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The American Journal of Managed Care August 2009
Outcomes of Patients Discharged From Pharmacy-Managed Cardiovascular Disease Management
Kari L. Olson, PharmD; Thomas Delate, PhD; Jon Rasmussen, PharmD; Tammy L. Humphries, PharmD; and John A. Merenich, MD; for the Clinical Pharmacy Cardiac Risk Service Study Group
Burden of Alzheimer's Disease and Association With Negative Health Outcomes
Daniel C. Malone, RPh, PhD; Trent P. McLaughlin, PhD; Peter M. Wahl, BA; Christopher Leibman, PharmD; H. Michael Arrighi, PhD; Mark J. Cziraky, PharmD; and Lisa M. Mucha, PhD
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Stephen G. Jones, MS; Soyal R. Momin, MS, MBA; Matthew W. Good, MD; Terence K. Shea, PharmD; and Kenneth Patric, MD
Cost Comparison of Peritoneal Dialysis Versus Hemodialysis in End-Stage Renal Disease
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Cost Evaluation of a Coordinated Care Management Intervention for Dementia
O. Kenrik Duru, MD, MSHS; Susan L. Ettner, PhD; Stefanie D. Vassar, MS; Joshua Chodosh, MD, MSPH; and Barbara G. Vickrey, MD, MPH
Cost Minimization of Medicare Part D Prescription Drug Plan Expenditures
Rajul A. Patel, PharmD, PhD; Helene Levens Lipton, PhD; Timothy W. Cutler, PharmD; Amanda R. Smith, MPH; Shirley M. Tsunoda, PharmD; and Marilyn R. Stebbins, PharmD
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Geoffrey F. Joyce, PhD; Dana P. Goldman, PhD; William B. Vogt, PhD; Eric Sun, PhD; and Anupam B. Jena, PhD
Guided Care and the Cost of Complex Healthcare: A Preliminary Report
Bruce Leff, MD; Lisa Reider, MHS; Kevin D. Frick, PhD; Daniel O. Scharfstein, ScD; Cynthia M. Boyd, MD, MPH; Katherine Frey, MPH; Lya Karm, MD; and Chad Boult, MD, MPH, MBA
A Telephone-Based Intervention for Increasing the Use of Osteoporosis Medication: A Randomized Controlled Trial
Jill Waalen, MD, MPH; Amalia L. Bruning, PA; Mark Jason Peters, MD; and Eric M. Blau, MD

Cost Evaluation of a Coordinated Care Management Intervention for Dementia

O. Kenrik Duru, MD, MSHS; Susan L. Ettner, PhD; Stefanie D. Vassar, MS; Joshua Chodosh, MD, MSPH; and Barbara G. Vickrey, MD, MPH
A dementia care management program proven to improve quality and outcomes showed a statistically nonsignificant cost offset (both payer and societal perspectives) over 18 months.
Objective: To calculate intervention costs and the potential cost offset of a care management intervention that substantially improved the quality of dementia care.

Study Design: From both a payer perspective and a social planner perspective, we analyzed data from a cluster randomized controlled trial (RCT) evaluating this intervention versus usual care. The RCT included 408 pairs of older adults with dementia and their caregivers. Caregivers were surveyed at baseline, at 12 months, and at 18 months to assess patient healthcare utilization and out-of-pocket costs.

Methods: We calculated fixed and per-patient intervention costs from RCT records. We combined the monthly per-patient costs of healthcare services, informal caregiving, and out-of-pocket costs, and we conducted multivariate analyses comparing this sum (potential cost offset) for intervention versus usual care patients. Covariates included patient age, sex, and baseline costs. We limited the main analysis to patients who survived until the 12-month survey or the 18-month survey.

Results: The intervention required a start-up cost of $70,256 and mean intervention per-patient permonth costs of $118. There were no significant differences in the mean monthly cost of healthcare and caregiving services for intervention versus usual care patients using the societal perspective (difference of −$555 per month, P = .28) or the payer perspective (difference of −$219 per month [including nursing home costs], P = .55; difference of −$256 per month [excluding nursing home costs], P = .47).

Conclusion: Although this analysis of a dementia care management intervention did not demonstrate a significant cost offset, the intervention may represent a worthwhile approach to improving the quality of care and health outcomes for patients with dementia and their caregivers.

(Am J Manag Care. 2009;15(8):521-528)
This cost analysis of a dementia care management program proven to improve quality and outcomes did not show a definitive cost offset over 18 months but may represent a cost-effective approach to providing high-quality dementia care in managed care settings.
  • Few programs that demonstrably improved quality of dementia care have been reported.
  • This program successfully connected patients and caregivers to existing community services, as recommended in guidelines.
  • This detailed cost analysis from the payer and social planner perspectives provides managed care decision makers with data on fixed and ongoing program costs, as well as on potential reductions in other healthcare and caregiving costs.
Dementia, defined as an acquired persistent impairment in 2 or more cognitive areas (eg, language and memory), is a leading cause of disability in older adults.1,2 Dementia of the Alzheimer type, the most common variant, affects more than 4 million Americans.3 Dementia care represents a substantial expense for healthcare organizations and society, with the combined costs for formal services (inpatient and outpatient medical care) and informal caregiving exceeding $25,000 per patient per year in most studies.4-8 The overall cost burden will escalate significantly over the coming decades as the American population ages and the prevalence of dementia increases.3 

Existing practice guidelines for dementia care reflect evidence from randomized controlled trials (RCTs) showing that assistance to caregivers can reduce the severity of patients’ symptoms, decrease the use of acute care services, and delay institutionalization, potentially lowering costs over time.2,9-12 Unfortunately, adherence to these  guidelines is variable across health systems.13-15 Collaborative care management programs emphasize coordinated and comprehensive approaches to improving quality of care. These programs are most effective for diseases such as dementia that are high-volume conditions primarily managed in the outpatient setting, have substantial variability in treatment, and rely on coordination with community agencies for recommended social services.16-19 Large healthcare organizations,  particularly managed care systems, have an opportunity to implement care management programs for patients with dementia that improve quality of care, reduce the burden on caregivers, and potentially have long-term cost offsets.16,17,20,21

In a recent evaluation of an RCT of a care management intervention for dementia, it was found that patient health-related quality of life, caregiving quality, social support, level of unmet caregiving  assistance needs, and adherence to published dementia care guidelines were better for intervention patients compared with patients receiving usual  care.12 Although this intervention substantially and broadly improved the quality of dementia care, health plan administrators need data on start-up costs and cost offsets to weigh the value of such programs. Some or all of the initial financial expenses may be recovered over time if the intervention provides an ongoing net savings (eg, by  reducing the need for costly services such as hospitalizations).

To understand the economics of this intervention, we calculated the associated start-up and annual fixed costs and projected the per-patient variable costs of the intervention operating at full capacity. We hypothesized that, among patients who survived for the entire study period, the costs of healthcare and caregiving services would be lower for patients in the intervention arm compared with patients receiving usual care from both payer and societal perspectives. We also hypothesized that savings associated with the intervention would represent a complete offset of the associated start-up and annual fixed costs, such that budget neutrality would be achieved within several years.

METHODS

The components of the care management intervention, as well as specific study-related outcomes that included adherence to each of 23 dementia guideline recommendations, have been described previously.12 In brief, patients with dementia receiving services in 18 primary care clinics within 3 healthcare organizations in the San Diego, California, area, together with their informal caregivers, were enrolled in a cluster RCT with an 18-month follow-up. Patient-caregiver dyads in the intervention arm were assigned a care manager, who was trained in the use of Internet-based care management software. The care managers performed a structured home assessment, identified problems, initiated care plan actions, and sent a summary to the primary care physician and other designated providers. Care managers provided ongoing follow-up as needed, with in-home reassessments every 6 months.

Three community agencies collaborated with the participating healthcare organizations to provide specific care services (eg, access to respite care). A physician champion was established within each healthcare organization. At each of the intervention clinics, providers received standardized interactive educational seminars on relevant care issues such as the evaluation of acute behavior changes. Selected intervention tools and documents with more detailed descriptions can be accessed at the Alzheimer’s Disease Coordinated Care for San Diego Seniors Web site (http://www.adc.ucla.edu/access/access.swf). Patients, caregivers, and providers in the usual care group did not receive any of the intervention protocol, and patients received care as usual.

Study Design and Participants

Institutional review boards at the University of California, Los Angeles, and all participating sites approved the study, and informed consent was obtained from all study subjects (or from their proxies). Patients were eligible for the intervention if they were at least 65 years of age, enrolled in Medicare (either fee-for-service or managed care plans), had a dementia diagnosis, and had an informal caregiver at least 18 years of age. Potentially eligible patients were identified by a dementia diagnosis code or a cholinesterase inhibitor prescription recorded in administrative claims data. Clinic providers were contacted to confirm each diagnosis and to suggest additional patients as potential participants. Patient-caregiver dyads were enrolled between August 2001 and November 2002. After enrollment, caregivers were surveyed at baseline, at 12 months, and at 18 months. The surveys collected detailed information about patient healthcare utilization, paid and unpaid caregiving hours, costs of paid nonprofessional caregivers, and out-of-pocket expenses in the 6 months before enrollment through 18 months after enrollment.

Within each healthcare organization, clinics were matched by patient volume and subsequently were randomized to either the intervention (9 clinics) or usual care (9 clinics). By the end of the enrollment period, each full-time care manager was managing approximately 50 patient-caregiver dyads. We used this figure to calculate the per-patient variable costs of the intervention, which depended on the scale of the intervention. We used an intent-to-treat framework based on the initial randomization and limited the main analyses to patients with complete utilization data at baseline who survived for the entire study period and had follow-up data at 12 months, 18 months, or both. Patients who were institutionalized during the study period were included in the analyses. We excluded from the main analyses patients who died, as the substantial costs associated with end-of-life care22,23 might overshadow any cost differences related to the intervention. Although mortality rates did not differ significantly between the intervention and usual care groups at any point during the study,12 we performed sensitivity analyses that included patients who died before the study ended.

Intervention Cost and Potential Cost Offset

In brief, we estimated the cost of the intervention by summing fixed 1-time start-up costs, annual fixed costs, and per-patient variable costs (eAppendix A available at www. ajmc.com). We did not have true cost data for healthcare and caregiving services not directly attributable to the intervention (ie, potential cost offset), but we estimated this information using expenditure data (eAppendix B available at www.ajmc.com). We determined the units of each service utilized by each patient and applied standard unit costs from sources such as the Medical Expenditure Panel Survey and the Centers for Medicare & Medicaid Services. Although we did not include pharmacy costs because sufficiently detailed information was unavailable to us, we performed an ancillary analysis examining the effect of the intervention on the rates of cholinesterase inhibitor use.

We considered 2 different perspectives in calculating the potential cost offset, a “payer” perspective and a “social planner” perspective (eAppendix C available at www.ajmc.com). The payer perspective is limited to the formal costs of care borne by the health plan. We calculated estimates for this perspective under 2 different assumptions with and without the cost of nursing home stays included. The social planner perspective implies that costs and benefits accruing to all members of society are measured.24 This perspective includes not only the formal costs of care but also the opportunity costs associated with informal caregiving, which represent a substantial proportion of the costs of dementia care.25,26

Statistical Analysis

In unadjusted analyses, we compared baseline characteristics and costs of healthcare for the intervention and usual care arms. We used the X2 test for categorical variables and the Wilcoxon 2-sample rank sum test or 2-sample t test for continuous variables, depending on their distributions. In ordinary least squares regression analyses, we compared the mean monthly costs of healthcare and caregiving services for intervention and usual care patients who survived the entire 18-month study period and had follow-up data available at 12 months, 18 months, or both. The estimated intervention effect was similar when using square root and log transformations of the dependent variable, so for ease of interpretation we report the results when using the original (nontransformed) cost variable.

To account for the complex sample design, including the clustering of patient-caregiver dyads within clinics, we used generalized estimating equations and adjusted for clinic as the clustering variable using statistical software (STATA 8.2; StataCorp LP, College Station, TX). In addition to the indicator variable for the intervention group versus the control group, we included as covariates patient age and sex, indicators for the healthcare organizations, an indicator of managed care versus fee-for-service insurance, and the patient’s mean monthly costs of healthcare and caregiving services during the 6 months before baseline. The analyses were weighted based on the number of months of follow-up data (maximum, 18 months) available for each subject to increase the influence of data from patients with longer study enrollment and to produce more reliable monthly cost means.27 We conducted 2 sensitivity analyses that included (1) patients with at least 1 follow-up survey regardless of whether they died during the study and (2) patients who survived for the entire study period and had follow-up data at both 12 months and 18 months.

RESULTS

 
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