The Relationships Among Age, Chronic Conditions, and Healthcare Costs

Published Online: December 01, 2004
Wei Yu, PhD; Arliene Ravelo, MPH; Todd H. Wagner, PhD; and Paul G. Barnett, PhD

Objective: To learn how age and chronic illness affect costs in the Veterans Affairs healthcare system.

Study Design: Veterans Affairs patients 65 years or older were identified from administrative data. We noted their healthcare utilization, cost, and diagnosis of any of 29 common chronic conditions (CCs). We examined how those 80 years or older differed from the younger patients.

Results: The Department of Veterans Affairs spent $8.5 billion to treat 1.6 million older patients in fiscal year 2000. Age was less important than chronic illness in explaining cost differences. The oldest patients incurred a mean of $1295 greater costs than the younger patients, primarily because they were more likely to have a high-cost CC. The oldest patients incurred higher total costs than the younger patients in only 14 of 29 groups defined by CC. Long-term care accounted for most of the extra cost of the oldest patients. When this cost was excluded, the oldest patients incurred only $266 more cost than the younger patients.

Conclusions: Growth in the population of the oldest patients will increase the number of individuals with CCs requiring long-term care. With its limited long-term care benefit, Medicare will avoid much of this financial consequence. In contrast, the financial risk of acute and long-term care gives the Department of Veterans Affairs an incentive to develop strategies to prevent CCs associated with long-term care.

(Am J Manag Care. 2004;10:909-916)

The Department of Veterans Affairs (VA) healthcare system is one of the largest integrated healthcare systems in the United States, comprising 163 hospitals, 137 nursing homes, 43 domiciliaries, and 913 outpatient clinics.1 In fiscal year (FY) 2002, the VA spent $23 billion to provide medical care to 4.7 million veterans.2 A unique feature of the veteran population is that the age distribution closely relates to the timing of wars and can change sharply in a short time. As the veterans of World War II and the Korean War have aged, the number of veterans 85 years or older has increased at a mean rate of 11% per year, from 156 000 in 1990 to 510 000 in 2000; it is projected to reach 1.3 million by 2010.3,4

The rapid aging among veterans has increased the demand for VA healthcare services, especially long-term care among the oldest veterans. A population-based survey showed that the percentage of older persons who ever used nursing homes increased from 22% in the 65- to 74-year-old cohort to 58% in the 85-to 94-year-old cohort.5 The VA has to respond to these changes because the 1999 Veterans Millennium Healthcare and Benefits Act, Public Law 106-117, mandates that the VA must provide nursing home care to any veterans in need of such care for a service-connected disability.

Although the oldest patients use more long-term care, they are also less likely to receive aggressive treatment. Two studies6,7 found that Medicare expenditures decreased with increasing age because hospital and intensive care unit use by the oldest beneficiaries declined.8-10 This research suggests that there are 2 competing effects. Long-term care is expensive, but because treatment is less aggressive, the net cost effect of the increasing numbers of the oldest veterans on the VA healthcare costs is ambiguous.

To accurately predict demand, we must understand what care older adults are using and the independent effects of age and chronic conditions (CCs) on costs. Studies7,11-13 have analyzed the relationship between age, CCs, and healthcare costs. The commonly used Medicare claims data include information on medical treatments and diagnoses, but these data offer limited insight on long-term care because of Medicare's restrictive long-term care benefits. Medicaid data are also incomplete because people must spend down their wealth before they become eligible. Hence, studies based on Medicare or Medicaid data do not provide complete information on the relationships among age, CCs, and use of long-term care. A study of the VA system can help VA policy makers make projections and can offer insight on expected trends in total healthcare costs of the non-VA population.

Although we focus on veterans, understanding changes in costs incurred by older veterans will increase our understanding of how the aging of the population will affect the larger US healthcare system. The aging of the veteran population is a harbinger of changes in the US population as a whole. The number of individuals 85 years or older increased from 3.0 million in 1990 to 4.2 million in 2000; it will reach 6.1 million in 2010, when they will account for 1.2% of the population.4

We emphasize age effects, the effects of having more older people in the population on the cost of healthcare. These are different from the effects of aging, that is, the effects of increased life expectancy on healthcare cost.14,15 In this study, we analyzed healthcare costs incurred by 1.6 million older (≥65 years) VA patients. We identified 29 common CCs. Then, controlling for each CC, we compared healthcare costs of the younger (65-79 years) patients with those of the oldest (≥80 years) patients.

METHODS

To understand patterns of resource use for treating chronic illness, we grouped patients by their most expensive condition. With veterans assigned to mutually exclusive groups, we then estimated costs by type of medical services actually used. We analyzed the differences in resource use between the younger patients and the oldest patients, particularly in long-term care.

Sample and Data Selection

We collected electronic medical records on all veterans aged 65 years or older who received VA care in federal FY 2000, ending September 30, 2000. We excluded 82 713 people who used the VA system for only pharmacy benefits. The study population comprised 1 596 789 veterans, of whom 1 283 542 were younger patients and 313 247 were the oldest patients.

We did not adjust costs for patients who died during the study year. The higher mortality rates of the oldest patients have 2 conflicting effects on annual healthcare costs. As a consequence of a higher mortality rate, the oldest patients had fewer days of life during the study year and thus fewer days in which they could incur costs. On the other hand, there are high costs associated with illness sufficiently severe to result in death. In the preliminary study, we calculated the costs excluding patients who died during the study year. We found that mean costs were lower for all 29 CC groups; however, the cost differences between the oldest patients and the younger patients remained. Because including people who died during the study year reflects actual costs for a cohort in any period, we retained these subjects in this analysis.

The VA uses contract providers for those services it cannot render conveniently. In FY 2000, 7% of VA costs were paid for contracted services. Because contract care is not completely described by VA data sets, we excluded it from analysis.

Chronic Condition Identification

We chose the 29 CCs because they were included in related studies,12,16 because they are given high priority in VA research17 or quality enhancement programs,18 or because they are known to be especially common among VA patients. We identified which patients had these CCs using the International Classification of Diseases, Ninth Revision, Clinical Modification diagnostic codes recorded in VA healthcare utilization files in FY 2000. We included in our review all diagnostic codes in the inpatient and outpatient files. For 28 conditions, we classified patients with a CC based on 1 or more diagnoses. For depression, we required 2 or more outpatient diagnoses or a single diagnosis from a psychiatric clinic.

We reviewed the classification methods from a Kaiser Permanente study12 and the Clinical Classifications Software developed by the Agency for Healthcare Research and Quality.19 We also reviewed other published studies,20,21 noting when methods differed from the Kaiser Permanente and Clinical Classifications Software methods. We conducted a sensitivity analysis of these classification methods. In a conservative approach, we excluded those codes identified by our physician consultants that did not clearly specify a CC.22

Cost Data

We determined the cost of all VA-provided medical care in FY 2000. For inpatient stays that spanned multiple FYs, we allocated inpatient costs in proportion to the number of days in FY 2000. Inpatient and outpatient costs were obtained from the Health Economics Resource Center's average cost database. We allocated costs for medical/surgical hospitalizations to each hospital stay using a clinical cost function that we developed from Medicare data through a regression of cost against the diagnosis related group relative value weights, length of stay, and use of an intensive care unit.23 We adjusted nursing home costs for case mix using the resource utilization group score.24 For inpatient rehabilitation and specialty mental healthcare, costs were measured by a mean daily rate.25 Outpatient healthcare costs were based on the Current Procedural Terminology, Fourth Edition codes recorded in the database. The relative weights were based on the Medicare Resource-Based Relative Value Scale,26 the relative value units developed by Ingenix Health Intelligence,27 surveys of provider fees and fee schedules, 28-30 and the 1999 survey of the American Dental Association.31 We used these relative weights to allocate VA outpatient costs to each encounter.32 Costs for outpatient pharmacy services were obtained from the VA Decision Support System national extract, which includes overhead costs proportionally distributed to the outpatient pharmacy departments.33

Cost Hierarchy Classification

Many veterans have multiple CCs. Because we could not clearly separate medical treatments by CC, we faced the challenging question of how to group the patients such that their resource use would be closely related to their CC.

We developed a hierarchical classification method that grouped patients who had any of the 29 CCs into 29 mutually exclusive CC groups. Patients were classified into only 1 group according to their most expensive CC. For example, a patient who had lung cancer and hypertension was assigned to the lung cancer group. This method was preferable to defining groups solely by CC, as this would have assigned patients with several conditions to several groups. Under that approach, a group's mean cost would be difficult to interpret because it would be affected by the inclusion of patients with other, higher-cost conditions.

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