Dataset Information

Development and validation of the primary care team dynamics survey.

ABSTRACT:

Objective

To develop and validate a survey instrument designed to measure team dynamics in primary care.

Data sources/study setting

We studied 1,080 physician and nonphysician health care professionals working at 18 primary care practices participating in a learning collaborative aimed at improving team-based care.

Study design

We developed a conceptual model and administered a cross-sectional survey addressing team dynamics, and we assessed reliability and discriminant validity of survey factors and the overall survey's goodness-of-fit using structural equation modeling.

Data collection

We administered the survey between September 2012 and March 2013.

Principal findings

Overall response rate was 68 percent (732 respondents). Results support a seven-factor model of team dynamics, suggesting that conditions for team effectiveness, shared understanding, and three supportive processes are associated with acting and feeling like a team and, in turn, perceived team effectiveness. This model demonstrated adequate fit (goodness-of-fit index: 0.91), scale reliability (Cronbach's alphas: 0.71-0.91), and discriminant validity (average factor correlations: 0.49).

Conclusions

It is possible to measure primary care team dynamics reliably using a 29-item survey. This survey may be used in ambulatory settings to study teamwork and explore the effect of efforts to improve team-based care. Future studies should demonstrate the importance of team dynamics for markers of team effectiveness (e.g., work satisfaction, care quality, clinical outcomes).

SUBMITTER: Song H

PROVIDER: S-EPMC4450936 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Development and validation of the primary care team dynamics survey.

Song Hummy H Chien Alyna T AT Fisher Josephine J Martin Julia J Peters Antoinette S AS Hacker Karen K Rosenthal Meredith B MB Singer Sara J SJ

Health services research 20141125 3

<h4>Objective</h4>To develop and validate a survey instrument designed to measure team dynamics in primary care.<h4>Data sources/study setting</h4>We studied 1,080 physician and nonphysician health care professionals working at 18 primary care practices participating in a learning collaborative aimed at improving team-based care.<h4>Study design</h4>We developed a conceptual model and administered a cross-sectional survey addressing team dynamics, and we assessed reliability and discriminant val ...[more]

PMID: 25423886

Similar Datasets

Project description:BackgroundMeasuring quality of primary care has attracted much attention around the world. Our team has developed and validated an Assessment Survey of Primary Care (ASPC) for evaluating quality of primary care in China. To facilitate the daily use of ASPC, this study aimed to develop and validate a rapid assessment version of ASPC (RA-ASPC) in China.MethodsThis is a multi-phase study on 21 experts and 1,184 patients from 12 primary care facilities in 10 cities in China. Importance, representativeness, easy understanding, and general applicability of each item in ASPC scale were rated to select the top two ranked items for constituting RA-ASPC. Reliability of RA-ASPC was tested by calculating both Cronbach's alpha and McDonald's omega coefficients. Structural validity was assessed by exploratory and confirmatory factor analysis (EFA and CFA). Concurrent validity was performed by analyzing the relationship between RA-ASPC and patient satisfaction. Discriminant validity was tested by assessing the difference of RA-ASPC scores between patients with or without family doctors.ResultsTen items were selected for RA-ASPC. Both Cronbach's alpha (0.732) and McDonald's omega (0.729) suggested satisfactory internal consistency. In EFA, explained variance of RA-ASPC (72.6%) indicated its ability to measure quality of primary care in China. CFA indicators showed convincing goodness-of-fit (GFI = 0.996, AGFI = 0.992, CFI = 1.000, NFI = 0.980, RMR = 0.022, and the RMSEA = 0.000) for RA-ASPC. Positive association between RA-ASPC and patient satisfaction supported the concurrent validity of RA-ASPC. Patients with family doctors perceived higher quality of primary care than those without family doctors, indicating good discriminant validity of RA-ASPC.ConclusionThe theoretical framework of RA-ASPC was in line with internationally recognized core functions of primary care. Good psychometric properties of RA-ASPC proved its appropriateness in assessing quality of primary care from patients' perspectives in China.

Project description:BACKGROUND:Patients with mental illness are frequently treated in primary care, where Primary Care Providers (PCPs) report feeling ill-equipped to manage their care. Team-based models of care improve outcomes for patients with mental illness, but multiple barriers limit adoption. Barriers include practical issues and psychosocial factors associated with the reorganization of care. Practice facilitation can improve implementation, but does not directly address the psychosocial factors or gaps in PCP skills in managing mental illness. To address these gaps, we developed Relational Team Development (RELATED). METHODS:RELATED is an implementation strategy combining practice facilitation and psychology clinical supervision methodologies to improve implementation of team-based care. It includes PCP-level clinical coaching and a team-level practice change activity. We performed a preliminary assessment of RELATED with a convergent parallel mixed method study in 2 primary care clinics in an urban Federally Qualified Health Center in Southwest, USA, 2017-2018. Study participants included PCPs, clinic staff, and patient representatives. Clinic staff and patients were recruited for the practice change activity only. Primary outcomes were feasibility and acceptability. Feasibility was assessed as ease of recruitment and implementation. Acceptability was measured in surveys of PCPs and staff and focus groups. We conducted semi-structured focus groups with 3 participant groups in each clinic: PCPs; staff and patients; and leadership. Secondary outcomes were change in pre- post- intervention PCP self-efficacy in mental illness management and team-based care. We conducted qualitative observations to better understand clinic climate. RESULTS:We recruited 18 PCPs, 17 staff members, and 3 patient representatives. We ended recruitment early due to over recruitment. Both clinics developed and implemented practice change activities. The mean acceptability score was 3.7 (SD=0.3) on a 4-point Likert scale. PCPs had a statistically significant increase in their mental illness management self-efficacy [change = 0.9, p-value= <.01]. Focus group comments were largely positive, with PCPs requesting additional coaching. CONCLUSIONS:RELATED was feasible and highly acceptable. It led to positive changes in PCP self-efficacy in Mental Illness Management. If confirmed as an effective implementation strategy, RELATED has the potential to significantly impact implementation of evidence-based interventions for patients with mental illness in primary care.

Project description:BackgroundThe science of effective teams is well documented; far less is known, however, about how specific team configurations may impact primary care team effectiveness. Further, teams experiencing frequent personnel changes (perhaps as a consequence of poor implementation) may have difficulty delivering effective, continuous, well-coordinated care. This study aims to examine the extent to which primary care clinics in the Veterans Health Administration have implemented team configurations consistent with recommendations based on the Patient-Centered Medical Home model and the extent to which adherence to said recommendations, team stability, and role stability impact healthcare quality. Specifically, we expect to find better clinical outcomes in teams that adhere to recommended team configurations, teams whose membership and configuration are more stable over time, and teams whose clinical manager role is more stable over time.Methods/designWe will employ a combination of social network analysis and multilevel modeling to conduct a database review of variables extracted from the Veterans Health Administration's Team Assignments Report (TAR) (one of the largest, most diverse existing national samples of primary care teams (nteams > 7000)), as well as other employee and clinical data sources. To ensure the examination of appropriate clinical outcomes, we will enlist a team of subject matter experts to select a concise set of clear, prioritized primary care performance metrics. We will accomplish this using the Productivity Measurement and Enhancement System, an evidence-based methodology for developing and implementing performance measurement.DiscussionWe are unaware of other studies of healthcare teams that consider team size, composition, and configuration longitudinally or with sample sizes of this magnitude. Results from this study can inform primary care team implementation policy and practice in both private- and public-sector clinics, such that teams are configured optimally, with adequate staffing, and the right mix of roles within the team.Trial registrationNot applicable-this study does not involve interventions on human participants.

Project description:PurposeSpecialty care coordination relies on information flowing bidirectionally between all three participants in the "specialty care triad" - patients, primary care providers (PCPs), and specialists. Measures of coordination should strive to account for the perspectives of each. As we previously developed two surveys to measure coordination of specialty care as experienced by PCPs and specialists, this study aimed to develop and evaluate the psychometric properties of a related survey of specialty care coordination as experienced by the patient, thereby completing the suite of surveys among the triad.MethodsWe developed a draft survey based on literature review, patient interviews, adaptation of existing measures, and development of new items. Survey responses were collected via mail and online in two waves, August 2019-November 2019 and September 2020-May 2021, among patients (N=939) receiving medical specialty care and primary care in the Veterans Affairs health system. Exploratory and confirmatory factor analysis were used to assess scale structure. Multiple linear regression was used to examine the relationship of the final coordination scales to patients' overall experience of specialty care coordination.ResultsA 38-item measure representing 10 factors that assess the patient's experience of coordination in specialty care among the patient, PCP, and specialist was finalized. Scales demonstrated good internal consistency reliability and, together, explained 59% of the variance in overall coordination. Analyses revealed an unexpected construct describing organization of care between patient and specialist that accounted for patient goals and preferences; this 10-item scale was named Patient-Centered Care Coordination.ConclusionsThe final survey, Coordination of Specialty Care - Patient, or CSC-Patient for short, is a reliable instrument that can be used alone or with its companions (CSC-PCP, CSC-Specialist) to provide a detailed assessment of specialty care coordination and identify targets for coordination improvement.

Project description:BackgroundCommunity health centers are increasingly embracing the Patient Centered Medical Home (PCMH) model to improve quality, access to care, and patient experience while reducing healthcare costs. Care coordination (CC) is an important element of the PCMH model, but implementation and measurability of CC remains a problem within the outpatient setting. Assessing CC is an integral component of quality monitoring in health care systems. This study developed and validated the Medical Home Care Coordination Survey (MHCCS), to fill the gap in assessing CC in primary care from the perspectives of patients and their primary healthcare teams.MethodsWe conducted a review of relevant literature and existing care coordination instruments identified by bibliographic search and contact with experts. After identifying all care coordination domains that could be assessed by primary healthcare team members and patients, we developed a conceptual model. Potentially appropriate items from existing published CC measures, along with newly developed items, were matched to each domain for inclusion. A modified Delphi approach was used to establish content validity. Primary survey data was collected from 232 patients with care transition and/or complex chronic illness needs from the Community Health Center, Inc. and from 164 staff members from 12 community health centers across the country via mail, phone and online survey. The MHCCS was validated for internal consistency, reliability, discriminant and convergent validity. This study was conducted at the Community Health Center, Inc. from January 15, 2012 to July 15, 2014.ResultsThe 13-item MHCCS - Patient and the 32-item MHCCS - Healthcare Team were developed and validated. Exploratory Structural Equation Modeling was used to test the hypothesized domain structure. Four CC domains were confirmed from the patient group and eight were confirmed from the primary healthcare team group. All domains had high reliability (Cronbach's α scores were above 0.8).ConclusionsPatients experience the ultimate output of care coordination services, but primary healthcare staff members are best primed to perceive many of the structural elements of care coordination. The proactive measurement and monitoring of the core domains from both perspectives provides a richer body of information for the continuous improvement of care coordination services. The MHCCS shows promise as a valid and reliable assessment of these CC efforts.

Dataset Information

Development and validation of the primary care team dynamics survey.

Objective

Data sources/study setting

Study design

Data collection

Principal findings

Conclusions

Publications

Development and validation of the primary care team dynamics survey.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets