The role of the clinical departments for understanding patient heterogeneity in one-year mortality after a diagnosis of heart failure: A multilevel analysis of individual heterogeneity for profiling provider outcomes

Abstract

PurposeTo evaluate the general contextual effect (GCE) of the hospital department on one-year mortality in Swedish and Danish patients with heart failure (HF) by applying a multilevel analysis of individual heterogeneity.MethodsUsing the Swedish patient register, we obtained data on 36,943 patients who were 45–80 years old and admitted for HF to the hospital between 2007 and 2009. From the Danish Heart Failure Database (DHFD), we obtained data on 12,001 patients with incident HF who were 18 years or older and treated at hospitals between June 2010 and June2013. For each year, we applied two-step single and multilevel logistic regression models. We evaluated the general effects of the department by quantifying the intra-class correlation coefficient (ICC) and the increment in the area under the receiver operating characteristic curve (AUC) obtained by adding the random effects of the department in a multilevel logistic regression analysis.ResultsOne-year mortality for Danish incident HF patients was low in the three audit years (around 11.1% -13.1%) and departments performed homogeneously (ICC ≈1.5% - 3.5%). The discriminatory accuracy of a model including age and gender was rather high (AUC≈ 0.71–0.73) but the increment in AUC after adding the department random effects into these models was only about 0.011–0.022 units in the three years.One-year mortality in Swedish patients with first hospitalization for heart failure, was relatively higher for 2007–2009 (≈21.3% - 22%) and departments performed homogeneously (ICC ≈ 1.5% - 3%). The discriminatory accuracy of a model including age, gender and patient risk score was rather high (AUC≈ 0.726–0.728) but the increment in AUC after adding the department random effects was only about 0.010–0.017 units in the three years.ConclusionUsing the DHFD standard benchmark for one-year mortality, Danish departments had a good, homogeneous performance. In reference to literature, Swedish departments had a homogeneous performance and the mortality rates for patients with first hospitalization for heart failure were similar to those reported since 2000. Considering this, if health authorities decide to further reduce mortality rates, a comprehensive quality strategy should focus on all Swedish hospitals. Yet, a complementary assessment for the period after the study period is required to confirm whether department performance is still homogeneous or not to determine the most appropriate action.

Disentangling the contribution of hospitals and municipalities for understanding patient level differences in one-year mortality risk after hip-fracture: A cross-classified multilevel analysis in Sweden

“…The AUC provides analogous information as the VPC [24] as both measures inform on the general contextual effect of the hospital and of the municipality levels in relation to the patients' oneyear mortality. As it has been explained elsewhere [12,13,18,[36][37][38][39][40][41] the general contextual effect, expresses the relevance of the hospital/municipality context for understanding patients' differences in one-year mortality.…”

Albuminuria measurement in diabetic care: a multilevel analysis measuring the influence of accreditation on institutional performance

“…Nevertheless, processes of care, such as the measurement of albuminuria, are under hospital control and hence are assumed to be sensitive to quality improvement interventions that target the hospital system in a given country 49–53. Based on the literature,22 25 41 54 55 it is reasonable to believe that the trend of increased compliance rates parallel to the implementation of the national accreditation (the Danish quality model) might actually reflect a behavioural change in diabetes care (ordering tests for albuminuria) by healthcare professionals.…”

“…In essence, the ultimate goal for performance monitoring and accreditation schemes is to encourage and guide providers to comply with evidence-based processes and standards of care to improve quality of clinical services 55. Processes of diabetic care provide needed disease control activities against a set of risk factors30 (eg, high levels of albuminuria) which in turn improve clinical outcomes (eg, prevention of kidney impairment) 5 7.…”

Acknowledging the role of patient heterogeneity in hospital outcome reporting: Mortality after acute myocardial infarction in five European countries

“…https://doi.org/10.1371/journal.pone.0228425.g003 such a way, the hospital context may condition patient outcomes beyond individual characteristics; that is, the same patient might have a different outcome if he or she is treated in a different hospital. However, while GEE modelling takes for granted that this GCE can be quantified by measuring differences between hospital averages only, in MLRM the GCE is measured by the share of the total patient variance that is between hospital averages; that is, the MLRM does not dislocate the individual patients from the hospital averages, but rather considers that there is a distribution of individual outcomes that can be decomposed into two levels of analysis, the individual and the hospital [9,12,14]. Therefore, "hospital effects" (i.e.…”

“…Either institutionally framed or developed under the umbrella of research projects, the wealth of administrative data offers the opportunity to access larger samples of patients, covering virtually all providers in a health plan, allowing cross-country comparisons and most importantly, enabling the systematic and continuous monitoring of providers' performance. Many institutional-based [1-7] and research-oriented examples [8][9][10][11][12][13][14][15] illustrate this enormous potential. On the other hand, as performance assessment is increasingly deemed to be the basis for different value-based initiatives (e.g.…”