Between-hospital variation in indicators of quality of care: a systematic review

Background: Efforts to mitigate unwarranted variation in the quality of care require insight into the 'level' (eg, patient, physician, ward, hospital) at which observed variation exists. This systematic literature review aims to synthesise the results of studies that quantify the extent to which hospitals contribute to variation in quality indicator scores. Methods: Embase, Medline, Web of Science, Cochrane and Google Scholar were systematically searched from 2010 to November 2023. We included studies that reported a measure of between-hospital variation in quality indicator scores relative to total variation, typically expressed as a variance partition coefficient (VPC). The results were analysed by disease category and quality indicator type. Results: In total, 8373 studies were reviewed, of which 44 met the inclusion criteria. Casemix adjusted variation was studied for multiple disease categories using 144 indicators, divided over 5 types: intermediate clinical outcomes (n=81), final clinical outcomes (n=35), processes (n=10), patient-reported experiences (n=15) and patient-reported outcomes (n=3). In addition to an analysis of between-hospital variation, eight studies also reported physician-level variation (n=54 estimates). In general, variation that could be attributed to hospitals was limited (median VPC=3%, IQR=1%-9%). Between-hospital variation was highest for process indicators (17.4%, 10.8%-33.5%) and lowest for final clinical outcomes (1.4%, 0.6%-4.2%) and patient-reported outcomes (1.0%, 0.9%-1.5%). No clear pattern could be identified in the degree of between-hospital variation by disease category. Furthermore, the studies exhibited limited attention to the reliability of observed differences in indicator scores. Conclusion: Hospital-level variation in quality indicator scores is generally small relative to residual variation. However, meaningful variation between hospitals does exist for multiple indicators, especially for care processes which can be directly influenced by hospital policy. Quality improvement strategies are likely to generate more impact if preceded by level-specific and indicator-specific analyses of variation, and when absolute variation is also considered. PROSPERO registration number: CRD42022315850.</p

Factors Influencing the Introduction of Value-Based Payment in Integrated Stroke Care: 'Evidence from a Qualitative Case Study'

Background: To address issues related to suboptimal insight in outcomes, fragmentation, and increasing costs, stakeholders are experimenting with value-based payment (VBP) models, aiming to facilitate high-value integrated care. However, insight in how, why and under what circumstances such models can be successful is limited. Drawing upon realist evaluation principles, this study identifies context factors and associated mechanisms influencing the introduction of VBP in stroke care. Methods: Existing knowledge on context-mechanism relations impacting the introduction of VBP programs (in real-world settings) was summarized from literature. These relations were then tested, refined, and expanded based on a case study comprising interviews with representatives from organizations involved in the introduction of a VBP model for integrated stroke care in Rotterdam, the Netherlands. Results: Facilitating factors were pre-existing trust-based relations, shared dissatisfaction with the status quo, regulatory compatibility and simplicity of the payment contract, gradual introduction of down-side risk for providers, and involvement of a trusted third party for data management. Yet to be addressed barriers included friction between short- and long-term goals within and among organizations, unwillingness to forgo professional and organizational autonomy, discontinuity in resources, and limited access to real-time data for improving care delivery processes. Conclusions: Successful payment and delivery system reform require long-term commitment from all stakeholders stretching beyond the mere introduction of new models. Careful consideration of creating the ‘right’ contextual circumstances remains crucially important, which includes willingness among all involved providers to bear shared financial and clinical responsibility for the entire care chain, regardless of where care is provided

Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial.

Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707

Between-Hospital and Between-Physician Variation in Outcomes and Costs in High- and Low-Complex Surgery: A Nationwide Multilevel Analysis

OBJECTIVES: Clinicians and policy makers are increasingly exploring strategies to reduce unwarranted variation in outcomes and costs. Adequately accounting for case mix and better insight into the levels at which variation exists is crucial for such strategies. This nationwide study investigates variation in surgical outcomes and costs at the level of hospitals and individual physicians and evaluates whether these can be reliably compared on performance. METHODS: Variation was analyzed using 92 330 patient records collected from 62 Dutch hospitals who underwent surgery for colorectal cancer (n = 6640), urinary bladder cancer (n = 14 030), myocardial infarction (n = 31 870), or knee osteoarthritis (n = 39 790) in the period 2018 to 2019. Multilevel regression modeling with and without case-mix adjustment was used to partition variation in between-hospital and between-physician components for in-hospital mortality, intensive care unit admission, length of stay, 30-day readmission, 30-day reintervention, and in-hospital costs. Reliability was calculated for each treatment-outcome combination at both levels. RESULTS: Across outcomes, hospital-level variation relative to total variation ranged between ≤ 1% and 15%, and given the high caseloads, this typically yielded high reliability (> 0.9). In contrast, physician-level variation components were typically ≤ 1%, with limited opportunities to make reliable comparisons. The impact of case-mix adjustment was limited, but nonnegligible. CONCLUSIONS: It is not typically possible to make reliable comparisons among physicians due to limited partitioned variation and low caseloads. Nevertheless, for hospitals, the opposite often holds. Although variation-reduction efforts directed at hospitals are thus more likely to be successful, this should be approached cautiously, partly because level-specific variation and the impact of case mix vary considerably across treatments and outcomes

Between-hospital variation in indicators of quality of care: a systematic review

Background: Efforts to mitigate unwarranted variation in the quality of care require insight into the 'level' (eg, patient, physician, ward, hospital) at which observed variation exists. This systematic literature review aims to synthesise the results of studies that quantify the extent to which hospitals contribute to variation in quality indicator scores. Methods: Embase, Medline, Web of Science, Cochrane and Google Scholar were systematically searched from 2010 to November 2023. We included studies that reported a measure of between-hospital variation in quality indicator scores relative to total variation, typically expressed as a variance partition coefficient (VPC). The results were analysed by disease category and quality indicator type. Results: In total, 8373 studies were reviewed, of which 44 met the inclusion criteria. Casemix adjusted variation was studied for multiple disease categories using 144 indicators, divided over 5 types: intermediate clinical outcomes (n=81), final clinical outcomes (n=35), processes (n=10), patient-reported experiences (n=15) and patient-reported outcomes (n=3). In addition to an analysis of between-hospital variation, eight studies also reported physician-level variation (n=54 estimates). In general, variation that could be attributed to hospitals was limited (median VPC=3%, IQR=1%-9%). Between-hospital variation was highest for process indicators (17.4%, 10.8%-33.5%) and lowest for final clinical outcomes (1.4%, 0.6%-4.2%) and patient-reported outcomes (1.0%, 0.9%-1.5%). No clear pattern could be identified in the degree of between-hospital variation by disease category. Furthermore, the studies exhibited limited attention to the reliability of observed differences in indicator scores. Conclusion: Hospital-level variation in quality indicator scores is generally small relative to residual variation. However, meaningful variation between hospitals does exist for multiple indicators, especially for care processes which can be directly influenced by hospital policy. Quality improvement strategies are likely to generate more impact if preceded by level-specific and indicator-specific analyses of variation, and when absolute variation is also considered. PROSPERO registration number: CRD42022315850.</p

Poliovirus-Neutralizing Antibody Seroprevalence and Vaccine Habits in a Vaccine-Derived Poliovirus Outbreak Region in the Democratic Republic of Congo in 2018: The Impact on the Global Eradication Initiative.

Despite the successes in wild-type polio eradication, poor vaccine coverage in the DRC has led to the occurrence of circulating vaccine-derived poliovirus outbreaks. This cross-sectional population-based survey provides an update to previous poliovirus-neutralizing antibody seroprevalence studies in the DRC and quantifies risk factors for under-immunization and parental knowledge that guide vaccine decision making. Among the 964 children between 6 and 35 months in our survey, 43.8% (95% CI: 40.6-47.0%), 41.1% (38.0-44.2%), and 38.0% (34.9-41.0%) had protective neutralizing titers to polio types 1, 2, and 3, respectively. We found that 60.7% of parents reported knowing about polio, yet 25.6% reported knowing how it spreads. Our data supported the conclusion that polio outreach efforts were successfully connecting with communities-79.4% of participants had someone come to their home with information about polio, and 88.5% had heard of a polio vaccination campaign. Additionally, the odds of seroreactivity to only serotype 2 were far greater in health zones that had a history of supplementary immunization activities (SIAs) compared to health zones that did not. While SIAs may be reaching under-vaccinated communities as a whole, these results are a continuation of the downward trend of seroprevalence rates in this region