Selected Quality Measures Research Articles

Implementation of the WHO Standards to assess quality of paediatric care at the facility level using service users’ perspective as source of data: a multicentre quality improvement study in Italy

ObjectivesThere is little experience in the use of the WHO Standards for improving the quality of care (QOC) for children at the facility level. We describe the use of 75...

Pediatric Respiratory Illnesses: An Update on Achievable Benchmarks of Care.

Pediatric respiratory illnesses (PRI): asthma, bronchiolitis, pneumonia, croup, and influenza are leading causes of pediatric hospitalizations, and emergency department (ED) visits in the United States. There is a lack of standardized measures to assess the quality of hospital care delivered for these conditions. We aimed to develop a measure set for automated data extraction from administrative data sets and evaluate its performance including updated achievable benchmarks of care (ABC). A multidisciplinary subject-matter experts team selected quality measures from multiple sources. The measure set was applied to the Public Health Information System database (Children's Hospital Association, Lenexa, KS) to cohorts of ED visits and hospitalizations from 2017 to 2019. ABC for pertinent measures and performance gaps of mean values from the ABC were estimated. ABC were compared with previous reports. The measure set: PRI report includes a total of 94 quality measures. The study cohort included 984 337 episodes of care, and 82.3% were discharged from the ED. Measures with low performance included bronchodilators (19.7%) and chest x-rays (14.4%) for bronchiolitis in the ED. These indicators were (34.6%) and (29.5%) in the hospitalized cohort. In pneumonia, there was a 57.3% use of narrow spectrum antibiotics. In general, compared with previous reports, there was improvement toward optimal performance for the ABCs. The PRI report provides performance data including ABC and identifies performance gaps in the quality of care for common respiratory illnesses. Future directions include examining health inequities, and understanding and addressing the effects of the coronavirus disease 2019 pandemic on care quality.

Measuring Ambulatory Racial and Ethnic Neurologic Disparities With the Axon Registry.

The primary objective is to examine potential racial and ethnic (R/E) disparities in ambulatory neurology quality measures within the American Academy of Neurology Axon Registry. R/E disparities in neurologic US morbidity and mortality have been clearly documented. Despite these findings, there have been no nationwide examinations of how ambulatory neurologic care affects these negative health outcomes. This was a retrospective nonrandomized cohort study of patients in the AAN Axon Registry. The Axon Registry is a neurology-specific outpatient quality registry that collects, reports, and analyzes real-world deidentified electronic health record (EHR) data. Patients were included in the study if they contributed toward one of the selected quality measures for multiple sclerosis, epilepsy, Parkinson disease, or headache during the study period of January 1, 2019-December 31, 2019. Descriptive analyses of patient demographics were performed and then stratified by race and ethnicity. There were a total of 633,672 patients included in these analyses. Separate analyses were performed for race (64% White, 8% Black, 1% Asian, and 27% unknown) and ethnicity (52% not Hispanic, 5% Hispanic, and 43% unknown). The mean age ranged from 18 to 55 years, with 61% female and 39% male. Quality measures were chosen based on completeness of R/E data and were either process or outcomes focused. Statistically significant differences were noted after controlling for multiple comparisons. The large proportion of missing or unknown R/E data and low overall rate of performance on these quality measures made the relevance of small differences difficult to determine. This analysis demonstrates the feasibility of using the Axon Registry to assess neurologic disparities in outpatient care. More education and training are required on the accurate capture of R/E data in the EHR.

Bibliometric Survey on Particle Swarm Optimization Algorithms (2001–2021)

Particle swarm optimization algorithms (PSOA) is a metaheuristic algorithm used to optimize computational problems using candidate solutions or particles based on selected quality measures. Despite the extensive research published, studies that critically examine its recent scientific developments and research impact are lacking. Therefore, the publication trends and research landscape on PSOA research were examined. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and bibliometric analysis techniques were applied to identify and analyze the published documents indexed in Scopus from 2001 to 2021. The published documents on PSOA increased from 8 to 1,717 (21,362.50%) due to the growing applications of PSOA in solving computational problems. “Conference papers” is the most common document type, whereas the most prolific researcher on PSOA is Andries P. Engelbrecht (South Africa). The most active affiliation (Ministry of Education) and funding organization (National Natural Science Foundation) are based in China. The research landscape on PSOA revealed high levels of publications, citations, and collaborations among the top authors, institutions, and countries worldwide. Keywords co-occurrence analysis revealed that “particle swarm optimization (PSO)” occurred more frequently than others. The findings of the study could provide researchers and policymakers with insights into the prospects and challenges of PSOA research relative to similar algorithms in the literature.

Assessment of hearing screening programmes across 47 countries or regions II: coverage, referral, follow-up and detection rates from newborn hearing screening

Objectives To assess the performance of newborn hearing screening (NHS) programmes, through selected quality measures and their relationship to protocol design. Design NHS coverage, referral, follow-up and detection rates were aggregated. Referral rates were compared to age at screening step 1, number of steps, and test method: OAE or aABR. Study sample A questionnaire on existing hearing screening was completed by experts from countries in Europe, plus Russia, Malawi, Rwanda, India and China. Results Out of 47 countries or regions, NHS coverage rates were reported from 26, referral rates from 23, follow up from 12 and detection rates from 13. Median coverage rate for step 1 was 96%. Referral rate from step 1 was 6–22% where screening may be performed <24 h from birth, 2–15% for >24 h, and 4% for >72 h. Referral rates to diagnostic assessment averaged 2.1% after one to two steps using OAE only, 1.7% after two steps including aABR, and 0.8% after three to four steps including aABR. Median detection rate for bilateral permanent hearing impairment ≥40dB was 1 per 1000 infants. Conclusion Referral rates were related to age, test method and number of screening steps. Quality measures were not available for many NHS programmes.

Implementing Oregon’s New Quality Measurement Program for Assisted Living Communities

Oregon legislation requires assisted living (AL) communities to report selected quality measures to the state licensing agency. The Quality Measurement Program (QMP) includes five metrics that assess different areas of resident safety and wellbeing: falls, antipsychotic medication use, staff training, staff retention, and resident satisfaction. This paper describes findings based on our 2019 survey of AL communities and offers suggestions for stakeholders interested in public reporting and quality metrics. Assisted living providers reported 28% of AL residents and 38% of memory care (MC) residents fell at least once in the prior 90 days, with 39% and 45% reporting an injury, respectively. Antipsychotic medication use was 20% among AL and 44% among MC residents. These findings and the survey methods used to collect them, combined with stakeholder and state agency staff participation, informed the current QMP approach. We describe how to collect meaningful quality metrics within the AL context.

Development of An All-Payer Quality Program for the Pennsylvania Rural Health Model.

Measuring rural health care quality is challenging, and payer and government reporting requirements are frequently misaligned. The Pennsylvania Rural Health Model, a multipayer global budget demonstration for rural hospitals, initially required the proposal of an All-Payer Quality (APQ) Program in which participating payers would have held participating hospitals accountable for performance on a common set of quality measures. We sought to identify quality measures appropriate for use in APQ measurement and reporting programs for globally budgeted rural hospitals. A method was devised to identify, assess, and select quality measures from an environmental scan of core measure sets. An initial screen identified measures that were relevant, valid, and reliable. Four reviewers then independently assessed measures that passed the initial screen on a Likert scale of 1-5 for relevance, validity, reliability, responsiveness, alignment, and feasibility, and they selected a proposed measure set guided by prespecified measure set criteria. The 4 reviewers selected 10 quality measures from a list of 344 measures drawn from 8 core measure sets. One hundred twenty-five measures satisfied screening criteria and were assessed. The mean total score was 21.5/30 (95% CI: 17.0-26.0). Inter-rater reliability was moderate (intraclass correlation coefficient range 0.544-0.656). A formal performance measure selection methodology can generate a set of rural-appropriate health care quality measures for a multipayer rural hospital global budget program. This methodology could be replicated to select quality measures for inclusion in rural multipayer quality measurement and reporting programs.

Evaluation of outcome relevance of quality indicators in the emergency department (ENQuIRE): study protocol for a prospective multicentre cohort study

IntroductionQuality of emergency department (ED) care affects patient outcomes substantially. Quality indicators (QIs) for ED care are a major challenge due to the heterogeneity of patient populations, health care structures...

Association of the Comprehensive End-Stage Renal Disease Care Model With Medicare Payments and Quality of Care for Beneficiaries With End-Stage Renal Disease

Medicare beneficiaries with end-stage renal disease (ESRD) are a medically complex group accounting for less than 1% of the Medicare population but more than 7% of Medicare fee-for-service payments. To evaluate the association of the Comprehensive End-Stage Renal Disease Care (CEC) model with Medicare payments, health care use, and quality of care. In this economic evaluation, a difference-in-differences design estimated the change in outcomes for 73 094 Medicare fee-for-service beneficiaries aligned to CEC dialysis facilities between the baseline (from January 2014 to March 2015) and intervention periods (from October 2015 to December 2017) relative to 60 464 beneficiaries at matched dialysis facilities. In the CEC model, dialysis facilities, nephrologists, and other providers partner to form ESRD Seamless Care Organizations (ESCOs), specialty-oriented accountable care organizations that coordinate care for beneficiaries with ESRD. ESCOs with expenditures below a benchmark set by the Centers for Medicare & Medicaid Services are eligible to share in savings if they meet quality thresholds. A total of 685 dialysis facilities affiliated with 37 ESCOs participated in the CEC model as of January 2017. Thirteen ESCOs joined the CEC model on October 1, 2015 (wave 1), and 24 ESCOs joined on January 1, 2017 (wave 2). Patients with ESRD who were aligned with CEC dialysis facilities were compared with patients at matched dialysis facilities. Medicare total and service-specific payments per beneficiary per month; hospitalizations, readmissions, and emergency department visits; and select quality measures. Relative to the comparison group (n = 60 464; 55% men; mean [SD] age, 63.5 [14.4] years), total Medicare payments for CEC beneficiaries (n = 73 094; 56% men; mean [SD] age, 63.0 [14.4] years) decreased by $114 in payments per beneficiary per month (95% CI, -$202 to -$26; P = .01), associated primarily with decreases in payments for hospitalizations and readmissions. Payment reductions were offset by shared savings payments to ESCOs, resulting in net losses of $78 in payments per beneficiary per month (95% CI, -$8 to $164; P = .07). Relative to the comparison group, CEC beneficiaries had 5.01 fewer hospitalizations per 1000 beneficiaries per month (95% CI, -8.45 to -1.56; P = .004), as well as fewer catheter placements (CEC beneficiaries with catheter as vascular access for periods longer than 90 days decreased by 0.78 percentage points [95% CI, -1.36 to -0.19; P = .01]) and fewer hospitalizations for ESRD complications (CEC beneficiaries were 0.11 percentage points less likely [95% CI, -0.20 to -0.02; P = .01] to be hospitalized in a given month). Total dialysis sessions and payments increased, suggesting improved adherence to dialysis treatments. Early findings from the CEC model demonstrate that a specialty accountable care organization model focused on a particular population was associated with reduced payments and improved quality of care. Future research can assess the longer-term outcomes of the CEC model and its applicability to populations with other complex chronic conditions.

Exploring Resident Care Information Technology Use and Nursing Home Quality.

A wide array of sophisticated information technology (IT) systems are being used in nursing home (NH) resident care to improve quality. The purpose of the current study was to explore differences in NH IT sophistication, a comprehensive measure of adoption, used in resident care processes based on facility characteristics over 4 consecutive years and to examine the impact on select long-stay NH quality measures. Results indicate IT systems used in resident care are becoming increasingly sophisticated. NH bed size, type of ownership, and location were significant predictors of IT score in areas related to resident care. Results also suggest that as electronic clinical processes and documents increase (e.g., incident reporting, nursing flowsheets, care planning) in resident care, more falls with injury are detected. Continued assessments of NH IT sophistication are important as the impact of technology on quality continues to be evaluated. [Journal of Gerontological Nursing, 46(4), 15-20.].

End-of-Life Care Quality Outcomes Among Medicare Beneficiaries with Hematologic Malignancies

Background: Benefits of hospice care for patients with advanced solid cancers have been extensively studied, but they have not been comprehensively documented in hematologic malignancies (HM). Surveys indicate that hematologists harbor concerns about adequacy of hospice services for patients with HM (Odejide et al., Cancer 2017; Hui et al., Ann Oncol 2015). A common perception is that these patients often receive chemotherapy until the very end of life (EOL) and are destined to die in the acute care setting (Sekeres & Gerds, Cancer 2015). They also experience a barrier to hospice use when transfusion dependence develops (LeBlanc et al., Blood 2018). In this context, some authors have questioned whether standard measures of EOL care quality proposed by the National Quality Forum (NQF) should apply to patients with HM, and whether the use of hospice services can improve such measures. Our objective was to describe EOL care quality measures derivable from Medicare administrative claims among patients with HM who did or did not use hospice services.Methods: From the population-based linked SEER-Medicare registry, we selected fee-for-service beneficiaries with leukemias (acute or chronic), myeloma, myeloproliferative neoplasms (MPN), myelodysplastic syndrome (MDS), or lymphoma (any subtype), who died in 2007-2011. We identified beneficiaries who used hospice services, and ascertained claims-based indicators of aggressive EOL care corresponding to select NQF care quality measures: 1) death in acute care hospital, 2) number of days spent in acute care hospital within 30 days of death, 3) intensive care unit (ICU) admission within 30 days of death, 4) use of chemotherapy within 14 days of death, and 5) Medicare spending for care within the last 30 days of life. Binary outcomes were compared in multivariable robust Poisson models (reporting relative risk, RR), count outcomes in negative binomial models, and costs in a log-gamma model. All estimates were reported with 95% confidence intervals (CI). Models were adjusted for age, sex, race, marital status, Medicaid co-insurance (indicator of low socio-economic status), prevalent poverty in the county of residence, comorbidity index, poor performance status indicator, calendar year, and survival from diagnosis.Results: We identified 13,556 decedents with leukemia, 7,910 with myeloma, 9,543 with MPN/MDS, and 22,990 with lymphoma, who had median age at death of 78 years (interquartile range [IQR] 72-84). Overall, 47% of patients used hospice services, enrolling at median 22 months from diagnosis (IQR, 5-59; varying from 13 in leukemia to 28 in lymphoma). Median length of stay on hospice was 9 days (IQR, 3-27), varying from 8 to 10 days between different HM. Overall, 39% of patients died in hospital settings (from 36% in myeloma to 41% in leukemia). Median number of days spent in hospital at EOL was 4 in all types of HM. ICU admissions within the last month of life occurred in 39% of patients, and chemotherapy was administered to 10% in the last 14 days (varying from 7% in MPN/MDS to 13% in leukemia). These measures significantly differed between hospice enrollees and non-enrollees (Table).In multivariable models, use of hospice services was associated with a significant decrease in the aggressiveness of EOL care, as follows: 95% decrease in inpatient deaths (adjusted RR, 0.05; 95%CI, 0.05-0.06), 48% decrease in days spent in hospital (adjusted relative count, 0.62; 95%CI 0.60-0.63), 44% decrease in the risk of ICU stay (adjusted RR, 0.56; 95%CI, 0.54-0.57), 47% decrease in the use of chemotherapy (adjusted RR, 0.53; 95%CI, 0.50-0.57), and 38% decrease in mean Medicare spending at EOL (adjusted relative cost, 0.62; 95%CI, 0.60-0.63).Conclusions: The proportion of Medicare beneficiaries with HM who die in inpatient setting (39%) or are admitted to ICU (39%) in the last month of life is higher than in a contemporary population of Medicare beneficiaries with cancer (22% and 27%, respectively, in 2009 per Teno et al., JAMA 2013). Across the spectrum of HM, which vary in prognosis and clinical course, use of hospice services is associated with markedly improved measures of EOL care quality, as well as lower Medicare spending in the last month of life. However, only 47% of beneficiaries with HM use hospice services (compared with 59% in Teno et al.). Chemotherapy use at EOL was uncommon, challenging the notion that pervasive chemotherapy is a barrier to hospice use in HM. DisclosuresOlszewski:Genentech: Research Funding; Spectrum Pharmaceuticals: Consultancy, Research Funding; TG Therapeutics: Research Funding.

Washington State Community Cancer Care Report: Implications for value-based purchasing.

104 Background: As quality reports are released for regions and individual clinics, an important question is whether those reports can be used for value based purchasing, particularly for community oncology clinics. We evaluated the reliability of select quality measures and estimated the likelihood that a clinic’s performance would be incorrectly categorized (misclassified) in the top quartile. Methods: We linked 2014-2016 cancer registry records for patients with enrollment and claims from Medicare and two major commercial insurers in Washington State. We calculated risk standardized rates (RSRs) for ED and hospital use during treatment and 3 quality measures for end of life care. Reliability (0-1 scale: 0-unreliabile, &gt; 0.7 good reliability, 1 perfectly reliable) was calculated as signal/(signal + statistical noise) from hierarchical logistic regression modeling for each metric. Misclassification was characterized as the probability of false negative and false positive assignment of clinics to the top quartile of performers in the region. We generated results for 3 and 1 year performance periods. Results: Over the 3 year period, the hospitalization metrics included 7,373 patients, 25 clinics; end of life metrics included 8,165 patients; 24 clinics. Conclusions: Although these metrics had fairly high levels of reliability, approximately one-third of clinics could be incorrectly identified as a top quartile performer. Use of these metrics in value based purchasing should account for potential misclassification to minimize unintended consequences.[Table: see text]

Measuring and improving comprehensive pediatric cardiac care: Learning from continuous quality improvement methods and tools

Quality improvement (QI) is becoming a central part of the work of clinicians throughout healthcare. Continuous quality improvement (CQI), Lean Management Systems (LMS) and Lean Six Sigma (LSS) are management philosophies as well as management methods. They offer an approach, a set of tools, and a way of thinking about how to more effectively assess and study clinical flow, including addressing variation in clinical process and operations. We define CQI as the daily use of QI methods as a regular part of practice engaging all practice staff, constantly measuring structure, processes, outcomes against effective practices (benchmarking), moving from one QI project to the next, pursuing the goal of “The right care for every child every time”. It is based on clear scientific principles, a valid way of measuring change and has theories of reliability and human factors that underpin the interventions.Significant variations in quality of care provided to pediatric patients leading to substandard care have been well documented. For example, in antibiotic prescribing for community acquired pneumonia; pediatric secondhand smoke reduction; screening for diabetes in cystic fibrosis program; and, in depression screening in Type 1 Diabetes. Despite this, not enough pediatric practices are performing continuous quality improvement (CQI) as part of their daily activities.All health care professionals caring for children should consider incorporating quality measurement into their practice. However, we need to focus on what is the right approach to take and the right questions to ask and address the challenges of aggregating scientifically imperfect tests of change. Increasingly, colleagues, patients, payers and certifying agencies expect such measurement to achieve the Triple Aim of better health, better care and lower cost. In addition, new payment models increasingly pay providers for demonstrated value rather than volume, and they expect participation in continuous improvement. Quality Improvement (QI) is a critical component of the American Board of Pediatrics (ABP) Maintenance of Certification (MOC) Part 4. This requires pediatricians to participate in a meaningful manner in two data-driven QI projects every five years. Pediatricians can select quality measures to evaluate whether patient outcomes and experience improve, and if not, identify and overcome barriers. In this paper we discuss performance improvement using CQI and related methods, suggest approaches to help pediatric cardiologists to ask the right questions when seeking to drive improvement, and consider the implications of measurement theory and complexity science for QI and CQI.

Assessing the Quality of Nursing Homes in Managed Care Organizations: Integrating LTSS for Dually Eligible Beneficiaries.

Little is known about the quality of nursing homes in managed care organizations (MCOs) networks. This study (1) described decision-making criteria for selecting nursing home networks and (2) compared selected quality indicators of network and nonnetwork nursing homes. The sample was 17 MCOs participating in a California demonstration that provided integrated long-term services and supports to dually eligible enrollees in 2017. The findings showed that the MCOs established a broad network of nursing homes, with only limited attention to using quality criteria. Network nursing homes (602) scored significantly lower on 6 selected quality measures than nonnetwork (117) nursing homes. Low registered nurse and total nurse staffing were strong predictors of network nursing homes controlling for facility characteristics. Managed care organizations should consider greater transparency about the quality of their nursing homes and use specific quality criteria to improve the quality of their networks.

Multiclassifier Systems for Predicting Neurological Outcome of Patients with Severe Trauma and Polytrauma in Intensive Care Units.

This paper presents an ensemble based classification proposal for predicting neurological outcome of severely traumatized patients. The study comprises both the whole group of patients and a subgroup containing those patients suffering traumatic brain injury (TBI). Data was gathered from patients hospitalized in the Intensive Care Unit (ICU) of the University Hospital in Salamanca. Predictive models were induced from both epidemiologic and clinical variables taken at the emergency room and along the stay in the ICU. The large number of variables leads to a low accuracy in the classifiers even when feature selection methods are used. In addition, the presence of a much larger number of instances of one of the classes in the subgroup of TBI patients produces a significantly lesser precision for the minority class. Usual ways of dealing with the last problem is to use undersampling and oversampling strategies, which can lead to the loss of valuable data and overfitting problems respectively. Our proposal for dealing with these problems is based in the use of ensemble multiclassifiers as well as in the use of an ensemble playing the role of base classifier in multiclassifiers. The proposed strategy gave the best values of the selected quality measures (accuracy, precision, sensitivity, specificity, F-measure and area under the Receiver Operator Characteristic curve) as well as the closest values of precision for the two classes under study in the case of the classification from imbalanced data.

Communication Training, Adverse Events, and Quality Measures: 2 Retrospective Database Analyses in Washington State Hospitals.

Washington State's HealthPact program was launched in 2011 as part of AHRQ's Patient Safety and Medical Liability Reform initiative. HealthPact delivered interdisciplinary communication training to health-care professionals with the goal of enhancing safety. We conducted 2 exploratory, retrospective database analyses to investigate training impact on the frequency of adverse events (AEs) and select quality measures across 3 time frames: pretraining (2009-2011), transition (2012), and posttraining (2013). Using administrative data from Washington State's Comprehensive Hospital Abstract Reporting System (CHARS) and clinical registry data from the Surgical Care and Outcomes Assessment Program (SCOAP), we compared proportions of AEs and quality measures between HealthPact (n = 4) and non-HealthPact (n = 93-CHARS; n = 48-SCOAP) participating hospitals. Risk ratios enabled comparisons between the 2 groups. Multivariable logistic regression enabled investigation of the association between training and the frequency of AEs. Approximately 9.4% (CHARS) and 7.7% (SCOAP) of unique patients experienced 1 AE or greater. In CHARS, the odds of a patient experiencing an AE in a HealthPact hospital were initially (pretraining) higher than in a non-HealthPact hospital (odds ratio [OR], 1.13; 95% confidence interval [CI], 1.10-1.17), lower in transition (OR, 0.80; 95% CI, 0.76-0.83) and posttraining (OR, 0.72; 95% CI, 0.69-0.75) periods. In SCOAP, ORs were consistently lower in HealthPact hospitals: pretraining (OR, 0.87; 95% CI, 0.80-0.95), transition (OR, 0.75; 95% CI, 0.70-0.81), and posttraining (OR, 0.63; 95% CI, 0.58-0.68). The proportion of at-risk patients that experienced each individual AE was low (<1%) throughout. Adherence to quality measures was high. Interprofessional communication training is an area of intense activity nationwide. A broad-based training initiative may play a role in mitigating AEs.

Development of the Quality Data Collection Tool for Prospective Quality Assessment and Reporting in Palliative Care.

Assessing and reporting the quality of care provided are increasingly important in palliative care, but we currently lack practical, efficient approaches for collection and reporting. In response, the Global Palliative Care Quality Alliance ("Alliance") sought to create a Quality Data Collection Tool for Palliative Care (QDACT-PC). We collaboratively and iteratively developed QDACT-PC, an electronic, point-of-care quality monitoring system for palliative care that supports prospective quality assessment and reporting in any clinical setting. QDACT-PC is the web-based data collection and reporting interface. Quality measures selected to be used in QDACT-PC were derived from a systematic review summarizing all published palliative care quality measure sets; Alliance clinical providers prioritized measures to be included in QDACT-PC to ensure maximal clinical relevance. Data elements and variables required to ascertain conformance to all selected quality measures were included in the QDACT-PC data dictionary. Whenever possible, variables collected in QDACT-PC align with validated surveys and/or nationally recognized common data elements. QDACT-PC data elements and software programmed business rules inform real-time assessments of conformance to selected quality measures. Data are deposited into a centralized registry for future analyses. QDACT-PC can be used to report on >80% of all published palliative care quality measures and 100% of high-priority measure. Electronic methods for collecting point-of-care quality monitoring data can be developed using collaborative partnerships between community and academic palliative care providers. Feasibility testing and creation of feedback reports are ongoing.

Full-Reference Image Quality Assessment with Linear Combination of Genetically Selected Quality Measures.

Information carried by an image can be distorted due to different image processing steps introduced by different electronic means of storage and communication. Therefore, development of algorithms which can automatically assess a quality of the image in a way that is consistent with human evaluation is important. In this paper, an approach to image quality assessment (IQA) is proposed in which the quality of a given image is evaluated jointly by several IQA approaches. At first, in order to obtain such joint models, an optimisation problem of IQA measures aggregation is defined, where a weighted sum of their outputs, i.e., objective scores, is used as the aggregation operator. Then, the weight of each measure is considered as a decision variable in a problem of minimisation of root mean square error between obtained objective scores and subjective scores. Subjective scores reflect ground-truth and involve evaluation of images by human observers. The optimisation problem is solved using a genetic algorithm, which also selects suitable measures used in aggregation. Obtained multimeasures are evaluated on four largest widely used image benchmarks and compared against state-of-the-art full-reference IQA approaches. Results of comparison reveal that the proposed approach outperforms other competing measures.

Are reductions in emergency department length of stay associated with improvements in quality of care? A difference-in-differences analysis

BackgroundWe sought to determine whether patients seen in hospitals who had reduced overall emergency department (ED) length of stay (LOS) in the 2 years following the introduction of the Ontario...

Patients’ perceived value of pharmacy quality measures: a mixed-methods study

ObjectiveTo describe patients’ perceived value and use of quality measures in evaluating and choosing community pharmacies.DesignFocus group methodology was combined with a survey tool. During the focus groups, participants assessed...