Performance Of Health Care System Research Articles

Evaluation of Turkey’s Healthcare System Performance in COVID-19 Pandemic Period

The main objective of this study is to evaluate the performance of Turkey’s Health System during the COVID-19 pandemic. A cross-sectional study was conducted in Turkey among 656 people using a questionnaire. STATA 14.0 statistical software package was used for analysing the data. Frequency, percentage, mean, standard deviation, t-test and one-way analysis of variance test were used. The participants’ Healthcare System Performance Evaluation Scale total score mean [Formula: see text] = 3.60 ± 0.6 in the sub-dimension of ‘Safe and Security’ [Formula: see text] = 3.63 ± 0.8, in the sub-dimension of ‘Transparency’ [Formula: see text] = 3.15 ± 1.1, in the sub-dimension ‘Accessibility’ [Formula: see text] = 3.79 ± 0.9, in the sub-dimension ‘Affordability’ [Formula: see text] = 3.83 ± 0.8 was determined. The Healthcare System Performance Evaluation Scale and a sub-dimension of this scale, accessibility, scores of them are high and differed statistically by age. The affordability sub-scale score was statistically different from income groups ( F = 6.47; p < .05). Although the performance of the general healthcare system is high, it was seen that the scores regarding the transparency of the information shared during COVID-19 were partially lower than other dimensions.

Healthcare team resilience during COVID-19: a qualitative study

BackgroundResilience, in the field of Resilience Engineering, has been identified as the ability to maintain the safety and the performance of healthcare systems and is aligned with the resilience potentials of anticipation, monitoring, adaptation, and learning. In early 2020, the COVID-19 pandemic challenged the resilience of US healthcare systems due to the lack of equipment, supply interruptions, and a shortage of personnel. The purpose of this qualitative research was to describe resilience in the healthcare team during the COVID-19 pandemic with the healthcare team situated as a cognizant, singular source of knowledge and defined by its collective identity, purpose, competence, and actions, versus the resilience of an individual or an organization.MethodsWe developed a descriptive model which considered the healthcare team as a unified cognizant entity within a system designed for safe patient care. This model combined elements from the Patient Systems Engineering Initiative for Patient Safety (SEIPS) and the Advanced Team Decision Making (ADTM) models. Using a qualitative descriptive design and guided by our adapted model, we conducted individual interviews with healthcare team members across the United States. Data were analyzed using thematic analysis and extracted codes were organized within the adapted model framework.ResultsFive themes were identified from the interviews with acute care professionals across the US (N = 22): teamwork in a pressure cooker, consistent with working in a high stress environment; healthcare team cohesion, applying past lessons to present challenges, congruent with transferring past skills to current situations; knowledge gaps, and altruistic behaviors, aligned with sense of duty and personal responsibility to the team. Participants’ described how their ability to adapt to their environment was negatively impacted by uncertainty, inconsistent communication of information, and emotions of anxiety, fear, frustration, and stress. Cohesion with co-workers, transferability of skills, and altruistic behavior enhanced healthcare team performance.ConclusionWorking within the extreme unprecedented circumstances of COVID-19 affected the ability of the healthcare team to anticipate and adapt to the rapidly changing environment. Both team cohesion and altruistic behavior promoted resilience. Our research contributes to a growing understanding of the importance of resilience in the healthcare team. And provides a bridge between individual and organizational resilience.

Development of the China’s list of ambulatory care sensitive conditions (ACSCs): a study protocol

BackgroundThe hospitalization rate of ambulatory care sensitive conditions (ACSCs) has been recognized as an essential indicator reflective of the overall performance of healthcare system. At present, ACSCs has been widely used in practice and research to evaluate health service quality and efficiency worldwide. The definition of ACSCs varies across countries due to different challenges posed on healthcare systems. However, China does not have its own list of ACSCs. The study aims to develop a list to meet health system monitoring, reporting and evaluation needs in China.MethodsTo develop the list, we will combine the best methodological evidence available with real-world evidence, adopt a systematic and rigorous process and absorb multidisciplinary expertise. Specific steps include: (1) establishment of working groups; (2) generations of the initial list (review of already published lists, semi-structured interviews, calculations of hospitalization rate); (3) optimization of the list (evidence evaluation, Delphi consensus survey); and (4) approval of a final version of China’s ACSCs list. Within each step of the process, we will calculate frequencies and proportions, use descriptive analysis to summarize and draw conclusions, discuss the results, draft a report, and refine the list.DiscussionOnce completed, China’s list of ACSCs can be used to comprehensively evaluate the current situation and performance of health services, identify flaws and deficiencies embedded in the healthcare system to provide evidence-based implications to inform decision-makings towards the optimization of China’s healthcare system. The experiences might be broadly applicable and serve the purpose of being a prime example for nations with similar conditions.

A multi-criteria decision analysis framework that prioritizes economic policy to enhance value based health care during the COVID-19 pandemic

ObjectiveTo investigate pandemic impacts on Value-Based Health Care (VBHC) globally, using multi-criteria decision analysis (MCDA) to address challenges through prioritizing economic policies.MethodsPreferred Reporting Items for Systematic reviews and Meta Analyses extension for Scoping-Reviews (PRISMA-ScR), PUBMED, Medline, and google-scholar were used to analyze pandemic impacts on VBHC domains. MCDA prioritized economic policies, utilizing the value-measurement model with additive-weighted scores. The criteria weighting-method used direct-rating, ranking and robust deliberation by four experts to priority rank economic policies for each VBHC domain.ResultsCOVID-19 impacted on all VBHC domains: Integrated Practice Units, outcome and cost measurement, Value-Based Reimbursement, Information Technology (IT), regional systems integration, geography of care and VBHC policy and institutions. There were changes in patient complexity, service delivery, activity, models of care, pricing, costs, IT, quality, and health status. COVID-19 pricing impacts included increased capacity costs, Personal Protective Equipment costs, cost per patient, service delivery changes, and telehealth costs. A median of 37% of patients globally avoided care, negatively impacting on diabetes, venous thromboembolism, Parkinson’s disease, kidney disease, myocardial infarction, stroke, and cancer patients. A consequence is inaccurate assessments of health status, underestimated projected health needs, and costs for risk-adjustment, impacting health services. Innovations include telehealth and changing service redesign. New care models include state-wide ICU-COVID Models of Care, Telehealth-Inpatient Physician Services, COVID-linked pathology testing, and increased Hospital in the Home. Artificial Intelligence innovations involved patient-screening, triage, risk-evaluation, care assessment, pathways, and laboratories. Risk-adjustment challenges impacted on Value-Based Reimbursement and patient risk-stratification. MCDA prioritized economic policies, including healthcare system performance, healthcare demand and supply, risk-adjustment, planning and market mechanisms, economic evaluation of healthcare, economic sustainability initiatives, and health determinants.ConclusionCOVID-19 demonstrated the limits of health systems globally, with increasing costs and limited budgets. The economic strategies identified can enhance VBHC globally.

The Eye-Opening Truth About Private Surgical Facilities in Canada.

This paper examines the contentious issue of using contracted surgical facilities (CSFs) for scheduled eye surgeries within Canada's publicly funded healthcare system. Despite the debate over the use of CSFs, there is a stark lack of Canadian-focused empirical evidence to guide policy decisions. This paper uses the Organisation for Economic Co-operation and Development's healthcare system performance conceptual model - access, quality and cost/expenditures - as a framework to explore the debates surrounding CSFs. It highlights the mixed evidence from international studies and proposes recommendations for policy makers to ensure equitable access, maintain high-quality care and achieve cost-effectiveness. The paper underscores the necessity for informed policy making supported by robust empirical research, stakeholder engagement and continuous policy evaluation to address the challenges posed by the integration of CSFs into Canada's healthcare landscape.

Unplanned 30-day readmission rate after ophthalmological surgery as a quality-of-care indicator.

The 30-day readmission rate provides a standardised quantitative evaluation of some postoperative complications. It is widely used worldwide in many medical and surgical specialities, and the World Health Organization recommends its use for monitoring healthcare system performance. In ophthalmology, its measurement is biased by the frequent and close planned surgery on one eye and then the other, particularly in the case of cataract surgery. This study measures the 30-day unplanned readmission rate in ophthalmology, globally and by surgery subtype, and describes the causes of readmission. All patients readmitted within 30 days of ophthalmic surgery at Nantes University Hospital between January 2017 and December 2020 were identified in the Medical Information System. An ophthalmologist examined each medical record and collected the following data: the reason for readmission, comorbidities, the pathology treated, surgery type, surgery duration, the surgeon's experience, anaesthesia type, severity and readmission morbidity. For the 8522 ophthalmic surgeries performed in the four-year study period, 282 30-day unplanned readmissions were identified. The overall 30-day unplanned readmission rate was 2.07% for elective surgery, with a high variability depending on the surgery type: 0.95% for phacoemulsification, 4.95% for vitreoretinal surgery (3.42% for non-elective vitreoretinal surgery, 5.44% for retinal detachment surgery), 5.66% for deep lamellar keratoplasty and 11.90% for trabeculectomy. The unplanned 30-day readmission rate for ocular trauma surgery (emergency care) was 11.0%. Seven percent of all unplanned 30-day readmissions were not associated with an ophthalmological problem. This study is the first to report 30-day unplanned readmission in ophthalmology, globally and by surgical subtype, for elective and urgent procedures. This indicator can be used longitudinally to detect an increase in risk or transversely to compare the quality of care between different public or private hospitals.

Teledentistry for improving access to, and quality of oral health care: A protocol for an overview of systematic reviews and meta-analyses.

Digital technologies are becoming essential to address and optimize the suboptimal performance of healthcare systems. Teledentistry involves the use of information and communication technology to improve access to oral health care and the quality of oral health care delivery. Several systematic reviews (SRs) have been conducted to synthesize evidence on the effectiveness of teledentistry but with conflicting results. The aim of this review is to comprehensively summarize available SRs and provide evidence on the impact of teledentistry on access to oral care, patients' and oral healthcare providers' outcomes, quality of oral health care and costs. This protocol has been registered with the International Prospective Register of Systematic Reviews (PROSPERO CRD42022373964). Six electronic databases including MEDLINE (Ovid), Embase (Embase.com), CINAHL (EBSCO), Web of Science, Cochrane Library and Epistemonikos will be searched for SRs of quantitative, qualitative, and mixed reviews evaluating teledentistry modalities involving both patients and/or oral health care providers (OHCPs). We will include studies published in English or French. The outcomes will include patients' outcomes (e.g., access to oral health care, patient-reported outcomes, and patient-reported experiences); patient indicators (e.g., clinical outcomes, adherence to treatment, adverse outcomes and costs); and OHCP indicators (e.g., diagnostic accuracy, barriers and enablers costs and equity). Two independent reviewers will perform data screening, data extraction and will assess the quality of included studies using AMSTAR 2 and ROBIS tools. Data will be synthesized narratively and presented by tables and graphs. We will report any overlap of primary studies in the SRs. A statement on the strength of evidence for each outcome will be provided if possible. This review will inform decision-makers, patients, OHCPs, and researchers on the potential effectiveness, benefits, and challenges of teledentistry and support them in making recommendations for its use. Results will be disseminated through peer-reviewed publications, presentations at conferences, and on social media.

Unmet need for healthcare in the Russian Federation: subnational retrospective modelling analysis (2014–2018)

IntroductionUnmet need for healthcare is a proxy indicator used to assess the performance of healthcare systems throughout the world. While the Russian Federation is committed to improving healthcare for its...

Digitalization of the Medical System and Demographic Processes in Estonia

The rapid growth in information technologies has produced effects for all the walks of human and public life. The health care sector did not stay out, although it needs to be acknowledged that it has not been effectively digitalized in all the countries, even developed ones. It should be emphasized that the demographic situation heavily depends on the health care system performance. A most advanced country in terms of the health care digitalization is certainly Estonia. This country with less than 1,500,000 of population has long digitalized all the services provided to its residents. 
 The article’s objective is to investigate the impact of health care system digitalization on demographic processes in Estonia. Some innovations in the Estonian medial system, implemented with the advent of new information technologies, are discussed: for doctors it is possible to exchange paperless information about a patient in the patient’s presence in case of need (including medical records or results of tests and examinations). On the other hand, such confidential information can be closed by the patient’s desire for any medical employee. Moreover, a person is well aware of who exactly has access to his/her data: doctor, police or an official body. 
 Being a digital country, Estonia was better prepared to deal online with various problems (first and foremost, distance training, distance job and medical service: testing, identifying contacts with ill persons and vaccination later on) posed by the pandemic of COVID-19. However, a change in the demographic situation, resulting from the spread of the virus, was triggered e. g. by the health care system performance and its response on the new challenge.
 It is emphasized that important information sources for investigating the demographic situation in Estonia and the health care system’s impact on demographic change include the statistical office and other official bodies, as well as international institutions. Using information on the pandemic extracted from online registers, researchers, medics, statisticians and professionals in other fields could help heath care system in quicker adaptation to new realities and in implementing additional methods for analysis of the morbidity rate in Estonia.  
 The experience of the Estonian health care system in implementing digitalization is undoubtedly important for Ukraine. It refers to creating new registers and systems already used in Estonia and other North European countries but lacking in Ukraine, and to improving existing medical information systems and their interactions.

Home health care facility location problem under demand uncertainty

The demand for home health care services is rapidly increasing due to the growing number of older people. The uncertainty surrounding this demand affects the network design processes and the performance of the home health care system in the long term. This study aims to address the issue of demand uncertainty in a home health care location problem. While decisions regarding the location of home health care facilities must be made immediately, the determination of distribution can be postponed until actual demand is observed. In such situations, minimax/maximin robust optimization methods are commonly employed to address uncertainty and facilitate informed decision-making, even in cases where there is limited information about future demand. However, these methods are often too conservative and may lead to suboptimal solutions. To tackle this issue, we propose a regret minimization method, which is reformulated as a robust model to overcome its intractability. Additionally, we propose a column-and-constraint generation algorithm to solve the robust optimization and regret minimization models. Finally, we conduct a comprehensive set of numerical experiments to compare the performance of the models in terms of solution quality and computational time. The results demonstrate that the regret minimization model enhances solution quality and consumes less computational time when reformulated.

Abstract 16307: Does the Method of Calculating the 30-day Readmission Rate After Hospitalization for Heart Failure Matter? Data From the VancOuver CoastAL Acute Heart Failure Registry

Introduction: The 30-day readmission rate after a heart failure (HF) hospitalization is widely used for assessing healthcare quality and system performance. However, there are different methodological approaches which may influence estimated rates, and no single accepted approach. The combined impact of these methods is unknown. Goals: We calculated 30-day HF readmission rates (RRs) of hospitalized patients using different published approaches to sampling and measurement. Methods: We included 1,849 patients discharged following unplanned hospitalization with a primary diagnosis of HF between 2016 to 2018 from the VancOuver CoastAL Acute Heart Failure (VOCAL-AHF) registry. We combined five distinct methodological factors (Table 1) to create 64 unique definitions and associated HF RRs. The readmission rates were averaged over 3-years. Multiple linear regression was used to determine the impact of different factors on estimated readmission rates. Results: The calculated 30-day RR for HF varied more than twofold depending solely on the methodological approach (6.4% to 15.0%, 8.6% absolute difference, 134% relative difference). The rates were highest when including all consecutive index admissions (11.1% to 15.0%), and lowest including only one index admission per patient per year (6.4% to 11.4%). The regression model ranked variables affecting RR as: index selection method, reference period, ICD-10 codes, 30-day survival, and index day (Table 2, p<0.001 in all). Conclusions: Our findings have important implications for policy and reporting. Transparent and consistent methods are needed to calculate 30-day RRs to ensure reproducible and comparable reporting.

Disaster preparedness of health professionals at mass gatherings: a scoping review

Mass gathering disasters involving large numbers of casualties can adversely affect the performance of healthcare systems. This scoping review aims to explore the current literature on the preparedness of health professionals for disasters during mass gathering events. Four databases were searched to identify papers examining health professionals' disaster preparedness during mass gatherings between 2011 and 2022. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis for Scoping Reviews was applied to undertake this review. A total of 2024 articles were identified, of which 18 qualified for inclusion in the scoping review. Some studies reported the level of professionals' preparedness for disaster management, while others reported strategies to enhance preparedness and challenges associated with disaster preparedness during mass gatherings. More studies are needed in this field to better understand the level of disaster preparedness of health professionals to improve response and management of potential disasters during mass gathering events.

8.G. Workshop: Developments in patient experience surveys: how do we maintain relevance and maximise impact?

Abstract Background Patient and service-user experiences of healthcare are a vital component of the monitoring and assessment of the quality and performance of health and social care services and systems, as well as an important predictor of patient outcomes. The National Care Experience Programme (NCEP) is a partnership between the Irish health and social care regulator (Health Information and Quality Authority, HIQA), the national public healthcare provider (Health Service Executive, HSE), and policy makers (Department of Health). The NCEP conducts national care experience surveys with the aim of learning from people's experiences in order to improve the quality of health and social care services in Ireland. The programme includes surveys of acute hospital inpatient, maternity, maternity bereavement, nursing home and end-of-life care. Additional surveys of cancer care and mental health services are currently in development. Objectives Regular review and adaptation of existing surveys, expansion into new areas of care, and development of new methods of data collection, analysis and dissemination of survey findings and stakeholder engagement are required in order to remain agile and responsive to evolving health and social care landscapes and the changing needs of stakeholders, as well as harnessing technological advances and ensuring sustainability. The aim of this workshop is to bring together experts in patient experience from across the health system to stimulate discussion, knowledge sharing and cross-fertilisation of ideas. Presentations will focus on international developments and trends in patient experience, as well as considerations for surveying bereaved parents and families on their experiences of maternity bereavement and end-of-life care. The use of new technologies, including computational text analytics and predictive modelling to facilitate qualitative data analysis and maximise the use of survey findings will be outlined, followed by case studies of how care experience data are used to inform health and social care legislation, policy and practice in Ireland. Experiences from other jurisdictions and potential implications will be discussed with the audience. The workshop will contribute to a better understanding of the value and impact of collecting patient experience feedback and explore how new technologies can be used to generate insights and maximise the use of survey data. Format of the workshop The workshop will include a brief introduction on patient experience and the Irish National Care Experience Programme, followed by five presentations with time for audience contributions and questions after each speaker. The workshop will conclude with a discussion with the audience and presenters. Key messages • Patient experiences are a key component of the monitoring and assessment of the quality and performance of health and social care services and systems. • Regular review and adaptation of surveys and development of new methods are required to remain responsive to evolving health and social care landscapes and ensure sustainability.

Global inpatient utilization from 1990 to 2020: effects of the COVID-19 pandemic

Abstract Background Inpatient service utilization rate is a key indicator for estimating the performance of health care systems on global, regional, and national levels. Methods We collected 1378 source-years of data, including administrative sources, nationally representative surveys, and government reports covering 130 countries overall, 29 of which are in the European region from 1990 to 2020. Inpatient admission was defined as an overnight stay at a formal healthcare facility for any cause. The data underwent age- and sex-splitting as per the available level of detail; survey sources were crosswalked to the gold-standard administrative data. The resulting data set was analyzed using Spatiotemporal Gaussian Process Regression (ST-GPR), a Bayesian meta-regression tool, to model the inpatient admission rate per capita across all countries, age groups, and sexes from 1990 to 2020. Admission rates were age- and sex-standardized to compute global proportions of hospitalized persons. Results In 2019, the global age-standardized inpatient utilization rate was 0.12 (95% uncertainty interval [UI] 0.09-0.15) admissions per capita. Globally, 0.93 billion (0.72-1.18) inpatient admissions were provided in 2019 compared to 0.68 billion (0.53-0.87) in 1990. In 2020, the global age-standardized inpatient utilization rate dropped to 0.057 (0.055-0.059) with a global proportion of hospitalized patients of 0.45 billion (0.43-0.46). Conclusions The increase in inpatient utilization from 1990 to 2019 may be attributable to population growth and increased capacity of health systems across most WHO regions. Health care utilization was highly variable between regions that was partly explainable by the variation in the socio-demographic index (SDI). The pandemic-mitigating measures limiting transportation and healthcare access were associated with the reduction in utilization in 2020. Key messages • The inpatient utilization rates were rising globally with large variation across regions, while decreasing in 2020 due the COVID-19 pandemic-related mitigating measures. • Health systems may use the inpatient utilization estimates to assess the effectiveness of health care reforms, plan for future capacity, and to allocate financial and human resources appropriately.

A Machine Learning Framework for Length of Stay Minimization in Healthcare Emergency Department

The emergency departments (EDs) in most hospitals, especially in middle-and-low-income countries, need techniques for minimizing the waiting time of patients. The application and utilization of appropriate methods can enhance the number of patients treated, improve patients’ satisfaction, reduce healthcare costs, and lower morbidity and mortality rates which are often associated with poor healthcare facilities, overcrowding, and low availability of healthcare professionals.  Modeling the length of stay (LOS) of patients in healthcare systems is a challenge that must be addressed for sound decision-making regarding capacity planning and resource allocation. This paper presents a machine learning (ML) framework for predicting a patient’s LOS within the ED. A study of the services in the ED of a tertiary healthcare facility in Uyo, Nigeria was conducted to gain insights into its operational procedures and evaluate the impact of certain parameters on LOS. Then, a computer simulation of the system was performed in R programming language using data obtained from records in the hospital. Finally, the performance of four ML classifiers involved in patients’ LOS prediction: Classification and Regression Tree (CART), Random Forest (RF), K-Nearest Neighbour (K-NN), and Support Vector Machine (SVM), were evaluated and results indicate that SVM outperforms others with the highest coefficient of determination (R2) score of 0.986984 and least mean square error (MSE) value of 0.358594. The result demonstrates the capability of ML techniques to effectively assess the performance of healthcare systems and accurately predict patients’ LOS to mitigate the low physician-patient ratio and improve throughput.

An improved fuzzy c-means-raindrop optimizer for brain magnetic resonance image segmentation

<p>The performance of healthcare systems, particularly regarding disease diagnosis and treatment planning, depends on the segmentation of medical images. Fuzzy c-means (FCM) is one of the most widely used clustering techniques for image segmentation due to its simplicity and effectiveness. FCM, on the other hand, has the disadvantages of being noise-sensitive, quickly settling on local optimal solutions, and being sensitive to initial values. This paper suggests a fuzzy c-means clustering improved with a nature-inspired raindrop optimizer for lesion extraction in brain magnetic resonance (MR) images to get around this constraint. In the preprocessing stage, the possible noises in a digital image, such as speckles, gaussian, etc., are eliminated by a hybrid filter—A combination of Gaussian, mean, and median filters. This paper presents a comparative analysis of FCM clustering and FCM-raindrop optimization (FCM-RO) approach. The algorithm performance is evaluated for images subjected to various possible noises that may affect an image during transmission and storage. The proposed FCM-RO approach is comparable to other methods now in use. The suggested system detects lesions with a partition coefficient of 0.9505 and a partition entropy of 0.0890. Brain MR images are analyzed using MATLAB software to find and extract malignancies. Image data retrieved from the public data source Kaggle are used to assess the system’s performance.</p>

Defining Priorities in Value-Based Cancer Care: Insights From the Alliance for Clinical Trials in Oncology National Cooperative Group Survey.

We determine how stakeholders prioritize the importance of oncologic outcomes, patient-reported outcomes (PROs), and cancer-related health care costs. A survey was distributed to the National Clinical Trials Network Alliance for Clinical Trials in Oncology cooperative group membership from May 14 to June 30, 2022. Respondents were asked to rate (5-point Likert scale) and rank (1-9) evidence-based value domains: overall survival, treatment toxicities/complications, quality of life (QOL), financial toxicity, access to care, compliance with evidence-based care, health system performance, scientific discovery and innovation, and cost to the health care system. A total of 514 members responded, including researchers (24.7%), nurses (19.5%), medical oncologists (17.9%), administrators (9.3%), surgical and radiation oncologists (9.1%), patient advocates (3.1%), and nonphysician providers (16.4%). Participants represented various practice settings including National Cancer Institute-designated cancer centers (29.8%), university-affiliated academic cancer centers (21%), hospital-owned oncology practices (21.8%), and others (27.4%). There was agreement in how respondents prioritized value domains (W = 0.39, P < .001). Respondents ranked patient QOL (mean rank: 2.6 ± 1.9) as most important above all other metrics including survival (mean rank: 3.5 ± 0.3) and access to care (mean rank: 3.5 ± 2.1; P < .001). Members engaged in direct patient care also ranked access to care of higher importance than nonclinicians (P = .026). Cost to the health care system (mean rank: 7.5 ± 2.1) and health system performance (mean rank: 7 ± 2) were ranked as least important (P < .001). Inclusion of PROs into therapeutic assessment (59.3%) was the most frequently selected priority of future cooperative group initiatives. Oncology community stakeholders deemed patient-centered value domains as most important and considered patient QOL the highest priority. Inclusion of PROs into clinical trials was endorsed as an important component of therapeutic assessment. These findings can be taken into consideration when creating a value framework for inclusion in cancer clinical trials.

380 Sustainable Health Care to Provide Good Quality Care in the Surgical Industry- United Kingdom

Abstract Aim The surgical industry has a major contribution towards sustainable health care. The aim is to critically evaluate sustainable healthcare to provide good quality care in the surgical industry in the United Kingdom. Method A systemic review was conducted using peer-reviewed studies and articles from the United Kingdom related to surgical and anesthetic fields within the last 5 years. The most relevant journal articles were selected based on their relevance to healthcare system performance sustainability, including risks, and subsequently screened using the PRISMA 2020 model screening approach. The findings of the relevant journal articles were then evaluated critically for each theme. Results A total of 79 studies were retrieved. Fifteen of the retrieved studies met the inclusion criteria. Ten of the papers evaluated some existing sustainability practices. Only seven papers discussed significant determinants of good quality health care. Only 86.67% of the papers highlighted the implications of sustainability. The key predictors of high-quality medical care are effective resource management, moral surgical team acquisitions, professional services, integration, short hospital stays, and low mortality and morbidity rates. Conserving water, optimizing treatment routes and transportation, and creating cultural change were found to be the pillars of high-quality sustainable healthcare. Conclusions The concept of sustainability varied across these studies and limitations on sustainability through reduced mortality, morbidity, and business services were observed. The most detrimental effect on the sustainability of the surgical industry remains to be anesthetic gas emission from the theatres. A significant discrepancy was noted between the available data and its implication.

Scaling Family Voices and Engagement to Measure and Improve Systems Performance and Whole Child Health: Progress and Lessons from the Child and Adolescent Health Measurement Initiative.

The 1997 legislation authorizing the United States Child Health Insurance Program sparked progress to measure and publicly report on children's healthcare services quality and system performance. To meet the moment, the national Child and Adolescent Health Measurement Initiative (CAHMI) public-private collaboration was launched to put families at the center of defining, measuring and using healthcare performance information to drive improved services quality and outcomes. Since 1996 the CAHMI followed an intentional path of collaborative action to (1) articulate shared goals for child health and advance a comprehensive, life-course and outcomes-based healthcare performance measurement and reporting framework; (2) collaborate with families, providers, payers and government agencies to specify, validate and support national, state and local use of dozens of framework aligned measures; (3) create novel public-facing digital data query, collection and reporting tools that liberate data findings for use by families, providers, advocates, policymakers, the media and researchers (Data Resource Center, Well Visit Planner); and (4) generate field building research and systems change agendas and frameworks (Prioritizing Possibilities, Engagement In Action) to catalyze prevention, flourishing and healing centered, trauma-informed, whole child and family engaged approaches, integrated systems and supportive financing and policies. Lessons call for a restored, sustainable family and community engaged measurement infrastructure, public activation campaigns, and undeterred federal, state and systems leadership that implement policies to incentivize, resource, measure and remove barriers to integrated systems of care that scale family engagement to equitably promote whole child, youth and family well-being. Population health requires effective family engagement.

Exploring patient perspectives: A qualitative inquiry into healthcare perceptions, experiences and satisfaction in Lebanon.

Patient perspectives have received increasing importance within health systems over the past four decades. Measures of patient experience and satisfaction are commonly used. However, these measures do not capture all the information that is available through engaging with patients. An improved understanding of the various types of patient perspectives and the distinctions between them is needed. The lack of such knowledge limits the usefulness of including patient perspectives as components within pay-for-performance initiatives. This study aimed to explore patient perspectives on hospital care in Lebanon. It also aimed to contribute insights that may improve the national pay-for-performance initiative and to the knowledge on engaging patients towards person-centered health systems. We conducted a qualitative study using focus group discussions with persons recently discharged after hospitalization under the coverage of the Lebanese Ministry of Public Health. This study was implemented in 2017 and involved 42 participants across eight focus groups. Qualitative content analysis was used to analyze the information provided by participants. Five overall themes supported by 17 categories were identified, capturing the meaning of the participants' perspectives: health is everything; being turned into second class citizens; money and personal connections make all the difference; wanting to be treated with dignity and respect; and tolerating letdown, for the sake of right treatment. The most frequently prioritized statement in a ranking exercise regarding patient satisfaction was regular contact with the patient's doctor. Patient perspectives include more than what is traditionally incorporated in measures of patient satisfaction and experience. Patient valuing of health and their perceptions on each of the health system, and access and quality of care should also be taken into account. Hospital pay-for-performance initiatives can be made more responsive through a broader consideration of these perspectives. More broadly, health systems would benefit from wider engagement of patients. We propose a framework relating patient perspectives to value-based healthcare and health system performance.