The goal of our case studies has been to understand the perspective and experiences of elderly Medicare beneficiaries who have enrolled in innovative managed care organizations (MCOs) and who are known to those organizations as having high risks for hospitalization and adverse health outcomes. We focused on this group to get an idea of the ways in which managed care could help high-risk seniors. High-risk seniors who had not been identified by their plans clearly require attention, but studying those people would not allow us to observe any proactive services. In addition, high-risk groups of seniors provide an important sentinel group for studying the performance of managed care organizations (Patterson et al. 1998).
We began our case studies by selecting four innovative MCOs: three managed care plans with capitated Medicare + Choice contracts and one large provider group with a history of accepting capitation to care for elderly Medicare beneficiaries.
We selected the four MCOs after developing a list of organizations that had innovative programs for seniors with multiple chronic conditions or disabilities. We developed the list using reports in the literature, suggestions from the project’s Technical Advisory Group, and the authors’ knowledge of the industry. In selecting the four to study, we looked for a mix of organizations in terms of plan type, Medicare + Choice payment level, profit/nonprofit tax status, and geographic location. All organizations also had to have more than 10,000 elderly Medicare beneficiaries and several years’ experience with special programs for seniors.
Once we selected the MCOs, we identified three groups of seniors who had severe limitations or multiple chronic conditions and who had been identified as high risk by their MCO. These groups include elderly beneficiaries being served by an MCO’s care management program, those who had attained advanced age (more than 84 years old), and those who had experienced a recent hip fracture or stroke. While these three groups do not constitute or represent all high-risk seniors, they provide a convenient way of illustrating the experiences of seniors whose high-risk status is known to their MCO.
We conducted the case study site visits from December 1997 through October 1998, and surveys from March 1999 through December 1999, with a second round of interviewing for the subsample of seniors with hip fracture or stroke conducted from October 1999 through July 2000.
A. Participating Managed Care Organizations
The four MCOs that participated in this study are:
Keystone Health Plan East (referred to herein as Keystone East): an IPA-model plan that, at the time of our case study, contracted directly with individual physicians to care for about 80 percent of its Medicare enrollees and had capitated contracts with large provider organizations to care for the other 20 percent.
Regence HMO Oregon(referred to herein as HMO Oregon): an IPA-model plan that relied on capitated contracts with large provider organizations to care for a substantial proportion of its Medicare beneficiaries.
Kaiser Permanente--Colorado (referred to herein as Kaiser Colorado): a group model HMO in which the HMO (the Kaiser Foundation Health Plan) contracts for physician services with the Colorado Permanente Medical Group, which has about 450 physicians who serve Kaiser Colorado members exclusively and who participate in all aspects of health plan management.5
Aspen Medical Group (referred to herein as Aspen): a large nonprofit multispecialty medical group in the St. Paul/Minneapolis area, which serves 13,000 Medicare + Choice beneficiaries who enrolled in Medica Health Plan and then selected Aspen as their primary care clinic. At the time of our visit, about 60 percent of the Medicare beneficiaries seen at Aspen were enrolled in managed care.
These four organizations represent a diverse mix in terms of their size, recent growth, geographic location, and other characteristics (Table II.1). In our case study, the major distinction among the four MCOs is the group nature of Kaiser Colorado and Aspen compared with the IPA/network organization at Keystone East and HMO Oregon. It is also important to note the much larger scale and recent growth rate for Keystone East and the very low growth rates at Aspen and HMO Oregon. Differential growth sets up different dynamics and opportunities in these organizations. For example, at the time of our site visit to Keystone East, the MCO was devoting substantial energies, including staff hiring and updating their data systems, in order to integrate almost 200,000 new members. The longer experience with Medicare managed care at the two group models, Aspen and Kaiser Colorado, is also an important difference among the four case-study MCOs.
|TABLE II.1. Managed Care Organizations Studied
|| Aspen Medical
Plan of Colorado
| Keystone Health
| Regence HMO
||St. Paul, MN
|Date of Site Visit
||Capitated Medical Group
(with 20 percent of enrollees in groups)
(with 75 percent of enrollees in groups)
|Total Enrollment at the Time of Our Visit
|Capitated Medicare Enrollment at the Time of Our Visit
|Growth in Medicare Enrollments During the Year Prior to Our Visit
||Close to zero
|Medicare Risk Plan Established
|NOTE: All MCO data were collected from the MCOs.
- Aspen began its Medicare risk plan under a demonstration that predated the 1982 enactment of the legislation authorizing Medicare managed care, the Tax Equity and Fiscal Responsibility Act (TEFRA) of 1982.
The four MCOs operated in market areas with differing characteristics (Table II.2). The major distinction is between the area in and around Philadelphia (served by Keystone East) and the areas served by the other organizations. The Philadelphia area is notable for its high provider supply and utilization patterns and its higher Medicare + Choice payment rates. The number of inpatient days per 1,000 residents in Philadelphia is at least twice that for the other areas and almost three times the rate for the Portland area. The Medicare payment level for 1998 was $718 for the city of Philadelphia, which is 40 to 70 percent more than the highest rate for the other catchment areas.
The other major distinction is the managed care penetration rate: the percentage of people who are enrolled in managed care. Among our four organizations, HMO Oregon operates in the area with the greatest managed care penetration, almost half the population and half the Medicare beneficiaries were enrolled in managed care. (Because many people do not have insurance, the penetration rate among all insured people is much higher than 50 percent.) Kaiser and Aspen also operate in areas with high managed care penetration. Keystone’s market has the lowest managed care penetration among Medicare beneficiaries, although managed care was growing quickly there during the late 1990s and was well above the average rate for the nation as a whole.
It is important to note that the four case-study MCOs implemented several services for high- risk seniors before those services were mandated by the Centers for Medicare & Medicaid Services (CMS; formerly known as the Health Care Financing Administration). For example, all four screened new members before it was mandated. In addition, they were identifying and assessing high-risk seniors before the regulation requiring Medicare + Choice plans to identify each person with a serious or complex medical condition, assess the condition, and develop a treatment plan that allows direct access to specialists.6 That regulation also requires that plans have in place programs for coordination of plan services with community and social services. The regulations do not, however, outline the responsibility of MCOs to address the non-acute care needs of the enrolled beneficiaries, nor do they define “serious and complex medical conditions.”
C. Characteristics of Our Sample of High-Risk Seniors
The characteristics of our sample indicate some traits that distinguish our sampled high-risk seniors from the overall Medicare population. The composition of our sample reflects two types of selection. First, our focus on people with advanced age and a previous stroke or hip fracture implies that our sample will be older than the average elderly Medicare beneficiary. Furthermore, members of any of our three sample subgroups (care management, advanced age, previous hip fracture or stroke) are more likely to have poorer-than-average self- assessed health status and possess multidimensional needs resulting from multiple functional limitations and chronic conditions.
To describe our sample of high-risk seniors, we present means of variables related to the demographic characteristics and the health and functioning of beneficiaries in our sample. Means from our survey are weighted to adjust for nonresponse and the probability of selection into a given survey sample,10 and allow us to make generalizations about the relevant populations of the three MCOs at the population level. Furthermore, to give a general sense of how our sample compares to the population of elderly Medicare beneficiaries, means derived from the 1997 Medicare Current Beneficiary Survey (MCBS) (Health Care Financing Administration 1999) are also included. Standard errors were not available for the means we derived from published data from the MCBS, but even those published for smaller subgroups were consistently less then one percent. Therefore, the following standard will be used to give an idea of whether the means are statistically significant: if the mean of our sample is more than 2 x (standard error) away from that of the MCBS, then it will be considered significantly different.
D. Analysis Methods
The analysis of case study information was based on the site visit reports and follow-up discussions with key staff at the four MCOs. Using the VIP and I-CAN frameworks, we looked for ways in which these organizations had attempted to meet the diverse and often extensive needs of high-risk seniors. In particular, we compared methods used to identify high-risk seniors and to then coordinate and manage their care.
Much of the survey data analysis is based on descriptive statistics (averages and cross-tabulations). In general, we present weighted means in order to provide as close a measure as possible for the target populations being described. When comparing the three organizations whose members were surveyed, we use regression analysis to control for the underlying differences in the characteristics of the beneficiaries enrolled in the three MCOs. These regressions are not weighted but do control for factors that reflect the probability of selection into the survey and survey nonresponse. In particular, the following control variables were used for most regressions:
- Plan (Kaiser Colorado, Aspen, Keystone East)
- Survey Subgroup (care management, advanced age, hip, stroke)
- Respondent Type (sample member, proxy, representative proxy)
- Gender (male, female)
- Age (age 65-74, age 75-84, age>84)
- Race (white, black, other)
- Education (no high school diploma, high school graduate, at least some college)
- Income (less than $10,000, $10 to $20,000, more than $20,000)
- Self-Reported Health Status (excellent, good, fair, poor)
- Medicaid (whether sample member reported having Medicaid coverage)
- Marital Status (whether married)
- Residential Status (whether sample member lives alone)
- Chronic Conditions (2 or fewer conditions, 3 or 4 conditions, 5 or more conditions)
- Dementia (whether the sample member has Alzheimer’s disease or other dementia)
- ADL Limitations (no limitations, limited in 1 or 2 activities, limited in 3 or more activities)
Means for these control variables, and their variation among the three MCOs included in the survey, are presented in Table II.6. The race categories used in the regressions (Table II.6) differ from those presented in Table II.4, because we were unable to control for ethnicity as a result of the small number of Hispanics. Ethnicity is therefore ignored as a control variable, and Hispanics are classified into their corresponding race category. Similarly, the regressions use only 3 categories to describe the number of chronic conditions. We combined seniors who reported no chronic conditions with those who reported fewer than two such conditions, because the group with no conditions was fairly small. Finally, we control for the presence of dementia, because we believe that that controlling for the number of chronic conditions alone will not capture the effect of relatively high rates of dementia in the Aspen and Kaiser samples, and the absence of an explicit control for this measure could lead to omitted variables bias. In the analysis of the hip fracture and stroke sample (see Chapter VI), the sample was too small to permit us to control for all the variables included in this list. We therefore developed a slightly smaller set of control variables that are listed in Appendix Table A.1.
When one of these control variables was missing for a sample member, we imputed the mean for the full sample. In addition, when a variable was missing for more than five percent of a sample, we added an extra control variable that indicated whether or not we had imputed for each sample member. This extra control variable enables us to control for any characteristics that are systematically related to whether the variable was missing for a sample member. We never imputed values for any of the variables used as outcomes in the regression analysis.
|TABLE II.6. Variability of Sample Characteristics Across MCOs
(Percentage and Their Standard Errors)
|| Kaiser Colorado
|| Keystone East
| Care management
| Advanced age
|| 68.8 (0.1)
| Hip fracture
|| 100.0 (0.0)
| Kaiser Colorado
| Keystone East
| Sample member
| Representative proxy
|Age at Time of Interview
| 65 to 74
| 75 to 84
| 85 or older
| Did not complete high school
| High school graduate
| At least some college
|Total Household Incomee
| Less than $10,000
| $10,000 to less than $20,000
| $20,000 or more
| Two or fewer
| Three to five
|Number of Chronic Conditionsd
| Two or fewer
| Three or four
| Five or more
|Alzheimer's or Other Dementia
|SOURCE: Telephone survey of 1,657 high-risk seniors from three managed care organizations, conducted between March and December 1999 by MPR.
NOTE: Values are percentages, with standard errors in parentheses.
- Percentages will sum to more than 100, because some seniors are in multiple sample frames.
- Race categories are different from those in Table II.4, because we were unable to control for ethnicity as a result of the small number of Hispanics. Ethnicity is therefore ignored as a control variable, and Hispanics are classified into their corresponding race category.
- ADL limitations involve the need of help or supervision with the five activities of daily living: bathing, eating, dressing, transferring, and toileting. These questions were asked of the 1,399 community residents only.
- People were asked whether they had been diagnosed with any of the following chronic conditions: arteriosclerosis, hypertension, heart attack, other heart disease, previous stroke, depression, cancer, diabetes, arthritis, asthma, previous hip fracture, or Alzheimer’s or other dementia.
- Nonresponse was high for the income question. In general, fewer than 80 percent of respondents answered these questions. Nonresponse was also something of a problem for the Medicaid question, where between 95 and 80 percent of respondents answered it.
* 5 to 20 percent nonresponse.
** Over 20 percent nonresponse.