Measuring Interdisciplinary Team Performance in

ORIGINAL ARTICLE

Measuring Interdisciplinary Team Performance in a Long-Term Care Setting Helena Temkin-Greener, PhD,* Diane Gross, PhD,* Stephen J. Kunitz, MD, PhD,* and Dana Mukamel, PhD†

Objectives: The objectives of this study were to test the reliability and the validity of a survey instrument for assessing interdisciplinary team performance in long-term care settings and to measure team performance in the Program of All-Inclusive Care for the Elderly (PACE). Research Design and Methods: The analysis is based on 1220 surveys completed by team members of 26 PACE programs. Cronbach’s alphas, analysis of variance, and regression models were used to assess the reliability and the validity of the instrument. Multivariate regression analysis was used to examine factors associated with team performance in PACE. Results: Cronbach’s alphas ranging from 0.76 to 0.89 demonstrate good-to-high reliability for all domains of the team process and performance (effectiveness). Construct validity is demonstrated through the results of the regression analysis showing that leadership, communication, coordination, and conflict management are positive and significant (P ⬍0.001) predictors of team cohesion and team effectiveness. The data also support the appropriateness of aggregating individual-level responses to the unit level. Perceived team effectiveness significantly (P ⬍0.05) increases with: age of the respondents; longer length of the team’s professional work experience; shorter duration of the team’s PACE experience; more ethnically diverse composition of the team; greater ethnic concordance between team members and the participants; and greater perceived resource availability. Conclusions: Several of the factors influencing team effectiveness in PACE are potentially modifiable and, therefore, could offer insights for improving team practice.

This study was supported with funding from the National Institute on Aging Grant R01-AG17555. From the *Department of Community and Preventive Medicine, University of Rochester, School of Medicine, Rochester, New York; and the †Department of Medicine, Health Policy and Research Unit, University of California–Irvine, Irvine, California. Reprints: Helena Temkin-Greener, PhD, Department of Community and Preventive Medicine, University of Rochester, School of Medicine. Box 644, 601 Elmwood Avenue, Rochester, NY 14642. E-mail: [email protected]. Copyright © 2004 by Lippincott Williams & Wilkins ISSN: 0025-7079/04/4205-0472 DOI: 10.1097/01.mlr.0000124306.28397.e2

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Key Words: team performance, long-term care, interdisciplinary, PACE (Med Care 2004;42: 472– 481)

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he team approach in health care has become a common way to organize service delivery. Today a variety of managerial and clinical teams are found in primary care practice, managed care, critical acute care, and long-term care.1 Among clinical teams, interdisciplinary teams are the most developed. They are defined as composed of at least 2 disciplines and are characterized by all members participating in the team’s activities, sharing leadership and relying on each other to accomplish team goals.2 Interdisciplinary teams are empowered to make and implement decisions, thus having a potential for effecting change.3 Considerable attention has been focused on the effectiveness of interdisciplinary teams, and studies have linked team performance to positive patient outcomes. For example, in acute care settings, poor team communication and lack of coordination among healthcare providers has been shown to impact care effectiveness, resulting in unnecessary hospital days and cost, increased readmissions, and mortality rates.4 – 6 In intensive-care units, a team-oriented culture and team processes reflective of good communication, the ability to resolve conflicts, effective leadership, and other quality attributes have been shown to result in shorter patient length of stay and higher perceived technical quality of care.7 Interdisciplinary team functioning has been considered especially important in caring for the frail elderly, because the complexity of these patients’ needs demands highly effective coordination of resources across time, multiple settings of care, and diverse disciplines.1,8 The extent to which interdisciplinary teamwork improves patient outcomes depends on how well team members work together. Much research has been devoted to understanding the team process, defining the components of team performance, and identifying characteristics of effective teams.9 –11 Although assessments of team performance in Medical Care • Volume 42, Number 5, May 2004

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health care are considered important, tested and proven methodologies for evaluating team performance are scarce and primarily limited to acute care.7,12–14 In long-term care, studies of interdisciplinary team performance have been largely qualitative and often anecdotal.15–17 This study is the first, to our knowledge, to validate, investigate the properties of, and apply a quantitative tool measuring interdisciplinary team processes and perceived effectiveness in a long-term care setting. We adapted an instrument developed18 and validated12 by the Shortell group for use in intensive-care units to a long-term care setting. We chose to apply and validate it in the Program of All-Inclusive Care for the Elderly (PACE). PACE is a community-based, managed care program that integrates acute and long-term care services for frail elderly with complex care needs.19,20 A critical feature of the model is its reliance on interdisciplinary teams for care planning and provision.17,20 PACE teams are composed of primary care physicians, nurse practitioners, clinic and home health nurses, social workers, occupational and physical therapists, dietitians, healthcare workers (aides), recreation therapists, transportation workers, and others.20,21 The PACE team is extensive and inclusive, encompassing all staff involved in planning and/or delivery of patient care. In everyday practice, smaller subsets of individuals or disciplines operate as proxies for this comprehensive team to accomplish the fundamental processes of care management and care delivery. Thus, PACE offers an excellent setting for testing the instrument and investigating its properties. The purpose of this study is 2-fold. First, we test the reliability and the validity of the adapted survey instrument. Second, we measure the perceived performance of interdisciplinary teams in 26 PACE sites and identify those areas that could benefit from quality improvement efforts.

MODEL OF TEAM PERFORMANCE IN LONG-TERM CARE We chose to adapt the model developed by Rousseau and Shortell for assessing the performance of nurse–physician interdisciplinary teams in intensive care.18 We found this model particularly suited for adaptation to long-term care for several reasons. First, the model’s domains— broad conceptual groupings that identify the essential components of team process and performance—are multidimensional and compatible with those which the literature suggests are crucial in geriatric and interdisciplinary teams serving people with complex needs. Second, although there are important differences between acute and long-term care, there are also many similarities in terms of team interaction. Finally, this tool offers a good starting point because it has been validated12 and shown to be associated with patient health outcomes.7 A number of variables that are fundamental to effective teamwork in health care, regardless of setting, have been identified in the literature. Most often, these include leader© 2004 Lippincott Williams & Wilkins

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ship, communication, coordination, and conflict resolution.2,8,12,22 When effective, these team processes are expected to result in greater team cohesiveness, defined as the degree to which group members identify with their team and with common team goals. Together, the team processes and team cohesion influence team performance, measured here by perceived team effectiveness.12 Furthermore, a number of variables could mediate the relationship between team process factors and team performance. These variables include working conditions (eg, stress, pace of work, distractions) and the availability of resources and staffing (eg, availability and quality of supplies). The relationship between the team process factors, team performance, and the mediating variables is depicted in the conceptual model presented in Figure 1. The team process and performance measures from the adapted survey are defined, and sample questions for each are presented in Appendix 1. A copy of the survey is available on request.

DATA AND METHODS Sample This study included 26 PACE programs in existence before January 2000. Data were collected between June and September 2001. The participating PACE programs identified all 1860 part-time and full-time employees who had direct patient care responsibilities. All received the team survey accompanied by a letter from their program administrator requesting their participation in the study. Participation was voluntary and survey responses were kept strictly confidential. The respondents mailed completed surveys directly to the research team. The surveys were self-administered, taking approximately 30 minutes to complete. Four approaches were used to maximize the response rates: 1) surveys were available in several languages; 2) a toll-free telephone line pro-

FIGURE 1. Managerial and team process factors affecting performance.

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vided support to respondents who had survey-related questions; 3) there were 2 follow-up mailings to nonrespondents; and 4) aides were paid $10 for completing the survey.

Survey Instrument The instrument consisted of 59 items measuring each of the team domains on a 5-point Likert scale. Each concept is measured by multiple questions/statements, both positively and negatively phrased. Questions about the respondents’ demographic background and work experience were also included. The instrument was piloted using 3 approaches. Because the PACE team is composed of staff with vastly different levels of education and experience, from physicians to aides, we had the questions reviewed by a specialist in education and English as a second language to confirm their appropriateness for a 5th grade reading comprehension level. The survey was also reviewed by an expert panel of 12 professionals, formerly employed in PACE, to assess the instrument’s items for their face and content validity. Feedback from this group was incorporated in a revised instrument, which was then piloted among 84 aides working in 2 long-term care settings: a PACE program and a nursing home.

ies,23,24 we hypothesized that diversity enhances a team’s ability to tap into a broad network of contacts and increases its responsiveness to changing organizational conditions. Ethnic diversity was calculated as an index of decreasing majority race (DMR), defined as: DMR ⫽ 1 ⫺ 共Pw 2 ⫹ Pn 2 兲, where Pw is the proportion of white and Pn is the proportion of nonwhite team members. The DMR index ranges from 0.0 to 0.5. A team composed of a single ethnic group has a DMR ⫽ 0, whereas a team with equal proportions of whites and nonwhites has a DMR ⫽ 0.5.

Program Characteristics Several program characteristics were also included: adequacy of perceived resources/staffing, workplace conditions, age of program, and ethnic concordance between staff and program participants. Following other research,25 we hypothesized that greater ethnic concordance increases a team’s perceived ability to meet patient and family care needs (a component of team effectiveness). We calculated an ethnicity overlap index (EOI) as

Variable Construction Domain Measures Our theoretical model identifies team effectiveness as an outcome of team performance. Leadership, coordination, communication, conflict management, and team cohesion are team process measures and predictors of team performance. For each item included in a domain, a numerical score was assigned, ranging from 1 for strongly disagree to 5 for strongly agree. An average was then computed by adding the values of the nonmissing items in a domain and dividing the sum by the number of nonmissing items in the domain. A score of 5 represents the most positive, and a score of 1 the most negative, appraisal of a domain.

Personal Characteristics To allow us to investigate the properties of responses to perceived team performance questions, we included the following individual-level variables: age, gender, ethnicity, education, professional (physicians, nurses, social workers, therapists, dietitians) and paraprofessional (aides, drivers, coordinators, and so on) categories, employment status (fulltime, part-time, or per diem), years of experience in occupation or profession, and years of experience in PACE.

Team Characteristics We also constructed variables measuring mean team characteristics: mean years of work experience of team members, mean years of experience on a PACE team, average age, percent females, and ethnic diversity. Based on prior stud-

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EOI ⫽ 1 ⫺

1

兺P 共P

2

P i

P i

⫺ PSt 兲2 ,

t

where PPi is the proportion of participants belonging to ethnic group i and PSt is the proportion of staff belonging to ethnic group i. When the proportion of staff and participants belonging to the same ethnic group i is the same, ie, if PPi ⫽ PSi , then EOI ⫽ 1. When the 2 groups are completely discordant (eg, 100% of participants are white, whereas 0% of staff are white), then the EOI ⫽ 0.5. It increases from 0.5 to 1 as the degree of concordance between ethnicity of staff and participants increases. Ethnic concordance of staff to participants is calculated separately for professionals and paraprofessionals.

STATISTICAL ANALYSIS Survey Reliability and Validity Evaluation of reliability and validity of the instrument was performed on the full sample, and repeated for the professionals © 2004 Lippincott Williams & Wilkins

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and the paraprofessionals separately. This was motivated by the hypothesis that professionals and paraprofessional could interpret or understand the questions differently. We assessed reliability by measuring the internal consistency of each domain using standardized Cronbach’s alpha. This statistic measures how strongly the various items comprising a domain are related to each other. Cronbach’s alpha ranges between 0 and 1, and values exceeding 0.7 indicate high reliability.26 We assessed validity by evaluating face, content, and construct validity. To assess construct validity, we examined whether the data support the theoretical model, which defines the relationships between the different domains. We evaluated this by estimating 2 regression models in which the dependent variables were team cohesion and team effectiveness, respectively, and the independent variables were leadership, communication, coordination, conflict management, and the mediating variables. These models included program fixed effects to account for the hierarchical nature of the data and the possibility that other program-specific factors (not explicitly identified) influence team cohesion and team effectiveness. We calculated the incremental adjusted R2 when team process variables were added to a model with site effects only. This incremental adjusted R2 indicates the contribution of team process variables to the explanation of the variation in team cohesion and effectiveness. The models were also estimated separately for professionals and paraprofessionals, but were found to be similar. Hence, we present only the results for the overall model.

Aggregation of Individual Responses to the Program Level For the survey instrument to be useful in measuring team performance in different programs, the responses have to: 1) have little variability across members of the same team and 2) have substantial variability of mean responses across programs. This assures that perceived team performance is viewed consistently within each team while at the same time is sufficiently sensitive to measure differences between teams. To evaluate this property of the instrument, we calculated the F-statistic for each of the 6 domains assessed in the survey. The F-statistic is the ratio of the variation between teams to the variation within teams (corrected for degrees of freedom). If variability within the team is much larger than across teams, the F-statistic will approach zero. We tested the hypothesis that the F-statistic equals zero. Rejecting this hypothesis indicates that survey responses can be aggregated to the team level and that they provide meaningful measures of differences between teams.

Predictors of Team Performance To gain insights into characteristics of individual respondents, teams, and programs that are associated with © 2004 Lippincott Williams & Wilkins

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effective team performance, we estimated regression models in which team effectiveness was the dependent variable and individual, team, and PACE site characteristics were the independent variables. These were estimated as random intercept models with clustering at the PACE program level to account for the potential correlation between observations for individuals in the same site. For all time-based variables, we included a linear and a squared term to allow for the possibility that the strength of the association declines or increases with time. Because such variables are likely to be highly collinear, we tested for their joint significance with an F-test. Because survey response rates varied by PACE site, we also estimated a model that included the response rate to allow for the possibility that it is correlated with team performance perceptions. This variable was not significant and all other coefficient estimates were similar. We therefore present the models excluding the response rate.

RESULTS Characteristics of Survey Respondents A total of 1220 surveys were completed for an overall response rate of 65%, 62% among aides and 67% among all others. The rates varied by site from 36% to 84%. Characteristics of survey respondents are summarized in Table 1. They are predominantly female (88%) and older than 40 years, reflecting the composition of the healthcare workforce in other long-term care settings. The ethnic composition of the PACE workforce is diverse: 54% white, non-Hispanic, and 46% other.

Instrument and Model Testing Reliability and Validity Descriptive statistics and reliability coefficients for each domain used in the survey are presented in Table 2. Although Cronbach’s alphas for paraprofessionals tend to be lower (range, 0.73– 0.87) than for the professionals (ranging from 0.78 to 0.91), all domains demonstrate good-to-high reliability. Overall, reliability is highest for the perceived team effectiveness (Cronbach’s alpha ⫽ 0.89) and lowest for coordination and conflict management (Cronbach’s alpha ⫽ 0.76). Several dimensions of validity were assessed. The survey’s face validity is derived from the fact that it was adapted from a previously tested and validated instrument and from its inspection by a panel of PACE providers who were asked to assess the relevance of the questions to PACE teams. Its content validity was ascertained by examining the relevance of the survey questions to the constructs being measured. Construct validity is demonstrated through the results of the regression analyses presented in Table 3. The

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TABLE 1. Descriptive Statistics: Personal, Team, and PACE Site Characteristics Variables Personal characteristics Age Gender Ethnicity Education

Occupation

Occupation category Employment status

Professional experience PACE experience Team structure characteristics Team’s professional experience Team’s PACE experience Mean age Percent female Ethnic diversity index*

PACE site characteristics Perceived resource/staffing availability Perceived workplace conditions Age of program Ethnic overlap index* Paraprofessionals-to-participants Professionals-to-participants

Category/Level sample size ⫽ 1220 Years Female White—not Hispanic Other High school or less Some college College graduate Postgraduate Other Aides Social work Nurse Physician and nurse practitioner Therapist Activity coordinator Driver Other Professional Paraprofessionals Full-time Part-time Per diem Years in profession Years in PACE Sample size ⫽ 26 Mean years of professional experience Mean years of team members in PACE Average age of team members Index range 0.0–0.5; 0.5 ⫽ most heterogeneous 0.0 ⫽ dominated by one race Sample size ⫽ 26 Mean score Mean score Years Index range 0.5–1; 1 ⫽ perfect overlap Index range 0.5–1; 1 ⫽ perfect overlap

Mean (Standard deviation)

41.58 (9.96) 87.86% 54.55% 45.55% 27.32% 24.95% 28.65% 17.93% 1.14% 43.64% 8.54% 19.07% 5.60% 7.12% 5.12% 3.42% 7.50% 49.24% 50.76% 81.02% 15.09% 3.89% 10.14 (8.94) 3.75 (3.38) 10.04 (2.13) 3.77 (1.11) 41.71 (2.14) 87.11% 0.42 (0.11)

3.77 (0.86) 3.18 (0.91) 7.35 (2.79) 0.94 (0.06) 0.97 (0.05)

*See methods section of the paper for definition and algorithm. Standard deviations are shown only for continuous variables.

estimated models confirm the associations posited in Figure 1. Team process variables explain 55% of the variation in team cohesion (model 1) and 52% of the variation in team effectiveness (model 2). As postulated in the theoretical model, leadership, communication, coordination,

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and conflict management are positive and significant (P ⬍0.001) predictors of team cohesion and perceived team effectiveness. Although workplace conditions are not significantly predictive of either team cohesion or team effectiveness, resources/staffing availability is. In model 3, © 2004 Lippincott Williams & Wilkins

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TABLE 2. Reliability of Survey Scales: Standardized Chronbach’s Alphas

Scales

Standardized Chronbach’s Alpha

No. of Questions

No. of Completed Responses

Mean Response*

Standard Deviation

All

Professionals

Paraprofessionals

9 10 6 10 7 7

1,211 1,158 1,164 1,152 1,217 1,155

3.79 3.60 3.87 3.55 3.99 4.19

0.77 0.69 0.75 0.66 0.73 0.69

0.81 0.82 0.76 0.76 0.82 0.89

0.86 0.85 0.78 0.79 0.86 0.91

0.73 0.79 0.75 0.74 0.79 0.87

5 5

1,183 1,181

3.18 3.77

0.91 0.86

0.79 0.84

0.79 0.85

0.77 0.83

Team domains Leadership Communication Coordination Conflict management Team cohesion Perceived team effectiveness Mediating variables Workplace conditions Resources and staffing *1 ⫽ most negative; 5 ⫽ most positive.

TABLE 3. Test of Construct Validity: Multivariate Regression Results Controlling for PACE Site* Intermediate “Outcome” ⴝ Team Cohesion Independent Variable

Intercept Leadership Communication Coordination Conflict management Workplace conditions Resources and staffing

Parameter Estimate

P Value

Model 1: Adjusted R2 ⫽ 0.603 Incremental Adjusted R2 ⫽ 0.5542 N ⫽ 1054 ⫺1.04370 0.0036 0.29173 ⬍0.0001 0.73739 0.0001 0.12463 0.0002 0.59637 0.0019 0.00632 0.7373 0.04927 0.0186

Intercept Team cohesion Workplace conditions Resources and staffing

Performance Outcome ⴝ Team Effectiveness Parameter Estimate

P Value

Model 2: Adjusted R2 ⫽ 0.594 Incremental Adjusted R2 ⫽ 0.5202 N ⫽ 1054 0.51499 0.0794 0.06829 0.0019 0.43019 0.0084 0.26499 ⬍0.0001 0.28603 ⬍0.0001 0.01571 0.3693 0.07464 0.0001 Adjusted Model 3: R2 ⫽ 0.4981 Incremental Adjusted R2 ⫽ 0.4242 N ⫽ 1054 1.51732 ⬍0.0001 0.51578 ⬍0.0001 0.05769 0.0028 0.13443 ⬍0.0001

*Site coefficients are not shown. Incremental adjusted R2 calculated for a model in which team variables were added to site fixed effects.

we examine the effect of team cohesion and the mediating variables on team effectiveness. The model explains 42% of the variation in team effectiveness, and all of the independent variables are statistically significant. It is also interesting to note the relative importance of the various team process variables. Communication appears to impact team cohesion and effectiveness the most, followed by conflict management, coordination, and finally leadership. © 2004 Lippincott Williams & Wilkins

Aggregating Measures to Unit Level Table 4 reports the F-statistic for each domain and shows that the variability within a team is significantly lower than the variability across teams. The mean of individual responses for each team domain is, therefore, a good approximation of the team as a whole. This also holds when tested separately for professionals and paraprofessionals.

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TABLE 4. Analysis of Variance: PACE Team Survey All Team Members

Professionals

Paraprofessionals

Mean Sample Mean Sample Mean Sample Score Size F-Stat P Value Score Size F-Stat P Value Score Size F-Stat P Value

Scales Team constructs Leadership Communication Coordination Conflict management Team cohesion Perceived team effectiveness Control variables Workplace conditions Resources and staffing

3.79 3.60 3.87 3.55 3.99 4.19

1,107 1,074 1,078 1,104 1,112 1,072

3.27 4.60 5.53 3.32 3.97 4.42

⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001

4.02* 3.70* 3.95* 3.60* 4.13* 4.22

534 526 526 525 535 526

1.80 2.47 3.51 2.72 2.31 2.52

0.0105 0.0001 ⬍0.0001 ⬍0.0001 0.0004 ⬍0.0001

3.59* 3.51* 3.80* 3.52* 3.88* 4.18

573 548 552 579 577 546

2.48 3.14 3.37 3.09 3.02 3.11

0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001

3.18 3.77

1,082 1,080

3.57 3.77

⬍0.0001 2.92* ⬍0.0001 3.71*

526 525

2.61 2.49

⬍0.0001 3.45* 0.0001 3.85*

556 555

2.70 2.51

⬍0.0001 ⬍0.0001

*Differences in means between professionals and paraprofessionals are statistically significant at P ⬍0.05.

Interestingly, on all team process domains, professionals view the teams as functioning better compared with paraprofessionals, yet there are no statistically significant differences between the professionals’ and the paraprofessionals’ assessments of team effectiveness. Paraprofessionals, compared with the professionals, view working conditions and the availability of resources in their respective teams as being better.

Team Performance in PACE In Table 5, we examine the association between perceived team effectiveness and individual, team, and PACE program characteristics. The only statistically significant individual-level characteristic is age (based on the F-test), with older respondents assessing team performance as being better compared with younger respondents. Several team characteristics are associated with the respondents’ assessment of team performance. The more years of professional work experience the team members have as a group, the more likely the team is considered to be effective. However, the more years of PACE work experience the team has, the less effective it is perceived to be. Furthermore, the more diverse the ethnic composition of the team, the more likely the team is perceived as effective. Team effectiveness is also positively associated with such program characteristics as resource availability, age of the program, and ethnic concordance between the participants and the professional as well as the paraprofessional team members.

DISCUSSION Theory-based, reliable, and valid measures of interdisciplinary teamwork have long been considered desirable and useful in explaining patient outcomes and in assisting with quality-of-care improvement efforts. In this article, we test the reliability and validity of a survey tool and show it to be useful in assessing interdisciplinary team processes and per-

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ceived performance in a long-term care setting. The survey tool, which was adapted from an instrument developed for intensive-care units, is grounded in a comprehensive theoretical model that explains how team processes affect perceived team performance. Based on a large, national survey, we have demonstrated the reliability of the modified instrument tool, as well as its face, content, and construct validity. Having established that the measures contained in the survey instrument represent reliable and valid indicators of team process and performance, our second objective was to assess the perceived performance of interdisciplinary teams in PACE. The PACE interdisciplinary team model has been hailed as an important innovation in caring for frail older individuals, and it has been mandated by federal regulations as a core requirement for all PACE programs.19,20 The only prior study of teams in PACE was based on a qualitative assessment of interdisciplinary teams in the first 11 PACE demonstration sites.16 The analysis we present here provides a different and a complementary perspective, being a first comprehensive, quantitative assessment of perceived team performance in 26 PACE sites. Our findings could be useful in identifying several potentially modifiable characteristics that influence interdisciplinary team performance and can, therefore, offer insights for improving team practice. Compared with paraprofessionals, professionals assess their teams as being better on all of the team process constructs: leadership, communication, coordination, conflict management, and cohesion. This could reflect their greater involvement in the core assessment/planning team and thus greater connectedness to the team model. According to the PACE philosophy, the “... team manages, integrates, and provides care. Together team members assess need, plan © 2004 Lippincott Williams & Wilkins

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TABLE 5. Factors Influencing Team Effectiveness in PACE: Multivariate Mixed Model Team Effectiveness N ⴝ 1054 Independent Variables Personal characteristics Age Age—2 Female (reference group ⫽ male) Occupation—professionals (reference group ⫽ paraprofessionals) Years of professional experience Years of professional experience—2 Years of working experience in PACE Years of working experience in PACE—2 Team structure charactersitics Years of professional experience Years of professional experience—2 Years of working experience in PACE Mean age of team members Percent female Ethnic diversity index:decreasing intensity of majority race PACE site characteristics Perceived resource/staffing availability Age of program Ethnic overlap index: Paraprofessionals-to-participants Professionals-to-participants

Parameter Estimate

P Value

0.0004 0.0001 0.1044 0.0361 0.0017 ⫺0.0002 ⫺0.0156 0.0004

0.9756* 0.7535* 0.0827 0.5592 0.7986 0.4300 0.2766 0.6040

0.0146 ⫺0.0022 ⫺0.3616 0.0079 ⫺0.0521 1.0799

0.7739* 0.3540* 0.0113 0.4167 0.8463 0.0013

0.5351 0.1220

0.0002 0.0179

2.0079 1.5504

0.0003 0.0012

*F-test for the joint significance of the linear and the squared terms is significant at P ⬍0.05.

treatment, provide most care, oversee contract services, monitor care and the participant’s changing situation.”27 In reality, the paraprofessional team members are less involved in the core team assessment/planning process and, as a result, could feel marginalized, as expressed by 1 aide’s survey comment such as: “I have found that the personnel most closely involved with the patient are least likely to be involved in their plan of care.” Greater attention to team building among the paraprofessionals could be important in improving the overall team process. A number of team and program characteristics appear important in influencing the perceptions of team effectiveness. Although more years of working experience of the team members seems to bring about better perceptions of their teams’ performance, the longer the experience on the PACE team, the worse the perception of the team’s effectiveness. This suggests that workers with prior experience could view their teams more favorably, perhaps as a result of their experience in other delivery models that do not use teams. At the same time, with a longer tenure on a PACE team could come the recognition of the team’s © 2004 Lippincott Williams & Wilkins

shortcomings, resulting in a “familiarity breeds contempt” syndrome. Sustaining the enthusiasm, active participation, and close collaboration, which teamwork demands, could require continued management support for active team building. Although the concept of team decision-making to improve patient care could be intuitively appealing to many who join the PACE team, members could come unprepared for the reality of teamwork because team skills are rarely taught in medicine, nursing, social work, or in other disciplines. The challenge of transitioning to an interdisciplinary model of care was expressed in several survey comments, such as: “As a professional, it took a while to understand and participate as a team member within the team concept”; and “PACE team is not something you just jump into. It’s because the support is not there that things fall through.” Management’s continued attention to and investment in interpersonal and team skill training could be important, as could providing team members with opportunities to increase their skills and, to the extent it is possible, alternate roles within a team (eg, the role of team facilitator).

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Two other program and team characteristics appear to be strongly associated with team performance: 1) ethnic concordance between staff and program participants and 2) ethnic diversity within a team. Research has demonstrated that racial concordance of patient and provider is associated with greater patient participation in care, higher satisfaction, and increased adherence to treatment.25 Our study suggests that racial concordance between PACE care providers and their patients also predicts better assessments of team performance by the providers. This appears to be true of both the professionals and the paraprofessionals. With respect to the impact of demographic (including ethnicity and race) diversity on workgroup performance, research has been more equivocal. Some have shown demographic heterogeneity to be beneficial, thus supporting a “value-in-diversity” hypothesis.28 Others have found heterogeneous workgroups to be less socially integrated, to have higher turnover rates, and to experience more conflict and communication problems than more homogeneous groups.29 In our study, greater ethnic diversity within a team appears to result in a better assessment of team performance. This finding is consistent with research showing that in collectivistic organizational cultures, as compared with individualistic ones, increased diversity of workgroups is related to increased performance.30 This suggests that an emphasis on increased diversity alone is not sufficient to bring about good outcomes. In organizations in which both collectivism (eg, emphasis on shared objectives) and diversity are important, managers need to foster a sense of shared values and common fate to integrate diverse people into their organization. Celebrating team success, rewarding the entire team based on outcomes, and eliciting input from all staff on areas for team improvement are a few possible methods of achieving this. The model of teamwork we used in this study recognizes the multidimensionality of the team process. Our findings suggest that efforts at improving team performance must also be multifaceted. Two caveats are noteworthy and instructive of further research needed. First, our assessment of team performance is a single point in time estimate. Programs’ ability to maintain good performance over longer periods of time might not be completely reflected in such a point estimate, as individual, program, and team structure, which could change over time, seem to impact performance. Reassessments of team performance are necessary to identify consistent high performers and to encourage continuous quality improvement. Second, the ultimate measure of team performance is the ability to bring about good patient outcomes. Although the current study does not address this issue, our research team is pursuing this line of inquiry with funding from the National Institute on Aging. The next step in this line of research is to examine if better-performing teams produce better risk-adjusted patient outcomes, and if so, to identify

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what organizational and team characteristics and care processes are associated with best health outcomes. Insights from such studies will further guide programs’ efforts to improve the care they provide.

ACKNOWLEDGMENTS The authors thank the PACE programs for their participation in this study. They also thank Rachel Ritz, MS, for her help with the analyses. REFERENCES 1. Committee on Quality of Health Care in America, Institute of Medicine. Crossing the Quality Chasm. A New Health System for the 21st Century. Washington, DC: National Academy Press; 2001. 2. Heinemann GD. Teams in health care settings. In: Heinemann GD, Zeiss AM, eds. Team Performance in Health Care: Assessment and Development. New York: Kluwer Academic/Plenum Publishers; 2002:3–28. 3. Garner HG. Multidisciplinary versus interdisciplinary teamwork. In: Garner HG, Orelove FP, eds. Teamwork in Human Services: Models and Applications Across the Life Span. Boston: Butterworth-Heinemann; 1994:19 –36. 4. Gavett JW, Drucker WR, McCrum MS, Dickinson JC. A Study of High Cost Inpatients in Strong Memorial Hospital. Rochester, New York: Rochester Area Hospital Corporation and the University of Rochester; 1985. 5. Knaus WA, Draper EA, Wagner DP, Zimmerman JE. An evaluation of outcome from intensive care in major medical centers. Ann Intern Med. 1986;104:410 – 418. 6. Baggs JG, Ryan SA, Phelps CE, Richeson JF, Johnson JE. The association between interdisciplinary collaboration and patient outcomes in a medical intensive care unit. Heart Lung. 1992;21:18 –24. 7. Shortell SM, Zimmerman JE, Rousseau DM, et al. The performance of intensive care units: does good management make a difference? Med Care. 1994;32:508 –525. 8. Heinemann GD, Zeiss AM. Team Performance in Health Care: Assessment and Development. New York: Kluwer Academic/Plenum Publishers; 2002. 9. Fried B, Topping S, Rundall TG. Groups and teams in health services organizations. In: Shortell SM, Kaluzny AD, eds. Health Care Management. Organization, Design and Behavior, 4th ed. Albany, NY: Delmar; 2000. 10. Nichols L, DeFriese AM, Malone CC. Team process. In: Heinemann GD, Zeiss AM, eds. Team Performance in Health Care. Assessment and Development. New York: Kluwer Academic/Plenum Publishers; 2002:71– 88. 11. Heinemann GD, Zeiss AM. A model of team performance. In: Heinemann GD, Zeiss AM, eds. Team Performance in Health Care: Assessment and Development. New York: Kluwer Academic/Plenum Publishers; 2002:29 – 42. 12. Shortell SM, Rousseau DM, Gillies RR, Devers K, Simons TL. Organizational assessment in intensive care units (ICUs): construct development, reliability, and validity of the ICU nurse–physician questionnaire. Med Care. 1991;29:709 –727. 13. Zimmerman J, Shortell S, Duffy J, et al. Improving intensive care: observations based on organizational case studies in nine intensive care units: a prospective multicenter study. Crit Care Med. 1993;21:1443–1451. 14. Zimmerman J, Rousseau DM, Duffy J, et al. Intensive care at two teaching hospitals: an organizational case study. Am J Crit Care. 1994;3:129 –138. 15. Sheridan JE, White J, Fairchild TJ. Ineffective staff, ineffective supervision, or ineffective administration? Why some nursing homes fail to provide adequate care. Gerontologist. 1992;32:334 –341. 16. Zimmerman Y. Interdisciplinary Teamwork as Case Management. PACE Internal Document. Cambridge, MA: Abt Associates Inc.; 1996:1–21. 17. Zimmerman Y, Pemberton D, Thomas L. Evaluation of the PACE Demonstration: Factors Contributing to Care Management and Decision Making in the PACE Model. Cambridge, MA: Abt Associates, Inc; 1998:1–30.

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18. Shortell S, Rousseau DM. Excerpted from The Organization and Management of Intensive Care Units. 1989. 19. Bodenheimer T. Long-term care for frail elderly people—the on look model. N Engl J Med. 2002;341:1324 –1328. 20. Eng C, Pedulla J, Eleazer PG, McCann R, Fox N. Program of All-inclusive Care for the Elderly (PACE): an innovative model of integrated geriatric care and financing. J Am Geriatr Soc. 1997;45: 223–232. 21. Pacala JT, Kane RL, Atherly AJ, et al. Using structured implicit review to assess quality of care in the Program of All-inclusive Care for the Elderly (PACE). J Am Geriatr Soc. 2000;48:903–910. 22. Flood BA. The impact of organizational and managerial factors on quality of care in health care organizations. Med Care Rev. 1994;51:381– 428. 23. Tushman ML. Special boundary roles in the innovation process. Administrative Science Quarterly. 1977;22:587– 605. 24. Donnellon A. Cross functional teams in product development: accommodating the structure to the process. Journal of Product Innovation Management. 1993;10:392.

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APPENDIX 1. Interdisciplinary Team Process and Performance in Long-Term Care: Domain Definitions and Sample† Assessment Items.

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