Characteristics of acute care hospitals with diversity plans and translation services.
Subject: Health care industry (Management)
Hospitals (United States)
Hospitals (Management)
Authors: Moseley, Charles B.
Shen, Jay J.
Ginn, Gregory O.
Pub Date: 01/01/2011
Publication: Name: Journal of Healthcare Management Publisher: American College of Healthcare Executives Audience: Trade Format: Magazine/Journal Subject: Business; Health care industry Copyright: COPYRIGHT 2011 American College of Healthcare Executives ISSN: 1096-9012
Issue: Date: Jan-Feb, 2011 Source Volume: 56 Source Issue: 1
Topic: Event Code: 200 Management dynamics Computer Subject: Health care industry; Company business management
Product: Product Code: 8060000 Hospitals NAICS Code: 622 Hospitals SIC Code: 8062 General medical & surgical hospitals; 8063 Psychiatric hospitals; 8069 Specialty hospitals exc. psychiatric
Geographic: Geographic Scope: United States Geographic Code: 1USA United States
Accession Number: 271594402
Full Text: EXECUTIVE SUMMARY

Hospitals provide diversity activities for a number of reasons. The authors examined community demand, resource availability, managed care, institutional pressure, and external orientation related variables that were associated with acute care hospital diversity plans and translation services. The authors used multiple logistic regression to analyze the data for 478 hospitals in the 2006 National Inpatient Sample (NIS) dataset that had available data on the racial and ethnic status of their discharges. We also used 2004 and 2006 American Hospital Association (AHA) data to measure the two dependent diversity variables and the other independent variables. We found that resource, managed care, and external orientation variables were associated with having a diversity plan and that resource, managed care, institutional, and external orientation variables were associated with providing translation services. The authors concluded that more evidence for diversity's impact, additional resources, and more institutional pressure may be needed to motivate more hospitals to provide diversity planning and translation services.

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Recently, a concerted effort has been made to increase the number of hospital diversity initiatives in acute care hospitals. Diversity in healthcare organizations refers to the combination of certain dimensions of patient and employee differences (e.g., biology, gender, age, culture, education) that interact and can result in dissimilar needs and preferences that the organization needs to address (Celik et al. 2008). Failure to address these diverse needs and preferences can adversely affect patients' health (Johnstone and Kanitsaki 2006; Divi et al. 2007; Cohen et al. 2005).

In 1999, 28 percent of US residents were members of a racial or ethnic minority group, and the US Census Bureau projects that that number will increase to 40 percent by 2030. Demographic changes are increasing the diversity of patient and workforce populations (Dansky et al. 2003).

Svehla (1994) describes diversity management as a strategically driven process focused on building skills and creating policies that bring out the best in employees and assessing marketing issues brought about by changes in the workforce and customer demographics. Hospital diversity activities can include human resources, planning, evaluation, and service delivery activities (Weech-Maldonado et al. 2002). In a survey of Pennsylvania hospital management diversity practices, Dreachslin, Weech-Maldonado, and Dansky (2004) found that the three most common diversity-related practices were strategic planning, evaluation of patient and community satisfaction, and the delivery of diversity services, particularly language translation services.

Given the current state of the research, it is unclear what factors are influencing hospitals to undertake diversity initiatives. Are hospitals that serve more ethnically or racially diverse patient populations more likely to have programs and activities? Or do other factors, such as resource availability, institutional forces, managed care, and external orientation, affect hospital diversity initiatives?

Some analysts in this area have concluded that not all healthcare organizations exhibit strategically driven diversity management (Dansky et al. 2003). While some organizations proactively initiate diversity management activities, others only make those changes necessary to comply with affirmative action guidelines. Identifying the forces that influence hospitals to develop diversity initiatives will aid in the design of policies and incentives that will encourage hospitals to develop more proactive diversity programs.

This study examines whether factors such as community demand, resource availability, managed care, institutional forces, and external orientation are associated with hospital diversity plans and translation services. This appears to be first study to examine the role of all these factors in a national sample of hospitals. Several state- and regional-level studies have investigated the environmental and organization factors that influence hospital diversity efforts, and they have reported conflicting results (Dansky et al. 2003; Weech-Maldonado et al. 2002; Whitman and Davis 2008; Wallace, Ermer, and Motshabi 1996). This study will help identify policies and incentives that may encourage more hospitals to develop diversity initiatives.

CONCEPTUAL FRAMEWORK

Hospitals should develop diversity programs to respond to community demand for better services for increasingly diverse ethnic/racial patient populations, especially those patients with limited English language proficiency (Brach and Fraser 2002). However, the two studies of the diversity efforts among Pennsylvania hospitals found that hospitals located in counties with higher percentages of minority patients were no more likely to pursue diversity efforts than hospitals in counties with lower percentages of minority patients (Dansky et al. 2003; Weech-Maldonado et al. 2002). These counterintuitive results may be due to these studies using the counties where hospitals were located as the geographic units to measure the percentage of minorities. Hospitals located in counties with higher percentages of minority populations do not necessarily serve higher percentages of minority patients.

Hospitals with more available resources are more likely to provide diversity programs and activities. In general, larger hospitals have more resources to allocate to diversity than smaller hospitals. However, studies of Pennsylvania, Alabama, and mid-Atlantic hospital diversity efforts found that hospital size had no effect on diversity activities (Whitman and Davis 2008; Dansky et al. 2003; Weech-Maldonado et al. 2002; Wallace, Ermer, and Motshabi 1996). Despite these results, the authors decided to use hospital size as a measure of resource availability, because it is a widely accepted indicator of hospital resource capacity (Jensen and Morrisey 1986).

Hospitals located in urban and suburban areas may have more resources to allocate to diversity than hospitals located in rural areas. The research on this relationship is mixed, however. A mid-Atlantic state hospital diversity study found that urban hospitals were more likely to have programs than rural hospitals (Wallace, Ermer, and Motshabi 1996). Two Pennsylvania hospital studies found no difference between urban and rural hospitals (Dansky et al. 2003; Weech-Maldonado et al. 2002). However, an Alabama hospital diversity study found that rural hospitals were more likely to include diversity as part of their mission statements than nonrural hospitals (Whitman and Davis 2008).

Another resource factor that could affect diversity is the level of competition in the local hospital market. Hospitals in more competitive markets may have fewer resources available to devote to diversity activities (Brach and Fraser 2002). Also, hospitals that are more dependent on Medicaid may have fewer resources available to devote to diversity due to constrained patient revenues. Interestingly, the authors could not find published empirical research that examines the association between these resource factors and diversity activities.

Hospitals could be influenced by their managed care payment sources to provide diversity activities. Brach and Fraser (2002) reported that some managed care payers require hospitals to report HEDIS indicators that measure linguistically appropriate patient care. This may especially be the case for hospitals with Medicaid capitation arrangements, because these hospitals serve larger non-English speaking populations (Brach and Fraser 2002). However, in the only empirical study of the association between type of payment source and diversity activities, Weech-Maldonado and colleagues (2002) did not find a managed care penetration effect on diversity activities among Pennsylvania hospitals. Managed care penetration may not be the best measure of a managed care impact on diversity behavior, because not all managed care organizations encourage hospitals to meet the needs of their diverse patient populations.

Institutional influences are reflected by differences in ownership, teaching status, and regulatory environment. Government-owned hospitals are more strongly compelled to develop diversity programs, because they are expected to serve the entire population, regardless of ethnicity and race (Brach and Fraser 2002). Not-for-profit hospitals are also motivated by legitimacy concerns, because they are supposed to serve their communities by providing community benefit activities (Brach and Fraser 2002). The Whitman and Davis (2008) study of the diversity activities of Alabama hospitals reported that public hospitals were more likely to conduct diversity programs than private hospitals. The Wallace, Ermer, and Motshabi ( 1996) study of diversity programs among mid-Atlantic state hospitals also found that government hospitals were more likely than private hospitals to have programs.

In contrast, the Dansky and colleagues (2003) and Weech-Maldonado and colleagues (2002) Pennsylvania hospital diversity studies found no association between type of hospital ownership and diversity efforts. These contrary results could be due to the skewed distribution of ownership type among the sampled hospitals in these studies--in both studies, 92 percent of the sampled hospitals were not-for-profit.

In a national study of hospital diversity data practices, Regenstein and Sickler (2006) found that public hospitals were less likely to utilize data on patient race, ethnicity, and language than private hospitals, and that investor-owned hospitals were more likely than public and not-for-profit hospitals to collect data on their patients' language.

Teaching hospitals are more likely to provide diversity programs. The Association of American Medical Colleges (AAMC) and its Council of Teaching Hospitals and Health Systems (COTH) are committed to promoting diversity in its member hospitals. The Wallace, Ermer, and Motshabi (1996) mid-Atlantic hospital diversity study found that teaching hospitals were more likely than non-teaching hospitals to have diversity programs.

Regenstein and Sickler (2006) also found that teaching hospitals were more likely to collect data on patient race and ethnicity than non-teaching hospitals, and they were more likely to use this data to assess and compare quality of care than non-teaching hospitals.

Hospitals with external strategic orientations are more likely to be involved in diversity activities. Dansky and colleagues (2003) found that Pennsylvania hospitals that were more externally oriented were more likely to have a diversity focus. One indicator of an external orientation is network participation. Research on network participation and hospital diversity efforts is mixed, however. The Dansky and colleagues (2003) and Weech-Maldonado and colleagues (2002) Pennsylvania hospital diversity studies found no network effect, while the Whitman and Davis (2008) Alabama hospital diversity study reported a network effect. These divergent results may be due to differences in the measurement of "network participation." Dansky and colleagues measured network participation as "health system" membership, while Whitman and Davis measured it as "multi-hospital system" membership.

Based on our review of the literature, the authors expect to find the following relationships between community demand, resource availability, managed care, institutional, and external orientation factors and hospital diversity activities:

* Hospitals with greater community demand for diversity activities {i.e., larger racial/ethnic minority patient populations) are more likely to have diversity activities.

* Hospitals with greater resource availability (i.e., larger size, urban location, higher occupancy rates, less dependency on Medicaid reimbursement, locations in less competitive markets) are more likely to provide diversity activities.

* Hospitals that are more affected by managed care (i.e., have capitation arrangements) are more likely to offer diversity activities.

* Hospitals with greater institutional pressures (i.e., government and not-for-profit ownership, teaching status) are more likely to have diversity activities.

* Hospitals that are more externally oriented (i.e., network participation, more reported community health orientation activities, self-assess against Baldrige criteria, greater hospital-physician integration) are more likely to provide diversity activities.

METHODS

This was a cross-sectional study with the individual community hospital as the unit of analysis. The sample of hospitals consisted of all of the 2006 NIS hospitals that had data on the minority status of their discharges. The 2006 NIS contained all the hospital discharges from 1,000 hospitals that were selected based on a stratified randomization process. We selected the 800 NIS hospitals that had data on the minority status of their discharges. These hospitals were located in 29 states (Arkansas, Arizona, California, Colorado, Connecticut, Florida, Hawaii, Iowa, Indiana, Kansas, Maryland, Massachusetts, Michigan, Missouri, North Carolina, Nebraska, New Hampshire, New Jersey, New York, Oklahoma, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Vermont, and Wisconsin). To collect the data on the other hospital characteristics, we merged this NIS data with the 2004 and 2006 American Hospital Association (AHA) Annual Survey data for those hospitals. After merging this data, we lost 322 hospitals, because these hospitals either did not have AHA identification numbers, had race information as missing values, or were not otherwise able to be matched. Thus, our final sample consisted of 478 hospitals.

Two dichotomous dependent variables were selected from the 2006 AHA Annual Survey data to represent hospital diversity initiatives. One variable was whether a hospital had a diversity plan. This variable was based on the member hospital's response to the survey question, "Does your hospital or health system currently have or plan to develop, execute or evaluate a diversity strategy or plan?"

To better determine the nature of these plans, we examined whether hospitals with plans had also reported collecting data on the race/ethnicity of their patients and on their patients' primary language. We found that 95 percent of the hospitals with plans had also collected data on their patients' race/ethnicity, and that 94 percent of these hospitals had also collected data on their patients' primary language. These high correlations lead us to believe that our diversity plan variable was a measure of our sampled hospitals' commitments to serving their minority and/or non-English speaking patient populations, rather than merely an effort to comply with equal employment opportunity (EEO) and other legal requirements.

The other diversity dependent variable was whether a hospital provided translation services. This variable was based on member hospitals' response to the question of whether they had provided linguistic/translation services during the last three days of the AHA Annual Survey reporting period. The survey defined linguistic/translation services as "services provided by the hospital designed to make healthcare more accessible to non-English speaking patients and their physicians."

Independent variables were grouped by five factors: (1) community demand, (2) resource availability, (3) managed care influence, (4) institutional pressures, and (5) external orientation. The community demand for diversity planning and translation services was measured by the percentages of African American, Hispanic/Latino American, and Asian American discharges from each sampled hospital. Resource availability was indicated by five variables: (1) hospital size as measured by number of beds, (2) urban versus rural location, (3) occupancy rate, (4) level of dependence on Medicaid inpatient revenues, and (5) location in a competitive market (Santerre and Neun 2007). Managed care influence was measured by whether hospitals had capitation arrangements. We selected this variable because managed care capitation arrangements provide an incentive for hospitals to better manage the health status of their patients, including their minority patients. Institutional pressures were indicated by not-for-profit or local government ownership type and hospital teaching status. The four external orientation variables were: (1) whether the hospital was a participant in a network, (2) the number of reported community health orientation activities, (3) whether hospitals had self-assessed against Baldrige criteria, and (4) the degree of hospital-physician integration. External orientation was measured using 2004 AHA data to allow for enough time for these activities to have had an impact on diversity. The level of measurement, data sources, variable definitions, and coding for all of the independent variables are shown in Exhibit 1.

We used multiple logistic regression models to examine the association between the independent variables that represented the five factors and each of the two dependent variables. To make meaningful intervals in the variables for logistic analysis, we recoded the continuous independent variables. We anticipated that community demand would be associated with the two dependent variables, so we forced all three demand variables into our multivariable models. The other independent variables were entered into the models based on the step-wise regression procedure. We set the threshold for entering these variables into the models at a significance level of less than 0.25, and the threshold for keeping them in the models at a significance level of less than 0.10.

RESULTS

Among the 478 hospitals, 76.8 percent had diversity plans and 54.6 percent provided translation services. Exhibit 2 presents the unadjusted, descriptive statistics for the independent variables for the hospitals with and without plans and with and without translation services. Compared with hospitals without diversity plans, hospitals with plans were more likely to: (1) have higher percentages of Hispanic/Latino discharges, (2) have capitation arrangements, (3) be located in competitive markets, (4) be teaching hospitals, (5) self-assess against Baldrige criteria, (6) report a higher number of community health orientation activities, (7) have greater physician integration, and (8) participate in networks. Compared with hospitals without translation services, hospitals with services were more likely to (1) have higher percentages of Asian discharges, (2) be located in an urban area, (3) have more beds, (4) have capitation arrangements, (5) be teaching hospitals, (6) self-assess against Baldrige criteria, (7) report a higher number of community health orientation activities, (8) have greater physician integration, and (9) participate in networks.

The multiple logistic regression results for the association between the independent variables and hospitals with diversity plans are shown in Exhibit 3. None of the community-demand variables were associated with having a plan. For the resource availability variables, hospitals in rural areas were less likely to have plans (OR 0.38 [CI 0.17, 0.82]), and for every 10 percent increase in Medicaid inpatient revenues, there was a 29 percent reduction in the likelihood of having a plan (OR 0.71 [CI 0.54, 0.95]). Hospitals with capitation arrangements were more likely to have a plan (OR 2.88 [CI 1.00, 8.35]). Among the external orientation variables, hospitals affiliated with networks were more likely to have a plan (OR 3.50 [CI 1.54, 7.96]), and an increase of one more reported community health orientation activity was associated with an 22 percent increase in the likelihood of having a plan (OR 1.22 [CI 1.12, 1.33]).

The associations between the independent variables and hospitals with translation services are shown in Exhibit 4. None of the community demand variables were associated with translation services. Among the resource variables, hospitals in rural areas were less likely to offer services (OR 0.45 [CI 0.25, 0.81]), and hospitals with capitation arrangements were more likely to provide services (OR 2.43 [CI 1.25, 4.70]). For the institutional variables, investor-owned hospitals were less likely to provide services (OR 0.46 [CI 0.26, 0.84]), and teaching hospitals were more likely to offer services (OR 2.07 [CI 1.16, 3.69]). Among the external orientation variables, an increase in one reported community health activity was associated with a 13 percent increase in the likelihood of offering services (OR 1.13 [CI 1.05, 1.21]).

DISCUSSION

The results indicate that the resource availability, managed care, and external orientation factors had some effect on hospital diversity plans. As expected, hospitals with more resources (i.e., urban location, less dependence on Medicaid reimbursement) were more likely to have diversity plans. The urban location result is consistent with the Wallace, Ermer, and Motshabi (1996) finding that urban, mid-Atlantic state hospitals were more likely to have diversity programs.

Hospitals with capitation arrangements and hospitals with external orientations (i.e., network participation, more reported community health orientation activities) were also more likely to have diversity plans. The external orientation finding is consistent with the Dansky and colleagues (2003) study that found Pennsylvania hospitals that were more externally oriented were more likely to have a diversity focus.

The findings indicate that the resource availability, managed care, institutional, and external orientation factors all had some effect on translation services. As expected, hospitals with more available resources (i.e., urban hospitals) and hospitals with capitation arrangements were more likely to provide services.

Institutional pressures affected services in the expected direction in that teaching hospitals were more likely to provide translation services, while investor-owned hospitals were less likely to have had services. Teaching hospitals may feel more institutional pressure to provide translation services than they do to have diversity plans, because they typically serve more patients who speak languages other than English. The teaching hospital result is consistent with the Regenstein and Sickler (2006) and Wallace, Ermer, and Motshabi (1996) studies that found that teaching hospitals were more likely to be involved in diversity behavior. Hospitals with external orientations (i.e., network participation, more reported community health orientation activities) were also more likely to provide services.

Contrary to expectations, hospitals with larger percentages of minority discharges were not more likely to have diversity plans or translation services. This is particularly puzzling for hospitals with larger populations of Hispanic and Asian discharges, because one would expect to find translation services in hospitals with relatively larger patient populations who may not speak English.

Hospitals with larger non-English speaking patient populations may not be able to afford to provide translation services because these patients are more likely to be uninsured or insured by Medicaid. When we entered only the minority status variables into the translation service regression model, we found that hospitals with more Asian American discharges were more likely to offer translation services. This finding provides some indirect support for the insurance status argument, because Asian American patients are more likely to be insured than other non-English speaking patients.

Our study methodology has several potential limitations. First, our measurement of whether hospitals were involved in diversity activities was limited to whether hospitals reported developing, executing, or evaluating a diversity plan and whether they provided translation services. Hospitals could have been involved in other types of diversity activities (e.g., recruitment of minority staff, training staff in cultural competency) that we were not able to measure due to data unavailability.

Furthermore, we had no way of determining the exact nature and scope of the diversity plans and translation services. However, as discussed, the authors believe that the diversity plan variable represented a hospital's commitment to serve their minority or non-English speaking patient populations, as opposed to just a pro forma effort to meet EEO or other legal requirements.

Another potential limitation is that our results may not generalize to the whole country, because we had to eliminate 40 percent of our NIS hospitals with minority status data that did not have AHA ID numbers or were missing minority status data from our sample.

CONCLUSIONS

Our results indicate that acute care hospitals in this country are developing diversity plans and providing translation services for reasons other than serving their minority patient populations. Factors such as resource availability, managed care influence, institutional pressures, and external orientation seem to influence whether these hospitals had diversity plans and provide translation services.

Why are hospitals with larger percentages of racial/ethnic minority discharges not more likely to develop diversity plans and offer translation services? One reason may be that these hospitals have not bought into the "business argument" for diversity management (Brach and Fraser 2002). What may be needed to help convince these executives is more direct evidence that diversity management can affect a hospital's bottom line by increasing market share and improving quality of care.

A second potential reason is that these hospitals may need additional resources, especially to provide translation services. This may be particularly true for rural hospitals and hospitals that are more dependent on Medicaid reimbursement. Rural hospitals may also be less likely to provide translation services due to a lack of trained interpreters in rural areas.

One potential solution to the resource problem would be for Medicare/Medicaid programs to reimburse rural hospitals for developing diversity plans and providing translation services. Medicare and state Medicaid programs could make the provision of these activities a requirement for rural hospitals to become critical access hospitals. Medicaid managed care plans could include funding for diversity planning and translation services in their contracts with hospitals with large minority patient populations.

A final potential reason is that there is not sufficient institutional pressure from government agencies and private accrediting bodies to develop diversity plans and provide translation services. The federal government may need to better enforce the culturally and linguistically appropriate services (CLAS) standards that mandate that hospitals that receive federal monies provide language access services. The Joint Commission (2008) may need to strengthen their requirement that accredited hospitals provide linguistically appropriate services "as necessary."

Wilson-Stronks and Galvez (2007) believe that The Joint Commission should be more proactive. They have recommended that The Joint Commission establish a written position on the provision of culturally and linguistically appropriate care that specifically addresses (1) the use of family members to provide interpretations, (2) the types of training and competencies expected of individuals who are used to interpret, (3) expectations for ongoing education of staff when the hospital serves a highly diverse patient population, and (4) the essential documents that require quality controlled translation into languages other than English.

In summary, we found that resource, managed care, institutional, and external orientation factors were associated with diversity planning and translation services in acute care hospitals. Our results indicate that more evidence for the business case for diversity, additional diversity resources, and increased institutional and managed care pressures may be needed to encourage more hospital executives to engage in diversity planning and provide translation services.

REFERENCES

Brach, C., and I. Fraser. 2002. "Reducing Disparities Through Culturally Competent Health Care: An Analysis of the Business Case." Quality Management in Health Care 10 (4): 15-28.

Celik, H., T. A. Abma, G. A. Widdershoven, F. C. 13. van Wijmen, and I. Klinge. 2008. "Implementation of Diversity in Healthcare Practices: Barriers and Opportunities." Patient Education and Counseling 71: 65-71.

Cohen, H. L., F. Rivara, E. K. Marcuse, H. McPhillips, and R. Davis. 2005. "Are Language Barriers Associated with Serious Medical Events in Hospitalized Pediatric Patients?" Pediatrics 116 (3): 575-79.

Dansky, K., H. R. Weech-Maldonado, G. De Souza, and J. L. Dreachslin. 2003. "Organizational Strategy and Diversity Management: Diversity-Sensitive Orientation as a Moderating Influence." Health Care Management Review 28(3): 243-53.

Divi, C., R. G. Koss, S. P. Schmaltz, and J. M. Loeb. 2007. "Language Proficiency and Adverse Events in US Hospitals: A Pilot Study." International Journal for Quality in Health Care 19 (2): 60-67.

Dreachslin, J. L., R. Weech-Maldonado, and R. H. Dansky. 2004. "Racial and Ethnic Diversity and Organizational Behavior:

A Focused Research Agenda for Health Services Management." Social Science and Medicine 59: 961-71.

Jensen, G. A., and M. A. Moprisey. 1986. "The Role of the Physician in Hospital Production." Review of Economics and Statistics 68: 432-42.

Johnstone, M. l., and O. Kanitsaki. 2006. "Culture, Language, and Patient Safety: Making the Link." International Journal for Quality in Health Care 18 (5): 383-88.

The Joint Commission. 2008. "Promoting Effective Communication: Language Access Services in Health Care." Joint Commission Perspectives 28 (2): 8-11.

Regenstein, M., and D. Sickler. 2006. "Race, Ethnicity, and Language of Patients: Hospital Practices Regarding Collection of Information to Address Disparities in Health Care." Washington: National Public Health and Hospital Institute.

Santerre, R. E., and S. P. Neun. 2007. Health Economics: Theories, Insights, and Industry Studies, 4th Edition. Mason, OH: Thomson South Western.

Svehla, T. 1994. "Diversity Management: Key to Future Success." Frontiers of Health Services Management 11 (2): 3-33.

Wallace, P. E., C. M. Ermer, and D. N. Motshabi. 1996. "Managing Diversity: A Senior Management Perspective." Hospital and Health Services Administration 41 (1): 91-104.

Weech-Maldonado, R., J. L. Dreachslin, K. H. Dansky, G. De Souza, and M. Gatto. 2002. "Racial/Ethnic Diversity Management and Cultural Competency: The Case of Pennsylvania Hospitals." Journal of Healthcare Management 47 (2): 111-26.

Whitman, M. V., and I. A. Davis. 2008. "Cultural and Linguistic Competence in Healthcare: The Case of Alabama General Hospitals." Journal of Healthcare Management 53 (1): 26-40.

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PRACTITIONER APPLICATION

John W. Bluford, president/CEO, Truman Medical Centers, Kansas City, Missouri

This article stirred my interest, as it is most timely in the context of healthcare reform, access, equity, patient-centeredness, and quality outcomes. As the article points out, there is clearly more that needs to be done to encourage hospitals to serve their minority populations well.

My orientation on this subject stems from more than 30 years of administrative practitioner experience in two distinguished academic medical centers in Minneapolis, Minnesota, and Kansas City, Missouri--both with a strong diversity orientation and robust interpreter service.

In those hospitals, our decision to serve the diverse population was prompted by our focus on patient-centeredness. We cater on a personal level to meet the specific needs of any patient cohort. For example, we adjusted our regulations regarding burning items in patient rooms out of respect for the religious practices of some of our Native American patients. And we developed an underwater birthing program to accommodate the customs of some patients with Southeast Asian heritage.

While I agree with the article's conclusion that more resources and institutional pressure are needed to encourage hospital diversity planning, I have some additional thoughts on this study. One is about the study's premise that hospitals located in competitive markets would be less likely to divert resources for diversity activities. I would say, for those institutions that intend to be successfully competitive, a more diverse, patient-centered orientation would be to their advantage. I also feel that hospital-physician integration is an internal orientation, not an external one; a great number of academic medical centers and safety net institutions are theoretically integrated by employment status of the physician faculty staff.

The authors did cover several possible factors that motivate the development of hospital diversity plans. Some important additional areas for future studies could include elements of quality, patient service, patient-centeredness, institutional reputation, and employee demographics. I would expect and hope that the studied hospitals with high-quality reputations and upper percentile HCAHP customer satisfaction scores would be more apt to offer diversity and interpreter services.

Diversity and translator services should not be programs, but a way of doing business. Hospital staffs and their boards should reflect the patient populations they

serve, with patient-centeredness always of utmost concern. These variables, in my view, trump all others and conform to the mission of most American hospitals in fostering a healthy community.

As we say at Truman Medical Centers, a diverse culture that is sensitive to all needs, regardless of race, ethnicity, religion, economic status, or gender is "Better. For Everyone!"

Charles B. Moseley, PhD, associate professor and chair, Department of Health Care Administration and Policy, School of Community Health Sciences, University of Nevada Las Vegas; Jay J. Shen, PhD, associate professor, Department of Health Care Administration and Policy, School of Community Health Sciences, University of Nevada Las Vegas; and Gregory O. Ginn, PhD, associate professor, School of Community Health Sciences, Department of Health Care Administration and Policy, University of Nevada Las Vegas
EXHIBIT 1
Independent Variable Level of Measurement, Data Sources,
Definitions, and Coding

                                     Level of       Data
Independent Variables               Measurement   Sources

Community demand:

  % African American (AA)           Hospital      2006 SID
  discharges

  % Hispanic/Latino (HL)            Hospital      2006 SID
  discharges

  % Asian American/ Pacific         Hospital      2006 SID
  Islander (AP) discharges

Resource availability:

  Location                          Hospital      2006 SID

  Bed size                          Hospital      2006 AHA

  Occupancy rate                    Hospital      2006 AHA

  Medicaid reimbursement            Hospital      2006 AHA

  Competitive market                County        2006 AHA

Managed care influence:

  Capitation arrangement            Hospital      2006 AHA

Institutional pressures:

  Ownership type:

    Not-for-profit                  Hospital      2006 AHA

    Investor owned                  Hospital      2006 AHA

  Teaching hospital status          Hospital      2006 SID

External orientation:

  Reported community health         Hospital      2004 AHA
  orientation activities

  Self-assessment on Baldrige       Hospital      2004 AHA
  criteria

  Degree of physician integration   Hospital      2004 AHA

  Network participation             Hospital      2004 AHA

Independent Variables                         Definitions

Community demand:

  % African American (AA)           # AA discharges / # total
  discharges                        discharges

  % Hispanic/Latino (HL)            # HL discharges / # total
  discharges                        discharges

  % Asian American/ Pacific         # AP discharges / # total
  Islander (AP) discharges          discharges

Resource availability:

  Location                          Located in rural area

  Bed size                          # staffed beds

  Occupancy rate                    # inpatient days /(# staffed
                                    beds * 365)

  Medicaid reimbursement            Medicaid revenue / total revenue

  Competitive market                HHI index > 1800

Managed care influence:

  Capitation arrangement            Had a capitation arrangement

Institutional pressures:

  Ownership type:

    Not-for-profit

    Investor owned

  Teaching hospital status

External orientation:

  Reported community health         Long-term plan, committed
  orientation activities            resources, joint community
                                    health assessment, use of health
                                    service indicators, joint
                                    capacity assessment,
                                    identification of unmet needs,
                                    joint collection and tracking of
                                    health information,
                                    dissemination of quality and
                                    cost reports

  Self-assessment on Baldrige       Self-assessed against Baldrige
  criteria                          criteria

  Degree of physician integration   Independent practice
                                    association, integrated salary
                                    model hospital, equity model
                                    hospital group practice without
                                    walls, open physician hospital
                                    organization, closed physician
                                    hospital organization,
                                    management service organization,
                                    or foundation hospital

  Network participation             Participated in a network

Independent Variables                  Coding

Community demand:

  % African American (AA)
  discharges

  % Hispanic/Latino (HL)
  discharges

  % Asian American/ Pacific
  Islander (AP) discharges

Resource availability:

  Location                          1-yes, 0-no

  Bed size                          Per 100 beds

  Occupancy rate

  Medicaid reimbursement

  Competitive market                1-yes, 0-no

Managed care influence:

  Capitation arrangement            1-yes, 0-no

Institutional pressures:

  Ownership type:

    Not-for-profit                  1-yes, 0-no

    Investor owned                  1-yes, 0-no

  Teaching hospital status          1-yes, 0-no

External orientation:

  Reported community health         0-8
  orientation activities

  Self-assessment on Baldrige       1-yes, 0-no
  criteria

  Degree of physician integration   0-8

  Network participation             1-yes, 0-no

EXHIBIT 2
Hospital Characteristics by Diversity Plans and Translation
Services (n = 478)

                                        With DP         Without DP
Independent Variables                  (n = 367)        (n = 111)

Community demand:

  % African American discharges       9.0 (14.1)       8.9 (13.6)
  (mean) (s.d.)

  % Hispanic/Latino discharges        9.6 (17.1)      13.3 (20.1) *
  (mean) (s.d.)

  % Asian American discharges         1.6 (3.5)        1.7 (3.1)
  (mean) (s.d.)

Resource availability:

  Rural location (frequency) (%)       58 (15.8)        23 (20.7)

  Bed size (mean) (s.d.)              185 (202)        168 (216)

  Occupancy rate (mean) (s.d.)       63.5 (53.7)      62.5 (32.7)

  % Medicaid reimbursement (mean)    15.3 (11.6)      17.6 (10.7)
  (s.d.)

  Competitive market (frequency)       71 (19.4)        37 (33.3)
  (%)

Managed care influence:

  Capitation arrangement               70 (19.1)         6 (5.4)
  (frequency) (%)

Institutional pressures:

  Ownership type:

    Public (frequency) (%)             66 (18.0)        13 (11.7)

    Not-for-profit (frequency) (%)    256 (69.8)        65 (58.6)

    Investor owned (frequency) (%)     46 (12.3)        33 (29.7)

    Teaching hospital (frequency)      94 (25.6)        19 (17.1)
    (%)

External orientation:

  Self assessed Baldrige criteria     215 (58.6)        33 (29.7)
  (frequency) (%)

  Community health orientation        6.0 (2.7)        3.5 (3.4)
  activities (mean) (s.d.)

  Physician integration (mean)       0.71 (0.81)      0.37 (0.65) ***
  (s.d.)

  Network participation               126 (34.3)        10 (9.0)
  (frequency) (%)

                                        With TS         Without TS
Independent Variables                  (n = 261)        (n = 217)

Community demand:

  % African American discharges       9.3 (14.0)      8.6 (13.8)
  (mean) (s.d.)

  % Hispanic/Latino discharges       10.2 (16.5)     10.8 (19.4)
  (mean) (s.d.)

  % Asian American discharges         1.9 (4.0)       1.2 (2.6)
  (mean) (s.d.)

Resource availability:

  Rural location (frequency) (%)       30 (11.5)       51 (23.5) ***

  Bed size (mean) (s.d.)              215 (217)       140 (182)  ***

  Occupancy rate (mean) (s.d.)       65.3 (52.8)     60.8 (45.6)

  % Medicaid reimbursement (mean)    16.2 (12.2)     15.4 (10.5)
  (s.d.)

  Competitive market (frequency)       55 (21.1)       53 (24.4)
  (%)

Managed care influence:

  Capitation arrangement               61 (23.4)       15 (6.9)  ***
  (frequency) (%)

Institutional pressures:

  Ownership type:

    Public (frequency) (%)             42 (16.1)       37 (17.1)

    Not-for-profit (frequency) (%)    195 (74.7)      126 (58.1)

    Investor owned (frequency) (%)     24 (9.2)        54 (24.9)

    Teaching hospital (frequency)      85 (32.6)       28 (12.9) ***
    (%)

External orientation:

  Self assessed Baldrige criteria     157 (60.2)       91 (41.9) ***
  (frequency) (%)

  Community health orientation        6.2 (2.7)       4.6 (3.2)  ***
  activities (mean) (s.d.)

  Physician integration (mean)       0.74 (0.80)     0.49 (0.76) ***
  (s.d.)

  Network participation                93 (35.6)       43 (19.8) ***
  (frequency) (%)

DP: diversity plan/strategy; TS: linguistic/translation services;
* p < 0.10, ** p < 0.05, *** p < 0.01

EXHIBIT 3
Influence of Community Demand, Resource Availability, Managed Care,
Institutional Pressures, and External Orientation Variables on
Hospital Diversity Plans (n = 478)

                                     Odds
Independent Variables                Ratio      95% CI      p-value

Community demand:

  % African American discharges:

    Bottom 50 percentile             1.00
      (reference)
    3rd quartile                     0.53    [0.28, 1.04]     0.07
    4th quartile                     1.02    [0.45, 2.29]     0.97

  % Hispanic/Latino discharges:

    Bottom 50 percentile             1.00
      (reference)
    3rd quartile                     1.02    [0.50, 2.10]     0.96
    4th quartile                     0.79    10.39, 1.61]     0.52

  % Asian American discharges:

    Bottom 50 percentile             1.00
      (reference)
    3rd quartile                     0.93    [0.45, 1.93]     0.84
    4th quartile                     0.91    [0.41, 2.02]     0.82

Resource availability:

  Rural location                     0.38    [017, 0.82]      0.01
  % Medicaid reimbursement (10%      0.71    [0.54, 0.95]     0.02
    increments)

Managed care influence:

  Capitation arrangement             2.88    [1.00, 8.35]     0.05

External orientation:

  Community health orientation
    activities (1 activity           1.22    [1.12, 1.33]   < 0.01
    increments)

  Network participation              3.50    [1.54, 7.96]   < 0.01

Max-scaled R-square = 0.30: C-score = 0.80; Hosmer and Lemeshow
Goodness-of-Fit p-value = 0.25

EXHIBIT 4
Influence of Community Demand, Resource Availability, Managed
Care, Institutional Pressures, and  External Orientation
Variables on Hospital Translation Services (n = 478)

                                       Odds
Independent Variables                  Ratio      95% CI      p-value

Community demand:

  % African American discharges:

    Bottom 50 percentile (reference)   1.00
    3rd quartile                       0.67    [0.39, 1.16]    0.15
    4th quartile                       0.91    [0.51, 1.65]    0.76

  % Hispanics/Latino discharges:

    Bottom 50 percentile (reference)   1.00
    3rd quartile                       1.29    [0.75, 2.22]    0.36
    4th quartile                       0.69    [0.39, 1.22]    0.20

  % Asian American discharges:

    Bottom 50 percentile (reference)   1.00
    3rd quartile                       1.28    [0.74, 2.22]    0.37
    4th quartile                       1.65    [0.89, 3.05]    0.11

Resource availability:

  Rural location                       0.45    [0.25, 0.81]    0.01

Managed care influence:

  Capitation arrangement               2.43    [1.25, 4.70]    0.01

Institutional pressures:

  Ownership type (not-for-profit as
  reference)

    Investor owned                     0.46    [0.26, 0.84]    0.01

  Teaching hospital                    2.07    [1.16, 3.69]    0.01

External orientation:

  Community health orientation
  activities (1 activity increments)   1.13    [1.05, 1.21]   >0.01

  Network participation                1.67    [1.03, 2.72]    0.04

Max-scaled R-square = 0.24; C-score = 0.75; Hosmer and Lemeshow
Goodness-of-Fit p-value = 0.18
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