National hospital ratings systems share few common scores and may generate confusion instead of clarity

Patient regional index: a new way to rank clinical specialties based on outpatient clinics big data

BACKGROUND

Many existing healthcare ranking systems are notably intricate. The standards for peer review and evaluation often differ across specialties, leading to contradictory results among various ranking systems. There is a significant need for a comprehensible and consistent mode of specialty assessment.

METHODS

This quantitative study aimed to assess the influence of clinical specialties on the regional distribution of patient origins based on 10,097,795 outpatient records of a large comprehensive hospital in South China. We proposed the patient regional index (PRI), a novel metric to quantify the regional influence of hospital specialties, using the principle of representative points of a statistical distribution. Additionally, a two-dimensional measure was constructed to gauge the significance of hospital specialties by integrating the PRI and outpatient volume.

RESULTS

We calculated the PRI for each of the 16 specialties of interest over eight consecutive years. The longitudinal changes in the PRI accurately captured the impact of the 2017 Chinese healthcare reforms and the 2020 COVID-19 pandemic on hospital specialties. At last, the two-dimensional assessment model we devised effectively illustrates the distinct characteristics across hospital specialties.

CONCLUSION

We propose a novel, straightforward, and interpretable index for quantifying the influence of hospital specialties. This index, built on outpatient data, requires only the patients' origin, thereby facilitating its widespread adoption and comparison across specialties of varying backgrounds. This data-driven method offers a patient-centric view of specialty influence, diverging from the traditional reliance on expert opinions. As such, it serves as a valuable augmentation to existing ranking systems.

Do Quality Measures or Hospital Characteristics Predict Readmission Penalties for Hip and Knee Arthroplasty?

BACKGROUND

Quality rating systems exist to grade the value of care provided by hospitals, but the extent to which these rating systems correlate with patient outcomes is unclear. The association of quality rating systems and hospital characteristics with excess readmission penalties for total hip arthroplasty (THA) and total knee arthroplasty (TKA) was studied.

METHODS

The fiscal year 2022 Inpatient Prospective Payment System final rule was used to identify 2,286 hospitals subject to the Hospital Readmissions Reduction Program. Overall, 6 hospital quality rating systems and 5 hospital characteristics were obtained. These factors were analyzed to determine the effect on hospital penalties for THA and TKA excess readmissions.

RESULTS

Hospitals that achieved a higher Medicare Overall Hospital Quality Star Rating demonstrated a significantly lower likelihood of receiving THA and TKA readmission penalties (Cramer's V = 0.236 and Rp = -0.233; P < .001 for both). Hospitals ranked among the US News & World Report's top 50 best hospitals for orthopaedics were significantly less likely to be penalized (V = 0.042; P = .043). The remaining 4 quality rating systems were not associated with readmission penalties. Penalization was more likely for hospitals with fewer THA and TKA discharges (Rp = -0.142; P < .001), medium-sized institutions (100 to 499 beds; V = 0.075; P = .002), teaching hospitals (V = 0.049; P = .019), and safety net hospitals (V = 0.043; P = .039). Penalization was less likely for West and Midwest hospitals (V = 0.112; P < .001).

CONCLUSIONS

A higher Overall Hospital Quality Star Rating and recognition among the US News & World Report's top 50 orthopaedic hospitals were associated with a reduced likelihood of THA and TKA readmission penalties. The other 4 widely accepted quality rating systems did not correlate with readmission penalties. Teaching and safety net hospitals may be biased toward higher readmission rates.

Hospital Rating Organizations' Quality and Patient Safety Scores: Analysis of Result Discrepancies

BACKGROUND

In the USA, multiple organizations rate hospitals based on quality and patient safety data, but few studies have analyzed and compared the rating results.

OBJECTIVE

Compare the results of different US hospital-rating organizations.

DESIGN

Observational data analysis of US acute care hospital ratings.

PARTICIPANTS

Four rating organizations: Hospital Compare® (HC), Healthgrades® (HG), The Leapfrog Group® (Leapfrog), and US News and World Report® (USN).

MAIN MEASURES

We analyzed the level of concordance (similar ranking), discordance (difference of 1 or more rankings), and severe discordance (difference of two or more rankings), as well as differences and correlations between the scores.

KEY RESULTS

From Feb 1 to Oct 3, 2023, we analyzed data from 2,384 hospitals. In Leapfrog, there were 688 hospitals (29%) with Grade A, 652 (27.3%) with B, 885 (37.1%) with C, 153 (6.4%) with D, and 6 (0.3%) with F. For HC, 333 hospitals (14%) had five stars, 676 (28.4%) four, 695 (29.2%) three, 502 (21.4%) two, and 171 (7.2%) one-star. In ratings between HC and Leapfrog, discordance was 70%, and severe discordance was 25.1%. USN ranked 469 hospitals (19.7%). Within the USN-ranked hospital group, there was a 62% discordance and 19.8% severe discordance between HC and Leapfrog. The analysis of orthopedic procedures from HG and USN showed discordance ranging from 48 to 61.2%.

CONCLUSION

The rating organizations' reported metrics were highly discordant. A hospital's ranking by one organization frequently did not correspond to a similar ranking by another. The methodology and included timeline and patient population can help explain the differences. However, the discordant ratings may confuse patients and customers.

Payer-Negotiated Price Variation and Relationship to Surgical Outcomes for the Most Common Cancers at NCI-Designated Cancer Centers

BACKGROUND

Federal rules mandate that hospitals publish payer-specific negotiated prices for all services. Little is known about variation in payer-negotiated prices for surgical oncology services or their relationship to clinical outcomes. We assessed variation in payer-negotiated prices associated with surgical care for common cancers at National Cancer Institute (NCI)-designated cancer centers and determined the effect of increasing payer-negotiated prices on the odds of morbidity and mortality.

MATERIALS AND METHODS

A cross-sectional analysis of 63 NCI-designated cancer center websites was employed to assess variation in payer-negotiated prices. A retrospective cohort study of 15,013 Medicare beneficiaries undergoing surgery for colon, pancreas, or lung cancers at an NCI-designated cancer center between 2014 and 2018 was conducted to determine the relationship between payer-negotiated prices and clinical outcomes. The primary outcome was the effect of median payer-negotiated price on odds of a composite outcome of 30 days mortality and serious postoperative complications for each cancer cohort.

RESULTS

Within-center prices differed by up to 48.8-fold, and between-center prices differed by up to 675-fold after accounting for geographic variation in costs of providing care. Among the 15,013 patients discharged from 20 different NCI-designated cancer centers, the effect of normalized median payer-negotiated price on the composite outcome was clinically negligible, but statistically significantly positive for colon [aOR 1.0094 (95% CI 1.0051-1.0138)], lung [aOR 1.0145 (1.0083-1.0206)], and pancreas [aOR 1.0080 (1.0040-1.0120)] cancer cohorts.

CONCLUSIONS

Payer-negotiated prices are statistically significantly but not clinically meaningfully related to morbidity and mortality for the surgical treatment of common cancers. Higher payer-negotiated prices are likely due to factors other than clinical quality.

Pre-COVID-19 hospital quality and hospital response to COVID-19: examining associations between risk-adjusted mortality for patients hospitalised with COVID-19 and pre-COVID-19 hospital quality

OBJECTIVES

The extent to which care quality influenced outcomes for patients hospitalised with COVID-19 is unknown. Our objective was to determine if prepandemic hospital quality is associated with mortality among Medicare patients hospitalised with COVID-19.

DESIGN

This is a retrospective observational study. We calculated hospital-level risk-standardised in-hospital and 30-day mortality rates (risk-standardised mortality rates, RSMRs) for patients hospitalised with COVID-19, and correlation coefficients between RSMRs and pre-COVID-19 hospital quality, overall and stratified by hospital characteristics.

SETTING

Short-term acute care hospitals and critical access hospitals in the USA.

PARTICIPANTS

Hospitalised Medicare beneficiaries (Fee-For-Service and Medicare Advantage) age 65 and older hospitalised with COVID-19, discharged between 1 April 2020 and 30 September 2021.

INTERVENTION/EXPOSURE

Pre-COVID-19 hospital quality.

OUTCOMES

Risk-standardised COVID-19 in-hospital and 30-day mortality rates (RSMRs).

RESULTS

In-hospital (n=4256) RSMRs for Medicare patients hospitalised with COVID-19 (April 2020-September 2021) ranged from 4.5% to 59.9% (median 18.2%; IQR 14.7%-23.7%); 30-day RSMRs ranged from 12.9% to 56.2% (IQR 24.6%-30.6%). COVID-19 RSMRs were negatively correlated with star rating summary scores (in-hospital correlation coefficient -0.41, p<0.0001; 30 days -0.38, p<0.0001). Correlations with in-hospital RSMRs were strongest for patient experience (-0.39, p<0.0001) and timely and effective care (-0.30, p<0.0001) group scores; 30-day RSMRs were strongest for patient experience (-0.34, p<0.0001) and mortality (-0.33, p<0.0001) groups. Patients admitted to 1-star hospitals had higher odds of mortality (in-hospital OR 1.87, 95% CI 1.83 to 1.91; 30-day OR 1.46, 95% CI 1.43 to 1.48) compared with 5-star hospitals. If all hospitals performed like an average 5-star hospital, we estimate 38 000 fewer COVID-19-related deaths would have occurred between April 2020 and September 2021.

CONCLUSIONS

Hospitals with better prepandemic quality may have care structures and processes that allowed for better care delivery and outcomes during the COVID-19 pandemic. Understanding the relationship between pre-COVID-19 hospital quality and COVID-19 outcomes will allow policy-makers and hospitals better prepare for future public health emergencies.

Lack of associations between hospital rating and outcomes in patients with an acute coronary syndrome

BACKGROUND

Public reporting of performance data has become a common tool in evaluation of healthcare providers. The rating may be misleading if the association between the measured variables and the outcome is weak.

METHODS AND RESULTS

Nationwide, register-based, cohort study. All Swedish patients hospitalised with an acute coronary syndrome during the time periods 2006-2010 and 2015-2017 were included in the study. Possible associations between cardiovascular morbidity and mortality for these patients and ranking scores for each hospital in a Swedish healthcare quality register for acute coronary syndromes were analysed. We found no association between the ranking score and mortality, and no or weak associations between the ranking score and readmissions.

CONCLUSIONS

Lack of associations between quality measurements and patient outcomes warrants improvement in ranking scores. Cautious use of the ranking results is necessary in comparisons between healthcare providers.

It takes quality improvement to cross the chasm

Healthcare organisations in the USA rank significantly lower in quality of care compared with other developed nations. Research shows US performance emphasises expensive treatment over effective prevention programmes. This study demonstrates how a comprehensive quality improvement programme can improve health outcomes in a large county-based Medicaid health plan. The health plan serves a diverse community of members spanning racial and ethnic groups with varying levels of clinical risk and social determinants of health burdens. We used a regression discontinuity design to evaluate the impact of a comprehensive quality improvement programme vs using mainly pay-for-performance on Healthcare Effectiveness Data and Information Set (HEDIS) metrics over the course of 10 years. We found significant improvements in several HEDIS metrics that occurred after the quality improvement programme was implemented. These results demonstrate the importance of using a comprehensive quality improvement strategy along with pay-for-performance to improve health outcomes. It was determined that this research was exempt from institutional review board approval, as it used administrative healthcare data, and did not involve direct interventions with human subjects.

The Imperfect Science of Publicly Reported Hospital Rating Systems: Lessons From Credit Rating Agencies

The number of publicly available hospital quality rating systems has substantially increased over the past 2 decades. These rating systems are meant to provide patients, clinicians, and payers with relevant information to select and pay differentially for better quality of care. However, there is evidence of inconsistency, unreliability, and bias in current hospital quality rating systems. Financial ratings are similarly intended to enable investors to identify stronger companies (as investment targets), and these rating systems could provide insight into strategies to improve hospital quality ratings. We evaluate the credit rating methodologies of Standard & Poor's, Moody's, and Fitch Group and propose principles to improve hospital quality rating systems through better standardized measures and the use of external audits of source data. Emulating key features of credit rating systems may advance the delivery of meaningful hospital quality ratings.

ICD-11: A catalyst for advancing patient safety surveillance globally

The World Health Organization's (WHO) international classification of disease version 11 (ICD-11) contains several features which enable improved classification of patient safety events. We have identified three suggestions to facilitate adoption of ICD-11 from the patient safety perspective. One, health system leaders at national, regional, and local levels should incorporate ICD-11 into all approaches to monitor patient safety. This will allow them to take advantage of the innovative patient safety classification methods embedded in ICD-11 to overcome several limitations related to existing patient safety surveillance methods. Two, application developers should incorporate ICD-11 into software solutions. This will accelerate adoption and utility of software-enabled clinical and administrative workflows relevant to patient safety management. This is enabled as a result of the ICD-11 application programming interface (or API) developed by the WHO. Third, health system leaders should adopt the ICD-11 using a continuous improvement framework. This will help leaders at national, regional and local levels to take advantage of specific existing initiatives which will be strengthened by ICD-11, including peer review comparisons, clinician engagement, and alignment of front-line safety efforts with post marketing surveillance of medical technologies. While the investment to adopt ICD-11 will be considerable, these will be offset by reducing the ongoing costs related to a lack of accurate routine information.

Comparing Consumer-Directed Hospital Rankings With STS Adult Cardiac Surgery Database Outcomes

BACKGROUND

Public interest in stratifying hospital performance has led to the proliferation of commercial, consumer-oriented hospital rankings. In cardiac surgery, little is known about how these rankings correlate with clinical registry quality ratings.

METHODS

The Society of Thoracic Surgeons (STS) Adult Cardiac Surgery Database was queried for isolated coronary artery bypass grafting or coronary artery bypass grafting/valve patients at hospitals among the top 100 U.S. News & World Report (USNWR) Cardiology & Heart Surgery rankings from 2016 to 2020. Hospitals were grouped into deciles by risk-adjusted observed/expected (O/E) ratios for morbidity and mortality using the STS 2018 risk models. Agreement between STS Adult Cardiac Surgery Database and USNWR ranked deciles was calculated by Bowker symmetry test. The association between each center's annual change in STS O/E ratio and change in USNWR ranking was modeled in repeated measures regression analysis.

RESULTS

Inclusion criteria were met by 524 393 patients from 149 hospitals that ranked in USNWR top 100 at least once during the study period. There was no agreement between USNWR ranking and STS major morbidity and mortality O/E ratio (P > .50 for all years). Analysis of patients undergoing surgery at the 65 hospitals that were consistently ranked in the top 100 during the study period demonstrated no association between annual change in hospital ranking and change in O/E ratio (P all > .3).

CONCLUSIONS

There was no agreement between annual USNWR hospital ranking and corresponding risk-adjusted STS morbidity or mortality. Furthermore, annual changes in USNWR rankings could not be accounted for using clinical outcomes. These findings suggest that factors unrelated to key surgical outcomes may be driving consumer-directed rankings.

The impact of transparency constraints on the efficiency of the Russian healthcare system: systematic literature review

There is an ongoing debate among researchers and policy-makers on how to make transparency a powerful tool of healthcare systems. This study addresses how the availability and accessibility of information about medical services to the general population affects healthcare outcomes in Russia. A systematic review was conducted and reported according to the Preferred Reporting Items for Systematic Reviewing and Meta-Analysis (PRISMA) guidelines. Transparency indicators of health facilities used in the world's most efficient healthcare systems are also reviewed. Although the increase of transparency in the Russian healthcare system is considered as a tool for improving its efficiency, very little has been done to improve the actual level of transparency. The existing institutional specifics of the Russian healthcare system impose serious restrictions on acceptable levels of transparency. In the reviewed empirical Russian studies, transparency is often viewed simplistically as either information available on the websites of medical organizations or issues related to the amount of accessible indicators of compulsory medical statistical reporting. The novelty of this study consists in (a) reviewing the most recent studies on the topic and (b) including studies in Russian in the analysis. We elaborate on general and specific policy implications for improving transparency-driven outcomes in the Russian healthcare system.

In-hospital Outcomes and Cost Associated With Treatments for Non-ST-elevation Myocardial Infarction

Background

Although variation in the management of patients with non-ST-elevation myocardial infarction (NSTEMI) is well documented across US hospitals, few data exist characterizing variation in outcomes following specific management strategies.

Methods

Admissions for NSTEMI to hospitals performing coronary angiography, percutaneous coronary intervention (PCI), and coronary artery bypass graft (CABG) surgery between 2016 and 2018 were identified from the National Inpatient Sample. Patients were categorized according to treatment rendered (medical therapy alone, angiography without revascularization, PCI, or CABG). The primary end point was variation in the incidence of composite in-hospital death, postprocedure myocardial infarction, or stroke, stratified by treatment rendered. Secondary outcomes included variation in length of stay (LOS), cost, and use of each treatment modality. Variation was characterized by the median odds ratio.

Results

Among 140,194 hospitalizations for NSTEMI, 35,748 (25.5%) patients received medical therapy alone, 28,678 (20.5%) underwent angiography without revascularization, 58,383 (41.6%) underwent PCI, and 17,385 (12.4%) underwent CABG. Despite adjusting for patient- and hospital-related factors, 2 similar patients were 25% more likely to experience the composite primary outcome following PCI and 45% more likely following CABG at 1 randomly selected hospital than at another. Significant hospital-level variations in LOS and cost were also apparent following each treatment modality.

Conclusions

In a large national analysis of hospitalizations for NSTEMI, significant variation was observed in clinical outcome, LOS, and cost associated with each treatment modality, despite adjustment for patient- and hospital-related factors.

Patient safety indicators from a spine surgery perspective: the importance of a specialty specific clinician working with the documentation team and the impact to your hospital

BACKGROUND CONTEXT

The Hospital Acquired Conditions (HAC) Reduction Program supports the Centers for Medicare and Medicaid Services (CMS) effort to prevent harm to patients by providing a financial incentive to reduce HACs. HAC scores are impacted by Patient Safety Indicators (PSIs), potentially preventable hospital-related events associated with harmful patient outcomes. PSIs are identified using International Classification of Diseases (ICD) coding; however, ICD coding does not always reflect the patient's true medical course.

PURPOSE

To evaluate the efficacy of and costs savings associated with a clinical documentation review process in tandem with clinician collaboration in identifying incorrectly generated PSIs.

STUDY DESIGN

Retrospective chart review.

PATIENT SAMPLE

All patients undergoing spine surgery at a single multi-surgeon tertiary spine center.

OUTCOME MEASURES

Occurrence of PSI.

METHODS

Over two 11-month periods, all PSIs attributable to spine surgery were determined. The number and type of spine related PSIs were compared before (Control) and after the implementation of a specialty specific clinical review (Intervention) to identify incorrectly generated PSIs. The financial impact of this intervention was calculated in the form of an annual cost savings to our hospital system.

RESULTS

During the Control phase, 61 PSIs were reported in 3368 spine cases, representing a total of 3.6 PSIs/month. During Intervention phase, 26 PSIs in 4,482 spine cases, resulting in a statistically significant decrease of 1.5 PSIs per month. The percentage of PSIs across all surgical cases attributable to spine surgery had a statistically significant decrease during the Intervention period compared to the Control period (16% vs. 10%, p=.034), resulting in the avoidance of a 1% CMS cost reduction, an annual cost saving of approximately $3-4 million dollars per year.

CONCLUSIONS

The implementation of a clinical documentation review process with clinician collaboration to ensure ICD-10 coding accurately reflects the patient's medical course leads to more accurate PSI reporting, with the potential for substantial cost-savings for hospitals from CMS reimbursement.

Use of hospitals in the New York City Metropolitan Region, by race: how separate? How equal in resources and quality?

BACKGROUND

Although racial and ethnic minorities disproportionately use some hospitals, hospital-based racial and ethnic composition relative to geographic region and its association with quality indicators has not been systematically analyzed.

METHODS

We used four race and ethnicity categories: non-Hispanic white (NHW), non-Hispanic black (NHB), Hispanic, and Asian/Pacific Islander/Alaskan Native/American Indian (API/AIAN), as well as a combined non-NHW category, from the 2010 (latest year publicly available) Medicare Institutional Provider & Beneficiary Summary public use file for 84 hospitals in the New York City region. We assessed the relative distribution of race and ethnicity across hospitals grouped at different geographic levels (region, county, hospital referral region [HRR], or hospital service areas [HSA]) using the dissimilarity index. Hospital characteristics included quality star ratings, essential professional services and diagnostic/treatment equipment, bed size, total expenses, and patients with dual Medicare and Medicaid enrollment. We assessed Spearman's rank correlation between hospital-based racial and ethnic composition and quality/structural measures.

RESULTS

Dissimilarity Index decreases from region (range 30.3-40.1%) to county (range 13.7-23.5%), HRR (range 10.5-27.5%), and HSA (range 12.0-16.9%) levels. Hospitals with larger non-NHW patients tended to have lower hospital ratings and higher proportions of dually-enrolled patients. They were also more likely to be safety net hospitals and non-federal governmental hospitals.

CONCLUSIONS

In the NYC metropolitan region, there is considerable hospital-based racial and ethnic segregation of Medicare patients among non-NHW populations, extending previous research limited to NHB. Availability of data on racial and ethnic composition of hospitals should be made publicly available for researchers and consumers.

Best and worst performing health facilities: A positive deviance analysis of perceived drivers of primary care performance in Nepal

Primary care services are on average of low quality in Nepal. However, there is marked variation in performance of basic clinical and managerial functions between primary health care centers. The determinants of variation in primary care performance in low- and middle-income countries have been understudied relative to the prominence of primary care in national health plans. We used the positive deviance approach to identify best and worst performing primary health care centers in Nepal and investigated perceived drivers of best performance. We selected eight primary health care centers in Province 1, Nepal, using an index of basic clinical and operational activities to identify four best and four worst performing primary health care centers. We conducted semi-structured, in-depth interviews with managers and clinical staff from each of the eight primary health care centers for a total of 32 interviews. We identified the following factors that distinguished best from worst performers: 1) Managing the facility effectively, 2) engaging local leadership, 3) building active community accountability, 4) assessing and responding to facility performance, 5) developing sources of funding, 6) compensating staff fairly, 7) managing clinical staff performance, and 8) promoting uninterrupted availability of supplies and equipment. These findings can be used to inform quality improvement efforts and health system reforms in Nepal and other similarly under-resourced health systems.

•

Local leaders and health workers felt good management was key to best performance.

•

Best performers reported strong leadership at both the facility and local levels.

•

Community accountability was also seen as a critical enabler of top performance.

•

Leaders of worst performers were less responsive to facility and community needs.

Relationships Between Pediatric Safety Indicators Across a National Sample of Pediatric Hospitals: Dispelling the Myth of the "Safest" Hospital

OBJECTIVE

There are many measures of healthcare quality, but no obvious summary measures to simplify ranking of hospital performance. With public reporting and accountability for hospital performance, the validity of composite measures for performance rankings has increased importance. This study aimed to explore the covariance of pediatric hospital quality indicators and evaluate the use of a single composite score.

METHODS

We performed an observational study of pediatric hospital performance across 13 safety indicators extracted from the Pediatric Health Information System, a comparative database of children's hospitals in the United States. We included patients discharged from 36 hospitals from January 1, 2016, to December 31, 2019. Using principal components analysis, we investigate relationships among patient safety measures from the Agency for Healthcare Research and Quality pediatric quality indicators and Center for Medicare and Medicaid Services hospital-acquired conditions. We compare and summarize rankings based on individual safety indicators and calculate alternative composite scores.

RESULTS

We identified 5 orthogonal variance components accounting for 68% of variation in pediatric hospital quality indicators. Rankings demonstrated greater within-hospital variation compared with between-hospital variation. We observed discordant rankings across commonly used summary measures and conclude that these pediatric safety measures demonstrate at least 2 underlying variance components.

CONCLUSIONS

This study demonstrates the multifactorial nature of patient safety. This implies no unique ordering of hospitals based on these measures, and thus, no pediatric hospital can claim to be "the safest." This raises further questions about appropriate methods to rank hospitals by safety.

Hospital Characteristics and Early Enrollment Trends in the American College of Cardiology Voluntary Public Reporting Program

IMPORTANCE

Limited data exist regarding the characteristics of hospitals that do and do not participate in voluntary public reporting programs.

OBJECTIVE

To describe hospital characteristics and trends associated with early participation in the American College of Cardiology (ACC) voluntary reporting program for cardiac catheterization-percutaneous coronary intervention (CathPCI) and implantable cardioverter-defibrillator (ICD) registries.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study analyzed enrollment trends and characteristics of hospitals that did and did not participate in the ACC voluntary public reporting program. All hospitals reporting procedure data to the National Cardiovascular Data Registry (NCDR) CathPCI or ICD registries that were eligible for the public reporting program from July 2014 (ie, program launch date) to May 2017 were included. Stepwise logistic regression was used to identify hospital characteristics associated with voluntary participation. Enrollment trends were evaluated considering the date US News & World Report (USNWR) announced that it would credit participating hospitals. Data analysis was performed from March 2017 to January 2018.

MAIN OUTCOMES AND MEASURES

Hospital characteristics and participation in the public reporting program.

RESULTS

By May 2017, 561 of 1747 eligible hospitals (32.1%) had opted to participate in the program. Enrollment increased from 240 to 376 hospitals (56.7%) 1 month after the USNWR announcement that program participation would be considered as a component of national hospital rankings. Compared with hospitals that did not enroll, program participants had increased median (IQR) procedural volumes for PCI (481 [280-764] procedures vs 332 [186-569] procedures; P < .001) and ICD (114 [56-220] procedures vs 62 [25-124] procedures; P < .001). Compared with nonparticipating hospitals, an increased mean (SD) proportion of participating hospitals adhered to composite discharge medications after PCI (0.96 [0.03] vs 0.92 [0.07]; P < .001) and ICD (0.88 [0.10] vs 0.81 [0.12]; P < .001). Hospital factors associated with enrollment included participation in 5 or more NCDR registries (odds ratio [OR],1.98; 95% CI, 1.24-3.19; P = .005), membership in a larger hospital system (ie, 3-20 hospitals vs ≤2 hospitals in the system: OR, 2.29; 95% CI, 1.65-3.17; P = .001), participation in an NCDR pilot public reporting program of PCI 30-day readmissions (OR, 2.93; 95% CI, 2.19-3.91; P < .001), university affiliation (vs government affiliation: OR, 3.85, 95% CI, 1.03-14.29; P = .045; vs private affiliation: OR, 2.22; 95% CI, 1.35-3.57; P < .001), Midwest location (vs South: OR, 1.47; 95% CI, 1.06-2.08; P = .02), and increased comprehensive quality ranking (4 vs 1-2 performance stars in CathPCI: OR, 8.08; 95% CI, 5.07-12.87; P < .001; 4 vs 1 performance star in ICD: OR, 2.26; 95% CI, 1.48-3.44; P < .001) (C statistic = 0.829).

CONCLUSIONS AND RELEVANCE

This study found that one-third of eligible hospitals participated in the ACC voluntary public reporting program and that enrollment increased after the announcement that program participation would be considered by USNWR for hospital rankings. Several hospital characteristics, experience with public reporting, and quality of care were associated with increased odds of participation.

Patient Outcomes With Febrile Neutropenia Based on Time to Antibiotics in the Emergency Department

OBJECTIVE

Although bacteremia in pediatric oncology patients with febrile neutropenia (FN) is not uncommon, sepsis and mortality are rare. Because of the lack of clinically meaningful decision tools to identify high-risk patients with bacteremia, time to antibiotic administration (TTA) is increasingly considered an important quality and safety measure in the emergency department. Because little evidence exists suggesting that this benchmark is beneficial, we sought to determine whether TTA of 60 minutes or less is associated with improved outcomes.

METHODS

We retrospectively reviewed patients presenting to a pediatric emergency department with FN from November 2013 to June 2016. Clinical outcomes including mortality, pediatric intensive care unit admission, imaging, fluid resuscitation of 40 mL/kg or greater in the first 24 hours, and length of stay were compared between TTA of 60 minutes or less and more than 60 minutes.

RESULTS

One hundred seventy-nine episodes of FN were analyzed. The median TTA was 76 minutes (interquartile range, 58-105). The incidence of bacteremia was higher in patients with TTA of more than 60 minutes (12% vs 2%, P = 0.04), but without impact on mortality, pediatric intensive care unit admission, fluid resuscitation, or median length of stay. The median TTA was not different for those who were and were not bacteremic (91 vs 73 minutes, P = 0.11).

CONCLUSIONS

Time to antibiotic administration of more than 60 minutes did not increase mortality in pediatric oncology patients with FN. Our study adds to the existing literature that TTA of 60 minutes or less does not seem to improve outcomes in pediatric FN. Further larger studies are required to confirm these findings and determine which features predispose pediatric FN patients to morbidity and mortality.

Leapfrog Hospital Safety Score, Magnet Designation, and Healthcare-Associated Infections in United States Hospitals

OBJECTIVE

Healthcare-associated infections (HAIs) pose a challenge to patient safety. Although studies have explored individual level, few have focused on organizational factors such as a hospital's safety infrastructure (indicated by Leapfrog Hospital Safety Score) or workplace quality (Magnet recognition). The aim of the study was to determine whether Magnet and hospitals with better Leapfrog Hospital Safety Scores have fewer HAIs.

METHODS

Ordered probit regression analyses tested associations between Safety Score, Magnet status, and standardized infection ratios, depicting whether a hospital had a Clostridium difficile infection (CDI) and methicillin-resistant Staphylococcus aureus (MRSA) bloodstream infection standardized infection ratio that was "better," "no different," or "worse" than a National Benchmark as per Centers for Disease Control and Prevention's National Healthcare Safety Network definitions.

RESULTS

Accounting for confounders, relative to "A" hospitals, "B" and "C" hospitals had significant and negative relationships with CDI (-0.16, P < 0.01, and -0.14, P < 0.05, respectively) but not MRSA bacteremia. Magnet hospitals had a significant and positive relationship with MRSA bloodstream infections (0.74, P < 0.001) but a significant negative relationship with CDI (-0.21, P < 0.01) compared with non-Magnet.

CONCLUSIONS

A hospitals performed better on CDI but not MRSA bloodstream infections. In contrast, Magnet designation was associated with fewer than expected MRSA infections but more than expected CDIs. These mixed results indicate that hospital global assessments of safety and workplace quality differentially and imperfectly predict its level of HAIs, suggesting the need for more precise organizational measures of safety and more nuanced approaches to infection prevention and reduction.

The Impact of Public Reporting Schemes and Market Competition on Hospital Efficiency

In the wake of growing attempts to assess the validity of public reporting, much research has examined the effectiveness of public reporting regarding cost or quality of care. However, relatively little is known about whether transparency through public reporting significantly influences hospital efficiency despite its emerging expectations for providing value-based care. This study aims to identify the dynamics that transparency brought to the healthcare market regarding hospital technical efficiency, taking the role of competition into account. We compare the two public reporting schemes, All-Payer Claims Database (APCD) and Hospital Compare. Employing Data Envelopment Analysis (DEA) and a cross-sectional time-series Tobit regression analysis, we found that APCD is negatively associated with hospital technical efficiency, while hospitals facing less competition responded significantly to increasingly transparent information by enhancing their efficiency relative to hospitals in more competitive markets. We recommend that policymakers take market mechanisms into consideration jointly with the introduction of public reporting schemes in order to produce the best outcomes in healthcare.

Sustainers: Hospitals with sustained superior performance

PURPOSE

The purpose of this article was to investigate the organizational and market-level variables associated with sustained superior hospital performance on Value-Based Purchasing total performance scores (TPS).

METHODOLOGY

TPS for 2014 through 2017 was obtained from the Centers for Medicare & Medicaid Services Hospital Compare website. Market-level data were from the 2017 Area Health Resource File, and hospital-level data were from the 2014 American Hospital Association Annual Survey database. We specified a logistic regression model to identify significant predictors of hospitals with sustained superior performance on TPS, that is, "sustainers."

PRINCIPAL FINDINGS

Only 8.4% of hospitals were classified as sustainers. Hospitals located in rural markets with a high Medicare Advantage penetration had a higher likelihood of being classified as sustainers. High RN staffing levels, lower Medicare share of inpatient days, not-for-profit ownership, and small size were all significant organizational predictors of sustained superior performance.

CONCLUSIONS

Both modifiable characteristics, such as nurse staffing levels, and nonmodifiable characteristics, such as rural markets and small hospital size, are associated with the likelihood of hospitals sustaining superior performance over time.

PRACTICE IMPLICATIONS

Managers need to carefully examine their staffing levels as they pursue interventions to sustain high TPS overtime. Moreover, factors such as Medicare share of inpatient days and size need to be considered when understanding barriers to sustained performance on Value-Based Purchasing domains.

Using Consistently Low Performance to Identify Low-Quality Physician Groups

Importance

There has been a growth in the use of performance-based payment models in the past decade, but inherently noisy and stochastic quality measures complicate the assessment of the quality of physician groups. Examining consistently low performance across multiple measures or multiple years could potentially identify a subset of low-quality physician groups.

Objective

To identify low-performing physician groups based on consistently low performance after adjusting for patient characteristics across multiple measures or multiple years for 10 commonly used quality measures for diabetes and cardiovascular disease (CVD).

Design, Setting, and Participants

This cross-sectional study used medical and pharmacy claims and laboratory data for enrollees ages 18 to 65 years with diabetes or CVD in an Aetna health insurance plan between 2016 and 2019. Each physician group's risk-adjusted performance for a given year was estimated using mixed-effects linear probability regression models. Performance was correlated across measures and time, and the proportion of physician groups that performed in the bottom quartile was examined across multiple measures or multiple years. Data analysis was conducted between September 2020 and May 2021.

Exposures

Primary care physician groups.

Main Outcomes and Measures

Performance scores of 6 quality measures for diabetes and 4 for CVD, including hemoglobin A1c (HbA1c) testing, low-density lipoprotein testing, statin use, HbA1c control, low-density lipoprotein control, and hospital-based utilization.

Results

A total of 786 641 unique enrollees treated by 890 physician groups were included; 414 655 (52.7%) of the enrollees were men and the mean (SD) age was 53 (9.5) years. After adjusting for age, sex, and clinical and social risk variables, correlations among individual measures were weak (eg, performance-adjusted correlation between any statin use and LDL testing for patients with diabetes, r = -0.10) to moderate (correlation between LDL testing for diabetes and LDL testing for CVD, r = .43), but year-to-year correlations for all measures were moderate to strong. One percent or fewer of physician groups performed in the bottom quartile for all 6 diabetes measures or all 4 cardiovascular disease measures in any given year, while 14 (4.0%) to 39 groups (11.1%) were in the bottom quartile in all 4 years for any given measure other than hospital-based utilization for CVD (1.1%).

Conclusions and Relevance

A subset of physician groups that was consistently low performing could be identified by considering performance measures across multiple years. Considering the consistency of group performance could contribute a novel method to identify physician groups most likely to benefit from limited resources.

Relationship Between Perioperative Outcomes Used for Profiling Hospital Noncardiac Surgical Quality

BACKGROUND

Risk-adjusted morbidity and mortality are commonly used by national surgical quality improvement (QI) programs to measure hospital-level surgical quality. However, the degree of hospital-level correlation between mortality, morbidity, and other perioperative outcomes (like reoperation) collected by contemporary surgical QI programs has not been well-characterized.

MATERIALS AND METHODS

Veterans Affairs (VA) Surgical Quality Improvement Program (VASQIP) data (2015-2016) were used to evaluate hospital-level correlation in performance between risk-adjusted 30-d mortality, morbidity, major morbidity, reoperation, and 2 composite outcomes (1- mortality, major morbidity, or reoperation; 2- mortality or major morbidity) after noncardiac surgery. Correlation between outcomes rates was evaluated using Pearson's correlation coefficient. Correlation between hospital risk-adjusted performance rankings was evaluated using Spearman's correlation.

RESULTS

Based on a median of 232 [IQR 95-331] quarterly surgical cases abstracted by VASQIP, statistical power for identifying 30-d mortality outlier hospitals was estimated between 3.3% for an observed-to-expected ratio of 1.1 and 45.7% for 3.0. Among 230,247 Veterans who underwent a noncardiac operation at 137 VA hospitals, there were moderate hospital-level correlations between various risk-adjusted outcome rates (highest r = 0.40, mortality and composite 1; lowest r = 0.32, mortality and morbidity). When hospitals were ranked based on performance, there was low-to-moderate correlation between rankings on the various outcomes (highest ρ = 0.47, mortality and composite 1; lowest ρ = 0.37, mortality and major morbidity).

CONCLUSIONS

Modest hospital-level correlations between perioperative outcomes suggests it may be difficult to identify high (or low) performing hospitals using a single measure. Additionally, while composites of currently measured outcomes may be an efficient way to improve analytic sample size (relative to evaluations based on any individual outcome), further work is needed to understand whether they provide a more robust and accurate picture of hospital quality or whether evaluating performance across a portfolio of individual measures is most effective for driving QI.

The Association of "U.S. News & World Report" Hospital Rankings and Outcomes Following Anterior Cervical Fusions: Do Rankings Even Matter?

STUDY DESIGN

Retrospective observational study.

OBJECTIVE

The aim of this study was to evaluate whether there are any differences in outcomes and costs for elective one- to three-level anterior cervical fusions (ACFs) performed at US News and World Report (USNWR) ranked and unranked hospitals.

SUMMARY OF BACKGROUND DATA

Although the USNWR rankings are advertised by media and are routinely used by patients as a guide in seeking care, evidence regarding whether these rankings are reflective of actual clinical outcome remains limited.

METHODS

The 2010-2014 USNWR hospital rankings were used to identify ranked hospitals in "Neurosurgery" and "Orthopedics." The 2010-2014 100% Medicare Standard Analytical Files (SAF100) were used to identify patients undergoing elective ACFs at ranked and unranked hospitals. Multivariable logistic regression and generalized linear regression analyses were used to assess for differences in 90-day outcomes and costs between ranked and unranked hospitals.

RESULTS

A total of 110,520 patients undergoing elective one- to three-level ACFs were included in the study, of which 10,289 (9.3%) underwent surgery in one of the 100 ranked hospitals. Following multivariate analysis, there were no significant differences between ranked versus unranked hospitals with regards to wound complications (1.2% vs. 1.1%; P = 0.907), cardiac complications (12.9% vs. 11.9%; P = 0.055), pulmonary complications (3.7% vs. 6.7%; P = 0.654), urinary tract infections (7.3% vs. 5.8%; P = 0.120), sepsis (9.3% vs. 7.9%; P = 0.847), deep venous thrombosis (1.9% vs. 1.3%; P = 0.077), revision surgery (0.3% vs. 0.3%; P = 0.617), and all-cause readmissions (4.7% vs. 4.4%; P = 0.266). Ranked hospitals, as compared to unranked hospitals, had a slightly lower odds of experiencing renal complications (7.0% vs. 4.9%; P = 0.047), but had significantly higher risk-adjusted 90-day charges (+$17,053; P < 0.001) and costs (+ $1695; P < 0.001).

CONCLUSION

Despite the higher charges and costs of care at ranked hospitals, these facilities appear to have similar outcomes as compared to unranked hospitals following elective ACFs.Level of Evidence: 3.

Higher Medicare Advantage Star Ratings Are Associated With Improvements In Patient Outcomes

Little is known about how well the Centers for Medicare and Medicaid Services' five-star rating system for the overall quality of Medicare Advantage (MA) contracts captures quality of care. Leveraging contract consolidation as a natural experiment to study the association between outcomes and insurer-initiated enrollee shifts to plans with higher-rated contracts, we found that enrollees experiencing a one-star MA rating increase were 20.8 percent less likely to voluntarily leave their plan to enroll in another plan or traditional Medicare. When hospitalized, they were 3.4 percent more likely to use a higher-quality hospital and 2.6 percent less likely to be readmitted within ninety days. Our findings suggest that MA star ratings may capture key domains of an MA plan's quality; however, the differences in outcomes that they capture might not all be clinically meaningful.

The Mayo Clinic Hospital Mortality Reduction Project: Description and Results

EXECUTIVE SUMMARY

Quality improvement, regulatory, and payer organizations use various definitions of hospital mortality as clinical outcome measures. In this prospective study, the authors evaluated a multicomponent intervention aimed at reducing inpatient mortality in a multistate healthcare delivery system. The project was initiated because of a statistically nonsignificant upward trend in mortality suggested by a six-quarter rise in the observed/expected mortality ratio generated by the Vizient Clinical Data Base and Resource Manager. The design of the mortality reduction plan was influenced by the known limitations of using hospital-wide mortality as a quality improvement measure. The primary objective was to reduce mortality through focused care redesign. The project leadership team attempted to implement standardized system-wide improvements while allowing individual hospitals to simultaneously pursue site-specific practice redesign opportunities. Between Q3, 2015, and Q4, 2017, system-wide mortality reduced from 1.78 to 1.53 (per 100 admissions; p = .01). The actual plan implemented in Mayo Clinic's hospitals is included as Appendix A to this article, published online as Supplemental Digital Content. The authors included it to allow comparison with similar efforts at other healthcare systems, as well as to stimulate criticism and discussion by readers.

Comparing Precision Machine Learning With Consumer, Quality, and Volume Metrics for Ranking Orthopedic Surgery Hospitals: Retrospective Study

Background

Patients’ choices of providers when undergoing elective surgeries significantly impact both perioperative outcomes and costs. There exist a variety of approaches that are available to patients for evaluating between different hospital choices.

Objective

This paper aims to compare differences in outcomes and costs between hospitals ranked using popular internet-based consumer ratings, quality stars, reputation rankings, average volumes, average outcomes, and precision machine learning–based rankings for hospital settings performing hip replacements in a large metropolitan area.

Methods

Retrospective data from 4192 hip replacement surgeries among Medicare beneficiaries in 2018 in a the Chicago metropolitan area were analyzed for variations in outcomes (90-day postprocedure hospitalizations and emergency department visits) and costs (90-day total cost of care) between hospitals ranked through multiple approaches: internet-based consumer ratings, quality stars, reputation rankings, average yearly surgical volume, average outcome rates, and machine learning–based rankings. The average rates of outcomes and costs were compared between the patients who underwent surgery at a hospital using each ranking approach in unadjusted and propensity-based adjusted comparisons.

Results

Only a minority of patients (1159/4192, 27.6% to 2078/4192, 49.6%) were found to be matched to higher-ranked hospitals for each of the different approaches. Of the approaches considered, hip replacements at hospitals that were more highly ranked by consumer ratings, quality stars, and machine learning were all consistently associated with improvements in outcomes and costs in both adjusted and unadjusted analyses. The improvement was greatest across all metrics and analyses for machine learning–based rankings.

Conclusions

There may be a substantive opportunity to increase the number of patients matched to appropriate hospitals across a broad variety of ranking approaches. Elective hip replacement surgeries performed at hospitals where patients were matched based on patient-specific machine learning were associated with better outcomes and lower total costs of care.

Healthcare systems approach to patient reported outcomes-benefits and challenges in thoracic surgery

Quality outcomes are the ultimate goal for our thoracic surgery patients. The collection of data to measure the outcomes have been in place for many years and yet are insufficient. The inclusion of patient reported outcomes (PROs) into data reporting, collection and analysis will help to truly understand what matters most to patients and allow us to provide value-based care every time. It is the responsibility of the healthcare system to provide the resources in order to leverage the patient voice and collect meaningful PROs that can influence the best outcomes possible.

Relationship of Hospital Star Ratings to Race, Education, and Community Income

INTRODUCTION

The Centers for Medicare & Medicaid Services (CMS) publishes hospital quality ratings to provide more transparent and useable quality information to patients and stakeholders. However, there is a gap in the literature regarding the geographic distribution of the hospitals with higher star ratings. In this paper, we focus on the associations between star ratings and community characteristics, including racial/ethnic mix, household income, educational attainment, and regional difference.

METHODS

A retrospective study and cross-sectional logistic and multinomial logistic regression analyses.

RESULTS

According to the multivariate regression results, hospitals in areas with lower income, lower educational attainment, and higher minority population shares have lower quality ratings (lower income: odds ratio [OR] 0.67; 95% CI, 0.49-0.91; lower education: OR 0.66; 95% CI, 0.51-0.85; higher minority: OR 0.52; 95% CI, 0.40-0.69). Compared with hospitals in the Midwest, hospitals in Northeast, South, and West regions have lower quality ratings (Northeast: OR 0.37; 95% CI, 0.25-0.56; South: OR 0.68; 95% CI, 0.51-0.91; West: OR 0.69; 95% CI, 0.49-0.97).

DISCUSSION AND CONCLUSION

Overall, our results show that hospitals with higher star ratings are less likely to be located in communities with higher minority populations, lower income, and lower levels of educational attainment. Findings contribute to the discussion of integrating social factors in hospital quality star rating calculation methodologies.

Do Hospital Rankings Mislead Patients? Variability Among National Rating Systems for Orthopaedic Surgery

INTRODUCTION

A growing number of online hospital rating systems for orthopaedic surgery are found. Although the accuracy and consistency of these systems have been questioned in other fields of medicine, no formal analysis of these systems in orthopaedics has been found.

METHODS

Five hospital rating systems (US News, HealthGrades, CareChex, Women's Choice, and Hospital Compare) were examined which designate "high-performing" and "low-performing" hospitals for orthopaedic surgery. Descriptive analysis was conducted for all hospitals defined as high- or low-performing in any of the five rating systems, and assessment for agreement/disagreement between ratings was done. A subsample of hospitals ranked by all systems was then created, and agreement between rating systems was investigated using a Cohen's kappa. Each hospital was included in a multinomial logistic regression model investigating which hospital characteristics increased the odds of being favorably/unfavorably rated by each system.

RESULTS

One thousand six hundred forty hospitals were evaluated by every rating system. Six hundred thirty-eight unique hospitals were identified as high-performing by at least 1 rating system; however, no hospital was ranked as high-performing by all five rating systems. Four hundred fifty-two unique hospitals were identified as low-performing; however, no hospital was ranked as low-performing by all the three rating systems which define low-performing hospitals. Within the study subsample of hospitals evaluated by each system, little agreement between any combination of rating systems (κ < 0.10) regarding top-tier or bottom-tier performance was found. It was more likely for a hospital to be considered high-performing by one system and low-performing by another (10.66%) than for the majority of the five rating systems to consider a hospital high-performing (3.76%).

CONCLUSION

Little agreement between hospital quality rating systems for orthopaedic surgery is found. Publicly available hospital ratings for performance in orthopaedic surgery offer conflicting results and provide little guidance to patients, providers, or payers when selecting a hospital for orthopaedic surgery.

LEVEL OF EVIDENCE

Level 1 economic study.

National Evaluation of Patient Preferences in Selecting Hospitals and Health Care Providers

BACKGROUND

Patient utilization of public reporting has been suboptimal despite attempts to encourage use. Lack of utilization may be due to discordance between reported metrics and what patients want to know when making health care choices.

OBJECTIVE

The objective of this study was to identify measures of quality that individuals want to be presented in public reporting and explore factors associated with researching health care.

RESEARCH DESIGN

Patient interviews and focus groups were conducted to develop a survey exploring the relative importance of various health care measures.

SUBJECTS

Interviews and focus groups conducted at local outpatient clinics. A survey administered nationally on an anonymous digital platform.

MEASURES

Likert scale responses were compared using tests of central tendency. Rank-order responses were compared using analysis of variance testing. Associations with binary outcomes were analyzed using multivariable logistic regression.

RESULTS

Overall, 4672 responses were received (42.0% response rate). Census balancing yielded 2004 surveys for analysis. Measures identified as most important were hospital reputation (considered important by 61.9%), physician experience (51.5%), and primary care recommendations (43.2%). Unimportant factors included guideline adherence (17.6%) and hospital academic affiliation (13.3%, P<0.001 for all compared with most important factors). Morbidity and mortality outcome measures were not among the most important factors. Patients were unlikely to rank outcome measures as the most important factors in choosing health care providers, irrespective of age, sex, educational status, or income.

CONCLUSIONS

Patients valued hospital reputation, physician experience, and primary care recommendations while publicly reported metrics like patient outcomes were less important. Public quality reports contain information that patients perceive to be of relatively low value, which may contribute to low utilization.

U.S. hospital performance methodologies: a scoping review to identify opportunities for crossing the quality chasm

Background

Hospital performance quality assessments inform patients, providers, payers, and purchasers in making healthcare decisions. These assessments have been developed by government, private and non-profit organizations, and academic institutions. Given the number and variability in available assessments, a knowledge gap exists regarding what assessments are available and how each assessment measures quality to identify top performing hospitals. This study aims to: (a) comprehensively identify current hospital performance assessments, (b) compare quality measures from each methodology in the context of the Institute of Medicine’s (IOM) six domains of STEEEP (safety, timeliness, effectiveness, efficiency, equitable, and patient-centeredness), and (c) formulate policy recommendations that improve value-based, patient-centered care to address identified gaps.

Methods

A scoping review was conducted using a systematic search of MEDLINE and the grey literature along with handsearching to identify studies that provide assessments of US-based hospital performance whereby the study cohort examined a minimum of 250 hospitals in the last two years (2017–2019).

Results

From 3058 unique records screened, 19 hospital performance assessments met inclusion criteria. Methodologies were analyzed across each assessment and measures were mapped to STEEEP. While safety and effectiveness were commonly identified measures across assessments, efficiency, and patient-centeredness were less frequently represented. Equity measures were also limited to risk- and severity-adjustment methods to balance patient characteristics across populations, rather than stand-alone indicators to evaluate health disparities that may contribute to community-level inequities.

Conclusions

To further improve health and healthcare value-based decision-making, there remains a need for methodological transparency across assessments and the standardization of consensus-based measures that reflect the IOM’s quality framework. Additionally, a large opportunity exists to improve the assessment of health equity in the communities that hospitals serve.

Assessing the Agreement of Hospital Performance on 3 National Mortality Ratings for 2 Common Inpatient Conditions

This study assesses the agreement of the US Centers for Medicare & Medicaid Services Hospital Compare, Healthgrades, and US News & World Report Best Hospitals on hospital performance for chronic obstructive pulmonary disease and heart failure.

Correlation between hospital rating agencies' data: An analysis and recommendation

Hospital rating agencies exist to inform consumers through publicly available patient safety data. The large number of rating agencies, the variability in their methodologies and data presentations leave few consumers considering these data in making healthcare decisions. The objective of this study was to analyze the comparability of data from four different healthcare rating agencies to understand whether there exists a correlation among the rating agencies' published data. Four well-known rating agencies' data were gathered for 30 Connecticut hospitals and analyzed using correlation methods. The overall rating score was used for comparison accounting for patients' probability of referencing this score in determining a hospital's safety. The results indicate little or no correlation between ratings of Connecticut hospitals among the reviewed rating agencies. The only statistically significant correlation was between CMS and Leapfrog. The lack of correlation among rating agencies' publicly available data identified in this study leads to consumer confusion. This research provides support for the need for a valid, reliable, and transparent healthcare rating system to inform patient decision making. These findings can be used to advocate for a legislatively mandated national reporting system that focuses on user understanding of the data.

Steering by their own lights: Why regulators across Europe use different indicators to measure healthcare quality

•

Indicator sets differ in how they define, measure, and assess healthcare quality.

•

National sets shaped by varying governance traditions and healthcare system configuration.

•

Targeting of quality dimensions and hospital activities shaped by system-specific ‘demand-side’ pressures.

•

Measurement styles shaped by ‘supply-side’ constraints on data access and indicator construction.

•

International benchmarking is easier when healthcare systems and governance traditions are similar.

Despite widespread faith that quality indicators are key to healthcare improvement and regulation, surprisingly little is known about what is actually measured in different countries, nor how, nor why. To address that gap, this article compares the official indicator sets--comprising some 1100 quality measures-- used by statutory hospital regulators in England, Germany, France, and the Netherlands. The findings demonstrate that those countries’ regulators strike very different balances in: the dimensions of quality they assess (e.g. between safety, effectiveness, and patient-centredness); the hospital activities they target (e.g. between clinical and non-clinical activities and management); and the ‘Donabedian’ measurement style of their indicators (between structure, process and outcome indicators). We argue that these contrasts reflect: i) how the distinctive problems facing each country’s healthcare system create different ‘demand-side’ pressures on what national indicator sets measure; and ii) how the configuration of national healthcare systems and governance traditions create ‘supply-side’ constraints on the kinds of data that regulators can use for indicator construction. Our analysis suggests fundamental differences in the meaning of quality and its measurement across countries that are likely to impede international efforts to benchmark quality and identify best practice.

Are hospital ratings systems transparent? An examination of Consumer Reports and the Leapfrog Hospital Safety Grade

The health care industry is complex, dynamic, and large. In such uncertain environments where a great deal of revenue is at stake, competition and comparative claims flourish. One such manifestation is hospital ratings systems. This research examines two influential hospital ratings to explore whether the hospital ratings of each system was straightforward and reproducible. Regressions and structural equations models were fit to examine the relationships among the hospital ratings constructs. Both hospital ratings systems were excellent in their transparency and reproducibility. The Consumer Reports and Leapfrog ratings systems can confidently tout that their hospital scores reflect what they claim to measure. The unique aspects of each system are also noted.

A Framework for Ranking Hospitals Based on Customer Perception Using Rough Set and Soft Set Techniques

Hospital ranking is a cumbersome task, as it involves dealing with a large volume of underlying data. Rankings are usually accomplished by comparing different dimensions of quality and services. Even the quality care measurement of a hospital is multi-dimensional: It includes the experience of both clinical care and patient care. In this research, however, the authors focus on ratings based only on customer perception. A framework which consists of two stages—Stage I and Stage II—is designed. In the first stage, the model uses a rough set in a fuzzy approximation space (RSFAS) technique to classify the data; whereas in the second stage, a fuzzy soft set (FSS) technique is employed to generate the rating score. The model is employed for comparing USA hospitals by region using annual HCAHPS survey data. This article shows how ranking of the healthcare institutions can be carried out using the RSFAS (rough set in a fuzzy approximation space) and fuzzy soft set techniques.

Evaluating Measures of Hospital Quality:Evidence from Ambulance Referral Patterns

Hospital quality measures are crucial to a key idea behind health care payment reforms: "paying for quality" instead of quantity. Nevertheless, such measures face major criticisms largely over the potential failure of risk adjustment to overcome endogeneity concerns when ranking hospitals. In this paper we test whether patients treated at hospitals that score higher on commonly-used quality measures have better health outcomes in terms of rehospitalization and mortality. To compare similar patients across hospitals in the same market, we exploit ambulance company preferences as an instrument for hospital choice. We find that a variety of measures used by insurers to measure provider quality are successful: choosing a high-quality hospital compared to a low-quality hospital results in 10-15% better outcomes.

Association of Rankings With Cardiovascular Outcomes at Top-Ranked Hospitals vs Nonranked Hospitals in the United States

Importance

The US News & World Report (USNWR) identifies the "Best Hospitals" for "Cardiology and Heart Surgery." These rankings may have significant influence on patients and hospitals.

Objective

To determine whether USNWR top-ranked hospitals perform better than nonranked hospitals on mortality rates and readmission measures as well as patient satisfaction.

Design, Setting, and Participants

This national retrospective study evaluated outcomes at 3552 US hospitals from 2014 to 2017.

Exposures

US News & World Report 2018 to 2019 Cardiology and Heart Surgery rankings (top-ranked vs nonranked hospitals).

Main Outcomes and Measures

Hospital-level 30-day risk-standardized mortality and readmission rates for Medicare fee-for-service beneficiaries age 65 years or older hospitalized for 3 cardiovascular conditions: acute myocardial infarction (AMI), heart failure (HF), and coronary artery bypass grafting (CABG) as well as Hospital Consumer Assessment of Healthcare Providers and Systems patient satisfaction star ratings obtained from publicly available Centers for Medicaid and Medicare Services data.

Results

Thirty-day mortality rates at top-ranked hospitals (n = 50), compared with nonranked hospitals (n = 3502), were lower for AMI (11.9% vs 13.2%, P < .001), HF (9.5% vs 11.9%; P < .001), and CABG (2.3%vs 3.3%; P < .001). Thirty-day readmission rates at the top-ranked hospitals (n = 50) when compared with nonranked hospitals (n = 2841) were similar for AMI (16.7% vs 16.5%; P = .64) and CABG (14.1% vs 13.7%; P = .15) but higher for HF (21.0% vs 19.2%; P < .001), Finally, patient satisfaction was higher at top-ranked hospitals (n = 50) compared with nonranked hospitals (n = 3412) (3.9 vs 3.3; P < .001).

Conclusions and Relevance

We found that USNWR top-ranked hospitals for cardiovascular care had lower 30-day mortality rates for AMI, HF, and CABG and higher patient satisfaction ratings compared with nonranked hospitals. However, 30-day readmission rates were either similar (for AMI and CABG) or higher (for HF) at top-ranked compared with nonranked hospitals. This discrepancy between readmissions and other performance measures raises concern that readmissions may not be an adequate metric of hospital care quality.

Statewide Longitudinal Progression of the Whole-Patient Measure of Safety in South Carolina

Meaningful improvement in patient safety encompasses a vast number of quality metrics, but a single measure to represent the overall level of safety is challenging to produce. Recently, Perla et al. established the Whole-Person Measure of Safety (WPMoS) to reflect the concept of global risk assessment at the patient level. We evaluated the WPMoS across an entire state to understand the impact of urban/rural setting, academic status, and hospital size on patient safety outcomes. The population included all South Carolina (SC) inpatient discharges from January 1, 2008, through to December 31, 2013, and was evaluated using established definitions of highly undesirable events (HUEs). Over the study period, the proportion of hospital discharges with at least one HUE significantly decreased from 9.7% to 8.8%, including significant reductions in nine of the 14 HUEs. Academic, large, and urban hospitals had a significantly lower proportion of hospital discharges with at least one HUE in 2008, but only urban hospitals remained significantly lower by 2013. Results indicate that there has been a decrease in harm events captured through administrative coded data over this 6-year period. A composite measure, such as the WPMoS, is necessary for hospitals to evaluate their progress toward reducing preventable harm.

Nurses' views on hospital organizational characteristics

BACKGROUND

Positive organizational characteristics are conducive to healthy work environments. Hospitals with positive organizational characteristics and healthy work environments attract nurses. In turn, positive organizational characteristics and healthy work environments in hospitals will result in positive nurse, patient, and organizational outcomes.

AIM

The aim of this study was to assess hospital organizational characteristics from the viewpoint of registered nurses (RNs) in the country of Jordan.

METHODS

The researcher used a survey method to conduct the study; the Revised Nursing Work Index (NWI-R) was used to collect data, utilizing a convenience sample of 308 RNs with a total response rate of 75%.

FINDINGS

The strongest positive hospital organizational characteristic was the presence of adequate support services which allow nurses to spend time with their patients. The strongest negative hospital organizational characteristics were the nursing delivery systems-particularly in primary nursing where they result in nurses having to do things that are against their nursing judgment-and the limited opportunities and freedom over many aspects of nursing care and unit/ward decisions.

CONCLUSIONS

Positive hospital organizational characteristics should be maintained because these produce positive nurse, patient, and organizational outcomes. Fostering a positive hospital organizational environment is a continuous effort. The results have implications for practice, research, and education.

Motivating provision of high quality care: it is not all about the money

Mylène Lagarde, Luis Huicho, and Irene Papanicolas discuss different strategies policy makers can use to motivate health providers in order to improve quality of care

Patient safety regulation in the NHS: mapping the regulatory landscape of healthcare

OBJECTIVES

The current research project sought to map out the regulatory landscape for patient safety in the English National Health Service (NHS).

METHOD

We used a systematic desk-based search using a variety of sources to identify the total number of organisations with regulatory influence in the NHS; we researched publicly available documents listing external inspection agencies, participated in advisory consultations with NHS regulatory compliance teams and reviewed the websites of all regulatory agencies.

RESULTS

Our mapping revealed over 126 organisations who exert some regulatory influence on NHS provider organisations in addition to 211 Clinical Commissioning Groups. The majority of these organisations set standards and collect data from provider organisations and a considerable number carry out investigations. We found a multitude of overlapping functions and activities. The variability in approach and overlapping functions suggest that there is no overall integrated regulatory approach.

CONCLUSION

Regulation potentially provides a variety of benefits in terms of maintaining the safety and quality of care by providing an external perspective on the care being delivered. However, the variability, extent and fragmentation of the regulatory system of the NHS make it hard for regulators to act effectively and places a massive burden on NHS provider organisations. Overlapping regulatory requests may distract locally driven initiatives to improve safety and quality. Further research is needed to understand the full extent of regulatory activity and the true benefits and costs incurred.

Disagreement Between Hospital Rating Systems: Measuring the Correlation of Multiple Benchmarks and Developing a Quality Composite Rank

In the United States, hospital rating system usefulness is limited by heterogeneity and conflicting results. US News Best Hospitals, Vizient Quality and Accountability Study, Centers for Medicare & Medicaid Services (CMS) Star Rating, Leapfrog Hospital Safety Grade, and the Truven Top 100 Hospitals ratings were compared using Spearman correlations. Rank aggregation was used to combine the scores generating a Quality Composite Rank (QCR). The highest correlation between rating systems was shown between the Leapfrog Safety Grade and the CMS Star Rating. In a proportional odds logistic regression, a greater discordance between the CMS Star Rating, Vizient rank, US News, and Leapfrog was associated with a lower overall rank in the QCR. Lack of transparency and understanding about the differences and similarities for these hospital ranking systems complicates use of the measures. By combining the results of these ranking systems into a composite, the measurement of hospital quality can be simplified.