The Gerontologist 47:244-247 (2007)
© 2007 The Gerontological Society of America
Helping People Make Better Long-Term-Care Decisions
Robert L. Kane, MD1,
Krista Boston, JD2 and
Mary Chilvers, MS, MLIS2
Correspondence: Address correspondence to Robert L. Kane, MD, School of Public Health, University of Minnesota, D-351 Mayo Memorial Building Box 197, 420 Delaware Street SE, Minneapolis, MN 55455. E-mail: kanex001{at}umn.edu
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Abstract
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Purpose:The purpose of this article is to describe an innovative online system to support long-term-care decision making.Design and Methods:The Long-Term Care Choices tool is a web-based system that uses expert opinion and structures decision making. Results: The system has been well accepted, and most users find it easy to use.Implications:Other states could adopt similar systems to help people navigate the long-term-care system.
Key Words: Long-term care • Decision making • World Wide Web • Expert opinion • ADRC projects
Making life decisions is hard. Making decisions about long-term care is especially difficult, because few people have a great deal of experience in the area and the decisions are often made at times of great stress and family turmoil. Frequently consumers act on the advice of professionals or friends who may offer only limited options based on their own predilections.
In order to assist consumers (older adults and their families) to make more thoughtful and deliberate long-term-care decisions, we developed a web-based system that separates the decision making into two stages (Potthoff, Kane, & Franco, 1998). The first stage determines what type(s) of long-term care are best suited to the individual. The second addresses which potential providers of the desired services are best able to meet the individual's needs and preferences.
The pertinent information for each of these two steps is different. Relevant items that affect the decision about the best type of care include what type of care produces the best results. Behind that question is a clear specification of just what outcomes one hopes to maximize. Such a decision is not easy, nor is there necessarily unanimity. For example, some family members may seek safety, whereas others (often the elder) seek autonomy and independence. Still others may hope primarily for improved function or slowed decline. Before the family can evaluate a decision, it must reach consensus about the predominant outcome. Family members may not agree among themselves and may have different priorities from the older client. Most older adults don't necessarily want a nursing home as the first option. Rather, many seniors, even those with disabilities, can maintain their autonomy and successfully live in their homes with in-home support through home- and community-based services (R. A. Kane, Kane, & Ladd, 1999). Public programs are available to defray the costs but can often result in poverty for the applicant, who must spend down into the low federal poverty guidelines for these programs. Concerns about the high cost of nursing home care include both the price charged and the likelihood of coverage under public programs. Cost becomes a greater factor when paying for care privately. Sometimes expensive care is less desirable if it is not covered by Medicaid.
The salient information for the second stage of decision making is more likely to hinge on issues like access and affordability. Most older adults considering a nursing home want it to be located where family members are able to visit easily. Other factors to consider include various elements of ambiance: Will people like me be there? Do they allow smoking? How does the food taste? Can I get a private room?
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The Minnesota Approach
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The Minnesota Board on Aging created the Long-Term Care Choices tool (www.longtermcarechoices.minnesotahelp.info) as part of a larger project to assist older adults and their families to make better long-term-care decisions. The underlying idea was to create a web portal that would support various aspects of long-term care and aging assistance. This work was supported by an Aging and Disability Resource Center Real Choices Systems Change grant from U.S. Department of Health and Human Services Centers for Medicare and Medicaid Services and the Administration on Aging.
Ideally, addressing the first question (i.e., choosing the best type of care) would mean drawing upon a strong body of evidence about the effectiveness of alternative long-term-care options to achieve various outcomes. Unfortunately, such a database is not yet available. To substitute for empirical evidence, we turned to expert opinion.
To elicit expert opinion, we invited a national group of experts from a wide variety of backgrounds to participate in the project. We directly contacted many people with strong reputations in the field. In addition, we contacted organizations associated with aging and long-term care (e.g., the American Medical Directors Association, American Geriatrics Society, New York University Gerontological Nursing Program, American Health Care Association, and American Association of Homes and Services for the Aging) to request the names of potential participants. Most organizations were reluctant to release names and instead offered to contact their members for volunteers.
We created a series of hypothetical patients in which four attributes (activity of daily living difficulties, presence of behavioral problems, extent of cognitive problems, and presence of incontinence) systematically varied. We designed the scenarios to generate every combination of these four elements (except for three combinations we judged to be meaningless) and combined them with a variant of each element in the right-hand column of Table 1. We asked each respondent to distribute 100 points across the types of long-term care that could best treat the base case with a variant composed of the core variables and a set of other conditions shown in the right-hand column of Table 1. The long-term-care options included a general skilled nursing facility, a rehabilitative facility, a cognitive facility, an inpatient rehabilitation unit, assisted living, cognitive assisted living, adult foster care, day care, home health care, formal home care, hospice, and informal home care.
We then asked the rater to repeat the task while we changed each of the variables in the right-hand column one at a time. However, we did not test all combinations. In all, 429 different combinations were possible. Each rater did five sets of scenarios for a total of 65 ratings per rater. Altogether, 196 experts rated a total of 12,728 scenarios. Table 2 shows the number of scenarios rated by each discipline.
We analyzed the ratings to estimate the relationship between each combination of the potential client attributes and the various types of long-term-care service options. We explored the differences among raters (R. L. Kane, Bershadsky, & Bershadsky, 2006). We created a recommended profile of services for each unique combination of attributes by using weighted averages and then reverse-engineered this information. We transformed the descriptions used to elicit the ratings into assessment profiles according to which we could describe potential service users.
The user of the web-based module has the potential to go through the 14-step process shown in Table 3, but branching may cause them to elect various sections and omit others. Items 1–4 are a simple preliminary assessment based on self-reported information. Items 5–12 provide information on various topics that the client may find relevant. (Item 9 branches into Items 10–12.)
The information collected in the self-assessment and daily living needs generates a profile of the client. Table 4 shows a sample profile from the self-assessment section. This table shows the content of the assessment with the responses for this sample client in bold. A computer program matches the client profile with a distribution of the experts' recommended types of services for a person with that profile. Figure 1 shows an example of such a printout for this sample client.
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Figure 1. An example of long-term-care recommendations for the client shown in Table 4. SNF = skilled nursing facility; ADL = activity of daily living
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The consumer is under no obligation to follow the computer's advice, which is offered as the best thinking of 200 national experts. Each of the elements has a series of help probes that provide more information and definitions of each service type. For example, a cognitive skilled nursing facility is defined as "continuous nursing and other health-related, psychosocial, and personal services to patients with memory-related illness, who require continued care on an in-patient basis." A general skilled nursing facility is defined as "continuous nursing and other health-related, psychosocial, and personal services to patients who are not in an acute phase of illness, but who mainly require continuous care on an in-patient basis." Rehabilitation is defined as "care delivered under the direction of a rehabilitation physician [that] would require the patient [to] be able to tolerate at least three hours a day of physical therapy, occupational therapy, or speech therapy."
Once the consumer has chosen a care modality (either using the generated advice or ignoring it), he or she moves to the second stage of decision making. To date this level is most developed for nursing homes. The user first indicates the zip code where he or she wants to live. The user then selects from a list the aspects of care that he or she finds most important and prioritizes them. The computer generates a list of nursing homes in the zip code (or nearest ones) based on their profiles for the most salient elements. These elements include a variety of quality measures (R. L. Kane, Arling, Mueller, Held, & Cooke, in press), staffing, or religious affiliation. The consumer can get detailed information about any of the providers in the database, but the information is first offered in response to the elements identified as most salient.
Although the tool has been available for only a short time, we have already gotten feedback on it. Although people who are approaching long-term-care decisions for the first time or who deal with such issues infrequently have found it very helpful in providing both structure and content, experienced case managers see it as too constricting and time consuming. Both groups of users felt overwhelmed by the number of issues raised (e.g., the number of elements that one might consider in choosing housing). They felt a need to prioritize and focus on a smaller subset of the most salient elements.
At the risk of using an anecdote, we allude to a note from an 84-year-old man who described a positive experience with the new web tool. Following his wife's move into the nursing home and his daughter's transition into an apartment of her own, Mr. X found himself in need of assistance in order to remain in his home. After happening upon an article on the site in the local newspaper, he used his background in computer science to log onto the user-friendly tool. He found help identifying his needs and then went on to build a community plan to meet those needs. Mr. X said, "It's really a maze going through all of this, but this service is a good guide for those of us in the process of downsizing." But most importantly for Mr. X, "the service helped me decide whether to stay living at home or not." He found help with his lawn care and housekeeping as well as resources he can use in the future to help him continue his independent lifestyle.
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Discussion
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Initially the designers expected that many users would be able to access this information directly and use it as the basis for making long-term-care decisions. Experience has shown that a substantial number of users are quite competent in using this web-based approach and do not need technical assistance accessing the information. Nonetheless, making long-term-care decisions can be a very stressful and confusing process. Not only must people weigh many factors, but they must undergo this process in the context of often-unresolved feelings and conflicts among family members. Some sort of decision support facilitator is often needed to help family members sort out their priorities. Thus, care managers or discharge planners could use the Long-Term Care Choices tool as a template. Indeed, such professionals using a structured tool are likely to perform more consistently than they might on their own. The challenge remains to convince experienced professionals to appreciate the value of a structured approach.
The tool needs to be developed differently for the two different groups of users: consumers and professionals. Professionals, who will be familiar with the tool from repeated use and familiar with the content, will want a simple tool that has few prompts and is quick and easy to use. Consumers, who have little experience with long-term care, will need a more detailed tool with many prompts and explanations.
One way to help people focus attention on the most salient components would be to allow each user to prioritize the elements that describe the attributes of a given service and use the priority list to rank the available locations. We have used this approach successfully in developing the Minnesota Nursing Home Report Card, whereby users can indicate which components of quality are most important to them; the homes that perform best on those parameters display first (R. L. Kane et al., in press).
In addition to revision of the current tool, the next phase of development will focus on addressing the needs of adults younger than 65 by developing a Choice tool especially for individuals with disabilities. We will continue to use feedback from users of the Long-Term Care Choices tool to modify and enhance the product so that it is usable and accessible to the mainstream caregiver who is likely seeking care after hours.
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Footnotes
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This work was supported by Aging and Disability Resource Center Real Choices Systems Change Grant 11-C-91940/5-01 from the U.S. Department of Health and Human Services Centers for Medicare and Medicaid Services and grant no. 90AM2757 from the Administration on Aging. 
1 School of Public Health, University of Minnesota, Minneapolis.
2 Board on Aging, Minnesota Department of Human Services, St. Paul.
Decision Editor: Nancy Morrow-Howell, PhD
Received for publication August 4, 2006.
Accepted for publication November 27, 2006.
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References
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- Kane, R. A., Kane, R. L., & Ladd, R., (1999). The heart of long-term care. New York: Oxford University Press.
- Kane, R. L., Arling, G., Mueller, C., Held, R., & Cooke, V., in press. A quality-based payment strategy for nursing home care in Minnesota. The Gerontologist..
- Kane, R. L., Bershadsky, B., & Bershadsky, J., (2006). Who recommends long-term care matters? The Gerontologist, 46, 474-482.[Abstract/Free Full Text]
- Potthoff, S., Kane, R. L., & Franco, S. J., (1998). Improving hospital discharge planning for elderly patients. Health Care Financing Review, 19, (2), 47-72.
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Abstract
The Minnesota Approach
