Research in Gerontological Nursing

Correlational Survey 

Use of Agency Staff in Nursing Homes

Nicholas G. Castle, PhD

Abstract

This article describes the extent and degree of use of agency staff by nursing homes and examines the relationship between agency staffing levels and quality of care in a large sample of nursing homes (N = 3,876). The quality indicators came from the Nursing Home Compare Web site. It was found that many nursing homes used agency staff (approximately 60% used at least some), and a strong association between better quality and lower agency use existed for both nurse aides and RNs. The influence on quality for the highest levels of agency use, compared with no agency use, was clinically significant. On the basis of these findings, facilities considering using high levels of agency staff should do so carefully.

Abstract

This article describes the extent and degree of use of agency staff by nursing homes and examines the relationship between agency staffing levels and quality of care in a large sample of nursing homes (N = 3,876). The quality indicators came from the Nursing Home Compare Web site. It was found that many nursing homes used agency staff (approximately 60% used at least some), and a strong association between better quality and lower agency use existed for both nurse aides and RNs. The influence on quality for the highest levels of agency use, compared with no agency use, was clinically significant. On the basis of these findings, facilities considering using high levels of agency staff should do so carefully.

Nursing homes have well-documented staffing problems, including high turnover rates, high vacancy rates, problems with absenteeism, and low staffing levels, to name just a few (Bourbonniere et al., 2006; Decker, 2006; Mueller et al., 2006). Given these problems that many facilities experience, it is not surprising that nursing homes are using agency staff as a source of workers. Agency staff are temporary caregivers used to fill available positions, staff who “have their working life organized by a private contractor, known generally as an agency, to carry out work within any number of facilities” (Manias, Aitken, Peerson, Parker, & Wong, 2003, p. 457).

In nursing homes, agency staff are predominantly used for nurse aide (NA) positions (Bourbonniere et al., 2006; Castle, Engberg, & Men, 2008). However, agency staff are not exclusively NAs; they also include licensed practical nurses (LPNs) and RNs. Few studies examining use of agency staff in nursing homes exist; thus, very little information is available regarding either the extent or degree of use of these staff. This information is not well-recorded in government data either, although the Centers for Medicare & Medicaid Services (CMS) (2008) are soliciting approaches to collect this information. It will likely be several years before national figures on agency staff use are disseminated by CMS. Thus, this research describes the extent and degree of use of agency staff (RNs, LPNs, and NAs) by nursing homes.

Some research has shown that higher use of agency staff lowers the quality of resident care (Bourbonniere et al., 2006; Castle et al., 2008). For example, Castle et al. (2008) determined that NA agency staffing above 25 full-time equivalent (FTE) staff per 100 beds was associated with poor quality. Nevertheless, little empirical evidence identifies whether a relationship exists between agency staffing and quality. In the research presented here, the relationship between agency staffing levels and quality of care is examined in a large sample of nursing homes.

Background

A particularly intransient problem for many nursing homes, low (and often inadequate) staffing levels of all caregivers (RNs, LPNs, and NAs) have been identified in the literature for several decades (see Castle [2008] for a literature review). This clearly makes examining agency staff use very salient. Agency staff are used to bolster staffing levels. If these agency staff are ineffective, then alternatives should be sought. Moreover, there is a significant predicted shortfall in the number of formal caregivers needed to provide care in the next decade (Stone, 2004). Given this prediction, it is even more necessary for the industry to effectively use the current workforce.

If this ineffectual relationship exists and use of agency staff does contribute to lower quality of care, it can also distort the nursing home market, and consumer decisions and perceptions may be erroneous. For example, the U.S. Department of Health and Human Services’ Nursing Home Compare ( http://www.Medicare.gov/NHCompare) reports staffing levels for almost all nursing homes in the United States. A consumer may choose a nursing home on the basis of its high staffing levels, with the presumption that quality of care is high. However, if high use of agency staff are used to maintain these staffing levels, the assumed level of quality may not materialize.

Literature Review

Much of the current literature on agency staff use in nursing homes and hospitals was reviewed previously by Castle (2009). However, it should be noted that few nursing home studies were identified, and hospital studies were reviewed to give a general understanding and context to the use of agency staff. In summary, this prior literature review identified that in both nursing home and hospital studies, use of agency staff likely negatively influences quality (i.e., quality is lower).

In addition to the hospital literature presented by Castle (2009), additional research was identified. In a hospital-based study, total quality of nursing care, nursing care planning, nursing instructions, and nursing evaluation were all significantly worse for agency nurses compared with permanent staff (Wu & Lee, 2006). However, Aiken, Xue, Clarke, and Sloane (2007) cautioned that the qualifications of agency nurses are similar to those of permanent nurses, and lower quality may result from poor hospital environments rather than from simply using agency nurses.

Other hospital studies have examined how to avoid potential issues (such as lower quality) by using agency staff. For example, these studies have examined improving organizational commitment (Jalonen, Virtanen, Vahtera, Elovainio, & Kivimaki, 2006), establishing standards for agency workers (Stiehl, 2004), and improving working relationships between permanent staff and agency staff (Charnley & Arnold, 2006). Other studies have examined how to reduce use of agency staff, such as using e-bidding systems (i.e., Internet-based systems that allow workers to choose shifts that they are available to work) (Daniel, Garman, Grady, & Phillips, 2006). Moreover, Gee (2007) presented eight strategies to reduce reliance on agency staff (i.e., shifts, recruitment/retention, duty rostering, allocation of staff, team working, flexible work hours, senior staff, and managing sickness absence).

In addition to the nursing home literature presented by Castle (2009), a few empirical nursing home-based studies examining use of agency staff were identified. (The studies by Bourbonniere et al. [2006] and Castle et al. [2008] are discussed at length by Castle [2009].) Castle and Engberg (2008) examined agency staff use from data collected from a survey conducted in 2003 (N = 1,071 nursing homes). The study found that agency staff use per 100 beds averaged 1.6, 2.9, and 6.9 FTE RNs, LPNs, and NAs, respectively. A single quality factor constructed from the 14 quality measures from Nursing Home Compare was used. More agency NAs resulted in a smaller increase in quality, compared with the use of an equivalent number of regular NAs (Castle & Engberg, 2008).

Thus, few studies examining agency staff in nursing homes were identified; most studies used data that are now dated, samples were generally small, and the focus was on NAs. The research presented in this article is significant because it uses recently collected data; focuses on RNs, LPNs, and NAs; and uses a large sample.

Conceptual Model

Using qualitative data from several thousand nursing home administrators and a review of the literature, Castle (2009) developed a conceptual model linking agency staff use and quality of care. That conceptual model was used to guide this analysis. The model proposes that quality of care is influenced by caregiver staffing levels. This link is some-what conclusive in the empirical literature (Castle, 2008). In turn, staffing levels are influenced by agency staff use, as agency staff increase the overall FTE staffing levels in the facility. However, in this conceptual model, agency staff have a negative influence on quality of care. As discussed above, some empirical studies suggest this may occur (Bourbonniere et al., 2006; Castle et al., 2008), but Castle (2009) also identified from nursing home administrators 18 ways in which agency staff have a negative influence on quality, including decreased continuity of care, decreased teamwork, and the need for greater supervision.

In this conceptual model, staffing levels and quality of care are both influenced by market characteristics (e.g., Medicaid payment rates) and facility characteristics (e.g., ownership status). These links are also somewhat conclusive in the empirical literature and follow many empirical analyses of quality that have included both market and facility characteristics (e.g., Bourbonniere et al., 2006; Zhang & Grabowski, 2004).

Method

Sources of Data

Data used in this investigation came from three sources, each described in detail below. The information on agency staffing came from a survey of nursing home administrators conducted during January to March 2007, which collected information from the previous year. To match this time frame, quality indicators from the 2006 Nursing Home Compare were used. Characteristics of the nursing homes came from the Online Survey Certification and Reporting (OSCAR) data collected in 2006.

The mailing sample for the survey was created using information from the OSCAR data. The unique OSCAR facility identification number was also included on all surveys so survey data could be subsequently matched to the OSCAR data. An OSCAR identification number is also included in Nursing Home Compare data, and thus the three data sources were matched using this common identifier.

Nursing Home Administrator Survey. Data were collected as part of a survey developed by the author. This survey was sent to 6,000 nursing homes, with 3,946 returned (response rate = 66%). As part of this survey, information was collected for staffing characteristics of RNs, LPNs, and NAs. These staffing characteristics included data on the use of agency staff and staffing levels.

Nursing homes with fewer than 30 beds and hospital-based facilities were excluded from the sample because their staffing characteristics are often highly variable. With the exception of these two exclusions, all other nursing homes in the United States were included in the sampling frame. From this sampling frame, facilities were randomly selected to receive a questionnaire.

Many of the survey questions had been used in previous questionnaires by the author, including agency use and staffing questions. The validity of these questions was previously assessed using face-to-face interviews with 89 directors of nursing and 87 nursing home administrators, and via cross-checking survey responses with existing nursing home records. For staffing levels, the construct validity of the measures was assessed by cross-checking the results with payroll records in 152 facilities (kappa statistics were considered high at ≥0.95). Also, agency staff use information was cross-checked with payroll records (the kappa statistic was considered high at 0.97). These findings indicate that the information collected was reliable.

The survey instrument used in the current analysis was also assessed through in-person interviews with 5 nursing home administrators. A few wording changes resulted, although none were for the agency use or staffing questions. After making these wording changes, the survey was further pilot tested with a sample of 100 nursing home administrators. The returned surveys were examined for nonresponse to items, which were found to be extremely low, and for any possible misinterpretation of items, which appeared to be minimal.

No incentives were used for nursing home administrators to complete the survey. One repeat survey mailing and one reminder letter was used, along with faxed copies and e-mail attachments when requested by respondents. The good response rate achieved may be attributable to interest by nursing home administrators in this topic and to the relatively short questionnaire used.

OSCAR Data. The OSCAR data comes from the Medicare and/or Medicaid certification process conducted by state licensure and certification agencies. This process occurs approximately every 12 months (range = 9 to 15 months). The data include most (approximately 97%) nursing homes in the United States. In 2006, approximately 17,000 facilities were included in the data. OSCAR data includes several hundred data elements, although only those pertaining to characteristics of the facility were used in this investigation. These facility characteristics include chain membership, occupancy rate, and ownership and are described further below. Staffing levels (but not agency use) are included in the OSCAR data but are considered to be somewhat unreliable (Kash, Hawes, & Phillips, 2007). Therefore, staffing level information came from the primary data discussed above.

Nursing Home Compare. Nursing Home Compare is a Web-based report card providing information for all Medicare and/or Medicaid certified nursing homes since 2002. This information includes quality indictors, called Quality Measures. These are aggregate facility-level measures that come from the Minimum Data Set (MDS). Further details on how these Quality Measures were chosen for inclusion in Nursing Home Compare is provided in a 2002 General Accounting Office report, and more general information about Nursing Home Compare can be found in the 2008 article by Mukamel, Weimer, Spector, Ladd, and Zinn.

The Nursing Home Compare Quality Measures were used in this investigation, first because they are readily available for almost all nursing homes; second, they are commonly used by researchers (e.g., Castle et al., 2008); and third, these measures are derived from resident assessments (i.e., the MDS) and are likely more reliable than other quality indicators (i.e., some measures in the OSCAR data are self-reported). However, no one overall indicator of nursing home quality currently exists, and thus several Quality Measures were used in this analysis.

The number and kind of quality indicators reported as part of Nursing Home Compare has varied from year to year. During the period of observation of this study, Nursing Home Compare reported 15 Quality Measures, although by the end of 2006, 19 were reported. Twelve measures were for long-stay residents (also known as the chronic care measures), and three measures were for short-stay residents (also known as post-acute measures). It is unclear whether agency staff influence care for either or both short-stay and long-stay residents; therefore, all 15 Quality Measures were used in this investigation. For all of these measures, the scores ranged from 0 to 100, with higher scores representing lower quality.

Data Analysis

To determine the extent of agency staff use (defined as the scope of agency staff use by all nursing homes in the sample), the percentage of nursing homes using any agency staff was calculated. Statistics are provided for use of only RN, LPN, or NA agency staff in addition to any use of RN, LPN, or NA agency staff.

The degree of agency staff use (defined as the scale of agency staff use by nursing homes in the sample) was determined by calculating the percentage of FTE staff. Statistics are provided for average FTE levels of RN, LPN, or NA agency staff use. In addition, the average percentage of total staff represented by these RN, LPN, and NA agency staff is presented.

Using a series of t tests, associations between each of the 15 Nursing Home Compare Quality Measures and various levels of agency staffing were examined. The associations were examined for RNs, LPNs, and NAs, and the levels of agency staff examined were 0% and 25% or more. The levels of 25% or more agency use were chosen because these levels represented high agency use. Previous research has shown that quality is likely most negatively influenced by high levels of agency use (Castle et al., 2008).

Associations between each of the 15 Quality Measures and agency staffing were further examined using multivariate analyses. Specifically, negative binomial regression was used because the Quality Measures followed a Poisson distribution with many zero counts (Agresti, 1996). Negative binomial regression is robust in accommodating a high frequency of zero counts. The facility, staffing, and market characteristics described below were used as control variables. In addition, the number of residents was used to capture the exposure of each facility to the risk for the negative event (i.e., poor quality), and the Huber-White sandwich estimator clustered by county was also used for all analyses to address the possible correction of outcomes within the same county. All analyses were performed using the statistical software STATA/SE for Windows, version 9.2.

Dummy variables for agency staff use were used in the multivariate analyses (0%, >0% to <25%, and 25% or more agency use). The statistical significance of the dummy variables in the regression are reported, but we also wanted to present evidence regarding the magnitude of the variation in quality that comes from the variation in agency staff use. Therefore, the predicted values for each of the 15 Quality Measures were used; predicted values of 0% use were subtracted from predicted values of 25% or more use, holding all other variables at their means. Each number represents a difference measure, the predicted value of the Quality Measures for facilities with 0% agency use and those with 25% or more use.

Model Specifications

Following previous research on agency staff use and the conceptual model, facility, staffing, and market characteristics were included as control variables in the multivariate analyses. Facility characteristics used as control variables were bed size, ownership, chain membership, private-pay census, average occupancy, and activities of daily living (ADL). Bed size represented the number of beds available in the facility. Two classes of facility ownership (for profit and not for profit) and two classes of chain membership (chain and nonchain) were used. The percentage of residents paying for care was used as a measure of private-pay census, and average occupancy is defined as the percentage of nursing home beds with residents. The ADL score was a facility score (ranging from 0 to 30) based on three OSCAR questions regarding difficulty with bathing, dressing, or transferring. Higher scores indicated a greater average of ADL impairment within the facility.

Staffing characteristics used as control variables were the numbers of FTE staff per 100 beds for RNs, LPNs, and NAs. In addition, a professional staff mix variable was included. This professional staff mix variable represented the ratio of RNs to other caregivers (LPNs and NAs).

Market characteristics were also used as control variables, and thus nursing home competition and Medicaid payment rates were used. A Herfindahl Index (HI) representing competition from other nursing homes in the county was calculated. The HI was calculated by taking each nursing home’s squared percentage share of beds in the county and summing for all nursing homes in the county. States vary in daily payment rates for Medicaid residents (Zhang & Grabowski, 2004). Using primary data collected by the author, state average Medicaid payment rates were included as a market characteristic.

Results

Of the 6,000 surveys mailed and the 3,946 returned, 3,876 included agency use information, giving an analytic response rate of 65%. Most (71%) of the questionnaires were returned by mail within 1 month. No significant differences were found on facility characteristics (i.e., bed size, ownership, chain membership, and private-pay census) for respondents compared with nonrespondents.

Descriptive statistics of facility, staffing, and agency staff characteristics are presented in Table 1. Most of the sample’s facility and staffing characteristics were not significantly different from equivalent characteristics recorded in the 2004 National Nursing Home Survey (NNHS) (data available from http://www.cdc.gov/nchs/nnhs.htm), a nationally representative study of nursing homes conducted by the National Center for Health Statistics. However, the average organizational size (131 beds) of the sample was significantly higher than that from the NNHS (106 beds). Staffing levels in the current study’s sample averaged 12.5, 11.2, and 24.8 FTE staff per 100 residents for RNs, LPNs, and NAs, respectively. Approximately half (54%) of the facilities in the sample were members of a chain, 58% were for profit, and the average occupancy rate was 87%.

Facility, Staffing, and Agency Staffing Characteristics of Nursing Homes (N = 3,876)

Table 1: Facility, Staffing, and Agency Staffing Characteristics of Nursing Homes (N = 3,876)

The extent of agency staff use is presented in Table 1. In 2006, 28.3% of facilities in the sample had some RN agency staff use, while 4.1% used only agency RNs (i.e., they did not use either LPN or NA agency staff). Nineteen percent of facilities had some LPN agency staff use, whereas 3.2% used only agency LPNs. Forty-two percent of facilities had some NA agency staff use, while 35.5% used only agency NAs.

The degree of agency staff use is presented as both FTE staff and percentage of total staff represented by agency workers. Of those facilities using agency staff in 2006, RN agency use averaged 2.3 FTE staff per 100 residents, LPNs averaged 3.1 FTE staff per 100 residents, and NAs averaged 4.9 FTE staff per 100 residents. As a percentage of total staff, this represents 18.5%, 27.7%, and 19.6% agency use for RNs, LPNs, and NAs, respectively.

Average values of the Quality Measures for nursing homes with no agency use and 25% or more agency staff use are presented in Table 2. For facilities with no agency NA use, 11 of the 15 quality measures values were significantly (p ≤ 0.05) lower than in facilities with 25% or more agency NA use (lower scores indicate better quality). In facilities with no agency LPN use, 7 of the 15 quality measures were significantly (p ≤ 0.05) lower than in facilities with 25% or more agency LPN use. In facilities with no agency RN use, 13 of the 15 quality measures were significantly (p ≤ 0.05) lower than in facilities with 25% or more agency RN use.

Nursing Home Compare Quality Measures Values with and Without Agency Staff Use

Table 2: Nursing Home Compare Quality Measures Values with and Without Agency Staff Use

The multivariate results, presented in Table 3, show the approximate point estimates for nursing homes with no agency use subtracted from those with 25% or more agency staff use. For NAs, 8 of the 15 Quality Measures were significantly (p ≤ 0.05) lower in the no agency-use facilities (lower scores indicate better quality), whereas 4 were significantly lower for LPNs and 6 were significantly lower for RNs. In some cases, the predicted point estimates were large. For example, facilities with no use of agency NAs had a 5.1% lower score compared with facilities with 25% or more NA agency use for the measure of percentage of residents with need for help with daily activities increased.

Change in Nursing Home Compare Quality Measures Values Associated with Level of Agency Staff Use

Table 3: Change in Nursing Home Compare Quality Measures Values Associated with Level of Agency Staff Use

Discussion

Because few descriptive accounts of agency staff use exist in the literature using a large sample of nursing homes, the descriptive results of this research should be of interest. Nearly 60% of all nursing homes used at least some agency staff in 2006. However, given the varying degree and extent of agency staff use identified, these descriptive findings are discussed further.

The percentage of facilities not using agency staff varies for RNs, LPNs, and NAs. Most facilities did not use any RN agency staff (approximately 70%) or LPN agency staff (approximately 80%), whereas more than 40% of facilities used at least some NA agency staff. This seems to support the notion that agency staff are used primarily for NA positions.

However, when examining the degree of agency use, a somewhat different picture is presented. Because more NA staff (i.e., more FTE staff) are used by nursing homes than either LPNs or RNs, the relative number of NA agency staff is lower. When the agency use statistics are presented as a percentage of staff positions filled, the numbers show that on any given day, 19.6% of NA positions are filled by agency staff, 27.7% of LPN positions are filled by agency staff, and 18.5% of RN positions are filled by agency staff.

Still, these descriptive statistics should also account for facilities with no (or very little) agency staff use. As such, in the sample of nursing homes, the actual percentage of positions filled by agency staff is relatively low (approximately 5% for RNs, LPNs, and NAs). Thus, the descriptive findings show that many nursing homes do not use any agency staff, and when they do, the levels are low for most facilities. However, the descriptive findings also show that a minority of nursing homes do use agency staff at high levels.

Following the generally held belief in the literature that agency staff use is detrimental, the association of agency use with the Nursing Home Compare Quality Measures was examined. The multivariate findings showed that 8 of 15 measures for NAs, 6 of 15 measures for RNs, and 4 of 15 measures for LPNs are significantly associated with agency use. These findings do not necessarily indicate an unequivocal quality-agency use relationship, but on the whole it is likely that, in general, no agency use is associated with lower quality measure scores (i.e., better quality), and higher agency use is associated with higher quality measure scores (i.e., worse quality).

The quality-agency use relationship is somewhat more robust when the short-stay Quality Measures are excluded; that is, the difference in Quality Measure scores were generally not significant for the short-stay Quality Measures. It may be that these measures are not sensitive to the use of agency staff. Alternatively, agency staff may not be used for short-stay residents, many of whom are characteristically receiving rehabilitation services on specialized units.

The findings for the association of agency staff use with the Nursing Home Compare Quality Measures may have practical significance, as they do show some clinical significance. In many cases, the difference between no agency use and 25% or more agency use translates to a 1% or 2% difference in the quality scores. These findings hold even after controlling for facility, staffing, and market characteristics (see point estimates in Table 3). Considered cumulatively, the impact on quality is large and may be meaningful for nursing home residents. The results suggest that policy makers, corporate management, and facility owners concerned with quality may want to manage use of agency staff more carefully.

These results may have some policy significance for minimum staffing levels. Policy debates are ongoing about whether minimum staffing levels should be mandated in nursing homes (Louwe & Kramer, 2002; Zhang & Grabowski, 2004). This debate is fueled by the belief that staffing levels influence quality of care. Numerous empirical studies have been conducted in this area, but many of these have conflicting results. Castle (2008) recently examined 70 of these studies (covering the years 1991–2006). His review concluded that an association likely exists between nursing home staffing levels and quality.

Some states have implemented minimum staffing level regulations, while federal policy has so far set only minimal guidelines in this area (Mueller et al., 2006). Nevertheless, if minimum staffing levels were implemented in all states or federal policy raised staffing levels for all facilities, then use of agency staff could increase to meet the requirements. Moreover, given the current staffing shortages experienced by many facilities, it is likely nursing homes will turn to agency staff. Given that the results show an association with quality of care, this could have the unintended effect of worsening quality in some facilities, although clearly this depends on the difference between how much quality is increased by adding more permanent staff versus decreased by using agency staff—with a caution that these findings are not causal.

Limitations and Suggestions for Further Research

Why or how agency use influences quality of care was not examined. Several mechanisms were recently discussed by Castle (2009) and include:

  • Facilities pay a premium for agency staff, which may divert dollars from care.
  • Agency staff are not familiar with residents, so they may interfere with continuity of care.
  • Agency staff are not familiar with facility practices, so they may weaken standards of care.
  • Unfamiliar caregivers in the form of agency staff may cause psychological distress for some residents.
  • Because agency staff are likely unfamiliar with residents, the facility, and facility practices, they will likely be less productive in the caregiving process.

Agency staffing levels were associated with quality of care, but it should be noted that it is not possible with the cross-sectional data used to determine causal direction; in other words, it is not possible to infer that agency use necessarily causes poor quality. For example, poor management may influence both the hiring of agency staff and low quality of care. The difference measures (Table 3) represent the predicted value of the Quality Measures for facilities with 0% agency use and 25% or more use, and not necessarily the change that would occur if a facility increased its agency staff use from the lower level to the higher. Longitudinal data should be used in the future to determine both the causal direction and the strength of the effects. Indeed, the work of Aiken et al. (2007) regarding hospital agency staff would suggest that causal effects may be weak. Moreover, Castle et al. (2008) noted that agency staff should not be blamed for poor quality; rather, it is more likely that how agency staff are used causes quality issues.

Alternative cut-off points could be used for the comparisons used in the analyses. No agency use was compared with 25% or more agency use. This clearly maximizes the differences between the two groups, and the 25% or more cut-off point was chosen arbitrarily. Thus, the analysis represents a somewhat stark contrast between use and no use of agency staff. Examining the functional form of the relationship between quality and agency use may be useful in further refining the analyses. Moreover, identifying the levels at which agency staff use are (and are not) most detrimental to quality could be useful for the nursing home industry.

Other quality indicators could be used for these analyses. These other indicators could come from secondary data sources such as the MDS, or alternatively could include more than just clinical measures, such as resident satisfaction and resident quality of life. Given that care is provided by an unfamiliar caregiver when agency staff are used, resident perceptions of quality of life may be especially negatively affected. In addition, the Nursing Home Compare Quality Measures used in this analysis do have some limitations, including omission of data and failure to measure all dimensions of quality.

Thus, the analysis presented should be seen as one of the first—but still incomplete—examinations of the association between agency staff use and quality in nursing homes. Many questions remain. For example, little research has examined agencies. Staffing agencies may vary in quality, and the relationship between the agency and nursing home may influence quality of care. Also, following the work of Aiken et al. (2007), the qualifications and experience of nursing home agency staff may influence quality of care.

Conclusion

This article described the extent and degree of use of agency staff by nursing homes. Many nursing homes use agency staff, with some facilities’ staff composed of a considerable percentage of agency workers. This article also examined the relationship between agency staffing levels and quality of care. A strong association exists between better quality and lower agency use for both NAs and RNs, and this influence on quality is likely clinically significant. Also, if national minimum caregiver staffing levels were implemented, some facilities may increase use of agency staff to meet the requirements with the unintended consequence of lowering quality. In conclusion, these findings suggest that nursing homes should carefully consider using high levels of agency staff.

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  • Wu, S.H. & Lee, J.L. (2006). A comparison study of nursing care quality in different working status nursing staffs: An example of one local hospital. Journal of Nursing Research, 14, 181–189.
  • Zhang, X. & Grabowski, D.C. (2004). Nursing home staffing and quality under the Nursing Home Reform Act. The Gerontologist, 44, 13–23.

Facility, Staffing, and Agency Staffing Characteristics of Nursing Homes (N = 3,876)

Variable Definition Percentage Mean (SD)
Facility characteristicsa
  Organizational size Number of beds 131.2 (91.1)
  Ownership For profit or not for profit 58.1%
  Chain membership Member of a nursing home chain or not 54%
  Occupancy Average daily occupancy rate 87.4% (15.6)
  Private-pay occupancy Average daily private-pay occupancy rate 17.8% (16.2)
  Medicaid occupancy Average daily Medicaid occupancy rate 58.5% (22.2)

Regular staffingb
  RN regular staffing FTE regular RNs per 100 residents 12.5 (9.1)
  LPN regular staffing FTE regular LPNs per 100 residents 11.2 (6.8)
  NA regular staffing FTE regular NAs per 100 residents 24.8 (7.3)

Extent of agency staff useb
  RN agency (any) Used any agency RNs in 2006 28.3%
  RN agency (only) Used only agency RNs in 2006 4.1%
  LPN agency (any) Used any agency LPNs in 2006 19%
  LPN agency (only) Used only agency LPNs in 2006 3.2%
  NA agency (any) Used any agency NAs in 2006 42.2%
  NA agency (only) Used only agency NAs in 2006 35.5%
  Any agency use Used any (RN, LPN, or NA) agency staff in 2006 58.9%

Degree of agency staffing (using FTE staff and only including facilities that use agency staff)b
  RN agency FTEs FTE agency RNs per 100 beds 2.3 (1.1)
  LPN agency FTEs FTE agency LPNs per 100 beds 3.1 (1.5)
  NA agency FTEs FTE agency NAs per 100 beds 4.9 (3.8)

Degree of agency staffing (as a percentage of staff and only including facilities that use agency staff)b
  RN agency Agency RNs as a percentage of all RNs 18.5%
  LPN agency Agency LPNs as a percentage of all LPNs 27.7%
  NA agency Agency NAs as a percentage of all NAs 19.6%

Degree of agency staffing (as a percentage of staff and including all facilities in sample)b
  RN agency Agency RNs as a percentage of all RNs 5.1%
  LPN agency Agency LPNs as a percentage of all LPNs 4.2%
  NA agency Agency NAs as a percentage of all NAs 5%

Nursing Home Compare Quality Measures Values with and Without Agency Staff Use

NAs LPNs RNs
Quality Measure Sample Average (N= 3,876) No Agency Use (N= 710) ≥25% Agency Use (N= 406) No Agency Use (N= 523) ≥25% Agency Use (N= 215) No Agency Use (N= 577) ≥25% Agency Use (N= 431)
Long-stay measures (% residents)
  Need for help with daily activities increased 13.1 10 14.8* 11.2 13.8* 9.8 14.2*
  Experienced moderate to severe pain 4.9 3.8 5.6* 4.5 4.8 4.3 5.6*
  High-risk residents with pressure ulcers 5.3 4.2 7.1* 5 6.9* 4.5 5.3
  Low-risk residents with pressure ulcers 5.1 5 6.5* 5.1 5.5 4.8 6.8*
  Physical restraint used 13.7 12.1 14.9* 12 12.8 12.1 14.9*
  More depressed or anxious 4.2 3.9 5 3.6 4.4 3 5.7*
  Low-risk residents with loss of bladder or bowel control 48.5 43.2 50.1* 46.9 50.5* 43.5 50.7*
  Catheter inserted and left in bladder 6.8 6.3 7.8* 6.8 7.1 6 6.7
  Spend most time in bed or in a chair 14.5 12.3 16.4* 13.8 15.6* 13.3 16.6*
  Ability to move in/around room worsened 8.6 7.7 8.9 7.6 8.9* 8.2 10.1*
  Developed urinary tract infection 19.7 17 21.6* 18.7 20.4* 18.1 21.4*
  Lost too much weight 9.3 8.8 9.5 8.7 9.5 8.5 9.6*
Short-stay measures (% residents)
  Experienced delirium 17.1 16.3 17.5 17.1 19.9* 16.1 19.9*
  Experienced moderate to severe pain 21.4 19.6 22.7* 20.2 21.1 21.4 23*
  Had pressure ulcers 3.5 3.7 4.9* 3.6 3.7 3.3 5.5*

Change in Nursing Home Compare Quality Measures Values Associated with Level of Agency Staff Use

Percent Change
NAs LPNs RNs
Quality Measure No Agency Use (n= 710) vs. ≥25% Agency Use (n= 406) No Agency Use (n= 523) vs. ≥25% Agency Use (n= 215) No Agency Use (n= 577) vs. ≥25% Agency Use (n= 431)
Long-stay measures
  Need for help with daily activities increased −5.1* −3.1* −3.4*
  Experienced moderate to severe pain −2.2* −0.5 −0.8
  High-risk residents with pressure ulcers −3* −1 −2.1*
  Low-risk residents with pressure ulcers −1.2 −0.4 −0.5
  Physical restraint used −1.1 +0.3 −1.2
  More depressed or anxious −0.9 −0.6 +0.2
  Low-risk residents with loss of bladder or bowel control −4.4* −2.1 −3.6*
  Catheter inserted and left in bladder −1.5* −0.7 −0.3
  Spend most time in bed or in a chair −4.4* −3.2* −5*
  Ability to move in/around room worsened −0.7 −1.9* −2.7*
  Developed urinary tract infection −2.3* −1.2 −2.6*
  Lost too much weight −0.4 −0.5 −0.8
Short-stay measures
  Experienced delirium −0.3 −1.6* −0.8
  Experienced moderate to severe pain −1.4* +0.2 −1.0
  Had pressure ulcers −0.4 −1.1 −0.5
Authors

Dr. Castle is Professor, Department of Health Policy and Management, University of Pittsburgh, Graduate School of Public Health, Pittsburgh, Pennsylvania.

Financial support, in part, was received from a grant from the Agency for Healthcare Research and Quality, R01 HS016808-01 Staffing Characteristics of Nursing Homes and Quality.

Address correspondence to Nicholas G. Castle, PhD, Professor, Department of Health Policy and Management, A610 Crabtree Hall, University of Pittsburgh, Graduate School of Public Health, 130 DeSoto Street, Pittsburgh, PA 15261; e-mail: CASTLEN@Pitt.edu.

Received: April 17, 2008
Accepted: March 17, 2009
Posted Online: May 29, 2009

10.3928/19404921-20090428-01

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