Citizen Participation and Its Impact on Performance in U.S. Nursing Homes

Abstract

Fundamental to democratic societies, citizen participation is an important tool for promoting active, informed, and empowered citizenry as well as responsive and accountable administration. Past literature on citizen participation has focused on its determinants, forms, and prevalence. This study examines the relationship between a specific form of citizen participation—client participation—and organizational performance. We use hybrid data on U.S. nursing homes that combine a survey of nursing home administrators’ managerial practices with federal performance appraisal data. Our empirical findings suggest that more intense levels of client participation, such as the use of clients’ feedback in decision-making, are positively associated with performance: They increase the overall five-star ratings and lower health deficiencies. In contrast, less intense client participation efforts, such as merely communicating with client/family groups, are not significantly related to performance. This study highlights the role of participation intensity, suggesting that public administrators should not only go beyond informing and listening to their stakeholders, but also take steps to use the obtained feedback in organizational decision-making.

Keywords

citizen participation clients performance quality nursing homes

Introduction

Citizen participation, an essential component of democracy, allows community members to receive information on public policies and programs, share feedback about their needs, and get involved in the formulation or implementation of policies and programs (Amirkhanyan & Lambright, 2017). Citizens’ feedback and engagement are important tools for promoting active, informed, and empowered citizenry as well as responsive and accountable administration. They can also help advance the managerial and organizational goals as an input for performance evaluation and improvement (Amirkhanyan & Lambright, 2017). Past studies suggest that understanding citizens’ needs and improving organizational services and overall performance is one of the main reasons why managers solicit feedback and engage others in decision-making (Campbell & Lambright, 2016; Campbell, Lambright, & Bronstein, 2012; Yang & Callahan, 2005). Much of the citizen participation literature we review in the next section of this article focuses on its determinants, types, characteristics, and prevalence. Studies connecting citizen participation to the use of citizens’ feedback and, ultimately, to organizational performance are limited. To address this gap, this research examines the relationship between organizational performance and one specific form of participation—client participation in organizational decision-making.

We study this relationship in the context of U.S. nursing homes.¹ While this industry includes public, nonprofit, and for-profit organizations, it has a high degree of “publicness” in terms of funding and regulation. Since the inception of the federal Medicare and Medicaid programs, public funding has been used to cover government programs outsourced to nonprofit and for-profit providers. In the field of nursing home care, approximately 70% of services delivered by nursing homes are paid either by Medicaid or Medicare programs (Kaiser Foundation Family 2017; Thomas, n.d.). In addition, all Medicare- and Medicaid-certified nursing facilities are subject to federal and state regulation through inspections, licensure, and sanctions. Thus, while being delivered through a range of multisector providers, accountability and citizen engagement in this field are as critical, similar to other publicly funded but privately delivered programs.²

To investigate this topic, we use a hybrid data set that combines a recent survey of nursing home administrators’ managerial practices with federal archival performance appraisal data that include a set of performance indicators—overall five-star ratings and total number of health deficiencies—for each nursing facility in the United States. Our empirical findings suggest that more intense levels of participation—the use of clients’ feedback in decision-making—are positively associated with organizational performance. They increase facilities’ overall five-star ratings and lower their health deficiencies. In contrast, less intense client participation efforts, such as administrators merely communicating with clients and civic groups, are not significantly associated with improved performance. Thus, this article highlights the role of participation intensity: More active levels of client participation make a difference, suggesting that public administrators should not only go beyond informing and listening to various external stakeholders, but also take steps to use the obtained feedback in organizational decision-making. No past studies, to our knowledge, have investigated the relationship between the use of client feedback in decision-making and the archival measures of organizational performance using large samples and quantitative data analysis. Thus, this study makes an important contribution, to our knowledge, of how client participation affects performance. In addition, this study explores the impact of participation in the context of long-term care, a policy area where participation is difficult as the result of low service measurability and informational asymmetries between providers and clients. It is noteworthy that we find evidence of impactful participation in that unique context. In the next sections, we review the literature on the forms and intensity of participation, introduce hypotheses, and describe our data and empirical strategy, followed by the empirical findings and discussion of their implications for research and practice.

Levels of Citizen Participation and Their Impact on Performance

Forms and Levels of Citizen Participation

Advancing the values of effectiveness, justice, and legitimacy, citizen participation is an integral part of contemporary democratic societies (Creighton, 2005; Fung, 2015). Democratic participation can be both indirect—such as voting or donating money—and direct. This latter form of participation is the focus of the current study. Direct citizen participation (or public participation) encompasses

efforts and processes by which community members: (1) receive information related to public policies and programs, (2) share feedback about their needs, opinions or values, and/or (3) are directly involved in the formulation or implementation of these policies and programs. (Amirkhanyan & Lambright, 2017, p. xv)

These efforts are not exclusive to government agencies. Private agencies that receive government funding also engage citizens in many ways (Amirkhanyan & Lambright, 2017; LeRoux, 2009). Documented in past studies, the motives for participation vary from strengthening democracy to those that primarily focus on achieving various internal, service-related, and other managerial goals (Amirkhanyan & Lambright, 2017). On one hand, citizen participation promotes citizens’ democratic identities, improves public trust, and educates and empowers citizens (Amirkhanyan & Lambright, 2017; Ebdon & Franklin, 2006; Gastil & Levine, 2005; LeRoux, 2009; Wang, 2001). On the other hand, citizen engagement helps organizations reach a better understanding of citizens’ needs, gauge public support, address public values conflict, and improve service quality and responsiveness (Amirkhanyan & Lambright, 2017; Creighton, 2005; Halachmi & Holzer, 2010; LeRoux, 2009; Nabatchi, 2012; Roberts, 2004; Smith, 2010).

A large body of scholarly literature has examined the forms of citizen participation used by public and private managers.³ Among the most common forms are public meetings (Adams, 2004; Amirkhanyan & Lambright, 2017; Arnstein, 1969; Creighton, 2005; Ebdon & Franklin, 2006; Fung, 2015; Wang, 2001); advisory boards (Amirkhanyan & Lambright, 2017; Creighton, 2005; Ebdon & Franklin, 2006; Saidel, 1998); data collection strategies such as citizen surveys, interviews, or focus groups (Adams, 2004; Amirkhanyan & Lambright, 2017; Ebdon & Franklin, 2006); as well as coproduction, citizen-initiated contact, engagement through information technology (Amirkhanyan & Lambright, 2017), and others. The strengths and weaknesses of these forms have led scholars to suggest using a combination of methods as a means to accomplish different tasks and target different audiences (Amirkhanyan & Lambright, 2017; Creighton, 2005).

While taking many forms, citizen participation can also vary in terms of intensity—“the extent to which participation efforts provide citizens with meaningful opportunities to engage in decision-making or service delivery in ways that influence policies or programs” (Amirkhanyan & Lambright, 2017, p. 43). Two taxonomies of participation intensity in this body of literature⁴ are particularly influential. Arnstein (1969) classifies participation into eight levels based on the extent to which power is distributed between governments and citizens: from the lower levels that involve manipulation, education, garnering citizens’ support, informing, and consulting with citizens, to the higher levels involving partnership, delegated power, and extensive citizen control. The low-intensity efforts are more symbolic and characterized by one-sided communication and limited citizens’ control. High-intensity participation is likely to be two-sided and involves more power sharing and greater influence on agencies’ decisions, actions, and outcomes (Arnstein, 1969). Similarly, Fung’s (2006) “democratic cube” is a classification of participation intensity based on participant selection, communication modes, and the degree to which citizens’ input is connected to policy outcomes. Fung ties participation intensity to its potential to advance legitimacy, justice, and effectiveness. Variation in intensity may in part be determined by “the manager’s willingness to structure the format to create representative and meaningful discourse” (Moynihan, 2003, p. 183). Thus, administrators play a critical role in choosing the intensity of participation based on normative considerations and calculations of instrumental benefits and administrative costs (Moynihan, 2003).

Arnstein and Fung agree that higher levels of participation go beyond merely communicating with citizens and informing them of policy alternatives. They involve the use of citizens’ input in decision-making. Research on the use of citizens’ input in policy-making and administration is limited. Some empirical studies suggest that client feedback is used in priority-setting and action planning, goal-setting, performance measurement, and resource allocation (Adams, 2004; Amirkhanyan & Lambright, 2017; Andrews, Cowell, & Downe, 2011; Campbell et al., 2012; Lukensmeyer, 2007; Moynihan, 2003; Quick & Feldman, 2011; Weeks, 2000). These uses, however, may be less common than the strategies of sharing citizens’ input with other organizations, making minor service-delivery changes, and initiating new services (Amirkhanyan & Lambright, 2017; Campbell et al., 2012). More importantly, we do not fully understand the impact that citizens’ feedback has on organizational performance and the broader community well-being. Some studies suggest that participatory governance can in fact contribute to significant reductions in poverty and unemployment (O’Leary, Gerard, & Bingham, 2006). Our goal is to contribute to this literature by further exploring the organizational-level effects of client participation.

Client Participation in the Context of Health and Human Services

The concept of citizen participation suggests that a wide range of individual stakeholders can get engaged in governance: from clients to the members of the general public, current and retired professionals in the field, interest group members, members of neighborhood associations, religious groups, and others (Arnstein, 1969; Creighton, 2005; Frederickson, 1991; Roberts, 2004; Van Til & Van Til, 1970; Vigoda, 2002). The focus of this study is on client participation and the impact of their participation on nursing home service quality. In the field of health and human services and social policy, organizational clients are a particularly relevant group as their experiences and well-being are profoundly affected by the services they receive (Van Til & Van Til, 1970). By seeking clients’ input, administrators can better understand their needs, develop stronger relationships, and use clients’ feedback to inform and enhance organizational governance and operations (Bryson, Quick, Slotterback, & Crosby, 2013; Burby, 2003; Fung, 2006; Nabatchi, 2010; Thomas, 1995). Client participation has been found to be among the most prevalent forms of citizen participation in the field of health and human services (Amirkhanyan & Lambright, 2017).

Our focus on client participation in the context of nursing home care warrants a more careful look at the related concept of patient and family participation in the broader field of health care.⁵ The opportunities for and the impacts of public participation—broadly speaking—have been significant and are likely to expand in the future in the field of health care (Nabatchi & Leighninger, 2015). The latter has been examined on a continuum from the patients’ role in health care such as in prevention, diagnosis, and treatment (encompassing doctor–patient interactions) to involvement in organizational design and governance, such as partnering with managers to plan, deliver, develop, research, or evaluate services (Carman et al., 2013; Snyder & Engstrom, 2016). Similar to the concept of participation intensity in the broader citizen participation literature, patient participation spans from lower to higher levels of power sharing between the management and the patients, as well as from micro-level caregiver–patient interactions to involvement in organizational or health systems–level decisions (Carman et al., 2013; Nabatchi & Leighninger, 2015; Snyder & Engstrom, 2016). Importantly, this literature finds a positive relationship between reports of shared decision-making and patient satisfaction (Jahng, Martin, Golin, & DiMatteo, 2005; Keating, Guadagnoli, Landrum, & Borbas, 2002; Snyder & Engstrom, 2016), as well as patient outcomes (Snyder & Engstrom, 2016). In these studies, shared decision-making involves patients with diabetes or breast cancer indicating that their opinion is included in the treatment determination, while patient outcomes span from patient satisfaction from the choice of treatment and information they were provided in the context of breast surgery (Keating et al., 2002) to health perception scales and adherence to treatment recommendations scales (Jahng et al., 2005). Theoretically, a set of enabling factors leads to patient involvement, which in turn is expected to influence patient satisfaction, as well as cost and health outcomes (Snyder & Engstrom, 2016). Importantly, past research also highlights the importance of matching patients’ actual and desired roles in decision-making (Keating et al., 2002). With this evidence in mind, patient participation in service delivery—in the context of both acute and chronic care facilities—is likely to be motivated by elements of technical rationality: systematic application of professional (evidence-based) practices, scientific techniques, and treatment models to help solve day-to-day problems.

Hypotheses

Building on the broader public participation literature and the studies of patient involvement in the health care setting, our study examines the effect of engaging clients in the nursing home care context. Our goal is to explore the effect of both lower level participation, such as the administrators’ interactions with clients and family members, and higher level participation that involves using clients’ and family members’ feedback in decision-making. We propose that both strategies will have a positive effect on organizational performance and, more specifically, on nursing home service quality.

Lower levels of client participation involve interactions that may not result in substantive changes in the way administrators act and organizations operate. Arnstein (1969) discusses the strategies of “manipulation,” “therapy,” “informing,” “consultation” and “placation” as lower levels, reflecting largely “rubberstamp” participation. While the participants lack decision-making power, and the “powerholders” have the ultimate control over decisions and policies, these strategies allow citizens to hear and be heard, as well as to be advised and educated. Similarly, Fung (2006) identifies “individual education,” “communicative influence,” “listening,” “expressing” and “developing preferences” as participation strategies that rank low on participants’ authority and communication mode.

Some of the lower intensity participation opportunities involve one-way communication from citizens to service providers. Numerous empirical studies, focusing on citizen participation more broadly, find that citizens’ contact of government officials through letters, phone calls, or visits and conversations during service delivery is a common form of citizen participation, ranging in prevalence from 13% to 40% across policy areas (Adams, 2004; Amirkhanyan & Lambright, 2017; Nabatchi & Leighninger, 2015; Roberts, 2004; Sharp, 2012). These interactions allow citizens to share their concerns and expectations. In the residential context, these contacts between clients and administrators are likely to be ongoing. Clients’ and families’ feedback may be related to staffing concerns and preferences, facility conditions and limitations, dietary preferences, access to specialized care, as well as social life and related initiatives. In addition, administrators may in turn “message” facility clients and family members about facility plans, rules, and regulations to enhance clients’ understanding and cooperation in various processes. Finally, nursing home administrators may engage in more interactive dialogues with client families and larger groups.

Although these interactions do not necessarily place client groups in advisory or leadership roles and may not involve any joint decision-making, we expect them to positively affect organizational performance. Administrators’ interactions, information sharing, conversations, and deliberations with clients and family members are likely to result in some transformations of participants’ relationships and roles (Forester, 1999). These transformations may involve development of a common language—shared understandings, meanings and values between service providers and clients—and may eventually result in a more family-like, relationship-based environment in a residential facility. Administrators’ conveying important updates and issues to client groups can have an educational effect, aiming at enhancing clients’ appreciation of important issues related to organizational policies, resources, or future plans (Gastil & Levine, 2005). Administrators may inform their clients of the challenges, constraints, or legal mandates that the organizations are facing, as well as the current efforts and the plans for improvement. These efforts are likely to result in clients’ deeper understandings of organizational operations, more trust toward the administration, further client-to-client discussions, behavioral changes, and activism. Taken together, even if mainly symbolic and less impactful, these efforts are likely to produce a more open culture and greater client–staff cooperation. In this context, client concerns are more likely to be raised, discussed, and responded to directly with the nursing home staff and administration rather than through complaints to state licensing and certification agencies. This additional information about client needs and wants can then be considered by administrators in service-delivery decisions.

In addition to the practices discussed above, theories of participation also identify the practices that allow for greater citizen control over the administrators’ decisions. Arnstein’s (1969) “partnership” strategies enables citizens to negotiate and share decision-making responsibilities, whereas Fung (2006) separates “advising and consultation,” “co-governing,” “aggregating and bargaining,” “deliberating and negotiating” as opportunities that allow for a greater authority, influence, and participation in decision-making by citizens. While giving clients full control over decision-making in nursing homes is likely not feasible, administrators who genuinely share some degree of decision-making power with clients may in fact take action to incorporate nursing home residents’ feedback into organizational policies and operations. It has been long understood that ordinary citizens can in fact provide insightful comments and recommendations, particularly when issues are clearly explained and participation opportunities are well organized (Gastil & Levine, 2005). Adjusting nursing home operations in ways that respond to the preferences related to treatment plan, staffing, room conditions, diet, events, and other aspects of residential life is likely to improve client cooperation, satisfaction, and outcomes, similar to the findings of greater patient compliance and satisfaction in non-long-term care settings (Jahng et al., 2005). They can help with early identification of emerging problems, patient compliance with treatment recommendations, minimization of errors in quality of care, and improvement in the clients’ quality of life. Thus, responding to clients’ preferences is likely to result in more patient-centered and responsive service provision.

In summary, we expect that both lower level participation, such as the administrators’ one-way or two-way interactions with client groups, and higher level participation—the actual use of clients’ and family members’ feedback in decision-making—will have a positive effect on service quality. Formally,

Hypothesis 1: Nursing home administrator’s interaction with clients (and client groups) will have a positive effect on service quality.

Hypothesis 2: Incorporating client’s and family members’ input in organizational policies and decisions will have a positive effect on service quality.

Method

Data

We use a combination of archival data and a recent survey of nursing home administrators. First, Nursing Home Compare (NHC), a national administrative database created by the Centers for Medicare and Medicaid Services (CMS), based on state agencies’ quality assessments of all Medicare and Medicaid certified nursing homes, contains facility names, addresses, federal provider numbers, ownership status, size, occupancy, hospital affiliation, staffing, and other characteristics. NHC includes unbalanced panel data with multiple observations for each facility. As explained below, we use two waves of the NHC data for the current analysis: the earlier wave for the independent variables and the later wave for the dependent variables. The second data set comes from the Texas A&M University’s (TAMU) National Nursing Home Survey, administered in 2013 (Compton, Calderon & Meier, 2013). The survey sample was randomly selected from nursing homes registered in the NHC data set. The survey was mailed to a random sample of 1,000 for-profit and 1,000 nonprofit homes, as well as to all 903 governmental nursing homes operating at the time. A total of 725 online or paper surveys were completed in three waves, producing a response rate of 24.9%. The final sample included 617 organizations due to the missing observations in the key variables.

The third data source, the Area Health Resource Files (AHRF), is a public data set produced by the U.S. Bureau of Health Professionals. AHRF includes county-level health care indicators and socioeconomic data. Whereas variables from the TAMU survey are self-reported, the data on performance and county-level context come from governmental data sets, minimizing common source bias (Amirkhanyan, Meier, O’Toole, Dakhwe, & Janzen, 2018).

Variables

The dependent variables are two facility-level measures of service quality from NHC: the total number of health deficiencies and the overall five-star rating. State inspections of all Medicare and Medicaid certified nursing facilities determine whether their processes and outcomes meet federal standards. In addition to these standard inspections, complaint inspections can be triggered by complaints filed by clients or other interested parties. The total number of health deficiencies reflects the number of regulatory violations found during a single inspection cycle (usually spanning from 9 to 15 months). In the literature, this measure has been used extensively as a valid and comprehensive indicator of nursing home service quality, capturing regulatory areas of administration, nursing care quality, human rights, nutrition, and others (Amirkhanyan, Meier, & O’Toole, 2017; Amirkhanyan et al., 2017; Mullan & Harrington, 2001; O’Neill, Harrington, Kitchener, & Saliba, 2003). Theoretically, it can take any value from 0 to more than 180. In our sample, the total number of health deficiencies ranges from 0 to 33 with the mean of 5.76, and standard deviation of 4.82.

The overall five-star rating is the second measure of service quality. Developed as a transparency tool by the CMS in 2008, the rating incorporates three domains: (a) health inspection results (number of deficiencies from the three most recent inspections, with more weight given to the most recent survey), (b) staffing (reflecting staffing hours per resident day), and (c) quality ratings (measures reflecting patients’ clinical data). The overall rating of all three domains is assigned stars ranging from one to five, with five representing the best quality of service.

Two items from the TAMU survey were used to create two central independent variables measuring client participation. The first item asked respondents how frequently they interacted with civic (resident/family) groups (with response categories of 0 = never, 1 = yearly, 1.5 = quarterly, 2 = monthly, 3 = weekly, 4 = more than once a week, 5 = daily). Based on the somewhat skewed distribution of these responses, we created a dummy variable coded 1 for those who reported interactions occurring monthly or more frequently (monthly, weekly, more than weekly, and daily) and 0 for interactions occurring never, yearly, or quarterly. Other studies on nursing homes also measured family/resident participation using a cut point of “monthly,” and provided evidence that residents’ quality of life is significantly enhanced when receiving at least monthly family visits (Mitchell & Kemp, 2000; Port et al., 2005). This variable measures the more basic level of citizen participation limited to “interacting” with groups representing clients and their families. We also asked to what extent respondents agreed with the following statement: “Residents’ and families’ feedback and outcomes are taken into consideration when revising policies” (with response categories of 4 = strongly agree, 3 = agree, 2 = disagree, or 1 = strongly disagree). Due to the skewed distribution of the data (there were few who disagreed), we created a dummy variable coded as 1 for strongly agree and 0 for all other responses. This variable measures the use of feedback in organizational policy-making. Our survey was administered to nursing homes’ top executives, and thus, the interactions between the executives and civic groups as well as incorporation of the feedback these groups provide are beyond the daily patient–nurse interactions⁶ and instead involve decisions and interactions with the administration.

The analysis incorporates several control variables from the NHC, TAMU survey, and AHRF (see Appendix A). First, we account for several organizational characteristics from the NHC. Because past performance likely affects present performance, we incorporate a lagged measure of total number of health deficiencies and overall star ratings (in the deficiencies model and star ratings model, respectively). Organizational ownership—public, nonprofit, or for-profit—has been shown to be an important predictor of nursing home performance (Amirkhanyan, Kim, & Lambright, 2008; Davis, 1993; Harrington, Woolhander, Mullan, Carillo, & Himmelstein, 2001; O’Neill et al., 2003). We created two dummy variables denoting nursing homes’ nonprofit and public status, as opposed to for-profit (the omitted ownership category in all models).

The impact of size on performance has been investigated across multiple policy areas with somewhat mixed results (Boyne, 2003; Moynihan & Pandey, 2005; Riportella-Muller & Slesinger, 1982). Past research found a positive association between nursing home size and regulatory violations, suggesting that smaller homes may be creating a more personalized, intimate, and nurturing environment and may be less likely to stifle innovation (Amirkhanyan, 2007). In our analysis, the number of residents occupying beds in a given nursing home reflects the organizational size. Availability of nursing staff has been shown to be correlated with various dimensions of performance (Amirkhanyan et al., 2008; Bowers, Esmond, & Jacobson, 2000). Thus, we control for staffing using the total nursing hours per resident per day, which include registered nurse, vocational nurse, and nurse aide hours per resident per day.

As we do not have direct measures of financial performance, we control for the percentage of Medicaid residents to reflect the scope of services provided to “impoverished” nursing home residents. Hospital affiliation measures a facility’s affiliation with a hospital (“1” if yes, “0” if freestanding). Hospital affiliation is likely to reflect lower managerial and organizational autonomy and higher level of acute (postsurgical) care needs among clients (Amirkhanyan, 2008). To account for organizational age and stability, we include two measures. As no information is available on when each facility was established, we use a proxy variable, years since certification, to measure facility’s age. Ownership change within a year indicates whether facility’s ownership changed within 12 months of the survey (“1” if yes, “0” if no).

We follow Angelelli, Mor, Intrator, Feng, and Zinn (2003), Castle (2005), and Grabowski (2001) in using the Herfindahl index to measure local market concentration, expecting nursing homes in more competitive markets to have fewer violations. This county-level index is the sum of squared market shares (measured in number of beds) for all Medicare- and Medicaid-certified nursing homes in each county, varying between 0 (most competitive) and 1 (most concentrated).

From the TAMU survey, we use several measures characterizing the nursing home administrators. While the main focus of this study is on senior administrators’ strategies, we also control for three key executives’ characteristics: race and gender of the manager are measured with dummy variables coded as “1” for White and “1” for female, respectively. Administrators’ tenure is measured using years as a nursing home administrator.

Finally, we use data from AHRF to control for various contextual factors. Urbanicity measures population density per square mile to account for the urban/suburban/rural context of the nursing home location. We also include the percentage of the county population below the poverty line as well as the percentage of county population aged above 65 years to account for demand and client population characteristics.

Regression Analysis

We estimate several regression models for each dependent variable. We estimate negative binomial regression models to deal with the count nature of the dependent variable and overdispersion of the total number of health deficiencies and include state fixed effects to control for state differences in regulation. For sensitivity analysis, we also estimate ordinary least squares (OLS) with robust standard errors and state fixed effects to account for heteroscedasticity, interdependence of observations, and unobserved factors in each state. For the overall five-star ratings, we estimate generalized ordered logit with state fixed effects. The specification takes the following form:

\begin{array}{l} Q_{2014 - 15} = β_{0} + β_{1} {FI}_{2012 - 13} + β_{2} {UF}_{2012 - 13} \\ + β_{3} Q_{2012 - 13} + β_{4} X_{2010 - 13} + e \end{array}

where “Q” represents measures of nursing home quality, “FI” is frequency of interaction with civic groups, “UF” is use of feedback in decision-making, and “X” a vector of control variables. The dependent variables come from the January 1, 2016, NHC file, reflecting total health deficiencies and the overall five-star ratings identified during the most recent inspection cycle as of January 1, 2016 (typically, 9 to 15 months prior to January 1, 2016, hence resulting in a “2014-15” subscript). The lagged quality measures as well as other organizational characteristics included as independent variables come from the January 1, 2014, NHC file, reflecting data collected during the most recent inspection cycle as of January 1, 2014 (typically, 9 to 15 months prior to January 1, 2014, hence resulting in “2013-14” subscript). We expect the administrators to take some time to consider and implement clients’ feedback into organizational policies and expect the impact on service quality to emerge with a lag of 1 to 2 years. Independent variables related to client participation are drawn from the TAMU Survey, administered in 2013. Finally, county specific control variables are retrieved from the 2010 to 2011 AHRFs.

Findings

Frequency distributions for two client participation variables are shown in Table 1. On average, nursing home administrators interact with residents or their family groups once a month, with about 19% of nursing home administrators communicating with these groups less than once a year. As an example, nursing homes may operate family councils and hold monthly meetings to discuss the quality of care and other facility issues. We recoded this item into a dichotomous variable equal to “1” for interacting more than monthly and “0” for interacting less than quarterly. Table 1 also shows that 52.2% of administrators “strongly agree” and 45.2% “agree” that clients’ and families’ feedback is considered in decision-making. To address the potential positivity bias, we recoded the item into a dichotomous variable as equal to “1” for “strongly agree” and “0” for “agree,” “disagree,” and “strongly disagree” responses.⁷ The correlation between two client participation measures is shown in Table 2. Pearson’s correlation coefficient between two measures was close to 0 (r = .08, p < .05), suggesting that interactions with residents/family are not strongly related to the degree to which their feedback is considered and incorporated in the decision-making.⁸

Table 1.

Tabular Statistics for Interaction With Civic Groups and the Use of Clients’ Feedback in Decision-Making.

	(Interaction with civic groups) How frequently do you interact with the civic (resident/family) groups?
Recoded	Response category	Obs. (N)	Percentage
0	Never	31	5.0
	Yearly	82	13.3
	Quarterly	3	0.5
1	Monthly	375	60.8
	Weekly	77	12.5
	More than once a week	24	3.9
	Daily	25	4.1
	(Clients’ feedback considered in decision-making) To what extent do you agree or disagree with the following statement? Residents’ and families’ feedback and outcomes are taken into consideration when revising policies.
Recoded	Response category	Obs. (N)	Percentage
0	Strongly disagree	1	0.2
	Disagree	15	2.4
	Agree	279	45.2
1	Strongly agree	322	52.2

Note. Total number of observation is 617 for both variables.

Table 2.

The Correlation Between Interaction With Civic Groups and the Use of Clients’ Feedback.

	(D) Interaction with civic groups	(D) Clients’ feedback considered
(D) Interaction with civic groups	1
(D) Clients’ feedback considered	.0792	1
	(.0492)

Note. “D” indicates that the variables are recoded as binary variables as noted in Table 1. Pearson’s correlation coefficient (p value).

Descriptive statistics for all variables are presented in Table 3. Facilities in our sample have on average 5.8 deficiencies in a single inspection cycle (2014-2015 wave), and their average star rating is 3.4 stars. In terms of ownership, 37% of facilities are nonprofit, whereas 32% are publicly owned. Nursing home administrators are overwhelmingly White (86%), and 46% are female. The average facility capacity is 91 residents with the mean staffing levels of 4.3 total nurse hours per resident per day. Nursing homes in our sample operate in counties with 15.3% of senior (age 65 and above) population and 15.4% residents in poverty.

Table 3.

Descriptive Statistics for Key Variables.

	Obs.	M	SD	Minimum	Maximum
Dependent variables
Deficiency in 2015	617	5.760	4.818	0	33
Overall five-star rating in 2015	617	3.425	1.333	1	5
Independent variables
(D) interaction with civic groups	617	0.812	0.391	0	1
(D) clients’ feedback considered	617	0.522	0.5	0	1
Controls
Deficiency in 2013	617	5.859	5.13	0	34
Overall five-star rating in 2013	617	3.596	1.256	1	5
Nonprofit	617	0.374	0.484	0	1
Public	617	0.319	0.467	0	1
White manager	617	0.856	0.352	0	1
Female manager	617	0.457	0.499	0	1
Years as a nursing home administrator	617	13.901	10.115	0	41
Total number of residents	617	90.564	70.123	10	694
Total nurse staffing hours	617	4.256	0.976	1.945	11.395
Medicaid residents (%)	617	57.545	22.224	0	100
Hospital affiliated	617	0.102	0.303	0	1
Ownership changed within 1 year	617	0.021	0.144	0	1
Years since certified	617	22.271	11.879	1	46
Population density	617	0.804	2.823	0.001	35.369
Older adult (%)	617	15.297	4.138	6.625	35.139
Poverty (%)	617	15.373	5.164	4	41.8
Market concentration	617	0.290	0.287	0.003	1

Note. “D” indicates that the variables are recoded as dummy variables.

Table 4 shows regression results including fixed effects, negative binomial, and ordered logit models. The findings consistently suggest that administrators’ interactions with family and resident groups are not significantly associated with nursing home performance. All three models indicate that interactions with civic groups do not significantly reduce deficiency or increase star quality rating. However, clients’ feedback used in decision-making does significantly enhance nursing home performance. Keeping other factors constant, use of clients’ and families’ feedback in revising policies significantly reduces the number of deficiencies. The standardized beta is –.08 (sig. <.05) in the fixed effects model and –.02 in the negative binomial model (sig. <.05). In addition, using clients’ feedback in decision-making also improves a facility’s overall five-star rating: When we standardize all independent and control variables, a nursing home’s ordered log-odds of being in a higher five-star rating category increase by 0.17 (sig. <.05). Thus, a higher level of participation intensity, entailing the use of clients’ feedback, appears to matter in improving performance after controlling for other relevant factors, including past performance.

Table 4.

The Impact of Client Participation on Nursing Home Performance.

	(1) Fixed effects		(2) Negative binomial		(3) Ordered logit
	DV: Deficiency		DV: Deficiency		DV: Star rating
	β/(SE)	β/(SE)	β/(SE)	β/(SE)	β/(SE)	β/(SE)
(D) Interaction with civic groups	−.038		−.007		.001
(D) Interaction with civic groups	(.04)		(.01)		(.08)
(D) Clients’ feedback considered		−.082*		−.014*		.173*
(D) Clients’ feedback considered		(.04)		(.01)		(.08)
Deficiency (2013)or star rating (2013)^a	.296**	.293**	.049**	.049***	.958**	.957**
Deficiency (2013)or star rating (2013)^a	(.04)	(.04)	(.01)	(.01)	(.09)	(.09)
Nonprofit	−.104*	−.100*	−.019*	−.018*	.281**	.284**
Nonprofit	(.05)	(.05)	(.01)	(.01)	(.09)	(.09)
Public	−.107*	−.104*	−.017^†	−.016^†	.212*	.223*
Public	(.05)	(.05)	(.01)	(.01)	(.10)	(.10)
White manager	−.050	−.043	−.010	−.010	.078	.069
White manager	(.04)	(.04)	(.01)	(.01)	(.08)	(.08)
Female manager	−.016	−.008	−.003	−.002	−.053	−.063
Female manager	(.04)	(.04)	(.01)	(.01)	(.08)	(.08)
Years as a nursing home administrator	−.035	−.040	−.005	−.006	.050	.053
Years as a nursing home administrator	(.04)	(.04)	(.01)	(.01)	(.08)	(.08)
Total number of residents	.037	.039	.005	.006	−.275**	−.272**
Total number of residents	(.05)	(.05)	(.01)	(.01)	(.09)	(.09)
Total nurse staffing hours	.046	.045	.007	.007	.101	.105
Total nurse staffing hours	(.04)	(.04)	(.01)	(.01)	(.08)	(.08)
Medicaid residents (%)	−.015	−.008	−.002	−.001	−.082	−.089
Medicaid residents (%)	(.04)	(.04)	(.01)	(.01)	(.09)	(.09)
Hospital affiliated	−.058	−.058	−.012	−.011	.015	.020
Hospital affiliated	(.04)	(.04)	(.01)	(.01)	(.08)	(.08)
Ownership changed in 1 year	−.005	−.002	−.001	−.001	−.013	−.017
Ownership changed in 1 year	(.04)	(.04)	(.01)	(.01)	(.07)	(.07)
Years since certified	.003	.006	.003	.004	−.107	−.115
Years since certified	(.04)	(.04)	(.01)	(.01)	(0.08)	(.08)
Population density	−.084^†	−.076^†	−.025**	−.023*	.180*	.164^†
Population density	(.04)	(.04)	(.01)	(.01)	(0.09)	(.09)
Elderly (%)	.016	.006	.002	−.001	.055	.071
Elderly (%)	(.04)	(.04)	(.01)	(.01)	(0.08)	(.08)
Poverty (%)	.031	.023	.003	.002	−.030	−.017
Poverty (%)	(.04)	(.04)	(.01)	(.01)	(0.08)	(.08)
Market concentration	.034	.035	.005	.005	−.154^†	−.161^†
Market concentration	(.05)	(.05)	(.01)	(.01)	(0.09)	(.09)
R² (pseudo R² for (2) and (3) model)	.1192	.1244	.0209	.0218	.1184	.1211
N	617	617	617	617	617	617

Note. Constants not presented. Standardized beta reported here.

Deficiency (2013) was controlled in the fixed effects model and the negative binomial models, and star rating (2013) was included in the ordered logit model.

†

p < .10. *p < .05. **p < .01 (two-tailed test).

Consistent with past studies (Amirkhanyan et al., 2008),⁹ nonprofit and public nursing homes perform significantly better than for-profit nursing homes, and urban areas are associated with fewer deficiencies and higher star ratings. In addition, the total number of residents and market competition are significantly related to five-star ratings: Star ratings are higher in smaller facilities, whereas higher levels of market competition is associated with higher ratings.

Discussion

In democracies, citizens have opportunities to engage in governance in a variety of ways. While the most common conceptualizations of active citizenship involve voting, contacting legislators, or participating in mass protests, other forms of participation in administration can also make tangible and long-lasting impacts on public and publicly funded institutions. This article focuses on client participation in organizational decision-making in the context of nursing home care, largely financed by Medicaid and Medicare programs and regulated by the CMS. This study makes a unique contribution to the public participation, organizational performance, and health policy literature by examining the relationship between service quality and administration–client interactions, as well as the use of clients’ feedback.

Similar to other management strategies, such as strategic planning or performance measurement, participation can be and often is used symbolically: to comply with the existing norms or mandates or to help establish relationships with stakeholders (Brody, Godschalk, & Burby, 2003; Burby, 2003; Cooper, 1979; Ebdon & Franklin, 2006; Godschalk & Stiftel, 1981; Slotterback, 2008; Yang & Callahan, 2005). In these cases, relying on low-intensity levels of participation may be an attractive option that minimizes the costs and possible conflicts that arise during active deliberations. Informing clients of new policies, services, or future plans and collecting comments, complaints, and preferences, are common examples of such lower level, one-sided participation mechanisms. While educating the clients, alleviating their concerns by sharing additional information, and learning about clients’ need and priorities, they merely allow citizens to hear and be heard (Arnstein, 1969), and result in minimal impact on or change in organizational policies and operations. We hypothesized that these strategies are likely to facilitate information sharing, build trust, improve organizational culture, and educate the clients and service providers about mutual preferences and challenges. Our study, however, suggests no evidence of quality improvement stemming from nursing home administrators’ “interactions” with client and resident groups. This finding is important, particularly because past empirical research in the field of health and human services finds that lower intensity participation is prevalent (Adams, 2004; Amirkhanyan & Lambright, 2017; Nabatchi & Leighninger, 2015; Roberts, 2004; Sharp, 2012). Although the strategies can serve various managerial purposes, such as compliance with external mandates or client education, our study suggests that these efforts may not result in tangible service quality improvements. We must note, however, that our study is focused on a single dimension (and two archival measures) of service quality. More research is needed to explore whether lower intensity levels are associated with improved client perceptions and satisfaction or other aspects of organizational performance.

Our research also suggests that when clients’ feedback is in fact incorporated in administrators’ decision-making, these efforts are associated with improvements in two archival measures of service quality developed by third-party inspectors: lower regulatory violations and higher star ratings. The measures of quality we use reflect violations in the federally mandated standards of health care quality related to patients’ quality of care, quality of life, residents’ rights, administration, nutrition, and others. Five-star ratings also reflect staffing levels and patient clinical outcomes. Incorporating clients’ input likely improves facility practices and reduces clinical and nursing care errors and the associated complications, thus improving clients’ clinical outcomes. Not just listening but also incorporating clients’ feedback in decision-making may also create trust between service providers and recipients, result in a deeper understanding of clients’ needs, and prompt a more proactive approach to problem-solving. As a complex professional field, nursing care is influenced by the best practices taught at professional schools and the norms advanced by professional associations. While adhering to these norms and standards, our research suggests that it is still beneficial to be responsive to clients, whose perception and participation may be critical in ensuring that the treatment is complied with and is therefore effective. Listening to and adopting clients’ feedback would ensure an environment in which the clients are more likely to have confidence and adhere to the professional advice. Listening to clients’ feedback and making changes may also reduce the prevalence of client complaints to state regulators that often trigger inspections resulting in additional deficiencies.

The significant association between client participation and performance is especially notable in the context of health and human services. Targeting clients with severe health limitations and poor prognoses, nursing home care suffers from low service measurability. Third-party reimbursement system, by which care provided to most nursing home clients is paid by a federal program or a private insurance company, further exacerbates the informational asymmetry between the clients, payers, and the providers. Historically, strong regulation has been used as a primary mechanism to minimize providers’ moral hazard and opportunistic behavior. It appears that participation, especially when it entails changes in administrators’ actions, may serve as an additional important accountability mechanism that can result in quality improvement. Past health care literature suggested a positive relationship between shared decision-making and client satisfaction (Jahng et al., 2005; Keating et al., 2002; Snyder & Engstrom, 2016). We find that, in addition to these subjective/perceptual benefits, participation is also associated with the more objective aspects of service quality: regulatory compliance with federal quality standards, as verified by independent third-party surveyors.

Several limitations of this study stem from its research design. Our focus on client participation in the health care context is unique in numerous ways, which limits the external generalizability of our findings. Organizational clients are a fairly uniform group with a set of concerns typically revolving around improved service quality and access. These concerns are largely consistent with the federal regulatory standards we use as measures of nursing home performance. Thus, it is reasonable to expect that by being responsive to clients’ concerns related to quality, nursing homes can also improve their deficiency scores assigned by the state regulators. By contrast, a city or county government implementing a range of health and human service programs is likely to face a more complex array of stakeholders with a wider variety of interests and demands. Satisfying or even taking into account these demands in policies and decisions can involve difficult trade-offs and conflict, and hence it may be harder to observe the association between participation of these different groups and organizational performance. Our findings may be more relevant in contexts with more narrowly defined “client groups” such as welfare to work programs, family planning, juvenile justice, and many others. In addition, our study may be particularly relevant to the context of nonprofit and for-profit government contractors: organizations with defined communities of service recipients and external mandates to deliver certain levels of service quality.

Another key limitation of the study has to do with the quantitative lens we use: While filling the gap in our knowledge of administrators’ practices having to do with incorporating input and translating it into action, our study does not address the process. Collection and adoption of input from one or more groups of stakeholders is likely to be a process complicated by structural, cultural, normative-institutional, political, and other considerations. Some features of feedback, as well as certain organizational and environmental factors might encourage or discourage decision makers from adopting the input. Describing and analyzing this dynamic process remains largely outside of the scope of this study; however, it represents an important direction for the future research.

In addition, by virtue of relying on a semi-structured survey of nursing home administrators, our data on client participation are limited to two measures reflecting managers’ actions. The focus of these interactions commonly involves clients’ sharing concerns regarding quality of life, quality of care, access, residents’ rights, and other topics, whereas the administrators provide information about facility resources and policies. Administrators likely use additional informal methods of client participation to gain or communicate information. In the absence of qualitative data on these interactions, we are limited in our ability to fully understand the process of client participation.

Our findings suggest important implications for long-term care administrators. Complying with the federal regulatory standards is an important priority in this context. Our study suggests that client participation can be a source of improvement in the scope of regulatory violations. While soliciting clients’ feedback and searching for ways to use that feedback in organizational policies and practices require staff time and resources, this investment appears is worth the effort: It can, in fact, reduce deficiencies in a variety of areas reflected in federal standards, such as administration, quality of care, quality of life, nutrition, residents’ rights, and others. In addition, despite the level of care complexity involved in caring for chronically ill patients and the limitations of patients’ expertise in these complex decisions, our survey suggests that the clients’ feedback, which goes beyond the usual patient–nurse interactions, may be beneficial when used in facility administrators’ decisions. These findings reaffirm the value of impactful participation in highly professionalized and complex fields where providers’ behavior is largely guided by professional training, norms, and standards.

This study suggests several directions for the future research. The focus of this article is on the use of client feedback in decision-making. Public service organizations have numerous external stakeholders, and engaging each of them in governance may produce its own unique benefits. Each of the multiple constituencies that public, nonprofit, and for-profit organizations have—volunteers, donors, partners, or community neighbors, to name a few—may care about distinct aspects of organizational work. Their participation may help ensure higher levels of accountability and help build trust between parties to jointly work on resolving complex problems. Thus, broadening the scope of the stakeholder groups in evaluating the impact of their feedback in organizational decision-making may be an interesting next step for researchers to pursue.

While the current study considers the effect of participation on an archival measure of quality—the aggregate of all regulatory violations—it may be interesting to explore the effect of participation on perceptual measures of performance, such as client, family, and staff satisfaction with service quality. In addition, limited by the design of our survey, we considered two levels of client contact: interaction with clients and use of clients’ feedback. Exploring a wider range of levels of participation—consultation, deliberation, joint decision-making, and others—may further contribute to our understanding of participation intensity and its impact on organizational performance.

Our article also motivates additional research of the impact of client (and, more broadly, citizen) participation in the context of human services. Establishing rapport and securing patients’ understanding and cooperation is a fundamental idea underlying most contemporary Western health care settings. By contrast, other human services, including social welfare, social work, residential facilities, substance abuse, and others, have historically included elements of paternalism: protecting clients from themselves by limiting their freedom or information available to them to improve their welfare (Reamer, 1983). In such settings, individuals may be seen as subjects or, at best, customers, rather than clients or active citizens. Studying the effect of client participation in non–health care human service settings is another direction for future research.

Finally, our article is confined to a “low tech, high touch” context, where client participation in treatment may be an important precondition for responsive services. At the same time, this is a unique context where clients’ capacity to “participate” may be limited due to health. The effect of client participation and, more broadly, citizen participation, may be considerably different in other fields, with a different level of service complexity or the presence of human clients immediately affected by these services. Thus, comparing the impact of clients’ input and its use across a broader range of public service areas may be helpful in understanding the impact of citizen participation on organizational services. Similar studies in education, juvenile services, job training, rehabilitative services, recreational services, family planning, and other areas could provide information on how the context of public programs affects the role that client participation can play in improving program performance.

Footnotes

Appendix A

Appendix B

Sensitivity Analysis Results Related to the Measures of Client Participation: The Impact of Client Participation on Nursing Home Performance Using Original Ordinal Categories of Client Participation Variables in the Survey.

	(1) Fixed effectDV: Deficiency		(2) Negative binomialDV: Deficiency		(3) Ordered logitDV: Star rating
	β/(SE)	β/(SE)	β/(SE)	β/(SE)	β/(SE)	β/(SE)
(Original) interaction with civic groups	−.014		−.004		.017
(Original) interaction with civic groups	(.04)		(.01)		(.08)
(Original) clients’ feedback considered		−.066^†		−.010		.158*
(Original) clients’ feedback considered		(.04)		(.01)		(.07)
Deficiency (2013)or star rating (2013)^a	.294**	.295**	.050**	.050**	.957**	.959**
Deficiency (2013)or star rating (2013)^a	(.04)	(.04)	(.01)	(.01)	(.09)	(.09)
Nonprofit	−.101*	−.100*	−.019*	−.018*	.282**	.286**
Nonprofit	(.05)	(.05)	(.01)	(.01)	(.09)	(.09)
Public	−.103*	−.103*	−.017^†	−.016^†	.214*	.219*
Public	(0.05)	(.05)	(.01)	(.01)	(.10)	(.10)
White manager	−.047	−.045	−.010	−.009	.079	.073
White manager	(0.04)	(.04)	(.01)	(.01)	(.08)	.08)
Female manager	−.015	−.009	−.003	−.002	−.053	−.063
Female manager	(0.04)	(.04)	(.01)	(.01)	(.08)	(.08)
Years as a nursing home administrator	−.039	−.040	−.006	−.006	.049	.053
Years as a nursing home administrator	(0.04)	(.04)	(.01)	(.01)	(.08)	(.08)
Total number of residents	.040	.039	.006	.006	−.275**	−.274**
Total number of residents	(0.05)	(.05)	(.01)	(.01)	(.09)	(.09)
Total nurse staffing hours	.047	.046	.007	.007	.101	.103
Total nurse staffing hours	(0.04)	(.04)	(.01)	(.01)	(.08)	(.08)
Medicaid residents (%)	−.015	−.011	−.002	−.001	−.081	−.084
Medicaid residents (%)	(0.04)	(.04)	(.01)	(.01)	(.09)	(.09)
Hospital affiliated	−.057	−.058	−.011	−.011	.015	.017
Hospital affiliated	(0.04)	(.04)	(.01)	(.01)	(.08)	(.08)
Ownership changed in 1 year	−.005	−.004	−.001	−.001	−.013	−.014
Ownership changed in 1 year	(0.04)	(.04)	(.01)	(.01)	(.07)	(.07)
Years since certified	.003	.005	.003	.004	−.106	−.114
Years since certified	(0.04)	(.04)	(.01)	(.01)	(.08)	(.08)
Population density	−.084^†	−.078^†	−.025**	−.024*	.180*	.168^†
Population density	(0.04)	(.04)	(.01)	(.01)	(.09)	(.09)
Elderly (%)	.013	.007	.001	.000	.052	.067
Elderly (%)	(0.04)	(.04)	(.01)	(.01)	(.09)	(.08)
Poverty (%)	.030	.027	.003	.002	−.031	−.024
Poverty (%)	(0.04)	(.04)	(.01)	(.01)	(.08)	(.08)
Market concentration	.035	.034	.005	.005	−.154^†	−.157^†
Market concentration	(0.05)	(.05)	(.01)	(.01)	(.09)	(.09)
R² (pseudo R² for (2) and (3) model)	.1180	.1222	.0207	.0212	.1184	.1208
N	617	617	617	617	617	617

Note. Constants not presented. Standardized beta reported here.

Deficiency (2013) was controlled in the fixed effects model and the negative binomial models, and star rating (2013) was included in ordered logit model.

†

p < .10. *p < .05. **p < .01 (two-tailed test).

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

ORCID iD

Ohbet Cheon

Author Biographies

Anna A. Amirkhanyan (amirkhan@american.edu) is an associate professor in the Department of Public Administration and Policy at the American University. She published one book and over twenty articles in the areas of organizational management, performance, public-private differences, privatization, and public participation.

Ohbet Cheon (ocheon@houstonmethodist.org) is a postdoctoral fellow at the Houston Methodist Research Institute and beginning in fall 2019 she will be an assistant professor at the Reh School of Business, Clarkson University. Her Research agenda focuses on public management, performance management, social disparities in health outcomes, and policy instruments in health care services.

Jourdan A. Davis (jd5530b@american.edu) is a doctoral student in the School of Public Affairs at American University. Her research interests include behavioral public administration, performance, citizen participation and engagement, social equity, and the long-term care context.

Kenneth J. Meier (kmeier@american.edu) is a distinguished scholar in Residence at American University. He is also a professor of Public Management at the Cardiff School of Business, Cardiff University, Wales and Professor of Bureaucracy and Democracy at Leiden University, the Netherlands. His research interests include public management, the role of bureaucracy in democratic systems, comparative public administration, and behavioral approaches to public administration.

Fei Wang (fw9435a@american.edu) is a doctoral student in the School of Public Affairs at the American University. Her research focuses on privatization, government contracting, and citizen participation. She is also interested in the topics of government regulation and cross-sector collaboration, particularly, in the context of health and human services.

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