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PM-O5 Assessing the Economic Impact of Case Management on Diabetics in a Commercially Insured Population, 2004.

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- 1. PM-O5 Assessing the Economic Impact of Case Management on Diabetics in a Commercially Insured Population Felix J. Bradbury, RN, MHA, ScD*, CHE Blue Cross Blue Shield of Louisiana 2004
- 2. AGENDA <ul><li>Background and Introduction </li></ul><ul><li>A Few Definitions… </li></ul><ul><li>The BCBSLA Population </li></ul><ul><li>What is the ROI for the Various Departments within Medical Management? </li></ul><ul><li>What is the cost-benefit of case management activities for diabetic members? </li></ul><ul><li>How can we model the cost-benefit for the long-term savings associated with case management activities? </li></ul>
- 3. The Three Questions We’re Working to Answer : <ul><li>Q1: What is the ROI for the various departments within Medical Management? </li></ul><ul><li>Q2: What s the cost-benefit of case management activities for diabetic members over the short-term period of a single year? </li></ul><ul><li>Q3: How can we model the cost-benefit for the long-term savings associated with case management activities? </li></ul>
- 4. A Few Definitions… <ul><li>Cost-benefit analysis: An economic evaluation method for determining whether or not an intervention or program is worth doing. The basic approach is to measure all relevant costs and benefits and determine the ratio between the two. In cost-benefit analysis, both costs and benefits are expressed in terms of dollars. </li></ul><ul><li>Cost-effectiveness analysis: An economic evaluation method in which costs are expressed in terms of dollars but benefits, or consequences, are generally expressed in non-dollar terms, i.e., QALYS, life-years gained per dollar spent, reduction in ALOS/dollar spent, etc </li></ul><ul><li>Cost-minimization analysis: An economic evaluation method in which the goal is a search for the least-costly alternative that yields equivalent – or better – results when compared to all other alternatives. </li></ul>
- 5. BCBSLA Population (Q1-2004 Membership) <ul><li>-Commercially insured population </li></ul><ul><li>-No Medicare primary </li></ul><ul><li>-No Medicaid members </li></ul><ul><li>-Large individual underwritten book of business </li></ul><ul><li>-Significant number of small self funded accounts </li></ul><ul><li>-277,324 members – MBA members - are excluded from analysis because they did not fall within the control of care management and case management programs for one or more of the following reasons: </li></ul><ul><ul><li>they do not reside in Louisiana, </li></ul></ul><ul><ul><li>are over 65 and receive their healthcare benefits through Medicare Part A and B, </li></ul></ul><ul><ul><li>hold a policy with very limited benefits, i.e., dental only, or life-insurance only benefits. </li></ul></ul>
- 6. QUESTION 1: What is the ROI for the Various Departments within Medical Management?
- 7. Summary of Medical Management Cost Savings, 2003 Medical management cost-savings are generated via a combination of the following activities: ( Note that cost savings due to non-certified days and changes in level of care (LOC) are based on per diem reimbursement. Case rates and DRG rates are not included in the current cost savings methodology.) -Changes in level of care, i.e., acute day to sub-acute day using M&R criteria and directly attributable to care management activities. -Non-certified care, i.e., denied days or services because of lack of medical necessity or pre-existing condition. Any admission day this was subsequently denied. Non-certification days may be applied to acute care, rehabilitation, SNF, LTAC, home health or hospice rates -Medical policy review, i.e., denial based on experimental or investigational procedures, or therapeutics. -Pharmacy benefit management, i.e., increasing generic utilization relative to brand utilization and leveraging pharmacy tiers.
- 8. Examples of Cost Savings from LOC Changes or Non-Certified Care in Per Diem Facilities Cost-savings are calculated by subtracting the median value for a lower level of care from the median value for a higher level of care. For example, the median allowed amount for a SNF day is $500/day; the median allowed amount for an acute day is $1,592.50. The difference between $1,592.50 and $500 is the cost savings. In this example, the cost savings for this change in level-of-care is $1,092.50 per change in level-of-care. All cost-saving estimates are based on the median allowed dollars. Median values across levels-of-care were used to generate estimated reimbursement amounts; median values were used in lieu of averages because the former is less susceptible to the influences of outlier values.
- 9. Medical Management Cost-Savings Model Assumptions <ul><li>Model reflects cost-savings which are the direct result of activities conducted by medical management staff. </li></ul><ul><li>All financial calculations are hard-dollar estimates. </li></ul><ul><li>Cost-savings estimates are based on the median allowed amounts across all products and lines of business </li></ul><ul><li>Because the number of actual days a member will be in the hospital is not known until the member has actually incurred the days, it is impossible to estimate all of the days saved. </li></ul><ul><li>One day per member per non-certification of level-of-care change is assumed. This results in conservative cost-savings estimates. </li></ul>
- 10. QUESTION 2: What is the Cost-Benefit of Case Management Activities for Diabetic Members Over the Short-term Period of a Single Year?
- 11. What are We Attempting to Demonstrate? <ul><li>Does the incremental cost-benefit associated with case management mean it’s a program worth doing? </li></ul><ul><li>Short-term savings <= 1 year </li></ul><ul><li>Long-term savings > 1 year </li></ul>
- 12. The Impact of Diabetes in Louisiana <ul><li>According to the Louisiana State Office of Public (OPH), diabetes affects an estimated 7.6 percent of Louisiana’s 4,496,334 citizens – over 301,254 people as of 2003. OPH also estimates the direct and indirect costs of diabetes in Louisiana - considered a conservative estimate given that approximately one third of all diabetics are undiagnosed - to be over $2.2 billion as of 1997. Unfortunately, these costs extend well beyond the enormous economic burden. In 2000, Louisiana had the highest death rate in the nation due to diabetes with a mortality rate of 42.2 per 100,000 population. The Centers for Disease Control and Prevention (CDC) ranks diabetes as the primary cause of blindness in adults aged 20 to 74 as well as the most common cause of non-traumatic amputations and end stage renal disease. </li></ul>
- 13. Diabetes and Case Management in a Commercially-Insured population <ul><li>Diabetes imposes a significant economic burden to Louisiana residents. </li></ul><ul><li>There are approximately 19,783 diagnosed diabetics out of a population of 625,484 managed members – this is approximately 3.2 percent of the BCBSLA managed membership as of the first quarter of 2004. </li></ul><ul><li>Of these 19,783 diabetics, an average census of approximately 80 diabetics are actively enrolled in diabetes case management programs on a monthly basis with a enrollment period of 60 to 90 days; this average includes both newly diagnosed and previously enrolled diabetics. </li></ul><ul><li>The average annual per capita cost for diabetic members across all lines of business for 2003 was ~ $10,798.97, sd = $28,391.01. This cost includes all inpatient, outpatient, professional and pharmacy costs. </li></ul><ul><li>The annualized costs for case managed diabetics is $26,178.53, sd = $54,377.93. </li></ul><ul><li>The annualized costs for diabetics not enrolled in case management $9,741.553, sd = $25,319.6 </li></ul><ul><li>The incremental difference between members enrolled and not enrolled is </li></ul><ul><li>$9,741.553 - $26,178.53 = -$16,436.96, sd = $39,848. </li></ul><ul><li>N = 1,920 members for the two year study period in question. </li></ul>Note: Historical costs are simply annualized costs and represent the sum of all allowed medical and pharmacy costs for a member observed during the 12-month period. These allowed costs are computed as the total allowed PMPM cost multiplied by 12.
- 14. The Basic Methodologies for Looking at Short-Term and Long-Term Savings <ul><li>Retrospective (case-control) study design used for short-term (time<=1 year) savings. </li></ul><ul><ul><li>Administrative claims cost data are used to compare the health care costs associated with two groups of diabetics: </li></ul></ul><ul><ul><ul><li>Diabetics enrolled in case management (Cases), and </li></ul></ul></ul><ul><ul><ul><li>Diabetics not enrolled in case management </li></ul></ul></ul><ul><li>Markov cohort simulation model for long-term savings (time>1 year) with input from claims data, predictive model, and literature reviews. </li></ul>
- 15. The Basic Model
- 16. The Retrospective (Case-Control) Study Design <ul><li>Months </li></ul><ul><li>Timeline: 1 2 3 4 5 6….//……….……24 Today </li></ul><ul><li>Cases: 0 X 0 X 0 X 0 X 0 X 0 X Today </li></ul><ul><li>……………………………………………………………… </li></ul><ul><li>Controls: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Today </li></ul>Notes: The “0s” represent observations on the dependent variable, in this case the average allowed costs for diabetic members each month within each of the two groups, and the “Xs” represent interventions from case management. The dotted lines indicate the study participants are not randomly selected but are assigned to either case group or a control group depending on whether or not they elected to participate in a case management program, i.e., the members are self-selecting. Self-selection may be controlled for using the Heckman approach to self-selection bias, i.e., the Heckman two-step consistent estimator for modeling with censored data.
- 17. Why a Retrospective Study Design? <ul><li>The advantages of case-control studies include the following attributes: </li></ul><ul><ul><li>Relatively quick and inexpensive as compared to cohort study designs. </li></ul></ul><ul><ul><li>Generally support causality by establishing associations between dependent and independent variables </li></ul></ul><ul><ul><li>Historical data are often available from either administrative databases or clinical records so secondary analyses are easily performed without having to obtain more information from the cases or controls. </li></ul></ul><ul><ul><li>The sample size requirements needed to test hypotheses of association are generally smaller than the sample sizes need for more robust designs such as cross-sectional and cohort designs. </li></ul></ul>
- 18. Study Design, Continued <ul><li>Cases are defined as plan members diagnosed with either Type I or Type II diabetes – with or without comorbid conditions - and who have been actively enrolled in the plan’s case management program for diabetes at any point between January 1, 2002 and December 31, 2003. </li></ul><ul><li>The control group consists of plan members – with or without comorbid conditions - diagnosed with Type I or Type II diabetes and who did not participate in the plan’s case management program for diabetes during the same calendar year. Reasons for non-participation include: </li></ul><ul><ul><li>Unable to contact member because of incorrect contact information or member moved </li></ul></ul><ul><ul><li>Member declined to enroll </li></ul></ul>
- 19. The CRMS Data <ul><ul><li>ICD-9-CM codes in the 2500-2500.x code range, This definition includes Type I and Type II diabetes as well as any co-morbid conditions that may associated with diabetes. </li></ul></ul><ul><ul><li>ETGs: </li></ul></ul><ul><ul><ul><li>Insulin dependent diabetes, w/o comorbidity </li></ul></ul></ul><ul><ul><ul><li>Insulin dependent diabetes, with comorbidity </li></ul></ul></ul><ul><ul><ul><li>Non-insulin dependent diabetes, w/o comorbidity </li></ul></ul></ul><ul><ul><ul><li>Non-insulin dependent diabetes, with comorbidity </li></ul></ul></ul><ul><ul><li>Comorbidities: ICD-9 CM codes for the most common comorbid conditions associated with diabetes were included in the analysis and include: </li></ul></ul><ul><ul><ul><li>cardiovascular disease, </li></ul></ul></ul><ul><ul><ul><li>hypertension, </li></ul></ul></ul><ul><ul><ul><li>septicemia, </li></ul></ul></ul><ul><ul><ul><li>bacteremia, </li></ul></ul></ul><ul><ul><ul><li>hyperosmolarity, </li></ul></ul></ul><ul><ul><ul><li>nephropathy, </li></ul></ul></ul><ul><ul><ul><li>neuropathy, and </li></ul></ul></ul><ul><ul><ul><li>retinopathy. </li></ul></ul></ul><ul><ul><li>Note: BCBSLA Case Management interventional processes for diabetes do not distinguish between Type I and Type II diabetics so no distinction is made in the analysis. Comorbidities were identified via peer reviewed research literature. </li></ul></ul>
- 20. An Example of the Data
- 21. What Do We Hope to See? 1500 Estimated Savings in Dollars 2.6 2.8 3 3.2 3.4 RR Score 0 5 10 15 Time Period (Months) Baseline Score Observed_RR_Score Savings Source: Blue Cross Blue Shield of Louisiana, MMRD, 2003 N=2,500 active members from January 1-December 31, 2003 Hypothetical ROI Analysis for High-Risk Members 0 500 1000
- 22. The Math Model <ul><li>Using ordinary least squares regression models to compare the total allowed dollars per year between the cases (enrolled) and controls (not enrolled) after adjusting for: </li></ul><ul><li>Age (excludes Medicare primary) </li></ul><ul><li>Sex </li></ul><ul><li>Number of comorbid conditions </li></ul><ul><li>Differences in benefits design </li></ul><ul><li>Length of time enrolled as BCBSLA member </li></ul><ul><li>Enrolled or not enrolled in case management </li></ul><ul><li>Case management severity (moderate high) </li></ul><ul><li>SES – using zip code data </li></ul><ul><li>Self-selection bias </li></ul>
- 23. Summary Statistics for CM Enrolled vs. Not Enrolled Claims paid or incurred between August 2003 and July 2004 Members enrolled in CM at any time during study period <ul><li>Enrolled variable | N mean sd cv </li></ul><ul><li>----------------------+------------------------------------- </li></ul><ul><li>N Hx Cost| 15399.00 9741.55 25319.60 2.60 </li></ul><ul><li>----------------------+------------------------------------- </li></ul><ul><li>Y Hx Cost| 1058.00 26178.53 54377.93 2.08 </li></ul><ul><li>----------------------+------------------------------------- </li></ul><ul><li>Total Hx Cost| 16457.00 10798.27 28391.01 2.63 </li></ul><ul><li>------------------------------------------------------------ </li></ul>Hx costs are annualized costs and represent the sum of all medical and pharmacy costs for a member observed during the 12-month period. These costs are computed as the total allowed PMPM cost multiplied by 12. Data are age-sex adjusted using OLS regression. The CV is coefficient of variation and is calculated as the standard deviation divided by the mean and is another measure of variation.
- 24. Incremental Savings? <ul><li>Using CRMS data, the incremental difference between the allowed paid claims for diabetics enrolled in case management vs. diabetics not enrolled case management is: </li></ul><ul><li> $9,741.55 - $26,178.53= -$16,436.98/year/enrolled diabetic. </li></ul><ul><li>Diabetic members enrolled in case management appear to have significantly greater costs of health services including primary care and specialty care services after adjusting for age, sex, months enrolled and benefits design. </li></ul><ul><li>Why? </li></ul><ul><ul><li>Increased volume of PCP and specialist visits </li></ul></ul><ul><ul><li>Increased compliance </li></ul></ul><ul><ul><li>Increased use of meds and other treatment regimens </li></ul></ul><ul><li>Is there a long-term payoff? </li></ul>
- 25. Conclusions <ul><ul><li>Diabetic members in case management programs appear to be consuming greater healthcare resources in the short-term than members not enrolled in case management programs. What conclusions can we draw from this? </li></ul></ul><ul><ul><ul><li>Nothing yet – it is hoped that the greater short-term consumption will result in long-term savings, and improved quality of life, for case management enrolled members through: </li></ul></ul></ul><ul><ul><ul><ul><li>Reduced inpatient hospital admits </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Reduced ER utilization </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Reduced incidence and prevalence of ESRD </li></ul></ul></ul></ul>
- 26. QUESTION 3: How Can We Model the Cost-Benefit of the Long-term Savings Associated with Case Management Activities?
- 27. Markov Modeling and Cost Savings <ul><li>Markov analysis is a technique that deals with probabilities of future occurrences by analyzing presently known or estimated probabilities. </li></ul><ul><li>Well-regarded as a method for evaluating long-term cost-benefit when long-term data are limited or nonexistent. </li></ul><ul><li>Markov models are useful when the decision problem involves risk over time, and when events may happen more than once. There are four assumptions to the Markov process: </li></ul><ul><ul><li>There is a limited or finite number of possible states </li></ul></ul><ul><ul><li>The probability of changing states remains the same over time (stationary vs. non-stationary Markov models) </li></ul></ul><ul><ul><li>We can reasonably predict any future state from the previous state and the matrix of transition probabilities. </li></ul></ul><ul><ul><li>The size and the makeup of the system – for example the proportion of diabetics- does not change during the analysis. </li></ul></ul>
- 28. Markov Transition State Models for Diabetics Enrolled and Not Enrolled in Case Management Programs
- 29. Setting Up the Markov Model (Cohort Simulation model)
- 30. The Markov Model - Continued
- 32. QUESTION & ANSWER SESSION
- 33. Bibliography <ul><li>Albright, A. (2000) Enhancing diabetes care in a low-income high-risk population . JAMA. V. 283(4) pp. 467-468. </li></ul><ul><li>Allred, C.A.; Arford, P.H.; Michel, Y, et al (1995) A cost-effectiveness analysis of acute care case management outcomes . Nursing Economics, v. 13(3) pp 129-136. </li></ul><ul><li>Boulware, E.L.; Jarr, B.G.; Tarver-Carr, Michelle, E., et al (2003) Screening for proteinuria in US adults: A cost-effectiveness analysis . JAMA. v.290(23) pp 3101-3114. </li></ul><ul><li>Cavazzoni, P.; Mukhopadhyay, N.; Carlson, C. et al (2004 ) Retrospective analysis of risk factors in patients with treatment-emergent diabetes during clinical trials of antipsychotic medications . The British Journal of Psychiatry. V. 185(s47) pp s94-s101 . </li></ul><ul><li>Craig, J; Chua, R.; Russell, C., et al. (2000) The cost-effectiveness of teleneurology consultations for patients admitted to hospitals without neurologists on site. 1: A retrospective comparison of the case-mix and management at two rural hospitals . Journal of Telemedicine and Telecare. V. 6(1) pp 46-49. </li></ul><ul><li>Dawson, K.G.; Gomes, D.; Hertzel, G., et al (2002) The economic costs of diabetes in Canada . Diabetes Care. v.25(8), pp 1303-1307. </li></ul><ul><li>De Pablos-Velasco, P.L.; Martinez-Martin, F.J.; Rodrigues-Perez, F., et al (2001) Prevalence and determinants of diabetes mellitus and glucose intolerance in a Canarian caucasian population – comparison of the 1997 ADA and the 1985 WHO criteria. The Guia Study . Diabetic Medicine. v.18(3) p 235-244. </li></ul><ul><li>DeBusk, R.F.; Miller, N.H.; and West, J.A. (1999) Diabetes Case Management (letters) Annals of Internal Medicine, v. 130(10) p 863-4. </li></ul><ul><li>Del Prato, S.; Heine, R.J.; Keilson, L. (2003) Treatment of patients over 64 years of age with Type 2 diabetes: Experience from nateglinide pooled database retrospective analysis . V.26(7) pp 2075-2080. </li></ul><ul><li>Gordois, A.; Scuffham, P.; Shearer, A., et al (2003) The health care costs of diabetic peripheral neuropathy in the U.S. Diabetes Care. v.26(6), pp 1790-1795. </li></ul><ul><li>Gregory, N.; Glauber, H.; and Brown, J. (2000) Type 2 Diabetes: Incremental medical care costs during the 8 years preceding diagnosis . Diabetes Care. v.23(1), pp 1654-1659. </li></ul><ul><li>Haardt, M.J; Selam, J.L; Slama, G., et al (1994) A cost-benefit comparison of intensive diabetes management with implantable pumps versus multiple subcutaneous inections in patients with Type I diabetes . Diabetes Care, v.17(8) pp847-851. </li></ul><ul><li>Helen, L.; James, C.; Ghali, W., et al (2004) Detailed cost analysis of care for survivors of severe sepsis . V. 32(4) pp 981-985. </li></ul><ul><li>Herman, W.H.; Brandle, M.; Zhang, P., et al (2003) Costs associated with the primary prevention of type 2 diabetes mellitus in the diabetes prevention program . Diabetes Care. v. 26(1) pp 36-47. </li></ul><ul><li>Hogam, P.; Dall, T.; Nikolov, P., The Lewin Group (2002) Economic costs of diabetes in the U.S. in 2002. Diabetes Care. v.26(3), pp 917-932. </li></ul><ul><li>Jerrell, J.M., and Hu, T. (1989) Cost-effectiveness of intensive clinical case management compared with an existing system of care . Inquiry: Blue Cross Blue Shield Association, v.26, pp 224-234. </li></ul><ul><li>Johnston, S.; Salkeld, G.; Sanderson, K., st al (1998) Intensive case management: a cost-effectiveness analysis , Austrlian and New Zealand Journal of Psychiatry, v 32. pp 551-559. </li></ul>
- 34. Bibliography - Continued <ul><li>Karter, A.J.; Stevens, M.; Herman, W.H., et al (2003) Out-of-Pocket costs and diabetes preventive services: The translating research into action for diabetes (TRIAD) study . Diabetes Care. v. 26(8) pp 2294-2299. </li></ul><ul><li>Klonoff, D.C.; and Schwartz, D.M. (2000) An economic analysis of interventions for diabetes . Diabetes Care. V.23(3) pp. 390-404. </li></ul><ul><li>Long, M.J., and Stevenson, B.S. (2000) What price an additional day of life? A cost-effectiveness study of case management , v.6(8) pp 881-886. </li></ul><ul><li>Obrien, J.; Patrick, A.; Caro, J.J., et al; licensee BioMed Central Ltd. (2003) Costs of managing complications resulting from type 2 diabetes mellitus in Canada . BMC Health Services Research. 3(1) pp 7-22. </li></ul><ul><li>Ping, Z.; Engelgau, M.; Valdez, R., et al (2003) Costs of screening for pre-diabetes among U.S. adults: A comparison of different screening strategies . Diabetes Care. v.26(9), pp 2536-2542. </li></ul><ul><li>Polonsky, W.H.; Earles, J.; Smith, S. et al (2003 ) Integrating medical management with diabetes self-management training: A randomized control trial of the diabetes outpatient intensive treatment program . Diabetes Care. V. 26(1) pp 3048-3053. </li></ul><ul><li>Ramsey, Scott; Summer, Kent; Leong, Stephanie, et al (2002). Productivity and medical costs of diabetes in a large employer group. Diabetes Care. v.25(1), pp 23-29. </li></ul><ul><li>Ray, N.F.; Thaemer, M.; Gardner, M.P., et al (1998) Economic consequences of diabetes mellitus in the U.S. in 1997. Diabetes Care. v.21(2), pp 296-309. </li></ul><ul><li>Robinson, J.A.; Robinson, K.J., and Lewis, D.J. (1992) Balancing quality of care and cost-effectiveness through case management . ANNA Journal, v. 19(2) pp182-188. </li></ul><ul><li>Robinson, J.A; Robinson, J.K; and Lewis, D.J. (1992) Balancing quality of care and cost-effectiveness through case management . ANNA Journal. V.19(2) pp. 182-187. </li></ul><ul><li>Sikka, R; Waters, J; Moore, W; et al (1999) Renal assessment practices and the effect of nurse case management of health maintenance organization patients with diabetes . Diabetes Care. V. 22(1). pp. 1-6. </li></ul><ul><li>Warren, H.B.; Pulls, T., and Fogelstrom-DeZeeuw, P. (1996) Cost-effectiveness of case management: Experiences of a university managed health care organization . American Journal of Medical Quality, v. 11(4) pp173-178. </li></ul>
- 35. THE END

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