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To examine the association between nursing home (NH) work environment attributes such as teams, consistent assignment and staff cohesion, and the risk of pressure ulcers and incontinence.
Minimum dataset for 46,044 residents in 162 facilities in New York State, for June 2006–July 2007, and survey responses from 7,418 workers in the same facilities.
For each individual and facility, primary and secondary data were linked. Random effects logistic models were used to develop/validate outcome measures. Generalized estimating equation models with robust standard errors and probability weights were employed to examine the association between outcomes and work environment attributes. Key independent variables were staff cohesion, percent staff in daily care teams, and percent staff with consistent assignment. Other facility factors were also included.
Residents in facilities with worse staff cohesion had significantly greater odds of pressure ulcers and incontinence, compared with residents in facilities with better cohesion scores. Residents in facilities with greater penetration of self-managed teams had lower risk of pressure ulcers, but not of incontinence. Prevalence of consistent assignment was not significantly associated with the outcome measures.
NH environments and management practices influence residents’ health outcomes. These findings provide important lessons for administrators and regulators interested in promoting NH quality improvement.
Over the years, much attention has been focused on the need to improve quality of care provided to nursing home (NH) residents in the United States. Pressure ulcers (PU) and urinary/bowel incontinence (UBI) are considered to be important quality indicators in NHs because they are closely related to quality of life, the risk of additional comorbidities and hospitalizations, and death (Berlowitz et al. 2001; Gruneir and Mor 2008). At the same time, they are preventable with good nursing care or treatable with behavioral or pharmacological therapies (Brandeis, Berlowitz, and Katz 2001; Bergstrom et al. 2005; Thomas 2006).
The Centers for Medicare and Medicaid Services (CMS) include PUs and UBIs among the 14 quality measures (QMs), for long-term residents, published quarterly on the NH Compare report card website. Although some QMs have improved over time, others remain largely unchanged. For example, the proportion of residents experiencing pain and the use of physical restraints have declined over time (Mukamel et al. 2008; American Health Care Association [AHCA] 2011). However, the prevalence of PUs has remained relatively high (unadjusted mean of 12.5 percent, per NH Compare website) and stable over time (Capon, Pavoni, and Mastromattei 2007; Mukamel et al. 2008, 2009). At the same time, the prevalence of incontinence is reported to have increased, affecting almost 52 percent of residents (Palmer 2008; American Health Care Association [AHCA] 2011). Furthermore, considerable variations in these outcome rates continue to persist across NHs (Li et al. 2010), ranging from none to 90 percent for UBIs and for PUs (CMS 2010).
Many studies have examined the association between NH quality of care and facility characteristics. Only recently have studies used health outcomes as QMs (Berlowitz, Young, and Hickey 2003; Dellefield 2006; Berlowitz et al. 2009). Typically, these studies have focused on measures of capacity (e.g., size, payer mix) and capability (e.g., nurse staffing levels/mix, ownership), with the results often being inconsistent (Berlowitz et al. 2009) and contradictory (Davis 1991; Porell and Caro 1998; Zinn and Mor 1998). Studies focusing on such facility characteristics have provided little insight on management or care practices that may impact residents’ outcomes.
To date, several interventions have been undertaken to prevent or reduce PUs (Berlowitz, Young, and Hickey 2003; Rosen et al. 2005) and to improve UBI rates (Schnelle 1990; Durrant and Snape 2003; Al-Samarrai et al. 2007) in NHs, but generally with poor results. Studies have suggested that while NHs establish QI committees they have difficulty implementing process improvements, because such initiatives are rarely supported by the work environment/culture within these institutions (Office of Inspector, General 2003; Rosen et al. 2005).
The importance of the work environment as a factor in improving organizational performance, including residents’ outcomes, has been advocated by researchers, policy experts, and culture change proponents (Barry, Brannon, and Mor 2005; Koren 2008). Numerous definitions of the work environment are present in the literature. In the context of long-term care (LTC), work environment has been represented by modifiable organizational traits and management practices that support how workers relate to each other and to the residents. Among others, these traits and practices may be represented by staff empowerment activities, including team approach to care delivery, consistent staff assignment to residents, and interventions focusing on improving staff cohesion, communication, and coordination of care (Eaton 2000; Rahman and Schnelle 2008; Rahman, Straker, and Manning 2009; Tourangeau et al. 2010). To date, only a handful of studies have examined these specific work environment attributes in relation to residents’ quality of care (Gittell et al. 2008; Temkin-Greener et al. 2004). Furthermore, culture change evaluations have not demonstrated significant improvements in NH care quality (Coleman et al. 2002; Stone, Reinhard, and Bowers 2002; Kane et al. 2007).
Little is still known about the relationship between specific NH work environment attributes, such as those mentioned above, and residents’ health outcomes. In this study, using a representative sample of New York State (NYS) facilities, we examined the relationships between these work environment measures and risk-adjusted outcomes for PUs and UBIs, controlling for other facility characteristics.
Research focusing on NHs as complex adaptive systems has suggested that management practices influence how workers relate to each other and, in turn, impact resident outcomes (Anderson, Issel, and McDaniel 2003). Managers directly or indirectly influence the quality of the work environment within their institutions by facilitating or inhibiting the nature of connections among their staff and by creating conditions that promote or stifle effective behaviors. For example, work in NHs is characterized by high levels of task interdependence between coworkers. By influencing organizational climate, communication patterns with and among staff, and by encouraging stable and relationship-oriented leadership, managers foster work group dynamics and cohesion (Shortell et al. 1994; Anderson and McDaniel 1999; Temkin-Greener et al. 2009a). NHs are also marked by constraints on the availability of resources necessary to provide high-quality care. In such settings, management practices that promote teamwork and continuity of care have been thought to influence care quality and health outcomes (Eaton 2000; Wunderlich, Kohler, and Gooloo 2001).
We chose to focus on these attributes of the work environment because they are highly valued in influencing the health outcomes of interest in this study—PU and incontinence. For example, a survey of certified nurse assistants (CNAs) identified improved teamwork and consistent assignment as major factors in ensuring successful continence treatment (Lekan-Rutledge, Palmer, and Belyea 1998). Others also identified teamwork, shared goals and values, timely feedback, and nursing consistency as critical components for incontinence care (Resnick et al. 2006; Lyons 2010). With regard to PU the On-Time Pressure Ulcer Prevention and Treatment program developed and piloted in over 30 NHs across the United States has identified similar work attributes as important components for quality improvement (QI) (AHRQ 2008). Other QI programs have also emphasized the importance of interdisciplinary staff collaboration and teamwork in adherence to best practices for PU prevention (Berlowitz, Young, and Hickey 2003).
Figure 1 provides a schema for the study's conceptual framework and the hypothesized relationships between the attributes of the work environment and resident outcomes.
Anderson et al. showed that better communication and collaboration between registered nurses and their supervisors, and greater involvement by nurses in decision making, were associated with better resident outcomes measured by a composite of 11 process indicators (Anderson and McDaniel 1999). NHs where management promotes communication openness among staff have been shown to have lower rates of restraints use (Anderson, Issel, and McDaniel 2003). More recently, Gittell et al. found that better relational coordination (communication, shared respect, and knowledge) among aides was associated with better residents’ quality of life (Gittell et al. 2008). We have previously tested a similar concept of staff cohesion, measuring the extent to which NH staff perceived to have common goals, values, and strong group identity (sense of belonging to a work group or team), shared responsibility for care delivery, and reported good working relationships with co-workers. We showed this measure to be psychometrically valid and reliable (Cronbach's alpha = 0.77) and found the domains of leadership, communication/coordination, and conflict resolution to be statistically significant (p-values < .0010) predictors of staff cohesion in NHs (Temkin-Greener et al. 2009b). Therefore, we hypothesized the following:
H1: Residents living in facilities with better staff cohesion have lower risk of pressure ulcers and urinary/bowel incontinence, ceteris paribus.
The practice of assigning daily care staff to consistently care for the same residents over time has been assumed to result in better quality of care (Eaton 2000). Empirical findings in this regard have been largely inconsistent. Several studies have shown the association between consistent assignment and staff turnover and satisfaction, but not directly with care quality (Banaszak-Holl and Hines 1996; Burgio et al. 2004). Most recently, a study has shown that NHs with higher penetration of consistent assignment have significantly fewer quality of care deficiencies, including those causing immediate harm or jeopardy to residents (Temkin-Greener et al. 2004). However, to date, the association between consistent assignment and residents’ health outcomes has not been demonstrated. We hypothesized the following:
H2: Residents in NHs with higher penetration of consistent assignment have lower risk of pressure ulcers and urinary/bowel incontinence, ceteris paribus.
In health care, teams have long been thought to promote care coordination and hence to potentially be effective in improving quality of care, particularly in settings serving the chronically ill (Berlowitz, Young, and Hickey 2003; Wagner 2004). Although team processes in NHs have been demonstrated to be associated with better outcomes (Rantz et al. 2004; Yeatts et al. 2004), the extent to which nursing staff actually work in teams has been largely unknown. Recently, a study of NYS NHS showed that in an average facility 16 percent of direct care staff reported working in daily care teams (Temkin-Greener et al. 2009b) charged with the day-to-day provision of care to the residents. Therefore, we hypothesized the following:
H3: Residents in NHs with higher prevalence of daily care teams have lower risk of pressure ulcers and urinary/bowel incontinence, ceteris paribus.
Primary data were obtained from a “parent” study, which recruited 190 NHs in NYS. All recruited facilities were certified for Medicare and Medicaid; had more than 50 beds (in smaller facilities measures of work performance are subject to greater measurement error); did not focus on special-needs patients (e.g., were not pediatric or rehabilitative-only facilities); and were in operation for at least 2 years (in order to identify more stable facilities).
In each participating facility, all staff members providing direct, daily care to the residents were eligible for the study. Facility administrators were provided with the number of survey packets corresponding to the estimated number of all direct care staff in a given facility (based on information provided by the facility management). They were asked to distribute these packets to all staff providing daily direct care to the residents. Respondents mailed the completed surveys back to the research team using prepaid envelopes. We used these data to obtain information on facility-level work environment attributes (survey available on request).
Primary data from 162 NYS NHs (85 percent of all participating homes) and 7,418 direct care workers employed in these facilities were obtained via surveys conducted between July 2006 and April 2007 (Temkin-Greener et al. 2009b). Of the respondents, 50 percent were CNAs, 19 percent licensed practical nurses (LPNs), 13 percent registered nurses (RNs), 9 percent therapists, and 9 percent others (e.g., social work, physicians). The overall response rate was 37.1 percent (median = 34.4 percent), with a standard deviation of 19.1 percent. Because some NH did have rather low response rates, we conducted a sensitivity analysis excluding facilities with response rates lower than 10 percent. This eliminated 12 facilities, but it did not change the findings in any measurable or statistically significant ways. We, therefore, decided not to exclude any facilities from the analysis presented here.
Since NH participation was voluntary and not based on a random sample, we used probability weights (described below) and compared the sample facilities to all NYS facilities on the outcome variables and facility characteristics (Table 1).
Secondary data included the minimum dataset (MDS) and the Online Survey Certification and Reporting System (OSCAR) for June 2006–July 2007, matching the survey timeline. The MDS is a federally mandated clinical assessment process for residents in Medicare and Medicaid certified facilities. It contains detailed information about residents’ health status. All LTC residents are assessed at admission and quarterly thereafter, or when health status changes significantly. The reliability and validity of the MDS in recording residents’ clinical health conditions is generally considered to be good (Mor et al. 2003). OSCAR contains information on facility characteristics (e.g., size, staffing hours). For individuals in each facility, primary and secondary data were linked.
The focus of this study was on the LTC NH residents, defined as individuals with either quarterly or annual MDS assessments, that is, with length of stay of at least 90 days. The reason we focused on LTC residents is because the prevalence of PUs and UBIs among them is likely to reflect the quality of care provided in the NH. By contrast, health outcomes of short-term (postacute) residents are more likely to be present at admission, thus reflecting the care received in the hospital prior to NH admission. For residents who had more than one quarterly assessment in the study window, we randomly selected one to avoid within-individual correlation.
Following the CMS criteria employed in the NH Compare quality report card website (CMS 2010), we identified two separate subgroups of residents—those at high risk for PU and those at low risk for incontinence. In the PU group, we included only high-risk residents who were defined as impaired in bed mobility or transfer; comatose; or malnourished. In total, 68,872 unique LTC residents, at high-risk for PUs, were identified in all NYS facilities. After linking the MDS, OSCAR, and the survey data, the final sample contained 20,929 unique LTC high-risk residents in 162 facilities. In the UBI group, we included only residents at low risk of incontinence, therefore excluding residents with short-term memory impairment or severe impairment in cognitive skills for decision making; total dependence in mobility ADLs; indwelling catheter; ostomy; or comatose. Overall, 113,369 such residents were identified in all NYS facilities. After linking the MDS, OSCAR, and the survey data, the final analytical sample included 25,115 unique LTC residents at low incontinence risk residing in 162 NHs.
We defined the two health outcomes of interest as dichotomous variables, based on the MDS. PU outcome was coded as one if any stage PU was present. Incontinence was coded as one if frequent or total bladder or bowel incontinence was present.
The three key measures of NH work environment were constructed from the survey responses. Staff cohesion measures group identity and commonality of goals with regard to resident care needs. This measure (based on a 7-item Likert scale) has been demonstrated as psychometrically valid and reliable for both professional and para-professional NH staff (Cronbach's α of 0.79 and 0.75, respectively) (Temkin-Greener et al. 2009a). Items from this scale, and their means and standard deviations, are presented in Appendix SA2. For each facility, the measure was constructed as the average of all responses provided by workers (professionals and para-professionals) in that institution. Scores range from 1 to 5, with higher scores denoting better staff cohesion.
We defined consistent assignment as percent of nursing staff in a facility who responded that they were “mostly assigned to the same residents” in carrying out their daily work assignments.
Staff may work in teams or not. Those who reported working in a team were asked to characterize their team as either formally organized by management, with explicit protocols and procedures, or self-organized and managed by workers. Therefore, we defined two types of teams as percent of direct care staff reporting being in self-managed and in formally organized teams in each facility. The organization of NHs into multiple units and shifts allows for the simultaneous coexistence of staff in all three modalities—no teams, self-managed teams, or formal teams. Teams were reported as being largely multidisciplinary and included a variety of personnel. There were no substantial differences in staff composition between formal and self-managed teams (Temkin-Greener et al. 2009b).
Based on literature review, we identified separate sets of individual-level risk adjustors for PUs and UBIs (Berlowitz et al. 2001; Mukamel et al. 2003; Li et al. 2009) and used the MDS data to construct risk-adjusted outcomes. Each risk adjustor was interacted with three age groups (66–75, 76–85, ≥86) to account for their differential age-related effects on outcome prevalence.
Facility-level characteristics, such as ownership (profit status), number of residents, and staff hours per resident per day for RN, LPNs, and CNAs, were obtained from OSCAR and used as control variables. We controlled for the location of each facility (upstate versus downstate) since NH practice patterns may vary substantially across these regions.
The analyses were performed in two steps. First, we selected risk adjustors for PUs and UBIs. We then fit generalized estimating equation (GEE) models to investigate the relationship between selected work attributes and risk-adjusted outcomes. In both steps individuals were the unit of analysis.
We used all eligible NYS NH residents to select risk adjustors. Following well-established methods for developing risk-adjusted outcomes (e.g., Mukamel et al. 2003), and to allow cross-validation of each estimated model, we randomly split each sample into two halves: a training sample (used to develop the risk adjustment model) and a validation sample (used to validate the risk adjustment model). Conditional fixed-effects logit models were used to select risk adjustors and their related interaction terms. Variables, or their interaction terms, which were significantly associated with the outcome at the 0.2 level were kept. A joint likelihood ratio test was performed to compare the reduced model with the full model to confirm that we did not exclude any potentially important variables/interactions. We then applied the estimated models to the validation sample and calculated the C-statistic (using random effects model) for both the training and the validation samples to evaluate the goodness of fit in both models.
Using the selected risk-adjustors, from step 1, GEE models with robust standard errors were fit to examine the relationships between work environment and the risk of PUs and UBIs, accounting for clustering at the facility level. Probability weights were used to correct for the higher proportion of nonprofit facilities in our sample compared with all NYS facilities.
Table 1 presents descriptive statistics for the sample and for all NYS facilities. Among residents in the sample NHs, the prevalence of PUs was 13.7 percent, and the prevalence of incontinence was 50.7 percent. There were no statistically significant (at the 0.05 level) differences in these outcomes between our sample and all NYS homes. However, sample facilities were statistically significantly different with regard to several control variables. For bed size and LPN hours/resident/day, the differences are quite small and not likely to be operationally meaningful. Because the study was open to all eligible NYS facilities, rather than a randomly selected sample, the respondents disproportionately came from the not-for-profit facilities and those located upstate. To correct for this sampling bias, we employed sampling probability weights in the GEE models.
Staff cohesion scores ranged from 2.83 to 4.35, across facilities, with a mean of 3.76 (SD = 0.23). Higher scores denote stronger cohesion. The penetration of formal daily care teams ranged from 0 to 33 percent with a mean of 8.5 percent, and the penetration of self-managed teams ranged from 0 to 50 percent with a mean of 7.64 percent. Furthermore, in an average facility, 39.43 percent (SD = 16.41 percent) of nursing staff reported consistent assignment, with a range of 0 to 100 percent.
The effects of individual-level risk factors on PUs and UBIs are shown in Tables 2 and and3,3, respectively. For PUs, the C-statistic of the reduced model was 0.769 in the training and 0.747 in the validation sample. For incontinence, the C-statistic of the reduced model was 0.890 in the training and 0.885 in the validation sample. These C-statistics suggest that the models fit the data well.
The findings for the relationship between facility-level work environment attributes, other covariates, and risk-adjusted outcomes are depicted in Table 4. These models also included individual risk adjustors, which were reported in Tables 2 and and3,,3,, and were not shown again in Table 4.
In partial support for hypothesis 1, we found residents in facilities with stronger staff cohesion to have significantly lower odds of PUs (OR = 0.957; p = .016) and of incontinence (OR = 0.924; p < .001). A one standard deviation (0.23) increase in the staff cohesion score resulted in 4.3 percent lower odds of PUs and 7.6 percent lower odds of incontinence.
We did not find statistically significant support for the association between consistent assignment and either risk-adjusted outcome (hypothesis 2).
After controlling for the individual risk factors and facility characteristics, we found no statistically significant association between prevalence of formally organized teams and either outcome of interest (hypothesis 3). However, for each 1 percent increase in the prevalence of self-managed teams, a resident's odds of having PU was reduced by 2.3 percent (OR = 0.977; p = .028). The coefficient of the squared term for self-managed team penetration was also significant (OR = 1.001; p = .001), suggesting diminishing returns to the positive effects that team penetration has on PU, with a leveling off of the beneficial impact at around 12 percent penetration, which is approximately at the 80th percentile of all NHs.
With regard to other facility characteristics, we found a statistically significant association between NHs located downstate and PUs (OR = 1.437; p = .004), but not for UBIs.
Nursing homes have been characterized as “total institutions” since they control most of the services and many environmental inputs. Therefore, care provided in NHs is thought to influence residents’ outcomes more directly than care provided in other settings. Identifying care and work environment attributes associated with better resident outcomes is a necessary first step in moving toward QI.
In this study, we focused on NH management practices such as teams, consistent assignment, and staff cohesion, and their association with risk-adjusted resident outcomes for PU and incontinence. In health care, the role of teams in improving care quality has been widely heralded, and almost all health care organizations are known to report some form of team practice (Shortell, Marsteller, and Lin 2004). A handful of studies have suggested that in NHs self-managed work teams have a modest positive impact on empowerment and performance among the CNAs (Yeatts et al. 2004; Yeatts and Cready 2007). Furthermore, penetration of self-managed teams has been shown to be associated with fewer NH quality of care deficiencies (Temkin-Greener et al. 2004).
To the best of our knowledge, ours is the first study to empirically demonstrate that higher penetration of self-managed team practice is significantly associated with better resident risk-adjusted outcome in NHs. However, we find this association only for PU, not for incontinence, and only with regard to self-managed teams, not those formally organized by the management; even though both types of teams report similar multidisciplinary structures (Temkin-Greener et al. 2009b). Team approach to care has been viewed as the norm in risk assessment, prevention, and treatment of residents at high risk for PU (AHRQ 2008), although typically such teams are quite specialized and are formally organized. It is possible that in absence of formal PU teams, self-managed teams may also positively influence this outcome. While formally organized teams may be structured and tasked to perform specific functions (in this case not PU-specific), more organically structured self-managed teams may be more apt to quickly respond to resident care needs as they arise. Such teams may be less hierarchical and more spontaneous in the way members communicate, coordinate care, and problem-solve, and thus may be more effective in situations needing quick response as is often the case with PU. Our prior work may provide an alternative explanation. We found that prevalence of formal teams was associated with cost savings, while prevalence of self-managed teams was not (Mukamel, Cai, and Temkin-Greener 2009). If formally organized teams are structured by the management to achieve cost savings, it may not be surprising that we find no association between their prevalence and outcome measures. Similarly, in our prior work, we found no associated between formally organized teams and deficiency citations, but we found such an association for self-managed teams (Temkin-Greener et al. 2004).
We found no relationship between team presence, either self-managed or formally organized, and the incontinence outcome. Team approach to care in NHs may be successful for improving specific outcomes, but it is not likely to be a panacea for all outcomes. At the same time, it may be possible that for certain outcomes teams cannot be effective in improving quality before they reach a minimum penetration threshold. In our sample, only 16 percent of staff in an average facility reported practicing in either self-managed or formal teams. At this level of penetration team impact on some measures of quality may be too marginal to be detectable.
Consistent assignment of nursing staff to residents has been viewed as another means for improving NH work environment. Nationally over 70 percent of NH directors reported consistent assignment of CNAs to residents (Doty, Kane, and Strula 2008). In our study sample, almost 40 percent of staff (SD = 16.41 percent) in average facility said they had consistent assignment. Although consistent assignment is relatively widespread across the study facilities, our findings do not provide support for its association with resident outcomes. Similarly, in our prior work, we did not find an association between consistent assignment and deficiency citations (Temkin-Greener et al. 2004). Although conceptually, consistent assignment provides an opportunity for staff to develop closer relationships with residents and families, it is not by any means a guarantee that such relationships will be positive and effectively lead to better outcomes. Just as creating teams without further investment in ensuring that they are “well-functioning teams” is not likely to ensure good outcomes, consistent assignment without sufficient support or means for problem resolution may create as many poor as good relationships, thus failing to bring about the hoped-for results.
Staff cohesion appears to be the only one of the three attributes that consistently showed a statistically significant association with both PU and incontinence measures. In an average facility, one standard deviation (0.23) increase in the staff cohesion score was associated with 4.3 percent lower odds of PUs and 7.6 percent lower odds of incontinence. Thus, a less than ¼ point improvement in a facility's staff cohesion score may be associated with rather substantial improvements in health outcomes of interest. Prior literature identified several factors as being important predictors of staff cohesion in health care organizations (Shortell, Marsteller, and Lin 2004; Temkin-Greener et al. 2004), including leadership, communication and coordination, and conflict management. In our prior work we also demonstrated these factors to be important predictors of staff cohesion in NHs (Temkin-Greener et al. 2009b). Based on a 5-point Likert scale, we found that a one-point increase in communication/coordination score resulted in a 0.36 increase in staff cohesion, while the effects of leadership and conflict management resulted in substantially lower impacts on staff cohesion, at 0.14 and 0.19, respectively. Since not all of these dimensions appear equally important predictors of staff cohesion, managers wishing to foster better staff cohesion may be well advised to focus first and foremost on interpersonal communication and coordination of care among their staff.
Controlling for all facility-level characteristics, residents in facilities located downstate were at a significantly higher risk of PU, but not of incontinence, compared with residents in upstate facilities. The lack of association with both outcome measures is not surprising as the literature on outcomes typically demonstrates little if any correlation between different QMs. Facilities that provide good PU care need not also provide good incontinence care. However, it is not immediately clear what explains the observed differential with regard to PU outcome by location, and this issue deserves further examination.
Two study limitations should be noted. First, although this study is based on NHs from the largest state in the United States, NYS, generalizations to facilities elsewhere should be made with caution. Second, participation in the survey was voluntary and the possibility of a response bias should be considered. In comparing all eligible NHs to those that participated in the survey, with regard to the outcome measures, we found no statistically significant differences (Table 1). Furthermore, there were no significant correlations between facility response rates and the independent or dependent variables, except for a correlation between lower prevalence of PUs in facilities with higher response rates. Although statistically significant, this correlation is very small (r = −0.230, p = .004), suggesting that response bias, if present, was minimal.
In summary, our findings demonstrate that residents in NHs with poorer staff cohesion experience worse resident risk-adjusted outcomes for PU and incontinence. Our findings for other work environment attributes, such as team presence, were less consistent. These findings, which were echoed in our prior work on deficiency citations (Temkin-Greener et al. 2004), emphasize the importance of good NH management practices in contributing to good resident outcomes.
Joint Acknowledgment/Disclosure Statement: We acknowledge the National Institute on Aging, grant R01 AG23077, which funded this study. Earlier versions of this study were presented in oral sessions at the 2009 annual meetings of the AcademyHealth and the American Public Health Association. The authors of this study have no financial or other disclosures to make.
Additional supporting information may be found in the online version of this article:
Appendix SA1: Author Matrix.
Appendix SA2: Staff Cohesion: Survey Assessment Items.
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