Ranking Hospitals According to Acute Myocardial Infarction Mortality

Differences in Hospital Risk-standardized Mortality Rates for Acute Myocardial Infarction When Assessed Using Transferred and Nontransferred Patients

BACKGROUND

One in 5 patients with acute myocardial infarction (AMI) are transferred between hospitals. However, current hospital performance measures based on AMI mortality exclude these patients from the evaluation of referral hospitals.

OBJECTIVE

To determine the relationship between risk-standardized mortality for transferred and nontransferred patients at referral hospitals.

RESEARCH DESIGN

This is a retrospective cohort study.

SUBJECTS

Fee-for-service Medicare claims from 2011 for patients hospitalized with a primary diagnosis of AMI, at hospitals admitting at least 15 patients in transfer.

MEASURES

Hospital-specific risk-standardized 30-day mortality rates (RSMRs) for 2 groups of patients: those admitted through transfer from another hospital, and those natively admitted without a preceding or subsequent interhospital transfer.

RESULTS

There were 304 hospitals admitting at least 15 patients in transfer. These hospitals cared for 77,711 natively admitted patients (median, 254; interquartile range, 162-321), and 11,829 patients admitted in transfer (median, 26; interquartile range, 19-46). Risk-standardized mortality rates were higher for natively admitted patients than for those admitted in transfer (mean, 11.5%±1.2% vs. 7.2%±1.1%). There was weak correlation between hospital performance as assessed by RSMR for patients natively admitted versus those admitted in transfer (Pearson r=0.24, P<0.001); when performance was arrayed by quartile, 102 hospitals (33.6%) differed at least 2 quartiles of performance across the 2 patient groups.

CONCLUSIONS

For Medicare patients with AMI, hospital-specific RSMRs for natively admitted patients are only weakly associated with RSMRs for patients transferred in from another hospital. Current AMI performance metrics may fail to provide guidance about hospital quality for transferred patients.

Acute myocardial infarction hospital admissions and deaths in England: a national follow-back and follow-forward record-linkage study

BACKGROUND

Little information is available on how primary and comorbid acute myocardial infarction contribute to the mortality burden of acute myocardial infarction, the share of these deaths that occur during or after a hospital admission, and the reasons for hospital admission of those who died from acute myocardial infarction. Our aim was to fill in these gaps in the knowledge about deaths and hospital admissions due to acute myocardial infarction.

METHODS

We used individually linked national hospital admission and mortality data for England from 2006 to 2010 to identify all primary and comorbid diagnoses of acute myocardial infarction during hospital stay and their associated fatality rates (during or within 28 days of being in hospital). Data were obtained from the UK Small Area Health Statistics Unit and supplied by the Health and Social Care Information Centre (now NHS Digital) and the Office of National Statistics. We calculated event rates (reported as per 100 000 population for relevant age and sex groups) and case-fatality rate for primary acute myocardial infarction diagnosed during the first physician encounter or during subsequent encounters, and acute myocardial infarction diagnosed only as a comorbidity. We also calculated what proportion of deaths from acute myocardial infarction occurred in people who had been in hospital on or within the 28 days preceding death, and whether acute myocardial infarction was one of the recorded diagnoses in such admissions.

FINDINGS

Acute myocardial infarction was diagnosed in the first physician encounter in 307 496 (69%) of 446 744 admissions with a diagnosis of acute myocardial infarction, in the second or later physician encounter in 52 374 (12%) admissions, and recorded only as a comorbidity in 86 874 (19%) admissions. Patients with comorbid diagnoses of acute myocardial infarction had two to three times the case-fatality rate of patients in whom acute myocardial infarction was a primary diagnosis. 135 950 deaths were recorded as being caused by acute myocardial infarction as the underlying cause of death, of which 66 490 (49%) occurred in patients who were in hospital on the day of death or in the 28 days preceding death. AMI was the primary diagnosis in 32 695 (49%) of these 66 490 patients (27 678 [42%] diagnosed in the first physician encounter and 5017 [8%] in a second or subsequent encounter), was a comorbid diagnosis in 12 118 (18%), and was not mentioned at all in the remaining 21 677 (33%). The most common causes of admission in people who did not have an acute myocardial infarction diagnosis but went on to die of acute myocardial infarction as the underlying cause of death were other circulatory conditions (7566 [35%] of 21 677 deaths), symptomatic diagnoses including non-specific chest pain, dyspnoea and syncope (1368 [6%] deaths), and respiratory disorders (2662 [12%] deaths), mainly pneumonia and chronic obstructive airways disease.

INTERPRETATION

As many acute myocardial infarction deaths occurring within 28 days of being in hospital follow a non-acute myocardial infarction admission as follow an acute myocardial infarction admission. These people are often diagnosed with other circulatory disorders or symptoms of circulatory disturbance. Further investigation is needed to establish whether there are symptoms and information that can be used to predict the risk of a fatal acute myocardial infarction in such patients, which can contribute to reducing the mortality burden of acute myocardial infarction.

FUNDING

Wellcome Trust, Medical Research Council, Public Health England, National Institute for Health Research.

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

Background

Mortality is a widely used, but often criticised, quality indicator for hospitals. In many countries, mortality is calculated from in-hospital deaths, due to limited access to follow-up data on patients transferred between hospitals and on discharged patients. The objectives were to: i) summarize time, place and cause of death for first time acute myocardial infarction (AMI), stroke and hip fracture, ii) compare case-mix adjusted 30-day mortality measures based on in-hospital deaths and in-and-out-of hospital deaths, with and without patients transferred to other hospitals.

Methods

Norwegian hospital data within a 5-year period were merged with information from official registers. Mortality based on in-and-out-of-hospital deaths, weighted according to length of stay at each hospital for transferred patients (W30D), was compared to a) mortality based on in-and-out-of-hospital deaths excluding patients treated at two or more hospitals (S30D), and b) mortality based on in-hospital deaths (IH30D). Adjusted mortalities were estimated by logistic regression which, in addition to hospital, included age, sex and stage of disease. The hospitals were assigned outlier status according to the Z-values for hospitals in the models; low mortality: Z-values below the 5-percentile, high mortality: Z-values above the 95-percentile, medium mortality: remaining hospitals.

Results

The data included 48 048 AMI patients, 47 854 stroke patients and 40 142 hip fracture patients from 55, 59 and 58 hospitals, respectively. The overall relative frequencies of deaths within 30 days were 19.1% (AMI), 17.6% (stroke) and 7.8% (hip fracture). The cause of death diagnoses included the referral diagnosis for 73.8-89.6% of the deaths within 30 days. When comparing S30D versus W30D outlier status changed for 14.6% (AMI), 15.3% (stroke) and 36.2% (hip fracture) of the hospitals. For IH30D compared to W30D outlier status changed for 18.2% (AMI), 25.4% (stroke) and 27.6% (hip fracture) of the hospitals.

Conclusions

Mortality measures based on in-hospital deaths alone, or measures excluding admissions for transferred patients, can be misleading as indicators of hospital performance. We propose to attribute the outcome to all hospitals by fraction of time spent in each hospital for patients transferred between hospitals to reduce bias due to double counting or exclusion of hospital stays.

Mortality in Dutch hospitals: trends in time, place and cause of death after admission for myocardial infarction and stroke. An observational study

Background

Patterns in time, place and cause of death can have an important impact on calculated hospital mortality rates. Objective is to quantify these patterns following myocardial infarction and stroke admissions in Dutch hospitals during the period 1996–2003, and to compare trends in the commonly used 30-day in-hospital mortality rates with other types of mortality rates which use more extensive follow-up in time and place of death.

Methods

Discharge data for all Dutch admissions for index conditions (1996–2003) were linked to the death certification registry. Then, mortality rates within the first 30, 90 and 365 days following admissions were analyzed for deaths occurring within and outside hospitals.

Results

Most deaths within a year after admission occurred within 30 days (60–70%). No significant trends in this distribution of deaths over time were observed. Significant trends in the distribution over place of death were observed for both conditions. For myocardial infarction, the proportion of deaths after transfer to another hospital has doubled from 1996–2003. For stroke a significant rise of the proportion of deaths outside hospital was found. For MI the proportion of deaths attributed to a circulatory disease has significantly fallen ovtime. Seven types of hospital mortality indicators, different in scope and observation period, all show a drop of hospital mortality for both MI and stroke over the period 1996–2003. For stroke the observed absolute reduction in death rate increases for the first year after admission, for MI the observed drop in 365-day overall mortality almost equals the observed drop in 30-day in hospital mortality over 1996–2003.

Conclusion

Changes in the timing, place and causes of death following admissions for myocardial infarction and stroke have important implications for the definitions of in-hospital and post-admission mortality rates as measures of hospital performance. Although necessary for understanding mortality patterns over time, including within mortality rates deaths which occur outside hospitals and after longer periods following index admissions remain debatable and may not reflect actual hospital performance but probably mirrors transfer, efficiency, and other health care policies.

Hospital variation in use of secondary preventive medicine after discharge for first acute myocardial infarction during 1995-2004

OBJECTIVE

To examine temporal trends in hospital use of secondary preventive medicine after discharge for first acute myocardial infarction (AMI) in Denmark.

DESIGN

Observational study from national administrative databases of 60,339 patients who survived a first AMI at 73 acute-care hospitals during 1995-2004.

OUTCOME MEASURES

At least 1 prescription claim for angiotensin-converting enzyme (ACE) inhibitors, beta-blockers, or statins within 90 days of discharge for AMI.

FINDINGS

The odds ratios between hospitals in the highest and lowest deciles, adjusted for age, gender, period, income, comorbidity, concomitant, and prior pharmaceutical therapy, in 1995 were 8.5 [95% confidence interval (CI), 5.5-12.2] for beta-blockers, 3.0 (2.3-3.7) for ACE inhibitors, and 6.2 (4.1-8.8) for statins. By 2004, the hospital variation had decreased for beta-blockers (3.2; 2.3-4.0) and statins (4.2; 3.0-5.5) but had increased for ACE inhibitors (3.8; 2.7-4.9). All the changes over time were significant (P < 0.001). Geographical characteristics of the hospital explained 32% of the variation in use of beta-blockers in 2004 and 27% in 1995, 39% of the variation in use of ACE inhibitors in 2004 and 3% in 1995, and 29% of the variation in use of statins and 19% in 1995.

CONCLUSIONS

Hospital use of secondary preventive medicine after discharge for AMI varied substantially. Hospital variation in use of beta-blockers and statins decreased with time whereas variation in use of ACE inhibitors increased. This may be attributed to gradually better agreement for the use of beta-blockers and statins and lesser agreement for the use of ACE inhibitors.

The Effect of Referral and Transfer Patients on Hospital Funding in a Capitated Health Care Delivery System

OBJECTIVES

(1) To investigate whether inpatients referred or transferred between facilities result in increased financial loss compared with those admitted directly, in a health care delivery system funded by capitation methods. (2) To determine whether the higher cost of those patients transferred or referred is fairly compensated by a diagnosis-based risk adjustment system, and whether tertiary care facilities bear an unfair financial burden for such patients in a capitated financing environment.

METHODS

The study cohort included all Veterans Affairs (VA) beneficiaries who received inpatient care during fiscal year (FY) 2004. Referral was defined as an outpatient visit to 1 facility followed by an admission to another facility. Transfers were consecutive inpatient stays at different hospitals. We defined loss as cost minus the share of budget determined by a Diagnostic Cost Group-based allocation. Both t tests and linear regression were used to compare the effect on cost and loss for patients transferred or not and referred or not.

RESULTS

Mean loss to a facility for patients transferred in was 1231 dollars more than for those not transferred. Mean loss for referred patients was 3341 dollars more than for those not referred, controlling for disease burden. For tertiary hospitals, the difference in losses for transfer patients was less than for other hospitals but greater for referral patients.

CONCLUSIONS

Patients referred or transferred from other facilities are more costly than those who are not. The difference may not be compensated by a diagnosis-based allocation system. A capitated health care system may consider additional funding to cover the cost of such patients.

Certificate of Need Regulation and Cardiac Catheterization Appropriateness After Acute Myocardial Infarction

BACKGROUND

Certificate of need (CON) regulation was introduced to control healthcare costs and improve quality of care in part by limiting the number of facilities providing complex medical care. Our objective was to examine whether rates of appropriate cardiac catheterization after admission for acute myocardial infarction varied between states with and without CON regulation of cardiac catheterization.

METHODS AND RESULTS

We performed a retrospective analysis of chart-abstracted data for 137,279 Medicare patients admitted for acute myocardial infarction between 1994 and 1996 at 4179 US acute-care hospitals. Using 3-level hierarchical generalized linear modeling adjusted for patient sociodemographic and clinical characteristics and physician and hospital characteristics, we compared catheterization rates within 60 days of admission for states (and the District of Columbia) with (n=32) and without (n=19) CON regulation in the full cohort and stratified by catheterization appropriateness. Appropriateness was categorized as strongly, equivocally, or weakly indicated. We found CON regulation was associated with a borderline-significant lower rate of catheterization overall (45.8% versus 46.5%; adjusted risk ratio [RR] 0.91, 95% confidence interval 0.82 to 1.00, P=0.06). After stratification by appropriateness, CON regulation was not associated with a significantly lower rate of catheterization among 63,823 patients with strong indications (49.9% versus 50.3%; adjusted RR 0.94, 95% confidence interval 0.86 to 1.02, P=0.17). However, CON regulation was associated with significantly lower rates of catheterization among 65,077 patients with equivocal indication (45.0% versus 46.0%; adjusted RR 0.88, 95% confidence interval 0.78 to 1.00, P=0.05) and among 8379 patients with weak indications (19.8% versus 21.8%; adjusted RR 0.84, 95% confidence interval 0.71 to 0.98, P=0.04). Associations were weakened substantially after adjustment for hospital coronary artery bypass graft surgery or cardiac catheterization capability.

CONCLUSIONS

CON regulation was associated with modestly lower rates of equivocally and weakly indicated cardiac catheterization after admission for acute myocardial infarction, but no significant differences existed in rates of strongly indicated catheterization.

Measuring Performance For Treating Heart Attacks And Heart Failure: The Case For Outcomes Measurement

To complement the current process measures for treating patients with heart attacks and with heart failure, which target gaps in quality but do not capture patient outcomes, the Centers for Medicare and Medicaid Services (CMS) has proposed the public reporting of hospital-level thirty-day mortality for these conditions in 2007. We present the case for including measurements of outcomes in the assessment of hospital performance, focusing on the care of patients with heart attacks and with heart failure. Recent developments in the methodology and standards for outcomes measurement have laid the groundwork for incorporating outcomes into performance monitoring efforts for these conditions.