Team climate and patients’ perception of primary healthcare attributes in Brazil: a cross-sectional study

ABSTRACT

Team climate and attributes of primary healthcare (PHC) are key elements for collaborative practice. Few researchers have explored the relationship between team climate and patients’ perceptions of PHC. This study aimed to assess the association between team climate and patients’ perceptions of primary healthcare attributes. A quantitative approach was adopted. In Stage 1, Team climate was assessed using Team Climate Inventory in 118 Family Health Strategy (FHS) teams at a PHC setting. In Stage 2, Patients’ perceptions of PHC attributes were assessed using the Primary Care Assessment Tool (PCATool) in a sample of 844 patients enrolled in teams studied in Stage 1. Cluster analysis was used to identify team climate groups. The analysis used multilevel linear regression models. Patients assigned to teams with the highest team climate scores had the highest PHC attributes scores. Patients who reported affiliation at the team level had the highest PCATool scores overall. They also scored higher on the attributes of comprehensiveness and coordinated care compared to patients with affiliation to the health unit. In conclusion, patients under the care of FHS teams exhibiting a more favorable team climate had more positive patient perceptions of PHC attributes.

KEYWORDS:

• Health personnel management
• interprofessional relations
• patient care team
• primary healthcare
• team climate

Introduction

Teamwork can improve the health outcomes of patients, families, and communities, while also improving the experience of patients and health professionals (Brandt et al., 2014). Existing literature points to significant benefits of effective teamwork in healthcare, including its positive impact on the delivery of high-quality care (Hicks et al., 2014; Piers et al., 2019), prudent use of resources, patients’ satisfaction (Will et al., 2019), and health professionals’ satisfaction (Espinoza et al., 2018; Peduzzi et al., 2021).

Primary healthcare (PHC) is an approach to organize and strengthen national health systems to bring services for health and wellbeing closer to communities. It is based on three principles: integrated health services to meet people’s health needs; addressing the determinants of health and participation of individuals, families, and communities (World Health Organization, 2018). PHC is based on teamwork and recognized as the preferred gateway to health systems strengthening (World Health Organization, 2018). Healthcare teams are typically comprised of a small number of health and social care professionals, allowing informal and frequent communication among its members (Morgan et al., 2015). These teams usually agree upon common health goals based on patients’ needs, with clarity about each profession’s role (Peduzzi & Agreli, 2018; Reeves et al., 2018). The concept of team climate, reflecting the attitudes and behaviors of team members, becomes pivotal in this context, and is defined as employee’s shared perceptions of organizational events, practices, and procedures (Anderson & West, 1998; MacInnes et al., 2020).

The study of the relationship between team climate and patients’ perceptions of PHC attributes can provide insights on how team characteristics influence patients’ overall experience at primary care settings. Attributes are domains of primary care used to measure the extent and quality of PHC services (Xhi et al., 2001). This measurement can inform the development of interprofessional interventions aimed at fostering a positive team climate and subsequently, enhance patients’ satisfaction with the quality of PHC.

Background

Team climate was the construct chosen in this study as a proxy for examining teamwork. The Team Climate Inventory is an example of how the assessment of team climate has been operationalized (Anderson & West, 1998). The inventory describes the four main dimensions of team climate: (a) participative safety, (b) common objectives, (c) task orientation or commitment to excellence, and (d) support for innovation (Anderson & West, 1998; M. West, 1990; M. A. West & Anderson, 1996).

Team climate has been shown to have an important role, and it is widely used to evaluate healthcare working environments. However, the role of teams and team climate in supporting improvements in attributes of primary healthcare and collaborative practice has received little attention.

Past researchers in Brazil have explored the relationship between team climate dimensions and collaborative practice in the context of PHC and the Family Health Strategy (FHS) (Agreli et al., 2017; Peduzzi & Agreli, 2018; Silva et al., 2016). However, these studies have not described patients’ perceptions about care they receive at the PHC level specifically from the FHS teams that are recognized as an established and successful PHC model in Brazil (Macinko & Harris, 2015).

FHS is a public health policy aimed at substitution for the traditional model of care (based on physician specialists) with a collaborative approach. Each FHS team is composed of a physician, a nurse, a nurse assistant, and four to six community health workers. Approximately 43% of FHS teams also have a dentist and a dental technician. FHC teams are organized in geographic areas covering populations of up to 1,000 households (Macinko & Harris, 2015). Research regarding the Brazilian Unified Health System (SUS) shows the positive impact of the FHS teams on the health outcomes of Brazilian communities in reduction in mortality and hospitalizations from heart and cerebrovascular diseases (Rasella et al., 2014), as well as improving access to healthcare (Macinko & Lima-Costa, 2012). Despite the increasingly widespread application of FHS teams in the population and the positive outcomes related to them, there has been little research carried out about the characteristics of high-quality primary healthcare services and primary healthcare teams. This study addressed patients’ perceptions of PHC attributes and quality, elucidating their interplay with team climate and patients’ affiliation with the FHS team. The study of settled interprofessional models, such as the FHS, is recommended in the interprofessional science literature (Reeves et al., 2017).

Strong, high-quality PHC is characterized by four core attributes: (a) First-contact care, (b) Longitudinality, (c) Comprehensiveness, (d) Coordinated care. There are others three derived attributes: (a) Family-centeredness, (b) Community orientation, (c) Cultural competence. These attributes form the basis of the Primary Care Assessment Tool – PCATool (Xhi et al., 2001), which was developed to assess the quality of PHC from the perspective of patients, health professionals, and managers. PCATool also includes questions related to variable affiliation. This variable refers to the connection between patients, either with specific health professionals or teams or health units (Oliveira et al., 2013). The focus on this aspect highlights that the affiliation between patients and professionals, and between patients and healthcare teams, constitutes key elements in the provision of comprehensive and strong PHC (Metersky et al., 2022). Although it is important not to overstate the case, the assessment of affiliation may provide insights on patients’ participation and collaboration in primary care teams, if affiliation is interpreted as reflecting patient’s relationship with their primary care teams. It is helpful, therefore, to consider in more detail the different alternatives of patients’ affiliation: to a specific professional, to the team, or to the health unit. The aim of this study was to assess the association between team climate in FHS teams and the patients’ perceptions of PHC attributes.

Method

Design

Cross-sectional research with a correlational design (Polit & Beck, 2016).

Setting and population

The study was conducted in Sao Paulo, capital of the State of Sao Paulo, which has the largest population in Brazil. The city of São Paulo is located in the Southeast region of Brazil and has a population of nearly 12 million. The population of the study encompassed FHS teams, their health professionals, and their patients (adults, 18 years of age or older). The sample of FHS teams was based on the National Register of Health Establishments of October 2017. The population of patients was identified through information from the Epidemiology and Information Center of the Municipal Health Secretariat (CEInfo-SMS) based on visits by dentists, nurses, and physicians between September and November 2017.

Inclusion criteria were as follows: PHC team with at least one professional of each category (community health agent, nurse, nursing assistant or technician, physician, dental surgeon, and oral health assistant or technician), and at least 6 months working in the same team for the first four categories and at least 4 months for the last two.

Sample

After applying the inclusion criteria to the total population of 1,328 teams identified in the National Register of Health Establishments, 174 FHS teams were identified, creating the basis of our sample. A significance level of 5% with a power of 87% led to the calculation of a sample of 150 teams, selected via simple random sampling with implicit stratification of time in which the teams were working together, calculated by the date of the last member to be incorporated into the team. The selection of patients was performed via a one-stage conglomerate probability sampling. In the first stage, a sample of teams was selected, drawing 10 patients in each team (expected sample). However, considering that the study could incur a possible selection bias, given the difficulties of location and availability of patients to participate, it was decided not to consider the complex structure of the sampling plan in the analyses and to treat this sample as a convenience sample of 844 patients, on average, 6 patients per team.

Variables and instruments

The Team Climate Inventory (TCI) by Anderson and West (1998) was used to assess team climate. TCI was validated in the context of Brazilian PHC (Silva et al., 2016). Confirmatory factor analysis confirmed the original model of four factors and 38 items, with factor loadings above .50. Cronbach’s alpha of .94 and composite reliability from .92 to .93.

The four dimensions of team climate (Agreli et al., 2017; Anderson & West, 1998) were defined as:

1. Participative safety: interaction and communication among team members and the decision-making process.

2. Common objectives: team clarity about shared goals.

3. Task orientation: individual and team responsibility and commitment to perform tasks to a high standard.

4. Support of innovation: each team member will strive to introduce new practices or improvements to support better healthcare.

The Primary Care Assessment Tool (PCA Tool) was used to assess patients’ perception of PHC attributes. The PCATool has been validated in many countries, showing good psychometric properties, and it is widely used to explore the quality of PHC from the patients’ perspective (D‘avila et al., 2017). It was validated in the context of the Brazilian Public Healthcare System (Harzheim et al., 2006), and a short version of the PCATool-Brazil has also been validated at the PHC context (Oliveira et al., 2013).

The PCATool-Brazil Short Version was chosen for this study to measure patients’ perceptions of PHC attributes. It has a Cronbach’s α of .82 and is composed of 23 items that cover the essential attributes of PHC: Affiliation, First-contact care, Longitudinality, Comprehensiveness, Coordinated care, and the derived attributes Family-centeredness and Community orientation (Oliveira et al., 2013). Three attributes of PCATool-Brazil were selected as key variables in the current study: affiliation, comprehensiveness, and coordinated care. The rationale behind the selection of these attributes lies in their intrinsic connection to the conceptual framework within the FHS. Affiliations is an indicative marker of the relationship between patients and teams. Comprehensiveness reflects the amalgamation of health promotion, preventive measures, and curative interventions, thereby exemplifying the holistic approach advocated by the FHS. Furthermore, the attribute of coordinated care was deemed critical, functioning as a tracer to ascertain the continuity of patient’s pathway within the healthcare network.

The affiliation variable expresses with whom the patient has the preferred bond: with one specific practitioner, with the team, or with the generic health unit. This variable results from patients’ answer to three questions related to the health professional, team, or health service of his/her choice. These three questions are at the beginning of the PCATool and inform the rest of the questionnaire (Oliveira et al., 2013).

Other variables used in the study were patients’ characteristics (sex, age group, race/color, education, marital status), region of the health unit, Regional Health Coordination (CRS in the Portuguese acronym).

Data collection

Data collection was performed by trained field researchers supervised by the research team. Data from PHC professionals were collected through face-to-face interviews in the health unit between Jan 3 and Dec 7, 2018, as described in Peduzzi et al. (2021). Data collection with patients was conducted from Oct 29, 2018, to July 15, 2019 using structured telephone interviews, recording the full interview from the reading and agreement of the Informed Consent Form (ICF) until the end of the questionnaire. Interviewers addressed the instrument’s questions to the patients by reading each question slowly and asking if there were any questions that need to be repeated or explained. The same procedure was adopted when presenting the five alternatives for each question of the instrument.

The interview questionnaire had three parts: eligibility questions, patient sociodemographic identification data, and PCATool-Brazil short version. At the beginning of the interview, there were two questions to assess eligibility: Do you know the team that serves you in the health unit? Do you know the dentist, the nurse, the physician, or the community health agent? To ensure anonymity of both professionals and patients, all records were coded with numbers.

Data analysis

Exploratory analysis was performed using Fisher’s exact test, Student´s test, ANOVA, Mann-Whitney test, Kruskal Wallis test, and Spearman’s correlation.

To identify team climate groups, a cluster analysis technique via the k-means partition method was used (Peduzzi et al., 2021). Patient’ perceptions about PHC attributes (dependent variable) were measured based on PCATool, and the analysis considered the means of the 23 items with imputation.

To evaluate the effects of variables: team climate (team climate group), user characteristics (sex, age, color, education, marital status), region (CRS), and type of affiliation (with one specific professional, with the team, with the health unit) on the patients’ perception of PHC attributes - (dependent variable), the analysis used multilevel linear regression models, given the hierarchical structure in which the information is arranged: patient served by a team.

A significance level of 5% was used for all statistical tests. The analyses were performed using the statistical package SPSS 20.0 and STATA 17.

Ethical considerations

The research was cleared by the Research Ethics Committee of the School of Nursing of University of Sao Paulo (CAAE: 64385717.6.0000.5392) and by the Research Ethics Committee of the Health Secretariat of the Sao Paulo municipality (CAAE: 64385717.6.3001.0086). All professionals were instructed about the study and signed an Informed Consent Form (ICF). All patients were informed about the research, and after the interviewer had read the ICF, asked if they agreed to participate in the study; their acceptance was recorded, and the record kept confidential on an external drive under the responsibility of the main researcher.

Results

The study analyzed a sample of 118 FHS teams encompassing 1,172 FHS providers and 844 patients enrolled in those teams (Figure 1).

Figure 1. Diagram illustrating the type and number of participants, their respective teams, the instruments, and additional variables.

Team climate of the FHS teams

The sample of 118 FHS teams with 1,172 professionals was composed of 43% community health agents, 14% nursing assistants, 13% oral health assistants, and 10% dentists, nurses, and physicians. The majority were women (88%); 52% black and brown, and 45% white; 54% were aged between 18 and 39, 27% between 40 and 49, 18% aged 50 or over; 42% had completed high school, 10% had incomplete higher education, and 38% had completed higher education and postgraduate studies. As for the length of time (in months) they had worked at the municipal health services, the health unit, and the team (mean ± sd), 89.2 ± 1.1, 71.4 ± 1.0., and 62.5 ± .9, respectively.

The average scores for team climate, both total and by dimension, were above 74 points. See Table 1: the averages of the four dimensions of team climate were not homogeneous (p < .001). The average scores for Participation in the team and Task orientation were similar to each other and higher than Support for new ideas and Common objectives (Table 1).

Table 1. Means of the team Climate’s score. São Paulo, 2019.

	Mean ± SD
Team Climate (0 – 100)
Participative safety	78.7 ± 6.7
Support of innovation	74.9 ± 7.3
Common objectives	74.8 ± 5.9
Task orientations	76.3 ± 7.9
Total score	76.1 ± 6.3

At first, we included team climate scores as a predictor variable in the regression model, and only “Support for new ideas” was negatively associated with patients’ perception of PHC attributes – PCATool – affiliation (−.096; 95% CI: −.152 to −.040; p = .001). However, considering that team climate is multidimensional, it made more sense to jointly analyze the effect of all four climate factors on patients’ perceptions of PHC attributes, so team climate was analyzed via team climate groups resulting from cluster analysis.

In this way, a typology of teams was constructed in terms of the four dimensions of team climates, which revealed the existence of four groups (G1, G2, G3, G4). More details on the method of analyzing the four types of team groups are presented in the article Peduzzi et al. (2021). The average scores of the four team climate groups (G1, G2, G3, G4) on each one of the four dimensions of team climate can be found in the Online Supplementary file.

According to the Supplementary file, it can be seen that group G1 (12.7% of the teams) had the highest averages in the four dimensions of team climate. Group G2 (54.2%) had the second highest averages, followed by group G3 (24.6%). Group G4 had the lowest team climate averages in all four dimensions (8.5%).

Patients’ perceptions of the PHC attributes

The sample of 844 patients was mostly cared for in health units located in the southern region of the city of São Paulo (53%), which is the poorest and most populated of the region. Most (74%) were women; 58% were brown and black; 53% were married or living with a partner; 36% had completed high school education, and 33% did not complete the mandatory first 9 years of education; 33% were 60 years old or older.

Most of the patients (65%) were served by teams with the highest scores of team climate (G1 or G2; Table 2).

Table 2. Description of the variables affiliation of the patient and the type of team climate. São Paulo, 2019.

	N = 844
User’s Affiliation	N (%)
Health Unit	150 (17,8)
One specific practitioner	371 (44,0)
Team	323 (38,3)
Team Climate Groups
G1	101 (12,1)
G2	446 (53,2)
G3	216 (25,8)
G4	75 (8,9)
No data	6

Regarding the affiliation attribute, almost half (44%) of patients reported their main affiliation with one specific professional, 38% with two or more team professionals, and 18% a generic affiliation to the health unit (Table 2). The affiliation with two or more professionals was considered a proxy for the bond with the team.

The average overall score on the PCATool, which expresses patient’s perception about the attributes of their PHC team, was 6.2 (SD = 1.7). When the three key attributes highlighted in the analysis were considered, there were mean scores of 5.0 (SD = 2.2) for user’s affiliation; mean score of 5.5 (SD = 3.3) for comprehensiveness; and mean score of 7.2 (SD = 2.3) for coordinated care (Table 3).

Table 3. Means of PCATool of patients of family health strategy teams. São Paulo, 2019.

	Mean ± SD	N
PCATool	6,2 ± 1,7	844
PCATool Attributes
Extension of affiliation	5,0 ± 2,2	844
Comprehensiveness – services available	5,5 ± 3,3	633
Coordination – care integration	7,2 ± 2,3	682

Analysis of key variables

The team climate group (p = .011), the affiliation (p < .001), the age groups 18–29 years (p = .012) and 30–39 years (p = .018) were significant variables in the model (Table 4).

Table 4. Results of the multilevel linear models for total PCATool attributes: affiliation, comprehensiveness, and coordination. São Paulo, 2019.

	PCATool
	Total		Attributes
			Affiliation		Comprehensiveness – available services		Coordination – integration of care
	Coefficient (IC95%)	p	Coefficient (CI95%)	P	Coefficient (CI95%)	P	Coefficient (CI95%)	P
Age Range (ref. = 60 years or more)		.071		.032		.805		.605
18–29 years	−0.57 (−1,01 a −0.12)	.012	−0.72 (−1,29 a −0.16)	.012	−0.56 (−1,49 a 0.37)	.240	−0.26 (−0.72 a 0.20)	.263
30–39 years	−0.50 (−0.91 a −0.09)	.018	−0.34 (−0.87 a 0.18)	.200	−0.29 (−1,18 a 0.59)	.518	−0.18 (−0.61 a 0.24)	.391
40–49 years	−0.26 (−0.62 a 0.10)	.151	−0.49 (−0.95 a −0.04)	.034	−0.35 (−1,13 a 0.42)	.370	−0.26 (−0.63 a 0.10)	.159
50–59 years	−0.31 (−0.63 a 0.01)	.058	−0.57 (−0.98 a −0.16)	.006	−0.12 (−0.83 a 0.60)	.747	−0.22 (−0.56 a 0.11)	.188
Affiliation or bonding with the team (ref.=Unit)		<.001		.183		<.001		.127
One provider	0.36 (0.04 a 0.68)	.027	−0.22 (−0.63 a 0.19)	.285	−0.08 (−0.79 a 0.63)	.819	0.20 (−0.13 a 0.53)	.238
Two or more provider from one team	0.94 (0.58 a 1,29)	<.001	0.09 (−0.37 a 0.54)	.704	1,12 (0.33 a 1,90)	.005	0.38 (0.01 a 0.74)	.044
Team Climate G1/G2 (ref. G3/G4)	0.33 (0.08 a 0.58)	.011	−0.06 (−0.44 a 0.32)	.741	0.39 (−0.22 a 0.99)	.210	0.19 (−0.06 a 0.44)	.142
N	820		820		614		804

(a) Adjusted for sex, color, marital status, education, CRS.

Patients served by teams with the highest team climate scores (G1/G2) had, on average, the highest PCATool scores (.33 points more; Table 4).

Specifically, regarding affiliation, it was found that patients who reported a connection with one specific professional (p = .027) and with the team (p < .001) had higher mean PCATool scores (total) compared to patients who reported affiliation to the health unit (.36 and .94 points more, respectively; Table 4).

In the assessment of the affiliation attribute, age groups were a significant variable (p = .032). Patients aged 18–29 years, 40–49 years, and 50–59 years were found to have lower PCATool scores than patients aged 60 years or older (Table 4).

Regarding the comprehensiveness attribute, there was a significant effect of the affiliation with the team (p=.005) on the average PCATool scores. Patients who reported affiliation to the FHS team had higher mean PCATool scores than those reporting a generic relation with the health unit (1.12 points more). No differences in mean scores were found between patients who reported an affiliation with one specific professional and those with the unit (Table 4).

Based on the analysis, the affiliation with the team was a significant factor (p = .044) in coordinated care. Patients who reported affiliation with the team had higher mean PCATool scores compared to those who reported a generic relation with the health unit. However, there were no statistically significant differences found between patients’ who reported an affiliation with one specific provider and those with a generic link with the unit. On average, younger patients (18–29 years and 30–39 years) had lower PCATool scores than patients aged 60 years or older (Table 4).

Discussion

In the present study, the majority of patients were assigned to teams with high team climate scores and the dimensions Participative safety and Task Orientation had higher scores. Patients assigned to teams with the highest team climate scores had the highest scores for PHC attributes. This result is consistent with the Brazilian PHC model, the FHS, in which patients and families are assigned to a specific team and services are organized on the bases of teamwork (Giovanella et al., 2020; Macinko & Harris, 2015). The findings of the study highlight that affiliation is an indicator of the quality of primary care (D‘avila et al., 2017) that can facilitate the building of bonds between patients and team members.

A positive team climate has been described as one in which practitioners “work through issues” through the creation of common bonds in an environment that is supportive (MacInnes et al., 2020, p. 10); therefore, building bonds can be extended through the relationship with patients. A study that applied the concept of team climate using TCI (Ndateba et al., 2023) showed that higher participative safety scores, “might contribute to higher team functioning since psychological safety influences participation in shared clinical decision-making” (Ndateba et al., 2023, p. 358), concurring with the results of the present study in which the TCI dimension of Participative safety had the highest scores.

Importantly, in the present study, patients who were cared for by teams with higher team climate scores had overall higher PHC attributes, compared to patients served by teams with lower team climate scores. Previous research demonstrated the crucial role of team climate in team performance. A positive team climate has been associated with higher levels of engagement among team members (Geue, 2018) and has been identified as a necessary condition for promoting innovation in teams (Eisenbeiss et al., 2008).

Regarding affiliation, we found that most patients reported their main connection with one specific practitioner or with the team. Although we are not aware of any similar study that investigated the affiliation of patients to healthcare teams, the concept of teamwork presupposes that teams know their patients’ care needs, define common goals, and perform health actions accordingly (Peduzzi & Agreli, 2018; Reeves et al., 2018), and these activities may strengthen affiliation between patients and team members.

Over a third of patients in the sample recognized their affiliation with two or more professionals from a specific FHS team, which was considered an affiliation between patients and their teams. This does not ensure that the patients recognize the practitioners with whom they feel connected as a team, but only as professionals from different areas who work together for their care. The patients’ bonds are not limited only to physicians, which is usual in the individual biomedical-oriented care model. The FHS teams also work on promotion and prevention, precisely because the involvement of all the members of the team allows for a more comprehensive approach.

The multilevel linear regression models allowed the assessment of the effects of variables on the perception of patients about the PHC attributes of the team, having as predictors the team climate groups and the affiliation to one specific professional, the team, or the Health Unit.

Patients reporting affiliation at the team level exhibited higher PCATool scores across all PHC attributes. Furthermore, these individuals demonstrated higher scores in comprehensiveness and coordinated care attributes, surpassing participants with a more generic affiliation with the health unit. The findings underscore the capacity of patients to develop connections with several practitioners within a team, indicating a perception of a team as a pivotal reference point. Such affiliations positively affect both patients’ care and the organizational dynamics of the health unit. This is particularly important, as the availability of a specific practitioner may vary, and diverse team members may possess distinct skills essential for addressing patients’ needs

Patients’ affiliation with the team’s practitioners reflects the quality of interaction and communication between the patient and the team, as well as the team’s knowledge of the patient’ needs, which enables them to provide comprehensive care. According to PCATool, comprehensiveness refers to services and guidance that the patients and their families may need at some point, such as mental health counseling, smoking cessation support, and information on aging-related changes (Prates et al., 2017).

Similarly, coordinated care refers to the patients’ experience of needing to consult a specialist or receive specialized services. This includes the patients’ perception of the referral process, such as whether information was conveyed to the specialist about the reason for the consultation, and whether the referring professional was aware of the results of the consultation with the specialist and showed interest in the quality of care that patients received. A study showed a positive association between coordinated care through human interaction and sharing objectives among health practitioners with higher team climate scores (Ndateba et al., 2023).

Limitations and contributions

The study was limited by the utilization of a convenience sample of patients, potentially introducing selection bias, and reliance on administered instruments. Additional limitations include the 4-year interval between data collection (Jan 2018 to July 2019) and the current publication, during which the COVID-19 pandemic unfolded (2020–2022), and Brazil grappled with multifaceted political, social, and economic crises from 2015 to 2022, negatively impacting PHC. Despite these limitations, the results are still relevant to management, emphasizing the critical significance of team climate and advocating for patients’ affiliation with professionals and teams, comprehensiveness and coordinated care in the Brazilian FHS teams. This significance is underscored by the enduring relevance of FHS as the prevailing Brazilian PHC model. Since January 2023, the Ministry of Health has reinstated health policies prioritizing PHC based on FHS.

Conclusion

The results suggest that patients under the care of FHS teams exhibiting a more favorable team climate had more positive perceptions of PHC attributes specially in comprehensiveness and coordinated care. This study also shows the role of high scores in both team climate and patient-team affiliation in enhancing patient’s perception of a strong and high-quality PHC orientation. These findings imply a positive relationship between team climate and patient’s perception about the quality of FHS teams in PHC setting. The research extends its impact arena by examining FHS teams, representing an established and successful PHC model in Brazil.

In terms of practical implications, this research offers insights for healthcare managers, policymakers, and practitioners, recommending investments in cultivating an improved team climate, with a specific focus on its four dimensions. Particularly, emphasis is placed on enhancing participative safety, indicative of robust interaction and effective communication among team members, and task orientation, emphasizing the achievement of elevated standards in healthcare tasks.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/13561820.2024.2351006.

Additional information

Funding

This work was supported by Sao Paulo Research Foundation (FAPESP) under Grant Fapesp – Public Notice PPSUS 2016 [number 2016/14975-1].

Notes on contributors

Marina Peduzzi

Marina Peduzzi is a senior professor in the School of Nursing in the University of Sao Paulo, Brazil. PhD in Public Health at Unicamp, post-doctoral program at King’s College London. She has experience in human resources for health and nursing, interprofessional education and collaborative practice research and has a background as a nurse. She is an executive member of the Brazilian Network for Interprofessional Education and Practice in Health (ReBETIS).

Heloise Lima Fernandes Agreli

Heloise Lima Fernandes Agreli is a national consultant in research for public health policies at the Oswaldo Cruz Foundation, Brazil. She has extensive experience in healthcare research and started her career as a nurse. She completed her PhD on interprofessional collaboration and has published more than 26 peer reviewed journal articles, book chapters, with a focus on interprofessional work, interprofessional education, leadership, implementation of evidence and patient involvement.

Jaqueline Alcantara Marcelino da Silva

Jaqueline Alcantara Marcelino da Silva is a professor in the Department of Nursing Management in the Federal University of São Carlos, Brazil. Vice-coordinator of the Nursing Postgraduate Program. She has experience in interprofessional education and collaborative practice research and has a background as a nurse. She is an executive member of the Brazilian Network for Interprofessional Education and Practice in Health (ReBETIS).

Mitti Ayako Hara Koyama

Mitti Ayako Hara Koyama is MSc in Statistics. She worked at SEADE Foundation and is currently a founding partner of a statistical consulting firm. She has extensive experience in statistics analysis in healthcare research.

Lislaine Aparecida Fracolli

Lislaine Aparecida Fracolli is a Full Professor in the Nursing School, at São Paulo University, Brazil. Vice-coordinator of the Inter-unities Nursing Postgraduate Program. She has a background as a nurse, she teaches and researches in Primary Health Care area. She has experience with teamwork approach in public health.

Andreas Xyrichis

Andreas Xyrichis is an NIHR Advanced Fellow in Interprofessional Science at King’s College London, and the Research Lead for the King’s Centre for Team Based Practice & Learning in Healthcare. He is also a Board Member and Research co-Lead of the UK Centre for the Advancement of Interprofessional Education, and the Editor-in-Chief of the Journal of Interprofessional Care.