Differences in Nursing Homes With Increasing and DecreasingUse of Physical Restraints
NICHOLAS G. CASTLE, PHD
OBJECTIVES. This article examines the organi-zational characteristics of nursing homes asso-ciated with increasing and decreasing use ofphysical restraints since the implementation ofthe Nursing Home Reform Act (NHRA) in1991.
METHODS. Nationally representative datafrom the 1992 and 1997 On-Line Survey Certi-fication of Automated Records are used first toprovide descriptive analyses and second formultinomial logistic regression analyses of or-ganizational factors associated with an in-crease or decrease in physical restraint use.
RESULTS. The results show that 2,331 nursinghomes increased their use of restraints by >4%and 2,100 decreased their use of restraints by>3%. Ownership, Alzheimer’s special careunits, and average occupancy rates have bidi-rectional influence and are associated withboth decreases and increases in restraint use,depending on their values. Chain membershipand staffing levels of rehabilitation services
are associated with increases in restraint use,whereas Medicaid census and private-pay cen-sus are associated with decreases in restraintuse. Change factors were also important. Anincrease in Medicaid census and a change tochain membership since 1991 have an unset-tling effect on care practices, increasing re-straint use.
CONCLUSIONS. Although the period used inthis analysis represents a time frame in whichthe restraint reduction mandates of the NHRAwere in effect, these results show that somenursing homes have increased their use ofphysical restraints. The organizational charac-teristics of these nursing homes differ fromthose that decreased their use of physical re-straints.
Key words: Restraints; On-Line Survey Cer-tification of Automated Records; NursingHome Reform Act. (Med Care 2000;38:1154–1163)
In nursing home inspections conducted by statelicensure and certification agencies, residents whoare physically restrained are defined as thosewhose “freedom of movement and/or normal ac-cess to his/her body is restricted by any manualmethod or physical or mechanical device that isattached . . . and cannot be easily removed by theresident.”1 These physical restraints include vests,
belts, mittens, wrist and ankle restraints, andchairs with locking trays (often called geri-chairs).
Physical restraints have been used in nursinghomes for many decades.2 Their use was especiallyprevalent for violent residents and those with mentalillnesses.3 However, restraining the nonviolent andnon–mentally ill became widespread. Why this hap-pened and when it began are unclear,2 but as a
From the Institute for Health, Health Care Policy, andAging Research, New Brunswick, New Jersey.
Address correspondence to: Dr Nicholas Castle, In-stitute for Health, Health Care Policy, and Aging Re-search, 30 College Ave, New Brunswick, NJ 08901.E-Mail: [email protected]
Supported in part by a grant from the NationalInstitute of Mental Health, MH58553-01.
Received January 18, 2000; initial review completedMarch 14, 2000; accepted August 30, 2000.
result, rates of restraint use have been reported to beas high as 84% of residents in some facilities.2
During the 1980s, there was an outcry againstthese now endemic restraint practices in nursinghomes. Both press reports4 and empirical re-search5–7 condemned their use. Three factors arethought to have influenced these objections: thepotential negative effects of physical restraints, achanging moral climate, and restraint practices inother countries. A recent review of physical re-straint use in nursing homes expands on thesefactors.8
See p 1151
These influences came to fruition in 1987 in theform of the Nursing Home Reform Act (NHRA).This legislation mandated that nursing homesreduce their use of physical restraints and thatresidents have the right to be free from anyphysical restraint imposed for purposes of disci-pline or convenience and not required to treattheir medical symptoms.8
The overall prevalence of restraint use in nurs-ing homes has decreased since the introduction ofthis legislation.9–13 National data show that theaverage percent of restrained residents in nursinghomes was 44% during 19891 and 16% during1997.1 However, these aggregate data may hide adisconcerting trend. That is, anecdotal evidencesuggests that some nursing homes may haveactually increased their use of physical restraintssince the implementation of the NHRA in 1991.
The reasons why some nursing homes mayhave increased their use of physical restraints areunclear, although it is known that restraint reduc-tion was not welcomed by all in the industry.14 Itwas thought that restraint reduction would in-crease the cost of care because of increased staffingrequirements. Some studies estimated that reduc-ing restraints under the NHRA mandate couldcost the nursing home industry as much as $1billion.14 Additionally, some staffs in nursinghomes continue to justify their use of restraintsbecause they believe that they protect the facilityfrom liability, protect residents from falls, preventagitated residents from hurting themselves andothers, and enable the use of other medical de-vices such as intravenous lines.8
Thus, although a number of nursing homes mayhave increased their use of physical restraints inthe face of the NHRA, little is known about thesefacilities. Yet, this information is important. Nurs-
ing homes that have increased restraint use maybenefit from educational initiatives designed toreduce their use. Clearly, in these cases, the healthand satisfaction of residents may also be im-proved.
Recent literature shows that organizationalcharacteristics of nursing homes are associatedwith restraint use. For example, using the 1991On-Line Survey Certification of AutomatedRecords (OSCAR) data from 195 nursing homes inNorth Carolina, Graber and Sloane13 found facil-ities with higher ratios of licensed vocational nurs-e(s)/nurse aide(s) and greater average disabilitylevels to be associated with the use of restraints.13
Results from the Cohen-Mansfield et al15 studyalso suggest that studying intrafacility, nonclinicalfactors associated with restraint use may be pro-ductive. Examining patterns of physical restraintuse measured according to location (eg, resident’sroom, living area), time of day, and staff habits,they found that restraints were utilized most oftenwhen the resident was located in an isolated areaof the facility, on Saturdays, and if the staff wereaccustomed to previous high levels of restraintuse.14
More recently, Phillips et al14 suggest that nursestaffing levels are associated with restraint use.Another study16 shows that staffing levels, occu-pancy rate, and special care units are associatedwith restraint use.
To date, no studies have differentiated betweennursing homes that have increased or decreasedtheir use of restraints. Given that a number ofnursing homes may have increased their use ofphysical restraints contrary to the NHRA mandate,these facilities differ from those that have de-creased their use of restraints. Therefore, this studyextends previous research by comparing the orga-nizational characteristics of nursing homes asso-ciated with increasing use of physical restraintswith nursing homes that have decreased their useof physical restraints since the implementation ofthe NHRA.
Methods
Data
Data used in this investigation came from the1992 and 1997 OSCARs. The OSCAR is conductedby state licensure and certification agencies as partof the Medicare/Medicaid certification process and
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includes most US facilities. In 1992, 15,455 facili-ties were included in the data; in 1997, 16,533facilities. Those facilities that are neither Medicarenor Medicaid certified (;800 in 1992 and ;1,000in 1997) are not included. The exclusion of thesefacilities in the OSCAR data may have someimpact on the overall representativeness of ourresults, but clearly in the absence of data, onecannot determine whether these facilities in-creased or decreased their use of restraints.
There are ;300 data elements in the OSCAR,most of which are either organizational or aggre-gate resident data. Facility data relevant to thisstudy are staffing levels, chain membership, occu-pancy rate, and ownership characteristics. Resi-dent data elements relevant to this study includethe number of residents who are restrained, arecatheterized, have psychiatric problems, or aregiven psychotropic medications.
The OSCAR data are widely used. First, they areoften used by researchers as a secondary source ofnursing home characteristics.2,16–18 Second, thedata are publicly available on the Health CareFinancing Administration Web site, in addition tomany individual state Web sites. Third, the data arefrequently used by the General Accounting Of-fice.19–22 However, even with this degree of appar-ent consensus regarding the usefulness of thedata, some limitations are evident.
Many of the facility characteristics in the OS-CAR data are self-reported by the nursing homeadministrator and director of nursing. It is doubtfulwhether facility factors such as ownership, chainmembership, or bed size are subject to reportingbias because these factors are often found onbusiness records readily available to surveyors. Inaddition, the facility may be fined for any misrep-resentation of these variables. Most data elementspertaining to resident characteristics are obtainedby direct observation by the surveyors, includingthe use of restraints, activities of daily living(ADLs), continence, and medications. However,these data are limited because 24-hour observa-tion is not possible. The information the surveyorsreport is pertinent only for the time they makerounds in the facility, usually during the day shift.The use of physical restraints may be biasedbecause other shifts may not follow day-shiftpractices; ie, restraint use may be higher at nightwhen staffing levels are lower. Clearly, it is notpossible to determine whether the present analy-sis is biased in this way; if it is, then this analysis isprobably most representative of residents who are
chronically restrained most of the time, includingthe day, evening, and night shifts. No prior noticeis given when surveyors inspect facilities; however,in reality, inspections are conducted every 9 to 15months. Facility practices may change when aninspection is anticipated. In addition, interraterreliability testing has not been performed for thedata as a whole, and such biases are generallyunknown.
Analytic Model
Given prior findings showing a relationshipbetween the organizational factors facility size,16
residence in special care units,14,16 staff-to-patientratios,13 and occupancy rate16 in the use of re-straints, these factors were included in this analy-sis. In addition, ownership,23 chain membership,24
and census factors25 are included because they aresignificant variables in examinations of the utili-zation of other nursing home services. In thisanalysis, these organizational variables are dividedinto structural, staffing, and census factors. Thedivisions follow the work of others16,26 and merelyorganize the variables.
Recent data may not accurately reflect the over-all standing of a facility on these structural, staff-ing, and census factors since the implementationof the NHRA. Facilities may have added specialcare units or become members of nursing homechains, for example. Because of the longitudinalnature of the data, it is possible to include vari-ables representing changes in these factors duringthe study period.
Aggregate resident factors known to be impor-tant in the investigation of restraints are includedas controls. These include ADLs,8,24,27 urinary in-continence,8,24 bowel incontinence,8,24 use of psy-choactive medications,8,23,24 and psychologicalstatus.8 In general, as resident acuity increases, asmeasured by these factors, restraint use is morelikely. Because acuity levels in nursing homes havegenerally increased in recent years, the changescore from 1992 to 1997 for each of these factors isalso included.
Operationalization of Variables
A resident is defined in the OSCAR as re-strained when $1 of the following devices is used:vests, belts, mittens, wrist and ankle restraints, and
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chairs with locking trays (geri-chairs). However,bed rails are not included.1 The use of theserestraints as observed by surveyors conducting theOSCAR survey is used in this analysis. Therefore,this is an observed measure, not an assessment ofmedical records or orders for restraint use. And, asdiscussed above, these checks occur during theday; therefore, the data are probably most repre-sentative of day-shift practices.
The number of beds in each facility is used as ameasure of organizational size. A dichotomous(eg, 0,1) ownership category, for-profit and not-for-profit, is used to represent ownership. If anursing home is a member of a nursing homesystem, it is categorized as a member of a chain.Likewise, if the nursing home has a special careunit, it is categorized as such. The full-time equiv-alent (FTE) hours of RNs, LPNs, and nurse aidesper 100 beds are included as nurse staffing vari-ables. FTE hours of speech, occupational, andphysical therapists per 100 beds are combined inthe rehabilitation services variable. The occupancyrate variable is created by dividing the averagecensus rate by the total bed size. Similarly, thenumbers of Medicaid and private-pay residentsare divided by the total bed size to create variablesrepresenting the proportional utilization of totalcapacity by Medicaid and private-pay residents,respectively.
The number of residents with urinary inconti-nence, those with bowel incontinence, and thosereceiving psychoactive medications is recorded inthe OSCAR. As with the restraint use variable,these are observed by the surveyors. These num-bers are divided by the overall occupancy to createvariables indicating the percent of residents witheach. The OSCAR data also contain informationregarding transfer, locomotion, dressing, eating,toilet use, and bathing of residents. These itemsare combined to create an average facility ADLscore.28 This score ranges from 0 to 1; higherscores indicate greater average ADL impairmentwithin the facility. Other resident information in-cludes the number of residents with psychologicaldisorders that were used to create a variableindicating the percent of residents with theseconditions in each nursing home.
Analytic Approach
Facilities with OSCAR data from both 1992 and1997 are used in this analysis. Because of delays in
reporting and collation of the data, the 1992OSCAR primarily contains information from 1991.This corresponds with the implementation of theNHRA in December 1991. The October 1997OSCAR is the second data source used. Thus,change in restraint use as our dependent variableis calculated from 1992 to 1997 and represents anysuch change since the implementation of theNHRA.
The initial analytic sample consisted of 15,455nursing homes at the 1992 baseline. Because ofdifficulties matching nursing homes from year toyear, some facilities were excluded from the sam-ple. This problem arises because nursing homesdo not necessarily keep the same federal identifi-cation number from inspection to inspection. Thefederal identification numbers are the primarysource of nursing home identification in the OS-CAR; however, facilities that change management,ownership, or location are often given new num-bers. Therefore, in this analysis, for those homeswith unmatched federal identification numbersfrom 1992 to 1997, facility name, address, and ZIPcode were used to link facilities. Missing cases stilloccurred, and ;12% (n 5 1,864) of nursing homesidentified in 1992 were excluded because theycould not be identified in 1997. This reduced theanalytic sample to 13,591 facilities. Hospital-basedfacilities or facilities that are part of a retirementcenter were further excluded because they tend tobe unrepresentative of other nursing homes interms of staff, clients,29 and organizational charac-teristics (n 5 1,212).30 Restraint use practices mayalso be different in these facilities.8 This reducedthe sample to 12,379 facilities.
There were very few missing data on any of thedependent or independent variables. Insufficientdata were present in 41 cases for the dependentvariable. In most cases, information for the inde-pendent variables in these analytic samples wasavailable and represented between 0% and 5% ofthese variables. All missing values for continuousor ordinal variables were imputed using meansubstitution, and dichotomous variables were ran-domly assigned 0 or 1 values according to thebinomial distribution with a probability as ob-served for the complete cases.31 The results re-ported are robust in that imputation did notproduce any significant change in our resultscompared with analyses performed before imput-ing missing data values.
Data entry errors occur in the OSCAR. Severalmethods were used to correct these errors. First,
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frequency distribution plots were used to identifyobvious outliers. Imputation, as described above,was used to replace ,1% of data values. In othercases, data errors are not so obvious. To helpidentify these cases, the upper 5% of variablevalues were examined longitudinally. That is,when possible, facilities were examined to deter-mine whether inconsistent values occurred from1992 to 1997 for the variables of interest. Elevatedvalues for 1992 or 1997 were assumed to be dataerrors. Imputation was used to replace these val-ues. This resulted in the correction of ,1% ofobservations. These were corrected using the 1992to 1997 average values for each facility. Limitationsof this approach are that systematic reportingerrors are not detected and improbable lowervalues are more difficult to identify.
A similar approach was used to examine poten-tial data errors in the dependent variable. Fewerthan 1% of facilities were excluded from theanalyses because of potential data errors with theproportion of residents physically restrainedwithin each nursing home, resulting in a finalanalytic sample of 12,193 facilities
This study examined the correlation betweenthe variables to identify whether the data had anyproblems of collinearity (not reported). Most of thecorrelations were small. The highest correlationswere found between facility size and staffing lev-els, although based on a threshold of 0.8, thevariables showed no problems of collinearity.32
Statistical Methods
The subject of this investigation is facilities withincreasing use of physical restraints, and it isposited that these facilities are distinct from thosewith decreasing use. However, both of thesegroups also probably differ from facilities withlittle increase or decrease in their use of restraints.Therefore, a multinomial logistic regression modelwith 3 possible outcomes is used: (1) increasingrestraint use, and the competing risks of (2) de-creasing restraint use and (3) stable use of re-straints. The last outcome is used as the referencegroup, and the other variables are estimated inrelation to this group.
Multinomial logistic regression is a generaliza-tion of the more commonly used dichotomouslogistic regression, which may be used when thereis an alternative outcome category that may occurinstead of the event of interest. The risk (adjusted)
of increased restraint use is estimated relative toother, and the risk (adjusted) of decreasing re-straint use relative to other. In this way the “com-peting” outcomes of increasing and decreasingrestraint use are controlled for. In this analysis, thatreferent group is nursing homes with stable re-straint use. Clearly, stable restraint use can beoperationalized in many ways. To facilitate multi-nomial logistic regression, the following distribu-tion of restraint use change scores from 1992 to1997 was used: facilities with a change of 23% to235% were defined as nursing homes decreasingtheir restraint use; facilities with a change of lessthan 23% to 4% were defined as stable; andfacilities with a change of from .4% to 25% weredefined as nursing homes increasing their restraintuse. These levels are arbitrary, but in sensitivityanalyses with varying cutoff values, the resultswere robust.
Results
Table 1 presents descriptive statistics of thevariables used in the analysis. This study foundthat an average of 22% of residents in nursinghomes in 1992 and 16% in 1997 were restrained.However, underlying this change in restraint use,this study found that 19% of facilities increasedtheir restraint use by $4%, 7% of which hadincreases .10%.
Adjusted odds ratio (AOR) estimates and 95%CIs for the multinomial logistic regression modelexamining the increase and decrease in restraintuse from 1992 to 1997 are presented in Table 2.The results for facilities increasing restraint use arepresented in the first column. Examining thestructural factors, we can see that for-profit facili-ties and members of chains are more likely toincrease their restraint use, while facilities withAlzheimer’s special care units are less likely toincrease their restraint use. Facilities that changedownership to become for-profit or a member of achain are more likely to increase their restraint use.Few of the census factors are significant. Facilitieswith a higher average occupancy are more likely toincrease their restraint use, as are those with anincrease in Medicaid census. Facilities with moreFTE RNs per 100 beds are less likely to increasetheir restraint use, and those with more nurseaides per 100 beds are more likely to increase theirrestraint use. The FTE nurse aides per 100 beds hasa particularly strong effect; with an AOR of 3.72,
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facilities with average nurse aide staffing (27 FTEsper 100 beds) are almost 1.5 times more likely toincrease restraint use. Some of the control vari-ables are also significant. ADLs have a particularlystrong effect. Facilities with high ADL scores(more physical impairment) are more likely toincrease their restraint use.
The second column of Table 2 examines de-creasing restraint use. This shows that larger facil-ities and those with Alzheimer’s special care unitsare more likely to decrease their restraint use.For-profit facilities and facilities that changedownership to become for-profit are less likely todecrease their restraint use. All but one of thecensus factors are significant. Facilities with ahigher average occupancy and those with a highMedicaid census or an increase in Medicaid censusare less likely to decrease their restraint use. Ahigh private-pay census and an increase inprivate-pay census are associated with decreasingrestraint use. Private-pay census has a particularlystrong effect; with a AOR of 2.49, facilities with anaverage private-pay census (26%) are 1.3 times
more likely to decrease restraint use. Facilities withhigher FTE rehabilitation services per 100 beds aremore likely to decrease their restraint use. Facilitieswith an increase in FTE LPNs per 100 beds or FTErehabilitation services per 100 beds are more likely todecrease their restraint use. Facilities with an in-crease in FTE nurse aides per 100 beds are less likelyto decrease their restraint use. Several of the controlvariables are also significant. Of note, facilities withhigher ADL scores (indicating more physical impair-ment) are less likely to decrease their restraint use, asare those with increasing ADL scores.
It is interesting to note that some factors, suchas ownership, Alzheimer’s special care units, andaverage occupancy rates, have bidirectional orlinear effects and are associated with both de-creases and increases in restraint use, dependingon their values. In contrast, chain membership andstaffing levels of rehabilitation services are associ-ated only with increases in restraint use, whereasMedicaid census and private-pay census are asso-ciated only with decreases in restraint use.
TABLE 1. Descriptive Statistics for Study Variables in 1992 and 1997
Increase in bed size (AOR/10-bed increase) 0.99 (0.98–1.00)† 1.00 (1.00–1.00)For-profit ownership (AOR for 1 vs 0) 1.20 (1.07–1.36)‡ 0.87 (0.72–1.00)*Change to for-profit ownership (AOR for 1 vs 0) 1.37 (1.00–1.90)* 0.79 (0.63–1.00)*Chain membership (AOR for 1 vs 0) 1.31 (1.16–1.45)‡ 0.99 (0.83–1.19)Change to chain membership (AOR for 1 vs 0) 1.76 (1.67–1.89)‡ 0.90 (0.74–1.12)Alzheimer’s special care unit (AOR for 1 vs 0) 0.77 (0.62–0.98)* 1.32 (0.98–1.77)*Addition of an Alzheimer special care unit (AOR for 1 vs 0) 1.11 (0.93–1.31) 0.94 (0.75–1.18)
Census factorsAverage occupancy (AOR for 100% vs 0%) 1.62 (1.00–2.61)* 0.34 (0.20–0.57)‡
Increase in average occupancy (AOR for 100% vs 0%) 1.00 (0.65–1.55) 1.37 (0.75–2.51)Medicaid census (AOR for 100% vs 0%) 0.81 (0.51–1.29) 0.27 (0.12–0.57)‡
Increase in Medicaid census (AOR for 100% vs 0%) 1.61 (0.97–2.68)* 0.38 (0.21–0.66)‡
Private-pay census (AOR for 100% vs 0%) 1.30 (0.79–2.14) 2.49 (1.17–5.11)*Increase in private-pay census (AOR for 100% vs 0%) 1.21 (0.72–1.95) 1.42 (1.18–1.97)*
Increase in FTE rehabilitation services/100 beds 1.00 (1.00–1.00) 1.11 (1.01–1.40)†
Control factorsADLs (AOR for 1 vs 0) 7.48 (4.10–14.12)‡ 0.89 (0.16–0.98)‡
Increase in ADLs (AOR for 1 vs 0) 1.24 (0.78–2.00) 0.35 (0.16–0.69)†
Incontinent bladder (AOR for 100% vs 0%) 1.36 (0.76–2.43) 1.89 (0.88–4.19)*Increase in incontinent bladder (AOR for 100% vs 0%) 1.18 (0.75–1.89) 0.70 (0.37–1.44)Incontinent bowel (AOR for 100% vs 0%) 2.74 (1.54–4.72)‡ 0.85 (0.38–1.82)Increase in incontinent bowel (AOR for 100% vs 0%) 1.11 (0.71–1.71) 0.72 (0.40–1.41)Antipsychotic medications (AOR for 100% vs 0%) 0.86 (0.59–1.23) 1.35 (0.83–2.11)Increase in antipsychotic medications (AOR for 100% vs 0%) 2.11 (1.59–2.80)‡ 0.66 (0.46–0.93)†
Psychiatric problems (AOR for 100% vs 0%) 1.18 (0.17–8.12) 3.78 (0.64–9.35)Increase in psychiatric problems (AOR for 100% vs 0%) 1.66 (1.53–1.85)‡ 0.90 (0.64–1.31)
n 5 12,193. This table shows a multinomial logistic regression. The first column shows the variables used in the analyses;the unit increase the AOR represents is given in parentheses. The second column shows the estimated AOR of increasedrestraint use relative to other, and the third column shows the estimated AOR of decreasing restraint use relative to other. Thereferent group is nursing homes with stable restraint use. Ratios .1 imply increased odds; those ,1, decreased odds(according to the specified unit increase given in parentheses). For example, facilities with Alzheimer’s special care unitsexperience a 1.32 increase in the odds of decreased restraint use relative to those without an Alzheimer’s special care unit. Afacility going from 0% occupancy to 100% occupancy experiences a 1.62 increase in odds of increased restraint use. For staffingfactors, the AOR is per 10-FTE increase per 100 beds. The upper and lower 95% CIs for the ORs are given in parentheses.
*Statistically significant OR at the P # 0.05 level.†Statistically significant OR at the P # 0.01 level.‡Statistically significant OR at the P # 0.001 level.
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Discussion
This investigation examines nursing homes’ in-creasing and decreasing use of physical restraintsfrom 1992 to 1997. Although this period represents atime frame in which the restraint reduction man-dates of the NHRA were in effect, our descriptiveanalysis shows that 2,331 nursing homes actuallyincreased their use of restraints. Clearly, the NHRAhas been extremely influential in reducing the overallprevalence of restraint use in nursing homes,8,10,14
but the number of facilities increasing their use ofrestraints in the face of this legislation is high.
For the nursing home industry, ownership, Alz-heimer’s special care units, and average occupancyrates appear important in both decreasing and in-creasing restraint use. In contrast, the organizationalfactors of chain membership, Medicaid census,private-pay census, and staffing levels of rehabilita-tion services differ in their influence on nursinghomes’ decreasing and increasing restraint use. Ingeneral, the change factor variables such as increas-ing Medicaid census were also important. Theseresults are discussed further in the following text.
The organizational goals and resultant behaviorof for-profit and not-for-profit providers may bedissimilar.33 For-profit nursing homes are oftenseen as profit oriented and as a result may be lessaggressive in implementing costly resident careservices.33 Not-for-profit nursing homes are oftenseen as more altruistic and as a result may be moreaggressive in implementing resident care services,regardless of costs.34 With respect to restraint use,the results of this analysis lend some support tothese beliefs. Although it should be noted that, ingeneral, empirical research comparing these orga-nizational types has not produced a consistentpicture corroborating either of these general be-haviors.35,36 Moreover, our results do not includethe myriad other resident care services that shouldalso be used to compare these facilities.
It is also worth noting that the assumption ofrestraint reduction as being expensive is question-able. A recent study has shown that reducing re-straints in some cases may be cost effective.10 As-suming that this study is correct, from the standpointof profitability, it would be counterproductive forfor-profit facilities not to decrease restraint use.Clearly, however, more research is needed to test therobustness of the findings of this study.
Facilities with Alzheimer special care units arefound to be less likely to increase restraint use andmore likely to decrease restraint use. Because
many Alzheimer special care units are restraintfree or actively promote restraint reduction, thisresult is intuitive. However, the operationalizationof this effect is ambiguous. Most Alzheimer specialcare units are small (mean size, 12 beds), so it isimprobable that these isolated treatment areaswould have a significant effect on the aggregatestatistics reported in this analysis. It is more likelythat the treatment of residents in Alzheimer spe-cial care units is consistent with how residents arecared for outside the unit. The efficacy of specialcare units has been questioned,37 but this analysissuggests that cross-fertilization of care practicesmay be one benefit.
Some research has shown that higher occu-pancy rates are associated with less desirableresident outcomes, such as an increase in theprevalence of pressure ulcers.38 Nyman36 suggeststhat nursing homes operating with high occu-pancy rates have less incentive to provide qualitycare. The results of this analysis corroborate thispremise for both increasing and decreasing use ofphysical restraints. The effect of occupancy rate ismuch stronger in decreasing the likelihood of adecrease in restraint use than on increasing thelikelihood of an increase in physical restraint use.
Recent evidence would suggest that chain mem-bership is important in examinations of care process-es.37 In theory, when a facility is a member of a chain,some economies of scale should be achieved. Forexample, the purchasing of equipment and suppliesmay be less expensive. These cost savings may beused in resident care. However, the results of thisanalysis suggest that chain nursing homes are morelikely to increase restraint use.
The results for Medicaid census were expectedto provide a parallel to those for private-paycensus. The majority of persons in nursing homesare either Medicaid or private-pay residents. Med-icaid recipients provide a low level of funding tonursing homes, and as a consequence, it may bedifficult for facilities to provide some services. Toavoid dependence on Medicaid payments, manynursing homes have focused on the private-paymarket because they have greater latitude in es-tablishing the price of services they provide tothese residents. To do so, nursing homes should bemore willing to provide additional services. There-fore, the effects of Medicaid and private-pay cen-sus identified in this analysis are congruent withthose expected. The results show that in nursinghomes with a higher Medicaid census, a decreasein restraint use was less likely.
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An increase in Medicaid census and a change tochain membership also increased the likelihood ofan increase in restraint use. These changes may havean unsettling effect on care practices, leading to anincrease in restraint use. Facilities undergoing sub-stantial reorganization, or as our control factorsshow, a change in resident case-mix, should becognizant that resident care patterns may also war-rant further attention to avoid potentially negativeresident outcomes.
Clearly, staffing patterns in nursing homes havean impact on resident care. For example, a highstaff-to-patient ratio was previously shown to beassociated with reductions in physical restraint use16
and with surveyor-imposed citations for restraintuse.13 Restraint-free facilities were also shown tohave a richer mix of nursing staff.17 The results of thisinvestigation suggest that facilities increasing anddecreasing their restraint use are also dependent onthe staffing levels of nurses. The staffing levels ofrehabilitation services also show a significant positiverelationship with decreasing restraint use.
The provision of individualized care alternatives torestraints are seen as intricate, involving professionaleducation to achieve levels of observation and as-sessment necessary for planning and implementingattentive care from staff.8 Rehabilitation service staffmay be able to respond to these challenges.
The dependent variable is somewhat imprecise in2 ways. First, restraint use is identified only at thetime of the Medicare/Medicaid certification inspec-tion. Second, some facilities have adopted devicesnot formally determined by regulators to be re-straints. Most notably, this includes belts with Velcrofasteners.38 Residents may not be able to unfastenthese devices; therefore, they serve the same purposeas traditional restraints.38 With the OSCAR data,there is no way to determine whether these types ofrestraints are used by facilities.
This study examined data only at 2 points in time.One problem with this approach is that the resultsfor some facilities may only be representative atthese 2 points of time. This approach does not showmany of the fluctuations, trends, or patterns thatcould occur from 1992 to 1997 with the variables weuse. The use of more data points would provide amore refined test of facility characteristics associatedwith increasing and decreasing use of physical re-straints.
The use of restraints in nursing homes has beenquestioned. Their use is associated with considerablerisk of morbidity,39 cognitive decline,40–43 and mor-tality.44 Hence, studying the use of restraints is
important. Clearly, many nursing homes have suc-cessfully reduced their use of physical restraints.However, this analysis is instructive in that it showsthat some nursing homes have increased their use ofrestraints since the passage of the NHRA, therebyadding to a growing literature concerned with carepractices in some nursing homes.19–22 This studyexamined organizational characteristics, but for reg-ulators and nursing facilities, there is still a need toimprove understanding of how and why restraintuse practices differ in nursing homes. Future re-search should address these questions.
Acknowledgment
I would like to thank Dr Donald Hoover (RutgersUniversity) for his statistical support during this project.
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