The Rise and Risks of Medicare Advantage "Affinity Plans".

This Viewpoint discusses the proliferation of Medicare Advantage plans targeting specific groups of individuals and whether these plans will improve quality of care for beneficiaries.

Measuring Equity in Readmission as a Distinct Assessment of Hospital Performance.

Importance: Equity is an essential domain of health care quality. The Centers for Medicare & Medicaid Services (CMS) developed 2 Disparity Methods that together assess equity in clinical outcomes. Objectives: To define a measure of equitable readmissions; identify hospitals with equitable readmissions by insurance (dual eligible vs non-dual eligible) or patient race (Black vs White); and compare hospitals with and without equitable readmissions by hospital characteristics and performance on accountability measures (quality, cost, and value). Design, Setting, and Participants: Cross-sectional study of US hospitals eligible for the CMS Hospital-Wide Readmission measure using Medicare data from July 2018 through June 2019. Main Outcomes and Measures: We created a definition of equitable readmissions using CMS Disparity Methods, which evaluate hospitals on 2 methods: outcomes for populations at risk for disparities (across-hospital method); and disparities in care within hospitals' patient populations (within-a-single-hospital method). Exposures: Hospital patient demographics; hospital characteristics; and 3 measures of hospital performance-quality, cost, and value (quality relative to cost). Results: Of 4638 hospitals, 74% served a sufficient number of dual-eligible patients, and 42% served a sufficient number of Black patients to apply CMS Disparity Methods by insurance and race. Of eligible hospitals, 17% had equitable readmission rates by insurance and 30% by race. Hospitals with equitable readmissions by insurance or race cared for a lower percentage of Black patients (insurance, 1.9% [IQR, 0.2%-8.8%] vs 3.3% [IQR, 0.7%-10.8%], P < .01; race, 7.6% [IQR, 3.2%-16.6%] vs 9.3% [IQR, 4.0%-19.0%], P = .01), and differed from nonequitable hospitals in multiple domains (teaching status, geography, size; P < .01). In examining equity by insurance, hospitals with low costs were more likely to have equitable readmissions (odds ratio, 1.57 [95% CI, 1.38-1.77), and there was no relationship between quality and value, and equity. In examining equity by race, hospitals with high overall quality were more likely to have equitable readmissions (odds ratio, 1.14 [95% CI, 1.03-1.26]), and there was no relationship between cost and value, and equity. Conclusion and Relevance: A minority of hospitals achieved equitable readmissions. Notably, hospitals with equitable readmissions were characteristically different from those without. For example, hospitals with equitable readmissions served fewer Black patients, reinforcing the role of structural racism in hospital-level inequities. Implementation of an equitable readmission measure must consider unequal distribution of at-risk patients among hospitals.

A Nationwide Network of Health AI Assurance Laboratories.

Importance: Given the importance of rigorous development and evaluation standards needed of artificial intelligence (AI) models used in health care, nationwide accepted procedures to provide assurance that the use of AI is fair, appropriate, valid, effective, and safe are urgently needed. Observations: While there are several efforts to develop standards and best practices to evaluate AI, there is a gap between having such guidance and the application of such guidance to both existing and new AI models being developed. As of now, there is no publicly available, nationwide mechanism that enables objective evaluation and ongoing assessment of the consequences of using health AI models in clinical care settings. Conclusion and Relevance: The need to create a public-private partnership to support a nationwide health AI assurance labs network is outlined here. In this network, community best practices could be applied for testing health AI models to produce reports on their performance that can be widely shared for managing the lifecycle of AI models over time and across populations and sites where these models are deployed.

Changes in Hospital Adverse Events and Patient Outcomes Associated With Private Equity Acquisition.

Importance: The effects of private equity acquisitions of US hospitals on the clinical quality of inpatient care and patient outcomes remain largely unknown. Objective: To examine changes in hospital-acquired adverse events and hospitalization outcomes associated with private equity acquisitions of US hospitals. Design, Setting, and Participants: Data from 100% Medicare Part A claims for 662 095 hospitalizations at 51 private equity-acquired hospitals were compared with data for 4 160 720 hospitalizations at 259 matched control hospitals (not acquired by private equity) for hospital stays between 2009 and 2019. An event study, difference-in-differences design was used to assess hospitalizations from 3 years before to 3 years after private equity acquisition using a linear model that was adjusted for patient and hospital attributes. Main Outcomes and Measures: Hospital-acquired adverse events (synonymous with hospital-acquired conditions; the individual conditions were defined by the US Centers for Medicare & Medicaid Services as falls, infections, and other adverse events), patient mix, and hospitalization outcomes (including mortality, discharge disposition, length of stay, and readmissions). Results: Hospital-acquired adverse events (or conditions) were observed within 10 091 hospitalizations. After private equity acquisition, Medicare beneficiaries admitted to private equity hospitals experienced a 25.4% increase in hospital-acquired conditions compared with those treated at control hospitals (4.6 [95% CI, 2.0-7.2] additional hospital-acquired conditions per 10 000 hospitalizations, P = .004). This increase in hospital-acquired conditions was driven by a 27.3% increase in falls (P = .02) and a 37.7% increase in central line-associated bloodstream infections (P = .04) at private equity hospitals, despite placing 16.2% fewer central lines. Surgical site infections doubled from 10.8 to 21.6 per 10 000 hospitalizations at private equity hospitals despite an 8.1% reduction in surgical volume; meanwhile, such infections decreased at control hospitals, though statistical precision of the between-group comparison was limited by the smaller sample size of surgical hospitalizations. Compared with Medicare beneficiaries treated at control hospitals, those treated at private equity hospitals were modestly younger, less likely to be dually eligible for Medicare and Medicaid, and more often transferred to other acute care hospitals after shorter lengths of stay. In-hospital mortality (n = 162 652 in the population or 3.4% on average) decreased slightly at private equity hospitals compared with the control hospitals; there was no differential change in mortality by 30 days after hospital discharge. Conclusions and Relevance: Private equity acquisition was associated with increased hospital-acquired adverse events, including falls and central line-associated bloodstream infections, along with a larger but less statistically precise increase in surgical site infections. Shifts in patient mix toward younger and fewer dually eligible beneficiaries admitted and increased transfers to other hospitals may explain the small decrease in in-hospital mortality at private equity hospitals relative to the control hospitals, which was no longer evident 30 days after discharge. These findings heighten concerns about the implications of private equity on health care delivery.

Actualización 2022 de los indicadores para la calidad asistencial y la atención farmacéutica a las personas que viven con el virus de la inmunodeficiencia humana / 2022 update of the indicators for quality of care and pharmaceutical care for people living with human immunodeficiency virus

Objetivo: actualizar y definir los indicadores para la mejora de la calidad asistencial y la atención farmacéutica a las personas que viven con infección por VIH en España. Método: el presente proyecto, que actualiza la versión anterior del documento de 2013, se desarrolló en 4 fases de trabajo realizadas entre enero y junio de 2022.En la fase 1, de organización, se creó un grupo de trabajo conformado por 7 especialistas en farmacia hospitalaria con amplia experiencia en atención farmacéutica y procedentes de distintos servicios del territorio nacional. Adicionalmente otros 34 especialistas, participaron en la valoración de los indicadores a través de 2 rondas de evaluación online para generación del consenso.Para la fase 2, inicialmente, se llevó a cabo una revisión bibliográfica con el objetivo de establecer una base a partir de la cual poder definir una propuesta de criterios de calidad e indicadores. A continuación, se realizó una propuesta preliminar de criterios y se establecieron revisiones para su ajuste en varias reuniones de trabajo telemáticas.En la fase 3 se estableció el consenso basado en la metodología de consenso Delphi-Rand/UCLA.Adicionalmente todos los indicadores clasificados como adecuados y necesarios fueron agrupados según 2 niveles de recomendación de monitorización, de manera que pueda orientar a los servicios en la prioridad de su medición: claves y avanzados.Por último, en la fase 4 se elaboró el documento final del proyecto, junto con las fichas descriptivas correspondientes para cada indicador con la finalidad de facilitar su medición y evaluación por parte de los servicios de farmacia hospitalaria. Resultados: se obtuvo un listado consensuado de ítems conformado por 79 indicadores adecuados y necesarios que permiten establecer un seguimiento y monitorización de la calidad y actividad de la atención farmacéutica a las personas que viven con VIH. De los mismos, 60 fueron establecidos como clave y 19 avanzados. Conclusiones: (AU)

Objective: To update and define indicators for improving the quality of care and pharmaceutical care for people living with HIV infection in Spain. Method: The present project, which updates the previous version of the 2013 document, was developed in four work phases carried out between January and June 2022.In phase 1, the organization phase, a working group was created, made up of seven hospital pharmacy specialists with extensive experience in pharmaceutical care and from different SFHs in Spain. In addition, another 34 specialists participated in the evaluation of the indicators through two rounds of online evaluation to generate consensus.For phase 2, initially, a review of the identified reference literature was carried out with the aim of establishing a basis from which to define a proposal for quality criteria and indicators. Then, a preliminary proposal of criteria was made and revisions were established for their adjustment in several telematic work meetings.In phase 3, consensus was established based on the Delphi-Rand/UCLA consensus methodology.In addition, all the indicators classified as appropriate and necessary were grouped according to two levels of monitoring recommendation, so as to guide the hospital pharmacy services in the priority of their measurement: key and advanced.Finally, in phase 4, the final project document was prepared, along with the corresponding descriptive sheets for each indicator in order to facilitate the measurement and evaluation of the indicators by the hospital pharmacy services. Results: Following the consensus methodology used, a list of items made up of 79 appropriate and necessary indicators was drawn up to establish a follow-up and monitoring of the quality and activity of pharmaceutical care for people living with HIV. Of these, 60 were established as key and 19 advanced. Conclusions ... (AU)

Disentangling the Role of Health Care Systems in Producing High-Quality Care.

This Viewpoint examines in-depth 5 features of health care systems that may influence quality of care: pooled resources, centralization, standardization, interprovider coordination, and cross-practice learning.

Organization and Performance of US Health Systems.

Importance: Health systems play a central role in the delivery of health care, but relatively little is known about these organizations and their performance. Objective: To (1) identify and describe health systems in the United States; (2) assess differences between physicians and hospitals in and outside of health systems; and (3) compare quality and cost of care delivered by physicians and hospitals in and outside of health systems. Evidence Review: Health systems were defined as groups of commonly owned or managed entities that included at least 1 general acute care hospital, 10 primary care physicians, and 50 total physicians located within a single hospital referral region. They were identified using Centers for Medicare & Medicaid Services administrative data, Internal Revenue Service filings, Medicare and commercial claims, and other data. Health systems were categorized as academic, public, large for-profit, large nonprofit, or other private systems. Quality of preventive care, chronic disease management, patient experience, low-value care, mortality, hospital readmissions, and spending were assessed for Medicare beneficiaries attributed to system and nonsystem physicians. Prices for physician and hospital services and total spending were assessed in 2018 commercial claims data. Outcomes were adjusted for patient characteristics and geographic area. Findings: A total of 580 health systems were identified and varied greatly in size. Systems accounted for 40% of physicians and 84% of general acute care hospital beds and delivered primary care to 41% of traditional Medicare beneficiaries. Academic and large nonprofit systems accounted for a majority of system physicians (80%) and system hospital beds (64%). System hospitals were larger than nonsystem hospitals (67% vs 23% with >100 beds), as were system physician practices (74% vs 12% with >100 physicians). Performance on measures of preventive care, clinical quality, and patient experience was modestly higher for health system physicians and hospitals than for nonsystem physicians and hospitals. Prices paid to health system physicians and hospitals were significantly higher than prices paid to nonsystem physicians and hospitals (12%-26% higher for physician services, 31% for hospital services). Adjusting for practice size attenuated health systems differences on quality measures, but price differences for small and medium practices remained large. Conclusions and Relevance: In 2018, health system physicians and hospitals delivered a large portion of medical services. Performance on clinical quality and patient experience measures was marginally better in systems but spending and prices were substantially higher. This was especially true for small practices. Small quality differentials combined with large price differentials suggests that health systems have not, on average, realized their potential for better care at equal or lower cost.

Efficiency of the Japanese Hospitalist System for Patients with Urinary Tract Infection: A Propensity-matched Analysis.

Objective The hospitalist system in the United States has been considered successful in terms of the quality of care and cost effectiveness. In Japan, however, its efficacy has not yet been extensively examined. This study examined the impact of the hospitalist system on the quality of care and healthcare economics in a Japanese population using treatment of urinary tract infection as an example. Methods We analyzed 271 patients whose most resource-consuming diagnosis at admission was urinary tract infection between April 2017 and March 2019. Propensity-matched analyses were performed to compare health care economics and the quality of care between the hospitalist system and the conventional system. Results In matched pairs, care by the hospitalist system was associated with a significantly shorter length of stay than that by the conventional system. The quality of care (oral antibiotics switch rate, rate of appropriate antibiotics change based on urine or blood culture results, detection rate of urinary tract infection etiology and the number of laboratory tests) was also considered to be favorably impacted by the hospitalist system. Although not statistically significant, hospital costs tended to be lower with the hospitalist system than with the conventional system. The mortality rate and 30-day readmission were also not significantly different between the groups. Conclusion The hospitalist system had a favorable impact on the quality of care and length of stay without increasing readmission in patients with urinary tract infection. This study is further evidence of the strong potential for the positive impact of an implemented hospitalist system in Japan.

Estrategias de mejora de calidad en lactancia en recién nacidos muy bajo peso: revisión del tema / Breastfeeding quality improvement strategies in very low birth weight newborns / Revisao das estratégias de melhoria da qualidade na amamentação de recém-nascidos de muito baixo peso

El abordaje nutricional en los recién nacidos de muy bajo peso al nacimiento constituye un desafío en la práctica clínica de los neonatólogos, y muchas veces se aborda fuera del período crítico. Existe evidencia contundente de que la optimización nutricional precoz impacta en forma directamente proporcional en la sobrevida y sobrevida sin morbilidades mayores para este grupo. La implementación de lactancia materna precoz en este contexto debe ser una prioridad del equipo asistencial, siendo la mejora de calidad una herramienta de demostrada utilidad para mejorar los resultados en términos de mortalidad y morbilidad neonatal.

The nutritional approach of the very low birth weight infant poses a great challenge to most neonatologists in their clinical practice, and it is frequently delayed until de newborn is in stable clinical conditions. Currently, scientific evidence supports that early nutritional optimization impacts directly on this group's survival and on their survival without major morbidities. Initiatives fostering early breastfeeding should be prioritized by the healthcare team. Quality improvement has shown to be a very useful resource to improve outcomes regarding neonatal mortality and morbidities.

A abordagem nutricional do recém-nascido de muito baixo peso representa um grande desafio para a maioria dos neonatologistas em sua prática clínica, sendo frequentemente postergada até que o recém-nascido esteja em condições clínicas estáveis. Atualmente, evidências científicas sustentam que a otimização nutricional precoce impacta diretamente na sobrevivência desse grupo e na sobrevivência sem maiores morbidades. Iniciativas de incentivo ao aleitamento materno precoce devem ser priorizadas pela equipe de saúde. A melhoria da qualidade tem se mostrado um recurso muito útil para melhorar os desfechos em relação à mortalidade e morbidades neonatais.

Association Between Individual Primary Care Physician Merit-based Incentive Payment System Score and Measures of Process and Patient Outcomes.

Importance: The Medicare Merit-based Incentive Payment System (MIPS) influences reimbursement for hundreds of thousands of US physicians, but little is known about whether program performance accurately captures the quality of care they provide. Objective: To examine whether primary care physicians' MIPS scores are associated with performance on process and outcome measures. Design, Setting, and Participants: Cross-sectional study of 80 246 US primary care physicians participating in the MIPS program in 2019. Exposures: MIPS score. Main Outcomes and Measures: The association between physician MIPS scores and performance on 5 unadjusted process measures, 6 adjusted outcome measures, and a composite outcome measure. Results: The study population included 3.4 million patients attributed to 80 246 primary care physicians, including 4773 physicians with low MIPS scores (≤30), 6151 physicians with medium MIPS scores (>30-75), and 69 322 physicians with high MIPS scores (>75). Compared with physicians with high MIPS scores, physicians with low MIPS scores had significantly worse mean performance on 3 of 5 process measures: diabetic eye examinations (56.1% vs 63.2%; difference, -7.1 percentage points [95% CI, -8.0 to -6.2]; P < .001), diabetic HbA1c screening (84.6% vs 89.4%; difference, -4.8 percentage points [95% CI, -5.4 to -4.2]; P < .001), and mammography screening (58.2% vs 70.4%; difference, -12.2 percentage points [95% CI, -13.1 to -11.4]; P < .001) but significantly better mean performance on rates of influenza vaccination (78.0% vs 76.8%; difference, 1.2 percentage points [95% CI, 0.0 to 2.5]; P = .045] and tobacco screening (95.0% vs 94.1%; difference, 0.9 percentage points [95% CI, 0.3 to 1.5]; P = .001). MIPS scores were inconsistently associated with risk-adjusted patient outcomes: compared with physicians with high MIPS scores, physicians with low MIPS scores had significantly better mean performance on 1 outcome (307.6 vs 316.4 emergency department visits per 1000 patients; difference, -8.9 [95% CI, -13.7 to -4.1]; P < .001), worse performance on 1 outcome (255.4 vs 225.2 all-cause hospitalizations per 1000 patients; difference, 30.2 [95% CI, 24.8 to 35.7]; P < .001), and did not have significantly different performance on 4 ambulatory care-sensitive admission outcomes. Nineteen percent of physicians with low MIPS scores had composite outcomes performance in the top quintile, while 21% of physicians with high MIPS scores had outcomes in the bottom quintile. Physicians with low MIPS scores but superior outcomes cared for more medically complex and socially vulnerable patients, compared with physicians with low MIPS scores and poor outcomes. Conclusions and Relevance: Among US primary care physicians in 2019, MIPS scores were inconsistently associated with performance on process and outcome measures. These findings suggest that the MIPS program may be ineffective at measuring and incentivizing quality improvement among US physicians.

Are Patient Satisfaction Instruments Harming Both Patients and Physicians?

In this Viewpoint, Richman and Schulman argue that patient satisfaction surveys may not actually reflect clinical performance or assist efforts to improve patient experience and are not useful tools to measure physician performance.

Protocol for an intervention development and pilot implementation evaluation study of an e-health solution to improve newborn care quality and survival in two low-resource settings, Malawi and Zimbabwe: Neotree.

INTRODUCTION: Every year 2.4 million deaths occur worldwide in babies younger than 28 days. Approximately 70% of these deaths occur in low-resource settings because of failure to implement evidence-based interventions. Digital health technologies may offer an implementation solution. Since 2014, we have worked in Bangladesh, Malawi, Zimbabwe and the UK to develop and pilot Neotree: an android app with accompanying data visualisation, linkage and export. Its low-cost hardware and state-of-the-art software are used to improve bedside postnatal care and to provide insights into population health trends, to impact wider policy and practice. METHODS AND ANALYSIS: This is a mixed methods (1) intervention codevelopment and optimisation and (2) pilot implementation evaluation (including economic evaluation) study. Neotree will be implemented in two hospitals in Zimbabwe, and one in Malawi. Over the 2-year study period clinical and demographic newborn data will be collected via Neotree, in addition to behavioural science informed qualitative and quantitative implementation evaluation and measures of cost, newborn care quality and usability. Neotree clinical decision support algorithms will be optimised according to best available evidence and clinical validation studies. ETHICS AND DISSEMINATION: This is a Wellcome Trust funded project (215742_Z_19_Z). Research ethics approvals have been obtained: Malawi College of Medicine Research and Ethics Committee (P.01/20/2909; P.02/19/2613); UCL (17123/001, 6681/001, 5019/004); Medical Research Council Zimbabwe (MRCZ/A/2570), BRTI and JREC institutional review boards (AP155/2020; JREC/327/19), Sally Mugabe Hospital Ethics Committee (071119/64; 250418/48). Results will be disseminated via academic publications and public and policy engagement activities. In this study, the care for an estimated 15 000 babies across three sites will be impacted. TRIAL REGISTRATION NUMBER: NCT0512707; Pre-results.

Assessing a New Prescreening Score for the Simplified Evaluation of the Clinical Quality and Relevance of eHealth Apps: Instrument Validation Study.

BACKGROUND: In 2020, more than 250 eHealth solutions were added to app stores each day, or 90,000 in the year; however, the vast majority of these solutions have not undergone clinical validation, their quality is unknown, and the user does not know if they are effective and safe. We sought to develop a simple prescreening scoring method that would assess the quality and clinical relevance of each app. We designed this tool with 3 health care stakeholder groups in mind: eHealth solution designers seeking to evaluate a potential competitor or their own tool, investors considering a fundraising candidate, and a hospital clinician or IT department wishing to evaluate a current or potential eHealth solution. OBJECTIVE: We built and tested a novel prescreening scoring tool (the Medical Digital Solution scoring tool). The tool, which consists of 26 questions that enable the quick assessment and comparison of the clinical relevance and quality of eHealth apps, was tested on 68 eHealth solutions. METHODS: The Medical Digital Solution scoring tool is based on the 2021 evaluation criteria of the French National Health Authority, the 2022 European Society of Medical Oncology recommendations, and other provided scores. We built the scoring tool with patient association and eHealth experts and submitted it to eHealth app creators, who evaluated their apps via the web-based form in January 2022. After completing the evaluation criteria, their apps obtained an overall score and 4 categories of subscores. These criteria evaluated the type of solution and domain, the solution's targeted population size, the level of clinical assessment, and information about the provider. RESULTS: In total, 68 eHealth solutions were evaluated with the scoring tool. Oncology apps (22%, 20/90) and general health solutions (23%, 21/90) were the most represented. Of the 68 apps, 32 (47%) were involved in remote monitoring by health professionals. Regarding clinical outcomes, 5% (9/169) of the apps assessed overall survival. Randomized studies had been conducted for 21% (23/110) of the apps to assess their benefit. Of the 68 providers, 38 (56%) declared the objective of obtaining reimbursement, and 7 (18%) out of the 38 solutions seeking reimbursement were assessed as having a high probability of reimbursement. The median global score was 11.2 (range 4.7-17.4) out of 20 and the distribution of the scores followed a normal distribution pattern (Shapiro-Wilk test: P=.33). CONCLUSIONS: This multidomain prescreening scoring tool is simple, fast, and can be deployed on a large scale to initiate an assessment of the clinical relevance and quality of a clinical eHealth app. This simple tool can help a decision-maker determine which aspects of the app require further analysis and improvement.

Evaluación de la satisfacción de servicios de salud prestados en unidades del primer nivel de atención / Evaluation of the Satisfaction with the Healthcare Services Provided in First-Level Units

Introducción: La calidad en la prestación de servicios de salud en el primer nivel de atención constituye una de las prioridades de las autoridades de salud a nivel mundial. Lograr un servicio con calidad y calidez constituye la premisa a lograr. Objetivo: Evaluar la satisfacción de usuarios y prestadores en relación con los servicios de salud prestados en unidades del primer nivel de atención de la ciudad de Riobamba, Chimborazo. Ecuador. Métodos: Investigación básica, no experimental, con enfoque descriptivo y explicativo. Muestra constituida por un total de 427 usuarios y 113 prestadores de salud, a quienes se les aplicó un cuestionario para conocer su nivel de satisfacción. Resultados: Promedio de edad de los usuarios de 48,57 años, con predominio de personas femeninas (67,45 por ciento), nivel económico bajo (67,68 por ciento) y trabajadores (34,66 por ciento). En relación con los prestadores, el promedio de edad fue de 36,18 años, con predominio de féminas (71,6 por ciento) y de personal de servicio (33,63 por ciento). La satisfacción de los usuarios fue media en cuanto a la tangibilidad (media de 3,25) y la garantía (3,00) y baja en capacidad de respuesta (2,75), confiabilidad (2,60) y empatía (2,60). La satisfacción de usuarios fue media en organización enfocada al cliente (3,38) y enfoque de procesos (3,05) y baja en relación con comunicación (2,90), liderazgo (2,84) y mejora continua (2,63). Conclusiones: El nivel de satisfacción de los usuarios y prestadores identificado puede considerarse bajo. Este resultado muestra la necesidad de identificar los factores que están incidiendo negativamente en la calidad del servicio(AU)

Introduction: Quality of health services provision at the first level of care is one of the priorities set by health authorities worldwide. The goal is to provide service with quality and warmth. Objective: To evaluate the satisfaction of users and providers regarding the health services provided at first-level healthcare units in Riobamba City, Chimborazo Province, Ecuador. Methods: A basic and nonexperimental research with a descriptive and explanatory approach was carried out. The sample consisted of a total of 427 users and 113 healthcare providers, to whom a questionnaire was applied in order to determine their level of satisfaction. Results: The average age of the users was 48.57 years, with a predominance of women (67.45 percent), low economic level (67.68 percent) and workers (34.66 percent). Regarding the providers, the average age was 36.18 years, with a predominance of women (71.68 percent) and service personnel (33.63 percent). User satisfaction was fair in tangibility (mean of 3.25) and guarantee (3.00), while being low in responsiveness (2.75), reliability (2.60) and empathy (2.60). User satisfaction was fair in customer-focused organization (3.38) and process focus (3.05), while being low in communication (2.90), leadership (2.84) and continuous improvement (2.63). Conclusions: The level of satisfaction of the identified users and providers can be considered low. This result shows the need to identify the factors that are affecting the quality of service negatively(AU)