«DiscoVeriNg HomelessNess Volume 13, Number 1 • 2011 U.S. Department of Housing and Urban Development | Office of Policy Development and Research ...»
“From Street Life to Housing: Consumer and Provider Perspectives on Service Delivery and Access to Housing,” by Tatjana Meschede of Brandeis University, is a qualitative study that demonstrates the achievements and failures of services attempting to reach those most likely to be left out of the homeless service delivery model—the chronically homeless street population. Her study investigates the bridges and barriers to housing for 174 chronically homeless street dwellers in urban Boston and examines whether the services provided by public shelters, healthcare professionals, detoxification centers, and substance-abuse programs actually help homeless individuals move off the street and into some kind of permanent housing situation. This study addresses important differences between providers’ and consumers’ perceptions and theories on homelessness, service needs of homeless street dwellers, and service provision. The author concludes that a Housing First model may be a better approach for these homeless individuals than the traditional continuum of care model that provides services but not housing. She emphasizes the importance of looking at homelessness as a housing problem and to begin by housing the homeless, then provide the supportive services they need to adjust to life off the streets.
Beginning with this issue, Cityscape will also present brief reactions to the Symposium articles from distinguished foreign scholars who have examined similar issues in their own countries.
America’s issues are not unique to these shores, and we may have much to learn from the policies of other nations. We are fortunate to begin this process with Julie Christian of the University of Birmingham and Suzanne Fitzpatrick of Heriot-Watt University in the United Kingdom.
Conclusion Most people in the metropolitan areas of the United States see the faces of homeless people often. Homelessness affects all of us, both directly and indirectly. Although any individual program may have controversies, federal funding to end homelessness is not controversial.
Both U.S. political parties favor public action to eliminate homelessness, but homelessness continues. We need to know why. We need to know more than we do. No one should be homeless. It is my hope that the Symposium in this issue of Cityscape will bring attention to and foster greater awareness of the growing issue of homelessness.
4 Discovering Homelessness
Guest Editor’s IntroductionReferences Leginski, Walter. 2007. Historical and Contextual Influences on the U.S. Response to Contemporary Homelessness. Toward Understanding Homelessness: The 2007 National Symposium on Homelessness Research. Washington, DC: U.S. Department of Health and Human Services and U.S. Department of Housing and Urban Development.
U.S. Department of Housing and Urban Development. 2010 ( June). The 2009 Annual Homeless Assessment Report to Congress. Washington, DC: U.S. Department of Housing and Urban Development. Available at http://www.hudhre.info/documents/5thHomelessAssessmentReport.pdf.
AbstractThis study explored how homeless-services providers are implementing homeless management information systems (HMIS) using an integrated theory base of innovation diffusion, sociotechnical systems, and organizational culture. Data were collected in 2 states from 24 homeless-services providers and 142 staff members. Cross-level relationships were analyzed using generalized hierarchical linear modeling. Results revealed striking disparities in HMIS use. In some organizations, many staff members accessed the system regularly, while in others, very few ever used the HMIS. The study found an association between organizational culture and HMIS use, which was moderated by gender. In organizations reporting higher levels of organizational proficiency, male staff members showed increased use of HMIS. Moreover, the homeless-services providers in this sample reported higher levels of organizational rigidity and resistance compared with a national normed sample of children’s mental health providers. The current study’s findings suggest that organizational context is critical to successful technology innovation diffusion. The study recommends that policymakers make efforts to alter both the organizational context and the technology to maximize the success of resources like HMIS.
Cityscape Cityscape: A Journal of Policy Development and Research • Volume 13, Number 1 • 2011 U.S. Department of Housing and Urban Development • Office of Policy Development and Research Cronley Introduction Technology plays an increasingly critical and diverse role in the human services. Service providers keep electronic records about clients’ health care (Poon et al., 2004); administer cognitive behavioral therapy over the Internet (Andersson, 2009); coordinate services electronically (Fitch, 2009); and engage in online community organizing and political activism (McNutt and Menon, 2008). Specific public policy efforts have encouraged innovation in the homeless-services sector. In 1999, the U.S. Department of Housing and Urban Development (HUD) introduced homeless management information systems (HMIS) to service providers. HMIS are designed to facilitate the migration from paper-based to electronic work systems with a two-fold goal of improving (1) data collection and (2) the effectiveness of homeless programs (HUD, 2007). As of 2008, 222 homeless-services provider communities reported that they were collecting client-level data in an HMIS (HUD, 2009). This study explores the extent to which these providers are implementing this technology and what factors are related to the process.
The nature of homelessness makes it difficult to provide consistent services and track outcomes, because many members of the homeless population live itinerantly, suffer from concurrent disabilities, have limited if any social and familial connections, and frequently eschew traditional social services (Wright, Rubin, and Devine, 1998). As early as 1986, researchers were developing a tracking tool for monitoring homeless services (Nichols, Wright, and Murphy, 1986). In implementing the HMIS program, HUD expected that systematic data collection methods would improve the accuracy of prevalence counts and knowledge of the population’s characteristics, which would, in turn, enhance the efficiency of resource allocation and service effectiveness.
Previous studies of innovation diffusion have suggested that the process of adopting and implementing new technologies is as much a social process as it is a technical process. Indeed, the culture of organizations, or the degree to which they encourage innovation and invite change, is related to successful innovation implementation (Carrilio, Packard, and Clapp, 2003; Glisson and James, 2002). Despite the substantial HUD funding and training efforts devoted to HMIS implementation, the process has been challenging and not always successful (Cronley and Patterson, 2010; Gutierrez and Friedman, 2005). Homeless-services providers are often small organizations that rely heavily on volunteers and former clients for staffing, a factor that may discourage the rapid uptake of new technologies (Corder, 2003). Case managers often provide services outdoors and off site, where access to digital technology is difficult.
This study applied theories of innovation diffusion to a model of organizational culture in an exploratory evaluation of the degree to which service providers are using HMIS. It is based on a pilot study of organizational culture and HMIS implementation (Cronley and Patterson, 2010).
The study suggests that technology implementation within homeless services is an erratic and longterm process. It is necessary that HUD focus continued funding on coordinating implementation efforts across multiple systems—human, technological, and organizational.
Homeless Management Information Systems The movement toward computer-based operations derives from HUD’s efforts to improve data collection and accountability among homeless-services providers. In 1993, the federal government passed the Government Performance and Results Act,1 which requires federal agencies to set performance goals and measure outcomes. Partly in response to this requirement, HUD began requiring homelessservices providers to implement HMIS in 1999 and, in 2001, began providing grants to service providers for purchasing the software, training staff members, and hiring people to manage the systems (HUD, 2007). All federally funded homeless-services providers, however, must implement HMIS to maintain additional HUD funding. Most organizations began implementing technology innovations less than 5 years ago, and HUD continues to push for expanded implementation and improved data quality.
HMIS typically link multiple service providers through secure, central homeless information databases, using encrypted Internet communication technology. It is common for organizations using HMIS to store client records electronically on the database and coordinate client care through real-time, shared access to the database. HMIS also integrate information and retrieval systems into databases, thereby facilitating resource referrals. Successful transformation from a paper-based to a computer-based system requires that organizations sustain HMIS utilization after they have installed the software. This utilization means that employees must consistently enter new client information into the system and recording services delivered. Challenges to sustained use include persuading service providers that client data collection procedures are necessary and training them to implement the technology as designed. For an organization to overcome these challenges, theory and research suggest the organizational social context must support technology (Pasmore et al., 1982; Trist and Bamforth, 1951). How members of the leadership team communicate the value of innovation and whether staff members have the flexibility in their work systems to adapt to new systems are critical to successful technology implementation.
Technology Use in Human Services A general understanding exists that using new technologies will improve human services. Benefits include (1) increasing the speed of service provision (Schoech, 1999) and (2) improving the quality, volume, and flow of information among agencies (Burt and Taylor, 2003; Fitch, 2009; McCoy and Vila, 2002) and between agencies and clients (Schoech, 1999). Much of the evidence supporting this position is qualitative, however, and relies on case studies (for example, Fitch, 2009) and self-reports from small numbers of participants (for example, Gomez et al., 2010). Although these findings are valuable, they fail to provide evidence that the benefits of technologies in specific settings can be generalized across social service sectors. Besides the lack of empirical evidence about the benefits of technology use in the human services, a lack of understanding exists about the extent to which organizations use these new technologies and why certain organizations choose to implement them and others do not. Substantial evidence suggests that many organizations choose not to or fail in their efforts to implement new technologies (Carillio, 2007; 2005; 2003; Fitch, 2005;
Herie and Martin, 2002; McCoy and Vila, 2002).
A study of technology trends in the U.S. healthcare industry showed that only 10 to 15 percent of U.S. hospitals use computerized physician order entry forms, although their use has been shown to reduce the incidence of serious medication errors by 55 percent (Poon et al., 2004). A qualitative study of substance-abuse services showed that many social workers who were interviewed lacked technical proficiency to use a computerized referral system (Drum, McCoy, and Lemon, 2004).
Glisson and Schoenwald (2005) contend that when the technology is disseminated, the adopting organizations change the technology to such a degree that they render it useless. The problem is referred to as technology transfer—the space between the clinical development of the innovation and its practical application in the community (Becker et al., 2000; McGovern et al., 2003; Miller et al., 2006).
One common cause of unsuccessful technology implementation is an overemphasis on technical factors rather than on organizational and personal factors (Cybluski, Zantinge, and Abbott-McNeil, 2006; Dhillon and Backhouse, 1996; Greenhalgh et al., 2004; Herie and Martin, 2002; Keddie and Jones, 2005; Lorenzi and Riley, 2003; Lorenzi and Riley, 2000). Dhillon and Backhouse describe technology utilization as a continual interplay among three systems: the technical process, the formal structure, and the informal structure. They argue that technical processes and formal structure are embedded in the informal structure, where meaning is created and values are stored. Failure to intervene at the informal level and to maintain integrity among the three systems impedes technology utilization. Glisson (1992) describes this misplaced emphasis as the technical imperative by which project planners view utilization as a solely technical process in which the success or failure rests exclusively on the technical components (for example, hardware and software) of the innovation.
Organizational culture is a factor that may influence technology implementation. Organizational culture is defined as the values, beliefs, and expectations that guide employee behavior (Schein, 1992); it encompasses decisionmaking systems, leadership, and work processes. For example, lack of leadership support for innovation has been shown to hinder technology implementation (Corder, 2003; Poon et al., 2004) because of poor project planning and management (2003).
Failure to provide logistical support (Mutschler and Hoefer, 1990) and organizational resistance to change (Drum et al., 2003; Lorenzi and Riley, 2000, 2003) are also associated with unsuccessful technology implementation. This culture of resistance may stem from a belief that technology interferes with client interactions (Carillio, 2005; Semke and Nurius, 1991) or from the opinion among human services workers that their work activities are not as easily automated and, thus, are less amenable to technology utilization (O’Looney, 2005).