A Multifactorial Intervention to Reduce the Risk of Falling among Elderly People Living in the Community
Mary E. Tinetti, Dorothy I. Baker, Gail McAvay, Elizabeth B. Claus, Patricia Garrett, Margaret Gottschalk, Marie L. Koch, Kathryn Trainor, and Ralph I. Horwitz
Background Since falling is associated with serious morbidityamong elderly people, we investigated whether the risk of fallingcould be reduced by modifying known risk factors.
Methods We studied 301 men and women living in the communitywho were at least 70 years of age and who had at least one ofthe following risk factors for falling: postural hypotension;use of sedatives; use of at least four prescription medications;and impairment in arm or leg strength or range of motion, balance,ability to move safely from bed to chair or to the bathtub ortoilet (transfer skills), or gait. These subjects were giveneither a combination of adjustment in their medications, behavioralinstructions, and exercise programs aimed at modifying theirrisk factors (intervention group, 153 subjects) or usual healthcare plus social visits (control group, 148 subjects).
Results During one year of follow-up, 35 percent of the interventiongroup fell, as compared with 47 percent of the control group(P = 0.04). The adjusted incidence-rate ratio for falling inthe intervention group as compared with the control group was0.69 (95 percent confidence interval, 0.52 to 0.90). Among thesubjects who had a particular risk factor at base line, a smallerpercentage of those in the intervention group than of thosein the control group still had the risk factor at the time ofreassessment, as follows: at least four prescription medications,63 percent versus 86 percent, P = 0.009; balance impairment,21 percent versus 46 percent, P = 0.001; impairment in toilet-transferskills, 49 percent versus 65 percent, P = 0.05; and gait impairment,45 percent versus 62 percent, P = 0.07.
Conclusions The multiple-risk-factor intervention strategy resultedin a significant reduction in the risk of falling among elderlypersons in the community. In addition, the proportion of personswho had the targeted risk factors for falling was reduced inthe intervention group, as compared with the control group.Thus, risk-factor modification may partially explain the reductionin the risk of falling.
Falling is a serious public health problem among elderly peoplebecause of its frequency, the morbidity associated with falls,and the cost of the necessary health care1,2,3. Approximately30 percent of people over 65 years of age who live in the communityfall each year4,5,6. Unintentional injury, which most oftenresults from a fall, ranks as the sixth leading cause of deathamong people over 65 years of age1. The nonfatal results offalls include physical injury,4,7 fear,4 functional deterioration,8,9,10,11,12and institutionalization8,9,10,11. Although the total costsassociated with falls are unknown, the yearly costs for acutecare associated with fall-related fractures are estimated at$10 billion1,2.
Several potentially modifiable risk factors for falling, suchas muscle weakness, impairment in balance, and use of medications,have been identified1,4,5,6,7. Furthermore, the risk of fallingincreases with the number of risk factors present,4,7 suggestingthat a multifactorial strategy of risk-factor abatement mayreduce the risk of falling.
Uncontrolled studies have reported a potential effect of suchinterventions on the incidence of falls,13,14 but preventivestrategies have not proved effective in controlled trials todate15,16,17,18. These negative results could have occurredbecause the subjects were either at too high or too low a riskof falling to benefit or because the interventions were notintensive enough. Alternatively, falls may not be preventableamong elderly persons.
We conducted a controlled study of the effects of a programof multiple-risk-factor reduction on the incidence of fallsamong elderly people. The primary aim was to assess the effectivenessof the multifactorial targeted risk-abatement strategy in reducingthe risk of falls among elderly persons in the community. Asecondary aim was to determine whether the strategy was effectivein altering the targeted risk factors themselves.
Methods
Setting and Subjects
The details of the study design and methods have been reportedelsewhere and are summarized here19. The potential subjectswere the 2522 enrollees of a health maintenance organization(HMO) in southern Connecticut who were at least 70 years ofage. Sixteen of the 17 eligible physicians who cared for atleast 100 of these enrollees agreed to participate. For reasonspreviously described, the 16 physicians were frequency-matchedinto four groups of 4 physicians each, on the basis of theirhigh or low scores on two measures -- namely, the number ofpeople at least 70 years of age among their patients (>150vs. 150) and the mean number of new prescriptions writtenper office visit ( 1 vs. <1)19. Two physicians in each groupof four were assigned randomly to the control group, and twoto the intervention group. Enrolled subjects were assigned tothe same study group as their physicians.
The eligibility criteria, in addition to age, included independentambulation, residence outside a nursing home (i.e., in the community),no current enrollment in another study of aging, a score ofat least 20 on the Folstein Mini-Mental State Examination,20no participation in vigorous sports or walking for exercisewithin the month before enrollment, and at least one of therisk factors described below. Enrollment took place betweenOctober 1, 1990, and April 30, 1992. By means of a random-numbergenerator in SAS software on a PC computer, each patient wasassigned a priority number within the physician's practice21.Patients were screened sequentially until approximately 20 eligibleand consenting subjects were enrolled from each physician'spractice. Of the 2229 potential subjects selected randomly,1950 (87 percent) agreed to be screened. A total of 355 screenedsubjects (18 percent) met the eligibility criteria. Among theseeligible subjects, 301 (85 percent) agreed to participate; 153subjects were assigned to the intervention group, and 148 tothe control group. The eligible patients who declined to participatedid not differ significantly from the enrolled subjects in termsof age, sex, or group assignment.
Assessment and Intervention
The development of the assessment and intervention protocolshas been described in detail elsewhere19. The risk factors wereselected on the basis of evidence of their association withthe risk of falling and the availability of assessment measuresand interventions considered feasible in usual clinical practice.The risk factors we targeted and the corresponding interventionsare shown in Table 1.
Table 1. Targeted Risk Factors and Corresponding Interventions.
The base-line assessments were conducted in the subjects' homesby the study nurse practitioner and physical therapist, whowere unaware of the group assignments. The nurse practitionerobtained demographic data, a history of falls, and informationon depressive symptoms,22 the presence of chronic diseases,and the level of independence in activities of daily living23and administered the Falls Efficacy Scale, a measure of thesubject's degree of confidence in performing 10 common activities(such as walking and stair climbing) without falling,24 andthe ambulation and mobility subscales of the Sickness ImpactProfile25. She also assessed corrected near vision26 and hearing27.The names and dosages of all prescription and nonprescriptionmedications were recorded from the containers. The number ofhazards for falling was determined by a room-by-room examinationof walking paths, furniture, and stairs.
Within one week of the nurse practitioner's assessment, thephysical therapist visited the subjects to assess the risk factorslisted in Table 1. Strength and joint impairment were identifiedby manual muscle testing and tests of range of motion, respectively28,29.The assessments of balance and transfer skills30 involved observingthe subjects for instability while they were sitting, movingto and from a chair or bed, standing, carrying objects, bendingover, and reaching. Deviation from a path, missed steps, stepheight and length, stability in turning, trunk position, andappropriate use of walking aids were observed while the subjectswalked 6.1 m (20 ft) on flat and uneven surfaces.
These assessments were repeated for 250 of the 301 participants(83 percent) a median of 4.5 months after the base-line assessment.The staff members performing the reassessments did not knowthe subjects' group assignments.
Intervention Group
The subjects assigned to the intervention group received theinterventions listed in Table 1 as indicated in the base-lineassessment31,32,33,34. Decision rules and priority lists wereused to select standardized intervention protocols for eachidentified risk factor19,30. Recommendations to adjust medicationswere discussed with the subjects' primary physicians, who thenmade the final decisions.
Home visits for physical therapy involved gait or transfer-skilltraining, if needed, as well as instruction in the progressive,competency-based balance and strengthening exercise programs30.Simple illustrated instructions with large print were providedfor each exercise program. Subjects were instructed to performthe exercises twice a day for 15 to 20 minutes per session.
The intervention phase lasted three months after the base-lineassessment but was extended if the subjects had health problemsthat interfered temporarily with their ability to exercise.The maintenance phase, during which the study staff contactedthe subjects monthly, lasted from the end of the interventionphase until six months after enrollment. Adherence to the exerciseprograms, as reported by the subjects, was assessed by the physicaltherapist on a weekly basis.
Control Group
The subjects assigned to the control group received home visitsfrom social-work students, during which structured interviewswere conducted19,35. The number of social visits was matchedto the estimated number of visits by a nurse practitioner orphysical therapist that would be required for subjects in theintervention group who had comparable risk factors.
Outcome
The primary outcome we studied was the incidence of falls,24as recorded on a calendar that subjects mailed to the researchstaff monthly. The subjects were contacted by an interviewerwho was blinded to their group assignments if no calendar wasreturned or if a fall was indicated for any day of the month11.During a follow-up telephone interview, the subjects were askedabout medical care sought after falls and injuries sustained.Serious injuries included fractures, head injuries requiringhospitalization, joint dislocations or severe sprains, and lacerationsrequiring suturing24. Monitoring for falls and injuries beganon the day of the physical therapist's base-line assessment.Data on falls for one year of follow-up (or up to the occurrenceof a fall before loss to follow-up) were available for 147 subjectsin the intervention group and 144 in the control group. Reasonsfor the 10 losses to follow-up included death (n = 8), severeillness (n = 1), and a decision by the subject not to continuein the study (n = 1).
Statistical Analysis
Base-line characteristics were compared in the two study groups.The length of time to the first fall was compared in the twogroups with a log-rank test. The proportion of subjects in eachgroup who fell was compared by means of a crude relative risk.Adjusted relative risks were calculated with use of a generalizedlinear interactive model36 by modeling the logarithmically transformedoutcome probabilities as a linear function of the covariates37,38.Tests of the interaction of covariates with group assignmentwere also examined with this model. Since it was the physicians,rather than the subjects, who were assigned randomly to thetreatment groups, we tested whether our results might be dueto the observed pattern of physician assignment, using a randomizationtest39. Within each block of four physicians, all permutationsof physicians' assignment to the intervention and control groupswere obtained (n = 1296); the associated relative risks werecalculated and ranked from low to high. The calculated relativerisk for the physician-assignment pattern observed in our studywas contained in the lowest 5 percent of this normal distributionof relative risks, indicating that our findings were not duemerely to the way in which physicians were randomly assigned.Therefore, all further analyses were conducted with the studysubjects used as the unit of analysis.
The total incidence density -- that is, the total number offalls divided by the total number of person-weeks of follow-up-- was calculated as a measure of the rate of falls within eachgroup and used to obtain crude incidence-rate ratios. Adjustedincidence-rate ratios were calculated by means of a pooled logistic-regressionmodel40,41 (with SAS software on a PC computer21). Each weekof follow-up was assumed to represent an independent periodof observation and was included separately for each subject.For each week, the outcome was defined as the occurrence ofa fall or no fall, and base-line as well as time-dependent characteristicswere included as covariates. To account for the interdependenceof observations, dummy variables that modeled the number ofprevious falls (0, 1, 2, or 3) and the week of the study (1through 52) were included as potential covariates.
For subjects who had reassessment interviews, we examined theeffect of the intervention on each of the eight risk factorsby means of a chi-square test; changes in the total number ofrisk factors, the environmental-hazard score, and the scoreon the Falls Efficacy Scale were examined by analysis of covariance,with the base-line score and the study group as independentvariables. All P values are two-tailed.
Results
The base-line characteristics of the subjects in the two groupswere similar (Table 2), although a slightly higher proportionof the intervention group than of the control group had educationbeyond high school, and a lower proportion had impairment ofleg strength. The mean number of risk factors per subject wassimilar in the two groups.
Table 2. Base-Line Characteristics of the Subjects, According to Treatment Group.
There was a significant difference between the interventionand control groups in the length of time to the first fall (P= 0.05) (Figure 1) and in the proportion of subjects who fell(35 percent vs. 47 percent, P = 0.04) (Table 3); the crude incidence-rateratio for falls in the intervention group as compared with thecontrol group was 0.64 (95 percent confidence interval, 0.49to 0.83) (Table 3). The risk reduction associated with the interventionwas maintained in multivariate analyses in which we adjustedfor age, sex, previous falls, and number of risk factors, aswell as the week of follow-up for the incidence-rate ratio (Table 3).Although the numbers were small, a similar trend towarda reduction in risk in the intervention group was seen for fallsrequiring medical care or resulting in serious injury (Table 3).Seven subjects in the control group (5 percent) and foursubjects in the intervention group (3 percent) had fractures.
Figure 1. Cumulative Percentages of Subjects in the Intervention and Control Groups Who Had One or More Falls during One Year of Follow-up.
The difference between the groups was significant (P = 0.05, by the log-rank test). The numbers still at risk for a fall at 3, 6, 9, and 12 months are shown below the figure. Only 10 of the subjects were lost to follow-up: 6 in the intervention group and 4 in the control group. Data on subjects were censored after a fall. The cumulative relative risks are shown for 3, 6, 9, and 12 months of follow-up.
Table 3. Incidence of Falls and Other Events during One Year of Follow-up, According to Treatment Group.
The mean (±SD) change in the scores on the Falls EfficacyScale, on which higher scores indicate greater self-confidence,differed significantly (P = 0.02) between the control group(-1.2 ±4.9) and the intervention group (+0.2 ±3.9),with adjustment for the base-line score. There was no significantdifference between the two groups in the mean change in theSickness Impact Profile scores.
Targeted Intervention Process
The subjects in the intervention group received a mean of 7.8±4.0 home visits (range, 0 to 22), as compared with 6.2±3.8 (range, 0 to 14) for the control subjects (t = 3.62,P<0.001). Eleven subjects in the intervention group did notcomplete the intervention phase, including eight who declinedto do so and three in whom intervening illnesses developed.
Table 4 shows the number of subjects in the intervention groupwith each risk factor and the types of interventions they received.The most common reason for not receiving an intervention fora risk factor was the presence of factors with a higher priorityor a contraindication to the intervention.
Table 4. Subjects in the Intervention Group Who Received Interventions and Types of Interventions Received.
Subjects in the intervention group reported performing 73 percentof the recommended exercise sessions, for a mean of 10 sessionseach week. Sixty-five percent of these subjects performed atleast 70 percent of sessions; 85 percent of subjects performedover half of the exercise sessions.
Risk factors were reassessed for 131 members (86 percent) ofthe intervention group and 119 members (80 percent) of the controlgroup a median of 4.5 months after the base-line assessment.The percentage of subjects in the intervention and control groupswho had a risk factor at base line and continued to have itat reassessment is shown in Table 5. At reassessment, a significantlysmaller percentage of the intervention group than of the controlgroup continued to use at least four prescription medications,to transfer unsafely to bathtub or toilet, or to have impairmentin balance or gait. Overall, the intervention group had a meandecline of 1.1 ±1.6 in the total number of risk factors,as compared with a decrease of 0.6 ±1.4 in the controlgroup (P = 0.03). When the change in the number of risk factorswas added to the model predicting the occurrence of falls amongthe 242 subjects with complete reassessment data, treatmentassignment was no longer significant, and the risk of fallingdeclined by 11 percent (adjusted relative risk, 0.89; 95 percentconfidence interval, 0.79 to 1.00) for each decrease of 1.0in the number of risk factors.
Table 5. Subjects with Each Risk Factor at Base Line Who Had the Risk Factor at Reassessment.
Adverse Events
As shown in Table 3, there was no significant difference inthe number of subjects in the two groups who died or were hospitalized,although those in the inter-intervention group had fewer hospitalizationsand fewer hospital days. The musculoskeletal symptoms of 10subjects in the intervention group were thought to be probablyrelated to the exercise program. All these events were self-limited.
Cost Effectiveness
The total cost of the intervention, including development, equipment,personnel, travel, and overhead costs, was $136,318, or an averageof $891 per subject in the intervention group. The cost perfall prevented ($136,318 divided by 70 [164 falls in the controlgroup - 94 in the intervention group]) was $1,947. The costfor preventing one fall that required medical care was $12,392.
Discussion
Contrary to the results of earlier intervention trials,15,16,17,18the targeted-intervention strategy reported here was associatedwith a reduction in the proportion of subjects who fell andin the incidence of falls. Although the numbers were small,the subjects in the intervention group also reported fewer injuriesand fewer episodes of medical care associated with falls. Selectingstudy subjects at risk for falling, targeting multiple modifiablerisk factors, and implementing the interventions ourselves mayall have contributed to the effectiveness of the intervention.Although it is not possible to determine whether risk-factorreduction was definitely responsible for the decrease in falls,the reduction in the number of risk factors in a larger proportionof the intervention group than of the control group, the reductionin the effect of treatment when the change in risk factors wasadded to the model, and the relation between the change in thenumber of risk factors and the incidence of falls all suggestthat risk-factor reduction at least partially explained thedecrease in the occurrence of falls.
The greatest difference between the two groups was among subjectswith impairments in balance or transfer skills and among thosewho took four or more prescription medications. The effect onmedications in the subjects in the intervention group couldhave resulted directly from the nurse's counseling the patientsand contacting physicians. In addition, several physicians reporteda heightened awareness of the relation between medications andfalling and of the frequency of postural hypotension. Similarproportions of subjects in the control and intervention groupsreported no longer using sedatives at the time of reassessment,perhaps reflecting intermittent use of these medications.
The absence of a greater effect of the interventions on musclestrength could be explained by the fact that manual muscle testingis insensitive to change. Also, because of the priorities assignedto the various risk factors, some subjects with muscle weaknessdid not receive instructions for a strengthening exercise program.Even for the muscle groups exercised, the intensity or durationof the exercise program may not have been great enough to effectimprovement.
As is often observed in clinical trials, a high proportion ofcontrol subjects had reductions or improvement in the risk factors42.Inherent variability in the risk factors, heightened motivationamong subjects participating in a trial, and reassessment selectivelybiased toward healthier subjects could all explain the improvementin the control subjects. Regardless of the reasons, the higherproportion of subjects in the intervention group who had improvementin blinded assessments suggests that the intervention did havea positive effect on these risk factors.
Several of our methods deserve comment. The use of a matched-blockdesign, rather than purely random sampling, was necessary toprevent the contamination of results that might have occurredif physicians had cared for subjects in both control and interventiongroups19. The groups appeared well matched, and simulation modelingrevealed a similar effect of the intervention among all thephysicians' patient groups.
As is typical of patients enrolled in HMOs, a high proportionof the subjects were white and had more than a high-school education.We believe the selection of the HMO setting was essential toensure that the physicians seen by the subjects were an integralpart of the medication protocols. The generalizability of theeffects of the intervention will need to be determined in otherhealth care settings.
More complete reporting of falls could have occurred in theintervention group than in the control group because of thegreater attention received by the subjects in the interventiongroup, whereas underreporting could have occurred if those subjectshad perceived that investigators wanted to see a reduction infalls. Bias alone, however, is unlikely to explain fully thedifferences between the two groups, since similar trends wereseen in terms of falls requiring medical care and falls causinginjury, events less susceptible to reporting bias.
This risk-reduction strategy could readily be implemented aspart of the clinical care of elderly patients. Third-party reimbursementwill be more likely if there is evidence of savings due to treatmentsthat were prevented. For falls requiring medical care, the costper fall prevented -- $12,392 -- compares favorably with a meancharge of $11,800 per hospitalization for injuries caused byfalls among persons 65 years of age or older43. Indeed, a completeanalysis of total and fall-related health care costs may showthe intervention to result in a net cost savings.
Finally, because many of the risk factors for falling also contributeto immobility and functional decline, the strategy studied herecould result in a reduction in the incidence of falls as wellas in an improvement in functional independence among elderlypatients. This improvement in function is likely, since theintervention not only reduced the number of risk factors anddecreased the incidence of falls, but also increased the subjects'confidence in performing daily activities -- an important independentdeterminant of daily functioning44.
Supported by a grant (UO1 AG09087) from the National Instituteon Aging. Dr. Tinetti was a Kaiser Family Foundation FacultyScholar.
We are indebted to Leo Cooney, M.D., for reviewing the manuscript,to Margaret Carlson and Betty McLellan for assistance in thepreparation of the manuscript, and to the physicians and staffof the Community Health Care Plan for their outstanding cooperationin carrying out this study.
Source Information
From the Departments of Medicine (M.E.T., P.G., R.I.H.) and Epidemiology and Public Health (G.M., E.B.C., K.T.), Yale University School of Medicine, and the Yale University School of Nursing (D.I.B.), New Haven, Conn.; the Department of Rehabilitation Services, Yale-New Haven Hospital, New Haven, Conn. (M.G.); and the Department of Physical Therapy, Quinnipiac College, Hamden, Conn. (M.L.K.).
Address reprint requests to Dr. Tinetti at 333 Cedar St., P.O. Box 208025, New Haven, CT 06520-8025.
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150) and the mean number of new prescriptions written per office visit (
1 vs. <1)19. Two physicians in each group of four were assigned randomly to the control group, and two to the intervention group. Enrolled subjects were assigned to the same study group as their physicians. 
