received inadequate prenatal care due to transportation barriers (Braveman et al., 2000). The compliance factor ranges from 84% to 92% for prenatal services. Step 2. Using the literature, determine cost-effectiveness of prenatal care. In a comparison of Missouri women receiving Medicaid, infants born to women who had received adequate prenatal care cost significantly less than infants born to women with inadequate care, defined as no appointments or appointments beginning after month 7 of pregnancy. For each dollar spent on prenatal services, Medicaid saved $1.49 (Schramm, 1992). Infants born to mothers receiving any prenatal care weighed 5.09 ounces more than those born to mothers who received no prenatal care. The cost of care for low birth weight infants is very high, such that the annual cost savings of prenatal care is $230 per patient (Henderson, 1994). Step 3. Determine the cost for a prenatal care visit and the number of visits required to meet the standards of adequate prenatal care. The average number of prenatal visits in a community setting was 8 with an obstetrician/gynecologist over the 9- month gestation period, while adequate care was defined as at least 9 visits starting within the first 3 months of pregnancy (Bienstock et al., 2001; Schramm, 1992). The cost of providing prenatal care is included in the cost-effectiveness results in Step 2. Step 4. Determine the cost of a prenatal trip. As determined in Chapter 5, round trip costs range from $26.16 to $40.36. Trip costs are shown in Table 7-2. Table 7-2: Prenatal Care Trip Costs Transit Cost Scenario Average Round Trip Cost Visit Cost Trips for Prenatal Care (Low Estimate) Trips for Prenatal Care (High Estimate) Total Trip Cost (Low Estimate) Total Trip Cost (High Estimate) Low $26.16 $52.68 8 9 $630.72 $709.56 Intermediate $33.26 $52.68 8 9 $687.52 $773.46 High $40.36 $52.68 8 9 $744.32 $837.36 Step 5. Incorporate the medical cost outcomes into the cost-effectiveness calculation. The average cost of care for prenatal patients is $1,045.69 compared to $2,244.11 for those without. The cost-effectiveness results are shown in Table 7-3. While there are 12 possible combinations of results (3 transit costs * 2 compliance rates * 2 trip amounts), we simplify the presentation by showing 3 outcomes: • Best outcome – lowest transit cost, highest compliance, lowest visits • Worst outcome – highest transit cost, lowest compliance, most visits Final Report 57

• Intermediate outcome – intermediate transit cost, mid range for compliance, and a most likely visit count (8). Prenatal care is cost saving for every scenario, with out most likely outcome of $367 savings per person. Considering that quality of life improvement for patients that have full term pregnancies (both mothers and infants) are not included here, NEMT for prenatal care is clearly cost-effective. Table 7-3: Cost-Effectiveness Results for Prenatal Care Combined Scenario ComplianceFactor Poorly Minus Well Cost of Prenatal Care Adjusted Cost Difference Travel & Medical Cost Net Change in Costs Low Transit $, Best Compliance, Fewest Visits 92% $1,198.42 $1,102.55 $630.72 $472 High Transit $, Worst Compliance, Most Visits 84% $1,198.42 $1,006.67 $873.36 $169 Intermediate Transit $, Mid Compliance, Likely Visits 88% $1,198.42 $1,054.61 $687.52 $367 7.1.3 Cancer Screening: Breast Cancer Some cancer screenings are highly effective at catching the early stages of cancer allowing for rapid treatment. Both breast and colorectal cancer benefit greatly from early detection to prevent costly treatments, such as intensive chemotherapy, or undesirable health outcomes including early mortality. This preventive care example presents the cost-effectiveness results for breast cancer screening. Step 1. Determine the compliance rates for breast cancer screening. Studies have shown that 45-65% of women over age 65 participate in breast cancer screening and follow-up treatment (Mandelblatt et al., 2003). A screening, however, is a trip and so those that are not compliant with screening do not incur any NEMT costs. Compliance does not factor into this analysis. Step 2. Using the literature, determine cost-effectiveness of breast cancer screening. Biennial breast cancer screening for women age 65 and older has incremental costs of $34,000 to $88,000 per life year gained (Mandelblatt et al., 2003). Step 3. Determine the cost of breast cancer screening. Mammography screening costs between $66 and $198 for breast cancer (Mandelblatt et al., 2003). A screening is recommended for women over age 65 every two years. Step 4. Determine the cost of a trip for breast cancer screening. These costs were determined in Chapter 5 and are shown in Table 7-4. Step 5. Incorporate the trip cost into the cost-effectiveness calculation. Given that breast cancer screening costs $34,000-$88,000 per life year saved, and $50,000 is Final Report 58

commonly accepted as an upper bound cost for an additional life year, the cost for a trip must be less than $16,000. Table 7-4 shows the net costs of NEMT for breast cancer screening. Although these costs are all higher than the healthcare utilization costs avoided, including our best estimate intermediate cost of $34,176, they fall under the $50,000 QALY cost estimate threshold, and thus are cost-effective. Table 7-4: Cost-Effectiveness Results for Breast Cancer Screening Combined Scenario Average Round Trip Cost Visit and Screen Cost (Low Estimate) Visit and Screen Cost (High Estimate) Total Trip Cost (Low) Total Trip Cost (High) Net Cost of Breast Cancer Screening Net Cost Difference (Low) Net Cost Difference (High) Low Transit $ $43.86 $66 $198 $110 $242 ($34,000) ($34,110) ($34,242) High Transit $ $74.86 $66 $198 $141 $273 ($34,000) ($34,141) ($34,273) Intermediate $44.44 $132 $176 ($34,000) ($34,176) 7.1.4 Cancer Screening: Colorectal Cancer This preventive care example presents the cost-effectiveness results for colorectal, or colon, cancer screening. Step 1. Determine the compliance rates for colon cancer screening. Although studies have shown that 36% of patients getting colorectal screens prefer colonoscopy, participation in this type of screening is low – about 18.2% (Scott et al., 2004). A screening, however, is a trip and so those that are not compliant with screening do not incur any NEMT costs. Compliance does not factor into this analysis. Step 2. Using the literature, determine cost-effectiveness of colon cancer screening. The cost-effectiveness of a colonoscopy every 10 years to screen for colon cancer is $9,083 to $22,012 (2000 dollars) per life year saved (Pignone et al., 2002a). Step 3. Determine the cost of colon cancer screening. Colonoscopy screening costs are between $285 and $1,012 for colorectal cancer (Pignone et al., 2002a). Step 4. Determine the cost of a trip for colon cancer screening. These costs were derived in Chapter 5 and are shown in Table 7-5. Step 5. Incorporate the trip cost into the cost-effectiveness calculation. Given that 18.2% of men are compliant with colon cancer screening, screening costs $9,083 to $22,012 per life year saved, and $50,000 is commonly accepted as an upper bound cost for an additional life year, the cost for a trip must be less than $27,988. Screenings are recommended every ten years, and as the costs in Table 7-5 show, the trip costs have little impact on colon cancer screening cost-effectiveness. Although these costs are all higher than the healthcare utilization costs avoided, including our best estimate intermediate cost of $22,735, they all fall comfortably below the $50,000 QALY cost estimate threshold, and thus are judged cost-effective. Final Report 59

Table 7-5: Cost-Effectiveness Results for Colon Cancer Screening Combined Scenario Average Round Trip Cost Visit and Screen Cost (Low Estimate) Visit and Screen Cost (High Estimate) Total Trip Cost (Low) Total Trip Cost (High) Net Cost of Colon Cancer Screening Net Cost Difference (Low) Net Cost Difference (High) Low Transit $ $43.86 $285 $1,012 $328.86 $1,055.86 $(22,012) ($22,341) ($23,068) High Transit $ $74.86 $285 $1,012 $329.44 $1,056.44 $(22,012) ($22,341) ($23,068) Intermediate $44.44 $648.50 $723.36 $(22,012) ($22,735) 7.1.5 Dental Care Research has demonstrated a link from oral health to general health, thus emphasizing the importance of dental preventive care (U.S. DHHS, 2000; Mertz & O’Neil, 2002; AHRQ, 2002). Dental caries is the leading chronic disease among children and the treatment for caries is the leading unmet need (Bader et al., 2004). 25% of children enter kindergarten with untreated dental decay. This problem affects poor children far more than non-poor (36.8% of poor children age 2-9 years old have untreated dental decay compared to 17.3% of non-poor children). Among adults aged 50-69, 31.2% of African Americans, 28.2% of Mexican Americans and 16.9% have untreated periodontal disease. For adults 70 years and over, the percentages rise to 47.1%, 32.0%, and 24.1% for the three groups (Stanton et al., 2003). Step 1. Determine the compliance rates for preventive dental care appointments. The authors assumed a 75% participation in preventive dental services in the cohort analyzed for cost-effectiveness (Ramos-Gomez et al., 1999). Participation in preventive dental care among low-income patients on Medicaid is very low – only 20% of children on Medicaid get preventive dental services. 42.9% of children under age 18 in middle or high-income categories received preventive dental services (Stanton et al., 2003). Step 2. Using the literature, determine cost-effectiveness of preventive dental care. The incremental cost-effectiveness ratio for providing preschool children with preventive dental services resulted in a ratio of $73 for each carious surface avoided (Ramos-Gomez et al., 1999). Step 3. Determine the cost of a preventive dental appointment. The cost of a specialist appointment according to the Medicare Prospective Payment fee schedule is $120.14; however dental visit costs vary widely by region (U.S. GAO, 2000b). This visit cost is a conservative estimate. Step 4. Determine the cost of a trip for preventive dental care. These costs were derived in Chapter 5. They range from $26.16 to $40.36, with $33.26 as the intermediate value. Step 5. Incorporate the trip cost into the cost-effectiveness calculation. Given the population compliance with preventive dental care, and the cost-effectiveness for Final Report 60

dental care is $75 per tooth, the additional cost of providing NEMT does not increase the overall cost of dental care beyond the $50,000 threshold. The cost-effectiveness results are shown in Table 7-6. While there are 12 possible combinations of results (3 transit costs * 2 compliance rates * 2 trip amounts), we simplify the presentation by showing 3 outcomes: • Best outcome – lowest transit cost, highest compliance, lowest visits (1) • Worst outcome – highest transit cost, lowest compliance, most visits (12) • Intermediate outcome – intermediate transit cost, mid range for compliance, and a most likely visit count (4). Although these costs are all higher than the healthcare utilization costs avoided, including our best estimate intermediate cost of $590 they all fall below the $50,000 QALY cost estimate threshold, and thus are judged cost-effective. Table 7-6: Cost-Effectiveness Results for Preventive Dental Care Combined Scenario Compliance Factor Net Cost of Dental Care per Carious Surface Avoided Adjusted Cost Difference Travel & Medical Cost Net Change in Costs Low Transit $, Best Compliance 43% $75 $32.25 $146.30 $(114) High Transit $, Worst Compliance 20% $75 $15.00 $1,926 $(1,911) Intermediate Transit $, Mid Compliance 31.5% $75 $23.63 $613.60 $(590) 7.2 Cost-Effectiveness of Increased Access to Healthcare for Chronic Conditions This section presents the cost-effectiveness case studies that lie at the heart of understanding how enhanced transportation access may improve healthcare for individuals with highly prevalent chronic conditions. These are based on extensive analysis of MEPS data that compares the healthcare expenditure patterns of well and poorly managed patients at the condition level. Beyond the health consequences for affected individuals, these conditions impose large societal costs. Fortunately, there appears to be significant evidence that proper disease management of these conditions has the potential to both reduce healthcare expenditures and improve the health of the patients. Most of this monitoring depends on a high number of routine physician visits, thus transportation plays a critical role in ensuring appropriate care. As discussed in Chapter 6, not all of the conditions can be accurately analyzed through the well and poorly managed delineation. Diabetes, hypertension, and congestive heart failure affect health over a wide time horizon. A one-year MEPS dataset snapshot does not appropriately capture this dynamic context. These conditions will be described using MEPS for the one-year comparison of healthcare costs, and the literature on future cost-effectiveness is also presented. Final Report 61

The following calculations rely on this formula: [Compliance factor * (poorly managed cost – well managed cost)] – [# of visits * (cost of transportation + cost of medical visit)] * QALY adj. = Net change in costs and quality of life for disease management 7.2.1 Asthma Asthma is highly prevalent in the U.S. population, especially among children. More than seven million children have an asthma diagnosis and 85% use some form of asthma medication. Untreated asthma results in exacerbations that can be deadly without medical interventions. As a result, asthma is an ideal condition for the disease management model – frequent physician contact has been shown to reduce expensive emergency room visits and hospitalizations. Step 1. Select all survey respondents in MEPS who did not miss a trip to the doctor due to transportation problems and who had health insurance during the entire year (2001). From this data set, we isolated all patients with the medical condition asthma, as determined using ICD-code 493. This dataset allows us to compare well managed to poorly managed asthma care with the effects of transportation difficulties and lack of insurance removed to avoid confounding the access to care situation. This process located 10,450,078 individuals. Step 2. Review the characteristics of well- and poorly managed asthma care through the literature. For asthma, poorly managed care is defined as any inpatient stay or emergency room visit. Well-managed care is defined as one year without inpatient or emergency room visits (National Asthma Education and Prevention Program, 1997). Step 3. Isolate the well-managed patients (those who do not have any hospitalizations or emergency room visits in the past 12 months) and review their per capita cost of care. These patients represent the expected costs for well-managed patients with transportation deficiencies addressed. We identified poorly managed patients as those with at least one hospitalization or emergency room visit. These patients represent expected costs for patients who are not well managed for many reasons, including transportation deficiencies. Likewise, we reviewed their per capita cost of care. Table 7-7 shows the results of this analysis. Median per capita costs were used because they are considered conservative and likely to be a more accurate estimate of true costs. The cost difference is $1,432. Final Report 62

Table 7-7: Cost Comparison of Asthma Patients in MEPS (2001) Per Capita Population Unweighted Frequency Inpatient Costs ER Costs Outpatient Costs Rx Costs Office Based Cost Total Costs (Mean) Total Costs (Median) Entire Asthma Population 1,347 $329 $47 $14 $403 $127 $920 $279 Transportation-Advantaged / Insured Asthma Population 1,224 $325 $47 $15 $401 $131 $919 $281 Poorly Managed 132 $3,312 $484 $40 $528 $228 $4,593 $1,675 Well Managed 1,092 $0.00 $0.00 $13 $387 $120 $520 $243 Difference Between Poorly and Well-Managed Care: $4,073 $1,432 Step 4. Determine the compliance factor(s) for asthma care from the literature. Asthma is the most prevalent chronic disease among children. For this reason, an asthma disease management program targeting a pediatric population was used to determine patient compliance with well-managed care for the children in the transportation-disadvantaged population. Following a disease management program, five of the 29 children randomized to the program did not experience changes to their condition significant enough to fit the well-managed asthma criteria. Thus, the noncompliance factor for children with asthma is 5/29 or 17%, and the compliance factor is 83% (Greineder et al., 1999). Adult asthma patients in a disease management program were also studied and non-adherence was estimated at 30 to 70% (Bender et al., 1997). The best-case scenario is compliance at 83%; the worst case is compliance of 30%. Applying this factor to the cost difference between well and poorly managed asthma patients derived in step 3 produces an adjusted cost difference of $1,189 in the best case scenario and $430 in the worst case. Step 5. Determine from the literature review how many visits or trips per capita, per year are required to manage a patient with chronic asthma adequately. Well- managed asthma requires 2 to 12 visits with providers per year (National Asthma Education and Prevention Program, 1997). Step 6. Use the Medicare Fee Schedule cost weights to determine the average medical cost of the required visits. The fee schedule contains five levels of physician visits for established patients, ranging from basic to extensive. As explained in Chapter 6, we use established cost weights as opposed to new cost weights (which are higher) because we assume that care will be well managed and this implies that patients have a usual source of care, i.e., that visits involve an established provider relationship. The five levels, codes, and cost weights are shown in Table 6-6. To capture both maintenance care and occasional specialist care, we use the fourth level cost weight of $82.62. Step 7. Determine the cost of the NEMT. This cost depends on rural or urban location and whether the patient is mobile or requires a modified vehicle for travel. These estimates were derived in Chapter 5 and, along with medical costs, are summarized in Table 7-8. Final Report 63

Table 7-8: Calculation of NEMT Cost for Asthma Trips for Asthma Total Annual Trip Cost Transit Cost Scenario Average Round Trip Cost Visit Cost Fewest Trips Most Trips Low Estimate High Estimate Low $ 42.14 $ 82.62 2 12 $ 249.52 $ 1,497.12 Intermediate $ 43.70 $ 82.62 2 12 $ 252.64 $ 1,515.84 High $ 75.86 $ 82.62 2 12 $ 316.96 $ 1,901.76 Step 8. Incorporate quality of life adjustments so that the analysis will correspond to the QALY methodology. Patients in the well-managed population have a median QALY score of 0.80 compared to the poorly managed patients who reported a score of 0.73. Thus, patients who move from poor to well managed status can expect a QALY increase of 9.6% ((0.80-0.73)/0.73). Note that the quality of life adjustment inflates the amount of cost saving, but deflates the amount of new costs. The cost-effectiveness results are shown in Table 7-9. While there are 12 possible combinations of results (3 transit costs * 2 compliance rates * 2 trip amounts), we simplify the presentation by showing 3 outcomes: • Best outcome – lowest transit cost, highest compliance, lowest visits • Worst outcome – highest transit cost, lowest compliance, most visits • Intermediate outcome – intermediate transit cost, mid range for compliance, and a most likely visit count. The latter outcome – average round trip cost of $43.70, a compliance rate of 56.5%, and 4 visits – produces our most likely estimate of $333 for adjusted cost savings per person. The results show that one year of asthma disease management provided through NEMT is cost saving in our intermediate outcome, and cost-effective overall in that the cost of NEMT does not exceed the $50,000/QALY threshold commonly accepted in healthcare. Final Report 64

Table 7-9: Cost-Effectiveness Results for Asthma NEMT Compliance Factor Poorly minus Well Median Cost per Capita Adjusted Cost Difference Annual Travel & Medical Cost Net Change in Costs QALY Adjustment QALY- Adjusted Cost Savings Combined Scenario (1) (2) (1)*(2) = (3) (4) (3)-(4) = (5) (6) (5)*(6) Low Transit $, Best Compliance, Fewest Trips 83% $1,431.65 $1,188.27 $249.52 $938.75 109.6% $1,029 High Transit $, Worst Compliance, Most Trips 30% $1,431.65 $429.50 $1,901.76 $(1,472.27) 109.6% $(1,325) Intermediate Transit $, Mid Compliance, Likely Trips 56.5% $1,431.65 $808.88 $505.28 $303.60 109.6% $333 7.2.2 Heart Disease Heart disease is the leading cause of death in the United States and accounts for 29 percent of the 2,416,425 total deaths recorded during 2001. There is a steep age- related gradient so that fully 37.5 percent of deaths for those aged 85 years and over are caused by heart disease (Anderson and Smith, 2003). More specifically, congestive heart failure (CHF) is a primary or secondary cause of death for approximately 250,000 people per year in the United States. CHF was the first-listed diagnosis for 962,000 hospitalizations in 1999, and it is the most common diagnosis among hospital patients age 65 and older. There are over three million outpatient office visits each year related to CHF. In 1998, the estimated annual direct cost due to HF was $18.8 billion (Shekelle et al., 2003). Step 1. Select all survey respondents in MEPS who did not miss a trip to the doctor due to transportation problems and who had health insurance during the entire year (2001). From this data, we isolate all patients with CHF as determined using ICD-9 code 428. This process located 1,412,685 individuals. In an earlier analysis, we computed cost-effectiveness using an inclusive definition of heart disease (ICD-9 codes 410-414, and 427-429. However, for the cost-effectiveness analysis included in this final report, it was thought that a focus on CHF was more relevant. Step 2. Review the characteristics of well- and poorly managed CHF care through the literature. Well-managed patients use ACE inhibitors and/or beta-adrenergic blockers. Poorly managed patients are not taking such medications. For CHF, care is defined following an inpatient stay or emergency room visit. Poorly managed heart failure patients will have more than one inpatient stays or emergency room visits within 90 days. Well-managed CHF patients will have one or fewer inpatient or emergency room visits (Hunt et al., 2001). Step 3. Isolate the well-managed patients (based on the use of the ACE inhibitors and/or beta-blocker medications) and review their per capita cost of care. These patients represent the expected costs for well-managed patients with transportation Final Report 65

deficiencies addressed. We identify poorly managed patients as those who use neither ACE inhibitors nor beta-blocker medications, and have at least one ER/inpatient stay. These patients represent expected costs for patients who are not well managed for many reasons, including transportation deficiencies. Likewise, we reviewed their median per capita cost of care. These costs are summarized in Table 7-10. Table 7-10: Cost Comparison of CHF Patients in MEPS (2001) Per Capita Population UnweightedFrequency Inpatient Costs ER Costs Outpatient Costs Rx Costs Office Based Cost Total Costs (Mean) Total Costs (Median) Entire CHF Population 161 $5,501 $154 $476 $486 $510 $7,127 $1,657 Transportation-Advantaged / Insured CHF Population 150 $5,710 $161 $501 $481 $537 $7,390 $1,788 Poorly Managed 39 $15,528 $485 $114 $238 $309 $16,673 $6,713 Well Managed 111 $2,085 $42 $643 $571 $622 $3,964 $1,033 Difference Between Poorly and Well-Managed Care: $12,709 $5,679 Step 4. Determine the compliance factor(s) for heart disease care from the literature. Heart failure is the single most common DRG in Medicare patients. In a well- managed population one year after an inpatient stay for CHF, 84% of patients were using appropriate ACE medications and 82% were using beta-blockers compared to 38% using ACE and 56% using beta-blockers in the poorly managed population (Akosah et al., 2002). We will use these compliance numbers for heart disease patients. Step 5. Determine from the literature review how many visits or trips per capita per year are required to manage a patient with heart disease adequately. Well-managed heart disease requires approximately 10 visits with clinicians per year – at least 2 of which are with cardiology specialists (Akosah et al., 2002). Step 6. Use the Medicare Fee Schedule cost weights to determine the average medical cost of the required visits. For this analysis we use an estimate equal to $52.68 for a standard physician visit and $120.14 for a cardiology specialist visit. Step 7. Determine the cost of a trip. This cost depends on rural or urban location and whether the patient is mobile or requires a modified vehicle for travel. These estimates were derived in Chapter 5 and, along with medical costs, whether specialist or primary care, are summarized in Table 7-11. Final Report 66

Table 7-11: Calculation of NEMT Cost for CHF Transit Cost Scenario Average Round Trip Cost Primary Care Visit Cost Specialist Visit Cost Trips for CHF (Primary Care) Trips for CHF (Specialist) Total Annual Trip Cost Low $43.88 $52.68 $120.14 8 2 $1,100.52 Intermediate $45.66 $52.68 $120.14 8 2 $1,118.32 High $92.10 $52.68 $120.14 8 2 $1,582.72 Step 8. Incorporate quality of life adjustments so that the analysis will correspond to the QALY methodology. Well-managed patients with CHF have a QALY score of 0.69 compared to poorly managed patients, who report a QALY score of 0.59. Thus, patients who move from poor to well managed status can expect a QALY increase of 16.9% ((0.69-0.59)/0.59). The cost-effectiveness results are presented in Table 7-12. While there are 6 possible combinations of results (3 transit costs * 2 compliance rates), we simplify the presentation by showing 3 outcomes: • Best outcome – lowest transit cost and highest compliance • Worst outcome – highest transit cost and lowest compliance • Intermediate outcome – intermediate transit cost and mid range for compliance. The latter outcome – average round trip cost of $45.66 and a compliance rate of 61% – produces our most likely estimate of $2,743 for adjusted cost savings per person. This analysis shows large potential gains from better management of heart disease for the transportation-disadvantaged population. Given the $50,000 per QALY threshold, providing NEMT for CHF is highly cost-effective. Table 7-12: Cost-Effectiveness Results for CHF NEMT Compliance Factor Poorly Minus Well Median Cost per Capita Adjusted Cost Difference Annual Travel & Medical Cost Net Change in Costs QALY Adjustment QALY- Adjusted Cost Savings Combined Scenario (1) (2) (1)*(2) = (3) (4) (3)-(4) = (5) (6) (5)*(6) Low Transit $, Best Compliance 84% $5,679.37 $4,770.67 $1,100.52 $3,670.15 116.9% $4,290 High Transit $, Worst Compliance 38% $5,679.37 $2,158.16 $1,582.72 $575.44 116.9% $673 Intermediate Transit $, Mid Compliance 61% $5,679.37 $3,464.42 $1,118.32 $2,346.10 116.9% $2,743 Final Report 67

7.2.3 Chronic Obstructive Pulmonary Disease (COPD) Chronic Obstructive Pulmonary Disease (COPD) is a condition of the lungs where airflow is restricted. Many diseases lead to COPD including emphysema and bronchitis. COPD is often the consequence of smoking and is the fourth leading cause of death worldwide (Van der Valk et al., 2004). Step 1. Select all survey respondents in MEPS who did not miss a trip to the doctor due to transportation problems and who had health insurance during the entire year (2001). From this data, we isolate all patients with COPD as determined using ICD-9 codes 490-492 (includes bronchitis, chronic bronchitis and emphysema). This process located 9,565,608 individuals. Step 2. Review the characteristics of well- and poorly managed COPD care through the literature. Well-managed patients with COPD have a prescription for bronchodilators (long acting beta2-agonists such as salmeterol or formoterol, anticholinergics like tiotropium, and/or theophylline), or patients are maintained on inhaled corticosteroids (National Clinical Guideline on Management of Chronic Obstructive Pulmonary Disease, 2004; Van der Valk et al., 2004). Poorly managed patients have at least one hospitalization for COPD over 1 year (Bourbeau et al., 2003). Step 3. Isolate the well-managed patients (based on the use of the medications specified in Step 2) and review their per capita cost of care. These patients represent the expected costs for well-managed patients with transportation deficiencies addressed. We identify poorly managed patients as those with at least one inpatient stay for COPD. These patients represent expected costs for patients who are not well managed for many reasons, including transportation deficiencies. Likewise, we reviewed their median per capita cost of care. These costs are summarized in Table 7-13. Table 7-13: Cost Comparison of COPD Patients in MEPS (2001) Per Capita Population Unweighted Frequency Inpatient Costs ER Costs Outpatient Costs Rx Costs Office Based Cost Total Costs (Mean) Total Costs (Median) Entire COPD Population 1,105 $548 $32 $31 $194 $146 $952 $150 Transportation- Advantaged / Insured COPD Population 1,009 $578 $31 $34 $191 $149 $984 $150 Poorly Managed 101 $6,358 $339 $55 $413 $238 $7,402 $1,077 Well Managed 908 $0.00 $0.00 $32 $169 $140 $342 $135 Difference Between Poorly and Well-Managed Care: $7,060 $942 Step 4. Determine the compliance factor(s) from the literature. 40% of patients were compliant with their medications two years after diagnosis with COPD (Make et al., 2003). Final Report 68

Step 5. Determine from the literature review how many visits or trips per capita per year are required to manage a patient with COPD. There are 13 outpatient visits per year for the management of advanced COPD (Strijbos et al., 1996). Step 6. Use the Medicare Fee Schedule cost weights to determine the average medical cost of the required visits. For this analysis we are use an estimate equal to $52.68 for a standard physician visit and $120.14 for a nephrology specialist visit. We assume that half the COPD visits will be with a specialist. Step 7. Determine the cost of a trip. This cost depends on rural or urban location and whether the patient is mobile or requires a modified vehicle for travel. These estimates were derived in Chapter 5 and, along with medical costs, whether specialist or primary care, are summarized in Table 7-14. Table 7-14: Calculation of NEMT Cost for COPD Transit Cost Scenario Average Round Trip Cost Primary Care Visit Cost Specialist Visit Cost Trips for COPD (Primary Care) Trips for COPD (Specialist) Total Annual Trip Cost Low $42.36 $52.68 $120.14 6 7 $1,707.74 Intermediate $43.34 $52.68 $120.14 6 7 $1,720.48 High $67.84 $52.68 $120.14 6 7 $2,038.98 Step 8. Incorporate quality of life adjustments so that the analysis will correspond to the QALY methodology. Well-managed patients with COPD have a QALY score of 0.80 compared to poorly managed patients, who report a QALY score of 0.76. Thus, patients who move from poor to well managed status can expect a QALY increase of 5.3 ((0.80-0.76)/0.76). The cost-effectiveness results for COPD are presented in Table 7-15. There are 3 possible outcomes depending solely on estimated transit costs. We do not find actual cost savings, but additional transit and healthcare costs pale in comparison to the $50,000 standard. Thus there are large potential gains from better management of COPD. Table 7-15: Cost-Effectiveness Results for COPD NEMT Compliance Factor Poorly minus Well Median Cost per Capita Adjusted Cost Difference Annual Travel & Medical Cost Net Change in Costs QALY Adjustment QALY- Adjusted Cost Savings Combined Scenario (1) (2) (1)*(2) = (3) (4) (3)-(4) = (5) (6) (5)*(6) Low Transit $ 40% $942.26 $376.90 $1,707.74 $(1,330.84) 105.3% $(1,260) High Transit $ 40% $942.26 $376.90 $2,038.98 $(1,662.08) 105.3% $(1,574) Intermediate Transit $ 40% $942.26 $376.90 $1,720.48 $(1,343.58) 105.3% $(1,272) Final Report 69

7.2.4 Hypertension High blood pressure, or hypertension (HTN), is highly prevalent and often occurs along with diseases such as diabetes, obesity and heart disease. For many, high blood pressure is quite manageable, however when untreated for a long period of time it can lead to serious health complications, including stroke, and early mortality. HTN does not have symptoms that are immediately improved through disease management, and this long-term nature creates difficulty when categorizing the well and poorly managed patients. This is addressed through two separate screens that are described in detail in Step 2. Step 1. Select all survey respondents in MEPS who did not miss a trip to the doctor due to transportation problems and who had health insurance during the entire year (2001). From this data, we isolate all patients with HTN as determined using ICD-9 codes 401-405 (includes essential hypertension; hypertensive heart disease; hypertensive renal disease; hypertensive heart and renal disease; and secondary hypertension). This process located 31,944,421 individuals. Step 2. Review the characteristics of well- and poorly managed HTN care through the literature. Well managed is defined as taking a beta-blocker or angiotensin- converting enzyme inhibitor, as well as 2 physician outpatient visits per year and 3 chemistry panels (CDC Diabetes Cost-effectiveness Group, 2002; National Heart, Blood and Lung Institute, 2004). Poorly managed patients have a diagnosis of hypertension and do not have appointments or take medications to control blood pressure. Step 3. Isolate the well-managed patients and review their per capita cost of care. We employ two separate screens to classify well and poorly managed HTN patients. The first screen categorizes poorly managed patients as having no visits or blood pressure lowering medications, while well managed patients do have visits and HTN medication. Table 7-16 summarizes the cost comparison under the first screen. Table 7-16: Drug and Visit Screen Cost Comparison of HTN in MEPS (2001) Per Capita Population Unweighted Frequency Inpatient Costs ER Costs Outpatient Costs Rx Costs Office Based Cost Total Costs (Mean) Total Costs (Median) Entire HTN Population 3,829 $102 $10 $27 $446 $170 $755 $432 Transportation-Advantaged / Insured HTN Population 3,539 $99 $9 $28 $449 $172 $757 $436 Poorly Managed 2,478 $40 $6 $5 $399 $67 $517 $328 Well Managed 1,061 $240 $18 $82 $568 $422 $1,330 $788 Difference Between Poorly and Well-Managed Care: $(813) $(460) The second screen compares well and poorly managed HTN patients based on medication utilization only. This comparison also looks at the difference in total healthcare costs between the well and poorly managed patients in consideration of the high prevalence of co-morbid conditions present in patients with poorly treated Final Report 70

blood pressure (Table 7-17). We believe that this second screen, using drugs only and counting all costs (inclusive of healthcare costs related to other diseases), best approximates the estimates of the savings associated with HTN disease management from the literature. We will use the average total cost change for the population moving from poor to well managed blood pressure to assess the cost-effectiveness of NEMT. Although median costs have been used in conditions that present the costs of utilization that is disease specific, the mean is a more appropriate measure when total costs are examined. Median costs will eliminate any bias presented by a few patients who are sick enough and therefore utilizing the most healthcare. When looking at the total cost of healthcare for all patients with high blood pressure, the bias of those who are most sick should be taken into account in our cost estimates, as they are the people who could benefit the most from HTN management. Table 7-17: Drug Screen Only HTN and TOTAL Cost Comparisons in MEPS (2001) Per Capita Population Unweighted Frequency Inpatient Costs ER Costs Outpatient Costs Rx Costs Office Based Cost HTN Costs (Mean) HTN Costs (Median) Total Costs (Mean) Total Costs (Median) Entire HTN Population 3,829 $102 $10 $27 $446 $170 $755 $432 $5,980 $2,595 Transportation- Advantaged / Insured HTN Population 3,539 $99 $9 $28 $449 $172 $757 $436 $6,044 $2,671 Poorly Managed 695 $27 $8 $11 $343 $161 $549 $340 $6,770 $2,586 Well Managed 2,844 $117 $10 $32 $474 $174 $807 $463 $5,869 $2,690 Difference Between Poorly and Well-Managed Care: ($258) ($123) $901 ($104) Step 4. Determine the compliance factor(s) from the literature. 60% of patients had 3-month appointments; 43% of patients use diuretics, while 29% used calcium channel blockers, and 25% used beta-blockers (Weir et al., 2000). Step 5. Determine from the literature review how many visits or trips per capita per year are required to manage a patient with HTN. Clinical guidelines recommend 4 outpatient visits per year (National Heart, Blood and Lung Institute, 2004). Step 6. Use the Medicare Fee Schedule cost weights to determine the average medical cost of the required visits. For this analysis we are use an estimate equal to $52.68 for a standard physician visit. We assume all of these visits will be with a primary care doctor. Step 7. Determine the cost of a trip. This cost depends on rural or urban location and whether the patient is mobile or requires a modified vehicle for travel. These estimates were derived in Chapter 5 and, along with medical costs, are summarized in Table 7-18. Final Report 71

Table 7-18: Calculation of NEMT Cost for HTN Transit Cost Scenario Average Round Trip Cost Primary Care Visit Cost Trips for HTN (Primary Care) Total Trip Cost Low $42.80 $52.68 4 $381.92 Intermediate $44.66 $52.68 4 $389.36 High $86.92 $52.68 4 $558.40 Step 8. Incorporate quality of life adjustments so that the analysis will correspond to the QALY methodology. In our first screen of well and poorly managed HTN patients, we saw QALY scores go down for the so-called well managed patients. Our second screen, using drug utilization as an indicator of good disease management, showed QALY scores that were higher for the well-managed patients. We use the second screen to measure both the QALY score change and the cost change for the HTN population. Well-managed patients with HTN have a QALY score of 0.80 compared to poorly managed patients, who report a QALY score of 0.76. Thus, patients who move from poor to well managed status can expect a QALY increase of 5.3% ((0.80-0.76)/0.76). The cost-effectiveness results are presented in Table 7-19. We simplify the 6 possible combinations of results by showing 3 outcomes: • Best outcome – lowest transit cost and highest compliance • Worst outcome – highest transit cost and lowest compliance • Intermediate outcome – intermediate transit cost and mid range for compliance. The latter outcome produces our most likely estimate of $(6). Cost savings occur in the best-case scenario; even in the worst-case, hypertension NEMT costs only $315. In light of the $50,000 standard, we are confident that disease management for HTN patients is highly cost-effective when future cost savings are taken into account. Table 7-19: Cost-Effectiveness Results for HTN NEMT Compliance Factor Poorly Minus Well Mean Cost per Capita Adjusted Cost Difference Travel & Medical Cost Annual Net Change in Costs QALY Adjustment QALY- Adjusted Cost Savings Combined Scenario (1) (2) (1)*(2) = (3) (4) (3)-(4) = (5) (6) (5)*(6) Low Transit $, Best Compliance 60% $901.00 $540.60 $381.92 $158.68 105.3% $167 High Transit $, Worst Compliance 25% $901.00 $225.25 $558.40 $(331.15) 105.3% $(315) Intermediate Transit $, Mid Compliance 42.5% $901.00 $382.93 $389.36 $(6.44) 105.3% $(6) Final Report 72

7.2.5 Diabetes Diabetes is a disorder of the pancreas where the body cannot produce or utilize insulin properly. In the United States, the prevalence of Type 2 diabetes is rising dramatically and many Americans with the disease are unaware that they have it. Diabetes follows a disease progression from onset to death that includes five major complications: nephropathy, neuropathy, retinopathy, cardiovascular disease and stroke. This progression can be prevented through appropriate disease management. Step 1. Select all survey respondents in MEPS who did not miss a trip to the doctor due to transportation problems and who had health insurance during the entire year (2001). From this data, we isolate all patients with diabetes using ICD-9 code 250 (includes type 1 and 2). This process located 11,580,578individuals. Step 2. Review the characteristics of well- and poorly managed care through the literature. Well managed, for patients with Type 2 Diabetes, is defined as using insulin, metformin, or sulfonylurea therapy for intensive glycemic control (CDC Diabetes Cost-effectiveness Group, 2002). Patients need to have clinical indicators such as hemoglobin a1C levels within the appropriate ranges. Indicators should be monitored by a physician at least once every three months, or 4 times per year (American Diabetes Association , 2004). MEPS includes a question on whether the diabetic patient received a hemoglobin a1C test in the past year. Step 3. Isolate the well-managed patients (based on whether they received tests for hemoglobin a1C levels) and review their per capita cost of care. Diabetes is highly co-morbid with other health conditions of increasing severity, including hypertension, congestive heart failure, and renal diseases. Thus, we will follow the process used for hypertension that examines the difference of all-inclusive average total costs, between well and poorly managed diabetic patients, to do the cost- effectiveness analysis of providing NEMT. These patients represent the expected costs for well-managed patients with transportation deficiencies addressed. Poorly managed patients have a diagnosis of diabetes and do not have appointments to monitor glucose levels, or take medications to control diabetes. These costs are summarized in Table 7-20. Table 7-20: Cost Comparison of Diabetes Patients in MEPS (2001) Per Capita Population Unweighted Frequency Inpatient Costs ER Costs Outpatient Costs Rx Costs Office Based Cost Diabetes Costs (Mean) Diabetes Costs (Median) Total Costs (Mean) Total Costs (Median) Entire Diabetes Population 1,555 $579 $55 $85 $759 $349 $1,827 $808 $8,070 $3,403 Transportation- Advantaged / Insured Diabetes Population 1,393 $449 $48 $90 $768 $352 $1,708 $818 $8,155 $3,539 Poorly Managed 648 $640 $81 $128 $592 $303 $1,745 $687 $9,034 $3,484 Well Managed 745 $286 $21 $58 $918 $393 $1,676 $912 $7,407 $3,560 Difference Between Poorly and Well-Managed Care: $68 ($224) $1,626 ($76) Final Report 73

Step 4. Determine the compliance factor(s) from the literature. 12% of patients missed 30% of their glycemic control appointments (Karter et al., 2004). 14.7% of patients didn’t get regular exercise to manage their diabetes because of transportation (Jorgensen et al., 2002). Of patients with diabetes admitted for cardiovascular treatment, 8% did not have a physician who monitored their conditions (Bethel et al., 2004). Compliance, therefore, ranges from 85.3% to 92%. Step 5. Determine from the literature review how many visits or trips per capita per year are required to manage a patient with diabetes. Well-managed diabetes requires at least 4 appointments a year (American Diabetes Association, 2004). Step 6. Use the Medicare Fee Schedule cost weights to determine the average medical cost of the required visits. For this analysis we are use an estimate equal to $52.68 for a standard physician visit and $120.14 for an endocrinology specialist visit. We assume that half the diabetes visits will be with a specialist. Step 7. Determine the cost of a trip. This cost depends on rural or urban location and whether the patient is mobile or requires a modified vehicle for travel. These estimates were derived in Chapter 5 and, along with medical costs, whether specialist or primary care, are summarized in Table 7-21. Table 7-21: Calculation of NEMT Cost for Diabetes Transit Cost Scenario Average Round Trip Cost Primary Care Visit Cost Specialist Visit Cost Trips for Diabetes (Primary Care) Trips for Diabetes (Specialist) Total Trip Cost Low $39.16 $52.68 $120.14 2 2 $502.28 Intermediate $42.37 $52.68 $120.14 2 2 $515.00 High $82.48 $52.68 $120.14 2 2 $675.56 Step 8. Incorporate quality of life adjustments so that the analysis will correspond to the QALY methodology. Well-managed patients with diabetes have a median QALY score of 0.73 as do the poorly managed patients. Therefore, no QALY adjustment has been made. The cost-effectiveness results for diabetes are presented in Table 7-22. We simplify the 6 possible combinations of results by showing 3 outcomes: • Best outcome – lowest transit cost and highest compliance • Worst outcome – highest transit cost and lowest compliance • Intermediate outcome – intermediate transit cost and mid range for compliance. The latter outcome produces our most likely estimate of $927 cost savings per person. Final Report 74

This highly cost-effective result is nevertheless based on a one-year analysis of the well and poorly managed as defined by the diabetes literature. This likely underestimates the long-term savings associated with better management of diabetes. Supporting this assumption are several diabetes interventions that have demonstrated cost-effectiveness in the literature. Screening and intervention for diabetic retinopathy for type 1 and 2 diabetic patients was $4,744 per QALY. For every dollar spent on care for diabetic pregnant women, there was a savings of $5.19. Screening to prevent nephropathy, and therefore ESRD, had a cost of $40,214 per QALY. Improved glycemic control for Type 1 diabetes had a cost of $22,933 per QALY and $18,360 per QALY for Type 2 diabetics (all costs in 1998 dollars) (Klonoff et al., 2000). The incremental cost-effectiveness ratio for intensive glycemic control is $41,384 per QALY. The ratio increased with the age at screening – from $9,614 for patients aged 25-34 and $2.1 million for patients age 85-94 (CDC Diabetes Cost-effectiveness Group, 2002). Table 7-22: Cost-Effectiveness Results for Diabetes NEMT Compliance Factor Poorly Minus Well Mean Total Cost per Capita Adjusted Cost Difference Travel & Medical Cost Annual Net Change in Costs QALY Adjustment QALY- Adjusted Cost Savings Combined Scenario (1) (2) (1)*(2) = (3) (4) (3)-(4) = (5) (6) (5)*(6) Low Transit $, Best Compliance 92% $1,626.41 $1,496.30 $505.28 $994.02 100% $994 High Transit $, Worst Compliance 85.3% $1,626.41 $1,387.33 $675.56 $717.77 100% $712 Intermediate Transit $, Mid Compliance 88.7% $1,626.41 $1,441.81 $515.00 $926.81 100% $927 7.2.6 Depression/Mental Health Depression in the community has a lifetime prevalence of 4.9% to 17.1%, and a 12- month prevalence of 5.2 to 7.6% (Pignone et al., 2002b; Kessler et al., 2003b). Conducting this case study is made difficult by the variety of diseases falling under the umbrella mental health condition, the inherent ambiguity of designating the set of relevant individuals (and dividing them into well and poorly managed), and the large range of effective (and ineffective) treatments. Nevertheless, the 2002 NHIS identified as much as 50% of our target population who suffer from depression and there are care guidelines for depression that can resolve symptoms (Harman et al., 2004). We believe there is strong evidence that enhanced NEMT can have a profound effect on patients with this disease. Step 1. Select all survey respondents in MEPS who did not miss a trip to the doctor due to transportation problems and who had health insurance during the entire year (2001). From this data, we isolate all patients with depression using ICD-9 codes Final Report 75

296.2-296.8 (affective psychoses) or 311 (depressive disorder). This process located 12,201,518 individuals. Step 2. Review the characteristics of well- and poorly managed depression care through the literature. Well managed patients with depression have at least 4 outpatient visits with any type of provider (primary care or specialist) for pharmacotherapy (antidepressant or mood stabilizers) that lasted at least 30 days; and/or at least 8 outpatient visits that last at least 30 minutes with a mental health psychotherapy provider (Kessler et al., 2003b). Twenty psychotherapy visits for mental healthcare are covered under typical managed care insurance (Simon et al., 2001). Appropriate medications for the treatment of depression include the following: SSRI, TCA, serotonin norepinephrine reuptake inhibitor [SNRI], norepinephrine reuptake inhibitor [NRI], or dopamine agonist [DA] (Care Management Institute, 2004). Step 3. Isolate the well-managed patients (based on the use of the medications or visits specified in Step 2) and review their per capita cost of care. These patients represent the expected costs for well-managed patients with transportation deficiencies addressed. Depressed patients incur significant medical costs and have high rates of co-morbidity that decrease with sufficient treatment of depression, so it is important to determine the difference between total health care costs, not just those attributable to mental health (Kessler et al., 2003b). Costs attributable to depression for the relevant population are summarized in Table 7-23. Table 7-23: Depression Only Cost Comparison for Depression Patients in MEPS (2001) Per Capita Population Unweighted Frequency Inpatient Costs ER Costs Outpatient Costs Rx Costs Office Based Cost Total Costs (Mean) Total Costs (Median) Entire Depression Population 1,427 $408 $7 $38 $590 $354 $1,397 $534 Transportation-Advantaged / Insured Depression Population 1,264 $382 $7 $40 $604 $354 $1,387 $565 Poorly Managed 976 $195 $4 $6 $443 $159 $808 $382 Well Managed 288 $1,006 $17 $154 $1,141 $1,008 $3,326 $1,570 Difference Between Poorly and Well-Managed Care: ($2,519) ($1,187) Total healthcare costs for these same patients are presented in Table 7-24. The average total healthcare cost for depressed patients will be used to calculate the cost difference between well and poorly managed patients. This follows the same rationale presented in Section 7.2.4 in that we want to retain the costs of the most ill depressed patients in our analysis of total costs. Though the literature contains evidence that depression management is cost-effective, the one-year, poor and well-managed utilization costs in MEPS do not show this. In fact, well-managed patients are fewer and much more costly, suggesting that the screen determined in Step 2 is flawed, or it is telling us that to manage patients well in a given year requires additional expenditures. A possible explanation is the likelihood that our MEPS sample includes a high proportion of very mild depression Final Report 76

cases that confound the true costs of poorly managed, severely depressed patients. If mildly depressed survey respondents indicate that they have depression, yet do not require and therefore do not receive much medication or many visits to treat their depression, the screen we apply will categorize them as poorly managed, despite the fact that their management is appropriate. MEPS does not include parameters to measure disease severity, which would help to determine whether this hypothesis is correct. Without an accurate measure of the true costs of poorly managed depression cases, this analysis is useful to the extent that we consider the value of higher quality of life. Table 7-24: Total Healthcare Cost Comparison for Depression Patients in MEPS (2001) Population Total Per Capita Costs (Mean) Total Per Capita Costs (Median) Entire Depression Population $6,549 $3,106 Transportation Advantaged / Insured Depression Population $6,793 $3,263 Poorly Managed Transportation Advantaged / Insured Population $6,510 $2,886 Well Managed Transportation Advantaged / Insured Population $7,739 $4,359 Difference Between Poorly and Well-Managed Care: ($1,229) ($1,473) Step 4. Determine the compliance factor(s) from the literature. Depression is largely undetected in the primary care setting – some 30 to 50% of cases are missed. With usual care, 66% of patients remain depressed, 35% of depressed patients can be expected to resolve without treatment and 50% of patients who are treated will recover fully (Pignone et al., 2002b). 21.7% of individuals with depression in the community are adequately treated over a 12-month interval (Kessler et al., 2003b). For this analysis, we use a compliance range of 22% to 50%. Step 5. Determine from the literature review how many visits or trips per capita per year are required to manage a patient with depression. Well-managed depression requires at least 4 visits with a primary care physician (low estimate) or 8 visits (high estimate) with a mental health specialist over one year (Kessler et al., 2003b). Step 6. Use the Medicare Fee Schedule cost weights to determine the average medical cost of the required visits. For this analysis we use an estimate equal to $52.68 for a standard physician visit and $120.14 for a clinical psychiatrist visit. Step 7. Determine the cost of a trip. This cost depends on rural or urban location and whether the patient is mobile or requires a modified vehicle for travel. These estimates were derived in Chapter 5 and, along with medical costs, whether specialist or primary care, are summarized in Table 7-25. Final Report 77

Table 7-25: Calculation of NEMT Cost for Depression Transit Cost Scenario Average Round Trip Cost Primary Care Visit Cost Specialist Visit Cost Total Trip Cost (Low Estimate= 4 visits to PCP) Total Trip Cost (High Estimate= 8 visits to Specialist) Low $39.16 $52.68 $120.14 $367.36 $1,274.40 Intermediate $42.34 $52.68 $120.14 $380.08 $1,299.84 High $82.48 $52.68 $120.14 $540.64 $1,620.96 Step 8. Incorporate quality of life adjustments so that the analysis will correspond to the QALY methodology. Well-managed patients with depression report a QALY score of 0.73 as do poorly managed patients in MEPS. Thus, there is no change in quality of life for better depression management as we have defined it in this analysis. Further analysis into separating patients into well and poorly managed using disease severity will likely alter these results. Nevertheless, a special comparison of patients with depression between transportation-disadvantaged or uninsured, and no transportation difficulties and insured, shows a mean quality differential of 24.0% and a median change of 17.7%. While this approach differs from that used above, it can be justified in that the well v. poor management split is confounding a clear quality discrepancy – individuals with better access to care (regarding transportation and insurance) exhibit much higher quality scores. The cost-effectiveness results for depression, using total health care costs, are presented in Table 7-26. While there are 24 possible combinations of results (3 transit costs * 2 compliance rates * 2 trip amounts * 2 QALY levels), we simplify the presentation by showing 3 outcomes: • Best outcome – lowest transit cost, highest compliance, lowest visits, high QALY improvement • Worst outcome – highest transit cost, lowest compliance, most visits, low QALY improvement • Intermediate outcome – intermediate transit cost, mid range for compliance, a most likely visit count, low QALY improvement. The latter outcome produces our most likely estimate of $675 additional costs per person, which given the $50,000 convention, is highly cost-effective. Final Report 78

Table 7-26: Cost-Effectiveness Results for Depression NEMT Compliance Factor Poorly Minus Well Mean Total Cost per Capita Adjusted Cost Difference Travel & Medical Cost Annual Net Change in Costs QALY Adjustment QALY- Adjusted Cost Savings Combined Scenario (1) (2) (1)*(2) = (3) (4) (3)-(4) = (5) (6) (5)*(6) Low Transit $, Best Compliance, Fewest Trips, High QALY 50% $(1,228.97) $(614.49) $367.36 $(981.852) 124.0% $(746) High Transit $, Worst Compliance, Most Trips, Low QALY 22% $(1,228.97) $(266.69) $1,620.96 $(1,887.65) 117.7% $(1,554) Intermediate Transit $, Mid Compliance, Likely Trips, Low QALY 36% $(1,228.97) $(440.59) $380.08 $(820.67) 117.7% $(675) 7.2.7 End-Stage Renal Disease End-stage renal disease (ESRD) is relatively uncommon in the population yet consumes a great deal of healthcare resources. ESRD patients have kidney failure that requires dialysis for maintenance or kidney transplantation for treatment. Many ESRD patients are also hypertensive and/or diabetic. ESRD presents a unique challenge in applying the cost-effectiveness methodology developed for this project. Patients with ESRD depend on dialysis for survival such that classification of patients into well or poorly managed categories is relatively impossible. ESRD patients that are poorly managed and therefore do not receive the necessary medical treatment for their condition are certain of renal failure and subsequent death. In order to evaluate the impact of NEMT on a population with chronic renal failure, we conducted the cost-effectiveness analysis from the perspective of preventing delays in access to a specialist who can manage pre- dialysis ESRD patients, and improve their overall care. Step 1. Select all survey respondents in MEPS who did not miss a trip to the doctor due to transportation problems and who had health insurance during the entire year (2001). From this data, we isolate all patients with ESRD as determined using ICD-9 codes 584 and 585 for acute and chronic renal failure and 586 for unspecified renal failure. This process located 221,195 individuals. Step 2. Review the characteristics of well- and poorly managed care through the literature. For ESRD, poorly managed care is defined as beginning dialysis within 4 months of visiting a nephrologist. Well-managed care is defined as having a period longer than 4 months between seeing a nephrologists and commencing dialysis (Obrador et al., 1998; Kinchen et al., 2002). Step 3. Isolate the well-managed patients (based on use of the medications specified in Step 2) and review their per capita cost of care. The MEPS data does not include Final Report 79

information on whether dialysis was delayed, so categorizing well and poorly managed ESRD patients within MEPS is not possible. Instead, we apply the estimate of cost savings avoided from the literature to the cost of ESRD. Patients commencing dialysis within 6 months of referral to a nephrologist had an average of 30 inpatient days per year compared to 8 days for those patients being specialist care earlier. Similarly, 70% of late-referred ESRD patients had serious medical complications, compared to 9% of ESRD patients initiating dialysis at an appropriate time. Finally, late-referred ESRD patients were much more likely to die within the first year of dialysis and to be excluded from kidney transplant waiting lists (Jungers, 2002; Obrador et al., 1998; Arora et al., 2000; Kessler et al., 2003a; Manns et al., 2003). The literature further suggests that up to 10% of the burden of dialysis could be avoided through early referral to a nephrologist (Jungers, 2002). The cost of ESRD is presented in Table 7-27. Table 7-27: Cost of ESRD in MEPS (2001) Per Capita Population Unweighted Frequency Inpatient Costs ER Costs Outpatient Costs Rx Costs Office Based Cost Total Costs (Mean) Total Costs (Median) Entire ESRD Population 34 $3,134 $176 $7,933 $536 $7,477 $19,255 $17,068 Step 4. Determine the compliance factor(s) from the literature. Late referral for ESRD patients can be due to either asymptomatic renal disease, a noncompliant primary care physician that does not make the referral, or a noncompliant patient that does not attend a specialist visit. In previous studies, 56% of late-referred ESRD patients were either asymptomatic or noncompliant (Obrador et al., 1998). Thus, the compliance factor for pre-dialysis ESRD visits is 44%. Step 5. Determine from the literature review how many visits or trips per capita per year are required to manage a patient with ESRD. For ESRD, well-managed care involves five or more office visits per year with a nephrologist (Avorn et al., 2002). Step 6. Use the Medicare Fee Schedule cost weights to determine the average medical cost of the required visits. For this analysis we use an estimate equal to $120.14 for a nephrology specialist visit. Step 7. Determine the cost of a trip. This cost depends on rural or urban location and whether the patient is mobile or requires a modified vehicle for travel. These estimates were derived in Chapter 5 and, along with medical costs, are summarized in Table 7-28. Final Report 80

Table 7-28: Calculation of NEMT Cost for ESRD Transit Cost Scenario Average Round Trip Cost Visit Cost Trips for ESRD (Low Estimate) Trips for ESRD (High Estimate) Total Trip Cost (Low Estimate) Total Trip Cost (High Estimate) Low $44.78 $120.14 5 10 $824.60 $1,649.20 Intermediate $45.74 $120.14 5 10 $829.40 $1,658.80 High $84.40 $120.14 5 10 $1,022.70 $2,045.40 Step 8. Incorporate quality of life adjustments so that the analysis will correspond to the QALY methodology. ESRD QALY scores are low, which is consistent with the literature. Because we do not have a comparison of the QALY scores for patients who were referred late to a nephrologist, we will use the higher risk of early mortality. Late referral to a nephrologist increased the risk of death by a factor of five compared to patients with an early referral (Kessler et al., 2003a). These results are presented in Table 7-29. We simplify the 6 possible combinations of results by showing 3 outcomes: • Best outcome – lowest transit cost and fewest visits • Worst outcome – highest transit cost and most visits • Intermediate outcome – intermediate transit cost and mid range for visits (7). The latter outcome produces our most likely estimate of $410 additional costs per person, which given the $50,000 cost per QALY convention, is highly cost-effective to secure timely access to a nephrologist for ESRD patients. Table 7-29: Cost-Effectiveness Results for ESRD NEMT Compliance Factor ESRD Cost Savings for Early Nephrologist Visit Adjusted Cost Difference Travel & Medical Cost Net Change in Costs Combined Scenario (1) (2) (1)*(2) = (3) (4) (3)-(4) = (5) Low Transit $, Fewest Trips 44% $1,706.70 $750.95 $824.60 ($74) High Transit $, Most Trips 44% $1,706.70 $750.95 $2,045.40 ($1,294) Intermediate Transit $, Likely Trips 44% $1,706.70 $750.95 $1,161.16 ($410) Final Report 81

7.3 Summary and Discussion The above sections describe each of 12 cost-effectiveness analyses in detail. In the following sections, we briefly address all 12 at once. While literally aggregating the results is problematic and involves no end of comparing apples to oranges, we instead attempt to provide a qualitative aggregation of the 12 analyses. 7.3.1 Summary of Condition Analyses Table 7-30 summarizes the condition specific results with the intermediate, most- likely estimate shown as the cost-effectiveness result. All twelve conditions are cost- effective, and four of the results are actually cost saving. Based on the rule of thumb of one QALY worth about $50,000, none of the conditions that we analyzed failed the test of cost-effectiveness. Hypertension, for example, shows a mere increase in net costs of $6 per QALY (well within the noise of being cost saving), and the least cost-effective condition (breast cancer screening) still comes in at significantly less than $50,000 net cost. Table 7-30: Summary of Condition-Specific Cost-Effectiveness Results Condition Type Cost per QALY Result Influenza Vaccinations Preventive $31 / QALY Highly Cost-Effective Prenatal Care Preventive $367 Cost Saving Cost Saving Breast Cancer Screening Preventive $34,176 / QALY Moderately Cost-Effective Colorectal Cancer Screening Preventive $22,735 / QALY Moderately Cost-Effective Dental Care Preventive $590 / QALY Highly Cost-Effective Asthma Chronic $333 Cost Saving Cost Saving Heart Disease (Congestive Heart Failure, CHF) Chronic $2,743 Cost Saving Cost Saving Chronic Obstructive Pulmonary Disease (COPD) Chronic $1,272 / QALY Highly Cost-Effective Hypertension (HTN) Chronic $6 / QALY Highly Cost-Effective Diabetes Chronic $927 Cost Saving Cost Saving Depression / Mental Health Chronic $675 / QALY Highly Cost-Effective End-Stage Renal Disease (ESRD) Chronic $410 / QALY Highly Cost-Effective 7.3.2 Discussion We have identified cases in MEPS by virtue of expenditures linked to that disease. This process is logical given a focus on actual healthcare costs. However, it does result in omitting individuals with chronic conditions who, for whatever reason, do not incur disease-related healthcare expenditures in that year. This most likely adds another conservative factor to our methods and overall results. That is, the cost differential between well and poorly managed would be even greater, thus enhancing any cost saving results, or lowering any additional costs from enhanced transportation. We did not update the costs and benefits to inflate the figures to 2005. In light of the illustrative nature of our findings, we do not believe this added detail is necessary. We expect that inflated figures would boost cost-effectiveness. Final Report 82

As described in Chapter 6 and Appendix C, healthcare improvements are worth an investment when the cost is reasonable in light of mortality and morbidity improvements. Thus, while cost savings are clearly the best outcome, the normal expectation is for cost increasing investments that are nevertheless judged to be cost- effective. Such are the results for the eight cases that are not estimated to be cost saving. These results may be aggregated but caution should prevail. First, an accurate population count is needed. This is best seen as the number of individuals with transportation difficulties suffering from each condition. Given a low sample size for the transportation-disadvantaged population as a whole, deriving reliable condition- specific counts may be problematic. Even with accurate counts, aggregating benefits across diseases runs the risk of duplicating benefits because of multiple conditions suffered by these individuals. Because of such concerns, the Spreadsheet Tool, described in Chapter 8, is that much more valuable to accommodate regional and local issues, including population figures, disease condition prevalence, and regional transportation and healthcare costs. Final Report 83