Hospital Level of Care and Neonatal Mortality in Low- and High-Risk Deliveries

Are birth outcomes in low risk birth cohorts related to hospital birth volumes? A systematic review

Background

There is convincing evidence that birth in hospitals with high birth volumes increases the chance of healthy survival in high-risk infants. However, it is unclear whether this is true also for low risk infants. The aim of this systematic review was to analyze effects of hospital’s birth volume on mortality, mode of delivery, readmissions, complications and subsequent developmental delays in all births or predefined low risk birth cohorts. The search strategy included EMBASE and Medline supplemented by citing and cited literature of included studies and expert panel highlighting additional literature, published between January/2000 and February/2020. We included studies which were published in English or German language reporting effects of birth volumes on mortality in term or all births in countries with neonatal mortality < 5/1000. We undertook a double-independent title-abstract- and full-text screening and extraction of study characteristics, critical appraisal and outcomes in a qualitative evidence synthesis.

Results

13 retrospective studies with mostly acceptable quality were included. Heterogeneous volume-thresholds, risk adjustments, outcomes and populations hindered a meta-analysis. Qualitatively, four of six studies reported significantly higher perinatal mortality in lower birth volume hospitals. Volume-outcome effects on neonatal mortality (n = 7), stillbirths (n = 3), maternal mortality (n = 1), caesarean sections (n = 2), maternal (n = 1) and neonatal complications (n = 1) were inconclusive.

Conclusion

Analyzed studies indicate higher rates of perinatal mortality for low risk birth in hospitals with low birth volumes. Due to heterogeneity of studies, data synthesis was complicated and a meta-analysis was not possible. Therefore international core outcome sets should be defined and implemented in perinatal registries.

Systematic review registration

PROSPERO: CRD42018095289

Supplementary Information

The online version contains supplementary material available at 10.1186/s12884-021-03988-y.

Access to risk-appropriate hospital care and disparities in neonatal outcomes in racial/ethnic groups and rural-urban populations

Variations in infant and neonatal mortality continue to persist in the United States and in other countries based on both socio-demographic characteristics, such as race and ethnicity, and geographic location. One potential driver of these differences is variations in access to risk-appropriate delivery care. The purpose of this article is to present the importance of delivery hospitals on neonatal outcomes, discuss variation in access to these hospitals for high-risk infants and their mothers, and to provide insight into drivers for differences in access to high-quality perinatal care using the available literature. This review also illustrates the lack of information on a number of topics that are crucial to the development of evidence-based interventions to improve access to appropriate delivery hospital services and thus optimize the outcomes of high-risk mothers and their newborns.

Cross-classified Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) to evaluate hospital performance: the case of hospital differences in patient survival after acute myocardial infarction

OBJECTIVE

To describe a novel strategy, Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) to evaluate hospital performance, by analysing differences in 30-day mortality after a first-ever acute myocardial infarction (AMI) in Sweden.

DESIGN

Cross-classified study.

SETTING

68 Swedish hospitals.

PARTICIPANTS

43 247 patients admitted between 2007 and 2009, with a first-ever AMI.

PRIMARY AND SECONDARY OUTCOME MEASURES

We evaluate hospital performance by analysing differences in 30-day mortality after a first-ever AMI using a cross-classified multilevel analysis. We classified the patients into 10 categories according to a risk score (RS) for 30-day mortality and created 680 strata defined by combining hospital and RS categories.

RESULTS

In the cross-classified multilevel analysis the overall RS adjusted hospital 30-day mortality in Sweden was 4.78% and the between-hospital variation was very small (variance partition coefficient (VPC)=0.70%, area under the curve (AUC)=0.54). The benchmark value was therefore achieved by all hospitals. However, as expected, there were large differences between the RS categories (VPC=34.13%, AUC=0.77) CONCLUSIONS: MAIHDA is a useful tool to evaluate hospital performance. The benefit of this novel approach to adjusting for patient RS is that it allowed one to estimate separate VPCs and AUC statistics to simultaneously evaluate the influence of RS categories and hospital differences on mortality. At the time of our analysis, all hospitals in Sweden were performing homogeneously well. That is, the benchmark target for 30-day mortality was fully achieved and there were not relevant hospital differences. Therefore, possible quality interventions should be universal and oriented to maintain the high hospital quality of care.

Delivery Hospital Characteristics and Postpartum Maternal Mortality: A National Case-Control Study in France

BACKGROUND

The variability in resources for managing critical events among maternity hospitals may impact maternal safety. Our main objective was to assess the risk of postpartum maternal death according to hospitals' organizational characteristics. A secondary objective aimed to assess the specific risk of death due to postpartum hemorrhage (PPH).

METHODS

This national population-based case-control study included all 2007-2009 postpartum maternal deaths from the national confidential enquiry (n = 147 cases) and a 2010 national representative sample of parturients (n = 14,639 controls). To adjust for referral bias, cases were classified by time when the condition/complication responsible for the death occurred: postpartum maternal deaths due to conditions present before delivery (n = 66) or during or after delivery (n = 81). Characteristics of delivery hospitals included 24/7 on-site availability of an anesthesiologist and an obstetrician, level of perinatal care, number of deliveries annually, and their teaching and profit status. In teaching and other nonprofit hospitals in France, obstetric care is organized on the principle of collective team-based management, while in for-profit hospitals, this organization is based mostly on that of "one woman-one doctor." Logistic regression models were used to estimate adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for postpartum maternal death.

RESULTS

The risk of maternal death from prepartum conditions was lower for women who gave birth in for-profit compared with teaching hospitals (aOR, 0.3; 95% CI, 0.1-0.8; P = .02) and in hospitals with <1500 vs ≥1500 annual deliveries (aOR, 0.4; 95% CI, 0.1-0.9; P = .02). Conversely, the risk of postpartum maternal death from complications occurring during or after delivery was higher for women who delivered in for-profit compared with teaching hospitals (aOR, 2.8; 95% CI, 1.3-6.0; P = .009), as was the risk of death from PPH in for-profit versus nonprofit hospitals (aOR, 2.8; 95% CI, 1.2-6.5; P = .019).

CONCLUSIONS

After adjustment for the referral bias related to prepartum morbidity, the risk of postpartum maternal mortality in France differs according to the hospital's organizational characteristics.

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

Background

Hospital performance, presented as the comparison of average measurements, dismisses that hospital outcomes may vary across types of patients. We aim at drawing out the relevance of accounting for patient heterogeneity when reporting on hospital performance.

Methods

An observational study on administrative data from virtually all 2009 hospital admissions for Acute Myocardial Infarction (AMI) discharged in Denmark, Portugal, Slovenia, Spain, and Sweden. Hospital performance was proxied using in-hospital risk-adjusted mortality. Multilevel Regression Modelling (MLRM) was used to assess differences in hospital performance, comparing the estimates of random intercept modelling (capturing hospital general contextual effects (GCE)), and random slope modelling (capturing hospital contextual effects for patients with and without congestive heart failure -CHF). The weighted Kappa Index (KI) was used to assess the agreement between performance estimates.

Results

We analysed 46,875 admissions of AMI, 6,314 with coexistent CHF, discharged from 107 hospitals. The overall in-hospital mortality rate was 5.2%, ranging from 4% in Sweden to 6.9% in Portugal. The MLRM with random slope outperformed the model with only random intercept, highlighting a much higher GCE in CHF patients [VPC = 8.34 (CI95% 4.94 to 13.03) and MOR = 1.69 (CI95% 1.62 to 2.21) vs. VPC = 3.9 (CI95% 2.4 to 5.9), MOR of 1.42 (CI95% 1.31 to 1.54) without CHF]. No agreement was observed between estimates [KI = -0,02 (CI95% -0,08 to 0.04].

Conclusions

The different GCE in AMI patients with and without CHF, along with the lack of agreement in estimates, suggests that accounting for patient heterogeneity is required to adequately characterize and report on hospital performance.

Precision public health: Mapping socioeconomic disparities in opioid dispensations at Swedish pharmacies by Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA)

BACKGROUND

In light of the opioid epidemic in the United States, there is growing concern about the use of opioids in Sweden as it may lead to misuse and overuse and, in turn, severe public health problems. However, little is known about the distribution of opioid use across different demographic and socioeconomic dimensions in the Swedish general population. Therefore, we applied an intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA), to obtain an improved mapping of the risk heterogeneity of and socioeconomic inequalities in opioid prescription receipt.

METHODS AND FINDINGS

Using data from 6,846,106 residents in Sweden aged 18 and above, we constructed 72 intersectional strata from combinations of gender, age, income, cohabitation status, and presence or absence of psychological distress. We modelled the absolute risk (AR) of opioid prescription receipt in a series of multilevel logistic regression models distinguishing between additive and interaction effects. By means of the Variance Partitioning Coefficient (VPC) and the area under the receiver operating characteristic curve (AUC), we quantified the discriminatory accuracy (DA) of the intersectional strata for discerning those who received opioid prescriptions from those who did not. The AR of opioid prescription receipt ranged from 2.77% (95% CI 2.69-2.86) among low-income men aged 18-34, living alone, without psychological distress, to 28.25% (95% CI 27.95-28.56) among medium-income women aged 65 and older, living alone, with psychological distress. In a model that conflated both additive and interaction effects, the intersectional strata had a fair DA for discerning opioid users from non-users (VPC = 13.2%, AUC = 0.68). However, in the model that decomposed total effects into additive and interaction effects, the VPC was very low (0.42%) indicating the existence of small interaction effects for a number of the intersectional strata.

CONCLUSIONS

The intersectional MAIHDA approach aligns with the aims of precision public health, through improving the evidence base for health policy by increasing understanding of both health inequalities and individual heterogeneity. This approach is particularly relevant for socioeconomically conditioned outcomes such as opioid prescription receipt. We have identified intersections of social position within the Swedish population at greater risk for opioid prescription receipt.

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

Background

Studies assessing institutional performance regarding quality of care are frequently performed using single-level statistical analyses investigating differences between provider averages of various quality indicators. However, such analyses are insufficient as they do not consider patients’ heterogeneity around those averages. Hence, we apply a multilevel analysis of individual-patient heterogeneity that distinguishes between ‘general’ (‘latent quality’ or measures of variance) and ‘specific’ (measures of association) contextual effects. We assess general contextual effects of the hospital departments and the specific contextual effect of a national accreditation programme on adherence to the standard benchmark for albuminuria measurement in Danish patients with diabetes.

Methods

From the Danish Adult Diabetes Database, we extracted data on 137 893 patient cases admitted to hospitals between 2010 and 2013. Applying multilevel logistic and probit regression models for every year, we quantified general contextual effects of hospital department by the intraclass correlation coefficient (ICC) and the area under the receiver operating characteristic curve (AUC) values. We evaluated the specific effect of hospital accreditation using the ORs and the change in the department variance.

Results

In 2010, the department context had considerable influence on adherence with albuminuria measurement (ICC=21.8%, AUC=0.770), but the general effect attenuated along with the implementation of the national accreditation programme. The ICC value was 16.5% in 2013 and the rate of compliance with albuminuria measurement increased from 91.6% in 2010 to 96% in 2013.

Conclusions

Parallel to implementation of the national accreditation programme, departments’ compliance with the standard benchmark for albuminuria measurement increased and the ICC values decreased, but remained high. While those results indicate an overall quality improvement, further intervention focusing on departments with the lowest compliance could be considered.

Risk-Appropriate Care to Improve Practice and Birth Outcomes

Identification and referral of women with high-risk pregnancies to hospitals better equipped and staffed to provide care for them have been important steps to improve birth outcomes. Based on recent recommendations from the American College of Obstetricians and Gynecologists and the Society for Maternal-Fetal Medicine to provide regionalized maternal care for pregnant women at high risk and reduce rates of maternal morbidity and mortality, health care organizations and providers have refocused their attention to women's well-being rather than solely on the well-being of the fetus or newborn. Opportunities to improve practice and birth outcomes exist through the implementation of a more standardized and integrated system of risk-appropriate care.

Mind the Gap: What explains the education-related inequality in missed opportunities for vaccination in sub-Saharan Africa? Compositional and structural characteristics

Missed opportunities for vaccination (MOV) is an important barrier hindering full immunisation coverage among eligible children. Though factors responsible for MOV are well documented in literature, little attention has been paid to the role of inequalities. The aim of this study is to examine the association between structural or compositional factors and education inequalities in MOV. Blinder-Oaxaca decomposition technique was used to explain the factors contributing to the average gap in missed opportunities for vaccination between uneducated and educated mothers in sub-Saharan Africa using DHS survey data from 35 sub Saharan African countries collected between 2007 and 2016. The sample contained 69,657 children aged 12 to 23 months. We observed a wide variation and inter-country differences in the prevalence of missed opportunity for vaccination across populations and geographical locations. Our results show that the prevalence of MOV in Zimbabwe among uneducated and educated mothers was 9% and 21% respectively while in Gabon corresponding numbers were 85% and 89% respectively. In 15 countries, MOV was significantly prevalent among children born to uneducated mothers (pro-illiterate inequality) while in 5 countries MOV was significantly prevalent among educated mothers (pro-educated inequality). Our results suggest that education-related inequalities in missed opportunities for vaccination are explained by compositional and structural characteristics; and that neighbourhood socio-economic status was the most important contributor to education-related inequalities across countries followed by either the presence of under-five children, media access or household wealth index. The results showed that differential effects such as neighbourhood socio-economic status, presence of under-five children, media access and household wealth index, primarily explained education-related inequality in MOV. Interventions to reduce gaps in education-related inequality in MOV should focus on social determinants of health.

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

Purpose

To 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.

Methods

Using 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.

Results

One-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.

Conclusion

Using 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.

Perinatal legislative policies and health outcomes

Perinatal epidemiology examines the variation and determinants of pregnancy outcomes from a maternal and neonatal perspective. However, improving public and population health also requires the translation of this evidence base into substantive public policies. Assessing the impact of such public policies requires sufficient data to include potential confounding factors in the analysis, such as coexisting medical conditions and socioeconomic status, and appropriate statistical and epidemiological techniques. This review will explore policies addressing three areas of perinatal medicine-elective deliveries prior to 39 weeks' gestation; perinatal regionalization; and mandatory paid maternity leave policies-to illustrate the challenges when assessing the impact of specific policies at the patient and population level. Data support the use of these policies to improve perinatal health, but with weaker and less certain effect sizes when compared to the initial patient-level studies. Improved data collection and epidemiological techniques will allow for improved assessment of these policies and the identification of potential areas of improvement when translating patient-level studies into public policies.

Increased risk of peripartum perinatal mortality in unplanned births outside an institution: a retrospective population-based study

BACKGROUND

Births in midwife-led institutions may reduce the frequency of medical interventions and provide cost-effective care, while larger institutions offer medically and technically advanced obstetric care. Unplanned births outside an institution and intrapartum stillbirths have frequently been excluded in previous studies on adverse outcomes by place of birth.

OBJECTIVE

The objective of the study was to assess peripartum mortality by place of birth and travel time to obstetric institutions, with the hypothesis that centralization reduces institution availability but improves mortality.

STUDY DESIGN

This was a national population-based retrospective cohort study of all births in Norway from 1999 to 2009 (n = 648,555) using data from the Medical Birth Registry of Norway and Statistics Norway and including births from 22 gestational weeks or birthweight ≥500 g. Main exposures were travel time to the nearest obstetric institution and place of birth. The main clinical outcome was peripartum mortality, defined as death during birth or within 24 hours. Intrauterine fetal deaths prior to start of labor were excluded from the primary outcome.

RESULTS

A total of 1586 peripartum deaths were identified (2.5 per 1000 births). Unplanned birth outside an institution had a 3 times higher mortality (8.4 per 1000) than institutional births (2.4 per 1000), relative risk, 3.5 (95% confidence interval, 2.5-4.9) and contributed 2% (95% confidence interval, 1.2-3.0%) of the peripartum mortality at the population level. The risk of unplanned birth outside an institution increased from 0.5% to 3.3% and 4.5% with travel time <1 hour, 1-2 hours, and >2 hours, respectively. In obstetric institutions the mortality rate at term ranged from 0.7 per 1000 to 0.9 per 1000. Comparable mortality rates in different obstetric institutions indicated well-functioning routines for referral.

CONCLUSION

Unplanned birth outside an institution was associated with increased peripartum mortality and with long travel time to obstetric institutions. Structural determinants have an important impact on perinatal health in high-income countries and also for low-risk births. The results show the importance of skilled birth attendance and warrant attention from clinicians and policy makers to negative consequences of reduced access to institutions.

Centralized or decentralized perinatal surgical care for rural women: a realist review of the evidence on safety

BACKGROUND

The precipitous closure of rural maternity services in British Columbia (BC), Canada, and internationally has demanded a reevaluation of how to meet the perinatal surgical needs of rural women in accordance with the Triple Aim objectives of safety, cost-effectiveness, and satisfaction of all key stakeholders. There is emerging international evidence that General Practitioners with Enhanced Surgical Skills (GPESS) are a well-positioned health service solution due to their generalist nature in low-volume settings. A realist review was undertaken to evaluate international evidence on efficacious models of perinatal surgical care. This article presents findings of the safety of such practice, one discrete part of the full realist review.

METHODS

This paper was derived from a larger review, which used a realist review methodology to guide the approach, and adhered to the RAMESES quality standard for realist reviews. Seven academic databases were searched in December 2013, using year (1990) and language (English) limiters in keeping with a rapid review approach. Mining of bibliographies in addition to consultation with international experts led to further inclusion of academic and grey literature up to March 2014.

RESULTS

Two hundred fifty-four articles were originally identified; 119 articles were removed from consideration for lack of fit, resulting in the review of 191 articles from the peer reviewed and grey literature. Of these, 53 pertained to safety and are considered herein. Evidence on the safety of GPESS was consistent in the literature cited. Clinical, case study, and qualitative evidence demonstrates that perinatal surgical care is equally safe when provided by GPESS and specialist physicians.

CONCLUSION

Findings allow health planners to confidently build perinatal surgical services around the contribution of GPs with enhanced surgical skills and focus on educational, regulatory, and continuing professional development mechanisms to ensure their sustainability. Volume-to-outcomes associations are variable and inconclusive with regards to safety, suggesting the need for more evidence. These findings, and the attendant health services planning directions, are reassuring as they suggest the viability of local models of care where feasible.

Short Term Survival after Admission for Heart Failure in Sweden: Applying Multilevel Analyses of Discriminatory Accuracy to Evaluate Institutional Performance

BACKGROUND

Hospital performance is frequently evaluated by analyzing differences between hospital averages in some quality indicators. The results are often expressed as quality charts of hospital variance (e.g., league tables, funnel plots). However, those analyses seldom consider patients heterogeneity around averages, which is of fundamental relevance for a correct evaluation. Therefore, we apply an innovative methodology based on measures of components of variance and discriminatory accuracy to analyze 30-day mortality after hospital discharge with a diagnosis of Heart Failure (HF) in Sweden.

METHODS

We analyzed 36,943 patients aged 45-80 treated in 565 wards at 71 hospitals during 2007-2009. We applied single and multilevel logistic regression analyses to calculate the odds ratios and the area under the receiver-operating characteristic (AUC). We evaluated general hospital and ward effects by quantifying the intra-class correlation coefficient (ICC) and the increment in the AUC obtained by adding random effects in a multilevel regression analysis (MLRA). Finally, the Odds Ratios (ORs) for specific ward and hospital characteristics were interpreted jointly with the proportional change in variance (PCV) and the proportion of ORs in the opposite direction (POOR).

FINDINGS

Overall, the average 30-day mortality was 9%. Using only patient information on age and previous hospitalizations for different diseases we obtained an AUC = 0.727. This value was almost unchanged when adding sex, country of birth as well as hospitals and wards levels. Average mortality was higher in small wards and municipal hospitals but the POOR values were 15% and 16% respectively.

CONCLUSIONS

Swedish wards and hospitals in general performed homogeneously well, resulting in a low 30-day mortality rate after HF. In our study, knowledge on a patient's previous hospitalizations was the best predictor of 30-day mortality, and this information did not improve by knowing the sex and country of birth of the patient or where the patient was treated.

Effect of hospital size and on-call arrangements on intrapartum and early neonatal mortality among low-risk newborns in Finland

OBJECTIVE

To evaluate the influence of delivery unit size and on-call staffing in the performance of low-risk deliveries in Finland.

STUDY DESIGN

A population-based study of hospital size and level based on Medical Birth Register data. Population was all hospital births in Finland in 2005-2009. Inclusion criteria were singleton births (birth weight 2500g or more) without major congenital anomalies or birth defects. Additionally, only intrapartum stillbirths were included. Birthweights and maternal background characteristics were adjusted for by logistic regression. Main outcome measures were intrapartum or early neonatal mortality, neonatal asphyxia and newborns' need for intensive care or transfer to other hospital and longer duration of care. On-call arrangements were asked from each of the hospitals.

RESULTS

Intrapartum mortality was higher in units where physicians were at home when on-call (OR 1.25; 95% CI 1.02-1.52). A tendency to a higher mortality was also recorded in non-university hospitals (OR 1.18; 95% CI 0.99-1.40). Early neonatal mortality was twofold in units with less than 1000 births annually (OR 2.11; 95% CI 0.97-4.56) and in units where physicians were at home when on-call (OR 1.85; 95% CI 0.91-3.76). These results did not reach statistical significance. No differences between the units were found regarding Apgar scores or umbilical cord pH.

CONCLUSION

The differences in mortality rates between different level hospitals suggest that adverse outcomes during delivery should be studied in detail in relation to hospital characteristics, such as size or level, and more international studies determining obstetric patient safety indicators are required.

The effectiveness of regionalization of perinatal care services--a systematic review

BACKGROUND

Several reports recommend the implementation of perinatal regionalization for improvements in maternal and neonatal outcomes, while research evidence on the effectiveness of perinatal regionalization has been limited. The interventional studies have been assessed for robust evidence on the effectiveness of perinatal regionalization on improving maternal and neonatal health outcomes.

METHODS

Bibliographic databases of Medline, EMbase, EconLit, HMIC have been searched using sensitive search terms for interventional studies that reported important patient or process outcomes. At least two authors assessed eligibility for inclusion and the risk of biases and extracted data from the included studies. As meta-analysis was not possible, a narrative analysis as well as a 'vote-counting' analysis has been conducted for important outcomes.

RESULTS

After initial screenings 53 full text papers were retrieved. Eight studies were included in the review from the USA, Canada and France. Studies varied in their designs, and in the specifications of the intervention and setting. Only three interrupted time series studies had a low risk of bias, of which only one study reported significant reductions in neonatal and infant mortality. Studies of higher risk of bias were more likely to report improvements in outcomes.

CONCLUSIONS

Implementing perinatal regionalization programs is correlated with improvements in perinatal outcomes, but it is not possible to establish a causal link. Despite several high profile policy statements, evidence of effect is weak. It is necessary to assess the effectiveness of perinatal regionalization using robust research designs in a more diverse range of countries.

Perinatal health inequalities and accessibility of maternity services in a rural French region: closing maternity units in Burgundy

Maternity unit closures in France have increased travel time for pregnant women in rural areas. We assessed the impact of travel time to the closest unit on perinatal outcomes and care in Burgundy using multilevel analyses of data on deliveries from 2000 to 2009. A travel time of 30min or more increased risks of fetal heart rate anomalies, meconium-stained amniotic fluid, out-of-hospital births, and pregnancy hospitalizations; a positive but non-significant gradient existed between travel time and perinatal mortality. The effects of long travel distances on perinatal outcomes and care should be factored into closure decisions.

Hospital-level variation in the use of intensive care

OBJECTIVE

To determine the extent to which hospitals vary in the use of intensive care, and the proportion of variation attributable to differences in hospital practice that is independent of known patient and hospital factors.

DATA SOURCE

Hospital discharge data in the State Inpatient Database for Maryland and Washington States in 2006.

STUDY DESIGN

Cross-sectional analysis of 90 short-term, acute care hospitals with critical care capabilities. DATA COLLECTION/METHODS: We quantified the proportion of variation in intensive care use attributable to hospitals using intraclass correlation coefficients derived from mixed-effects logistic regression models after successive adjustment for known patient and hospital factors.

PRINCIPAL FINDINGS

The proportion of hospitalized patients admitted to an intensive care unit (ICU) across hospitals ranged from 3 to 55 percent (median 12 percent; IQR: 9, 17 percent). After adjustment for patient factors, 19.7 percent (95 percent CI: 15.1, 24.4) of total variation in ICU use across hospitals was attributable to hospitals. When observed hospital characteristics were added, the proportion of total variation in intensive care use attributable to unmeasured hospital factors decreased by 26-14.6 percent (95 percent CI: 11, 18.3 percent).

CONCLUSIONS

Wide variability exists in the use of intensive care across hospitals, not attributable to known patient or hospital factors, and may be a target to improve efficiency and quality of critical care.

Hospital-level associations with 30-day patient mortality after cardiac surgery: a tutorial on the application and interpretation of marginal and multilevel logistic regression

Background

Marginal and multilevel logistic regression methods can estimate associations between hospital-level factors and patient-level 30-day mortality outcomes after cardiac surgery. However, it is not widely understood how the interpretation of hospital-level effects differs between these methods.

Methods

The Australasian Society of Cardiac and Thoracic Surgeons (ASCTS) registry provided data on 32,354 patients undergoing cardiac surgery in 18 hospitals from 2001 to 2009. The logistic regression methods related 30-day mortality after surgery to hospital characteristics with concurrent adjustment for patient characteristics.

Results

Hospital-level mortality rates varied from 1.0% to 4.1% of patients. Ordinary, marginal and multilevel regression methods differed with regard to point estimates and conclusions on statistical significance for hospital-level risk factors; ordinary logistic regression giving inappropriately narrow confidence intervals. The median odds ratio, MOR, from the multilevel model was 1.2 whereas ORs for most patient-level characteristics were of greater magnitude suggesting that unexplained between-hospital variation was not as relevant as patient-level characteristics for understanding mortality rates. For hospital-level characteristics in the multilevel model, 80% interval ORs, IOR-80%, supplemented the usual ORs from the logistic regression. The IOR-80% was (0.8 to 1.8) for academic affiliation and (0.6 to 1.3) for the median annual number of cardiac surgery procedures. The width of these intervals reflected the unexplained variation between hospitals in mortality rates; the inclusion of one in each interval suggested an inability to add meaningfully to explaining variation in mortality rates.

Conclusions

Marginal and multilevel models take different approaches to account for correlation between patients within hospitals and they lead to different interpretations for hospital-level odds ratios.

Coeliac disease in children: a social epidemiological study in Sweden

AIM

Little is known on the possible existence of socioeconomic and geographical differences in early coeliac disease (CD) risk. Therefore, we investigated these aspects in children before age two.

METHODS

Linking the Swedish Medical Birth Registry to several other national registries, we identified all singletons born in Sweden from 1987 to 1993 (n = 792,401) and followed them until 2 years of age to identify cases of CD. Applying multilevel logistic regression analysis, we investigated the association between socioeconomic position (SEP) and CD in children and also whether a possible geographical variation in CD risk was explained by individual characteristics.

RESULTS

Low SEP was associated with CD in boys OR 1.37 (95% CI 1.03-1.82), but not in girls OR 0.87 (95% CI 0.68-1.12). We found a considerable geographical variation in disease risk (i.e. intra-municipality correlation ≈ 10%) that was not explained by individual characteristics.

CONCLUSIONS

Low SEP is associated with CD in boys but not in girls. Also, CD appears to be conditioned by geographical area of residence. While our study represents an innovative contribution to the epidemiology of CD in children, the reasons for the observed geographical and socioeconomic differences could be speculated but are still unknown.

Inter-doctor variations in the assessment of functional incapacities by insurance physicians

Background

The aim of this study was to determine the - largely unexplored - extent of systematic variation in the work disability assessment by Dutch insurance physicians (IPs) of employees on long-term sick leave, and to ascertain whether this variation was associated with the individual characteristics and opinions of IPs.

Methods

In March 2008 we conducted a survey among IPs on the basis of the 'Attitude - Social norm - self-Efficacy' (ASE) model. We used the ensuing data to form latent variables for the ASE constructs. We then linked the background variables and the measured constructs for IPs (n = 199) working at regional offices (n = 27) to the work disability assessments of clients (n = 83,755) and their characteristics. These assessments were carried out between July 2003 and April 2008. We performed multilevel regression analysis on three important assessment outcomes: No Sustainable Capacity or Restrictions for Working Hours (binominal), Functional Incapacity Score (scale 0-6) and Maximum Work Disability Class (binominal). We calculated Intra Class Correlations (ICCs) at IP level and office level and explained variances (R²) for the three outcomes. A higher ICC reflects stronger systematic variation.

Results

The ICCs at IP level were approximately 6% for No Sustainable Capacity or Restrictions for Working Hours and Maximum Work Disability Class and 12% for Functional Incapacity Score. Background IP variables and the measured ASE constructs for physicians contributed very little to the variation - at most 1%. The ICCs at office level ranged from 0% to around 1%. The R² was 11% for No Sustainable Capacity or Restrictions for Working Hours, 19% for Functional Incapacity Score and 37% for Maximum Work Disability Class.

Conclusion

Our study uncovered small to moderate systematic variations in the outcome of disability assessments in the Netherlands. However, the individual characteristics and opinions of insurance physicians have very little impact on these variations. Our findings provided no indications of other reasons for these variations. They may be related to different work routines or to different views on the workload of a 'normal' employee. If so, they could be reduced by well-developed and comprehensively implemented guidelines. Therefore, further research is needed.

Should births be centralised in higher level hospitals? Experiences from regionalised health care in Finland

OBJECTIVE

To describe: (i) trends in centralisation and unplanned out-of-hospital births; (ii) perinatal mortality by place of birth; and (iii) health and birth outcomes in areas served by hospitals of different levels.

DESIGN

Cross-sectional analysis of medical birth register data.

SETTING

Finland, from 1991 to 2008, and Uusimaa district from 2004 to 2008.

POPULATION

All births.

METHODS

In the hospital-based analysis, birthweight was adjusted by logistic regression. In the area-based analysis results were calculated according to where women lived, grouping them into areas served by different hospitals. The mother's background characteristics were adjusted for by logistic regression.

MAIN OUTCOME MEASURES

Place of birth, unplanned out-of-hospital birth, perinatal mortality, newborn outcomes, and birth procedures.

RESULTS

The number of birthing hospitals declined, the mean number of births per hospital increased, and more births, particularly high-risk births, occurred in university hospitals. Unplanned out-of-hospital births were rare, and their numbers increased in the 2000s, but regional differences declined. Perinatal mortality was higher in the university hospitals than in other hospitals, but after adjusting for birthweight, it was lower. Among children weighing more than 2500 g, mortality was similar for all hospital levels. In out-of-hospital births, perinatal mortality was much higher than in other children. The area-based analysis did not systematically show better or worse results for the areas served by lower level hospitals: after adjusting for the background characteristics of the mothers, all differences were found to be small.

CONCLUSIONS

The health and service data do not support the need to close down small hospitals in a regionalised system where there is a referral system that functions well.

Variation in plasma calcium analysis in primary care in Sweden--a multilevel analysis

Background

Primary hyperparathyroidism (pHPT) is a common disease that often remains undetected and causes severe disturbance especially in postmenopausal women. Therefore, national recommendations promoting early pHPT detection by plasma calcium (P-Ca) have been issued in Sweden. In this study we aimed to investigate variation of P-Ca analysis between physicians and health care centres (HCCs) in primary care in county of Skaraborg, Sweden.

Methods

In this cross sectional study of patients' records during 2005 we analysed records from 154 629 patients attending 457 physicians at 24 HCCs. We used multilevel logistic regression analysis (MLRA) and adjusted for patient, physician and HCC characteristics. Differences were expressed as median odds ratio (MOR).

Results

There was a substantial variation in number of P-Ca analyses between both HCCs (MOR_HCC 1.65 [1.44-2.07]) and physicians (MOR_physician 1.95 [1.85-2.08]). The odds for a P-Ca analysis were lower for male patients (OR 0.80 [0.77-0.83]) and increased with the number of diagnoses (OR 25.8 [23.5-28.5]). Sex of the physician had no influence on P-Ca test ordering (OR 0.93 [0.78-1.09]). Physicians under education ordered most P-Ca analyses (OR 1.69 [1.35-2.24]) and locum least (OR 0.73 [0.57-0.94]). More of the variance was attributed to the physician level than the HCC level. Different mix of patients did not explain this variance between physicians. Theoretically, if a patient were able to change both GP and HCC, the odds of a P-Ca analysis would in median increase by 2.45. Including characteristics of the patients, physicians and HCCs in the MLRA model did not explain the variance.

Conclusions

The physician level was more important than the HCC level for the variation in P-Ca analysis, but further exploration of unidentified contextual factors is crucial for future monitoring of practice variation.

Multilevel survival analysis of health inequalities in life expectancy

BACKGROUND

The health status of individuals is determined by multiple factors operating at both micro and macro levels and the interactive effects of them. Measures of health inequalities should reflect such determinants explicitly through sources of levels and combining mean differences at group levels and the variation of individuals, for the benefits of decision making and intervention planning. Measures derived recently from marginal models such as beta-binomial and frailty survival, address this issue to some extent, but are limited in handling data with complex structures. Beta-binomial models were also limited in relation to measuring inequalities of life expectancy (LE) directly.

METHODS

We propose a multilevel survival model analysis that estimates life expectancy based on survival time with censored data. The model explicitly disentangles total health inequalities in terms of variance components of life expectancy compared to the source of variation at the level of individuals in households and parishes and so on, and estimates group differences of inequalities at the same time. Adjusted distributions of life expectancy by gender and by household socioeconomic level are calculated. Relative and absolute health inequality indices are derived based on model estimates. The model based analysis is illustrated on a large Swedish cohort of 22,680 men and 26,474 women aged 6569 in 1970 and followed up for 30 years. Model based inequality measures are compared to the conventional calculations.

RESULTS

Much variation of life expectancy is observed at individual and household levels. Contextual effects at Parish and Municipality level are negligible. Women have longer life expectancy than men and lower inequality. There is marked inequality by the level of household socioeconomic status measured by the median life expectancy in each socio-economic group and the variation in life expectancy within each group.

CONCLUSION

Multilevel survival models are flexible and efficient tools in studying health inequalities of life expectancy or survival time data with a geographic structure of more than 2 levels. They are complementary to conventional methods and override some limitations of marginal models. Future research on determinants of health inequalities in the LE of the specific cohort on the household and individual factors could reveal some important causes over the marked household level inequalities.

Impact of maternity unit closures on access to obstetrical care: the French experience between 1998 and 2003

As in many other countries, the number of maternity units has diminished substantially in France, raising concerns about the reduced accessibility of obstetric services. We describe here the impact of closures on distance and mean travel time between pregnant women's homes and maternity units. We used data from the 1998 and 2003 French National Perinatal Surveys and from vital registries to measure indicators of accessibility: straight-line distance to the nearest maternity unit, number of units within a 15-km radius and reported travel time to the unit for delivery. We analyzed these measures for all births, births in rural versus urban areas and according to regional rates of maternity closures. From 1998 to 2003, 20% of maternity units closed (reducing the number from 759 to 621) with regional variations in the rate of closure from 0.0% to 36.0%. Mean distance to the nearest maternity unit increased (6.6-7.2 km, p < 0.001). The proportion of women living more than 30 km from a maternity ward was low; but rose from 1.4% to 1.8%. The number of maternity units with a 15-km radius of the place of residence fell (median, 3 to 2). Differences were more marked in rural areas and in regions highly affected by closures. However, reported travel time did not increase and even declined slightly for women from urban areas and in regions moderately affected by the closures. As such, the closures do not appear to have had a negative impact on the geographic accessibility of maternity units. Pregnant women were faced with a reduction in the number of maternity units near their homes and our results suggest that they more often chose their maternity units based on proximity. A full assessment of the impact of closures on accessibility to obstetric services would require information on how these changes affected available choices for care during pregnancy and delivery.

Changing analytical approaches in European epidemiology -- a short comment on a recent article

Multilevel analysis is today considered a more appropriate way to monitor health care performance, as it allows a less biased estimation of uncertainty, and can also separate and quantify contextual (as opposed to individual) effects. Multilevel analysis should be applied as the standard methodology for hospital comparisons. A greater awareness of this question in future Journal articles may be in order.