Attributes of Primary Health Care in Mato Grosso Do Sul State: PCAT-Brazil Paired for Users and Health Professionals, 2018

Attributes of Primary Health Care in Mato Grosso Do Sul State: PCAT-Brazil Paired for Users and Health Professionals, 2018 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Attributes of Primary Health Care in Mato Grosso Do Sul State: PCAT-Brazil Paired for Users and Health Professionals, 2018 Rafael Aiello Bomfim, Hazelelponi Leite, Edilson José Zafalon, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1415480/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Objective. The objective of the present study was to verify the quality of adult and older adults health care in Primary Health Care (PHC) services in the four health macro-regions of the State of Mato Grosso do Sul, 2018. Methods. A quantitative survey was carried out in which the municipalities participating in the study included the four macro-regions following the Director Regional Plan (DRP). In this study, the quality of care was verified using the validated version of the PCAT-Br for adult and older adults users over 18 years of age and professionals. The macro-regions were compared between PHC attributes and between professionals and users in the State of Mato Grosso do Sul. Analysis of variance (ANOVA) and paired student t-test was performed. STATA v.14.2 software (College Station, TX, USA) was used for the analyses. Sensitivity analysis was done to compare the macro-regions and socio-demographic characteristics. Results. Eight hundred twenty-five users and 424 professionals participated in the study. According to users, the Accessibility attribute was the attribute with the worst performance in all macro-regions. There were significant differences between the perception of users and professionals in all attributes evaluated and regional differences between the perception of users among the four macro-regions analyzed. Conclusions. There was a difference in perception between users and professionals, and there were macro-regional differences between PHC attributes. Therefore, it is necessary to strengthen PHC care networks in the State, mainly considering the users' perspective. Primary Health Care Public Health PCAT-Brazil Introduction In Brazil, Primary Health Care (PHC), through the work of Family Health teams (eSF), corresponds to the structuring and coordinating axis of the Unified Health System (SUS), being the main access route for users to health services. SUS services, whose actions must be centred on the individual, meeting their health needs 1 . Shreds of evidence indicate the positive impact of PHC on the primary health indicators in the country after the implementation of the Family Health Strategy (ESF), mainly due to the significant increase in the number of eSF, implying greater coverage of this service in Brazilian territory 2 , 3 , 4 , 5 , 6 . However, the country still faces difficulties in implementing PHC and in the quality and effectiveness of the services offered 7 , 8 . One of the main barriers to implementing comprehensive PHC in Brazil is the qualification in the training of health workers, as there is a misalignment between health training and the principles of SUS and PHC 9 , 10 . The organization and orientation of services by PHC attributes promote better indicators, greater user satisfaction, equity, lower costs, and, consequently, positively impact the health of the population 1 , 11 . The evaluation of operational quality in PHC is linked to the presence and extent of four essential attributes and two derived ones. The essential ones correspond to attention to the first contact (accessibility), longitudinality, comprehensiveness and care coordination, and the derived attributes consist of people- and family-centered (family orientation) health care and cultural competence 11 . Thus, it is important to use strategies to consolidate universal and equitable access within the scope of the SUS through tools that promote evaluation and monitoring of the performance of PHC teams 12 . The evaluation process also makes it possible to unveil the experiences lived by both users and professionals that can reflect on other levels of care services in the health care network and other experiences articulated with the rest of the system 9 . Given the different organizational arrangements and specific aspects of care offerings in health services existing in Brazil, the search for performance evaluation, knowledge of the opinions of professionals who work in it, as well as information on users' experiences, can evidence the actual effectiveness of PHC and assist in the definition of public policies 12 – 14 . The objective of this study was to verify the quality of adult health care in PHC services from the perspective of users and professionals in the four health macro-regions of the State of Mato Grosso do Sul, using the PCAT-Brazil instrument. Methods This study was a cross-sectional research carried out from August to December 2018 in Mato Grosso do Sul State. The municipalities participating in the study included the 11 health microregions of Mato Grosso do Sul following the Regional Master Plan(RMP), which divided the State into four macro-regions: 1) Campo Grande, Dourados, Três Lagoas and Corumbá. Sample size calculation The sample size calculation was performed on the representativeness of the macro-regions using the STATA software (College Station, TX, USA). The parameter used was Alpha of 5% and power of 80%, assuming 10% of losses, totalling 800 users and 400 PHC professionals. The participating municipalities were defined by random selection, including all the microregions. Therefore, we respect at least four health units in each municipality and four users per health unit selected to obtain an overview of the perception of users and professionals (ratio 2:1) of the SUS in the State of Mato Grosso do Sul. Calibration of examiners Data collection was performed by interviewers who received theoretical and practical qualifications (24 hours) and underwent inter-and intra-examiner calibration, resulting in a Kappa index equal to or greater than 0.87. First, the interviewers got to know the instrument to become familiar with the characteristics of the study and facilitate the application and completion of the questionnaire. Then, the items and questions of the Primary Care Assessment Tool (PCAT-Brazil), validated in Brazil 15 , were studied and discussed to give fluency to the execution. The possible doubts that arose were resolved in time to ensure the reliability of the data. This instrument was chosen because it has already been used in several countries, which gives it the characteristic of international comparability 16 . Data collection In this study, the quality of care was verified using the PCAT-Brazil instrument for adult users over 18 years of age and professionals 15 . This instrument measures the presence and extent of essential and derived attributes of PHC and thus infers strong or weak orientation for PHC of the evaluated service 17 . In addition, the municipal health departments indicated the Primary Health Units (PHU) and those that accepted and agreed to participate in the research was included. The sample of health professionals consisted of those in the eSF in the selected units. In addition, professionals should assist adult users, fulfil a workload of at least 20 hours per week and work at the health unit for at least one year. The sample of professionals was determined by random selection, as those who worked in the health units indicated by the municipal secretariats were interviewed. After the inclusion of professionals, we included only users attended by the included professional. The interviewers collected data from the users at the participants' homes. These were randomly selected from a list also provided by the municipal health departments, containing the families assigned to each area of activity of the ESF participating in the study. Users should have resided in the territory for at least one year for the inclusion criteria. PCAT-Brazil score The scores for each attribute or component were calculated by the simple arithmetic mean of the response values of the items that make up each attribute or its component. The scores were calculated and transformed into a scale from 0 to 10, according to the PHC Assessment Instrument Manual (PCAT-Brazil) 15 . In the adult version, answered by users, the essential score is measured by the sum of the average score of the components that belong to the essential attributes (plus Affiliation Degree) divided by the number of components. The overall score is measured by the average score of components belonging to essential attributes plus components belonging to derived attributes (plus Affiliation Degree), divided by the total number of components. More information on calculation scores could be seen elsewhere 15 . Outcome Variable The score for each essential and derived PHC attribute was the dependent variable. A score ≥ 6.6 is considered by the methodology of the PCAT instrument as a minimum quality value to assess primary care services from the adult user’s perspective and in both surveys this general quality value 15 . Main exposures variables The macro region (Campo Grande, Dourados, Três Lagoas and Corumbá) and the professional/users data were the main exposures variables. Descriptive variables Descriptive data from users like gender, income, education, self-reported race, according to the Brazilian IBGE, time living in the region, sex and age group were reported. Furthermore, descriptive data from professionals like the category of the health professional, gender, and if they lived and worked in the same city and time since graduation was described. Statistical analysis The macro-regions were compared between APS attributes and between professionals and users in the State of Mato Grosso do Sul. To compare the averages between the macro-regions, analysis of variance (ANOVA) with test Tukey (post-hoc) to verify associations and for professionals and users, paired Student's t-test was used (the professional was paired with the users). A significance level of 5% was considered, and Data Analysis and Statistical Software (STATA) v.14 (College Station, TX, USA) was used. Chi-squared tests between each sociodemographic characteristics of participants and the four macro-regions was done as a sensitivity analysis to show that possible variations on Overall Score was not influenced by sociodemographic data. The Research Ethics Committee of the Federal University of Mato Grosso do Sul approved this study (CAAE 58735316.4.0000.0021). Results A total of 825 PHC users from 29 municipalities in the State of Mato Grosso do Sul participated in the study. Regarding the sociodemographic profile of the participants, female users were predominant, in the age groups of 18 to 34 years, self-declared whites and Browns, with an elementary school and above ten years resided in the area assigned to the health units, as shown in Table 1 . Table 1 Descriptive characteristics of all users, Mato Grosso do Sul State, Brazil (n = 825). Socio-demographic variables n % 95% CI Gender Female 686 83.2 80.4 85.5 Male 139 16.8 14.4 19.6 Self-Declared Race Whites 299 36.2 33.0 39.6 Browns 335 40.6 37.7 44.0 Blacks 45 5.5 4.1 7.2 Indigenous 7 0.8 0.4 1.8 Yellow 3 0.4 0.1 1.1 Missing 136 16.5 14.1 19.2 Income up to 1 MW 246 29.8 26.8 33.0 between 1 and 2 MW 172 20.8 18.2 23.8 between 2 and 3 MW 53 6.4 4.9 8.3 between 3 and 5 MW 17 2.1 1.3 3.3 between 5 and 8 MW 1 0.1 0.01 0.8 up to 8 MW 1 0.1 0.01 0.8 do not know 194 23.5 20.7 26.5 Missing 141 17.1 14.7 19.8 Schooling illiterate 46 5.6 4.2 7.4 1–4 years 325 39.4 36.1 42.8 4–8 years 249 30.2 27.1 33.4 > 8 years 63 7.6 6.0 9.7 Post-graduation 7 0.8 0.4 1.8 Missing 135 16.4 14.0 19.1 Time of residence in the city Up to 10 years 245 29.8 26.7 32.9 above ten years 433 52.6 49.0 55.9 Missing 147 17.9 15.4 20.6 Age 18 a 34 244 29.6 26.6 32.8 35 a 44 142 17.2 14.8 19.9 45 a 59 194 23.5 20.7 26.5 Over 60 110 13.3 11.2 15.8 Missing 135 16.3 14.0 19.1 Macro region Campo Grande 423 51.3 47.9 54.7 Dourados 276 33.5 30.3 36.8 Três Lagoas 100 12 10.1 14.5 Corumbá 26 3.2 2.2 4.6 MW - Minimum wage Concerning the profile of the 424 professionals linked to PHC in the 29 municipalities of the State of Mato Grosso do Sul, the majority did not reside in the region attached to the health unit they operate. Furthermore, they presented a predominant age between 22 and 44 years, trained for more than ten years and predominantly nurses, as shown in Table 2. Table 2 Descriptive characteristics of health professionals in Mato Grosso do Sul State, Brazil (n=424). Varible n % 95% CI Gender Female 283 66.7 62.1 72.1 Male 77 18.2 14.8 22.1 Missing 64 15.1 12.0 20.0 Health Professional Nurses 176 41.5 36.9 46.3 Dentists 128 30.2 26.0 34.7 GP 56 13.3 10.3 16.8 Other 64 15.0 12.0 19.0 Live in the same city that works. No 19 83.7 2.9 6.9 Yes 355 4.5 79.9 87.0 Missing 50 11.8 9.0 15.2 Age 22-34 163 38.4 33.9 43.2 35-44 112 26.4 22.4 30.8 45-59 67 15.8 12.6 19.6 > 60 20 4.7 3.1 7.2 Missing 62 14.6 11.6 18.3 Time since graduation up to 10 years 170 40.6 36.0 45.3 Above ten years 190 44.8 40.1 49.6 Missing 62 14.6 11.6 18.3 Macro region Campo Grande 215 50.7 47.9 54.7 Dourados 144 34 30.3 36.8 Três Lagoas 52 12.3 10.1 14.5 Corumbá 13 3 1.8 5.2 Table 3 presents the average score of PHC attributes by macro region and by category of participants. The attribute accessibility presented low evaluation among users and professionals in the four macro-regions of the State, while professionals evaluated longitudinality with good performance (above 6.6). On the other hand, from the users' perspective, only the macro-regions of Dourados and Três Lagoas were well evaluated, reaching an average of 7.06 and 6.78, values above the minimum quality value respectively. The attribute care coordination - Integration of Care was not well evaluated by the users, with the highest average corresponding to 3.40 in the macro region of Dourados. However, the professionals had a counterpoint, with the lowest average of 7.37 in Três Lagoas. care coordination – Information System was the attribute that presented the best values among all in the expectation of both users and professionals. Table 3 Attributes comparison between macro region and contrasting users and professionals in Mato Grosso do Sul State, Brazil, 2018. Attributes Macro region Users mean (SE) p Profissionals mean (SE) p Accessibility Campo Grande 3.31 (0.08) 0.003 3.90(0.08) 0.16 Dourados 3.83 (0.09) 4.08 (0.11) Três Lagoas 4.28 (0.17) 3.88 (0.19) Corumbá 2.72 (0.20) 3.30 (0.23) Longitudinality Campo Grande 5.89 (0.10) 0.007 7.46 (0.10) 0.14 Dourados 7.06 (0.11) 7.93 (0.11) Três Lagoas 6.78 (0.23) 8.11 (0.17) Corumbá 5.91 (0.28) 7.49 (0.30) Care coordination – Integration of Care Campo Grande 2.51(0.17) < 0.001 7.42 (0.12) 0.30 Dourados 3.40 (0.25) 7.66 (0.14) Três Lagoas 3.15 (0.37) 7.37 (0.26) Corumbá 0.65 (0.45) 7.39 (0.36) Care coordination - health systems Campo Grande 6.51 (0.11) 0.001 8.22 (0.12) 0.30 Dourados 7.72 (0.12) 8.71 (0.12) Três Lagoas 6.28 (0.22) 8.78 (0.22) Corumbá 6.50 (0.27) 8.37 (0.36) Comprehensiveness – Available services Campo Grande 5.57 (0.07) 0.04 7.12 (0.09) 0.40 Dourados 5.91 (0.08) 7.25 (0.12) Três Lagoas 5.41 (0.16) 6.64 (0.23) Corumbá 6.26 (0.20) 7.09 (0.41) Comprehensiveness – Executed Services Campo Grande 3.74(0.12) 0.02 6.55 (0.15) 0.69 Dourados 4.64 (0.13) 6.68 (0.19) Três Lagoas 4.31 (0.27) 6.91 (0.31) Corumbá 3.27 (0.45) 6.29 (0.66) Family Orientation Campo Grande 4.72 (0.15) 0.003 8.58 (0.12) 0.92 Dourados 6.26 (0.18) 8.51 (0.17) Três Lagoas 5.07 (0.33) 8.71 (0.27) Corumbá 6.58 (0.34) 8.46 (0.66) People Orientation Campo Grande 4.40 (0.12) < 0.001 7.00 (0.13) 0.89 Dourados 4.44 (0.13) 7.12 (0.17) Três Lagoas 5.34 (0.29) 7.01 (0.34) Corumbá 3.11 (0.28) 6.75 (0.41) Overall Score Campo Grande 5.00 (0.07) 0.001 7.03 (0.17) 0.22 Dourados 5.85 (0.08) 7.24 (0.08) Três Lagoas 5.41 (0.14) 7.17 (0.17) Corumbá 4.65 (0.15) 6.89 (0.28) SE- Standard Error The results referring to the attributes people- and family-centered (family orientation) health care differed between the participants. The scores were higher for professionals in all macro-regions than users (Table 4). The average score ranged from 4.72 in the macro region of Campo Grande to 6.58 in the region of Corumbá in terms of family orientation. The highest average score related to people orientation was equivalent to the Três Lagoas macro region with 5.34. There were significant differences in all analysed attributes between professional and user´s views, being the views about user under the minimum quality value of 6.6. Table 4 Distribution of scores under Professionals and users in Mato Grosso do Sul (n=1249). Atributo Category Média DP IC(95%) p Accessibility Professionals 3.94 1.31 3.81-4.06 <0.001 Users 3.58 1.66 3.46-3.69 Longitudinality Professionals 7.70 1.42 7.56-7.83 <0.001 Users 6.39 2.20 6.24-6.54 Coordination - integration of care Professionals 7.49 1.78 7.32-7.66 <0.001 Users 2.82 3.81 6.24-6.54 Coordination - health systens Professionals 8.46 1.71 8.30- 8.63 <0.001 Users 6.89 2.30 6.73-7.05 Integrality - Disposable services Professionals 7.10 1.49 6.96-7.24 <0.001 Users 5.69 1.52 5.59-5.79 Integrality - Presting services Profissionais 6.63 2.26 6.41-6.84 <0.001 Users 4.10 2.53 3.92-4.27 Family Orientation Professionals 8.57 1.96 8.38-8.75 <0.001 Users 5.33 3.24 5.11-5.56 Community Orientation Profissionais 7.03 2.09 6.83-7.23 <0.001 Users 4.48 2.51 4.31-4.66 General Score Professionals 7.11 1.05 7.01-7.21 0.05). Discussion This study highlighted two critical findings. The first was the difference in perception between users and professionals in all analyzed attributes, with worse evaluations for all attributes among users, not reaching the minimum of 6.6. Second, there were macro-regional differences, only from users' perspective, in all attributes analysed in the State of Mato Grosso do Sul. The PHC acts as a coordinator of care for the population to have population benefits 1 . The present research results showed significant differences in the evaluations of PHC attributes between users and professionals. We observed a weak health services orientation evaluated in the perspective of the experiences and answers of the users and a strong orientation in the point of view of the professionals. These data confirm the results of previous studies that used the PCAT-Brazil 20 , 21 , 22 , 23 , 24 . The overestimated perception from professionals regarding the evaluation of the service is favourable. Nevertheless, the confrontation of ideas between professionals and users shows whether this is confirmed or not.The highest scores best evaluated by both group participants converge to the attribute care coordination - Information System, corroborating the results of other study 24 . This fact becomes relevant because, without coordination, the potential of longitudinality would decrease, it would compromise comprehensiveness, and the first contact would be essentially administrative. Coordination is defined as a state of harmony resulting from a joint effort. Therefore, it expresses its essence: the availability of information about previous problems and services and the recognition of this for the service and current needs 25 , 26 . In this sense, macroregional differences were observed in the evaluations of PHC coverage in the State of Mato Grosso do Sul, mainly from the users' perspective. The macro-regions of Dourados and Três Lagoas were better evaluated. On the other hand, the macro region of Corumbá had the worst evaluation. Different realities, permeated by socioeconomic historicity issues that imply different demands and relationships in user-centred care 27 , may have influenced the perceptions and experiences of users in this macro region. Comparing our results to the major national epidemiological survey conducted in Brazil (The National Health Survey in 2019) that used the PCAT-Brazil 28 , they found the overall score of 5.8[5.6-6.0] to Mato Grosso do Sul State. Our present findings have showed the overall score of 5.3 [IC95% 5.2–5.4] 28 . A score ≥ 6.6 is considered by the methodology of the PCAT instrument as a minimum quality value to assess primary care services from the adult user’s perspective and in both surveys this general quality value was not reached, in both surveys, confirming representativeness of our study design to the State and that there is macro-regional differences that need to be addressed. It was not seen under professionals views, that showed values above the minimum of 6.6. This study has strengths and limitations; the first is related to the fact that the instrument does not assess the final result but the process through cross-sectional data that does not infer causality. As potential, we highlight the broad scope of the research, being representative in the four health macro-regions and all microregions. To the authors' knowledge, it is the largest state survey in Mato Grosso do Sul using the full version of the PCAT-Brazil for professionals and users. The instrument used is objective, easy to apply, and presents greater possibilities for comparison since it was evaluated and applied worldwide. In addition, the tool allows the evaluation of the attributes separately, even being related to each other in the health service practice. It is worth emphasizing the importance of these attributes positively and concretely, as it supports the evaluation and investigation strategies of health systems based on and defined in a service-oriented towards PHC 29 as the degree of orientation to PHC increased the mental component score of quality of life 30 . Another strength of the study concerns the relationship of inclusion of professionals and users of the same Health Units in the research; most of the studies developed until then were carried out with professionals or users. Finally, it is concluded that there is a need to improve the development of PHC in the State, especially the attributes of accessibility and comprehensiveness of the services provided. In addition, it is necessary to strengthen PHC care networks in the State, mainly taking into account the users' perspective. Declarations Ethics approval and consent to participate The Brazilian Committee approved the survey protocol on Ethics in Human Research (The Research Ethics Committee of the Federal University of Mato Grosso do Sul approved this study (CAAE 58735316.4.0000.0021). Informed consent was obtained from all subjects and from legal guardian of illiterate participants. All methods were carried out in accordance with relevant guidelines and regulations. Consent for publication ‘Not Applicable’ Availability of data and materials The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Competing interests The authors declare no conflict of interest. Funding This study was partially financed by the Fiocruz/Mato Grosso do Sul and Federal University of Mato Grosso do Sul Authors' contributions RAB contributed to the conception design, performed all statistical analyses data interpretation, drafted and critically revised the manuscript. HQNCL contributed to the conception, design, data interpretation drafted and critically revised the manuscript. EJZ contributed to the conception, design, data interpretation drafted and critically revised the manuscript. ADC contributed to the conception, design, data interpretation drafted and critically revised the manuscript. MLMS contributed to the conception, design, data interpretation drafted and critically revised the manuscript. Acknowledgements This study was partially financed by the Federal University of Mato Grosso do Sul (UFMS) and by Fiocruz, MAto Grosso do Sul References Starfield B, Shi L, Macinko J. Contribution of Primary Care to Health Systems and Health. 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Araújo RL, Mendonça AVM, Sousa MF Perception of users and health professionals in the Federal District: the attributes of primary care. Saúde Debate. 2015; 39(105): 387-399. Carneiro, MDSM; Silva, MGCD; Pinto, FJM; Melo, DMS; Gomes, JM. Assessment of the coordination attribute in Primary Health Care: application of the PCATool to professionals and users. Saúde em Debate. 2014, 38: 279-295. Starfield, B. Atenção Primária: equilíbrio entre necessidades de saúde, serviços e tecnologia. Brasília: UNESCO, Ministério da Saúde, 2002. Brazil. Ministry of Health. Secretariat of Primary Health Care. Department of Family Health. Primary Health Care Assessment Instrument Manual: PCATool-Brasil – 2020 [electronic resource] / Ministry of Health, Primary Health Care Secretariat. – Brasília: Ministry of Health, 2020. Pinto LF, Quesada LA, D'Avila OP, Hauser L, Gonçalves MR, Harzheim E. Primary Care Assessment Tool: regional differences based on the National Health Survey from Instituto Brasileiro de Geografia e Estatística. Cien Saude Colet. 2021;26(9):3965-3979. Brazil. Ministry of Health. Department of Health Care. Department of Health Surveillance. National Policy Guide for Primary Care – Module 1: Integration of Primary Care and Health Surveillance [electronic resource] / Ministry of Health, Department of Health Care, Department of Health Health Surveillance. – Brasília: Ministry of Health, 2018. Honorato dos Santos de Carvalho VC, Rossato SL, Fuchs FD, Harzheim E, Fuchs SC. Assessment of primary health care received by the elderly and health related quality of life: a cross-sectional study. BMC Public Health. 2013 Jun 24;13:605. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 11 Apr, 2022 Reviews received at journal 31 Mar, 2022 Reviewers agreed at journal 29 Mar, 2022 Reviewers invited by journal 29 Mar, 2022 Editor assigned by journal 21 Mar, 2022 Editor invited by journal 08 Mar, 2022 Submission checks completed at journal 07 Mar, 2022 First submitted to journal 03 Mar, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1415480","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":88879278,"identity":"cf616342-fa4d-4d8b-b1bb-dfbe33078d5d","order_by":0,"name":"Rafael Aiello Bomfim","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIie2QsYoCMRCGJwTWZmHbVPoKEUE48E2uSR4gXHFNCpVUa+MDWIi+wtlsPRLINYIPcMXFN9jutjS7gtis4bqDy1cMP8N8ZCYAicRfhAJB3wUE8LoN1MQUQNGGLFRxajskosCjIss2RZRiRRGFhreipBcvd4vXYhWURle9CrOZwLDPy8ZlEy6rT7WxxJD16av/GZtzDPtw+DZTJiunTFAoKfuVkS3qThm5wU8jt07tYwq3OXQKd/kUpJmrj5gythkPtzA+dvk7Ew7VISjHZ7cMz/biaz3jQzc41PV8qXZne/SNfnL+DXb/ja5ibP6R5W+GE4lE4p9wBX6cXnnRqOfSAAAAAElFTkSuQmCC","orcid":"","institution":"Federal University of Mato Grosso do Sul","correspondingAuthor":true,"prefix":"","firstName":"Rafael","middleName":"Aiello","lastName":"Bomfim","suffix":""},{"id":88879279,"identity":"6509032b-4d99-45e7-a910-8bcf185b0713","order_by":1,"name":"Hazelelponi Leite","email":"","orcid":"","institution":"Federal University of Mato Grosso do Sul","correspondingAuthor":false,"prefix":"","firstName":"Hazelelponi","middleName":"","lastName":"Leite","suffix":""},{"id":88879280,"identity":"826ede57-4555-4ecf-b788-d4b17d944ad9","order_by":2,"name":"Edilson José Zafalon","email":"","orcid":"","institution":"Federal University of Mato Grosso do Sul","correspondingAuthor":false,"prefix":"","firstName":"Edilson","middleName":"José","lastName":"Zafalon","suffix":""},{"id":88879281,"identity":"5a0bee39-5bd2-4cce-9dc4-af9f18883ad4","order_by":3,"name":"Alessandro Diogo De-Carli","email":"","orcid":"","institution":"Federal University of Mato Grosso do Sul","correspondingAuthor":false,"prefix":"","firstName":"Alessandro","middleName":"Diogo","lastName":"De-Carli","suffix":""},{"id":88879282,"identity":"64b6a312-7f99-41de-b01e-b80c43befe8e","order_by":4,"name":"Mara Lisiane Moraes Santos","email":"","orcid":"","institution":"Federal University of Mato Grosso do Sul","correspondingAuthor":false,"prefix":"","firstName":"Mara","middleName":"Lisiane Moraes","lastName":"Santos","suffix":""}],"badges":[],"createdAt":"2022-03-03 12:29:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1415480/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1415480/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":19088486,"identity":"07b09c23-3cd3-49cd-bcdd-03b06e9bb86f","added_by":"auto","created_at":"2022-03-10 18:26:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":516343,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1415480/v1/a1a0b0d0-644f-42ed-a01c-51565e2391cf.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eAttributes of Primary Health Care in Mato Grosso Do Sul State: PCAT-Brazil Paired for Users and Health Professionals, 2018\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn Brazil, Primary Health Care (PHC), through the work of Family Health teams (eSF), corresponds to the structuring and coordinating axis of the Unified Health System (SUS), being the main access route for users to health services. SUS services, whose actions must be centred on the individual, meeting their health needs\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Shreds of evidence indicate the positive impact of PHC on the primary health indicators in the country after the implementation of the Family Health Strategy (ESF), mainly due to the significant increase in the number of eSF, implying greater coverage of this service in Brazilian territory\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHowever, the country still faces difficulties in implementing PHC and in the quality and effectiveness of the services offered\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. One of the main barriers to implementing comprehensive PHC in Brazil is the qualification in the training of health workers, as there is a misalignment between health training and the principles of SUS and PHC\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. The organization and orientation of services by PHC attributes promote better indicators, greater user satisfaction, equity, lower costs, and, consequently, positively impact the health of the population\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. The evaluation of operational quality in PHC is linked to the presence and extent of four essential attributes and two derived ones. The essential ones correspond to attention to the first contact (accessibility), longitudinality, comprehensiveness and care coordination, and the derived attributes consist of people- and family-centered (family orientation) health care and cultural competence\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThus, it is important to use strategies to consolidate universal and equitable access within the scope of the SUS through tools that promote evaluation and monitoring of the performance of PHC teams\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. The evaluation process also makes it possible to unveil the experiences lived by both users and professionals that can reflect on other levels of care services in the health care network and other experiences articulated with the rest of the system\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Given the different organizational arrangements and specific aspects of care offerings in health services existing in Brazil, the search for performance evaluation, knowledge of the opinions of professionals who work in it, as well as information on users' experiences, can evidence the actual effectiveness of PHC and assist in the definition of public policies\u003csup\u003e\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e The objective of this study was to verify the quality of adult health care in PHC services from the perspective of users and professionals in the four health macro-regions of the State of Mato Grosso do Sul, using the PCAT-Brazil instrument.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis study was a cross-sectional research carried out from August to December 2018 in Mato Grosso do Sul State. The municipalities participating in the study included the 11 health microregions of Mato Grosso do Sul following the Regional Master Plan(RMP), which divided the State into four macro-regions: 1) Campo Grande, Dourados, Tr\u0026ecirc;s Lagoas and Corumb\u0026aacute;.\u003c/p\u003e\n\u003cdiv class=\"Section2\" id=\"Sec3\"\u003e\n \u003ch2\u003eSample size calculation\u003c/h2\u003e\n \u003cp\u003eThe sample size calculation was performed on the representativeness of the macro-regions using the STATA software (College Station, TX, USA). The parameter used was Alpha of 5% and power of 80%, assuming 10% of losses, totalling 800 users and 400 PHC professionals. The participating municipalities were defined by random selection, including all the microregions. Therefore, we respect at least four health units in each municipality and four users per health unit selected to obtain an overview of the perception of users and professionals (ratio 2:1) of the SUS in the State of Mato Grosso do Sul.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec4\"\u003e\n \u003ch2\u003eCalibration of examiners\u003c/h2\u003e\n \u003cp\u003eData collection was performed by interviewers who received theoretical and practical qualifications (24 hours) and underwent inter-and intra-examiner calibration, resulting in a Kappa index equal to or greater than 0.87. First, the interviewers got to know the instrument to become familiar with the characteristics of the study and facilitate the application and completion of the questionnaire. Then, the items and questions of the Primary Care Assessment Tool (PCAT-Brazil), validated in Brazil\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, were studied and discussed to give fluency to the execution. The possible doubts that arose were resolved in time to ensure the reliability of the data. This instrument was chosen because it has already been used in several countries, which gives it the characteristic of international comparability\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec5\"\u003e\n \u003ch2\u003eData collection\u003c/h2\u003e\n \u003cp\u003eIn this study, the quality of care was verified using the PCAT-Brazil instrument for adult users over 18 years of age and professionals\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. This instrument measures the presence and extent of essential and derived attributes of PHC and thus infers strong or weak orientation for PHC of the evaluated service\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. In addition, the municipal health departments indicated the Primary Health Units (PHU) and those that accepted and agreed to participate in the research was included.\u003c/p\u003e\n \u003cp\u003eThe sample of health professionals consisted of those in the eSF in the selected units. In addition, professionals should assist adult users, fulfil a workload of at least 20 hours per week and work at the health unit for at least one year. The sample of professionals was determined by random selection, as those who worked in the health units indicated by the municipal secretariats were interviewed. After the inclusion of professionals, we included only users attended by the included professional. The interviewers collected data from the users at the participants\u0026apos; homes. These were randomly selected from a list also provided by the municipal health departments, containing the families assigned to each area of activity of the ESF participating in the study. Users should have resided in the territory for at least one year for the inclusion criteria.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec6\"\u003e\n \u003ch2\u003ePCAT-Brazil score\u003c/h2\u003e\n \u003cp\u003eThe scores for each attribute or component were calculated by the simple arithmetic mean of the response values of the items that make up each attribute or its component. The scores were calculated and transformed into a scale from 0 to 10, according to the PHC Assessment Instrument Manual (PCAT-Brazil)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eIn the adult version, answered by users, the essential score is measured by the sum of the average score of the components that belong to the essential attributes (plus Affiliation Degree) divided by the number of components. The overall score is measured by the average score of components belonging to essential attributes plus components belonging to derived attributes (plus Affiliation Degree), divided by the total number of components. More information on calculation scores could be seen elsewhere\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec7\"\u003e\n \u003ch2\u003eOutcome Variable\u003c/h2\u003e\n \u003cp\u003eThe score for each essential and derived PHC attribute was the dependent variable. A score\u0026thinsp;\u0026ge;\u0026thinsp;6.6 is considered by the methodology of the PCAT instrument as a minimum quality value to assess primary care services from the adult user\u0026rsquo;s perspective and in both surveys this general quality value\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec8\"\u003e\n \u003ch2\u003eMain exposures variables\u003c/h2\u003e\n \u003cp\u003eThe macro region (Campo Grande, Dourados, Tr\u0026ecirc;s Lagoas and Corumb\u0026aacute;) and the professional/users data were the main exposures variables.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec9\"\u003e\n \u003ch2\u003eDescriptive variables\u003c/h2\u003e\n \u003cp\u003eDescriptive data from users like gender, income, education, self-reported race, according to the Brazilian IBGE, time living in the region, sex and age group were reported. Furthermore, descriptive data from professionals like the category of the health professional, gender, and if they lived and worked in the same city and time since graduation was described.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec10\"\u003e\n \u003ch2\u003eStatistical analysis\u003c/h2\u003e\n \u003cp\u003eThe macro-regions were compared between APS attributes and between professionals and users in the State of Mato Grosso do Sul. To compare the averages between the macro-regions, analysis of variance (ANOVA) with test Tukey (post-hoc) to verify associations and for professionals and users, paired Student\u0026apos;s t-test was used (the professional was paired with the users). A significance level of 5% was considered, and Data Analysis and Statistical Software (STATA) v.14 (College Station, TX, USA) was used. Chi-squared tests between each sociodemographic characteristics of participants and the four macro-regions was done as a sensitivity analysis to show that possible variations on Overall Score was not influenced by sociodemographic data.\u003c/p\u003e\n \u003cp\u003eThe Research Ethics Committee of the Federal University of Mato Grosso do Sul approved this study (CAAE 58735316.4.0000.0021).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 825 PHC users from 29 municipalities in the State of Mato Grosso do Sul participated in the study. Regarding the sociodemographic profile of the participants, female users were predominant, in the age groups of 18 to 34 years, self-declared whites and Browns, with an elementary school and above ten years resided in the area assigned to the health units, as shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDescriptive characteristics of all users, Mato Grosso do Sul State, Brazil (n\u0026thinsp;=\u0026thinsp;825).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eSocio-demographic variables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e686\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e83.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e80.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e16.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e14.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelf-Declared Race\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eWhites\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e299\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e36.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e33.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eBrowns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e40.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e37.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eBlacks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eIndigenous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eYellow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e16.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e14.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eup to 1 MW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e29.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e26.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ebetween 1 and 2 MW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e20.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e18.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ebetween 2 and 3 MW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ebetween 3 and 5 MW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ebetween 5 and 8 MW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eup to 8 MW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003edo not know\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e23.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e20.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e17.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e14.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eSchooling\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eilliterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e1\u0026ndash;4 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e39.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e36.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e4\u0026ndash;8 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e249\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e30.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e27.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;8 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ePost-graduation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e16.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e14.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime of residence in the city\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eUp to 10 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e29.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e26.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eabove ten years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e433\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e52.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e49.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e17.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e15.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e18 a 34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e29.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e26.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e35 a 44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e17.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e14.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e45 a 59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e23.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e20.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eOver 60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e13.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e11.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e16.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e14.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eMacro region\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eCampo Grande\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e423\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e51.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e47.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eDourados\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e33.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e30.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eTr\u0026ecirc;s Lagoas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e10.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eCorumb\u0026aacute;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" align=\"left\" \u003e\n \u003cp\u003eMW - Minimum wage\u003c/p\u003e\n \u003c/td\u003e\n \n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003eConcerning the profile of the 424 professionals linked to PHC in the 29 municipalities of the State of Mato Grosso do Sul, the majority did not reside in the region attached to the health unit they operate. Furthermore, they presented a predominant age between 22 and 44 years, trained for more than ten years and predominantly nurses, as shown in Table\u0026nbsp;2.\u003c/p\u003e\n\u003ctable border=\"1\" width=\"0\"\u003e\n \u003ccaption\u003e\n \u003cp\u003eTable 2\u003c/p\u003e\n \u003cp\u003eDescriptive characteristics of health professionals in Mato Grosso do Sul State, Brazil (n=424).\u003c/p\u003e\n \u003c/caption\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003e\u003cstrong\u003eVarible\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"73\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd width=\"37\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd width=\"37\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd width=\"37\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e283\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e66.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e62.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e72.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e18.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e14.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e22.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e15.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e12.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" width=\"457\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealth Professional\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd width=\"37\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd width=\"37\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003eNurses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e41.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e36.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e46.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003eDentists\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e30.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e26.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e34.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003eGP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e13.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e10.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e16.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e15.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e12.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e19.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" width=\"457\"\u003e\n \u003cp\u003e\u003cstrong\u003eLive in the same city that works.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd width=\"37\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd width=\"37\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e83.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e6.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e79.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e87.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e9.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e15.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd width=\"37\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd width=\"37\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd width=\"37\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003e22-34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e38.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e33.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e43.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003e35-44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e26.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e22.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e30.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003e45-59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e15.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e12.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e19.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003e\u0026gt; 60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e14.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e11.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e18.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" width=\"457\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime since graduation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd width=\"37\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd width=\"37\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003eup to\u0026nbsp; 10 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e40.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e36.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e45.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003eAbove ten years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e44.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e40.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e49.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e14.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e11.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e18.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003e\u003cstrong\u003eMacro region\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd width=\"37\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd width=\"37\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd width=\"37\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003eCampo Grande\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e50.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e47.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e54.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003eDourados\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e30.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e36.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003eTr\u0026ecirc;s Lagoas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e12.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e10.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e14.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"421\"\u003e\n \u003cp\u003eCorumb\u0026aacute;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37\"\u003e\n \u003cp\u003e5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e presents the average score of PHC attributes by macro region and by category of participants. The attribute accessibility presented low evaluation among users and professionals in the four macro-regions of the State, while professionals evaluated longitudinality with good performance (above 6.6). On the other hand, from the users\u0026apos; perspective, only the macro-regions of Dourados and Tr\u0026ecirc;s Lagoas were well evaluated, reaching an average of 7.06 and 6.78, values above the minimum quality value respectively. The attribute care coordination - Integration of Care was not well evaluated by the users, with the highest average corresponding to 3.40 in the macro region of Dourados. However, the professionals had a counterpoint, with the lowest average of 7.37 in Tr\u0026ecirc;s Lagoas. care coordination \u0026ndash; Information System was the attribute that presented the best values among all in the expectation of both users and professionals.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAttributes comparison between macro region and contrasting users and professionals in Mato Grosso do Sul State, Brazil, 2018.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAttributes\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMacro region\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUsers mean (SE)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eProfissionals mean (SE)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccessibility\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCampo Grande\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.31 (0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.90(0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDourados\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.83 (0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.08 (0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTr\u0026ecirc;s Lagoas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.28 (0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.88 (0.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCorumb\u0026aacute;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.72 (0.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.30 (0.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eLongitudinality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCampo Grande\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.89 (0.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.46 (0.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDourados\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.06 (0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.93 (0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTr\u0026ecirc;s Lagoas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.78 (0.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.11 (0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCorumb\u0026aacute;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.91 (0.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.49 (0.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eCare coordination \u0026ndash; Integration of Care\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCampo Grande\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.51(0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.42 (0.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDourados\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.40 (0.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.66 (0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTr\u0026ecirc;s Lagoas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.15 (0.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.37 (0.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCorumb\u0026aacute;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.65 (0.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.39 (0.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eCare coordination - health systems\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCampo Grande\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.51 (0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.22 (0.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDourados\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.72 (0.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.71 (0.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTr\u0026ecirc;s Lagoas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.28 (0.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.78 (0.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCorumb\u0026aacute;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.50 (0.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.37 (0.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eComprehensiveness \u0026ndash; Available services\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCampo Grande\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.57 (0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.04\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.12 (0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDourados\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.91 (0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.25 (0.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTr\u0026ecirc;s Lagoas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.41 (0.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.64 (0.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCorumb\u0026aacute;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.26 (0.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.09 (0.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eComprehensiveness \u0026ndash; Executed Services\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCampo Grande\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.74(0.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.55 (0.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDourados\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.64 (0.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.68 (0.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTr\u0026ecirc;s Lagoas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.31 (0.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.91 (0.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCorumb\u0026aacute;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.27 (0.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.29 (0.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamily Orientation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCampo Grande\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.72 (0.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.58 (0.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDourados\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.26 (0.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.51 (0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTr\u0026ecirc;s Lagoas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.07 (0.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.71 (0.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCorumb\u0026aacute;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.58 (0.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.46 (0.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003ePeople Orientation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCampo Grande\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.40 (0.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.00 (0.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDourados\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.44 (0.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.12 (0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTr\u0026ecirc;s Lagoas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.34 (0.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.01 (0.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCorumb\u0026aacute;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.11 (0.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.75 (0.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall Score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCampo Grande\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.00 (0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.03 (0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDourados\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.85 (0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.24 (0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTr\u0026ecirc;s Lagoas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.41 (0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.17 (0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCorumb\u0026aacute;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.65 (0.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.89 (0.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eSE- Standard Error\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003eThe results referring to the attributes people- and family-centered (family orientation) health care differed between the participants. The scores were higher for professionals in all macro-regions than users (Table\u0026nbsp;4). The average score ranged from 4.72 in the macro region of Campo Grande to 6.58 in the region of Corumb\u0026aacute; in terms of family orientation. The highest average score related to people orientation was equivalent to the Tr\u0026ecirc;s Lagoas macro region with 5.34. There were significant differences in all analysed attributes between professional and user\u0026acute;s views, being the views about user under the minimum quality value of 6.6.\u003c/p\u003e\n\u003ctable border=\"1\" width=\"0\"\u003e\n \u003ccaption\u003e\n \u003cp\u003eTable 4\u003c/p\u003e\n \u003cp\u003eDistribution of scores under Professionals and users in Mato Grosso do Sul (n=1249).\u0026nbsp;\u003c/p\u003e\n \u003c/caption\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"105\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Atributo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"122\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76\"\u003e\n \u003cp\u003e\u003cstrong\u003eM\u0026eacute;dia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85\"\u003e\n \u003cp\u003e\u003cstrong\u003eDP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"114\"\u003e\n \u003cp\u003e\u003cstrong\u003eIC(95%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"47\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"105\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccessibility\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"122\"\u003e\n \u003cp\u003eProfessionals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76\"\u003e\n \u003cp\u003e3.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85\"\u003e\n \u003cp\u003e1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"114\"\u003e\n \u003cp\u003e3.81-4.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"47\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"122\"\u003e\n \u003cp\u003eUsers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76\"\u003e\n \u003cp\u003e3.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85\"\u003e\n \u003cp\u003e1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"114\"\u003e\n \u003cp\u003e3.46-3.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"105\"\u003e\n \u003cp\u003e\u003cstrong\u003eLongitudinality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"122\"\u003e\n \u003cp\u003eProfessionals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76\"\u003e\n \u003cp\u003e7.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85\"\u003e\n \u003cp\u003e1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"114\"\u003e\n \u003cp\u003e7.56-7.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"47\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"122\"\u003e\n \u003cp\u003eUsers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76\"\u003e\n \u003cp\u003e6.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85\"\u003e\n \u003cp\u003e2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"114\"\u003e\n \u003cp\u003e6.24-6.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"105\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoordination - integration of care\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"122\"\u003e\n \u003cp\u003eProfessionals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76\"\u003e\n \u003cp\u003e7.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85\"\u003e\n \u003cp\u003e1.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"114\"\u003e\n \u003cp\u003e7.32-7.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"47\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"122\"\u003e\n \u003cp\u003eUsers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76\"\u003e\n \u003cp\u003e2.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85\"\u003e\n \u003cp\u003e3.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"114\"\u003e\n \u003cp\u003e6.24-6.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"105\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoordination - health systens\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"122\"\u003e\n \u003cp\u003eProfessionals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76\"\u003e\n \u003cp\u003e8.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85\"\u003e\n \u003cp\u003e1.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"114\"\u003e\n \u003cp\u003e8.30- 8.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"47\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"122\"\u003e\n \u003cp\u003eUsers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76\"\u003e\n \u003cp\u003e6.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85\"\u003e\n \u003cp\u003e2.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"114\"\u003e\n \u003cp\u003e6.73-7.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"105\"\u003e\n \u003cp\u003eIntegrality\u003cstrong\u003e\u0026nbsp;- Disposable services\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"122\"\u003e\n \u003cp\u003eProfessionals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76\"\u003e\n \u003cp\u003e7.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85\"\u003e\n \u003cp\u003e1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"114\"\u003e\n \u003cp\u003e6.96-7.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"47\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"122\"\u003e\n \u003cp\u003eUsers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76\"\u003e\n \u003cp\u003e5.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85\"\u003e\n \u003cp\u003e1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"114\"\u003e\n \u003cp\u003e5.59-5.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"105\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntegrality - Presting services\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"122\"\u003e\n \u003cp\u003eProfissionais\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76\"\u003e\n \u003cp\u003e6.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85\"\u003e\n \u003cp\u003e2.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"114\"\u003e\n \u003cp\u003e6.41-6.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"47\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"122\"\u003e\n \u003cp\u003eUsers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76\"\u003e\n \u003cp\u003e4.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85\"\u003e\n \u003cp\u003e2.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"114\"\u003e\n \u003cp\u003e3.92-4.27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"105\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamily Orientation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"122\"\u003e\n \u003cp\u003eProfessionals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76\"\u003e\n \u003cp\u003e8.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85\"\u003e\n \u003cp\u003e1.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"114\"\u003e\n \u003cp\u003e8.38-8.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"47\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"122\"\u003e\n \u003cp\u003eUsers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76\"\u003e\n \u003cp\u003e5.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85\"\u003e\n \u003cp\u003e3.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"114\"\u003e\n \u003cp\u003e5.11-5.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"105\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunity Orientation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"122\"\u003e\n \u003cp\u003eProfissionais\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76\"\u003e\n \u003cp\u003e7.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85\"\u003e\n \u003cp\u003e2.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"114\"\u003e\n \u003cp\u003e6.83-7.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"47\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"122\"\u003e\n \u003cp\u003eUsers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76\"\u003e\n \u003cp\u003e4.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85\"\u003e\n \u003cp\u003e2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"114\"\u003e\n \u003cp\u003e4.31-4.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"105\"\u003e\n \u003cp\u003e\u003cstrong\u003eGeneral Score\u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"122\"\u003e\n \u003cp\u003eProfessionals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76\"\u003e\n \u003cp\u003e7.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"114\"\u003e\n \u003cp\u003e7.01-7.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"47\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"122\"\u003e\n \u003cp\u003eUsers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76\"\u003e\n \u003cp\u003e5.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85\"\u003e\n \u003cp\u003e1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"114\"\u003e\n \u003cp\u003e5.22-5.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSensitivity analysis showed no differences between any socio-demographic data and the four macroregionals in Mato Grosso do Sul State (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study highlighted two critical findings. The first was the difference in perception between users and professionals in all analyzed attributes, with worse evaluations for all attributes among users, not reaching the minimum of 6.6. Second, there were macro-regional differences, only from users' perspective, in all attributes analysed in the State of Mato Grosso do Sul.\u003c/p\u003e \u003cp\u003eThe PHC acts as a coordinator of care for the population to have population benefits\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The present research results showed significant differences in the evaluations of PHC attributes between users and professionals. We observed a weak health services orientation evaluated in the perspective of the experiences and answers of the users and a strong orientation in the point of view of the professionals. These data confirm the results of previous studies that used the PCAT-Brazil\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. The overestimated perception from professionals regarding the evaluation of the service is favourable. Nevertheless, the confrontation of ideas between professionals and users shows whether this is confirmed or not.The highest scores best evaluated by both group participants converge to the attribute care coordination - Information System, corroborating the results of other study\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. This fact becomes relevant because, without coordination, the potential of longitudinality would decrease, it would compromise comprehensiveness, and the first contact would be essentially administrative. Coordination is defined as a state of harmony resulting from a joint effort. Therefore, it expresses its essence: the availability of information about previous problems and services and the recognition of this for the service and current needs\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this sense, macroregional differences were observed in the evaluations of PHC coverage in the State of Mato Grosso do Sul, mainly from the users' perspective. The macro-regions of Dourados and Tr\u0026ecirc;s Lagoas were better evaluated. On the other hand, the macro region of Corumb\u0026aacute; had the worst evaluation. Different realities, permeated by socioeconomic historicity issues that imply different demands and relationships in user-centred care\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, may have influenced the perceptions and experiences of users in this macro region.\u003c/p\u003e \u003cp\u003eComparing our results to the major national epidemiological survey conducted in Brazil (The National Health Survey in 2019) that used the PCAT-Brazil\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, they found the overall score of 5.8[5.6-6.0] to Mato Grosso do Sul State. Our present findings have showed the overall score of 5.3 [IC95% 5.2\u0026ndash;5.4]\u003csup\u003e28\u003c/sup\u003e. A score\u0026thinsp;\u0026ge;\u0026thinsp;6.6 is considered by the methodology of the PCAT instrument as a minimum quality value to assess primary care services from the adult user\u0026rsquo;s perspective and in both surveys this general quality value was not reached, in both surveys, confirming representativeness of our study design to the State and that there is macro-regional differences that need to be addressed. It was not seen under professionals views, that showed values above the minimum of 6.6.\u003c/p\u003e \u003cp\u003eThis study has strengths and limitations; the first is related to the fact that the instrument does not assess the final result but the process through cross-sectional data that does not infer causality. As potential, we highlight the broad scope of the research, being representative in the four health macro-regions and all microregions. To the authors' knowledge, it is the largest state survey in Mato Grosso do Sul using the full version of the PCAT-Brazil for professionals and users. The instrument used is objective, easy to apply, and presents greater possibilities for comparison since it was evaluated and applied worldwide. In addition, the tool allows the evaluation of the attributes separately, even being related to each other in the health service practice. It is worth emphasizing the importance of these attributes positively and concretely, as it supports the evaluation and investigation strategies of health systems based on and defined in a service-oriented towards PHC\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e as the degree of orientation to PHC increased the mental component score of quality of life\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Another strength of the study concerns the relationship of inclusion of professionals and users of the same Health Units in the research; most of the studies developed until then were carried out with professionals or users.\u003c/p\u003e \u003cp\u003eFinally, it is concluded that there is a need to improve the development of PHC in the State, especially the attributes of accessibility and comprehensiveness of the services provided. In addition, it is necessary to strengthen PHC care networks in the State, mainly taking into account the users' perspective.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Brazilian Committee approved the survey protocol on Ethics in Human Research (The Research Ethics Committee of the Federal University of Mato Grosso do Sul approved this study (CAAE 58735316.4.0000.0021). Informed consent was obtained from all subjects and from legal guardian of illiterate participants. All methods were carried out in accordance with relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026lsquo;Not Applicable\u0026rsquo;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was partially financed by the Fiocruz/Mato Grosso do Sul and Federal University of Mato Grosso do Sul\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRAB\u0026nbsp;\u003c/strong\u003econtributed to the conception design, performed all statistical analyses data interpretation, drafted and critically revised the manuscript. \u003cstrong\u003eHQNCL\u0026nbsp;\u003c/strong\u003econtributed to the conception, design, data interpretation drafted and critically revised the manuscript. \u003cstrong\u003eEJZ\u003c/strong\u003e contributed to the conception, design, data interpretation drafted and critically revised the manuscript. \u003cstrong\u003eADC\u003c/strong\u003e contributed to the conception, design, data interpretation drafted and critically revised the manuscript. \u003cstrong\u003eMLMS\u003c/strong\u003e contributed to the conception, design, data interpretation drafted and critically revised the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was partially financed by the Federal University of Mato Grosso do Sul (UFMS) and by Fiocruz, MAto Grosso do Sul\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eStarfield B, Shi L, Macinko J. Contribution of Primary Care to Health Systems and Health. The Milbank Quarterly 2005; 83(3):457-502.\u003c/li\u003e\n \u003cli\u003eBastos ML, Menzies D, Hone T, Dehghani K, Trajman A. The impact of the Brazilian family health on selected primary care sensitive conditions: A systematic review. PLoS One. 2017; (8):e0182336.\u003c/li\u003e\n \u003cli\u003eMacinko J, Guanais FC, Souza MFM. Evaluation of the impact of the Family Health Program on infant mortality in Brazil, 1990-2002. J Epidemiol Community Health 2006; 60:13-9.\u003c/li\u003e\n \u003cli\u003edo Nascimento DDG, Moraes SHM, Santos CAST, de Souza AS, \u003cstrong\u003eBomfim RA\u003c/strong\u003e, De Carli AD, Kodjaoglanian VL, Dos Santos MLM, Zafalon EJ. Impact of continuing education on maternal and child health indicators PLoS One 2020 Jun 26;15(6):e0235258.\u003c/li\u003e\n \u003cli\u003eHone T, Saraceni V, Medina Coeli C, Trajman A, Rasella D, Millett C, Durovni B. Primary healthcare expansion and mortality in Brazil\u0026apos;s urban poor: A cohort analysis of 1.2 million adults. PLoS Med. 2020 Oct 30;17(10):e1003357.\u003c/li\u003e\n \u003cli\u003eRocha R, Soares RR. Evaluating the impact of community-based health interventions: evidence from Brazil\u0026apos;s Family Health Program. Health Econ. 2010; 19(supl): 126-58.\u003c/li\u003e\n \u003cli\u003eBrasil. Minist\u0026eacute;rio da Sa\u0026uacute;de. eGestor: Relat\u0026oacute;rio Hist\u0026oacute;rico de Coberta \u0026ndash; equipes de \u003cem\u003esa\u0026uacute;de\u003c/em\u003e da fam\u0026iacute;lia (eSF) e de equipes de Aten\u0026ccedil;\u0026atilde;o B\u0026aacute;sica (eAB) eGestor. Brasil 2020.\u003c/li\u003e\n \u003cli\u003eMoraes dos Santos ML, Zafalon EJ, Bomfim RA, Kodjaoglanian VL, Mendon\u0026ccedil;a de Moraes SH, et al. Impact of distance education on primary health care indicators in central Brazil: An ecological study with time trend analysis. PLOS ONE. 2019; 14(3): e0214485.\u003c/li\u003e\n \u003cli\u003eAfonso MPD, Shimizu HE, Merchan-Hamann E, Ramalho WM, Afonso T. Association between hospitalisation for ambulatory care-sensitive conditions and primary health care physician specialisation: a cross-sectional ecological study in Curitiba (Brazil).\u003cem\u003eBMJ Open\u003c/em\u003e 2017; 7: e015322.\u003c/li\u003e\n \u003cli\u003eGomes TN, Thuany M, Dos Santos FK, Rosemann T, Knechtle B. Physical (in)activity, and its predictors, among Brazilian adolescents: a multilevel analysis. BMC Public Health. 2022 Feb 3;22(1):219.\u003c/li\u003e\n \u003cli\u003eStarfield B. Primary care: balance between health needs, services and technology. Bras\u0026iacute;lia, DF: UNESCO Brazil; Ministry of Health; 2002\u003c/li\u003e\n \u003cli\u003eTasca R, Massuda A, Carvalho WM, Buchweitz C, Harzheim E. Recommendations to strengthen Primary health care in Brazil . Rev Panam Salud Publica. 2020; 44: e4.\u003c/li\u003e\n \u003cli\u003eMalouin RA, Starfield B, Sepulveda MJ. Evaluating the tools used to assess the medical home. Manag Care 2009; 18(6):44-8\u003c/li\u003e\n \u003cli\u003eStarfield B, Cassady C, Nanda J, Forrest CB, Berk R. Consumer Experiences and Provider Perceptions of the Quality os Primary Care: implications for de Managed Care. J Fam Pract. 1998 Mar;46(3):216-26.\u003c/li\u003e\n \u003cli\u003eHarzheim E, Oliveira MMC, Agostinho MR, Hauser L, Stein AT, Gon\u0026ccedil;alves MR et al. Valida\u0026ccedil;\u0026atilde;o do instrumento de avalia\u0026ccedil;\u0026atilde;o da aten\u0026ccedil;\u0026atilde;o prim\u0026aacute;ria \u0026agrave; sa\u0026uacute;de: PCATool-Brasil adultos. Rev Bras Med Fam Comunidade. 2013; 8(29): 274-84\u003c/li\u003e\n \u003cli\u003eD\u0026rsquo;Avila OP, Pinto LFS, Hauser L, Gon\u0026ccedil;alves MR, Harzheim E. The use of the Primary Care Assessment Tool (PCAT): an integrative review and proposed update. Cien Saude Colet. 2017 Mar;22(3):855-865. doi: 10.1590/1413-81232017223.03312016.\u003c/li\u003e\n \u003cli\u003eBrazil. Ministry of Health. Department of Health Care. Department of Primary Care. Primary health care assessment tool manual: primary care assessment tool pcatool - Brazil / Ministry of Health, Secretariat of Health Care, Department of Primary Care. \u0026ndash; Bras\u0026iacute;lia: Ministry of Health, 2010. 80 p.: il. \u0026ndash; (Series A. Standards and Technical Manuals).\u003c/li\u003e\n \u003cli\u003eCastro RCL, Knauth DR, Harzheim E, Hauser L, Duncan BB. Quality assessment of primary care by health professionals: a comparison of different types of services. Cad. Sa\u0026uacute;de P\u0026uacute;blica. 2012; 28(9): 1772-1784.\u003c/li\u003e\n \u003cli\u003eOliveira MMC, Harzheim E, Riboldi J, Duncan BB. PCATool-ADULTO-BRASIL: a reduced version. Rev Bras Med Fam Comunidade. 2013; 8(29): 256-63.\u003c/li\u003e\n \u003cli\u003eCarneiro MSM, Melo DMS, Gomes JM, Pinto FJM, Silva MG Carlos. Assessment of the coordination attribute in Primary Health Care: application of the PCATool to professionals and users. Sa\u0026uacute;de debate. 2014; 38: 279-295.\u003c/li\u003e\n \u003cli\u003eNascimento AC, Moys\u0026eacute;s ST, Werneck RI, Gabardo MCL, Moys\u0026eacute;s SJ. Assessment of public oral healthcare services in Curitiba, Brazil: a cross-sectional study using the Primary Care Assessment Tool (PCATool) BMJ Open. 2019 Jan 17;9(1):e023283.doi: 10.1136/bmjopen-2018-023283.\u003c/li\u003e\n \u003cli\u003eIba\u0026ntilde;ez N, Rocha JSY, Castro PC, Ribeiro MCSA, Forster AC, Novaes MHD, Viana ALA. Avalia\u0026ccedil;\u0026atilde;o do desempenho da aten\u0026ccedil;\u0026atilde;o b\u0026aacute;sica no Estado de S\u0026atilde;o Paulo. Cien Saude Colet. 2006; 11(3): 683-703.\u003c/li\u003e\n \u003cli\u003eStralen CJ, Belis\u0026aacute;rio S, van Stralen TBS, Lima \u0026Acirc;MD, Massote AW, Oliveira C L. Percep\u0026ccedil;\u0026atilde;o dos usu\u0026aacute;rios e profissionais de sa\u0026uacute;de sobre aten\u0026ccedil;\u0026atilde;o b\u0026aacute;sica: compara\u0026ccedil;\u0026atilde;o entre unidades com e sem sa\u0026uacute;de da fam\u0026iacute;lia na Regi\u0026atilde;o Centro-Oeste do Brasil. Cad. Sa\u0026uacute;de P\u0026uacute;blica. 2008; 24(1): 148-158.\u003c/li\u003e\n \u003cli\u003eAra\u0026uacute;jo RL, Mendon\u0026ccedil;a AVM, Sousa MF Perception of users and health professionals in the Federal District: the attributes of primary care. Sa\u0026uacute;de Debate. 2015; 39(105): 387-399.\u003c/li\u003e\n \u003cli\u003eCarneiro, MDSM; Silva, MGCD; Pinto, FJM; Melo, DMS; Gomes, JM. Assessment of the coordination attribute in Primary Health Care: application of the PCATool to professionals and users. Sa\u0026uacute;de em Debate. 2014, 38: 279-295.\u003c/li\u003e\n \u003cli\u003eStarfield, B. Aten\u0026ccedil;\u0026atilde;o Prim\u0026aacute;ria: equil\u0026iacute;brio entre necessidades de sa\u0026uacute;de, servi\u0026ccedil;os e tecnologia. Bras\u0026iacute;lia: UNESCO, Minist\u0026eacute;rio da Sa\u0026uacute;de, 2002.\u003c/li\u003e\n \u003cli\u003eBrazil. Ministry of Health. Secretariat of Primary Health Care. Department of Family Health. Primary Health Care Assessment Instrument Manual: PCATool-Brasil \u0026ndash; 2020 [electronic resource] / Ministry of Health, Primary Health Care Secretariat. \u0026ndash; Bras\u0026iacute;lia: Ministry of Health, 2020.\u003c/li\u003e\n \u003cli\u003ePinto LF, Quesada LA, D\u0026apos;Avila OP, Hauser L, Gon\u0026ccedil;alves MR, Harzheim E. Primary Care Assessment Tool: regional differences based on the National Health Survey from Instituto Brasileiro de Geografia e Estat\u0026iacute;stica. Cien Saude Colet. 2021;26(9):3965-3979.\u003c/li\u003e\n \u003cli\u003eBrazil. Ministry of Health. Department of Health Care. Department of Health Surveillance. National Policy Guide for Primary Care \u0026ndash; Module 1: Integration of Primary Care and Health Surveillance [electronic resource] / Ministry of Health, Department of Health Care, Department of Health Health Surveillance. \u0026ndash; Bras\u0026iacute;lia: Ministry of Health, 2018.\u003c/li\u003e\n \u003cli\u003eHonorato dos Santos de Carvalho VC, Rossato SL, Fuchs FD, Harzheim E, Fuchs SC. Assessment of primary health care received by the elderly and health related quality of life: a cross-sectional study. BMC Public Health. 2013 Jun 24;13:605.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Primary Health Care, Public Health, PCAT-Brazil","lastPublishedDoi":"10.21203/rs.3.rs-1415480/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1415480/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective.\u003c/strong\u003e The objective of the present study was to verify the quality of adult and older adults health care in Primary Health Care (PHC) services in the four health macro-regions of the State of Mato Grosso do Sul, 2018. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods.\u003c/strong\u003e A quantitative survey was carried out in which the municipalities participating in the study included the four macro-regions following the Director Regional Plan (DRP). In this study, the quality of care was verified using the validated version of the PCAT-Br for adult and older adults users over 18 years of age and professionals. The macro-regions were compared between PHC attributes and between professionals and users in the State of Mato Grosso do Sul. Analysis of variance (ANOVA) and paired student t-test was performed. STATA v.14.2 software (College Station, TX, USA) was used for the analyses. Sensitivity analysis was done to compare the macro-regions and socio-demographic characteristics. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults.\u003c/strong\u003e Eight hundred twenty-five users and 424 professionals participated in the study. According to users, the Accessibility attribute was the attribute with the worst performance in all macro-regions. There were significant differences between the perception of users and professionals in all attributes evaluated and regional differences between the perception of users among the four macro-regions analyzed. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions.\u003c/strong\u003e There was a difference in perception between users and professionals, and there were macro-regional differences between PHC attributes. Therefore, it is necessary to strengthen PHC care networks in the State, mainly considering the users' perspective.\u003c/p\u003e","manuscriptTitle":"Attributes of Primary Health Care in Mato Grosso Do Sul State: PCAT-Brazil Paired for Users and Health Professionals, 2018","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-03-10 18:26:10","doi":"10.21203/rs.3.rs-1415480/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2022-04-11T06:11:43+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-03-31T23:39:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"f5f8fb45-28a7-46f1-b4c7-43f37899d9f1","date":"2022-03-29T17:29:08+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-03-29T17:07:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-03-21T13:06:12+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2022-03-08T11:33:55+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-03-07T14:44:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2022-03-03T12:19:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f394ab38-6178-4fd9-939d-af0397034cd2","owner":[],"postedDate":"March 10th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2022-07-18T21:29:07+00:00","versionOfRecord":[],"versionCreatedAt":"2022-03-10 18:26:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1415480","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1415480","identity":"rs-1415480","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}