Cultura de segurança em unidades de terapia intensiva na perspectiva da equipe multiprofissional: Estudo multicêntrico / Cultura de seguridad en unidades de terapia intensiva en la perspectiva del equipo multiprofesional: Estudio multicéntrico / Safety Culture in intensive care units from multiprofessional team perspective: A multicenter study

Resumo Introdução: A Cultura de Segurança do Paciente é considerada um importante componente estrutural dos serviços, que favorece a implantação de práticas seguras e a diminuição da ocorrência de eventos adversos. Objetivo: Identificar os fatores associados à cultura de segurança do paciente nas unidades de terapia intensiva adulto em hospitais de grande porte da região Sudeste do Brasil. Método: Estudo transversal do tipo survey e multicêntrico. Participaram 168 profissionais de saúde de quatro unidades (A, B, C e D) de terapia intensiva adulto. Foi utilizado o questionário "Hospital Survey on Patient Safety Culture". Considerou-se como variável dependente o nível de cultura de segurança do paciente e variáveis independentes aspectos sociodemográficos e laborais. Foram usadas estatísticas descritivas e para a análise dos fatores associados foi elaborado um modelo de regressão logística múltipla. Resultados: Identificou-se associação entre tipo de hospital com onze dimensões da cultura de segurança, quanto à função a categoria profissional médico, técnico de enfermagem e enfermeiro foram relacionadas com três dimensões; o gênero com duas dimensões e tempo de atuação no setor com uma dimensão. Conclusão: Evidenciou-se que o tipo de hospital, categoria profissional, tempo de atuação no setor e gênero foram associados às dimensões de cultura de segurança do paciente.

Resumen Introducción: La cultura de seguridad del paciente se considera un componente estructural importante de los servicios, que favorece la aplicación de prácticas seguras y la reducción de la aparición de acontecimientos adversos. Objetivo: Identificar los factores asociados a la cultura de seguridad del paciente en unidades de terapia intensiva adulto en hospitales de la región Sudeste del Brasil. Metodología: Estudio transversal de tipo encuesta y multicéntrico. Participaron 168 profesionales de salud de cuatro unidades (A, B, C y D) de terapia intensiva adulto. Se utilizó el cuestionario "Hospital Survey on Patient Safety Culture". Se consideró como variable dependiente el nivel de cultura de seguridad del paciente y variables independientes los aspectos sociodemográficos y laborales. Fueron usadas estadísticas descriptivas y, para analizar los factores asociados, fue elaborado un modelo de regresión logística múltiple. Resultados: Se identificó asociación entre tipo de hospital con once dimensiones de cultura de seguridad del paciente. En relación a la función, personal médico, técnicos de enfermería y personal de enfermería fueron asociados con tres dimensiones, el género con dos dimensiones y tiempo de actuación con una dimensión en el modelo de regresión. Conclusión: Se evidenció que el tipo de hospital, función, tiempo de actuación en el sector y género fueron asociados a las dimensiones de la cultura de seguridad del paciente.

Abstract Introduction: Patient safety culture is considered an important structural component of the services, which promotes the implementation of safe practices and the reduction of adverse events. Objective: To identify the factors associated with patient safety culture in adult intensive care units in large hospitals in Belo Horizonte. Method: Cross-sectional survey and multicenter study. A total of 168 health professionals from four units (A, B, C and D) of adult intensive care participated. The questionnaire "Hospital Survey on Patient Safety Culture" was used. The patient's level of safety culture was considered as a dependent variable, and sociodemographic and labor aspects were the independent variables. Descriptive statistics were used and a multiple logistic regression model was developed to analyze the associated factors. Results: An association was identified between the type of hospital and eleven dimensions of the safety culture. In terms of function, the doctors, nursing technicians, and nurse were related to three dimensions; gender with two dimensions, and time working in the sector with one dimension. Conclusion: It was evidenced that the type of hospital, function, time working in the sector, and gender were associated with the dimensions of patient safety culture.

The first decade of the Danish Palliative Care Database: improvements and ongoing challenges in the quality and use of specialised palliative care.

BACKGROUND: Danish Palliative Care Database comprises five quality indicators: (1) Contact with specialised palliative care (SPC) among referred patients, (2) Waiting time of less than 10 days, (3) Proportion of patients who died from (A) cancer or (B) non-cancer diseases, and had contact with SPC, (4) Proportion of patients completing the patient-reported outcome measure at baseline (EORTC QLQ-C15-PAL), and (5) Proportion of patients discussed at a multidisciplinary conference. PURPOSE: To investigate changes in the quality indicators from 2010 until 2020 in cancer and non-cancer patients. Patients/material: Patients aged 18+ years who died from 2010 until 2020. METHOD: Register-based study with the Danish Palliative Care Database as the main data source. Indicator changes were reported as percentage fulfilment. RESULTS: From 2010 until 2020, the proportion of patients with non-cancer diseases in SPC increased slightly (2.5-7.2%). In 2019, fulfilment of the five indicators for cancer and non-cancer were: (1) 81% vs. 73%; (2) 73% vs. 68%; (3A) 50%; (3B) 2%; (4) 73% vs. 66%; (5) 73% vs. 65%. Whereas all other indicators improved, the proportion of patients waiting less than 10 days from referral to contact decreased. Differences between type of unit were found, mainly lower for hospice. INTERPRETATION: Most patients in SPC had cancer. All indicators except waiting time improved during the 10-year period. The establishment of the Danish Palliative Care Database may have contributed to the positive development; however, SPC in Denmark needs to be improved, especially regarding a reduction in waiting time and enhanced contact for non-cancer patients.

Medication adherence star ratings measures, health care resource utilization, and cost.

OBJECTIVE: To examine the association between missed CMS Star Ratings quality measures for medication adherence over 3 years for diabetes, hypertension, and hyperlipidemia medications (9 measures) and health care utilization and relative costs. STUDY DESIGN: Retrospective cohort study. METHODS: The study examined eligible patients who qualified for the diabetes, statin, and renin-angiotensin system antagonist medication adherence measures in 2018, 2019, and 2020 and were continuously enrolled in a Medicare Advantage prescription drug plan from 2017 through 2021. A total of 103,900 patients were divided into 4 groups based on the number of adherence measures missed (3 medication classes over 3 years): (1) missed 0 measures, (2) missed 1 measure, (3) missed 2 or 3 measures, and (4) missed 4 or more measures. To achieve a quality measure, patients had to meet the Pharmacy Quality Alliance 80% threshold of proportion of days covered during the calendar year. RESULTS: The mean age of the cohort was 71.1 years, and 49.9% were female. Compared with patients who missed 0 of 9 adherence measures, those who missed 1 measure, 2 or 3 measures, and 4 or more measures experienced 12% to 26%, 22% to 42%, and 24% to 50% increased risks, respectively, of all-cause and diabetes-related inpatient stays and all-cause and diabetes-related emergency department visits (all  P  values < .01). Additionally, patients who missed 1, 2 or 3, and 4 or more adherence measures experienced 14%, 19%, and 20% higher monthly medical costs, respectively. CONCLUSIONS: Missing Star Ratings quality measures for medication adherence was associated with an increased likelihood of health care resource utilization and increased costs for patients taking medications to treat diabetes, hypertension, and hyperlipidemia.

Colorectal cancer health and care quality indicators in a federated setting using the Personal Health Train.

OBJECTIVE: Hospitals and healthcare providers should assess and compare the quality of care given to patients and based on this improve the care. In the Netherlands, hospitals provide data to national quality registries, which in return provide annual quality indicators. However, this process is time-consuming, resource intensive and risks patient privacy and confidentiality. In this paper, we presented a multicentric 'Proof of Principle' study for federated calculation of quality indicators in patients with colorectal cancer. The findings suggest that the proposed approach is highly time-efficient and consume significantly lesser resources. MATERIALS AND METHODS: Two quality indicators are calculated in an efficient and privacy presevering federated manner, by i) applying the Findable Accessible Interoperable and Reusable (FAIR) data principles and ii) using the Personal Health Train (PHT) infrastructure. Instead of sharing data to a centralized registry, PHT enables analysis by sending algorithms and sharing only insights from the data. RESULTS: ETL process extracted data from the Electronic Health Record systems of the hospitals, converted them to FAIR data and hosted in RDF endpoints within each hospital. Finally, quality indicators from each center are calculated using PHT and the mean result along with the individual results plotted. DISCUSSION AND CONCLUSION: PHT and FAIR data principles can efficiently calculate quality indicators in a privacy-preserving federated approach and the work can be scaled up both nationally and internationally. Despite this, application of the methodology was largely hampered by ELSI issues. However, the lessons learned from this study can provide other hospitals and researchers to adapt to the process easily and take effective measures in building quality of care infrastructures.

Calculation of Overall Hospital Quality Star Ratings With and Without Inclusion of the Peer Grouping Step.

Importance: The Centers for Medicare & Medicaid Services (CMS) Overall Star Rating is widely used by patients and consumers, and there is continued stakeholder curiosity surrounding the inclusion of a peer grouping step, implemented to the 2021 Overall Star Rating methods. Objective: To calculate hospital star rating scores with and without the peer grouping step, with the former approach stratifying hospitals into 3-, 4-, and 5-measure group peer groups based on the number of measure groups with at least 3 reported measures. Design, Setting, and Participants: This cross-sectional study used Care Compare website data from January 2023 for 3076 hospitals that received a star rating in 2023. Data were analyzed from April 2023 to December 2023. Exposure: Peer grouping vs no peer grouping. Main Outcomes and Measures: The primary outcome was the distribution of star ratings, with 1 star being the lowest-performing hospitals and 5 stars, the highest. Analyses additionally identified the number of hospitals with a higher, lower, or identical star rating with the use of the peer grouping step compared with its nonuse, stratified by certain hospital characteristics. Results: Among 3076 hospitals that received a star rating in 2023, most were nonspecialty (1994 hospitals [64.8%]), nonteaching (1807 hospitals [58.7%]), non-safety net (2326 hospitals [75.6%]), non-critical access (2826 hospitals [91.9%]) hospitals with fewer than 200 beds (1822 hospitals [59.2%]) and located in an urban geographic designations (1935 hospitals [62.9%]). The presence of the peer grouping step resulted in 585 hospitals (19.0%) being assigned a different star rating than if the peer grouping step was absent, including considerably more hospitals receiving a higher star rating (517 hospitals) rather than a lower (68 hospitals) star rating. Hospital characteristics associated with a higher star rating included urbanicity (351 hospitals [67.9%]), non-safety net status (414 hospitals [80.1%]), and fewer than 200 beds (287 hospitals [55.6%]). Collectively, the presence of the peer grouping step supports a like-to-like comparison among hospitals and supports the ability of patients to assess overall hospital quality. Conclusions and Relevance: In this cross-sectional study, inclusion of the peer grouping in the CMS star rating method resulted in modest changes in hospital star ratings compared with application of the method without peer grouping. Given improvement in face validity and the close association between the current peer grouping approach and stakeholder needs for peer-comparison, the current CMS Overall Star Rating method allows for durable comparisons in hospital performance.

Assessing quality of hepato-pancreato-biliary surgery: nationwide benchmarking.

BACKGROUND: Clinical auditing is a powerful tool to evaluate and improve healthcare. Deviations from the expected quality of care are identified by benchmarking the results of individual hospitals using national averages. This study aimed to evaluate the use of quality indicators for benchmarking hepato-pancreato-biliary (HPB) surgery and when outlier hospitals could be identified. METHODS: A population-based study used data from two nationwide Dutch HPB audits (DHBA and DPCA) from 2014 to 2021. Sample size calculations determined the threshold (in percentage points) to identify centres as statistical outliers, based on current volume requirements (annual minimum of 20 resections) on a two-year period (2020-2021), covering mortality rate, failure to rescue (FTR), major morbidity rate and textbook/ideal outcome (TO) for minor liver resection (LR), major LR, pancreaticoduodenectomy (PD) and distal pancreatectomy (DP). RESULTS: In total, 10 963 and 7365 patients who underwent liver and pancreatic resection respectively were included. Benchmark and corresponding range of mortality rates were 0.6% (0 -3.2%) and 3.3% (0-16.7%) for minor and major LR, and 2.7% (0-7.0%) and 0.6% (0-4.2%) for PD and DP respectively. FTR rates were 5.4% (0-33.3%), 14.2% (0-100%), 7.5% (1.6%-28.5%) and 3.1% (0-14.9%). For major morbidity rate, corresponding rates were 9.8% (0-20.5%), 28.1% (0-47.1%), 36% (15.8%-58.3%) and 22.3% (5.2%-46.1%). For TO, corresponding rates were 73.6% (61.3%-94.4%), 54.1% (35.3-100), 46.8% (25.3%-59.4%) and 63.3% (30.7%-84.6%). Mortality rate thresholds indicating a significant outlier were 8.6% and 15.4% for minor and major LR and 14.2% and 8.6% for PD and DP. For FTR, these thresholds were 17.9%, 31.6%, 22.9% and 15.0%. For major morbidity rate, these thresholds were 26.1%, 49.7%, 57.9% and 52.9% respectively. For TO, lower thresholds were 52.5%, 32.5%, 25.8% and 41.4% respectively. Higher hospital volumes decrease thresholds to detect outliers. CONCLUSION: Current event rates and minimum volume requirements per hospital are too low to detect any meaningful between hospital differences in mortality rate and FTR. Major morbidity rate and TO are better candidates to use for benchmarking.

Putting the pieces together: towards an integrative framework for healthcare performance.

PURPOSE: In the past few decades, performance measuring systems have become important managerial tools for healthcare organizations. Healthcare performance metrics are a useful tool in understanding how healthcare organizations achieve their goals while satisfying the needs of their patients and conforming to national and international standards. Various efforts have been made to assess healthcare performance. Most of these measures are focused on a single perspective or developed by a single source to meet management and strategic objectives on time. DESIGN/METHODOLOGY/APPROACH: We develop a review of the literature to shed light on the measures used to assess performance in the healthcare sector at various points in time, as well as to establish a thorough understanding of healthcare performance measurement. FINDINGS: Developing real-time digital traceability of metrics and an integrative perspective that increases the actionability of information acquired is an attractive potential made possible by the introduction of new technologies and the digitization of data. ORIGINALITY/VALUE: We conclude that a proper measurement system should be one to combine patient, physician, non-medical staff and system perspective, which will further facilitate the assessment of healthcare performance and the comparative function.

Implementation of quality indicators for vulvar cancer in gynaecological cancer centres certified by the German Cancer Society (DKG).

PURPOSE: In 2018, the first guideline-based quality indicators (QI) for vulvar cancer were implemented in the data-sheets of certified gynaecological cancer centres. The certification process includes guideline-based QIs as a fundamental component. These indicators are specifically designed to evaluate the level of care provided within the centres. This article aims to give an overview of the developing process of guideline based-QIs for women with vulvar cancer and presents the QIs results from the certified gynaecological cancer centres. METHODS: The QIs were derived in a standardized multiple step process during the update of the 2015 S2k guideline "Diagnosis, Therapy, and Follow-Up Care of Vulvar Cancer and its Precursors" (registry-number: no. 015/059) and are based on strong recommendations. RESULTS: In total, there are eight guideline-based QIs for vulvar cancer. Four QIs are part of the certification process. In the treatment year 2021, 2.466 cases of vulvar cancer were treated in 177 centres. The target values in the centres for pathology reports on tumour resection and lymphadenectomy as well as sentinel lymph nodes have increased since the beginning of the certification process and have been above 90% over the past three treatment years (2019-2021). DISCUSSION: QIs based on strong guideline recommendations, play a crucial role in measuring and allowing to quantify essential aspects of patient care. By utilizing QIs, centres are able to identify areas for process optimization and draw informed conclusions. Over the years the quality of treatment of vulvar cancer patients measured by the QIs was improved. The certification system is continuously reviewed to enhance patient care even further by using the outcomes from QIs revaluation.

Is the QCI framework suited for monitoring outcomes and costs in a teaching hospital using value-based healthcare principles? A retrospective cohort study.

OBJECTIVES: The objective is to develop a pragmatic framework, based on value-based healthcare principles, to monitor health outcomes per unit costs on an institutional level. Subsequently, we investigated the association between health outcomes and healthcare utilisation costs. DESIGN: This is a retrospective cohort study. SETTING: A teaching hospital in Rotterdam, The Netherlands. PARTICIPANTS: The study was performed in two use cases. The bariatric population contained 856 patients of which 639 were diagnosed with morbid obesity body mass index (BMI) <45 and 217 were diagnosed with morbid obesity BMI ≥45. The breast cancer population contained 663 patients of which 455 received a lumpectomy and 208 a mastectomy. PRIMARY AND SECONDARY OUTCOME MEASURES: The quality cost indicator (QCI) was the primary measures and was defined asQCI = (resulting outcome * 100)/average total costs (per thousand Euros)where average total costs entail all healthcare utilisation costs with regard to the treatment of the primary diagnosis and follow-up care. Resulting outcome is the number of patients achieving textbook outcome (passing all health outcome indicators) divided by the total number of patients included in the care path. RESULTS: The breast cancer and bariatric population had the highest resulting outcome values in 2020 Q4, 0.93 and 0.73, respectively. The average total costs of the bariatric population remained stable (avg, €8833.55, min €8494.32, max €9164.26). The breast cancer population showed higher variance in costs (avg, €12 735.31 min €12 188.83, max €13 695.58). QCI values of both populations showed similar variance (0.3 and 0.8). Failing health outcome indicators was significantly related to higher hospital-based costs of care in both populations (p <0.01). CONCLUSIONS: The QCI framework is effective for monitoring changes in average total costs and relevant health outcomes on an institutional level. Health outcomes are associated with hospital-based costs of care.

Interventional analytics in skilled nursing facilities associated with reduced readmissions.

OBJECTIVE: To assess differences in longitudinal profiles for 30-day risk-adjusted readmission rates in skilled nursing facilities (SNFs) associated with Penn Medicine's Lancaster General Hospital (LGH) that implemented an interventional analytics (IA) platform vs other LGH facilities lacking IA vs other SNFs in Pennsylvania vs facilities in all other states. STUDY DESIGN: Retrospective longitudinal analysis of CMS readmissions data from 2017 through 2022, and cross-sectional analysis using CMS quality metrics data. METHODS: CMS SNF quality performance data were aggregated and compared with risk-adjusted readmissions by facility and time period. Each SNF was assigned to a cohort based on location, referral relationship with LGH, and whether it had implemented IA. Multivariable mixed effects modeling was used to compare readmissions by cohort, whereas quality measures from the fourth quarter of 2022 were compared descriptively. RESULTS: LGH profiles differed significantly from both state and national profiles, with LGH facilities leveraging IA demonstrating an even greater divergence. In the most recent 12 months ending in the fourth quarter of 2022, LGH SNFs with IA had estimated readmission rates that were 15.24, 12.30, and 13.06 percentage points lower than the LGH SNFs without IA, Pennsylvania, and national cohorts, respectively (all pairwise P < .0001). SNFs with IA also demonstrated superior CMS claims-based quality metric outcomes for the 12 months ending in the fourth quarter of 2022. CONCLUSIONS: SNFs implementing the studied IA platform demonstrated statistically and clinically significant superior risk-adjusted readmission rate profiles compared with peers nationally, statewide, and within the same SNF referral network (P < .0001). A more detailed study on the use of IA in this setting is warranted.

Association between regulator inspection and ratings on primary care prescribing: an observational study in England 2014 to 2019.

BACKGROUND: Healthcare regulators in many countries undertake inspections of healthcare providers and publish inspection outcomes with the intention of improving quality of care. Comprehensive inspections of general practices in England by the Care Quality Commission began for the first time in 2014. It is assumed that inspection and rating will raise standards and improve care, but the presence and extent of any improvements is unknown. We aim to determine if practice inspection ratings are associated with past performance on prescribing indicators and if prescribing behaviour changes following inspection. METHODS: Longitudinal study using a dataset of 6771 general practices in England. Practice inspection date and score was linked with monthly practice-level data on prescribing indicators relating to antibiotics, hypnotics and non-steroidal anti-inflammatory drugs. The sample covers practices receiving their first inspection between September 2014 and December 2018. Regression analysis and the differential timing of inspections is used to identify the impact on prescribing. RESULTS: Better-rated practices had better prescribing in the period before inspections began. In the six months following inspections, no overall change in prescribing was observed. However, the differences between the best and worse rated practices were reduced but not fully. The same is also true when taking a longer-term view. There is little evidence that practices responded in anticipation of inspection or reacted differently once the ratings were made public. CONCLUSION: While some of the observed historic variation in prescribing behaviour has been lessened by the process of inspection and ratings, we find this change is small and appears to come from both improvements among lower-rated practices and deteriorations among higher-rated practices. While inspection and rating no doubt had other impacts, these prescribing indicators were largely unchanged.

COVID-19 Admission Rates and Changes in Care Quality in US Hospitals.

Importance: Unprecedented increases in hospital occupancy rates during COVID-19 surges in 2020 caused concern over hospital care quality for patients without COVID-19. Objective: To examine changes in hospital nonsurgical care quality for patients without COVID-19 during periods of high and low COVID-19 admissions. Design, Setting, and Participants: This cross-sectional study used data from the 2019 and 2020 Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project State Inpatient Databases. Data were obtained for all nonfederal, acute care hospitals in 36 states with admissions in 2019 and 2020, and patients without a diagnosis of COVID-19 or pneumonia who were at risk for selected quality indicators were included. The data analysis was performed between January 1, 2023, and March 15, 2024. Exposure: Each hospital and week in 2020 was categorized based on the number of COVID-19 admissions per 100 beds: less than 1.0, 1.0 to 4.9, 5.0 to 9.9, 10.0 to 14.9, and 15.0 or greater. Main Outcomes and Measures: The main outcomes were rates of adverse outcomes for selected quality indicators, including pressure ulcers and in-hospital mortality for acute myocardial infarction, heart failure, acute stroke, gastrointestinal hemorrhage, hip fracture, and percutaneous coronary intervention. Changes in 2020 compared with 2019 were calculated for each level of the weekly COVID-19 admission rate, adjusting for case-mix and hospital-month fixed effects. Changes during weeks with high COVID-19 admissions (≥15 per 100 beds) were compared with changes during weeks with low COVID-19 admissions (<1 per 100 beds). Results: The analysis included 19 111 629 discharges (50.3% female; mean [SD] age, 63.0 [18.0] years) from 3283 hospitals in 36 states. In weeks 18 to 48 of 2020, 35 851 hospital-weeks (36.7%) had low COVID-19 admission rates, and 8094 (8.3%) had high rates. Quality indicators for patients without COVID-19 significantly worsened in 2020 during weeks with high vs low COVID-19 admissions. Pressure ulcer rates increased by 0.09 per 1000 admissions (95% CI, 0.01-0.17 per 1000 admissions; relative change, 24.3%), heart failure mortality increased by 0.40 per 100 admissions (95% CI, 0.18-0.63 per 100 admissions; relative change, 21.1%), hip fracture mortality increased by 0.40 per 100 admissions (95% CI, 0.04-0.77 per 100 admissions; relative change, 29.4%), and a weighted mean of mortality for the selected indicators increased by 0.30 per 100 admissions (95% CI, 0.14-0.45 per 100 admissions; relative change, 10.6%). Conclusions and Relevance: In this cross-sectional study, COVID-19 surges were associated with declines in hospital quality, highlighting the importance of identifying and implementing strategies to maintain care quality during periods of high hospital use.

The Ability of Primary Care Practices to Measure and Report on Care Quality.

BACKGROUND: Creating useful clinical quality measure (CQM) reports in a busy primary care practice is known to depend on the capability of the electronic health record (EHR). Two other domains may also contribute: supportive leadership to prioritize the work and commit the necessary resources, and individuals with the necessary health information technology (IT) skills to do so. Here we describe the results of an assessment of the above 3 domains and their associations with successful CQM reporting during an initiative to improve smaller primary care practices' cardiovascular disease CQMs. METHODS: The study took place within an AHRQ EvidenceNOW initiative of external support for smaller practices across Washington, Oregon and Idaho. Practice facilitators who provided this support completed an assessment of the 3 domains previously described for each of their assigned practices. Practices submitted 3 CQMs to the study team: appropriate aspirin prescribing, use of statins when indicated, blood pressure control, and tobacco screening/cessation. RESULTS: Practices with advanced EHR reporting capability were more likely to report 2 or more CQMs. Only one-third of practices were "advanced" in this domain, and this domain had the highest proportion of practices (39.1%) assessed as "basic." The presence of advanced leadership or advanced skills did not appreciably increase the proportion of practices that reported 2 or more CQMs. CONCLUSIONS: Our findings support previous reports of limited EHR reporting capabilities within smaller practices but extend these findings by demonstrating that practices with advanced capabilities in this domain are more likely to produce CQM reports.

Hospital performance evaluation indicators: a scoping review.

BACKGROUND: Hospitals are the biggest consumers of health system budgets and hence measuring hospital performance by quantitative or qualitative accessible and reliable indicators is crucial. This review aimed to categorize and present a set of indicators for evaluating overall hospital performance. METHODS: We conducted a literature search across three databases, i.e., PubMed, Scopus, and Web of Science, using possible keyword combinations. We included studies that explored hospital performance evaluation indicators from different dimensions. RESULTS: We included 91 English language studies published in the past 10 years. In total, 1161 indicators were extracted from the included studies. We classified the extracted indicators into 3 categories, 14 subcategories, 21 performance dimensions, and 110 main indicators. Finally, we presented a comprehensive set of indicators with regard to different performance dimensions and classified them based on what they indicate in the production process, i.e., input, process, output, outcome and impact. CONCLUSION: The findings provide a comprehensive set of indicators at different levels that can be used for hospital performance evaluation. Future studies can be conducted to validate and apply these indicators in different contexts. It seems that, depending on the specific conditions of each country, an appropriate set of indicators can be selected from this comprehensive list of indicators for use in the performance evaluation of hospitals in different settings.

Adherence to diabetes quality indicators in primary care and all-cause mortality: A nationwide population-based historical cohort study.

BACKGROUND: In the last three decades, much effort has been invested in measuring and improving the quality of diabetes care. We assessed the association between adherence to diabetes quality indicators and all-cause mortality in the primary care setting. METHODS: A nationwide, population-based, historical cohort study of all people aged 45-80 with pharmacologically-treated diabetes in 2005 (n = 222,235). Data on annual performance of quality indicators (including indicators for metabolic risk factor management and glycemic control) and vital status were retrieved from electronic medical records of the four Israeli health maintenance organizations. Cox proportional hazards and time-dependent models were used to estimate hazard ratios (HRs) for mortality by degree of adherence to quality indicators. RESULTS: During 2,000,052 person-years of follow-up, 35.8% of participants died. An inverse dose-response association between the degree of adherence and mortality was shown for most of the quality indicators. Participants who were not tested for proteinuria or did not visit an ophthalmologist during the first-5-years of follow-up had HRs of 2.60 (95%CI:2.49-2.69) and 2.09 (95%CI:2.01-2.16), respectively, compared with those who were fully adherent. In time-dependent analyses, not measuring LDL-cholesterol, blood pressure, HbA1c, or HbA1c>9% were similarly associated with mortality (HRs ≈1.5). The association of uncontrolled blood pressure with mortality was modified by age, with increased mortality shown for those with controlled blood pressure at older ages (≥65 years). CONCLUSIONS: Longitudinal adherence to diabetes quality indicators is associated with reduced all-cause mortality. Primary care professionals need to be supported by health care systems to perform quality indicators.

Developing quality indicators for cancer hospitals in China: a national modified Delphi process.

OBJECTIVE: Although demand and supply of cancer care have been rapidly increasing in recent decades, there is a lack of systemic quality measurement for cancer hospitals in China. This study aimed to develop a set of core indicators for measuring quality of care for cancer hospitals in China. DESIGN: The development of quality indicators was based on a literature review and a two-round modified Delphi survey. The theoretical framework and initial indicators were identified through the comprehensive literature review, and the selection of quality indicators relied on experts' consensus on the importance and feasibility of indicators by the modified Delphi process. In addition, indicator weight was identified using the analytical hierarchical process method and percentage weight method. SETTING AND PARTICIPANTS: A panel of leading experts including oncologists, cancer care nurses, quality management experts from various regions of China were invited to participate in the two-round modified Delphi process from October to December 2020. A total of 25 experts completed the two-round modified Delphi process. RESULTS: The experts reached consensus on a set of 47 indicators, comprising 17 structure indicators, 19 process indicators and 11 outcome indicators. Experts gave much higher weight to outcome indicators (accounting for 53.96% relative weight) than to structure (16.34%) and process (29.70%) indicators. In addition, experts also showed concerns and gave suggestions on data availability of specific outcome indicators. CONCLUSIONS: Drawing on the comprehensive literature review and the modified Delphi process, this study developed a core set of quality indicators that can be used to evaluate quality performance of cancer hospitals. This is helpful in supporting quality cancer care in China and will provide new insights into the systemic measurement of cancer care internationally.

Evidence-based interventions for identifying candidate quality indicators to assess quality of care in diabetic foot clinics: a scoping review.

BACKGROUND: Foot ulcers in people with diabetes are a serious complication requiring a complex management and have a high societal impact. Quality monitoring systems to optimize diabetic foot care exist, but a formal and more evidence-based approach to develop quality indicators (QIs) is lacking. We aimed to identify a set of candidate indicators for diabetic foot care by adopting an evidence-based methodology. METHODS: A systematic search was conducted across four academic databases: PubMed, Embase CINAHL and Cochrane Library. Studies that reported evidence-based interventions related to organization or delivery of diabetic foot care were searched. Data from the eligible studies were summarized and used to formulate process and structure indicators. The evidence for each candidate QI was described in a methodical and transparent manner. The review process was reported according to the "Preferred Reported Items for Systematic reviews and Meta-Analysis" (PRISMA) statements and its extension for scoping reviews. RESULTS: In total, 981 full-text articles were screened, and 322 clinical studies were used to formulate 42 candidate QIs. CONCLUSIONS: An evidence-based approach could be used to select candidate indicators for diabetic foot ulcer care, relating to the following domains: wound healing interventions, peripheral artery disease, offloading, secondary prevention, and interventions related to organization of care. In a further step, the feasibility of the identified set of indicators will be assessed by a multidisciplinary panel of diabetic foot care stakeholders.

The risk analysis index demonstrates exceptional discrimination in predicting frailty's impact on neurosurgical length of stay quality metrics.

BACKGROUND: Quality measures determine reimbursement rates and penalties in value-based payment models. Frailty impacts these quality metrics across surgical specialties. We compared the discriminatory thresholds for the risk analysis index (RAI), modified frailty index-5 (mFI-5) and increasing patient age for the outcomes of extended length of stay (LOS [eLOS]), prolonged LOS within 30 days (pLOS), and protracted LOS (LOS > 30). METHODS: Patients ≥18 years old who underwent neurosurgical procedures between 2012 and 2020 were queried from the ACS-NSQIP. We performed receiver operating characteristic analysis, and multivariable analyses to examine discriminatory thresholds and identify independent associations. RESULTS: There were 411,605 patients included, with a median age of 59 years (IQR, 48-69), 52.2% male patients, and a white majority 75.2%. For eLOS: RAI C-statistic 0.653 (95% CI: 0.652-0.655), versus mFI-5 C-statistic 0.552 (95% CI: 0.550-0.554) and increasing patient age C-statistic 0.573 (95% CI: 0.571-0.575). Similar trends were observed for pLOS- RAI: 0.718, mFI-5: 0.568, increasing patient age: 0.559, and for LOS>30- RAI: 0.714, mFI-5: 0.548, and increasing patient age: 0.506. Patients with major complications had eLOS 10.1%, pLOS 26.5%, and LOS >30 45.5%. RAI showed a larger effect for all three outcomes, and major complications in multivariable analyses. CONCLUSION: Increasing frailty was associated with three key quality metrics that is, eLOS, pLOS, LOS > 30 after neurosurgical procedures. The RAI demonstrated a higher discriminating threshold compared to both mFI-5 and increasing patient age. Preoperative frailty screening may improve quality metrics through risk mitigation strategies and better preoperative communication with patients and their families.

Trauma Registry: Trauma Quality indicators analysis in hospitalized patients.

PURPOSE: to consolidate a Trauma Register (TR) trough REDCap data acquisition platform and to validate, in this context, local Quality Indicators (QI) as improvement opportunities in trauma management. METHODS: continuous data acquisition of all patients admitted in Irmandade da Santa Casa de Misericórdia de São Paulo adult Trauma bay and it's validation in REDCap platform; 6 months retrospective cohort of QI impact in length of hospitalar stay, complications and mortality. Fisher, Chi-squared, Wilcoxon and Kruskal-Wallis tests were used to correlate QIs fails with the endpoints, considering p<0.05 and CI <95% as statically significant. RESULTS: 465 were admitted in Trauma bay, with 137 patients hospitalized (29.5%); the number of QIs compromised were related with more complications (p=0.075) and increased length of stay (p=0.028), especially the delay in open fracture's surgical management, which increased the severe complications' incidence (p=0.005). CONCLUSION: the REDCap data acquisition platform is useful as a tool for multi center TR implementation, from ethical and logistical point of view; nevertheless, the proposed QIs are validated as attention points in trauma management, allowing improvements in traumatized patients treatment.