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Provides a business model based on the UCLA Health System and explains how other businesses can use the same system to provide excellent customer experiences and dominate their industry.

Issues. The Health Care Quality Indicator (HCQI) Project of the Organization for Economic Cooperation and Development (OECD), which is aimed at developing a set of indicators for comparing the quality of health care across OECD member countries, requires a balanced conceptual framework that outlines the main concepts and domains of performance that should be captured for the current and subsequent phases of the project. Addressing the issues. This article develops a conceptual framework for the OECD’s HCQI Project. It first argues that developing such a framework should start by addressing the question, ‘performance of what—and to what ends?’ We identify at least two different major classes of frameworks: (i) health and (ii) health care performance frameworks, both of which are in common use. For the HCQI, we suggest a conceptual framework that is largely a purposeful modification of the existing performance frameworks and which is driven by the health determinants model. Conclusions. The conceptual basis for performance frameworks can be traced back to the health determinants model. A health performance framework takes a broader, societal or public health view of health determination, whereas a health care performance takes a narrower, mostly clinical or technical view of health care in relation to health (needs). This article proposes an HCQI framework that focuses on the quality of health care, maintains a broader perspective on health and its other determinants, and recognizes the key aims of health policy.

\"Separate Beds is the shocking story of Canada's system of segregated health care. Operated by the same bureaucracy that was expanding health care opportunities for most Canadians, the 'Indian Hospitals' were underfunded, understaffed, overcrowded, and rife with coercion and medical experimentation. Established to keep the Aboriginal tuberculosis population isolated, they became a means of ensuring that other Canadians need not share access to modern hospitals with Aboriginal patients. Tracing the history of the system from its fragmentary origins to its gradual collapse, Maureen K. Lux describes the arbitrary and contradictory policies that governed the 'Indian Hospitals, ' the experiences of patients and staff, and the vital grassroots activism that pressed the federal government to acknowledge its treaty obligations. A disturbing look at the dark side of the liberal welfare state, Separate Beds reveals a history of racism and negligence in health care for Canada's First Nations that should never be forgotten.\"-- Provided by publisher.

Background The previously published “Dose Response Multicentre International Collaborative Initiative (DoReMi)” study concluded that the high mortality of critically ill patients with acute kidney injury (AKI) was unlikely to be related to an inadequate dose of renal replacement therapy (RRT) and other factors were contributing. This follow-up study aimed to investigate the impact of daily fluid balance and fluid accumulation on mortality of critically ill patients without AKI (N-AKI), with AKI (AKI) and with AKI on RRT (AKI-RRT) receiving an adequate dose of RRT. Methods We prospectively enrolled all consecutive patients admitted to 21 intensive care units (ICUs) from nine countries and collected baseline characteristics, comorbidities, severity of illness, presence of sepsis, daily physiologic parameters and fluid intake-output, AKI stage, need for RRT and survival status. Daily fluid balance was computed and fluid overload (FO) was defined as percentage of admission body weight (BW). Maximum fluid overload (MFO) was the peak value of FO. Results We analysed 1734 patients. A total of 991 (57 %) had N-AKI, 560 (32 %) had AKI but did not have RRT and 183 (11 %) had AKI-RRT. ICU mortality was 22.3 % in AKI patients and 5.6 % in those without AKI ( p  < 0.0001). Progressive fluid accumulation was seen in all three groups. Maximum fluid accumulation occurred on day 2 in N-AKI patients (2.8 % of BW), on day 3 in AKI patients not receiving RRT (4.3 % of BW) and on day 5 in AKI-RRT patients (7.9 % of BW). The main findings were: (1) the odds ratio (OR) for hospital mortality increased by 1.075 (95 % confidence interval 1.055–1.095) with every 1 % increase of MFO. When adjusting for severity of illness and AKI status, the OR changed to 1.044. This phenomenon was a continuum and independent of thresholds as previously reported. (2) Multivariate analysis confirmed that the speed of fluid accumulation was independently associated with ICU mortality. (3) Fluid accumulation increased significantly in the 3-day period prior to the diagnosis of AKI and peaked 3 days later. Conclusions In critically ill patients, the severity and speed of fluid accumulation are independent risk factors for ICU mortality. Fluid balance abnormality precedes and follows the diagnosis of AKI.

ObjectivesThe aim of this study was to prioritise a set of indicators to measure World Health Organization (WHO) quality-of-care standards for small and/or sick newborns (SSNB) in health facilities. The hypothesis is that monitoring prioritised indicators can support accountability mechanisms, assess and drive progress, and compare performance in quality-of-care (QoC) at subnational levels.DesignProspective, iterative, deductive, stepwise process to prioritise a list of QoC indicators organised around the WHO Standards for improving the QoC for small and sick newborns in health facilities. A technical working group (TWG) used an iterative four-step deductive process: (1) articulation of conceptual framework and method for indicator development; (2) comprehensive review of existing global SSNB-relevant indicators; (3) development of indicator selection criteria; and (4) selection of indicators through consultations with a wide range of stakeholders at country, regional and global levels.SettingThe indicators are prioritised for inpatient newborn care (typically called level 2 and 3 care) in high mortality/morbidity settings, where most preventable poor neonatal outcomes occur.ParticipantsThe TWG included 24 technical experts and leaders in SSNB QoC programming selected by WHO. Global perspectives were synthesised from an online survey of 172 respondents who represented different countries and levels of the health system, and a wide range of perspectives, including ministries of health, research institutions, technical and implementing partners, health workers and independent experts.ResultsThe 30 prioritised SSNB QoC indicators include 27 with metadata and 3 requiring further development; together, they cover all eight standard domains of the WHO quality framework. Among the established indicators, 10 were adopted from existing indicators and 17 adapted. The list contains a balance of indicators measuring inputs (n=6), processes (n=12) and outcome/impact (n=9).ConclusionsThe prioritised SSNB QoC indicators can be used at health facility, subnational and national levels, depending on the maturity of a country’s health information system. Their use in implementation, research and evaluation across diverse contexts has the potential to help drive action to improve quality of SSNB care. WHO and others could use this list for further prioritisation of a core set.

ObjectivesRegular breast cancer screening is a widely used cancer prevention strategy. Important quality indicators of screening include cancer detection rate, false positive rate, benign biopsy rate and post-screen invasive cancer rate. We compared quality indicators of community radiology clinics to those of ‘Screen Test’, which feature centralised batch reading and quality control processes. Both types of providers operated under a single provincial Breast Cancer Screening Programme.SettingCommunity radiology clinics are operated by independent fee-for-service radiologists serving large and small communities throughout the Canadian province of Alberta. Launched by the provincial cancer agency, the Screen Test operates two physical clinics serving metropolises and mobile units serving remote regions. Eligible women may self-refer to any provider for screening mammography.ParticipantsWomen aged 50 to 69 years who had at least one screening mammogram between July 2006 and June 2010 in Alberta were included. Women with missing health region information or prior breast cancer diagnosis were excluded.ResultsA total of 389 788 screening mammograms were analysed, of which 12.7% were performed by Screen Test. Compared with Screen Test during 2006 to 2008, community radiology clinics had a lower cancer detection rate (3.6 vs 4.6 per 1000 screens, risk ratio (RR): 0.81, 95% CI: 0.67 to 0.98) and a much higher false positive rate (9.4% vs 3.4%, RR: 2.72, 95% CI: 2.55 to 2.90). Most other performance indicators were also better in Screen Test overall and across all health regions. These performance indicators were similar during 2008 to 2010, showing no improvement with time.ConclusionsScreen Test has a quality assurance process in place and performed significantly better. This provides empirical evidence of the effectiveness of a quality assurance process and may explain some of the large differences in breast cancer screening indicators between provinces and countries with formal programmes and those without.

ObjectivePerformance visualisation tools are increasingly being applied in healthcare to enhance decision-making and improve quality of care. However, there is a lack of comprehensive synthesis of their overall effectiveness and the contextual factors that influence their success in different clinical settings. This study aims to provide a broad synthesis of visualisation interventions not limited to a specific department.DesignSystematic review.Data sourcesMEDLINE and Embase were searched until December 2022.Eligibility criteriaRandomised controlled trials (RCTs) and observational studies in English involving a visualisation intervention, either alone or as a core intervention, that reported quantitative outcomes including process and outcome indicators.Data extraction and synthesisData on study characteristics, intervention characteristics, outcome measures and results were extracted. The quality of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation approach, and risk of bias was evaluated with Risk of Bias 2 for RCTs and Risk of Bias in Non-randomised Studies - of Interventions for non-randomised studies.Results Of the 12 studies included, 2 were RCTs and 10 were observational studies, including 1 before-after study and 1 interrupted time series study. Five studies (42%) were conducted in teaching hospital settings. Compared with the control group or baseline, 10 studies reported a statistically significant change in at least one of their outcome measures. A majority of the studies reported a positive impact, including prescription adherence (6/10), screening tests (3/10) and monitoring (3/10). Visualisation tool factors like type, clinical setting, workflow integration and clinician engagement, may have some influence on the effectiveness of the intervention, but no reliable evidence was identified.ConclusionPerformance visualisation tools have the potential to improve clinical performance indicators. More studies with standardised outcome measures and integrating qualitative methods are needed to understand the contextual factors that influence the effectiveness of these interventions.

ObjectivesDelivery of virtual care increased throughout the COVID-19 pandemic and persisted after physical distancing measures ended. However, little is known about how to measure the quality of virtual care, as current measures focus on in-person care and may not apply to a virtual context. This scoping review aims to understand the connections between virtual care modalities used with ambulatory patient populations and quality measures across the Quintuple Aim (provider experience, patient experience, per capita cost, population health and health equity).DesignVirtual care was considered any interaction between patients and/or their circle of care occurring remotely using any form of information technology. Five databases (MEDLINE, Embase, PsycInfo, Cochrane Library, JBI) and grey literature sources (11 websites, 3 search engines) were searched from 2015 to June 2021 and again in August 2022 for publications that analysed virtual care in ambulatory settings. Indicators were extracted, double-coded into the Quintuple Aim framework; patient and provider experience indicators were further categorised based on the National Academy of Medicine quality framework (safety, effectiveness, patient-centredness, timeliness, efficiency and equity). Sustainability was added to capture the potential for continued use of virtual care.Results13 504 citations were double-screened resulting in 631 full-text articles, 66 of which were included. Common modalities included video or audio visits (n=43), remote monitoring (n=11) and mobile applications (n=11). The most common quality indicators were related to patient experience (n=58 articles), followed by provider experience (n=25 articles), population health outcomes (n=23 articles) and health system costs (n=19 articles).ConclusionsThe connections between virtual care modalities and quality domains identified here can inform clinicians, administrators and other decision-makers how to monitor the quality of virtual care and provide insights into gaps in current quality measures. The next steps include the development of a balanced scorecard of virtual care quality indicators for ambulatory settings to inform quality improvement.

ImportanceInternational efforts are being made towards a person-centred care (PCC) model, but there are currently no standardised mechanisms to measure and monitor PCC at a healthcare system level. The use of metrics to measure PCC can help to drive the changes needed to improve the quality of healthcare that is person centred.ObjectiveTo develop and validate person-centred care quality indicators (PC-QIs) measuring PCC at a healthcare system level through a synthesis of the evidence and a person-centred consensus approach to ensure the PC-QIs reflect what matters most to people in their care.MethodsExisting indicators were first identified through a scoping review of the literature and an international environmental scan. Focus group discussions with diverse patients and caregivers and interviews with clinicians and experts in quality improvement allowed us to identify gaps in current measurement of PCC and inform the development of new PC-QIs. A set of identified and newly developed PC-QIs were subsequently refined by Delphi consensus process using a modified RAND/UCLA Appropriateness Method. The international consensus panel consisted of patients, family members, community representatives, clinicians, researchers and healthcare quality experts.ResultsFrom an initial 39 unique evidence-based PC-QIs identified and developed, the consensus process yielded 26 final PC-QIs. These included 7 related to structure, 16 related to process, 2 related to outcome and 1 overall global PC-QI.ConclusionsThe final 26 evidence-based and person-informed PC-QIs can be used to measure and evaluate quality incorporating patient perspectives, empowering jurisdictions to monitor healthcare system performance and evaluate policy and practice related to PCC.

ObjectiveAlthough 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.DesignThe 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 participantsA 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.ResultsThe 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.ConclusionsDrawing 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.