Hospital quality variation matters - A time-trend and cross-section analysis of outcomes in German hospitals from 2006 to 2014

The elicitation of patient and physician preferences for calculating consumer-based composite measures on hospital report cards: results of two discrete choice experiments

PURPOSE

The calculation of aggregated composite measures is a widely used strategy to reduce the amount of data on hospital report cards. Therefore, this study aims to elicit and compare preferences of both patients as well as referring physicians regarding publicly available hospital quality information METHODS: Based on systematic literature reviews as well as qualitative analysis, two discrete choice experiments (DCEs) were applied to elicit patients' and referring physicians' preferences. The DCEs were conducted using a fractional factorial design. Statistical data analysis was performed using multinomial logit models RESULTS: Apart from five identical attributes, one specific attribute was identified for each study group, respectively. Overall, 322 patients (mean age 68.99) and 187 referring physicians (mean age 53.60) were included. Our models displayed significant coefficients for all attributes (p < 0.001 each). Among patients, "Postoperative complication rate" (20.6%; level range of 1.164) was rated highest, followed by "Mobility at hospital discharge" (19.9%; level range of 1.127), and ''The number of cases treated" (18.5%; level range of 1.045). In contrast, referring physicians valued most the ''One-year revision surgery rate'' (30.4%; level range of 1.989), followed by "The number of cases treated" (21.0%; level range of 1.372), and "Postoperative complication rate" (17.2%; level range of 1.123) CONCLUSION: We determined considerable differences between both study groups when calculating the relative value of publicly available hospital quality information. This may have an impact when calculating aggregated composite measures based on consumer-based weighting.

Impact of the Italian Healthcare Outcomes Program (PNE) on the Care Quality of the Poorest Performing Hospitals

One of the main aims of the Italian National Healthcare Outcomes Program (Programma Nazionale Esiti, PNE) is the identification of the hospitals with the lowest performance, leading them to improve their quality. In order to evaluate PNE impact for a subset of outcome indicators, we evaluated whether the performance of the hospitals with the lowest scores in 2016 had significantly improved after five years. The eight indicators measured the risk-adjusted likelihood of the death of each patient (adjusted relative risk-RR) 30 days after the admission for acute myocardial infarction, congestive heart failure, stroke, chronic obstructive pulmonary disease, chronic kidney disease, femur fracture or lung and colon cancer. In 2016, the PNE identified 288 hospitals with a very low performance in at least one of the selected indicators. Overall, 51.0% (n = 147) of these hospitals showed some degree of improvement in 2021, and 27.4% of them improved so much that the death risk of their patients fell below the national mean value. In 34.7% of the hospitals, however, the patients still carried a mean risk of death >30% higher than the average Italian patient with the same disease. Only 38.5% of the hospitals in Southern Italy improved the scores of the selected indicators, versus 68.0% in Northern and Central Italy. Multivariate analyses, adjusting for the baseline performance in 2016, confirmed univariate results and showed a significantly lower likelihood of improvement with increasing hospital volume. Despite the overall methodological validity of the PNE system, current Italian policies and actions aimed at translating hospital quality scores into effective organizational changes need to be reinforced with a special focus on larger southern regions.

Stability of hospital quality indicators over time: A multi-year observational study of German hospital data

BACKGROUND

Retrospective hospital quality indicators can only be useful if they are trustworthy signals of current or future quality. Despite extensive longitudinal quality indicator data and many hospital quality public reporting initiatives, research on quality indicator stability over time is scarce and skepticism about their usefulness widespread.

OBJECTIVE

Based on aggregated, widely available hospital-level quality indicators, this paper sought to determine whether quality indicators are stable over time. Implications for health policy were drawn and the limited methodological foundation for stability assessments of hospital-level quality indicators enhanced.

METHODS

Two longitudinal datasets (self-reported and routine data), including all hospitals in Germany and covering the period from 2004 to 2017, were analysed. A logistic regression using Generalized Estimating Equations, a time-dependent, graphic quintile representation of risk-adjusted rates and Spearman's rank correlation coefficient were used.

RESULTS

For a total of eight German quality indicators significant stability over time was demonstrated. The probability of remaining in the best quality cluster in the future across all hospitals reached from 46.9% (CI: 42.4-51.6%) for hip replacement reoperations to 80.4% (CI: 76.4-83.8%) for decubitus. Furthermore, graphical descriptive analysis showed that the difference in adverse event rates for the 20% top performing compared to the 20% worst performing hospitals in the two following years is on average between 30% for stroke and AMI and 79% for decubitus. Stability over time has been shown to vary strongly between indicators and treatment areas.

CONCLUSION

Quality indicators were found to have sufficient stability over time for public reporting. Potentially, increasing case volumes per hospital, centralisation of medical services and minimum-quantity regulations may lead to more stable and reliable quality of care indicators. Finally, more robust policy interventions such as outcome-based payment, should only be applied to outcome indicators with a higher level of stability over time. This should be subject to future research.

Organizational attributes that contribute to the learning & improvement capabilities of healthcare organizations: a scoping review

BACKGROUND

This study aims to explore and identify the organizational attributes that contribute to learning and improvement capabilities (L&IC) in healthcare organizations. The authors define learning as a structured update of system properties based on new information, and improvement as a closer correspondence between actual and desired standards. They highlight the importance of learning and improvement capabilities in maintaining high-quality care, and emphasize the need for empirical research on organizational attributes that contribute to these capabilities. The study has implications for healthcare organizations, professionals, and regulators in understanding how to assess and enhance learning and improvement capabilities.

METHODS

A systematic search of peer-reviewed articles published between January 2010 and April 2020 was carried out in the PubMed, Embase, CINAHL, and APA PsycINFO databases. Two reviewers independently screened the titles and abstracts and conducted a full-text review of potentially relevant articles, eventually adding five more studies identified through reference scanning. Finally, a total of 32 articles were included in this review. We extracted the data about organizational attributes that contribute to learning and improvement, categorized them and grouped the findings step-by-step into higher, more general-level categories using an interpretive approach until categories emerged that were sufficiently different from each other while also being internally consistent. This synthesis has been discussed by the authors.

RESULTS

We identified five attributes that contribute to the L&IC of healthcare organizations: perceived leadership commitment, open culture, room for team development, initiating and monitoring change, and strategic client focus, each consisting of multiple facilitating aspects. We also found some hindering aspects.

CONCLUSIONS

We have identified five attributes that contribute to L&IC, mainly related to organizational software elements. Only a few are identified as organizational hardware elements. The use of qualitative methods seems most appropriate to understand or assess these organizational attributes. We feel it is also important for healthcare organisations to look more closely at how clients can be involved in L&IC.

TRIAL REGISTRATION

Not applicable.

Can competition improve hospital quality of care? A difference-in-differences approach to evaluate the effect of increasing quality transparency on hospital quality

Public reporting on the quality of care is intended to guide patients to the provider with the highest quality and to stimulate a fair competition on quality. We apply a difference-in-differences design to test whether hospital quality has improved more in markets that are more competitive after the first public release of performance data in Germany in 2008. Panel data from 947 hospitals from 2006 to 2010 are used. Due to the high complexity of the treatment of stroke patients, we approximate general hospital quality by the 30-day risk-adjusted mortality rate for stroke treatment. Market structure is measured (comparatively) by the Herfindahl-Hirschman index (HHI) and by the number of hospitals in the relevant market. Predicted market shares based on exogenous variables only are used to compute the HHI to allow a causal interpretation of the reform effect. A homogenous positive effect of competition on quality of care is found. This effect is mainly driven by the response of non-profit hospitals that have a narrow range of services and private for-profit hospitals with a medium range of services. The results highlight the relevance of outcome transparency to enhance hospital quality competition.

Defining minimum volume thresholds to increase quality of care: a new patient-oriented approach using mixed integer programming

A positive relationship between treatment volume and outcome quality has been demonstrated in the literature and is thus evident for a variety of procedures. Consequently, policy makers have tried to translate this so-called volume-outcome relationship into minimum volume regulation (MVR) to increase the quality of care-yet with limited success. Until today, the effect of strict MVR application remains unclear as outcome quality gains cannot be estimated adequately and restrictions to application such as patient travel time and utilization of remaining hospital capacity are not considered sufficiently. Accordingly, when defining MVR, its effectiveness cannot be assessed. Thus, we developed a mixed integer programming model to define minimum volume thresholds balancing utility in terms of outcome quality gain and feasibility in terms of restricted patient travel time and utilization of hospital capacity. We applied our model to the German hospital sector and to four surgical procedures. Results showed that effective MVR needs a minimum volume threshold of 125 treatments for cholecystectomy, of 45 and 25 treatments for colon and rectum resection, respectively, of 32 treatments for radical prostatectomy and of 60 treatments for total knee arthroplasty. Depending on procedure type and incidence as well as the procedure's complication rate, outcome quality gain ranged between 287 (radical prostatectomy) and 977 (colon resection) avoidable complications (11.7% and 11.9% of all complications). Ultimately, policy makers can use our model to leverage MVR's intended benefit: concentrating treatment delivery to improve the quality of care.

International comparison of variation in performance between hospitals for THA and TKA: Is it even possible? A systematic review including 33 studies and 8 arthroplasty register reports

In order to improve care for total hip and knee arthroplasties (THA/TKA), hospitals may want to compare their performance with hospitals in other countries. Pooling data across countries also enable early detection of infrequently occurring safety issues. We therefore aimed to assess the between-hospital variation and definitions used for revision, readmission, and complications across countries.

PubMed, Embase, Web of Science, Cochrane library, Emcare, and Academic Search Premier were searched from January 2009 to August 2020 for studies reporting on: (i) primary THA/TKA; (ii) revision, readmission, or complications; and (iii) between-hospital variation. Most recent registry reports of Network of Orthopedic Registries of Europe members were also reviewed. Two reviewers independently screened records, extracted data, and assessed the risk of bias using the Integrated quality Criteria for the Review Of Multiple Study designs tool for studies and relevant domains for registries. We assessed agreement for the following domains: (i) outcome definition; (ii) follow-up and starting point; (iii) case-mix adjustment; and (iv) type of patients and hospitals included.

Between-hospital variation was reported in 33 (1 high-quality, 13 moderate-quality, and 19 low-quality) studies and 8 registry reports. The range of variation for revision was 0–33% for THA and 0–27% for TKA varying between assessment within hospital admission until 10 years of follow-up; for readmission, 0–40% and 0–32% for THA and TKA, respectively; and for complications, 0–75% and 0–50% for THA and TKA, respectively. Indicator definitions and methodological variables varied considerably across domains.

The large heterogeneity in definitions and methods used likely explains the considerable variation in between-hospital variation reported for revision, readmission, and complications , making it impossible to benchmark hospitals across countries or pool data for earlier detection of safety issues. It is necessary to collaborate internationally and strive for more uniformity in indicator definitions and methods in order to achieve reliable international benchmarking in the future.

Can we trust the standardized mortality ratio? A formal analysis and evaluation based on axiomatic requirements

BACKGROUND

The standardized mortality ratio (SMR) is often used to assess and compare hospital performance. While it has been recognized that hospitals may differ in their SMRs due to differences in patient composition, there is a lack of rigorous analysis of this and other-largely unrecognized-properties of the SMR.

METHODS

This paper proposes five axiomatic requirements for adequate standardized mortality measures: strict monotonicity (monotone relation to actual mortality rates), case-mix insensitivity (independence of patient composition), scale insensitivity (independence of hospital size), equivalence principle (equal rating of hospitals with equal actual mortality rates in all patient groups), and dominance principle (better rating of unambiguously better performing hospitals). Given these axiomatic requirements, effects of variations in patient composition, hospital size, and actual and expected mortality rates on the SMR were examined using basic algebra and calculus. In this regard, we distinguished between standardization using expected mortality rates derived from a different dataset (external standardization) and standardization based on a dataset including the considered hospitals (internal standardization). The results were illustrated by hypothetical examples.

RESULTS

Under external standardization, the SMR fulfills the axiomatic requirements of strict monotonicity and scale insensitivity but violates the requirement of case-mix insensitivity, the equivalence principle, and the dominance principle. All axiomatic requirements not fulfilled under external standardization are also not fulfilled under internal standardization. In addition, the SMR under internal standardization is scale sensitive and violates the axiomatic requirement of strict monotonicity.

CONCLUSIONS

The SMR fulfills only two (none) out of the five proposed axiomatic requirements under external (internal) standardization. Generally, the SMRs of hospitals are differently affected by variations in case mix and actual and expected mortality rates unless the hospitals are identical in these characteristics. These properties hamper valid assessment and comparison of hospital performance based on the SMR.

The impact of quality on hospital choice. Which information affects patients' behavior for colorectal resection or knee replacement?

Quality competition among hospitals, induced by patients freely choosing their hospital in a price regulated market, can only be realized if quality differences between hospitals are transparent, understandable, and thus influence patients' hospital choice. We use data from ~145,000 German patients and ~ 900 hospitals for colorectal resections and knee replacements to investigate whether patients value quality and specialization when choosing their hospital. Using a random utility choice model, we estimate patients' marginal utilities, willingness to travel and change in hospital demand for quality improvements. Patients respond to service quality and specialization and thus, quality competition seems to be present. Colorectal resection patients are willing to travel longer for more specialized hospitals (+9% for procedure volume, +9% for certification). Knee replacement patients travel longer for hospitals with better service quality (+6%) and higher procedure volume (+12%). However, clinical quality indicators, often difficult to access and interpret, barely play a role in patients' hospital choice. Furthermore, we find that competition on quality for colorectal resection is rather local, whereas for knee replacement we observe regional competition patterns.

Impact of suspending minimum volume requirements for knee arthroplasty on hospitals in Germany: an uncontrolled before-after study

Background

In 2004, the Federal Joint Committee, supreme decision-making body in German healthcare, introduced minimum volume requirements (MVRQs) as a quality instrument. Since then, MVRQs were implemented for seven hospital procedures. This study evaluates the effect of a system-wide intermission of MVRQ for total knee arthroplasty (TKA), demanding 50 annual cases per hospital.

Methods

An uncontrolled before–after study based on federal-level data including the number of hospitals performing TKA, and TKA cases from the external hospital quality assurance programme in Germany (2004–2017). Bi- and multivariate analyses based on hospital-level secondary data of TKA cases and TKA quality indicators extracted from hospital quality reports in Germany (2006–2014).

Results

The number of TKAs performed in Germany decreased by 11% after suspending the TKA-MVRQ in 2011, and rose by 13% after its reintroduction in 2015. The number of hospitals with less than 50 cases rose from 10 to 25% and their case share from 2 to 5.5% during suspension. Change in hospital volume after the suspension of TKA-MVRQ was not associated with hospital size, ownership, or region. All four evaluable quality indicators increased significantly in the year after their first public reporting. Compared to hospitals meeting the TKA-MVRQ, three indicators show slight but statistically significant better quality in hospitals below the TKA-MVRQ.

Conclusions

In Germany, TKA-MVRQs seem to induce in-hospital caseload adjustments rather than foster regional inter-hospital case transfers as intended.

Understanding the large heterogeneity in hospital readmissions and mortality for acute myocardial infarction

This study aims to investigate the variation in two acute myocardial infarction (AMI) outcomes across public hospitals in Portugal. In-hospital mortality and 30-day unplanned readmissions were studied using two distinct AMI cohorts of adults discharged from all acute care public hospital centers in Portugal from 2012-2015. Hierarchical generalized linear models were used to assess the association between patient and hospital characteristics and hospital variability in the two outcomes. Our findings indicate that hospitals are not performing homogeneously-the risk of adverse events tends to be consistently larger in some hospitals and consistently lower in other hospitals. While patient characteristics accounted for a larger share of the explained between-hospital variance, hospital characteristics explain an additional 8% and 10% of hospital heterogeneity in the mortality and the readmission cohorts respectively. Admissions to hospitals with low AMI caseloads or located in Alentejo/Algarve and Lisbon had a higher risk of mortality. Discharges from larger-sized hospitals were associated with increased risk of readmissions. Future health policies should incorporate these findings in order to incentivize more consistent health care outcomes across hospitals. Further investigation addressing geographical disparities, hospital caseload and practices is needed to direct actions of improvement to specific hospitals.

Measures of hospital competition and their impact on early mortality for congestive heart failure, acute myocardial infarction and cardiac surgery

OBJECTIVE

To measure competition amongst providers and to examine whether a correlation exists with hospitals mortality for congestive heart failure (CHF), acute myocardial infarction (AMI), isolated-coronary artery bypass graft (CABG) or valve surgery.

DESIGN

Cross-sectional study based on publically available data from the National Outcome Evaluation Program (Edition 2016) of the Italian Agency for Regional Health Services.

SETTING AND PARTICIPANTS

Patients discharged during 2015 for CHF or AMI, and between 2014 and 2015 for cardiac surgery (respectively, from 662, 395 and 91 hospitals).

MAIN OUTCOME MEASURES

Risk-adjusted mortality rates at 30 days and measures of hospital competition for areas centred on hospital' location (fixed-radius 50-150 km, variable-radius to capture 10-30 hospitals and 6-10% of national volume). Competition was estimated as number of providers and Herfindahl-Hirschman Index (HHI).

RESULTS

Indicators of competitions varied by condition and were sensitive to method used for the area definition. Hospital mortality after AMI and valve surgery increased with competition in areas identified by the variable-radius method (higher rates for a greater number of hospitals or lower HHIs). In area with fixed radius of 100-150 km, competition reduced mortality after CABG procedures (lower rates for a greater number of hospitals or smaller HHIs). Neither the number of hospitals nor HHI correlated with outcomes in CHF.

CONCLUSIONS

The measures of hospital competition changed according to definition of local market and results in mortality correlations varied among conditions. Understanding the relationship between hospital competition and outcomes is important to identify strategies to improve quality of care.

Versorgungsstrukturen und Mengen-Ergebnis-Beziehung beim akuten Herzinfarkt – Verlaufsbetrachtung der deutschlandweiten Krankenhausabrechnungsdaten von 2005 bis 2015

Hintergrund Studien haben beschrieben, dass höhere Herzinfarktfallzahlen des behandelnden Krankenhauses mit besseren Behandlungsergebnissen assoziiert sind. Vor diesem Hintergrund wird die Entwicklung der akutstationären Herzinfarktversorgung sowie der Mengen-Ergebnisbeziehung im Zeitverlauf analysiert. Ziel der Arbeit ist, die Entwicklungen zu bewerten und Anhaltspunkte für eine Verbesserung der Herzinfarktversorgung in Deutschland abzuleiten.

Methode Anhand der deutschlandweiten Krankenhausabrechnungsdaten (DRG-Statistik) von 2005 bis 2015 wurden Patienten mit akutem Herzinfarkt im erstbehandelnden Krankenhaus identifiziert und anhand der jährlichen Herzinfarktfallzahl des behandelnden Krankenhauses in fallzahlgleiche Quintile eingeteilt.

Ergebnisse Im Beobachtungszeitraum zeigte sich ein zunehmender Anteil interventionell versorgter Herzinfarktpatienten. Die Krankenhaussterblichkeit im erstbehandelnden Krankenhaus ging insgesamt von 12,1 auf 8,7% zurück. In allen Jahren wurde in den höheren Fallzahlquintilen eine geringere Sterblichkeit im Vergleich zum unteren Fallzahlquintil beobachtet. Im Jahr 2015 zeigte sich im Vergleich zur Behandlung in Krankenhäusern mit sehr geringer Fallzahl ein um 20% reduziertes Sterberisiko (adjustiertes OR jeweils 0,8 [95% KI 0,7–0,9]) in Krankenhäusern mit mittlerer, hoher oder sehr hoher Fallzahl. Mehr als 40% der Krankenhäuser mit sehr geringer Fallzahl waren in städtischen Regionen lokalisiert.

Schlussfolgerung Eine gezieltere Steuerung von Patienten mit Herzinfarktsymptomen in Krankenhäuser mit hohen Herzinfarktfallzahlen könnte die Versorgung weiter verbessern. Eine solche Versorgungssteuerung ist sowohl aus Gründen der medizinischen Qualität als auch der Wirtschaftlichkeit insbesondere in städtischen Regionen erforderlich.

Quality and resource efficiency in hospital service provision: A geoadditive stochastic frontier analysis of stroke quality of care in Germany

We specify a Bayesian, geoadditive Stochastic Frontier Analysis (SFA) model to assess hospital performance along the dimensions of resources and quality of stroke care in German hospitals. With 1,100 annual observations and data from 2006 to 2013 and risk-adjusted patient volume as output, we introduce a production function that captures quality, resource inputs, hospital inefficiency determinants and spatial patterns of inefficiencies. With high relevance for hospital management and health system regulators, we identify performance improvement mechanisms by considering marginal effects for the average hospital. Specialization and certification can substantially reduce mortality. Regional and hospital-level concentration can improve quality and resource efficiency. Finally, our results demonstrate a trade-off between quality improvement and resource reduction and substantial regional variation in efficiency.

Reframing the Biological Basis of Neuroprotection Using Functional Genomics: Differentially Weighted, Time-Dependent Multifactor Pathogenesis of Human Ischemic Brain Damage

Background: Neuroprotection studies are generally unable to demonstrate efficacy in humans. Our specific hypothesis is that multiple pathophysiologic pathways, of variable importance, contribute to ischemic brain damage. As a corollary to this, we discuss the broad hypothesis that a multifaceted approach will improve the probability of efficacious neuroprotection. But to properly test this hypothesis the nature and importance of the multiple contributing pathways needs elucidation. Our aim is to demonstrate, using functional genomics, in human cardiac surgery procedures associated with cerebral ischemia, that the pathogenesis of perioperative human ischemic brain damage involves the function of multiple variably weighted proteins involving several pathways. We then use these data and literature to develop a proposal for rational design of human neuroprotection protocols.

Methods: Ninety-four patients undergoing deep hypothermic circulatory arrest (DHCA) and/or aortic valve replacement surgery had brain damage biomarkers, S100β and neurofilament H (NFH), assessed at baseline, 1 and 24 h post-cardiopulmonary bypass (CPB) with analysis for association with 92 single nucleotide polymorphisms (SNPs) (selected by co-author WAK) related to important proteins involved in pathogenesis of cerebral ischemia.

Results: At the nominal significance level of 0.05, changes in S100β and in NFH at 1 and 24 h post-CPB were associated with multiple SNPs involving several prospectively determined pathophysiologic pathways, but were not individually significant after multiple comparison adjustments. Variable weights for the several evaluated SNPs are apparent on regression analysis and, notably, are dissimilar related to the two biomarkers and over time post CPB. Based on our step-wise regression model, at 1 h post-CPB, SOD2, SUMO4, and GP6 are related to relative change of NFH while TNF, CAPN10, NPPB, and SERPINE1 are related to the relative change of S100B. At 24 h post-CPB, ADRA2A, SELE, and BAX are related to the relative change of NFH while SLC4A7, HSPA1B, and FGA are related to S100B.

Conclusions: In support of the proposed hypothesis, association SNP data suggest function of specific disparate proteins, as reflected by genetic variation, may be more important than others with variation at different post-insult times after human brain ischemia. Such information may support rational design of post-insult time-sensitive multifaceted neuroprotective therapies.