PM-O5 Assessing the Economic Impact of Case Management on Diabetics in a  Commercially Insured Population Felix J. Bradbur...
AGENDA <ul><li>Background and Introduction </li></ul><ul><li>A Few Definitions… </li></ul><ul><li>The BCBSLA Population </...
The Three Questions We’re Working to Answer : <ul><li>Q1: What is the ROI for the various departments within Medical Manag...
A Few Definitions… <ul><li>Cost-benefit analysis:  An economic evaluation method for determining whether or not an interve...
BCBSLA Population (Q1-2004 Membership) <ul><li>-Commercially insured population </li></ul><ul><li>-No Medicare primary </l...
QUESTION 1: What is the ROI for the Various Departments within  Medical Management?
Summary of Medical Management Cost Savings, 2003 Medical management cost-savings are generated via a combination of the fo...
Examples of Cost Savings from LOC Changes or Non-Certified Care in Per Diem Facilities Cost-savings are calculated by subt...
Medical Management  Cost-Savings Model Assumptions <ul><li>Model reflects cost-savings which are the direct result of acti...
QUESTION 2: What is the Cost-Benefit of Case Management Activities for Diabetic Members Over the Short-term Period of a Si...
What are We Attempting to Demonstrate? <ul><li>Does the incremental cost-benefit associated with case management mean it’s...
The Impact of Diabetes in Louisiana <ul><li>According to the Louisiana State Office of Public (OPH), diabetes affects an e...
Diabetes and Case Management in a Commercially-Insured population <ul><li>Diabetes imposes a significant economic burden t...
The Basic Methodologies for Looking at Short-Term and Long-Term Savings <ul><li>Retrospective (case-control) study design ...
The Basic Model
The Retrospective (Case-Control)  Study Design <ul><li>Months </li></ul><ul><li>Timeline: 1  2  3  4  5  6….//……….……24 Tod...
Why a Retrospective Study Design? <ul><li>The advantages of case-control studies include the  following attributes: </li><...
Study Design, Continued <ul><li>Cases are defined as plan members diagnosed with either Type I or Type II diabetes – with ...
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 diabet...
An Example of the Data
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) Baseli...
The Math Model <ul><li>Using ordinary least squares regression models to compare the total allowed dollars per year betwee...
Summary Statistics for CM Enrolled vs. Not Enrolled Claims paid or incurred between August 2003 and July 2004  Members enr...
Incremental Savings? <ul><li>Using CRMS data, the incremental difference between the allowed paid claims for diabetics enr...
Conclusions <ul><ul><li>Diabetic members in case management programs appear to be consuming greater healthcare resources i...
QUESTION 3: How Can We Model the Cost-Benefit of the Long-term Savings Associated with Case Management Activities?
Markov Modeling and Cost Savings <ul><li>Markov analysis is a technique that deals with probabilities of future occurrence...
Markov Transition State Models for Diabetics Enrolled and Not Enrolled in  Case Management Programs
Setting Up the Markov Model (Cohort Simulation model)
The Markov Model -  Continued
 
QUESTION &  ANSWER SESSION
Bibliography <ul><li>Albright, A. (2000)  Enhancing diabetes care in a low-income high-risk population .  JAMA. V. 283(4) ...
Bibliography - Continued <ul><li>Karter, A.J.; Stevens, M.; Herman, W.H., et al (2003)  Out-of-Pocket costs and diabetes p...
THE END
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Mckesson Payor Solutions Conference Presentation of Case Management, 2004

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Presentation by Felix Bradbury, RN, ScD, FACHE for Mckesson entitled
PM-O5 Assessing the Economic Impact of Case Management on Diabetics in a Commercially Insured Population, 2004.

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  • GOOD AFTERNOON HONORED COLLEAGUES - WELCOME TO PM 05 Assessing the Economic Impact of Case Management on Diabetics in a Commercially Insured Population – I’M DELIGHTED THAT THERE’S BEEN SUCH A TERRIFIC TURNOUT. MY NAME IS FELIX BRADBURY AND I’M THE DIRECTOR OF MMRD FOR BLUE CROSS AND BLUE SHIELD OF LOUISIANA. Louisiana is my home so I bid you welcome hope you enjoy your stay. AS A HOUSEKEEPING NOTE , I HAVE A LOT OF GROUND TO COVER IN THE NEXT HOUR SO PLEASE WRITE YOUR QUESTIONS DOWN AND HOLD THEM TO THE END OF THE PRESENTATION. I’VE ALLOWED 15-20 MINUTES TO ANSWER YOUR QUESTIONS. Before I begin I want to relate a story about cost-benefit and cost-savings that one of our case management nurses shared with me. She told me “See, if you don’t make us look good and we go away, then you have nothing to report on and you go away…” So I have a clear motive to make case management look good. THE PRIMARY PURPOSES OF THIS PRESENTATION ARE TO DISCUSS : Cost savings attributable to Medical management activities The economic impact of diabetes on the population Our method for evaluating the short term economic impact of case management on a diabetic population Present a Markov model for assessing the long-term economic impact of case management on a diabetic population. Where we are with the results The data I am going to discuss reflects our own data but I’ve altered the numbers a little bit to protect the innocent, or perhaps the guilty, whichever the case may be.
  • Background and Introduction Three Questions We’re Working to Answer A Few Definitions The BCBSLA Population The Economic Impact of Diabetes The CRMS Data Short-term savings – Medical Management Overall Medical Management Processes Estimates of Annual hard dollar savings for Medical Management Measuring the Impact of Case Management Short-term Impact Long-term savings estimates via Markov Models Most studies focus on cost-effectiveness. In contrast, my efforts at BCBSLA have focused on cost-benefit analysis and cost minimization analysis.
  • Q1: What is the ROI for the various departments within Medical Management? Q2: What s the cost-benefit of case management activities for diabetic members over the short-term period of a single year? Q3: How can we model the cost-benefit of the long-term savings associated with case management activities? One way in which the health plans are working to manage the costs associated with this costly and debilitating chronic condition is by implementing diabetes case management programs. These programs are designed to target members with diabetes and provide education and information to assist members with managing their condition. Case management programs are increasing in popularity throughout the United States among both health plans and employer groups. The former groups seek to use Case management programs to demonstrate the value add of their plan, while the latter seeks to use Case management programs as a tool to combat spiraling premium costs that result from, other factors, higher utilization of health care resources by members with chronic conditions such as diabetes. Both groups see these programs as the Holy Grail in controlling healthcare costs but no one has really worked to determine conclusively if there really is gold – in the form of hard-dollar savings - at the end of the Case management rainbow.
  • Without trying to be too academic, the following definitions are presented in order to get us all grounded in the same framework: 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. 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 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.
  • -Commercially insured population -No Medicare primary -No Medicaid members -Large individual underwritten book of business -Significant number of small self funded accounts -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: they do not reside in Louisiana, are over 65 and receive their healthcare benefits through Medicare Part A and B, hold a policy with very limited benefits, i.e., dental only, or life-insurance only benefits
  • QUESTION 1: What is the ROI for the Various Departments within Medical Management?
  • 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&amp;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.
  • 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.
  • Assumptions: Model reflects cost-savings which are the direct result of activities conducted by medical management staff. All financial calculations are hard-dollar estimates. Cost-savings estimates are based on the median allowed amounts across all products and lines of business 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. One day per member per non-certification of level-of-care change is assumed. This results in conservative cost-savings estimates.
  • QUESTION 2: What is the Cost-Benefit of Case Management Activities for Diabetic Members Over the Short-term Period of a Single Year?
  • What are We Attempting to Demonstrate? Does the incremental cost-benefit associated with case management mean it’s a program worth doing? Short-term savings &lt;= 1 year Long-term savings &gt; 1 year
  • The Impact of Diabetes in Louisiana 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.
  • Diabetes imposes a significant economic burden to Louisiana residents. 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. 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. 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. The annualized costs for case managed diabetics is $26,178.53, sd = $54,377.93. The annualized costs for diabetics not enrolled in case management $9,741.553, sd = $25,319.6 The incremental difference between members enrolled and not enrolled is $26,178.53 - $9,741.553 = $16,436.96, sd = $39,848. N = 1,920 members for the two year study period in question.
  • Retrospective (case-control) study design. The relative advantages of case-control studies include the following attributes: Case-control studies are relatively quick and inexpensive as compared to cohort study designs. Case-control studies tend to support causality by establishing associations between dependent and independent variables Historical data are often available from either administrative databases or clinical records so secondary analyses – analyses of existing data – are easily performed without having to obtain more information from the cases or controls. 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. The disadvantages of case-control studies include the following attributes: Potential for administrative or clinical data to be incomplete. The criteria used in the diagnoses of cases may not be the same among providers so that cases and controls are not homogeneous. The occurrence of the assumed antecedent (disease state or condition) in the history is obtained from selected cases and controls and is not randomized. Thus, the antecedents are not obtained from a universe of all antecedents, so one cannot know what the association would be for all or for a different representative sample of all people having the antecedent.
  • The above diagram shows the basic model which is under evaluation. The vertical dashed lines are a Visio thing that, while I trie repeatedly, was unable to remove. EXPLAIN DIAGRAM STARTING FROM TOP
  • This is a basic schematic of the retrospective study design: 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.
  • The advantages of case-control studies include the following attributes: Relatively quick and inexpensive as compared to cohort study designs. Generally support causality by establishing associations between dependent and independent variables 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. 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.
  • 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. 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: Unable to contact member because of incorrect contact information or member moved Member declined to enroll
  • CRMS DATA 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. ETGs: Insulin dependent diabetes, w/o comorbidity Insulin dependent diabetes, with comorbidity Non-insulin dependent diabetes, w/o comorbidity Non-insulin dependent diabetes, with comorbidity Comorbidities: ICD-9 CM codes for the most common comorbid conditions associated with diabetes were included in the analysis and include: cardiovascular disease, hypertension, septicemia, bacteremia, hyperosmolarity, nephropathy, neuropathy, and retinopathy.
  • This table shows the data used in this study. With the exception of the SES data from our Marketing Research area, all data was obtained from CRMS.
  • This is a slide from last year’s presentation on predictive modeling. In terms of our results, we’re not there yet. LAGNIAPE: THIS LAST SECTION PRESENTS ONE POSSIBLE METHODOLOGY FOR CALCULATING ROI. The above plot shows the change in RR score relative to baseline and estimated savings. If you know a member’s baseline RR Score and then track their RR score across time before and after their entry into Care Management, you can calculate the change in their RR Score. Because there is a 1-to-1 correlation between RR Score and Predicted costs, any difference in RR score can directly translated into costs savings. For example: if John Doe has a baseline RR score of 3.2, then we know he has a a predicted total annual cost of $6,384 because the predicted costs increase by an average of $1,995 per one unit change in RR Score. Therefore, If his RR score is reduced by two points from 3.2 down to 1.2, then we know ~$4,000 has been saved. The advantage of using a baseline study is that the member acts as his or her own control group.
  • 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: Age (excludes Medicare primary) Sex Number of comorbid conditions Differences in benefits design Length of time enrolled as BCBSLA member Enrolled or not enrolled in case management Case management severity (moderate high) SES – using zip code data Self-selection bias
  • This slide shows the summary statistics for members enrolled in case management vs. members not enrolled in case management between August 2003 and July 2004. It is based on claims paid and incurred during that time period and includes a 90 day claims lag runout. 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.
  • Using CRMS data, the incremental difference between the allowed paid claims for diabetics enrolled in case management vs. diabetics not enrolled case management is: $9,741.55 - $26,178.53= -$16,436.98/year/enrolled diabetic. Diabetic members enrolled in case management appear to have significantly greater utilization of health services including primary care and specialty care services. Is there a long-term payoff?
  • The initial conclusions indicate: Its too early to publish any conclusive findings as the study was designed to run 2002 through 2004 and use completed claims data so a 39 month period of time is needed. We will be publishing our conclusions next year. 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? 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: Reduced inpatient hospital admits Reduced ER utilization Reduced incidence and prevalence of ESRD
  • Markov analysis is a technique that deals with probabilities of future occurrences by analyzing presently known or estimated probabilities. Well-regarded as a method for evaluating long-term cost-benefit when long-term data are limited or nonexistent. 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: There is a limited or finite number of possible states The probability of changing states remains the same over time (i.e., stationary vs. non-stationary Markov models) We can reasonable predict any future state from the previous state and the matrix of transition probabilities. The size and the makeup of the system – for example the proportion of diabetics- does not change during the analysis.
  • The above is a cohort simulation model established to demonstrate the long-term savings associated with case management activities for diabetics. The low, moderate and high risk categories are arbitrary constructs intended as proxies for severity of diabetes. They are based on RR score range from the BCBSLA predictive model, or HbA1c values, or allowed/dollars/diabetic/year.
  • The above is the Markov cohort simulation model produced using TreeAge data 4.0 software. The data from the Markov transition state diagram were loaded into the model, estimated costs/savings were used as the payoff and the results are shown on the next slide.
  • This Markov model output assumes a monthly savings cycle for case management activity and a half-cycle correction factor for a five year time horizon. The savings are estimated at $5,268.82/year/enrolled diabetic assuming a five year horizon and a nominal discount rate of 3%/year. Also note the expected rate of cost increase is greater for the diabetics not enrolled in case management. Note that the Markov model shows savings because the likelihood of a diabetic member enrolled in case management incurring higher claims costs is lower than for a diabetic member not enrolled in case management.
  • QUESTION &amp; ANSWER SESSION
  • Mckesson Payor Solutions Conference Presentation of Case Management, 2004

    1. 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. 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. 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. 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. 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. 6. QUESTION 1: What is the ROI for the Various Departments within Medical Management?
    7. 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. 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. 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. 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. 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. 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. 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. 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. 15. The Basic Model
    16. 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. 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. 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. 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. 20. An Example of the Data
    21. 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. 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. 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. 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. 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. 26. QUESTION 3: How Can We Model the Cost-Benefit of the Long-term Savings Associated with Case Management Activities?
    27. 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. 28. Markov Transition State Models for Diabetics Enrolled and Not Enrolled in Case Management Programs
    29. 29. Setting Up the Markov Model (Cohort Simulation model)
    30. 30. The Markov Model - Continued
    31. 32. QUESTION & ANSWER SESSION
    32. 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>
    33. 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>
    34. 35. THE END

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