Organizational Maturity as a Tool for Quality Governance: A Longitudinal Study in a Brazilian Hospital

Organizational Maturity as a Tool for Quality Governance: A Longitudinal Study in a Brazilian Hospital | 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 Organizational Maturity as a Tool for Quality Governance: A Longitudinal Study in a Brazilian Hospital Raimundo Nonato Diniz Rodrigues Filho, Lidia Morais This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9673189/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 Objective To analyze the evolution of organizational maturity and its role in supporting quality governance in a Brazilian hospital. Methods A longitudinal organizational study was conducted using a structured maturity assessment tool applied between 2020 and 2023. The instrument evaluated subsections across four domains: governance, patient care, diagnostics and therapeutics, and support services. A composite maturity index was calculated based on mean subsection scores. K-means cluster analysis was applied to standardized temporal trajectories to identify patterns of institutional development. Results The global maturity index increased from 0.279 in 2020 to 0.580 in 2023, representing an absolute increase of 0.301 (107.9% relative increase). Domain-level maturity in 2023 was highest in governance (0.619) and lowest in support services (0.510). Cluster analysis identified five distinct patterns of development, indicating heterogeneous trajectories across organizational domains. The greatest improvements were observed in pharmaceutical care, infection prevention and control, supply chain management, neonatal care, and specialized diagnostic services. Conclusion Organizational maturity models can support data-driven quality governance and improve decision-making processes in healthcare organizations. Health Policy Management Health Economics & Outcomes Research Quality improvement Quality of care Organizational governance Hospitals Health services research Figures Figure 1 Figure 2 Introduction Improving the quality of healthcare services is a strategic priority for contemporary health systems. Increasing organizational complexity requires robust governance structures capable of integrating management, clinical care, and performance monitoring. Donabedian’s framework conceptualizes healthcare quality through structure, process, and outcomes¹,². Building on this model, multiple approaches have been developed, including accreditation programs, patient safety strategies, and continuous improvement systems³–⁵. Organizational maturity models have emerged as tools to assess institutional capacity for implementing structured quality practices. These models enable identification of developmental stages, comparison across organizational domains, and prioritization of improvement strategies⁶–⁸. Despite their increasing use, empirical evidence on the application of maturity models in hospital settings—particularly in middle-income countries—remains limited⁹–¹². This study aims to analyze the evolution of organizational maturity and its role in supporting quality governance in a Brazilian hospital. Methods Study design This was a longitudinal observational organizational study based on a structured maturity assessment model. Setting The study was conducted in a Brazilian hospital, with annual evaluations performed between 2020 and 2023. Maturity assessment model The assessment tool evaluated subsections across four organizational domains: governance, patient care, diagnostics and therapeutics, and support services. Scores ranged from 0 to 1, representing progressive levels of maturity. The maturity assessment tool was used as an institutional quality governance instrument to support structured monitoring of organizational development over time. It assessed the extent to which key hospital processes were formalized, implemented, monitored and continuously improved. Although the tool was not designed as a psychometric scale, it provided a standardized managerial framework for longitudinal assessment. Its primary utility was to support identification of organizational gaps, prioritization of improvement initiatives and governance-oriented decision-making. Data collection Annual scores were collected for each subsection, forming a temporal series for analysis. Data were standardized prior to clustering to ensure comparability across subsections. Statistical analysis A composite maturity index was calculated as the mean of subsection scores. Domain-level averages were also computed annually. K-means cluster analysis was applied to standardized trajectories to identify patterns of institutional evolution. Solutions ranging from two to five clusters were tested, with selection based on silhouette index performance. This study was conducted and reported in accordance with the STROBE guidelines for observational studies. Results Overall maturity evolution Organizational maturity increased consistently over time. The global index rose from 0.279 in 2020 to 0.580 in 2023, representing a relative increase of 107.9%. The temporal evolution is presented in Fig. 1 . Additionally, subsections included in the accelerated growth cluster corresponded to those with the highest absolute increases, reinforcing consistency between cluster patterns and observed improvements (Fig. 2 , Table 2 ). Table 2 Subsections with highest absolute increase in organizational maturity (2020–2023) Domain Subsection 2020 2023 Absolute increase Patient care Pharmaceutical care 0.290 0.960 0.670 Support services Infection prevention and control 0.310 0.850 0.540 Governance Supply chain management 0.280 0.770 0.490 Patient care Neonatal care 0.470 0.960 0.490 Diagnostics and therapeutics Specialized diagnostic and therapeutic methods 0.130 0.600 0.470 Governance Access to care management 0.320 0.760 0.440 Governance Infrastructure and technology management 0.340 0.710 0.370 Governance Workforce management 0.200 0.550 0.350 Governance Organizational leadership 0.300 0.640 0.340 Diagnostics and therapeutics Endoscopic and videoscopic methods 0.200 0.520 0.320 Domain-level maturity In 2023, maturity levels were highest in governance (0.619), followed by patient care (0.581), diagnostics and therapeutics (0.580), and support services (0.510). Domain-level results are summarized in Table 1 . Table 1 Mean organizational maturity index by domain and year Domain 2020 2021 2022 2023 Patient care 0.293 0.369 0.452 0.581 Diagnostics and therapeutics 0.252 0.410 0.475 0.580 Support services 0.276 0.346 0.472 0.510 Governance 0.279 0.401 0.479 0.619 Overall index 0.279 0.381 0.468 0.580 Cluster analysis findings Cluster analysis identified five distinct patterns of institutional development, with a mean silhouette index of 0.32, indicating moderate separation. Cluster characteristics are described in Table 3 . The moderate silhouette value (0.32) suggests meaningful but not fully distinct clustering, reflecting the inherent complexity of organizational development processes. Table 3 Cluster characteristics of organizational maturity trajectories Cluster Number of subsections Pattern of evolution Main characteristics Representative examples 1 4 Persistent low maturity Consistently low scores over time with minimal improvement Infrastructure management, administrative support 2 5 Gradual growth Progressive increase in maturity between 2020 and 2023 Clinical protocols, patient flow organization 3 3 Stable intermediate maturity Moderate scores maintained over time with limited variation Clinical governance, performance monitoring 4 6 Accelerated growth Rapid increase in maturity over the study period Pharmaceutical care, infection control, supply chain 5 2 High baseline maturity High maturity scores from baseline with minimal variation Specialized diagnostics, neonatal care High-growth subsections The largest gains in maturity were observed in pharmaceutical care (+ 0.67), infection prevention and control (+ 0.54), supply chain management (+ 0.49), neonatal care (+ 0.49), and specialized diagnostic services (+ 0.47). These results are detailed in Table 2 and Fig. 2 . Discussion Statement of principal findings This study demonstrates a consistent and heterogeneous improvement in organizational maturity over time, with distinct patterns of development identified through cluster analysis. These findings reinforce that organizational maturity may act as a proxy for institutional readiness, bridging the gap between structural capacity and sustained quality improvement outcomes. Strengths and limitations Strengths include the longitudinal design, the use of a structured maturity model, and the application of cluster analysis. Limitations include the single-center design and the absence of direct clinical outcomes. A further limitation is that the maturity assessment tool was used as an institutional governance instrument rather than as a formally validated psychometric scale. However, its longitudinal application using a consistent scoring structure allowed assessment of organizational trajectories over time. Interpretation within the context of the wider literature The findings align with established frameworks in quality improvement and healthcare governance, including Donabedian’s model and MUSIQ¹⁸. These frameworks emphasize the importance of organizational context in sustaining improvement. Implications for policy, practice and research Organizational maturity models can support structured quality governance and guide decision-making. They provide a framework for prioritizing improvement initiatives and inform system-level strategies in middle-income settings. Future studies should further test the applicability, reliability and validity of maturity assessment tools across different hospital settings and health systems. Conclusions Organizational maturity models represent a useful approach for monitoring and guiding quality improvement processes in hospitals. These findings highlight the potential of maturity-based approaches as scalable tools for strengthening quality governance in resource-constrained health systems. Declarations Disclosure of Interest No potential competing interest was reported by the authors. Funding No funding was received for this study. Data Availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request. References Donabedian A. Evaluating the quality of medical care. Milbank Q. 1966;44(3):166-206. Donabedian A. The quality of care: how can it be assessed? JAMA. 1988;260(12):1743-1748. Berwick DM. A primer on leading the improvement of systems. BMJ. 1996;312:619-622. Batalden PB, Davidoff F. What is quality improvement and how can it transform healthcare? Qual Saf Health Care. 2007;16(1):2-3. Langley GJ, Moen R, Nolan KM, Nolan TW, Norman CL, Provost LP. The Improvement Guide. 2nd ed. San Francisco: Jossey-Bass; 2009. World Health Organization. Quality of Care: A Process for Making Strategic Choices in Health Systems. Geneva: WHO; 2006. World Health Organization, OECD, World Bank. Delivering Quality Health Services: A Global Imperative for Universal Health Coverage. Geneva: WHO; 2018. Institute of Medicine. Crossing the Quality Chasm. Washington: National Academy Press; 2001. Institute of Medicine. To Err Is Human. Washington: National Academy Press; 2000. Porter ME. What is value in health care? N Engl J Med. 2010;363(26):2477-2481. Braithwaite J, Shaw CD, Moldovan M, Greenfield D, Hinchcliff R, Mumford V, et al. Comparison of health service accreditation programs. Int J Qual Health Care. 2012;24(6):568-577. Greenfield D, Braithwaite J. Health sector accreditation research: a systematic review. Int J Qual Health Care. 2008;20(3):172-183. Shaw CD. Toolkit for accreditation programs. Int J Qual Health Care. 2004;16 Suppl 1:i67-i72. Shaw CD, Groene O, Mora N, Sunol R. Accreditation and ISO certification in healthcare. Int J Qual Health Care. 2010;22(6):445-451. Pomey MP, Contandriopoulos AP, Francois P, Bertrand D. Accreditation: a tool for organizational change in hospitals? Int J Health Care Qual Assur. 2004;17(3):113-124. Flodgren G, Pomey MP, Taber SA, Eccles MP. Effectiveness of external inspection of compliance with standards. Cochrane Database Syst Rev. 2011;(11):CD008992. Kringos DS, Sunol R, Wagner C, Mannion R, Michel P, Klazinga NS, et al. The influence of context on quality improvement success. BMC Health Serv Res. 2015;15:277. Kaplan HC, Provost LP, Froehle CM, Margolis PA. The Model for Understanding Success in Quality (MUSIQ). BMJ Qual Saf. 2012;21(1):13-20. Braithwaite J, Churruca K, Long JC, Ellis LA, Herkes J. When complexity science meets implementation science. BMC Med. 2018;16:63. Ovretveit J. Leading improvement effectively: review of research. Int J Health Care Qual Assur. 2009;22(5):439-448. Shortell SM, Bennett CL, Byck GR. Assessing the impact of continuous quality improvement on clinical practice. Milbank Q. 1998;76(4):593-624. Greenhalgh T, Robert G, Macfarlane F, Bate P, Kyriakidou O. Diffusion of innovations in service organizations. Milbank Q. 2004;82(4):581-629. Dixon-Woods M, Martin GP. Does quality improvement improve quality? Future Hosp J. 2016;3(3):191-194. Leatherman S, Sutherland K. The Quest for Quality in the NHS. London: Nuffield Trust; 2008. Braithwaite J, Westbrook JI. The development of a national demonstration project on quality and safety. Med J Aust. 2011;194(7):343-344. Additional Declarations The authors declare no competing interests. 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Increasing organizational complexity requires robust governance structures capable of integrating management, clinical care, and performance monitoring.\u003c/p\u003e \u003cp\u003eDonabedian\u0026rsquo;s framework conceptualizes healthcare quality through structure, process, and outcomes\u0026sup1;,\u0026sup2;. Building on this model, multiple approaches have been developed, including accreditation programs, patient safety strategies, and continuous improvement systems\u0026sup3;\u0026ndash;⁵.\u003c/p\u003e \u003cp\u003eOrganizational maturity models have emerged as tools to assess institutional capacity for implementing structured quality practices. These models enable identification of developmental stages, comparison across organizational domains, and prioritization of improvement strategies⁶\u0026ndash;⁸.\u003c/p\u003e \u003cp\u003eDespite their increasing use, empirical evidence on the application of maturity models in hospital settings\u0026mdash;particularly in middle-income countries\u0026mdash;remains limited⁹\u0026ndash;\u0026sup1;\u0026sup2;. This study aims to analyze the evolution of organizational maturity and its role in supporting quality governance in a Brazilian hospital.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eThis was a longitudinal observational organizational study based on a structured maturity assessment model.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSetting\u003c/h3\u003e\n\u003cp\u003eThe study was conducted in a Brazilian hospital, with annual evaluations performed between 2020 and 2023.\u003c/p\u003e\n\u003ch3\u003eMaturity assessment model\u003c/h3\u003e\n\u003cp\u003eThe assessment tool evaluated subsections across four organizational domains: governance, patient care, diagnostics and therapeutics, and support services. Scores ranged from 0 to 1, representing progressive levels of maturity.\u003c/p\u003e \u003cp\u003eThe maturity assessment tool was used as an institutional quality governance instrument to support structured monitoring of organizational development over time. It assessed the extent to which key hospital processes were formalized, implemented, monitored and continuously improved. Although the tool was not designed as a psychometric scale, it provided a standardized managerial framework for longitudinal assessment. Its primary utility was to support identification of organizational gaps, prioritization of improvement initiatives and governance-oriented decision-making.\u003c/p\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eAnnual scores were collected for each subsection, forming a temporal series for analysis. Data were standardized prior to clustering to ensure comparability across subsections.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eA composite maturity index was calculated as the mean of subsection scores. Domain-level averages were also computed annually. K-means cluster analysis was applied to standardized trajectories to identify patterns of institutional evolution. Solutions ranging from two to five clusters were tested, with selection based on silhouette index performance.\u003c/p\u003e \u003cp\u003eThis study was conducted and reported in accordance with the STROBE guidelines for observational studies.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eOverall maturity evolution\u003c/h2\u003e \u003cp\u003eOrganizational maturity increased consistently over time. The global index rose from 0.279 in 2020 to 0.580 in 2023, representing a relative increase of 107.9%. The temporal evolution is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Additionally, subsections included in the accelerated growth cluster corresponded to those with the highest absolute increases, reinforcing consistency between cluster patterns and observed improvements (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \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 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSubsections with highest absolute increase in organizational maturity (2020\u0026ndash;2023)\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=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDomain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubsection\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAbsolute increase\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePharmaceutical care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.670\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSupport services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfection prevention and control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.850\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.540\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGovernance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSupply chain management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.770\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.490\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeonatal care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.490\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnostics and therapeutics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpecialized diagnostic and therapeutic methods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.470\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGovernance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAccess to care management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.760\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.440\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGovernance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfrastructure and technology management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.710\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.370\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGovernance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWorkforce management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.350\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGovernance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOrganizational leadership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.340\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnostics and therapeutics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEndoscopic and videoscopic methods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.320\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\n\u003ch3\u003eDomain-level maturity\u003c/h3\u003e\n\u003cp\u003eIn 2023, maturity levels were highest in governance (0.619), followed by patient care (0.581), diagnostics and therapeutics (0.580), and support services (0.510). Domain-level results are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean organizational maturity index by domain and year\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDomain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.452\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.581\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnostics and therapeutics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.475\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.580\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSupport services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.472\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.510\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGovernance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.479\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.619\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOverall index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.468\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.580\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCluster analysis findings\u003c/h2\u003e \u003cp\u003eCluster analysis identified five distinct patterns of institutional development, with a mean silhouette index of 0.32, indicating moderate separation. Cluster characteristics are described in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The moderate silhouette value (0.32) suggests meaningful but not fully distinct clustering, reflecting the inherent complexity of organizational development processes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCluster characteristics of organizational maturity trajectories\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of subsections\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePattern of evolution\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMain characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRepresentative examples\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePersistent low maturity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConsistently low scores over time with minimal improvement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInfrastructure management, administrative support\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGradual growth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProgressive increase in maturity between 2020 and 2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eClinical protocols, patient flow organization\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStable intermediate maturity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate scores maintained over time with limited variation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eClinical governance, performance monitoring\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAccelerated growth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRapid increase in maturity over the study period\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePharmaceutical care, infection control, supply chain\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh baseline maturity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh maturity scores from baseline with minimal variation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSpecialized diagnostics, neonatal care\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=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eHigh-growth subsections\u003c/h2\u003e \u003cp\u003eThe largest gains in maturity were observed in pharmaceutical care (+\u0026thinsp;0.67), infection prevention and control (+\u0026thinsp;0.54), supply chain management (+\u0026thinsp;0.49), neonatal care (+\u0026thinsp;0.49), and specialized diagnostic services (+\u0026thinsp;0.47). These results are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStatement of principal findings\u003c/h2\u003e \u003cp\u003eThis study demonstrates a consistent and heterogeneous improvement in organizational maturity over time, with distinct patterns of development identified through cluster analysis. These findings reinforce that organizational maturity may act as a proxy for institutional readiness, bridging the gap between structural capacity and sustained quality improvement outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eStrengths include the longitudinal design, the use of a structured maturity model, and the application of cluster analysis. Limitations include the single-center design and the absence of direct clinical outcomes.\u003c/p\u003e \u003cp\u003eA further limitation is that the maturity assessment tool was used as an institutional governance instrument rather than as a formally validated psychometric scale. However, its longitudinal application using a consistent scoring structure allowed assessment of organizational trajectories over time.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eInterpretation within the context of the wider literature\u003c/h2\u003e \u003cp\u003eThe findings align with established frameworks in quality improvement and healthcare governance, including Donabedian\u0026rsquo;s model and MUSIQ\u0026sup1;⁸. These frameworks emphasize the importance of organizational context in sustaining improvement.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eImplications for policy, practice and research\u003c/h2\u003e \u003cp\u003eOrganizational maturity models can support structured quality governance and guide decision-making. They provide a framework for prioritizing improvement initiatives and inform system-level strategies in middle-income settings. Future studies should further test the applicability, reliability and validity of maturity assessment tools across different hospital settings and health systems.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOrganizational maturity models represent a useful approach for monitoring and guiding quality improvement processes in hospitals. These findings highlight the potential of maturity-based approaches as scalable tools for strengthening quality governance in resource-constrained health systems.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDisclosure of Interest \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo potential competing interest was reported by the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDonabedian A. Evaluating the quality of medical care. Milbank Q. 1966;44(3):166-206.\u003c/li\u003e\n\u003cli\u003eDonabedian A. The quality of care: how can it be assessed? JAMA. 1988;260(12):1743-1748.\u003c/li\u003e\n\u003cli\u003eBerwick DM. A primer on leading the improvement of systems. BMJ. 1996;312:619-622.\u003c/li\u003e\n\u003cli\u003eBatalden PB, Davidoff F. What is quality improvement and how can it transform healthcare? Qual Saf Health Care. 2007;16(1):2-3.\u003c/li\u003e\n\u003cli\u003eLangley GJ, Moen R, Nolan KM, Nolan TW, Norman CL, Provost LP. The Improvement Guide. 2nd ed. San Francisco: Jossey-Bass; 2009.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Quality of Care: A Process for Making Strategic Choices in Health Systems. Geneva: WHO; 2006.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization, OECD, World Bank. Delivering Quality Health Services: A Global Imperative for Universal Health Coverage. Geneva: WHO; 2018.\u003c/li\u003e\n\u003cli\u003eInstitute of Medicine. Crossing the Quality Chasm. Washington: National Academy Press; 2001.\u003c/li\u003e\n\u003cli\u003eInstitute of Medicine. To Err Is Human. Washington: National Academy Press; 2000.\u003c/li\u003e\n\u003cli\u003ePorter ME. What is value in health care? N Engl J Med. 2010;363(26):2477-2481.\u003c/li\u003e\n\u003cli\u003eBraithwaite J, Shaw CD, Moldovan M, Greenfield D, Hinchcliff R, Mumford V, et al. Comparison of health service accreditation programs. Int J Qual Health Care. 2012;24(6):568-577.\u003c/li\u003e\n\u003cli\u003eGreenfield D, Braithwaite J. Health sector accreditation research: a systematic review. Int J Qual Health Care. 2008;20(3):172-183.\u003c/li\u003e\n\u003cli\u003eShaw CD. Toolkit for accreditation programs. Int J Qual Health Care. 2004;16 Suppl 1:i67-i72.\u003c/li\u003e\n\u003cli\u003eShaw CD, Groene O, Mora N, Sunol R. Accreditation and ISO certification in healthcare. Int J Qual Health Care. 2010;22(6):445-451.\u003c/li\u003e\n\u003cli\u003ePomey MP, Contandriopoulos AP, Francois P, Bertrand D. Accreditation: a tool for organizational change in hospitals? Int J Health Care Qual Assur. 2004;17(3):113-124.\u003c/li\u003e\n\u003cli\u003eFlodgren G, Pomey MP, Taber SA, Eccles MP. Effectiveness of external inspection of compliance with standards. Cochrane Database Syst Rev. 2011;(11):CD008992.\u003c/li\u003e\n\u003cli\u003eKringos DS, Sunol R, Wagner C, Mannion R, Michel P, Klazinga NS, et al. The influence of context on quality improvement success. BMC Health Serv Res. 2015;15:277.\u003c/li\u003e\n\u003cli\u003eKaplan HC, Provost LP, Froehle CM, Margolis PA. The Model for Understanding Success in Quality (MUSIQ). BMJ Qual Saf. 2012;21(1):13-20.\u003c/li\u003e\n\u003cli\u003eBraithwaite J, Churruca K, Long JC, Ellis LA, Herkes J. When complexity science meets implementation science. BMC Med. 2018;16:63.\u003c/li\u003e\n\u003cli\u003eOvretveit J. Leading improvement effectively: review of research. Int J Health Care Qual Assur. 2009;22(5):439-448.\u003c/li\u003e\n\u003cli\u003eShortell SM, Bennett CL, Byck GR. Assessing the impact of continuous quality improvement on clinical practice. Milbank Q. 1998;76(4):593-624.\u003c/li\u003e\n\u003cli\u003eGreenhalgh T, Robert G, Macfarlane F, Bate P, Kyriakidou O. Diffusion of innovations in service organizations. Milbank Q. 2004;82(4):581-629.\u003c/li\u003e\n\u003cli\u003eDixon-Woods M, Martin GP. Does quality improvement improve quality? Future Hosp J. 2016;3(3):191-194.\u003c/li\u003e\n\u003cli\u003eLeatherman S, Sutherland K. The Quest for Quality in the NHS. London: Nuffield Trust; 2008.\u003c/li\u003e\n\u003cli\u003eBraithwaite J, Westbrook JI. The development of a national demonstration project on quality and safety. Med J Aust. 2011;194(7):343-344.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Hospital Santa Barbara","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":"Quality improvement, Quality of care, Organizational governance, Hospitals, Health services research","lastPublishedDoi":"10.21203/rs.3.rs-9673189/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9673189/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo analyze the evolution of organizational maturity and its role in supporting quality governance in a Brazilian hospital.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA longitudinal organizational study was conducted using a structured maturity assessment tool applied between 2020 and 2023. The instrument evaluated subsections across four domains: governance, patient care, diagnostics and therapeutics, and support services. A composite maturity index was calculated based on mean subsection scores. K-means cluster analysis was applied to standardized temporal trajectories to identify patterns of institutional development.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe global maturity index increased from 0.279 in 2020 to 0.580 in 2023, representing an absolute increase of 0.301 (107.9% relative increase). Domain-level maturity in 2023 was highest in governance (0.619) and lowest in support services (0.510). Cluster analysis identified five distinct patterns of development, indicating heterogeneous trajectories across organizational domains. The greatest improvements were observed in pharmaceutical care, infection prevention and control, supply chain management, neonatal care, and specialized diagnostic services.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOrganizational maturity models can support data-driven quality governance and improve decision-making processes in healthcare organizations.\u003c/p\u003e","manuscriptTitle":"Organizational Maturity as a Tool for Quality Governance: A Longitudinal Study in a Brazilian Hospital","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-12 14:36:42","doi":"10.21203/rs.3.rs-9673189/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":"f3afd10a-bd8f-4868-884e-cd6f0198bfaa","owner":[],"postedDate":"May 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":68002142,"name":"Health Policy"},{"id":68002143,"name":"Management"},{"id":68002144,"name":"Health Economics \u0026 Outcomes Research"}],"tags":[],"updatedAt":"2026-05-12T14:36:42+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-12 14:36:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9673189","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9673189","identity":"rs-9673189","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}