Contribution of Functional Health Facility Management Teams on functionality of Quality Improvement Teams among Primary Healthcare Facilities in Tanzania

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Mwaisengela, Patricia A. Materu, Chrisogone J. German, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5554637/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Committees for managing health facilities are thought of as tools for leveraging changes and impact to a high-quality health system. Objective This paper aims at assessing the contribution of functional Health Facility Management Teams (HFMTs) on the functionality of Health Facility Quality Improvement Teams (HFQITs) among Primary Healthcare Facilities (PHCs) in Tanzania. Methods This is a quantitative secondary data analysis using the Star Rating Assessment (SRA) data collected in the fiscal year 2017/2018. Functionality of Health Facility Management Teams (HFMTs) and Health Facility Quality Improvement Teams (HFQITs) were measured by considering availability of team members with terms of reference, conduct of regular meetings and HFQITs self-assessments of quality of healthcare. With the aid of Stata 18, we used Chi Square and Proportion Z tests for comparative analyses in regard to facility level, facility location and facility ownership. Spatial variation by region were visualized with the aid of QGIS 3.8 Firenze. Results This study involved 5,933 PHCs, majority of which were rural located (78.3%), public owned (77.2%) and dispensaries (87.7%). On average, 23.3% and 22.6% of PHCs had functional HFMTs and HFQITs respectively. More functional HFQITs were observed among PHCs with functional HFMTs (p < 0.001). Conclusions HFMTs functionality impacts on how well HFQITs work. Functional HFQITs are essential for enhancing compliance with healthcare standards that in the end improve patient satisfaction. Health Facility Management Teams Health Facility Quality Improvement Teams Primary Healthcare Facilities Healthcare Quality Standards Star Rating Assessment Tanzania Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1.0 Background Globally, healthcare governance is crucial for building resilient health systems by shaping power dynamics, strengthening coordination and ensuring availability of sustainable, adaptive, and responsive healthcare services [ 1 – 3 ]. Health facility management committees are considered mechanisms for leveraging health system change and, therefore, enhancing health system performance [ 4 ]. Having a proper health system management with skilled health managers has been shown to be an important foundation for a high-quality health system [ 5 ]. As a foundation for resilient and sustainable systems in addressing health emergencies, it is important to strengthen the management of PHC facilities [ 6 ]. For instance, in Ghana, PHC facilities that performed well in management also performed well with regard to processes of care and patient experience of care to women [ 7 ]. This supports the need for strengthening the management of PHC facilities as a foundation for improving the quality of care provided given that HFMTs have an obligation to coordinate and support development of quality improvement plans for the sake of addressing identified quality gaps in healthcare facilities contributing to PHC performance [ 8 – 10 ]. In Tanzania, health services are delivered through a decentralized system that broadly falls into three functional levels namely Local Government Authority (LGA) which is the primary level, regional (secondary level), and referral hospital (tertiary level) [ 11 ]. At the LGA level, primary healthcare services are delivered through dispensaries and health centers, with health centers acting as referral points for dispensaries. These health centers offer a wider range of services, including inpatient care. The highest tier consists of level 1 hospitals, which function as referral centers, such as council hospitals or designated council hospitals. If no government hospital is available, a service agreement may be established with a faith-based hospital [ 12 , 13 ]. At the LGA level, Council Health Management Teams (CHMTs) work as governance agencies with the primary role of coordinating the distribution, use and allocation of resources for various operationalizations including overseeing Quality Improvement (QI) initiatives and implementation of healthcare policy frameworks [ 14 , 15 ]. Just like in secondary and tertiary levels of healthcare, primary healthcare facilities have key teams namely health facility management teams (HFMTs) and Health Facility Quality Improvement Teams (HFQITs) [ 16 ]. As stated in Tanzania Quality Improvement Framework (2011–2016), one of the roles and responsibilities of Health Facility Management Teams is to oversee the quality improvement processes and Quality Improvement Team functionality [ 16 ]. Quality improvement teams (QITs) have emerged as key mechanisms by which to initiate and implement improvement efforts within healthcare organizations [ 17 ] which contributes to improved compliance with set healthcare standards [ 18 ] that ultimately impacts to better health outcomes. It is known that, one of the basic goals of any healthcare system is quality improvement that is expected to have positive effect on the well-being of clients by enhancing safety, effectiveness, patient-centeredness, timeliness, efficiency, and equity in the delivery of health services [ 19 – 21 ]. Therefore, functionality of HFMTs is expected to influence HFQITs functionality [ 16 ] which is expected to impact quality of healthcare. Despite HFMTs pivotal role, little scholarly attention is paid to its contribution to quality improvement processes and QIT functionality and therefore, little is known. Having important role to play of coordinating, implementing, monitoring and evaluating of QI activities for common quality improvement challenges that a health facility may be facing [ 16 ], it is of utmost importance that, HFMTs contribution on QITs functionality is known. As of now, there is no countrywide reliable data source that gathers information on both HFMTs and HFQITs functionality; however, in 2014, the Government of Tanzania introduced the implementation of “Big Results Now” initiative in the health sector; which resulted into the design of Star Rating Assessment (SRA) as one of its interventions aiming at improving the performance of PHC facilities [ 22 ]. In the financial year 2015/2016 Tanzania Mainland conducted a countrywide assessment of all PHC facilities and assigned a star ranging from 0 to 5 stars based on the status of quality services; and in 2017/2018, countrywide re-assessment was done [ 8 , 23 ]. The Star Rating Assessment Tool (SRT) has twelve (12) service areas, namely Legality (Licensing and Certification), Health Facility Management, Use of Facility Data for Planning and Service Improvement, Staff Performance Assessment, Organization of Services, Handling Emergencies and Referral, Client Focus, Social Accountability, Facility Infrastructure, Infection Prevention and Control (IPC), Clinical Services, and Clinical Support Services [ 23 ]. Both HFQITs and HFMTs functionality are measured as indicators in an area, namely “Health Facility Management”. This paper aims, therefore, at assessing the contribution of functional HFMTs to the functionality of HFQITs among Primary Healthcare Facilities, as evidenced by the second-round Star Rating Assessment. This was the most recent assessment that was comprehensive enough to cover all twenty-six regions of Tanzania mainland and was conducted in fiscal year 2017/2018. 2.0 Methods 2.1 Study design This study employed the analytical cross-sectional design to ascertain the implication of functional HFMTs on functionality of HFQITs in the context of second round SRA conducted during the fiscal year 2017/2018. 2.2 Setting As Fig. 1 shows, Tanzania is a lower middle-income country located in East Africa with a surface area estimated to 945,087 km 2 . According to the population and housing census (2022), Tanzania has a total population of 61,741,120, with 40,196,497 (65,1%) residing in urban areas whereas 21,544,623 (34.9) in rural [ 24 ]. Administratively, Tanzania mainland has 26 regions, 139 Districts, 184 Councils, 570 Divisions, 3,956 Wards, and 12,319 villages [ 24 ]. Primary health facilities are into three levels: district hospitals, health centers and dispensaries. As of 16th July 2023, there is a total of 6,519 local government-owned PHC of which 5,582 (85.6%) are dispensaries, 767 (11.8%) are health centers, and 170 (2.6%) are district hospitals [ 25 ]. 2.3 Study Units This paper aims to reveal the contribution of HFMTs on the functionality of HFQITs in PHC facilities in Tanzania which is located in the Eastern part of Africa with 26 administrative regions (Fig. 1 ) visited for the second assessment that was conducted in the financial year 2017/2018 where a total of 5,933 PHC facilities that account for 81.4% of visited health facilities were extracted for analysis. About 18.6% of visited PHC facilities were dropped due to having missing values to most of the indicators necessary for the functionality of both HFMTs and HFQITs. 2.4 Data Source As far as this study is concerned, data were sourced from Star Rating Assessment (SRA), which is an initiative belonging to the BRN workstream, namely Performance Management of Health Facilities. Data were collected from Star Rating Tools (SRT) for Dispensaries, Health Centers and District Hospitals and subsequently entered into the Health Management Information System (HMIS) through DHIS2 on the same day of assessment to guarantee correctness, accuracy and timeliness. Regardless of the level of service, the SRT is broken down into four domains: Domain A is for facility management and staff performance with service areas 1, 2, 3, and 4, namely legality, facility management, Health Management Information System, and staff performance and appraisal system respectively. Domain B is for service charters and social accountability with service areas 5, 6, 7, and 8, namely organization of services, emergency and referral system, client focus, and social accountability, respectively. Domain C is for safe and conducive facilities with service areas 9 and 10 namely facility infrastructure and Infection Prevention and Control (IPC) respectively and Domain D is for Quality of Care and Services with service areas 10 and 11 namely clinical services and clinical support services respectively. Within service areas, there are several indicators within which verification criteria denote quality standards that are to be met by a health facility (14). To date, three SRAs have been conducted where a baseline assessment was conducted in the fiscal year 2015/2016, the second assessment (reassessment) was conducted in the fiscal year 2017/2018, and the most recent assessment (third assessment) was conducted in the fiscal year 2021/2022 for only ten (10) regions. Therefore, the second assessment is the most recent assessment that was comprehensive enough to produce representative findings of which all twenty-six (26) regions were visited. 2.5 Data management Data were extracted from SRA data base for each health facility. The functionality of both HFQITs and HFMTs was measured as indicators in area 2, namely Health Facility Management, of which HFMTs functionality was measured by verification criteria, namely availability of the team, formal appointment of the team with terms of references, HFMTs meeting on regular schedule and quarterly meeting of HFMTs whereas QIT functionality was measured by availability of the team, regular quarterly meeting of the team with recorded meetings minutes and HFQITs conduct of self-internal assessments on quality of services using tools that meet national standards. Extracted data were transposed and manipulated in Microsoft Excel to form a single dataset. The dataset was imported to Stata IC 18 for descriptive and inferential statistical analysis. 2.6 Data Analysis Data were geospatially visualized with the aid of Quantum Geographical Information Software (QGIS) 3.16 Hannover. Comparative analysis is made regionwide for all twenty-six (26) regions of Tanzania mainland to ascertain differences in coverage of health facilities with functional HFQITs among functional and non-functional HFMTs in reference to 4 performance categories, i.e., less than 20%, between 20% to less than 40%, between 40% to less than 60% and greater than or equal to 60% assigned as poor, weak, good progress and good performance respectively [ 23 ]. The spatial regional variation documentation highlights the need to understand the broader subnational systems and context which may influence culture and effectiveness at the facility level and a health system as whole [ 7 ]. One sample proportion Z test was conducted to determine the extent to which functional HFMTs or HFQITs are significantly different from non-functional ones), two samples proportional Z test to determine differences in HFQITs functionality among functional and non-functional HFMTs with separate analyses conducted for each facility level, ownership and location, Chi-square test to determine whether there is a statistically significant difference in the percentage of functional HFQITs across all 26 regions and compare differences in HFQITs functionality across facility levels (Dispensary, Health Center and District Hospital), location (Rural and Urban) and ownership (Public or Private) for both functional and non-functional HFMTs. 2.7 Inclusion criteria As argued by Schafer (2016), missing data leads to biased results [ 26 ]. Therefore, the criteria for inclusion were all health facilities (Level 1 Hospitals, Health Centers, and dispensaries) visited during the second SRA (2017/2018), with no missing or invalid verification criteria on the functionality of both HFMTs and HFQITs from the SRA tool. 2.8 Exclusion criteria The exclusion criteria were all health facilities with any missing verification criteria regarding the functionality of both HFMTs and HFQITs from the SRA tool. 3.0 Results 3.1 Characteristics of health facilities involved in the analysis As Table 1 shows, this analysis covered 5,933 primary healthcare facilities, with the majority being dispensaries (87.7%), located in rural areas (78.3%), and publicly owned (77.2%). Of the facilities analyzed, 1,382 (23.3%) had functional Health Facility Management Teams (HFMTs), while 1,338 (22.6%) had functional Health Facility Quality Improvement Teams (HFQITs). Table 1 Characteristics of health facilities involved in the analysis Variable N (%) Functional HFMTs Functional HFQITs % 95% C. I % 95% C. I Lower Upper Lower Upper Overall 5933 (100) 23.3 22.1 24.4 22.6% 21.5 23.6 Facility Type Hospitals 80 (1.4) 47.50 36.6 58.4 41.3 30.5 52.0 Health Centers 652 (11.0) 32.20 28.6 35.8 34.7 31.0 38.3 Dispensaries 5201 (87.7) 21.80 20.7 22.9 20.7 19.6 21.8 Facility Location Urban 1285 (21.7) 27.70 25.3 30.2 27.8 25.3 30.2 Rural 4648 (78.3) 22.10 20.9 23.3 21.1 19.9 22.3 Facility Ownership Public 4578 (77.2) 23.40 22.2 24.7 22.6 21.4 23.8 Private 1355 (22.8) 22.80 20.6 25.0 22.5 20.3 24.7 3.2 Overall contribution of functional HFMT on HFQIT functionality As Fig. 2 shows, A two-sample proportional Z test conducted revealed that 13.8% (95% C.I 12.8% − 14.8%) of health facilities with non-functional HFMTs had functional HFQIT. On the other hand, 51.2% (95% C.I 48.6% − 53.9%) of health facilities with functional HFMTs had functional HFQIT. This difference is statistically significant, highlighting that functional HFMTs are significantly more likely to have functional HFQITs compared to non-functional ones (z=-29.1, p < 0.001). 3.3 Contribution of functional HFQIT on HFMT functionality by facility level Figure 3 shows that, among health facilities with non-functional HFMTs, an analysis showed significant difference in health facilities that had functional HFQITs among dispensaries, health centers and level 1 hospitals ( \(\:{Chi}^{2}\) =30.04, p < 0.001). On the other hand, compared to non-functional HFMTs, among health facilities with functional HFMTs, a smaller significant difference in health facilities that had functional HFQITs among dispensaries, health centers and level 1 hospitals was observed ( \(\:{Chi}^{2}\) =10.00, p = 0.007). This indicates that, dispensaries, health centers and level 1 hospitals differ more significantly in terms of functionality of HFQITs where HFMTs are non-functional. An analysis revealed that among hospitals, 16.7% (95% C.I 5.4% − 27.9%) of non-functional HFMTs had functional HFQIT. On the other hand, 68.4% (95% C.I 53.6% − 83.2%) of hospitals with functional HFMTs had functional HFQIT. This difference is statistically significant highlighting that, among hospitals, functional HFMTs are significantly more likely to have functional HFQITs compared to non-functional ones (z=-4.7, p < 0.001). An analysis conducted revealed among Health Centers, 23.5% (95% C.I 19.6% − 27.5%) with non-functional HFMTs had functional HFQIT. On the other hand, 58.1% (95% C.I 51.4% − 64.8%) of health centers with functional HFMTs had functional HFQIT. This difference is statistically significant, highlighting that functional HFMTs are significantly more likely to have functional HFQITs compared to non-functional ones among hospitals (z=-8.7, p < 0.001). An analysis conducted revealed among dispensaries, 12.8% (95% C.I 11.7% − 13.8%) with non-functional HFMTs had functional HFQIT. On the other hand, 49.4% (95% C.I 46.5% − 52.3%) of dispensaries with functional HFMTs had functional HFQIT. This difference is statistically significant, highlighting that, among dispensaries, functional HFMTs are significantly more likely to have functional HFQITs compared to non-functional ones (z=-26.9, p < 0.001). The Comparative analysis shows statistically significant difference in HFQITs functionality among HFMTs with functional (chi2 = 54, p = 0.05) and non-functional HFQITs (chi2 = 54, p = 0.05) 3.4 Contribution of functional HFQIT on HFMT functionality by facility location Figure 4 shows that, among health facilities with non-functional HFMTs, an analysis showed a non-significant difference in health facilities that had functional HFQITs among rural and urban-located health facilities ( \(\:{Chi}^{2}\) =3.04, p = 0.081). On the other hand, among health facilities with functional HFMTs, a significant difference in health facilities that had functional HFQITs among rural and Urban located health facilities wa observed ( \(\:{Chi}^{2}\) =13.29, p < 0.001). This indicates that, rural and urban health facilities significantly differ in health facilities with functional HFQITs where HFMTs are also functional. An analysis conducted revealed that among rural-located health facilities, 13.4% (95% C.I 12.3% − 14.5%) of health facilities with non-functional HFMTs had functional HFQIT. On the other hand, 48.3% (95% C.I 45.3% − 51.4%) of health facilities with functional HFMTs had functional HFQIT. This difference is statistically significant, highlighting that functional HFMTs are significantly more likely to have functional HFQITs compared to non-functional ones (z=-24.2, p < 0.001). Among urban-located health facilities, 15.6% (95% C.I 13.3% − 17.9%) of health facilities with non-functional HFMTs had functional HFQIT. On the other hand, 59.5% (95% C.I 54.5% − 64.6%) of health facilities with functional HFMTs had functional HFQIT. This difference is statistically significant, highlighting that functional HFMTs are significantly more likely to have functional HFQITs compared to non-functional ones (z=-15.7, p < 0.001). 3.5 Contribution of functional HFQIT on HFMT functionality by facility ownership As shown by Fig. 5 , among health facilities with non-functional HFMTs, an analysis showed non-significant difference in health facilities that had functional HFQITs among privately and public owned health facilities ( \(\:{Chi}^{2}\) =3.29, p = 0.07). On the other hand, among health facilities with functional HFMTs, a significant difference in health facilities that had functional HFQITs among privately and public owned health facilities was observed ( \(\:{Chi}^{2}\) =6.47, p = 0.011). This indicates that, private and public owned health facilities significantly differ in health facilities with functional HFQITs where HFMTs are also functional. Among public-owned health facilities, 12.1% (95% C.I 10.2% − 14.1%) of health facilities with non-functional HFMTs had functional HFQIT. On the other hand, 57.6% (95% C.I 52.1% − 63.1%) of health facilities with functional HFMTs had functional HFQIT. This difference is statistically significant, highlighting that, among public-owned health facilities, functional HFMTs are significantly more likely to have functional HFQITs compared to non-functional ones (z=-24.0, p < 0.001). Among privately owned health facilities, 14.3% (95% C.I 13.2% − 15.5%) of health facilities with non-functional HFMTs had functional HFQIT. On the other hand, 49.4% (95% C.I 46.4% − 52.4%) of health facilities with functional HFMTs had functional HFQIT. This difference is statistically significant, highlighting that functional HFMTs are significantly more likely to have functional HFQITs compared to non-functional ones (z=-16.8, p < 0.001). 3.6 Contribution of HFQIT on HFMT functionality by regions Among health facilities with non-functional HFMTs, an analysis showed non-significant difference in health facilities that had functional HFQITs among health facilities in all twenty-six regions ( \(\:{Chi}^{2}\) =162.9, p < 0.001). On the other hand, among health facilities with functional HFMTs, a significant difference in health facilities that had functional HFQITs among all regions was observed ( \(\:{Chi}^{2}\) =71.52, p < 0.001). This indicates that, regionwide, health facilities differ more significantly in health facilities with functional HFQITs where HFMTs are non-functional. A region-sorted two-sample proportion Z test conducted for all twenty-six (26) regions reveals statistically significant differences in the proportions of health facilities with functional HFQITs among health facilities with functional and non-functional HFMTs. Figure 6 indicates that among non-functional HFMTs, twenty-one (21) regions had poor coverage (less than 20%) of health facilities with functional HFQITs, while the remaining six regions had weak coverage. Neither of the regions showed good nor good progress. On the other hand, among functional HFMTs, only Katavi region showed poor coverage. Good and desirable coverage was revealed among Kilimanjaro, Geita, and Singida regions, while weak coverage was in Kigoma, Manyara, Songwe, Njombe, Ruvuma, and Lindi. All remaining sixteen (16) regions showed good progress coverage (Fig. 1 ). 4.0 Discussion This study revealed positive contribution of functional HFMTs on QITs functionality. Some other studies reveal negative effect of non-functionality of HFMTs on operationalization of QIT activities implementation [ 16 , 27 , 28 ] and therefore, improving facility management is an important consideration to improve healthcare delivery and consequently enhance patient satisfaction [ 8 , 29 ]. The disaggregated analysis conducted in this study in regard to facility level, location and ownership gives a clearer direction for targeted interventions on Primary Healthcare facilities given that HFMTs are responsible for planning, coordinating and managing the provision of health and social welfare services with a broad range of specific functions that include: ensuring the viability of HFQITs and Work Improvement Teams (WITs) [ 16 , 30 ]. Functionality of HFMTs being an influence to HFQITs functionality corresponds to another study by Kacholi et al. (2021) which identifies one of the major factors factor that impedes Quality Improvement Teams’ effectiveness being poor Health Facility Management [ 31 ], therefore, by having functional HFMTs and consequently functional HFQITs, Health facilities are more likely to have their customers satisfied with healthcare service delivery [ 32 , 33 ] and caters the importance of investing in leadership competencies at the PHC level as an essential strategy that contributes in the resilience of a health sector [ 34 , 35 ] and also helps to improve the performance of a health system [ 36 , 37 ]. Effective facility management is crucial for ensuring the proper performance of various health facility functions [ 10 , 38 ] and contributes to increased community trust, leading to greater healthcare-seeking behavior [ 39 ]. Previous studies have documented that training and mentoring of primary healthcare facility managers are necessary to improve the implementation of priority health interventions and enhance their ability to adhere to established management standards [ 40 , 41 ]. This fosters effective leadership and contributes to the transition from a healthcare system to a system for health [ 42 ]. Ultimately, these efforts are expected to facilitate the achievement of the Sustainable Development Goals (SDGs) [ 43 ]. Satisfactory performance coverage of functional HFQITs among non-functional HFMTs and Poor performance coverage of HFQITs functionality among functional HFMTs is an indication that, there are other factors than HFMTs functionality that might have influenced functionality of HFQITs such as the working environment [ 27 , 28 ], Health Facility Governing Committees functionality [ 38 ], facility finances, and revenue collection [ 39 – 41 ], and employee morale [ 42 , 43 ], were not taken into account in our analysis. 5.0 Conclusion and Recommendations The functionality of Health Facility Quality Improvement Teams (HFQITs) is profoundly influenced by HFMTs effectiveness. Enhancing HFMTs is an important step towards functionality of HFQITs that play a pivotal role in implementing quality improvement initiatives that subsequently impacts to resilient health care systems. Functional HFQITs is an important consideration towards achieving Tanzania’s Universal Health Insurance which seeks to provide equitable access to quality healthcare by enhancing health service delivery, promote and improve overall health outcomes across all socioeconomic groups. Declarations Authors Contributions SMM analyzed data and developed an initial draft, CJG and PAM cleaned and manipulated raw data, ESE, ESK, MGA, NAK, RK and PL had a critical role of reviewing the manuscript. All authors contributed to the interpretation of results, discussion of findings and critically reviewed the manuscript. Funding: No official funding was received by the authors for the study. Data manipulation and analysis was conducted as a part of usual responsibilities. Most of authors are from Health Quality Assurance Unit which is responsible in implementing SRA and hence obliged to disseminate evaluation results through publications. Data Availability: Upon request from the corresponding author, the dataset used in the current study is available Competing interests: The authors declared no conflict of interest. However, during SRA of PHCs that yielded these data, Eliudi S. Eliakimu, Joseph C. Hokororo, Chrisogone J. German and Talhiya A. Yahya were working with the Health Quality Assurance Division (now called Health Quality Assurance Unit) and were responsible for the implementation of SRA and Quality Improvement Plans (QIPs) follow-up. Ethical Approval: This study did not involve human subjects, hence for this type of study formal consent is not required. However, prior permission was sought from the Ministry of Health before using data. Ethical clearance is not necessary for this type of a study because data were collected in the course of implementing government initiative (Star Rating Assessment) and hence this analysis aims at giving feedback after its successful implementation. Disclaimers: The authors declare that the views expressed in this manuscript are their own and not an official position of any institution or funder for personal interests. Acknowledgements: The authors would like to acknowledge the Ministry of Health for granting permission to use the SRA data. Furtherly, our sincere gratitude goes to key partners in the implementation of the SRA that include directorates and units of Ministry of Health embracing Health Quality Assurance Unit, Curative Services Division, Preventive Services Division and the Directorate of Health, Social Welfare and Nutrition Services of the President’s Office – Regional Administration and Local Government (PO-RALG), development partners including the World Bank, Centres for Disease Control and Prevention, Danish International Development Agency, The World Health Organization, Association of Private Health Facilities in Tanzania, and Christian Social Services Commission. 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Performance of quality improvement teams and associated factors in selected regional referral hospitals in Tanzania: A cross-sectional study. Pan Afr Med J. 2021;38:1–15. https://doi.org/10.11604/pamj.2021.38.223.23767 . Mwaisengela SM, Hokororo JC, German CJ, Kinyenje ES, Bahegwa RP, Yahya TA, et al. Functionality of Primary Health Facilities Management Teams: Learning from 2017/2018’s Tanzania Star Rating Assessment. J Service Sci Manage. 2023;16:94–109. https://doi.org/10.4236/jssm.2023.162007 . Kwamie A, van Dijk H, Agyepong IA. Advancing the application of systems thinking in health: Realist evaluation of the Leadership Development Programme for district manager decision-making in Ghana. Health Res Policy Syst. 2014;12. https://doi.org/10.1186/1478-4505-12-29 . Karamagi HC, Titi-Ofei R, Kipruto HK, Seydi ABW, Droti B, Talisuna A, et al. On the resilience of health systems: A methodological exploration across countries in the WHO African Region. PLoS ONE. 2022;17. https://doi.org/10.1371/journal.pone.0261904 . Forsgren L, Tediosi F, Blanchet K, Saulnier DD. Health systems resilience in practice: a scoping review to identify strategies for building resilience. BMC Health Serv Res. 2022;22. https://doi.org/10.1186/s12913-022-08544-8 . Anasel M, Kapologwe N, Kalolo A, editors. Leadership and Governance in Primary Healthcare: An Exemplar for Practice in Resource Limited Settings. First Edition. CRC Press: Taylor & Francis group; 2023. https://doi.org/10.1201.9781003346821 WHO. Strengthening health systems to improve health outcomes: WHO’s framework for action. World Health Organization; 2007. Kesale AM, Mahonge C, Muhanga M. The functionality variation among health facility governing committees under direct health facility financing in Tanzania. PLOS Global Public Health. 2022;2:e0000366. https://doi.org/10.1371/journal.pgph.0000366 . Akinleye DD, McNutt LA, Lazariu V, McLaughlin CC. Correlation between hospital finances and quality and safety of patient care. PLoS ONE. 2019;14. https://doi.org/10.1371/journal.pone.0219124 . Dong GN. Performing well in financial management and quality of care: Evidence from hospital process measures for treatment of cardiovascular disease. BMC Health Serv Res. 2015;15. https://doi.org/10.1186/s12913-015-0690-x . Nguyen OK, Halm EA, Makam AN. Relationship between hospital financial performance and publicly reported outcomes. J Hosp Med. 2016;11:481–8. https://doi.org/10.1002/jhm.2570 . Goula A, Rizopoulos T, Stamouli MA, Kelesi M, Kaba E, Soulis S. Internal Quality and Job Satisfaction in Health Care Services. Int J Environ Res Public Health. 2022;19. https://doi.org/10.3390/ijerph19031496 . Okafor IP, Dada AA, Olubodun T, Olufunlayo TF. Health worker motivation to deliver quality care in western Nigeria. IJQHC Commun 2022;2. https://doi.org/10.1093/ijcoms/lyac012 Additional Declarations No competing interests reported. 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Mwaisengela","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIiWNgGAWjYHACNgaGCgkexvYGINvAglgtZ2zkmHsOgLRIEKmFsS3NmH1GAohDhBb5GcnPHnxgO5zYO/P51Q0/CiQY+Nu7E/BqMbiRZm44g+dw4szZOWU3e4AOkzhzdgN+LRIJZtI8EocTN87OSbvBA9RiIJGLX4v8jPRv0jwGhxP33zyTdvMPMVoYbuQAbUlIM2acwX7sNlG2GJx5U24444CNHGNPDtttGQMJHoJ+kW9P3/bg4z9QVB5/dvPNHxs5/vZeAg4TSICxeAzAJH7lIMB/AMZif0BY9SgYBaNgFIxIAABu9kr1VN2ITgAAAABJRU5ErkJggg==","orcid":"","institution":"Ministry of Health","correspondingAuthor":true,"prefix":"","firstName":"Syabo","middleName":"M.","lastName":"Mwaisengela","suffix":""},{"id":446165298,"identity":"b3543235-29cd-404d-9e61-41c79c9067bd","order_by":1,"name":"Patricia A. Materu","email":"","orcid":"","institution":"University of Dodoma","correspondingAuthor":false,"prefix":"","firstName":"Patricia","middleName":"A.","lastName":"Materu","suffix":""},{"id":446165299,"identity":"808d9654-7a5c-418c-a06a-121771cfca7c","order_by":2,"name":"Chrisogone J. German","email":"","orcid":"","institution":"Ministry of Health","correspondingAuthor":false,"prefix":"","firstName":"Chrisogone","middleName":"J.","lastName":"German","suffix":""},{"id":446165300,"identity":"9a6ff5d3-2ea5-42c1-bb40-9d010c547c2d","order_by":3,"name":"Raymond R. Kiwesa","email":"","orcid":"","institution":"President’s Office - Regional Administration and Local Government","correspondingAuthor":false,"prefix":"","firstName":"Raymond","middleName":"R.","lastName":"Kiwesa","suffix":""},{"id":446165302,"identity":"e86ba306-6b5e-46c3-8790-98eb40e6afc5","order_by":4,"name":"Erick S. Kinyenje","email":"","orcid":"","institution":"Ministry of Health","correspondingAuthor":false,"prefix":"","firstName":"Erick","middleName":"S.","lastName":"Kinyenje","suffix":""},{"id":446165304,"identity":"5df82202-d95b-4470-b36c-f3f2e8e54cc5","order_by":5,"name":"Pankras W. Luoga","email":"","orcid":"","institution":"Muhimbili University of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Pankras","middleName":"W.","lastName":"Luoga","suffix":""},{"id":446165306,"identity":"ab3cd6c1-91dc-4856-bcde-3b1901aacf99","order_by":6,"name":"Joseph C. 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Health facility management committees are considered mechanisms for leveraging health system change and, therefore, enhancing health system performance [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Having a proper health system management with skilled health managers has been shown to be an important foundation for a high-quality health system [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. As a foundation for resilient and sustainable systems in addressing health emergencies, it is important to strengthen the management of PHC facilities [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. For instance, in Ghana, PHC facilities that performed well in management also performed well with regard to processes of care and patient experience of care to women [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This supports the need for strengthening the management of PHC facilities as a foundation for improving the quality of care provided given that HFMTs have an obligation to coordinate and support development of quality improvement plans for the sake of addressing identified quality gaps in healthcare facilities contributing to PHC performance [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn Tanzania, health services are delivered through a decentralized system that broadly falls into three functional levels namely Local Government Authority (LGA) which is the primary level, regional (secondary level), and referral hospital (tertiary level) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. At the LGA level, primary healthcare services are delivered through dispensaries and health centers, with health centers acting as referral points for dispensaries. These health centers offer a wider range of services, including inpatient care. The highest tier consists of level 1 hospitals, which function as referral centers, such as council hospitals or designated council hospitals. If no government hospital is available, a service agreement may be established with a faith-based hospital [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. At the LGA level, Council Health Management Teams (CHMTs) work as governance agencies with the primary role of coordinating the distribution, use and allocation of resources for various operationalizations including overseeing Quality Improvement (QI) initiatives and implementation of healthcare policy frameworks [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eJust like in secondary and tertiary levels of healthcare, primary healthcare facilities have key teams namely health facility management teams (HFMTs) and Health Facility Quality Improvement Teams (HFQITs) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. As stated in Tanzania Quality Improvement Framework (2011\u0026ndash;2016), one of the roles and responsibilities of Health Facility Management Teams is to oversee the quality improvement processes and Quality Improvement Team functionality [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Quality improvement teams (QITs) have emerged as key mechanisms by which to initiate and implement improvement efforts within healthcare organizations [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] which contributes to improved compliance with set healthcare standards [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] that ultimately impacts to better health outcomes. It is known that, one of the basic goals of any healthcare system is quality improvement that is expected to have positive effect on the well-being of clients by enhancing safety, effectiveness, patient-centeredness, timeliness, efficiency, and equity in the delivery of health services [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Therefore, functionality of HFMTs is expected to influence HFQITs functionality [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] which is expected to impact quality of healthcare.\u003c/p\u003e \u003cp\u003eDespite HFMTs pivotal role, little scholarly attention is paid to its contribution to quality improvement processes and QIT functionality and therefore, little is known. Having important role to play of coordinating, implementing, monitoring and evaluating of QI activities for common quality improvement challenges that a health facility may be facing [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], it is of utmost importance that, HFMTs contribution on QITs functionality is known.\u003c/p\u003e \u003cp\u003eAs of now, there is no countrywide reliable data source that gathers information on both HFMTs and HFQITs functionality; however, in 2014, the Government of Tanzania introduced the implementation of \u0026ldquo;Big Results Now\u0026rdquo; initiative in the health sector; which resulted into the design of Star Rating Assessment (SRA) as one of its interventions aiming at improving the performance of PHC facilities [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In the financial year 2015/2016 Tanzania Mainland conducted a countrywide assessment of all PHC facilities and assigned a star ranging from 0 to 5 stars based on the status of quality services; and in 2017/2018, countrywide re-assessment was done [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Star Rating Assessment Tool (SRT) has twelve (12) service areas, namely Legality (Licensing and Certification), Health Facility Management, Use of Facility Data for Planning and Service Improvement, Staff Performance Assessment, Organization of Services, Handling Emergencies and Referral, Client Focus, Social Accountability, Facility Infrastructure, Infection Prevention and Control (IPC), Clinical Services, and Clinical Support Services [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Both HFQITs and HFMTs functionality are measured as indicators in an area, namely \u0026ldquo;Health Facility Management\u0026rdquo;.\u003c/p\u003e \u003cp\u003eThis paper aims, therefore, at assessing the contribution of functional HFMTs to the functionality of HFQITs among Primary Healthcare Facilities, as evidenced by the second-round Star Rating Assessment. This was the most recent assessment that was comprehensive enough to cover all twenty-six regions of Tanzania mainland and was conducted in fiscal year 2017/2018.\u003c/p\u003e"},{"header":"2.0 Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study design\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis study employed the analytical cross-sectional design to ascertain the implication of functional HFMTs on functionality of HFQITs in the context of second round SRA conducted during the fiscal year 2017/2018.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Setting\u003c/h2\u003e \u003cp\u003eAs Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows, Tanzania is a lower middle-income country located in East Africa with a surface area estimated to 945,087 km\u003csup\u003e2\u003c/sup\u003e. According to the population and housing census (2022), Tanzania has a total population of 61,741,120, with 40,196,497 (65,1%) residing in urban areas whereas 21,544,623 (34.9) in rural [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Administratively, Tanzania mainland has 26 regions, 139 Districts, 184 Councils, 570 Divisions, 3,956 Wards, and 12,319 villages [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Primary health facilities are into three levels: district hospitals, health centers and dispensaries. As of 16th July 2023, there is a total of 6,519 local government-owned PHC of which 5,582 (85.6%) are dispensaries, 767 (11.8%) are health centers, and 170 (2.6%) are district hospitals [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Study Units\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis paper aims to reveal the contribution of HFMTs on the functionality of HFQITs in PHC facilities in Tanzania which is located in the Eastern part of Africa with 26 administrative regions (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) visited for the second assessment that was conducted in the financial year 2017/2018 where a total of 5,933 PHC facilities that account for 81.4% of visited health facilities were extracted for analysis. About 18.6% of visited PHC facilities were dropped due to having missing values to most of the indicators necessary for the functionality of both HFMTs and HFQITs.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Data Source\u003c/h2\u003e \u003cp\u003eAs far as this study is concerned, data were sourced from Star Rating Assessment (SRA), which is an initiative belonging to the BRN workstream, namely \u003cem\u003ePerformance Management of Health Facilities.\u003c/em\u003e Data were collected from Star Rating Tools (SRT) for Dispensaries, Health Centers and District Hospitals and subsequently entered into the Health Management Information System (HMIS) through DHIS2 on the same day of assessment to guarantee correctness, accuracy and timeliness.\u003c/p\u003e \u003cp\u003eRegardless of the level of service, the SRT is broken down into four domains: Domain A is for facility management and staff performance with service areas 1, 2, 3, and 4, namely legality, facility management, Health Management Information System, and staff performance and appraisal system respectively. Domain B is for service charters and social accountability with service areas 5, 6, 7, and 8, namely organization of services, emergency and referral system, client focus, and social accountability, respectively. Domain C is for safe and conducive facilities with service areas 9 and 10 namely facility infrastructure and Infection Prevention and Control (IPC) respectively and Domain D is for Quality of Care and Services with service areas 10 and 11 namely clinical services and clinical support services respectively.\u003c/p\u003e \u003cp\u003eWithin service areas, there are several indicators within which verification criteria denote quality standards that are to be met by a health facility (14). To date, three SRAs have been conducted where a baseline assessment was conducted in the fiscal year 2015/2016, the second assessment (reassessment) was conducted in the fiscal year 2017/2018, and the most recent assessment (third assessment) was conducted in the fiscal year 2021/2022 for only ten (10) regions. Therefore, the second assessment is the most recent assessment that was comprehensive enough to produce representative findings of which all twenty-six (26) regions were visited.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Data management\u003c/h2\u003e \u003cp\u003eData were extracted from SRA data base for each health facility. The functionality of both HFQITs and HFMTs was measured as indicators in area 2, namely Health Facility Management, of which HFMTs functionality was measured by verification criteria, namely availability of the team, formal appointment of the team with terms of references, HFMTs meeting on regular schedule and quarterly meeting of HFMTs whereas QIT functionality was measured by availability of the team, regular quarterly meeting of the team with recorded meetings minutes and HFQITs conduct of self-internal assessments on quality of services using tools that meet national standards. Extracted data were transposed and manipulated in Microsoft Excel to form a single dataset. The dataset was imported to Stata IC 18 for descriptive and inferential statistical analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Data Analysis\u003c/h2\u003e \u003cp\u003eData were geospatially visualized with the aid of Quantum Geographical Information Software (QGIS) 3.16 Hannover. Comparative analysis is made regionwide for all twenty-six (26) regions of Tanzania mainland to ascertain differences in coverage of health facilities with functional HFQITs among functional and non-functional HFMTs in reference to 4 performance categories, i.e., less than 20%, between 20% to less than 40%, between 40% to less than 60% and greater than or equal to 60% assigned as poor, weak, good progress and good performance respectively [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe spatial regional variation documentation highlights the need to understand the broader subnational systems and context which may influence culture and effectiveness at the facility level and a health system as whole [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOne sample proportion Z test was conducted to determine the extent to which functional HFMTs or HFQITs are significantly different from non-functional ones), two samples proportional Z test to determine differences in HFQITs functionality among functional and non-functional HFMTs with separate analyses conducted for each facility level, ownership and location, Chi-square test to determine whether there is a statistically significant difference in the percentage of functional HFQITs across all 26 regions and compare differences in HFQITs functionality across facility levels (Dispensary, Health Center and District Hospital), location (Rural and Urban) and ownership (Public or Private) for both functional and non-functional HFMTs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Inclusion criteria\u003c/h2\u003e \u003cp\u003eAs argued by Schafer (2016), missing data leads to biased results [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Therefore, the criteria for inclusion were all health facilities (Level 1 Hospitals, Health Centers, and dispensaries) visited during the second SRA (2017/2018), with no missing or invalid verification criteria on the functionality of both HFMTs and HFQITs from the SRA tool.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 Exclusion criteria\u003c/h2\u003e \u003cp\u003eThe exclusion criteria were all health facilities with any missing verification criteria regarding the functionality of both HFMTs and HFQITs from the SRA tool.\u003c/p\u003e \u003c/div\u003e"},{"header":"3.0 Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Characteristics of health facilities involved in the analysis\u003c/h2\u003e \u003cp\u003eAs Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows, this analysis covered 5,933 primary healthcare facilities, with the majority being dispensaries (87.7%), located in rural areas (78.3%), and publicly owned (77.2%). Of the facilities analyzed, 1,382 (23.3%) had functional Health Facility Management Teams (HFMTs), while 1,338 (22.6%) had functional Health Facility Quality Improvement Teams (HFQITs).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of health facilities involved in the analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eFunctional HFMTs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eFunctional HFQITs\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e95% C. I\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e95% C. I\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOverall\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5933 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFacility Type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitals\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e41.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e52.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth Centers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e652 (11.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e31.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDispensaries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5201 (87.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFacility Location\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1285 (21.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e30.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4648 (78.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFacility Ownership\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4578 (77.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1355 (22.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e24.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Overall contribution of functional HFMT on HFQIT functionality\u003c/h2\u003e \u003cp\u003eAs Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows, A two-sample proportional Z test conducted revealed that 13.8% (95% C.I 12.8% \u0026minus;\u0026thinsp;14.8%) of health facilities with non-functional HFMTs had functional HFQIT. On the other hand, 51.2% (95% C.I 48.6% \u0026minus;\u0026thinsp;53.9%) of health facilities with functional HFMTs had functional HFQIT. This difference is statistically significant, highlighting that functional HFMTs are significantly more likely to have functional HFQITs compared to non-functional ones (z=-29.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Contribution of functional HFQIT on HFMT functionality by facility level\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows that, among health facilities with non-functional HFMTs, an analysis showed significant difference in health facilities that had functional HFQITs among dispensaries, health centers and level 1 hospitals (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Chi}^{2}\\)\u003c/span\u003e\u003c/span\u003e=30.04, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). On the other hand, compared to non-functional HFMTs, among health facilities with functional HFMTs, a smaller significant difference in health facilities that had functional HFQITs among dispensaries, health centers and level 1 hospitals was observed (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Chi}^{2}\\)\u003c/span\u003e\u003c/span\u003e=10.00, p\u0026thinsp;=\u0026thinsp;0.007). This indicates that, dispensaries, health centers and level 1 hospitals differ more significantly in terms of functionality of HFQITs where HFMTs are non-functional.\u003c/p\u003e \u003cp\u003eAn analysis revealed that among hospitals, 16.7% (95% C.I 5.4% \u0026minus;\u0026thinsp;27.9%) of non-functional HFMTs had functional HFQIT. On the other hand, 68.4% (95% C.I 53.6% \u0026minus;\u0026thinsp;83.2%) of hospitals with functional HFMTs had functional HFQIT. This difference is statistically significant highlighting that, among hospitals, functional HFMTs are significantly more likely to have functional HFQITs compared to non-functional ones (z=-4.7, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eAn analysis conducted revealed among Health Centers, 23.5% (95% C.I 19.6% \u0026minus;\u0026thinsp;27.5%) with non-functional HFMTs had functional HFQIT. On the other hand, 58.1% (95% C.I 51.4% \u0026minus;\u0026thinsp;64.8%) of health centers with functional HFMTs had functional HFQIT. This difference is statistically significant, highlighting that functional HFMTs are significantly more likely to have functional HFQITs compared to non-functional ones among hospitals (z=-8.7, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eAn analysis conducted revealed among dispensaries, 12.8% (95% C.I 11.7% \u0026minus;\u0026thinsp;13.8%) with non-functional HFMTs had functional HFQIT. On the other hand, 49.4% (95% C.I 46.5% \u0026minus;\u0026thinsp;52.3%) of dispensaries with functional HFMTs had functional HFQIT. This difference is statistically significant, highlighting that, among dispensaries, functional HFMTs are significantly more likely to have functional HFQITs compared to non-functional ones (z=-26.9, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eThe Comparative analysis shows statistically significant difference in HFQITs functionality among HFMTs with functional (chi2\u0026thinsp;=\u0026thinsp;54, p\u0026thinsp;=\u0026thinsp;0.05) and non-functional HFQITs (chi2\u0026thinsp;=\u0026thinsp;54, p\u0026thinsp;=\u0026thinsp;0.05)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Contribution of functional HFQIT on HFMT functionality by facility location\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows that, among health facilities with non-functional HFMTs, an analysis showed a non-significant difference in health facilities that had functional HFQITs among rural and urban-located health facilities (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Chi}^{2}\\)\u003c/span\u003e\u003c/span\u003e=3.04, p\u0026thinsp;=\u0026thinsp;0.081). On the other hand, among health facilities with functional HFMTs, a significant difference in health facilities that had functional HFQITs among rural and Urban located health facilities wa observed (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Chi}^{2}\\)\u003c/span\u003e\u003c/span\u003e=13.29, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This indicates that, rural and urban health facilities significantly differ in health facilities with functional HFQITs where HFMTs are also functional.\u003c/p\u003e \u003cp\u003eAn analysis conducted revealed that among rural-located health facilities, 13.4% (95% C.I 12.3% \u0026minus;\u0026thinsp;14.5%) of health facilities with non-functional HFMTs had functional HFQIT. On the other hand, 48.3% (95% C.I 45.3% \u0026minus;\u0026thinsp;51.4%) of health facilities with functional HFMTs had functional HFQIT. This difference is statistically significant, highlighting that functional HFMTs are significantly more likely to have functional HFQITs compared to non-functional ones (z=-24.2, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eAmong urban-located health facilities, 15.6% (95% C.I 13.3% \u0026minus;\u0026thinsp;17.9%) of health facilities with non-functional HFMTs had functional HFQIT. On the other hand, 59.5% (95% C.I 54.5% \u0026minus;\u0026thinsp;64.6%) of health facilities with functional HFMTs had functional HFQIT. This difference is statistically significant, highlighting that functional HFMTs are significantly more likely to have functional HFQITs compared to non-functional ones (z=-15.7, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Contribution of functional HFQIT on HFMT functionality by facility ownership\u003c/h2\u003e \u003cp\u003eAs shown by Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, among health facilities with non-functional HFMTs, an analysis showed non-significant difference in health facilities that had functional HFQITs among privately and public owned health facilities (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Chi}^{2}\\)\u003c/span\u003e\u003c/span\u003e=3.29, p\u0026thinsp;=\u0026thinsp;0.07). On the other hand, among health facilities with functional HFMTs, a significant difference in health facilities that had functional HFQITs among privately and public owned health facilities was observed (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Chi}^{2}\\)\u003c/span\u003e\u003c/span\u003e=6.47, p\u0026thinsp;=\u0026thinsp;0.011). This indicates that, private and public owned health facilities significantly differ in health facilities with functional HFQITs where HFMTs are also functional.\u003c/p\u003e \u003cp\u003eAmong public-owned health facilities, 12.1% (95% C.I 10.2% \u0026minus;\u0026thinsp;14.1%) of health facilities with non-functional HFMTs had functional HFQIT. On the other hand, 57.6% (95% C.I 52.1% \u0026minus;\u0026thinsp;63.1%) of health facilities with functional HFMTs had functional HFQIT. This difference is statistically significant, highlighting that, among public-owned health facilities, functional HFMTs are significantly more likely to have functional HFQITs compared to non-functional ones (z=-24.0, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eAmong privately owned health facilities, 14.3% (95% C.I 13.2% \u0026minus;\u0026thinsp;15.5%) of health facilities with non-functional HFMTs had functional HFQIT. On the other hand, 49.4% (95% C.I 46.4% \u0026minus;\u0026thinsp;52.4%) of health facilities with functional HFMTs had functional HFQIT. This difference is statistically significant, highlighting that functional HFMTs are significantly more likely to have functional HFQITs compared to non-functional ones (z=-16.8, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Contribution of HFQIT on HFMT functionality by regions\u003c/h2\u003e \u003cp\u003eAmong health facilities with non-functional HFMTs, an analysis showed non-significant difference in health facilities that had functional HFQITs among health facilities in all twenty-six regions (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Chi}^{2}\\)\u003c/span\u003e\u003c/span\u003e=162.9, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). On the other hand, among health facilities with functional HFMTs, a significant difference in health facilities that had functional HFQITs among all regions was observed (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Chi}^{2}\\)\u003c/span\u003e\u003c/span\u003e=71.52, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This indicates that, regionwide, health facilities differ more significantly in health facilities with functional HFQITs where HFMTs are non-functional.\u003c/p\u003e \u003cp\u003eA region-sorted two-sample proportion Z test conducted for all twenty-six (26) regions reveals statistically significant differences in the proportions of health facilities with functional HFQITs among health facilities with functional and non-functional HFMTs.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e indicates that among non-functional HFMTs, twenty-one (21) regions had poor coverage (less than 20%) of health facilities with functional HFQITs, while the remaining six regions had weak coverage. Neither of the regions showed good nor good progress.\u003c/p\u003e \u003cp\u003eOn the other hand, among functional HFMTs, only Katavi region showed poor coverage. Good and desirable coverage was revealed among Kilimanjaro, Geita, and Singida regions, while weak coverage was in Kigoma, Manyara, Songwe, Njombe, Ruvuma, and Lindi. All remaining sixteen (16) regions showed good progress coverage (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4.0 Discussion","content":"\u003cp\u003eThis study revealed positive contribution of functional HFMTs on QITs functionality. Some other studies reveal negative effect of non-functionality of HFMTs on operationalization of QIT activities implementation [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] and therefore, improving facility management is an important consideration to improve healthcare delivery and consequently enhance patient satisfaction [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The disaggregated analysis conducted in this study in regard to facility level, location and ownership gives a clearer direction for targeted interventions on Primary Healthcare facilities given that HFMTs are responsible for planning, coordinating and managing the provision of health and social welfare services with a broad range of specific functions that include: ensuring the viability of HFQITs and Work Improvement Teams (WITs) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFunctionality of HFMTs being an influence to HFQITs functionality corresponds to another study by Kacholi et al. (2021) which identifies one of the major factors factor that impedes Quality Improvement Teams\u0026rsquo; effectiveness being poor Health Facility Management [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], therefore, by having functional HFMTs and consequently functional HFQITs, Health facilities are more likely to have their customers satisfied with healthcare service delivery [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] and caters the importance of investing in leadership competencies at the PHC level as an essential strategy that contributes in the resilience of a health sector [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] and also helps to improve the performance of a health system [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEffective facility management is crucial for ensuring the proper performance of various health facility functions [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] and contributes to increased community trust, leading to greater healthcare-seeking behavior [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Previous studies have documented that training and mentoring of primary healthcare facility managers are necessary to improve the implementation of priority health interventions and enhance their ability to adhere to established management standards [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. This fosters effective leadership and contributes to the transition from a healthcare system to a system for health [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Ultimately, these efforts are expected to facilitate the achievement of the Sustainable Development Goals (SDGs) [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSatisfactory performance coverage of functional HFQITs among non-functional HFMTs and Poor performance coverage of HFQITs functionality among functional HFMTs is an indication that, there are other factors than HFMTs functionality that might have influenced functionality of HFQITs such as the working environment [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], Health Facility Governing Committees functionality [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], facility finances, and revenue collection [\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], and employee morale [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], were not taken into account in our analysis.\u003c/p\u003e"},{"header":"5.0 Conclusion and Recommendations","content":"\u003cp\u003eThe functionality of Health Facility Quality Improvement Teams (HFQITs) is profoundly influenced by HFMTs effectiveness. Enhancing HFMTs is an important step towards functionality of HFQITs that play a pivotal role in implementing quality improvement initiatives that subsequently impacts to resilient health care systems. Functional HFQITs is an important consideration towards achieving Tanzania\u0026rsquo;s Universal Health Insurance which seeks to provide equitable access to quality healthcare by enhancing health service delivery, promote and improve overall health outcomes across all socioeconomic groups.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSMM analyzed data and developed an initial draft, CJG and PAM cleaned and manipulated raw data, ESE, ESK, MGA, NAK, RK and PL had a critical role of reviewing the manuscript. All authors contributed to the interpretation of results, discussion of findings and critically reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eNo official funding was received by the authors for the study. Data manipulation and analysis was conducted as a part of usual responsibilities. Most of authors are from Health Quality Assurance Unit which is responsible in implementing SRA and hence obliged to disseminate evaluation results through publications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability:\u0026nbsp;\u003c/strong\u003eUpon request from the corresponding author,\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ethe dataset used in the current study is available\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declared no conflict of interest. However, during SRA of PHCs that yielded these data, Eliudi S. Eliakimu, Joseph C. Hokororo, Chrisogone J. German and Talhiya A. Yahya were working with the Health Quality Assurance Division (now called Health Quality Assurance Unit) and were responsible for the implementation of SRA and Quality Improvement Plans (QIPs) follow-up.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval:\u003c/strong\u003e This study did not involve human subjects, hence for this type of study formal consent is not required. However, prior permission was sought from the Ministry of Health before using data. Ethical clearance is not necessary for this type of a study because data were collected in the course of implementing government initiative (Star Rating Assessment) and hence this analysis aims at giving feedback after its successful implementation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclaimers:\u0026nbsp;\u003c/strong\u003eThe authors declare that the views expressed in this manuscript are their own and not an official position of any institution or funder for personal interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe authors would like to acknowledge the Ministry of Health for granting permission to use the SRA data. Furtherly, our sincere gratitude goes to key partners in the implementation of the SRA that include directorates and units of Ministry of Health embracing Health Quality Assurance Unit, Curative Services Division, Preventive Services Division and the Directorate of Health, Social Welfare and Nutrition Services of the President\u0026rsquo;s Office \u0026ndash; Regional Administration and Local Government (PO-RALG), development partners including the World Bank, Centres for Disease Control and Prevention, Danish International Development Agency, The World Health Organization, Association of Private Health Facilities in Tanzania, and Christian Social Services Commission. Nevertheless, Regional Secretariats, Local Government Authorities and Healthcare Workers in visited PHC Facilities in all 26 regions are highly acknowledged for their cooperation in the implementation of SRA.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWiig S, O\u0026rsquo;Hara JK. Resilient and responsive healthcare services and systems: challenges and opportunities in a changing world. BMC Health Serv Res. 2021;21. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12913-021-07087-8\u003c/span\u003e\u003cspan address=\"10.1186/s12913-021-07087-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eForsgren L, Tediosi F, Blanchet K, Saulnier DD. Health systems resilience in practice: a scoping review to identify strategies for building resilience. 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IJQHC Commun 2022;2. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/ijcoms/lyac012\u003c/span\u003e\u003cspan address=\"10.1093/ijcoms/lyac012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Health Facility Management Teams, Health Facility Quality Improvement Teams, Primary Healthcare Facilities, Healthcare Quality Standards, Star Rating Assessment, Tanzania","lastPublishedDoi":"10.21203/rs.3.rs-5554637/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5554637/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eCommittees for managing health facilities are thought of as tools for leveraging changes and impact to a high-quality health system.\u003c/p\u003e\u003cp\u003e\u003cb\u003eObjective\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis paper aims at assessing the contribution of functional Health Facility Management Teams (HFMTs) on the functionality of Health Facility Quality Improvement Teams (HFQITs) among Primary Healthcare Facilities (PHCs) in Tanzania.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis is a quantitative secondary data analysis using the Star Rating Assessment (SRA) data collected in the fiscal year 2017/2018. Functionality of Health Facility Management Teams (HFMTs) and Health Facility Quality Improvement Teams (HFQITs) were measured by considering availability of team members with terms of reference, conduct of regular meetings and HFQITs self-assessments of quality of healthcare. With the aid of Stata 18, we used Chi Square and Proportion Z tests for comparative analyses in regard to facility level, facility location and facility ownership. Spatial variation by region were visualized with the aid of QGIS 3.8 Firenze.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis study involved 5,933 PHCs, majority of which were rural located (78.3%), public owned (77.2%) and dispensaries (87.7%). On average, 23.3% and 22.6% of PHCs had functional HFMTs and HFQITs respectively. More functional HFQITs were observed among PHCs with functional HFMTs (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eHFMTs functionality impacts on how well HFQITs work. Functional HFQITs are essential for enhancing compliance with healthcare standards that in the end improve patient satisfaction.\u003c/p\u003e","manuscriptTitle":"Contribution of Functional Health Facility Management Teams on functionality of Quality Improvement Teams among Primary Healthcare Facilities in Tanzania","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-28 05:35:20","doi":"10.21203/rs.3.rs-5554637/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3f8562b1-c4eb-401d-8056-abe0eab5ad9b","owner":[],"postedDate":"April 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-29T09:09:12+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-28 05:35:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5554637","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5554637","identity":"rs-5554637","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}