Health Care Quality Measures Research Articles

Ethics Consultation in U.S. Hospitals: Adherence to National Practice Standards

Background Adherence to widely accepted practice standards is a frequently used measure of healthcare quality. In the U.S., the most widely recognized authoritative source of practice standards for ethics consultation (EC) is the second edition of the American Society for Bioethics and Humanities’ Core Competencies for Healthcare Ethics Consultation report. Methods To determine the extent to which EC practices in U.S. hospitals adhere to these practice standards, we developed and analyzed 12 evaluative measures from a national survey. Results Only three of the 12 standards achieved over 75% adherence with reported EC practices: allowing anyone involved in a case to request an EC (100%), not requiring an attending physician’s permission to conduct an EC (97.6%), and having at least one person on the ethics consultation service (ECS) with advanced level EC proficiency (79.3%). Conclusions Implications are discussed for achieving consensus on EC standards as they continue to evolve.

The contributions of public health policies and healthcare quality to gender gap and country differences in life expectancy in the UK

BackgroundIn many high-income countries, life expectancy (LE) has increased, with women outliving men. This gender gap in LE (GGLE) has been explained with biological factors, healthy behaviours, health status, and sociodemographic characteristics, but little attention has been paid to the role of public health policies that include/affect these factors. This study aimed to assess the contributions of avoidable causes of death, as a measure of public health policies and healthcare quality impacts, to the GGLE and its temporal changes in the UK. We also estimated the contributions of avoidable causes of death into the gap in LE between countries in the UK.MethodsWe obtained annual data on underlying causes of death by age and sex from the World Health Organization mortality database for the periods 2001–2003 and 2014–2016. We calculated LE at birth using abridged life tables. We applied Arriaga’s decomposition method to compute the age- and cause-specific contributions into the GGLE in each period and its changes between two periods as well as the cross-country gap in LE in the 2014–2016 period.ResultsAvoidable causes had greater contributions than non-avoidable causes to the GGLE in both periods (62% in 2001–2003 and 54% in 2014–2016) in the UK. Among avoidable causes, ischaemic heart disease (IHD) followed by injuries had the greatest contributions to the GGLE in both periods. On average, the GGLE across the UK narrowed by about 1.0 year between 2001–2003 and 2014–2016 and three avoidable causes of IHD, lung cancer, and injuries accounted for about 0.8 years of this reduction. England & Wales had the greatest LE for both sexes in 2014–2016. Among avoidable causes, injuries in men and lung cancer in women had the largest contributions to the LE advantage in England & Wales compared to Northern Ireland, while drug-related deaths compared to Scotland in both sexes.ConclusionWith avoidable causes, particularly preventable deaths, substantially contributing to the gender and cross-country gaps in LE, our results suggest the need for behavioural changes by implementing targeted public health programmes, particularly targeting younger men from Scotland and Northern Ireland.

Are clinicians using routinely collected data to drive practice improvement? A cross-sectional survey

Clinical registry participation is a measure of healthcare quality. Limited knowledge exists on Australian hospitals' participation in clinical registries and whether this registry data informs quality improvement initiatives. To identify participation in clinical registries, determine if registry data inform quality improvement initiatives, and identify registry participation enablers and clinicians' educational needs to improve use of registry data to drive practice change. A self-administered survey was distributed to staff coordinating registries in seven hospitals in New South Wales, Australia. Eligible registries were international-, national- and state-based clinical, condition-/disease-specific and device/product registries. Response rate was 70% (97/139). Sixty-two (64%) respondents contributed data to 46 eligible registries. Registry reports were most often received by nurses (61%) and infrequently by hospital executives (8.4%). Less than half used registry data 'always' or 'often' to influence practice improvement (48%) and care pathways (49%). Protected time for data collection (87%) and benchmarking (79%) were 'very likely' or 'likely' to promote continued participation. Over half 'strongly agreed' or 'agreed' that clinical practice improvement training (79%) and evidence-practice gap identification (77%) would optimize use of registry data. Registry data are generally only visible to local speciality units and not routinely used to inform quality improvement. Centralized on-going registry funding, accessible and transparent integrated information systems combined with data informed improvement science education could be first steps to promote quality data-driven clinical improvement initiatives.

Risk Adjustment Model for Preserved Health Status in Patients With Heart Failure and Reduced Ejection Fraction: The CHAMP-HF Registry.

Health status outcomes are increasingly being promoted as measures of health care quality, given their importance to patients. In heart failure (HF), an American College of Cardiology/American Heart Association Task Force proposed using the proportion of patients with preserved health status as a quality measure but not as a performance measure because risk adjustment methods were not available. We built risk adjustment models for alive with preserved health status and for preserved health status alone in a prospective registry of outpatients with HF with reduced ejection fraction across 146 US centers between December 2015 and October 2017. Preserved health status was defined as not having a ≥5-point decrease in the Kansas City Cardiomyopathy Questionnaire Overall Summary score at 1 year. Using only patient-level characteristics, hierarchical multivariable logistic regression models were developed for 1-year outcomes and validated using data from 1 to 2 years. We examined model calibration, discrimination, and variability in sites' unadjusted and adjusted rates. Among 3932 participants (median age [interquartile range] 68 years [59-75], 29.7% female, 75.4% White), 2703 (68.7%) were alive with preserved health status, 902 (22.9%) were alive without preserved health status, and 327 (8.3%) had died by 1 year. The final risk adjustment model for alive with preserved health status included baseline Kansas City Cardiomyopathy Questionnaire Overall Summary, age, race, employment status, annual income, body mass index, depression, atrial fibrillation, renal function, number of hospitalizations in the past 1 year, and duration of HF (optimism-corrected C statistic=0.62 with excellent calibration). Similar results were observed when deaths were ignored. The risk standardized proportion of patients alive with preserved health status across the 146 sites ranged from 62% at the 10th percentile to 75% at the 90th percentile. Variability across sites was modest and changed minimally with risk adjustment. Through leveraging data from a large, outpatient, observational registry, we identified key factors to risk adjust sites' proportions of patients with preserved health status. These data lay the foundation for building quality measures that quantify treatment outcomes from patients' perspectives.

How to fix the Merit-based Incentive Payment System (MIPS) in emergency medicine.

How to fix the Merit-based Incentive Payment System (MIPS) in emergency medicine.

Implementation of collaborative care for depressive disorder treatment among accountable care organizations.

Collaborative care – primary care models combining care management, consulting behavioral health clinicians, and registries to target mental health treatment – is a cost-effective depression treatment model, but little is known about uptake of collaborative care in a national setting. Alternative payment models such as accountable care organizations (ACOs), in which ACOs are responsible for quality and cost for defined patient populations, may encourage collaborative care use.Determine prevalence of collaborative care implementation among ACOs and whether ACO structure or contract characteristics are associated with implementation.Cross-sectional analysis of 2017–2018 National Survey of ACOs (NSACO). Overall, 55% of ACOs returned a survey (69% of Medicare, 36% of non-Medicare ACOs); 48% completed at least half of core survey questions. We used logistic regression to examine the association between implementation of core collaborative care components – care management, a consulting mental health clinician, and a patient registry to track mental health symptoms – and ACO characteristics.Four hundred five National Survey of ACOs respondents answering questions on collaborative care implementation.Only 17% of ACOs reported implementing all collaborative care components. Most reported using care managers (71%) and consulting mental health clinicians (58%), =just 26% reported using patient registries. After adjusting for multiple ACO characteristics, ACOs responsible for mental health care quality measures were 15 percentage points (95% CI 5–23) more likely to implement collaborative care.Most ACOs are not utilizing behavioral health collaborative care. Including mental health care quality measures in payment contracts may facilitate implementation of this cost-effective model. Improving provider capacity to track and target depression treatment with patient registries is warranted as payment contracts focus on treatment outcomes.

State- and Provider-Level Racism and Health Care in the U.S.

This study examines the associations between state-level and provider sources of racism and healthcare access and quality for non-Hispanic Black and White individuals. Data from 2 sources were integrated: (1) data from the Association of American Medical Colleges' Consumer Survey of Health Care Access (2014-2019), which included measures of self-reported healthcare access, healthcare quality, and provider racial discrimination and (2) administrative data compiled to index state-level racism. State-level racism composite scores were calculated from federal sources (U.S. Census, Department of Labor, Department of Justice). The data set comprised 21,030 adults (n=2,110 Black, n=18,920 White) who needed care within the past year. Participants were recruited from a national panel, and the survey employed age-insurance quotas. Logistic and linear regressions were conducted in 2020, adjusting for demographic, geographic, and health-related covariates. Among White individuals, more state-level racism was associated with 5% higher odds of being able to get care and 6% higher odds of sufficient time with provider. Among Black individuals, more state-level racism was associated with 8% lower odds of being able to get care. Provider racial discrimination was also associated with 80% lower odds of provider explaining care, 77% lower odds of provider answering questions, and 68% lower odds of sufficient time with provider. State-level racism may engender benefits to healthcare access and quality for White individuals and may decrease access for Black individuals. Disparities may be driven by both White advantage and Black disadvantage. State-level policies may be the actionable levers of healthcare inequities with implications for preventive medicine.

Will Improvements in Patient Experience With Care Impact Clinical and Quality of Care Outcomes?: A Systematic Review.

Patient experiences with health care have been widely used as benchmark indicators of quality for providers, health care practices, and health plans. The objective of this study was to summarize the literature regarding the associations between Consumer Assessment of Healthcare Providers and Systems (CAHPS) patient experiences and clinical and quality outcomes. A systematic review of the literature was completed using PubMed, Embase, and Cumulative Index to Nursing and Allied Health Literature on December 14, 2019. Separate searches were conducted to query terms identifying CAHPS surveys with clinical and quality outcomes of care. Two reviewers completed all components of the search process. Studies investigating associations between CAHPS composite ratings and health care sensitive clinical outcomes or quality measures of care were included in this review. Studies were excluded if they did not investigate patient experiences using CAHPS composite ratings or if CAHPS composites were not treated as the independent variable. Nineteen studies met inclusion criteria, 10 investigating associations of CAHPS composite ratings with clinical outcomes and 9 investigating these associations with quality measures. Patient-provider communication was the most studied CAHPS composite rating and was significantly associated with self-reported physical and mental health, frequency of emergency room visits and inpatient hospital stays, hospitalization length, and CAHPS personal physician global ratings. Ratings of patient experience with care may influence clinical and quality outcomes of care. However, key inconsistencies between studies affirm that more research is needed to solidify this conclusion and investigate how patient experiences differentially relate to outcomes for various patient groups.

Value-Based Pay-for-Performance Gaps in the Care Delivery Framework for a Large-Scale Health System.

Many health systems are engaging in pay-for-performance agreements with payers that focus primarily on improving ambulatory preventive screenings. These also are referred to as gaps in care. Gaps in care are typically measured by the Healthcare Effectiveness Data and Information Set measures of health care quality. To address gaps in care effectively, the physician-led Gaps in Care program at Northwell Health works to improve processes related to measurement, data attribution, patient outreach, and patient engagement. Following a structured framework to address patient gaps in care is a successful strategy for accomplishing complex value-based care delivery.

Medication-Related Hospital Readmissions Within 30 Days of Discharge: Prevalence, Preventability, Type of Medication Errors and Risk Factors.

Background: Hospital readmission rates are increasingly used as a measure of healthcare quality. Medicines are the most common therapeutic intervention but estimating the contribution of adverse drug events as a cause of readmissions is difficult. Objectives: To assess the prevalence and preventability of medication-related readmissions within 30 days after hospital discharge and to describe the risk factors, type of medication errors and types of medication involved in these preventable readmissions. Design: A cross-sectional observational study. Setting: The study took place across the cardiology, gastroenterology, internal medicine, neurology, psychiatry, pulmonology and general surgery departments in the OLVG teaching hospital, Netherlands. Participants: Patients with an unplanned readmission within 30 days after discharge from an earlier hospitalization (index hospitalization: IH) were reviewed. Measurements: The prevalence and preventability of medication-related readmissions were assessed by residents in multidisciplinary meetings. A senior internist and hospital pharmacist reassessed the prevalence and preventability of identified cases. Generalized estimating equation with logistic regression was performed to identify risk factors of potentially preventable medication-related readmissions. Results: Of 1,111 included readmissions, 181 (16%) were medication-related, of which 72 (40%) were potentially preventable. The number of medication changes at IH (Adjusted odds ratio [ORadj]: 1.14; 95% CI: 1.05–1.24) and having ≥3 hospitalizations 6 months before IH (ORadj: 2.11; 95% CI: 1.12–3.98) were risk factors of a preventable medication-related readmission. Of these preventable readmissions, 35% were due to prescribing errors, 35% by non-adherence and 30% by transition errors. Medications most frequently involved were diuretics and antidiabetics. Conclusion: This study shows that 16% of readmissions are medication-related, of which 40% are potentially preventable. If the results are confirmed in larger multicentre studies, this may indicate that more attention should be paid to medication-related harm in order to lower the overall readmission rates.

ICRE Abstracts: Quality Improvement

ICRE Abstracts: Quality Improvement

Strategies for developing and implementing a rheumatoid arthritis healthcare quality framework: a thematic analysis of perspectives from arthritis stakeholders

ObjectivesTo obtain stakeholder perspectives to inform the development and implementation of a rheumatoid arthritis (RA) healthcare quality measurement framework.DesignQualitative study using thematic analysis of focus groups and interviews.SettingArthritis stakeholders from...

Are Spanish‐Speaking Families Less Satisfied with Care in Pediatric Otolaryngology?

Language barriers may impact family experience, which is a key measure of healthcare quality. We compared family satisfaction between Spanish-speaking families (SSF) and English-speaking families (ESF) in pediatric otolaryngology. Retrospective cohort study. Responses from the Family Experience Survey (FES), a hospital quality benchmarking survey, were analyzed from 2017 to 2019 at one academic pediatric otolaryngology practice. Question responses were compared between SSF versus ESF using mixed effect logistic regression models, adjusting for patient age, medical complexity, and insurance. A total of 4,964 FES survey responses were included (14% SSF). In multivariate analysis adjusting for age, medical complexity, and insurance, SSF were 1.7 times more likely than ESF to rate their provider with the highest rating (i.e. 9-10/10; 95% confidence interval [CI] 1.24-2.22). However, SSF were less likely than ESF to provide the highest rating on many individual aspects of care, including whether providers explained things intelligibly (odds ratio [OR] 0.43, 95% CI 0.25-0.74), listened carefully (OR 0.36, 95% CI 0.28-0.47), knew their medical child's history (OR 0.53, 95% CI 0.44-0.64), provided understandable information (OR 0.36, 95% CI 0.16-0.83), spent sufficient time with them (OR 0.38, 95% CI 0.31-0.48), allowed them to discuss their questions (OR 0.57, 95% CI 0.47-0.70), or had enough input in their children's' care (OR 0.46, 95% CI 0.26-0.80). In a large cohort of pediatric otolaryngology patients, SSF rated many individual aspects of their child's care less positively compared to ESF, despite rating their provider highly. Further research is needed to explore the reasons for these differences and how they can be improved. 4 Laryngoscope, 2021.

Development and validation of the predictive risk of death model for adult patients admitted to intensive care units in Japan: an approach to improve the accuracy of healthcare quality measures

BackgroundThe Acute Physiology and Chronic Health Evaluation (APACHE) III-j model is widely used to predict mortality in Japanese intensive care units (ICUs). Although the model’s discrimination is excellent, its calibration is poor. APACHE III-j overestimates the risk of death, making its evaluation of healthcare quality inaccurate. This study aimed to improve the calibration of the model and develop a Japan Risk of Death (JROD) model for benchmarking purposes.MethodsA retrospective analysis was conducted using a national clinical registry of ICU patients in Japan. Adult patients admitted to an ICU between April 1, 2018, and March 31, 2019, were included. The APACHE III-j model was recalibrated with the following models: Model 1, predicting mortality with an offset variable for the linear predictor of the APACHE III-j model using a generalized linear model; model 2, predicting mortality with the linear predictor of the APACHE III-j model using a generalized linear model; and model 3, predicting mortality with the linear predictor of the APACHE III-j model using a hierarchical generalized additive model. Model performance was assessed with the area under the receiver operating characteristic curve (AUROC), the Brier score, and the modified Hosmer–Lemeshow test. To confirm model applicability to evaluating quality of care, funnel plots of the standardized mortality ratio and exponentially weighted moving average (EWMA) charts for mortality were drawn.ResultsIn total, 33,557 patients from 44 ICUs were included in the study population. ICU mortality was 3.8%, and hospital mortality was 8.1%. The AUROC, Brier score, and modified Hosmer–Lemeshow p value of the original model and models 1, 2, and 3 were 0.915, 0.062, and < .001; 0.915, 0.047, and < .001; 0.915, 0.047, and .002; and 0.917, 0.047, and .84, respectively. Except for model 3, the funnel plots showed overdispersion. The validity of the EWMA charts for the recalibrated models was determined by visual inspection.ConclusionsModel 3 showed good performance and can be adopted as the JROD model for monitoring quality of care in an ICU, although further investigation of the clinical validity of outlier detection is required. This update method may also be useful in other settings.

Meaningful Use of Electronic Health Records and Ambulatory Healthcare Quality Measures.

IntroductionElectronic Health Record (EHR) adoption rates for office-based physicians doubled between 2008 and 2015, from 42% to 89%, and more than 60% of all office-based physicians achieved meaningful use by 2016. The US government has paid billions of dollars in incentives to promote EHR meaningful use. Nonetheless, evidence linking EHR meaningful use to quality measures improvements is limited.ObjectiveThis study aims to examine the relationship between EHR meaningful use and capabilities among four quality measures in an ambulatory healthcare setting.Study designA cross-sectional study design of the 2015-2016 National Ambulatory Medical Care Survey dataset.MethodsWe used adjusted multivariate regression models to examine associations between (a) EHR meaningful use and (b) 10 EHR-computerized capabilities, with four quality measures (blood pressure screening, tobacco use screening, obesity screening, and obesity education).ResultsWe analyzed 30,787 office visits, representing an annual estimate of 680 million national office visits. Results showed that 95% of visits were to offices meeting EHR meaningful use criteria. We found one positive association between EHR meaningful use and obesity screening (OR= 3.5, 95% CI [1.742-6.917]). We also found eight positive associations between EHR capabilities and three quality measures (screening for blood pressure and obesity, and obesity education). These associations included five EHR-computerized capabilities: “record patient problem list”, “view lab results”, “Reminders for interventions/screening”, “Order lab results” and “Recording clinical notes”. No EHR capability was associated with screening for tobacco use.ConclusionsWe looked at a handful of screening-oriented quality measures in ambulatory healthcare and found limited associations with EHR meaningful use but multiple positively significant associations with EHR capabilities. Although EHR meaningful use has become more commonly used, offering substantial administrative efficiency over paper records, current patterns of EHR meaningful use do not always appear to translate into a better quality of care in physician offices. However, quality measures used represent limited procedures for a handful of specific conditions and not the overall healthcare aspect.

Current status and future directions of U.S. genomic nursing health care policy

As genomic science moves beyond government-academic collaborations into routine healthcare operations, nursing's holistic philosophy and evidence-based practice approach positions nurses as leaders to advance genomics and precision health care in routine patient care. To examine the status of and identify gaps for U.S. genomic nursing health care policy and precision health clinical practice implementation. We conducted a scoping review and policy priorities analysis to clarify key genomic policy concepts and definitions, and to examine trends and utilization of health care quality benchmarking used in precision health. Genomic nursing health care policy is an emerging area. Educating and training the nursing workforce to achieve full dissemination and integration of precision health into clinical practice remains an ongoing challenge. Use of health care quality measurement principles and federal benchmarking performance evaluation criteria for precision health implementation are not developed. Nine recommendations were formed with calls to action across nursing practice workforce and education, nursing research, and health care policy arenas. To advance genomic nursing health care policy, it is imperative to develop genomic performance measurement tools for clinicians, purchasers, regulators and policymakers and to adequately prepare the nursing workforce.

Implementing Health Care Quality Measures in Electronic Health Records: A Conceptual Model.

There is significant literature on the development and validation of quality measures, but comparably less on their implementation into learning health systems. Electronic Health Records (EHRs) have made vast amounts of data available for quality improvement purposes. In this paper we describe a conceptual model for EHR implementation of quality measures. The model involves five steps: (1) select a measure; (2) define measure criteria; (3) validate criteria and measurement process; (4) improve recording of measure-related activity; and (5) engage quality improvement processes. The model was used to develop and implement a quality measure in the Home-Based Medical Care (HBMC) setting. Harris Health House Call Program (HHHC) provides primary medical and palliative care for homebound patients in Houston. Four-hundred twenty-four primary care patients followed in the HHHC. Completion rate of the 9-item Patient Health Questionnaire (PHQ-9) within the Electronic Health Record of newly enrolled HHHC patients. Use of the conceptual model to guide implementation of a quality measure of depression screening in a HMBC practice was successful. Additional components of early leadership and clinician buy-in were required, as well as strong relationships with IT to ease implementation and limit disruptions in clinicians' work-flow. This conceptual model was feasible for guiding implementation of a quality measure for depression care of HBMC patients, and it can guide broader implementation of EHR-based quality measures in the future.

Using Patient-Reported Outcomes toAssess Healthcare Quality: Toward Better Measurement of Patient-Centered Care in Cardiovascular Disease.

Patient-reported outcomes (PROs) are elicited directly from patients so they can describe their overall health status, including their symptoms, function, and quality of life. While commonly used as end points in clinical trials, PROs can play an important role in routine clinical care, population health management, and as a means for quantifying the quality of patient care. In this review, we propose that PROs be used to improve patient-centered care in the treatment of cardiovascular diseases given their importance to patients and society and their ability to improve doctor- provider communication. Furthermore, given the current variability in patients' health status across different clinics and the fact that PROs can be improved by titrating therapy, we contend that PROs have a key opportunity to serve as measures of healthcare quality.

Effect of effective patient communication and customer orientation on service quality leading to patient satisfaction: a study of multi-specialty hospitals of North India

Patient satisfaction has remained a cardinal indicator for the measurement of healthcare quality for a long time. It may be considered as a proxy but it is a dominant indicator to measure success of a hospital. As the hospital services are critical in nature and deal with the life and health of patients, effective and quality communication in a perceptive and convincing manner leads to patient satisfaction. Effective communication in hospitals results in patient compliance and better quality of services. The model tries to find out the impact of effective patient communication and customer orientation on service quality and effect of service quality on patient satisfaction. The structural model has been tested with the help of structural equation modelling using partial least square method, on a sample size of 500 patients from selected multi-specialty hospitals of North India. The findings of the study imply that effective patient communication and customer-oriented behaviour significantly impacts the service quality in multi-specialty hospitals which explains substantial variance in patient satisfaction.

Comparison of patient satisfaction toward healthcare performance between government hospitals and private hospitals

Background: Patient satisfaction is a direct measurement of healthcare quality and has gained momentum during the last three decades. The current study aimed to assess and compare patient satisfaction between government and private hospitals in the Kingdom of Saudi Arabia. Methodology: A cross-sectional online survey was conducted using a pre-tested and validated questionnaire. An Arabic version of National Health Service (NHS) and Quality Hospital Solutions (QHS) was used to collect the responses from the patients. The inclusion criteria included patients treated at any hospital, government or private, and adult patients (above 18 years old). Exclusion criteria included critically ill patients (CCU and ICU patients) and patients who cannot read and write. Satisfaction scores in various subdomains related to the hospital services were measured and were subjected to statistical analysis using Statistical Package for the Social Sciences ver.23 using appropriate tests of significance. Results: The overall satisfaction scores showed that there was no significant difference between government and private hospitals. Female patients were more satisfied than male patients. Patients’ satisfaction regarding attitude, behavior, and communication of doctors and auxiliary staff were significantly better in private hospitals than government hospitals. Conclusion: The satisfaction level of private hospital patients showed better scores in certain domains than government hospitals. Hospitals must enact quality improvement measures concerning administration and organization to enhance the quality of health services.