Comparing hospital mortality--how to count does matter for patients hospitalized for acute myocardial infarction (AMI), stroke and hip fracture

Risk Prediction Models for Hospital Mortality in General Medical Patients: A Systematic Review

Objective

To systematically review contemporary prediction models for hospital mortality developed or validated in general medical patients.

Methods

We screened articles in five databases, from January 1, 2010, through April 7, 2022, and the bibliography of articles selected for final inclusion. We assessed the quality for risk of bias and applicability using the Prediction Model Risk of Bias Assessment Tool (PROBAST) and extracted data using the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS) checklist. Two investigators independently screened each article, assessed quality, and extracted data.

Results

From 20,424 unique articles, we identified 15 models in 8 studies across 10 countries. The studies included 280,793 general medical patients and 19,923 hospital deaths. Models included 7 early warning scores, 2 comorbidities indices, and 6 combination models. Ten models were studied in all general medical patients (general models) and 7 in general medical patients with infection (infection models). Of the 15 models, 13 were developed using logistic or Poisson regression and 2 using machine learning methods. Also, 4 of 15 models reported on handling of missing values. None of the infection models had high discrimination, whereas 4 of 10 general models had high discrimination (area under curve >0.8). Only 1 model appropriately assessed calibration. All models had high risk of bias; 4 of 10 general models and 5 of 7 infection models had low concern for applicability for general medical patients.

Conclusion

Mortality prediction models for general medical patients were sparse and differed in quality, applicability, and discrimination. These models require hospital-level validation and/or recalibration in general medical patients to guide mortality reduction interventions.

OECD indicator 'AMI 30-day mortality' is neither comparable between countries nor suitable as indicator for quality of acute care

BACKGROUND

Hospital mortality after acute myocardial infarction (AMI, ICD-10: I21-I22) is used as OECD indicator of the quality of acute care. The reported AMI hospital mortality in Germany is more than twice as high as in the Netherlands or Scandinavia. Yet, in Europe, Germany ranks high in health spending and availability of cardiac procedures. We provide insights into this contradictory situation.

METHODS

Information was collected on possible factors causing the reported differences in AMI mortality such as prevalence of risk factors or comorbidities, guideline conform treatment, patient registration, and health system structures of European countries. International experts were interviewed. Data on OECD indicators 'AMI 30-day mortality using unlinked data' and 'average length of stay after AMI' were used to describe the association between these variables graphically and by linear regression.

RESULTS

Differences in prevalence of risk factors or comorbidities or in guideline conform acute care account only to a smaller extent for the reported differences in AMI hospital mortality. It is influenced mainly by patient registration rules and organization of health care. Non-reporting of day cases as patients and centralization of AMI care-with more frequent inter-hospital patient transfers-artificially lead to lower calculated hospital mortality. Frequency of patient transfers and national reimbursement policies affect the average length of stay in hospital which is strongly associated with AMI hospital mortality (adj R2 = 0.56). AMI mortality reported from registries is distorted by different underlying populations.

CONCLUSION

Most of the variation in AMI hospital mortality is explained by differences in patient registration and organization of care instead of differences in quality of care, which hinders cross-country comparisons of AMI mortality. Europe-wide sentinel regions with comparable registries are necessary to compare (acute) care after myocardial infarction.

Use of linked data to assess the impact of including out-of-hospital deaths on 30-day in-hospital mortality indicators: a retrospective cohort study

BACKGROUND

The Canadian Institute for Health Information (CIHI) annually reports on health system performance indicators, including various 30-day in-hospital mortality rates. We aimed to assess the impact of including out-of-hospital deaths on 3 CIHI indicators: 30-day acute myocardial infarction (AMI) in-hospital mortality, 30-day stroke in-hospital mortality and hospital deaths following major surgery.

METHODS

We followed national cohorts of patients admitted to hospital in 1 of 9 Canadian provinces for AMI, stroke and major surgery for 30-day all-cause mortality in 2 fiscal years (2011/12 and 2016/17). We calculated descriptive statistics to characterize the cohorts. The CIHI Discharge Abstract Database was linked with the Canadian Vital Statistics Death Database using a probabilistic algorithm to identify out-of-hospital deaths. We calculated absolute numbers, relative proportions and 30-day mortality rates for in-hospital, out-of-hospital and all deaths. We compared results between fiscal years.

RESULTS

We found that hospital admissions increased between fiscal years for each indicator; however, cohort characteristics remained consistent. In 2016/17, the number of out-of-hospital deaths that occurred was 325 for AMI, 545 for stroke and 820 for major surgery. The relative proportions of out-of-hospital deaths ranged from 12.3% for AMI to 14.9% for major surgery in 2016/17 (an increase from 10.6% and 13.1%, respectively, from 2011/12). In-hospital mortality rates improved over time for all 3 indicators, while out-of-hospital mortality rates remained consistent between fiscal years at 0.8% for AMI, 1.9%-2.0% for stroke and 0.2%-0.3% for major surgery.

INTERPRETATION

Improvements between fiscal years were attributable to reductions in in-hospital mortality, rather than deaths occurring outside of hospitals. Trends over time were the same for each indicator irrespective of whether in-hospital mortality or all deaths were measured.

Regional differences in access to acute ischaemic stroke care and patient outcomes

BACKGROUND

Advances in stroke management such as acute stroke units and thrombolysis are not uniformly distributed throughout our population, with rural areas being relatively disadvantaged. It remains unclear, however, whether such disparities have led to corresponding differences in patient outcomes.

AIMS

To describe the regional differences in acute ischaemic stroke care and outcomes within the Australian state of Tasmania.

METHODS

A retrospective case note audit was used to assess the care and outcomes of 395 acute ischaemic stroke patients admitted to Tasmania's four major public hospitals. Sixteen care processes were recorded, which covered time-critical treatment, allied health interventions and secondary prevention. Outcome measures were assessed using 30-day mortality and discharge destination, both of which were analysed for differences between urban and rural hospitals using logistic regression.

RESULTS

No patients in rural hospitals were administered thrombolysis; these hospitals also did not have acute stroke units. With few exceptions, patients' access to the remaining care indicators was comparable between regions. After adjusting for confounders, there were no significant differences between regions in terms of 30-day mortality (odds ratio (OR) = 0.99, 95% confidence interval (CI) 0.46-2.18) or discharge destination (OR = 1.24, 95% CI 0.81-1.91).

CONCLUSIONS

With the exception of acute stroke unit care and thrombolysis, acute ischaemic stroke care within Tasmania's urban and rural hospitals was broadly similar. No significant differences were found between regions in terms of patient outcomes. Future studies are encouraged to employ larger data sets, which capture a broader range of urban and rural sites and record patient outcomes at extended interval.

Trauma-registry survival outcome follow up: 30 days is mandatory and appears sufficient

INTRODUCTION

Thirty-day in-hospital mortality is a common outcome measure in trauma-registry research and benchmarking. However, this does not include deaths after hospital discharge before 30 days or late deaths beyond 30 days since the injury. To evaluate the reliability of this outcome measure, we assessed the timing and causes of death during the first year after major blunt trauma in patients treated at a single tertiary trauma center.

METHODS

We used the Helsinki Trauma Registry to identify severely injured (NISS ≥ 16) blunt trauma patients during 2006 to 2015. The Population Register center of Finland provided the mortality data for patients and Statistics Finland provided the cause of death information from death certificates. Disease, work-related disease, medical treatment, and unknown cause of death were considered as non-trauma related deaths. We divided the 1-year study period into the following three categories: in-hospital death before 30 days (Group 1), death after discharge but within 30 days (Group 2), and death 31 to 365 days since admission (Group 3).

RESULTS

We included 3557 patients with a median NISS of 29. Altogether, 21.8% (776/3557) patients died during the first year since the injury. Of these non-survivors, 12.7% (450) were in Group 1, 4.0% (141) in Group 2, and 5.2% (185) in Group 3. Non-traumatic deaths not directly related to the injury increased substantially as the time from the injury increased and were 2.0% (9/450) in Group 1, 13.5% (19/141) in Group 2, and 35.7% (66/185) in Group 3.

CONCLUSION

Thirty-day mortality is a proper outcome that measures survival after severe blunt trauma. However, applying only in-hospital mortality instead of actual 30-day mortality may exclude non-survivors who die at another facility before day 30. This could result in over-optimistic benchmarking results. On the other hand, extending the follow-up period beyond 30 days increases the rate of non-traumatic deaths. By combining data from different registries, it is possible to address this challenge in current trauma-registry research caused by lack of follow up.

Rising incidence of acute pancreatitis in Sweden: National estimates and trends between 1990 and 2013

BACKGROUND

Recent reports from western countries have indicated an increased incidence and a decreased mortality in acute pancreatitis. However, the incidence assessment has often been hampered by the inclusion of both first-time and recurrent episodes of acute pancreatitis.

METHODS

In this retrospective cohort study, all Swedish residents hospitalized with a first-time episode of acute pancreatitis between 1990 and 2013 were identified using national registers. Sex- and age-standardized incidence rates per 100,000 individuals and year were calculated, as were annual percent changes (APC) from joinpoint regression models.

RESULTS

Overall, between 1990 and 2013, 66,131 individuals had a first-time episode of acute pancreatitis in Sweden. Comparing the first five years (1990-1994) to the last four years (2010-2013) of the study period, the overall incidence of acute pancreatitis increased from 25.2 (95% confidence interval (CI): 24.1, 26.3) to 38.3 (95% CI: 37.0, 39.5) cases per 100,000 individuals and year. An increase in incidence was observed irrespective of the subtypes of acute pancreatitis as well as the sex and age of the patients. Although the incidence of complicated acute pancreatitis declined in both men and women between 1990 and 2004, it started to increase in both sexes (APC 3.0; 95% CI: 0.5, 5.5 in men; APC 5.4; 95% CI: 2.6, 8.2 in women) from 2005 onwards.

CONCLUSION

Based on nationwide data, the incidence of first-time acute pancreatitis has increased in Sweden over a period of 24 years. The incidence of disease-related complications has also been on the rise during the past few years, after declining for more than 15 years before that.

Lessons Learned From the Environmental Public Health Tracking Sub-County Data Pilot Project

OBJECTIVE

Small area data are key to better understanding the complex relationships between environmental health, health outcomes, and risk factors at a local level. In 2014, the Centers for Disease Control and Prevention's National Environmental Public Health Tracking Program (Tracking Program) conducted the Sub-County Data Pilot Project with grantees to consider integration of sub-county data into the National Environmental Public Health Tracking Network (Tracking Network).

DESIGN

The Tracking Program and grantees developed sub-county-level data for several data sets during this pilot project, working to standardize processes for submitting data and creating required geographies. Grantees documented challenges they encountered during the pilot project and documented decisions.

RESULTS

This article covers the challenges revealed during the project. It includes insights into geocoding, aggregation, population estimates, and data stability and provides recommendations for moving forward.

CONCLUSION

National standards for generating, analyzing, and sharing sub-county data should be established to build a system of sub-county data that allow for comparison of outcomes, geographies, and time. Increasing the availability and accessibility of small area data will not only enhance the Tracking Network's capabilities but also contribute to an improved understanding of environmental health and informed decision making at a local level.

Emergency laparotomy research methodology: A systematic review

BACKGROUND

Emergency abdominal surgery is associated with poorer clinical outcomes than similar procedures in the elective setting. Research into emergency laparotomy (EL) care is moving from observational studies which simply measure EL outcomes to interventional research evaluating the implementation of care strategies designed to improve the quality and outcomes from EL care. There is no consensus as to the optimal approach to conducting research in this sphere. The primary objective of this review was to examine how mortality and other outcome measures were reported in previous EL research and to identify what might be the most appropriate methods in future outcome research.

METHODS

A systematic review was performed in accordance with the PRISMA principles. Electronic databases were interrogated with a pre-specified search strategy to identify English language studies addressing outcomes from EL care. Retrieved papers were screened and assessed according to pre-defined eligibility criteria. The mortality and other outcomes reported in each paper were extracted and examined.

RESULTS

16 studies were included. They demonstrated significant heterogeneity in case definition, outcome reporting and data processing. A wide range of mortality and other outcome measures were applied and reported. Only few studies included on patient-reported outcomes measures.

CONCLUSION

The heterogeneity in EL research, demonstrated by this review must be considered when EL outcomes are compared. A standardized approach with respect to case definition, outcome measurement, and data analysis would provide for more valid and comparable evaluation of EL outcomes. Future EL research should include more patient centred outcomes.

Comparative analysis of recurrent events after presentation with an index myocardial infarction or ischaemic stroke

Aims

Acute myocardial infarction (AMI) and stroke are important causes of mortality and morbidity. Our aims are to determine the comparative epidemiology of AMI and ischaemic stroke; and examine the differences in cardiovascular outcomes or mortality occurring after an AMI or stroke.

Methods and results

The Singapore National Registry of Diseases Office collects countrywide data on AMI, stroke, and mortality. Index events of AMI and ischaemic stroke between 2007 and 2012 were identified. Patients were then matched for occurrences of subsequent AMI, stroke, or death within 1-year of the index event. There were 33 222 patients with first-ever AMI and 20 982 with first-ever stroke. AMI patients were significantly more likely to be men (66.3% vs. 56.9%), non-Chinese (32.1% vs. 24.1%), and smokers (43.1% vs. 38.6%), but less likely to have hypertension (65.6% vs. 79%) and hyperlipidaemia (61.1% vs. 65.5%), compared with stroke patients. In total 6.8% of the AMI patients had recurrent AMI, whereas 4.8% of the stroke patients had recurrent stroke within 1 year; 31.7% of the AMI patients died, whereas 17.1% of the ischaemic stroke patients died within 1 year. Older age, Malay ethnicity, and diabetes mellitus were statistically significant risk factors for all-cause mortality and for the composite endpoint of AMI, stroke, and all-cause mortality, at 1 year.

Conclusions

Risk profiles of patients with AMI and stroke are significantly different. Patients suffer recurrent events in vascular territories similar to the index event. Age and diabetes mellitus are significant predictors of recurrent vascular events and mortality.

Effects of external inspection on sepsis detection and treatment: a study protocol for a quasiexperimental study with a stepped-wedge design

INTRODUCTION

Inspections are widely used in health care as a means to improve the health services delivered to patients. Despite their widespread use, there is little evidence of their effect. The mechanisms for how inspections can promote change are poorly understood. In this study, we use a national inspection campaign of sepsis detection and initial treatment in hospitals as case to: (1) Explore how inspections affect the involved organizations. (2) Evaluate what effect external inspections have on the process of delivering care to patients, measured by change in indicators reflecting how sepsis detection and treatment is carried out. (3) Evaluate whether external inspections affect patient outcomes, measured as change in the 30-day mortality rate and length of hospital stay.

METHODS AND ANALYSIS

The intervention that we study is inspections of sepsis detection and treatment in hospitals. The intervention will be rolled out sequentially during 12 months to 24 hospitals. Our effect measures are change on indicators related to the detection and treatment of sepsis, the 30-day mortality rate and length of hospital stay. We collect data from patient records at baseline, before the inspections, and at 8 and 14 months after the inspections. We use logistic regression models and linear regression models to compare the various effect measurements between the intervention and control periods. All the models will include time as a covariate to adjust for potential secular changes in the effect measurements during the study period. We collect qualitative data before and after the inspections, and we will conduct a thematic content analysis to explore how inspections affect the involved organisations.

ETHICS AND DISSEMINATION

The study has obtained ethical approval by the Regional Ethics Committee of Norway Nord and the Norwegian Data Protection Authority. It is registered at www.clinicaltrials.gov (Identifier: NCT02747121). Results will be reported in international peer-reviewed journals.

TRIAL REGISTRATION

NCT02747121; Pre-results.

Nurses' reports of staffing adequacy and surgical site infections: A cross-sectional multi-centre study

BACKGROUND

It is indicated that healthcare personnel's perceptions of the work environment may reflect the clinical outcomes for the patients they care for. However, the body of evidence is inconsistent when it comes to the association between work environment and surgical site infection.

OBJECTIVES

The aim of this study is to examine the associations between nurse-reported characteristics of the work environment and incidence of surgical site infections after total hip arthroplasty.

DESIGN AND SETTINGS

This is a cross-sectional multicentre study conducted in 16 Norwegian hospitals.

PARTICIPANTS

Clinical outcomes for 2885 patients >18years that underwent total hip arthroplasty are combined with work environment descriptions from 320 nurses.

MATERIALS AND METHODS

We combine data about surgical site infections from The Norwegian Surveillance System for Antibiotic Consumption and Healthcare-Associated Infections and hospital characteristics such as overall survival probability (from administrative patient data) and nurses' reports of characteristics of the work environment (from a multicentre survey among nurses in Norwegian hospitals). Stepwise mixed-effects logistic regression model was performed to examine the associations between characteristics of the work environment and surgical site infections.

RESULTS

The incidence of surgical site infection among 2885 patients undergoing total hip arthroplasty in 16 Norwegian hospitals was 2.6%. Older age, elective procedures and high scores for staffing adequacy were associated with risk for surgical site infection. The association between high scores for adequate staffing and low risk for surgical site infections was present for patients that were admitted for an elective procedure, but not for patients admitted for a non-elective procedure.

CONCLUSION

Our results show that the risk of surgical site infections after elective total hip arthroplasty was lower in hospitals where nurses assessed staffing as adequate. Our findings add to the existing literature that examines the linkage between work environment and clinical outcomes.

In Hospital and 3-Month Mortality and Functional Recovery Rate in Patients Treated for Hip Fracture by a Multidisciplinary Team

Objectives

Medical comorbidities affect outcome in elderly patients with hip fracture. This study was designed to preliminarily evaluate the usefulness of a hip-fracture unit led by an internal medicine specialist.

Methods

In-hospital and 3-month outcomes in patients with hip fracture were prospectively evaluated in 121 consecutive patients assessed before and followed after surgery by a multidisciplinary team led by internal medicine specialist; 337 consecutive patients were recalled from ICD-9 discharge records and considered for comparison regarding in-hospital mortality.

Results

In the intervention period, patients treated within 48 hours were 54% vs. 26% in the historical cohort (P<0.0001). In-hospital mortality remained stable at about 2.3 per 1000 person-days. At 3 months, 10.3% of discharged patients had died, though less than 8% of patients developed postoperative complications (mainly pneumonia and respiratory failure). The presence of more than 2 major comorbidities and the loss of 3 or more BADL were independent predictors of death. 50/105 patients recovered previous functional capacity, but no independent predictor of functional recovery could be identified. Mean length of hospital stay significantly decreased in comparison to the historical cohort (13.6± 4.7 vs 17 ± 5 days, p = 0.0001). Combined end-point of mortality and length of hospitalization < 12 days was significantly lower in study period (27 vs 34%, p <0.0132).

Conclusions

Identification and stabilization of concomitant clinical problems by internal medicine specialists may safely decrease time to surgery in frail subjects with hip fracture. Moreover, integrated perioperative clinical management may shorten hospital stay with no apparent increase in in-hospital mortality and ultimately improve the outcome. These results are to be confirmed by a larger study presently ongoing at our institution.

Variation between Hospitals with Regard to Diagnostic Practice, Coding Accuracy, and Case-Mix. A Retrospective Validation Study of Administrative Data versus Medical Records for Estimating 30-Day Mortality after Hip Fracture

BACKGROUND

The purpose of this study was to assess the validity of patient administrative data (PAS) for calculating 30-day mortality after hip fracture as a quality indicator, by a retrospective study of medical records.

METHODS

We used PAS data from all Norwegian hospitals (2005-2009), merged with vital status from the National Registry, to calculate 30-day case-mix adjusted mortality for each hospital (n = 51). We used stratified sampling to establish a representative sample of both hospitals and cases. The hospitals were stratified according to high, low and medium mortality of which 4, 3, and 5 hospitals were sampled, respectively. Within hospitals, cases were sampled stratified according to year of admission, age, length of stay, and vital 30-day status (alive/dead). The final study sample included 1043 cases from 11 hospitals. Clinical information was abstracted from the medical records. Diagnostic and clinical information from the medical records and PAS were used to define definite and probable hip fracture. We used logistic regression analysis in order to estimate systematic between-hospital variation in unmeasured confounding. Finally, to study the consequences of unmeasured confounding for identifying mortality outlier hospitals, a sensitivity analysis was performed.

RESULTS

The estimated overall positive predictive value was 95.9% for definite and 99.7% for definite or probable hip fracture, with no statistically significant differences between hospitals. The standard deviation of the additional, systematic hospital bias in mortality estimates was 0.044 on the logistic scale. The effect of unmeasured confounding on outlier detection was small to moderate, noticeable only for large hospital volumes.

CONCLUSIONS

This study showed that PAS data are adequate for identifying cases of hip fracture, and the effect of unmeasured case mix variation was small. In conclusion, PAS data are adequate for calculating 30-day mortality after hip-fracture as a quality indicator in Norway.

Demographic factors in hip fracture incidence and mortality rates in California, 2000-2011

Background

Hip fractures result in both health and cost burdens from a public health perspective and have a major impact on the health care system in the USA. The purpose was to examine whether there were systematic differences in hip fracture incidence and 30-, 90-, and 365-day mortality after hip fracture in the California population as a function of age, gender, and race/ethnicity from 2000–2011.

Methods

This was a population-based study from 2000 to 2011 using data from the California Office of Statewide Health and Planning and Development (OSHPD, N = 317,677), California State Death Statistical Master File records (N = 224,899), and the US Census 2000 and 2010. There were a total of 317,677 hospital admissions for hip fractures over the 12-year span and 24,899 deaths following hip fractures. All participants without linkage (substituted for social security) numbers were excluded from mortality rate calculations. Variation in incidence and mortality rates across time, gender, race/ethnicity, and age were assessed using Poisson regression models. Odds ratio and 95 % confidence intervals are provided.

Results

The incidence rate of hip fractures decreased between 2000 and 2011 (odds ratio (OR) = 0.98, 95 % confidence interval (CI) 0.98, 0.98). Mortality rates also decreased over time. There were gender, race/ethnicity, and age group differences in both incidence and mortality rates.

Conclusions

Males were half as likely to sustain a hip fracture, but their mortality within a year of the procedure is almost twice the rate than women. As age increased, the prevalence of hip fracture increased dramatically, but mortality did not increase as steeply. Caucasians were more likely to sustain a hip fracture and to die within 1 year after a hip fracture. The disparities in subpopulations will allow for targeted population interventions and opportunities for further research.

[Quality assurance with administrative data (QSR): follow-up in quality measurement - an analysis of patient records]

The present study analyses the information gain obtained by evaluating adverse events during follow-up compared to the sole analysis of events during the initial hospital stay for quality measurement purposes. The analysis is based on AOK administrative data from the years 2010 to 2012. The analyses were carried out for 10 quality indicators from the 4 QSR sectors knee replacement for osteoarthritis, appendectomy, prostate surgery for benign prostatic syndrome (BPS) and therapeutic cardiac catheterization (PCI) in patients with myocardial infarction. A total of 409,774 AOK cases were included. For almost all indicators considered, a relevant share of complications can be found to have occurred only after discharge from the initial hospitalization (7.7 %-92.6 %). Furthermore, there is only a weak connection between the findings from the first hospitalization and those from the follow-up period (0.0449 < r < 0.1935). 26-66 % of the hospitals will be classified differently based on Standardized Mortality/Morbidity Ratio (SMR) quartiles if follow-up events are included in the quality assessment (with the exception of "Other Complications after PCI" of 14 %). In summary, quality assessment is improved considerably by evaluating the follow-up period for almost all indicators considered. A quality measurement based solely on events in the initial hospital stay obscures relevant adverse events that have an impact on a comparative hospital quality assessment for these indicators.

Variations in the Quality of Care at Large Public Hospitals in Beijing, China: A Condition-Based Outcome Approach

Background

Public hospitals deliver over ninety percent of all outpatient and inpatient services in China. Their quality is graded into three levels (A, B, and C) largely based on structural resources, but empirical evidence on the quality of process and outcome of care is extremely scarce. As expectations for quality care rise with higher living standards and cost of care, such evidence is urgently needed and vital to improve care and to inform future health reforms.

Methods

We compiled and analyzed a multicenter database of over 4 million inpatient discharge summary records to provide a comprehensive assessment of the level and variations in clinical outcomes of hospitalization at 39 tertiary hospitals in Beijing. We assessed six outcome measures of clinical quality: in-hospital mortality rates (RSMR) for AMI, stroke, pneumonia and CABG, post-procedural complication rate (RS-CR), and failure-to-rescue rate (RS-FTR). The measures were adjusted for pre-admission patient case-mix using indirect standardization method with hierarchical linear mixed models.

Results

We found good overall quality with large variations by hospital and condition (mean/range, in %): RSMR-AMI: 6.23 (2.37–14.48), RSMR-stroke: 4.18 (3.58–4.44), RSMR-pneumonia: 7.78 (7.20–8.59), RSMR-CABG: 1.93 (1.55–2.23), RS-CR: 11.38 (9.9–12.88), and RS-FTR: 6.41 (5.17–7.58). Hospital grade was not significantly associated with any risk-adjusted outcome measures.

Conclusions

Going to a higher grade public hospital does not always lead to better patient outcome because hospital grade only contains information about hospital structural resources. A hospital report card with some outcome measures of quality would provide valuable information to patients in choosing providers, and for regulators to identify gaps in health care quality. Reducing the variations in clinical practice and patient outcome should be a focus for policy makers in the next round of health sector reforms in China.

30-Day Survival Probabilities as a Quality Indicator for Norwegian Hospitals: Data Management and Analysis

Background

The Norwegian Knowledge Centre for the Health Services (NOKC) reports 30-day survival as a quality indicator for Norwegian hospitals. The indicators have been published annually since 2011 on the website of the Norwegian Directorate of Health (www.helsenorge.no), as part of the Norwegian Quality Indicator System authorized by the Ministry of Health. Openness regarding calculation of quality indicators is important, as it provides the opportunity to critically review and discuss the method. The purpose of this article is to describe the data collection, data pre-processing, and data analyses, as carried out by NOKC, for the calculation of 30-day risk-adjusted survival probability as a quality indicator.

Methods and Findings

Three diagnosis-specific 30-day survival indicators (first time acute myocardial infarction (AMI), stroke and hip fracture) are estimated based on all-cause deaths, occurring in-hospital or out-of-hospital, within 30 days counting from the first day of hospitalization. Furthermore, a hospital-wide (i.e. overall) 30-day survival indicator is calculated. Patient administrative data from all Norwegian hospitals and information from the Norwegian Population Register are retrieved annually, and linked to datasets for previous years. The outcome (alive/death within 30 days) is attributed to every hospital by the fraction of time spent in each hospital. A logistic regression followed by a hierarchical Bayesian analysis is used for the estimation of risk-adjusted survival probabilities. A multiple testing procedure with a false discovery rate of 5% is used to identify hospitals, hospital trusts and regional health authorities with significantly higher/lower survival than the reference. In addition, estimated risk-adjusted survival probabilities are published per hospital, hospital trust and regional health authority. The variation in risk-adjusted survival probabilities across hospitals for AMI shows a decreasing trend over time: estimated survival probabilities for AMI in 2011 varied from 80.6% (in the hospital with lowest estimated survival) to 91.7% (in the hospital with highest estimated survival), whereas it ranged from 83.8% to 91.2% in 2013.

Conclusions

Since 2011, several hospitals and hospital trusts have initiated quality improvement projects, and some of the hospitals have improved the survival over these years. Public reporting of survival/mortality indicators are increasingly being used as quality measures of health care systems. Openness regarding the methods used to calculate the indicators are important, as it provides the opportunity of critically reviewing and discussing the methods in the literature. In this way, the methods employed for establishing the indicators may be improved.

Survival curves to support quality improvement in hospitals with excess 30-day mortality after acute myocardial infarction, cerebral stroke and hip fracture: a before-after study

OBJECTIVES

To evaluate survival curves (Kaplan-Meier) as a means of identifying areas in the clinical pathway amenable to quality improvement.

DESIGN

Observational before-after study.

SETTING

In Norway, annual public reporting of nationwide 30-day in-and-out-of-hospital mortality (30D) for three medical conditions started in 2011: first time acute myocardial infarction (AMI), stroke and hip fracture; reported for 2009. 12 of 61 hospitals had statistically significant lower/higher mortality compared with the hospital mean.

PARTICIPANTS

Three hospitals with significantly higher mortality requested detailed analyses for quality improvement purposes: Telemark Hospital Trust Skien (AMI and stroke), Østfold Hospital Trust Fredrikstad (stroke), Innlandet Hospital Trust Gjøvik (hip fracture).

OUTCOME MEASURES

Survival curves, crude and risk-adjusted 30D before (2008-2009) and after (2012-2013).

INTERVENTIONS

Unadjusted survival curves for the outlier hospitals were compared to curves based on pooled data from the other hospitals for the 30-day period 2008-2009. For patients admitted with AMI (Skien), stroke (Fredrikstad) and hip fracture (Gjøvik), the curves suggested increased mortality from the initial part of the clinical pathway. For stroke (Skien), increased mortality appeared after about 8 days. The curve profiles were thought to reflect suboptimal care in various phases in the clinical pathway. This informed improvement efforts.

RESULTS

For 2008-2009, hospital-specific curves differed from other hospitals: borderline significant for AMI (p=0.064), highly significant (p≤0.005) for the remainder. After intervention, no difference was found (p>0.188). Before-after comparison of the curves within each hospital revealed a significant change for Fredrikstad (p=0.006). For the three hospitals, crude 30D declined and they were non-outliers for risk-adjusted 30D for 2013.

CONCLUSIONS

Survival curves as a supplement to 30D may be useful for identifying suboptimal care in the clinical pathway, and thus informing design of quality improvement projects.

Use of electronic health records to ascertain, validate and phenotype acute myocardial infarction: A systematic review and recommendations

Electronic health records (EHRs) offer the opportunity to ascertain clinical outcomes at large scale and low cost, thus facilitating cohort studies, quality of care research and clinical trials. For acute myocardial infarction (AMI) the extent to which different EHR sources are accessible and accurate remains uncertain. Using MEDLINE and EMBASE we identified thirty three studies, reporting a total of 128658 patients, published between January 2000 and July 2014 that permitted assessment of the validity of AMI diagnosis drawn from EHR sources against a reference such as manual chart review. In contrast to clinical practice, only one study used EHR-derived markers of myocardial necrosis to identify possible AMI cases, none used electrocardiogram findings and one used symptoms in the form of free text combined with coded diagnosis. The remaining studies relied mostly on coded diagnosis. Thirty one studies reported positive predictive value (PPV)≥ 70% between AMI diagnosis from both secondary care and primary care EHRs and the reference. Among fifteen studies reporting EHR-derived AMI phenotypes, three cross-referenced ST-segment elevation AMI diagnosis (PPV range 71-100%), two non-ST-segment elevation AMI (PPV 91.0, 92.1%), three non-fatal AMI (PPV range 82-92.2%) and six fatal AMI (PPV range 64-91.7%). Clinical coding of EHR-derived AMI diagnosis in primary care and secondary care was found to be accurate in different clinical settings and for different phenotypes. However, markers of myocardial necrosis, ECG and symptoms, the cornerstones of a clinical diagnosis, are underutilised and remain a challenge to retrieve from EHRs.

Hypothermia and low body temperature are common and associated with high mortality in hip fracture patients

Hip fractures remain one of the commonest injuries treated by orthopaedic surgeons. Despite recent initiatives, the fracture engenders a very high mortality. The UK National Hip Fracture Database reports a 30-day mortality of 8%. The pathophysiology that results in such high mortality remains imperfectly understood. The significance of thermal dysregulation in polytrauma is becoming increasingly recognised. Hypothermia is a common feature of polytrauma and is associated with adverse outcomes. No previous studies have explored the prevalence and outcomes of hip fracture patients with hypothermia and/or low body temperature. We sought to evaluate this. We prospectively collected the demographic details and admission tympanic temperature of all patients presenting to our institution with hip fracture. Patient mortality was also recorded. Seven hundred and eighty-one patients were included. The mean age was 80 years. 38% (300) had a temperature below 36.5°C. 4% (30) presented with a tympanic temperature greater than 37.5°C. The 30-day mortality for patients with a normal admission temperature (between 36.5° and 37.5°C) was 5.1%. This value was 15.3% for those whose admission temperature was less than 36.5°C (p<0.0001). Correcting for potential confounders of age and gender, those with an admission temperature of less than 36.5°C had a 2.8 fold increase in the odds of mortality at 30-days compared with those with an admission temperature of between 36.5° and 37.5°C (p<0.0005). Low body temperature is strongly linked to 30-day mortality in hip fracture patients.

An observational study: associations between nurse-reported hospital characteristics and estimated 30-day survival probabilities

Background

There is a growing body of evidence for associations between the work environment and patient outcomes. A good work environment may maximise healthcare workers’ efforts to avoid failures and to facilitate quality care that is focused on patient safety. Several studies use nurse-reported quality measures, but it is uncertain whether these outcomes are correlated with clinical outcomes. The aim of this study was to determine the correlations between hospital-aggregated, nurse-assessed quality and safety, and estimated probabilities for 30-day survival in and out of hospital.

Methods

In a multicentre study involving almost all Norwegian hospitals with more than 85 beds (sample size=30, information about nurses’ perceptions of organisational characteristics were collected. Subscales from this survey were used to describe properties of the organisations: quality system, patient safety management, nurse–physician relationship, staffing adequacy, quality of nursing and patient safety. The average scores for these organisational characteristics were aggregated to hospital level, and merged with estimated probabilities for 30-day survival in and out of hospital (survival probabilities) from a national database. In this observational, ecological study, the relationships between the organisational characteristics (independent variables) and clinical outcomes (survival probabilities) were examined.

Results

Survival probabilities were correlated with nurse-assessed quality of nursing. Furthermore, the subjective perception of staffing adequacy was correlated with overall survival.

Conclusions

This study showed that perceived staffing adequacy and nurses’ assessments of quality of nursing were correlated with survival probabilities. It is suggested that the way nurses characterise the microsystems they belong to, also reflects the general performance of hospitals.

Patients' preferences for osteoporosis drug treatment: a discrete-choice experiment

Introduction

The patient’s perspective is becoming increasingly important in clinical and policy decisions. In this study, we aimed to evaluate the preferences of patients with, or at risk of, osteoporosis for medication attributes, and to establish how patients trade between these attributes.

Methods

A discrete choice experiment survey was designed and patients were asked to choose between two hypothetical unlabelled drug treatments (and an opt-out option) that vary in five attributes: efficacy in reducing the risk of fracture, type of potential common side-effects, mode and frequency of administration and out-of-pocket costs. An efficient experimental design was used to construct the treatment option choice sets and a mixed logit panel data model was used to estimate patients’ preferences and trade-offs between attributes.

Results

A total of 257 patients with, or at risk of, osteoporosis completed the experiment. As expected, patients preferred treatment with higher effectiveness and lower cost. They also preferred either an oral monthly tablet or 6-month subcutaneous injection above weekly oral tablets, 3-month subcutaneous, 3-month intravenous or yearly intravenous injections. Patients disliked being at risk of gastro-intestinal disorders more than being at risk of skin reactions and flu-like symptoms. There was significant variation in preferences across the sample for all attributes except subcutaneous injection.

Conclusions

This study revealed that osteoporotic patients preferred 6-month subcutaneous injection and oral monthly tablet, and disliked gastro-intestinal disorders. Moreover, patients were willing to pay a personal contribution or to trade treatment efficacy for better levels of other attributes. Preferences for treatment attributes varied across patients and this highlights the importance of clinical decision-making taking individual preferences into account to improve osteoporosis care.