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The American Journal of Managed Care November 2018
A Randomized, Pragmatic, Pharmacist-Led Intervention Reduced Opioids Following Orthopedic Surgery
David H. Smith, PhD, RPh; Jennifer L. Kuntz, PhD; Lynn L. DeBar, PhD, MPH; Jill Mesa; Xiuhai Yang, MS; Jennifer Schneider, MPH; Amanda Petrik, MS; Katherine Reese, PharmD; Lou Ann Thorsness, RPh; David Boardman, MD; and Eric S. Johnson, PhD
Understanding and Improving Value Frameworks With Real-World Patient Outcomes
Anupam B. Jena, MD, PhD; Jacquelyn W. Chou, MPP, MPL; Lara Yoon, MPH; Wade M. Aubry, MD; Jan Berger, MD, MJ; Wayne Burton, MD; A. Mark Fendrick, MD; Donna M. Fick, RN, PhD; David Franklin, BA; Rebecca Killion, MA; Darius N. Lakdawalla, PhD; Peter J. Neumann, ScD; Kavita Patel, MD, MSHS; John Yee, MD, MPH; Brian Sakurada, PharmD; and Kristina Yu-Isenberg, PhD, MPH, RPh
From the Editorial Board: Glen D. Stettin, MD
Glen D. Stettin, MD
A Narrow View of Choosing Wisely
Daniel B. Wolfson, MHSA, Executive Vice President and COO, ABIM Foundation
Cost of Pharmacotherapy for Opioid Use Disorders Following Inpatient Detoxification
Kathryn E. McCollister, PhD; Jared A. Leff, MS; Xuan Yang, MPH, MHS; Joshua D. Lee, MD; Edward V. Nunes, MD; Patricia Novo, MPA, MPH; John Rotrosen, MD; Bruce R. Schackman, PhD; and Sean M. Murphy, PhD
Overdose Risk for Veterans Receiving Opioids From Multiple Sources
Guneet K. Jasuja, PhD; Omid Ameli, MD, MPH; Donald R. Miller, ScD; Thomas Land, PhD; Dana Bernson, MPH; Adam J. Rose, MD, MSc; Dan R. Berlowitz, MD, MPH; and David A. Smelson, PsyD
Effects of a Community-Based Care Management Model for Super-Utilizers
Purvi Sevak, PhD; Cara N. Stepanczuk, MPP; Katharine W.V. Bradley, PhD; Tim Day, MSPH; Greg Peterson, PhD; Boyd Gilman, PhD; Laura Blue, PhD; Keith Kranker, PhD; Kate Stewart, PhD; and Lorenzo Moreno, PhD
Predicting 30-Day Emergency Department Revisits
Kelly Gao; Gene Pellerin, MD; and Laurence Kaminsky, PhD
Patients' Adoption of and Feature Access Within Electronic Patient Portals
Jennifer Elston Lafata, PhD; Carrie A. Miller, PhD, MPH; Deirdre A. Shires, PhD; Karen Dyer, PhD; Scott M. Ratliff, MS; and Michelle Schreiber, MD
Currently Reading
Impact of Dementia on Costs of Modifiable Comorbid Conditions
Patricia R. Salber, MD, MBA; Christobel E. Selecky, MA; Dirk Soenksen, MS, MBA; and Thomas Wilson, PhD, DrPH

Impact of Dementia on Costs of Modifiable Comorbid Conditions

Patricia R. Salber, MD, MBA; Christobel E. Selecky, MA; Dirk Soenksen, MS, MBA; and Thomas Wilson, PhD, DrPH
Alzheimer disease and other dementias (ADOD) have a substantial impact on the prevalence and costs of certain comorbid conditions compared with matched beneficiaries without ADOD.
ABSTRACT

Objectives: To use the CMS 5% data sample to explore the impact of Alzheimer disease and other dementias (ADOD) on individual and population costs of certain potentially modifiable comorbid conditions, in order to assist in the design of population health management (PHM) programs for individuals with ADOD.

Study Design: A cross-sectional retrospective analysis was performed on parts A and B claims data of 1,056,741 Medicare beneficiaries 65 years and older with service dates in 2010.

Methods: The primary analysis compared the prevalence and costs of 15 comorbid conditions among those with and without ADOD in the entire sample of 1,056,741; in addition, a subset of beneficiaries without ADOD were matched by age, sex, and race on a 1:1 basis to beneficiaries with ADOD. Prevalence and cost ratios were calculated to examine the impact of potentially modifiable study comorbid conditions in both populations.

Results: The prevalence of ADOD in the entire sample was 9.4%, and their costs represented 22.8% of the total. In the matched sample, all 15 comorbid conditions chosen for the study were more prevalent and showed higher mean individual costs in beneficiaries with ADOD compared with those without. The ADOD population also had higher costs and prevalence than the non-ADOD population when single comorbid conditions were examined separately. Study conditions with the highest individual cost ratios were urinary tract infections (UTIs), diabetes with complications, and fractures. Study conditions with the highest population cost ratios were fractures, UTIs, and diabetes without complications.

Conclusions: Prevalence and costs of all study comorbidities were higher in beneficiaries with ADOD compared with those without. Individual cost ratios and population cost ratios may be useful for PHM programs trying to cost-effectively manage individuals with ADOD and comorbid chronic conditions.

Am J Manag Care. 2018;24(11):e344-e351
Takeaway Points

Alzheimer disease and other dementias (ADOD) have a substantial impact on the prevalence and costs of certain comorbid conditions that may be modifiable by care management.
  • In the Medicare 5% sample, 9.4% of individuals had at least 1 claim for ADOD and were linked to 22.8% of total costs.
  • After 1:1 matching on age, sex, and race, patients with ADOD represented 50% of the sample but 70% of the costs.
  • Among those with ADOD, prevalence and costs were higher for all 15 study comorbid conditions.
  • Understanding the impact and underlying causes of comorbidities in those with ADOD should help stakeholders prioritize care management efforts.
Alzheimer disease and other dementias (ADOD) make up a group of devastating and expensive medical conditions. According to the Alzheimer’s Association, approximately 5.3 million Medicare beneficiaries have ADOD.1 The estimated prevalence among fee-for-service (FFS) beneficiaries is 11%, and the prevalence among those with dual-eligibility status is estimated to be 20%.2 In 2017, Medicare and Medicaid were expected to cover $159 billion, or 61%, of the $259 billion in total healthcare and long-term care payments for individuals with ADOD. The combination of longer lives and aging baby boomers is expected to magnify the ADOD epidemic.3 By 2050, the number of Medicare beneficiaries with ADOD is projected to nearly triple to 13.8 million,4 with the associated healthcare costs exceeding $1 trillion.1

Patients with ADOD have a higher prevalence of chronic conditions (eg, hypertension, diabetes, chronic obstructive pulmonary disease [COPD]) and also higher healthcare costs than the general Medicare population.5-8 These higher costs can be caused by failure to optimally manage these chronic conditions (and other conditions) in patients with ADOD, leading to exacerbations or complications with attendant need for increased utilization of costly healthcare services, including emergency department visits and hospitalizations, and more frequent and longer transitions of care, including increased use of postacute services, such as skilled nursing facilities.

Population health management (PHM) is a technique used to improve the health of defined populations by identifying at-risk patients; deploying individualized interventions, including care management (CM), designed to improve adherence to evidence-based care plans; and measuring outcomes across the population, including improvement in clinical status and reductions in preventable acute events.9 Management of patients with ADOD with comorbid conditions via these programs is more complex than management of patients with similar conditions without ADOD. First, identification of the at-risk population with ADOD through claims data is challenging because ADOD are generally not the primary or even secondary diagnosis listed. Second, PHM interventions are usually focused on engaging directly with patients and activating them to increase care plan adherence. Because of their dementia, patients with ADOD may not be able to follow their prescribed care plans or report their symptoms accurately. They often must rely on informal or formal caregivers not generally targeted by PHM programs to coordinate their medical care.10

The objective of this study was to use the CMS 5% data sample to explore the impact of ADOD on individual and population costs of certain comorbid conditions that are potentially modifiable by CM and other management strategies in order to assist in the design of PHM programs for individuals with ADOD.11,12 It was hypothesized that the inability of individuals with ADOD to manage the modifiable comorbid conditions examined in this study would have a significant impact on their healthcare costs. Prior studies examining the differences in cost between patients with and without ADOD used matching based on the presence of comorbid conditions, removing any cost differential caused by the inability to manage from independent consideration. For this reason, our study was designed to match beneficiaries based only on age, sex, and race so as to reveal the full impact of ADOD on the costs of the modifiable comorbid study conditions.

This study aims to help PHM stakeholders gain insights into the unique challenges of managing the healthcare costs of individuals with ADOD at a population level and at an individual level. We believe that the results provide stakeholders in PHM with a framework for allocating resources and interventions, including CM, where they would have the greatest impact on cost, population health, and the patient experience.

METHODS

Total Population

A cross-sectional retrospective analysis was performed on parts A and B claims data from a 5% CMS sample of 1,056,741 FFS Medicare beneficiaries 65 years and older with service dates in 2010. This data set included individual files for place of service (outpatient, skilled nursing facility, inpatient, home health, and hospice) and eligibility data (age, sex, and race). Part D (drug) claims data are not included in this data sample; thus, drug costs are not part of this analysis.

Population Selection Criteria

Consistent with methodologies13 used in prior ADOD cost and utilization studies,7 individuals with ADOD were selected based on having at least 1 instance of an ADOD diagnostic code (International Classification of Diseases, Ninth Revision [ICD-9] codes 290, 294, and 331). All 10 diagnostic fields available in the CMS claims data set were examined for the presence of an ADOD diagnostic code. The 2 populations of interest were beneficiaries with at least 1 diagnosis of ADOD and beneficiaries with no diagnosis of ADOD, designated the non-ADOD population in this paper. The data were stratified by the presence or absence of 1 or more of the modifiable comorbid conditions.

Modifiable Comorbidities

Fifteen modifiable comorbid diagnostic groups based on Agency for Healthcare Research and Quality Clinical Classifications Software (CCS) groupings14 were selected by the authors (P.S., T.W., and C.S.), each of whom has a different skill set related to PHM (MD/MBA, PhD [epidemiology], and the former CEO of a disease management company, respectively). T.W. provided P.S. with a list of all CCS diagnostic groups; P.S. selected disease groups based on the estimated cost and prevalence of the condition in the study population from prior literature and a professional assessment of the modifiability (ie, prevention, reduction of complications, or avoidance of acute incidents) of the clinical course by employing PHM interventions.

As is typical in the selection of chronic conditions to manage in PHM programs, the study conditions chosen are potentially modifiable via the application of PHM interventions (including CM), thus providing an opportunity for significant cost savings. Mental health conditions, such as depression, that may be amenable to PHM were not included because they can be challenging and costly to definitively diagnose in the presence of dementia.15

The 15 study comorbid conditions, followed by the CCS codes in parentheses, were asthma (128), congestive heart failure (CHF) (108), chronic renal failure (158), COPD (127), diabetes with complications (50), diabetes (diabetes without complications) (49), fractures (225-239), influenza (123), myocardial infarction/coronary artery disease (100-101), osteoporosis (206), pneumonia (122), stroke (109), syncope (245), ulcer/gastritis (139-140), and urinary tract infection (UTI) (159).

Costs

Cost differences were calculated between ADOD and non-ADOD groups, both overall and by each modifiable comorbid condition. Costs were reported as they existed in the claims data sets; no adjustment was made for inflation to current rates. It should be noted that costs reflect actual parts A and B payments made by CMS on behalf of the Medicare program for all covered services in 2010 and do not include co-payments, deductibles, and other out-of-pocket expenses paid by beneficiaries.


 
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