The Impact of a Geriatric Assessment Team on Patient Problems and Outcomes

The Impact of a Geriatric Assessment Team on Patient Problems and Outcomes

Cheryl A. Dellasega

Hospital care of persons aged 65 and over accounts for the majority of Medicare expenditures. In 1997, $137.8 billion in hospital benefits were paid to persons over the age of 65, representing an increase of 7.1% from fiscal year 1996 (Health Care Financing Administration, 1999). In an effort to control costs, increased attention has been focused on efforts to both streamline and improve the delivery of health care services for geriatric patients. Experts contend that such efforts must be carefully planned and evaluated (Soumerai, McLaughlin, Ross-Degnan, Casteris, & Bollini, 1994), because measures to control costs can affect vulnerable elderly patients in unforseen ways, such as increasing pain and suffering.

Comprehensive geriatric assessment teams (GATs) became popular in the previous decade as a programmed effort to reduce or eliminate the adverse consequences of hospitalization for elders. The National Institutes of Health Consensus Development Conference defines geriatric assessment as a multidisciplinary evaluation in which older adults’ multiple problems are identified, described, and explained (National Institutes of Health, 1988). A review of studies examining the outcomes of geriatric assessment indicated that an interventional approach with providers to geriatric assessment would be a viable strategy for improving outcomes of older hospital patients.

Many different models of GAT have been developed and tested, first in the hospital, and then in outpatient settings (Siu et al., 1996). The most popular institutional approaches have been inpatient units and/or consultative services. To date, inpatient units have demonstrated the most consistent positive impact on patient outcomes (Applegate et al., 1990; Fillet, 1994; Landefeld, Palmer, Kresevic, Fortinsky, & Kowal, 1995; Lefton, Bonstelle, & Frengley, 1983; Rubenstein et al., 1984). Inpatient geriatric care teams are based on the premise that special efforts are needed to address the unique circumstances of elderly hospital patients in order to prevent prolonged stays and adverse outcomes. A study by Covinsky and colleagues (1997) demonstrated that a special inpatient unit designed to promote functional independence in acutely ill eiders reduced length of stay (LOS) and decreased nursing home use, but had no effect on readmission rates or caregiver strain. Another study by Weingarten and colleagues (1998) showed that a case management/practice guidelines intervention also successfully reduced LOS but increased the intensity of post-discharge care for some patients. These efforts illustrate the complex response of acutely ill elders to relatively contained intervention efforts.

Research on beneficial outcomes of the consultative model have been less conclusive. Diverse positive outcomes such as improved functional status, better diagnostic accuracy, improved mental status, and decreased mortality have been found (Hogan, Fox, Bradley, & Mann, 1987; Katz, Dube, & Calkins, 1985; Lichtenstein & Winograd, 1984; McVey, Becker, Saltz, Feussner, & Cohen, 1989; Thomas, Brahan, & Haywood, 1993). A few studies showed no clearly defined beneficial outcomes from GAT via the consultative model (Epstein et al., 1990; Reuben et al., 1995; Winograd, Gerety, & Lai, 1993). Several investigators have suggested this may be because studies were not focused on specific at-risk patient groups or problems (Reuben et al., 1992; Wieland & Rubenstein, 1996; Winograd, Gerety, Brown, & Kolodnay, 1988).

When a vulnerable group of elders are targeted and specific outcomes identified, the results of GAT interventions seem favorable. Hogan and colleagues (1987) implemented a consultative model of GAT for elderly patients with objectively measured confusion and functional declines, problems with incontinence, and polypharmacy. Subjects responded to GAT with significantly improved mental status, fewer medications, and decreased mortality rates. Another later study by Miller, Applegate, Elam, and Graney (1994) reinforces the notion that specific groups of elderly patients may benefit more from GAT. In this research a geriatric assessment unit produced greater benefits for rehabilitation patients than a medical-surgical unit.

Building on this body of study, Reuben, Fishman, McNabney, and Wolde-Tsadik (1996) broke GAT into three process components: geriatric problems, recommendations, and implementation strategies. Using this model, researchers and clinicians can focus GAT on specific patient problems, and tailor interventions to meet individual needs. Offering support for a process model of GAT, Wieland and Rubenstein (1996) suggest that researchers think outside the “black box” of GAT and begin to investigate these three components in depth.

The purpose of this study was to use a consultative model GAT to identify specific patient problems amenable to intervention, rather than diagnoses. Multidisciplinary strategies tailored to address these problems were then proposed and tested. The impact of the multidisciplinary GAT intervention on patient outcomes of health, function, and cost was then evaluated.

Methods and Subjects

A prospective cohort design was used to answer the research questions. Potential subjects were those persons aged 70 years or older who were admitted to the study site hospital for treatment of an acute medical condition and scheduled for discharge to home (patients admitted from nursing homes whose discharge destination was predetermined were excluded). Patients representing either end of the illness continuum (terminally ill or totally independent in Activities of Daily Living [ADLs]) were also excluded. Finally, patients also needed to be under the care of the five physicians who reviewed the study protocol and agreed to have their patients participate.

During the course of this study 500 patients were admitted to the participating physicians’ service. Of these, approximately 250 patients (50%) met the selection criteria, and 40% (n=105) agreed to participate and were seen by the team. Eight (6%) of these patients died, one in the hospital and seven after discharge. By the time of the last data collection, 84 subjects (80%) were still in the study. The most common reasons for drop out were a change in health status, mortality, or not wanting home visits by the research assistant (RA) to collect followup data.


All eligible patients and/or their legally responsible party were approached by the RA within 24 hours of admission, given an explanation of the study, and asked to sign a consent form indicating their willingness to be involved in the geriatric assessment intervention. Baseline data on the subject’s demographic, cognitive, and medical status were collected by the RA.

Those persons who chose to participate in the study were seen by the Geriatric Assessment Team, which consisted of a master’s-prepared geriatric clinical nurse specialist (GCNS), a pharmacist, a nutritionist, a social worker, and the primary physician. Each of these team members completed an assessment to identify patient problems and needs within 48 hours of admission, and documented their findings and recommendations on a consultation sheet for the primary physician that had been placed on the subject’s chart. The entire team, including the primary physician, met weekly to discuss new patients, make recommendations regarding care, and evaluate the status of those already enrolled.

The RAs collected data on admission, the day of discharge, and 3 and 6 months post-discharge. For the 3 and 6 month data collection, RAs visited subjects in their homes to collect followup information.

Geriatric Team Intervention

The geriatric team intervention consisted of an initial visit by each of the five team members to the patient/subject within 48 hours of admission. At this time, a comprehensive assessment was conducted to identify key problems and discipline-specific approaches to treat these problems. Once the team members had completed their assessment and made recommendations, the entire team, including the primary treating physician, met to discuss implementation of interventions. The GCNS documented the interventions implemented for the problem codes.

The problems identified by the GAT in order of frequency were: functional decline: 87% (n=91), social problems: 84% (n=88), fall risk: 76% (n=80), nutrition problems: 71% (n=75), medication problems: 70% (n=74), depression: 66% (n=69), cognitive impairment: 59% (n=62), and incontinence: 40% (n=42).

Table 1 describes the problems, the most frequent recommendations, and the implementation rates.

Table 1.

Problem Codes and Recommended Interventions

Problem Patient Recommendation Frequencies

Cognitive Impairment

(MMSE Score <24)

APN to re-evaluate mental status – 24

Further evaluation of etiology – 16

Signs, cues, aids – 17

Follow Alzheimer’s standard – 12

Depression (Yesavage

Depression Scale >5)

Monitor/reassess – 60

Start antidepressant – 16

Continue current therapy – 8

Psychiatry consult – 5

Change antidepressant – 5

Functional Decline

(Evidence of Impairment

on Katz ADLs) (Katz et

al., 1963)

Maintain pre-hospital functional level – 67

Physical therapy – 44

Ambulate two times a day – 7

Medication Problems

Discontinue medication – 26

Change medication – 17

Monitor side effects – 12

Therapeutic monitoring – 11

Add new medication – 12

Renal dose medication – 10

Fall Risk (Fall

Assessment and Portions

of Tinetti Scale as

Appropriate) (Perlin,

1992, Tinetti, 1986)

Nursing measures – 52

Bedcheck – 16

Physical therapy evaluation – 13

Check orthostatic blood pressures – 5

Use assistive devices – 4

Incontinence (10

Question Continence


Further investigation into cause (for

example, stool impaction, UA, PVR) – 15

Bladder training – 12

Discontinue Foley catheter – 7

Urology consult – 6

Nutrition Problems

(Nutritional Assessment


Nutritional supplements – 26

Diet education – 19

Diet modification – 11

Diet change – 9

Calorie counts – 6

Social Problems (Six

Question Social

Assessment Tool)

Home care/VNA/private – 7

Alternative arrangement – 30


Patient Recommendation Frequencies Frequencies

APN to re-evaluate mental status – 24 21 (88%)

Further evaluation of etiology – 16 16 (100%)

Signs, cues, aids – 17 16 (94%)

Follow Alzheimer’s standard – 12 11 (92%)

Monitor/reassess – 60 55 (92%)

Start antidepressant – 16 7 (44%)

Continue current therapy – 8 7 (88%)

Psychiatry consult – 5 5 (100%)

Change antidepressant – 5 5 (100%)

Maintain pre-hospital functional level – 67 58 (87%)

Physical therapy – 44 37 (84%)

Ambulate two times a day – 7 (100%)

Discontinue medication – 26 20 (77%)

Change medication – 17 11 (65%)

Monitor side effects – 12 11 (92%)

Therapeutic monitoring – 11 10 (91%)

Add new medication – 12 8 (67%)

Renal dose medication – 10 8 (80%)

Nursing measures – 52 48 (92%)

Bedcheck – 16 15 (94%)

Physical therapy evaluation – 13 10 (77%)

Check orthostatic blood pressures – 5 4 (80%)

Use assistive devices – 4 4 (100%)

Further investigation into cause (for 11 (73%)

example, stool impaction, UA, PVR) – 15

Bladder training – 12 11 (92%)

Discontinue Foley catheter – 7 6 (86%)

Urology consult – 6 5 (83%)

Nutritional supplements – 26 24 (92%)

Diet education – 19 18 (94%)

Diet modification – 11 9 (82%)

Diet change – 9 8 (895)

Calorie counts – 6 6 (100%)

Home care/VNA/private – 7 57 (79%)

Alternative arrangement – 30 15 (50%)


To evaluate functional health status, the Sickness Impact Profile (SIP) was used (Bergner, Bobbitt, Carter, & Gilson, 1981; Conn, Bobbitt, & Bergner, 1978; Gilson et al., 1975). This 136-item self-report questionnaire uses a forced choice format to evaluate how the individual is currently functioning in usual activities. The SIP contains 12 subscales designed to assess a person’s behavior in relation to health status. The subscales are: (a) emotional balance and mood (EB); (b) body care/movement as needed for performance of ADLs (BCM); (c) mobility in and outside the home (M); (d) home management tasks (HM); (e) ambulation with assistance, aides, or independently (A1); (f) social interaction with individuals and groups (SI); (g) intellectual function, cognition, and performance (IF); (h) communication via written and spoken modalities (CT); (I) recreation and leisure activities (RP); (j) work (W); (k) eating and appetite (E); and (i) sleep/rest (SR). The SIP has demonstrated good reliability and validity in several studies (Bergner et al., 1976; Carter, Bobbitt, Bergner, & Gilson, 1976; Pollard, Bobbitt, Bergner, Martin, & Gilson, 1976). Internal reliability was established at .96 and test-retest at .92. The SIP was selected as a measure of function because it can be administered via self-report and is sensitive to change.

The Mini-Mental State Exam (MMSE) (Folstein, Folstein, & McHugh, 1975) was used to assess mental status. While not diagnostic of specific cognitive syndromes, the MMSE is a reliable and valid measure of cognition that has been used in numerous studies (Dellasega & Morris, 1993). Further, it is easy for health care providers to use in a variety of settings without extensive training. The lower the score ([is less than] 24), the greater the cognitive impairment indicated.

Depression, a common geriatric mental health problem, was evaluated by the Yesavage Geriatric Scale (Yesavage et al., 1983), a reliable and valid measure of geriatric depression with a 84% sensitivity and 95% specificity. It is easily administered through self-report and provides a quick indication of the presence or absence of depression in older adults. Chenitz, Stone, and Salisbury (1991) found the scale to be an appropriate measure of geriatric depression over time. A score of five or more indicates depression.

Demographic information collected included diagnoses, gender, marital status, ethnic background, living arrangements, and educational level. Discharge destination, length-of-stay, and development of iatrogenic problems were also recorded at the time of discharge.

Data Analyses and Results

Table 2 contains a comparison of characteristics of completers (all four times of measurement) and noncompleters on key demographic variables.

Table 2.

Demographic Characteristics of Completers and Noncompleters

Completers Noncompleters

Variable M + sd M + sd

Age 79.46 (5.44) 79.79 (5.97)


Male 38 23

Female 46 33

Marital Status

Single 5 2

Married 37 27

Widowed 42 24

Divorced 3 0


Less than high school 27 25

Some high school 8 7

High school 24 13

Vocational/Technical 3 0

College 14 5

Other 4 5

Living Status

Alone 33 19

With spouse 34 23

With child 12 7

With relative 4 4

With friend 0 2

Other 1 1

Length of Stay 10.67 (7.39) 8.71 (5.688)

SIP Subscales

EB 148.02 (153.60) 162.83 (181.03)

SR 182.40 (146.96) 221.19 (136.40)

BCM 521.30 (426.00) 686.33 (485.38)

HM 304.80 (177.24) 358.37 (174.67)

M 233.61 (176.06) 269.07 (174.28)

SI 367.29 (289.33) 396.37 (128.10)

AI 269.81 (173.72) 285.75 (128.10)

IF 225.00 (222.24) 238.67 (234.53)

CT 150.17 (159.30) 176.96 (158.86)

W 349.33 (56.91) 354.65 (45.37)

RP 194.19 (107.84) 214.58 (85.56)

E 104.29 (115.87) 109.92 (91.78)

Mini Mental 25.21 (4.08) 24.42 (5.41)

Exam Score

Yesavage 9.07 (5.86) 10.53 (6.29)

Depression Score

To identify changes in SIP status over time, repeated ANOVA measures were used to compare problem categories. Table 3 presents the significant findings. Interventions for seven distinct categories of patient problems were associated

with significant improvements on many aspects of patient functional status. These patient problem categories were: cognitive impairment, depression, functional decline, medication problems, fall risk, incontinence, and social problems. Targeted interventions resulted in significantly improved functioning in the following functional areas: sleep/rest, body care/movement, eating, and emotional balance.

Table 3.

Significant Improvement in Sickness Impact Profile (SIP) Scores for

Each Problem Code Over Time

Problem Code SIP Subscale P Value

Cognitive Sleep/Rest .031


Body care/Movement .003

Eating .001

Depression Emotional calance .011

Sleep/Rest .002

Body care/Movement .003

Eating .000

Functional Decline Emotional balance .036

Sleep/Rest .003

Body care/Movement .001

Eating .000

Medication Problem Emotional balance .017

Sleep/Rest .009

Body care/Movement .001

Eating .000

Fall Risk Emotional balance .006

Sleep/Rest .017

Body care .001

Eating .000

Incontinence Sleep/Rest .015

Body care/Movement .001

Eating .000

Social Problems Emotional balance .008

Sleep/Rest .007

Body care/Movement .002

Eating .000

The final outcome variable measured was average hospital LOS and discharge destination for each problem code as an estimate of cost. These results are in Table 4. While detailed comparisons were not performed, incontinence, fall risk, and cognitive impairment were associated with increased LOS and reduced rates of discharge to home.

Table 4.

Cost Implications

Problem Length of Stay Discharged Home

Cognitive impairment 10.7 31 (57%)

Depression 9.7 41 (70%)

Functional Decline 9.6 51 (67%)

Medication Problems 9.2 41 (68%)

Fall Risk 10.5 49 (67%)

Incontinence 12.0 17 (55%)

Nutrition Problems 10.1 49 (68%)

Social Problems 9.4 43 (71%)


The only significant difference between those who completed all times of measurement for the study and those who dropped out was their score on one subscale of the SIP (body care/movement). Patients who required more assistance were more likely to be noncompletors. Implementation rates varied across problem codes from a low of 44% (ambulate) to a high of 100% in five areas (further cognitive evaluation, psychiatry consult, change antidepressant, use assistive devices, use calorie counts). The greatest SIP scale improvements occurred for the problem code social problems where there were highly significant increases in four subscales (emotional balance, sleep/rest, body care/movement, and eating). There were significant improvements in four subscales across all problem codes for those who received interventions, with the exception of cognitive impairment and incontinence, where no improvement in emotional balance was noted. The most frequent iatrogenic complication was incontinence, which occurred in every problem category. Although LOS did not vary greatly across problem categories, patients with incontinence (11.97) and cognitive impairment had the longest stays (11.97 and 10.7 days respectively) and among the lowest rates of discharge to home.


This method of geriatric assessment led to high implementation rates, perhaps because the physicians in the study had agreed to participate a priori and were involved in the planning process. Frequent meetings between primary physicians and team members also helped build confidence and motivation, which may explain the physicians’ overall willingness to implement recommendations. The one exception was reluctance to prescribe a new antidepressant when the team recommended it. Possible explanations include fear the medication would complicate the medical regimen, the primary physicians’ familiarity with these patients and a belief they were not depressed, and lack of confidence in the assessment tool. We do know that treated patients significantly improved in their depression scores by the 3 and 6 month post-discharge measurements, a time when antidepressant medications were likely to be most effective.


Differential outcomes of an inpatient GAT intervention for specific patient problems were apparent in this study. The problems of cognitive impairment and incontinence were the least frequently identified problems, but they had the greatest effect on resource use. Patients with problems of incontinence and cognitive impairment also had the greatest LOS (11.9 and 10.7 respectively), were discharged home less frequently, and showed the least improvement on SIP subscales. Surprisingly, patients with social problems and depression were the most likely to be discharged home.

Certain patient problems may require additional attention and very specific targeted interventions. Geriatric team assessment targeted at specific problems such as cognitive impairment and incontinence, which are likely to coexist, may be more practical and effective than global assessment. With the current focus on cost containment, interventions that reduce resource use in this population are critical. A more sophisticated cost-effective analysis of the most prevalent recommendations in each problem code may direct future clinical and research efforts.

The longitudinal data collection schedule clearly documented the stepwise rather than straightforward response to interventions, which has been demonstrated elsewhere (Dellasega, Orwig, Ahern, & Lenz, 1999). Due to the time required to see the effect of certain interventions such as an antidepressant, using a longitudinal approach to study outcomes is desirable. When conducting in-hospital intervention research, it can be very important to include post-discharge evaluation of outcomes.

This study is limited by several factors. First, the physicians who participated were likely to be favorably inclined toward special interventions for geriatric patients at the onset of the study. Second, obviously many of the patients had more than one problem. The degree to which combinations of problems enhanced or detracted from the effectiveness of the interventions was not explored. A larger sample would be needed to perform this type of cluster analysis.

The pressure to trim costs while providing quality care to elderly hospital patients continues to escalate. Interventions to comprehensively address inpatient problems as well as maximize beneficial post-discharge outcomes are increasingly important in this climate. This preliminary study demonstrates the value of a targeted GAT intervention for problems experienced by at-risk elders, and indicates future direction for continued clinical and research work in this area.

This study utilized a model of consultative geriatric assessment that incorporated concepts of specificity as proposed by Weiland and Rubenstein (1996). Findings demonstrate that the interventions had an impact on the patients’ short and long-term functional and cognitive outcomes. Further clinical and research efforts to refine the GAT intervention and test its impact are underway in an effort to continue improving elderly hospital patient outcomes in a variety of domains.

Complete copies of the study protocol are available upon request from the authors.


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Cheryl A. Dellasega, PhD, GNP, is Associate Professor, Pennsylvania State University, College of Medicine, Hershey, PA.

Francis A. Salerno, MD, is Chief, Division of Geriatrics, Lehigh Valley Hospital, Allentown, PA.

Lisa A. Lacko, MSN, RN, is Geriatric Research Specialist, Lehigh Valley Hospital, Allentown, PA.

Thomas E. Wasser, PhD, is Director of Clinical Epidemiology, Lehigh Valley Hospital, Allentown, PA.

Note: A version of this paper was presented at the American Society Aging Annual Meeting in San Diego, CA, March 2000.

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