Hospital Mortality Rates

6. QUALITY AND OUTCOMES OF CARE Hospital mortality rates

Variations in acute myocardial infarction (AMI) 30-day case fatality rates at the national level are influenced The specific methodology used to calculate the by the level of within-country variation in rates across hospital case fatality rates presented here differs hospitals. Most OECD countries have established national from that used for the indicator “Mortality following hospital performance measurement and public reporting acute myocardial infarction” and is likely to vary programmes to monitor efforts to improve the cost, quality from the methods used by participating countries and access of hospital care. for national monitoring and reporting purposes. Key methodological choices include: unit of measurement, Figure 6.20 plots the AMI 30-day case fatality rates (where type of hospital, patient risk adjustment variables, the death occurs in the same hospital as the initial AMI selection of reference population, method of admission). Rates are presented according to the caseload standardisation and data issues. for each hospital and identifies where the rates are higher or lower than expected. While most hospitals have rates Different analytical methods can result in quite no different than expected, all countries (except Norway) different rates for and rankings of organisations and had at least one outlier hospital. countries, making direct comparison between rates problematic. The specific analytical method used here The total number of hospitals and proportion of hospitals is one of several valid options considered during the by number of AMI admissions varies across countries development work of the OECD. For more details on (Table 6.1). Countries with a large number of hospitals are the methodology used to calculate these indicators likely to have more outlier hospitals than countries with see Brownwood et al. (forthcoming). fewer hospitals. Figure 6.21 presents the differences in dispersion of AMI 30-day case fatality rates across hospitals Figure 6.20 is a funnel plot and reflects that the within countries. The interquartile range of rates within precision of indicator rates increases as the caseload countries varies markedly. For example, the difference increases. All rates within the 99.7% control limits between the upper and lower rates for Israel is 1.8 deaths are considered to be no different than expected, per 100 admissions, and 4.9 deaths per 100 admissions whereas those outside the 99.7% control limits are for Latvia (based on unlinked data). Using linked data, the considered higher or lower than expected. The results are slightly different, with Sweden rather than Israel reference population rate was calculated from pooled having the least within-country variation. data from selected countries and used to calculate the standardised rates. Figure 6.21 is a turnip plot Multiple factors contribute to variations in outcomes of that graphically represents the relative dispersion care including hospital structure, processes of care and of rates but does not give an indication of statistical organisational culture. Significant variation in adherence significance of the variations in rates. Countries are to guideline recommendations for cardiac care is observed ordered according to ascending level of dispersion across countries and within countries (OECD, 2015, p. 174). as measured by the interquartile range (between the In Sweden, a comprehensive national programme of 25th percentile and the 75th percentile) of rates. quality improvement that includes public reporting, rapid Hospitals with less than 50 AMI admissions were diffusion of technology, use of evidence-based practice and excluded from both figures to improve data reliability. a system of evaluating and reporting quality and outcomes of care is likely to have contributed to a reduced variation in hospital care of patients after an AMI (Chung et al., 2015, p. 7). References

Brownwood, I. et al. (forthcoming), “OECD Hospital Performance Project: Methodological Development Definition and comparability of International Measurement of Acute Myocardial Infraction 30-Day Mortality Rates at the Hospital Level”, The case-fatality rate measures the percentage of OECD Health Working Papers, OECD Publishing, Paris. people aged 45 and over who die within 30 days following admission to hospital for a specific acute Chung, S.C. et al. (2015), “Comparison of Hospital Variation condition. Rates based on unlinked data refer to in Acute Myocardial Infarction Care and Outcome situations where the death occurred in the same Between Sweden and United Kingdom: Population Based hospital as the initial admission. Rates based on linked Cohort Study Using Nationwide Clinical Registries”, data include all deaths irrespective of where they British Medical Journal, Vol. 351, http://doi.org/10.1136/ occur. While the linked data method is considered bmj.h3913. more robust, it requires a unique patient identifier to OECD (2015a), Cardiovascular Disease and Diabetes: Policies link the data across the relevant datasets, which is not for Better Health and Quality of Care, OECD Health available in all countries. Policy Studies, OECD Publishing, Paris, http://dx.doi. org/10.1787/9789264233010-en.

112 Health at a Glance 2017 © OECD 2017 6. QUALITY AND OUTCOMES OF CARE

Hospital mortality rates

6.20. Thirty-day mortality after admission to hospital for AMI based on linked data, 2013-2015 (or nearest years)

Within expected range Canada Denmark Finland Israel Italy Korea Latvia Norway Slovenia Sweden United Kingdom Reference population rate 99.7% Control limits Age, sex, co-morbidity standardised mortality rates per 100 admissions of adults aged 45 years and over 40

0 50 5501 0501 5502 0502 5503 0503 5504 0504 550 Number of AMI admissions, 2013-2015 (or nearest years)

Note: Each dot in the figure represents a single hospital, unless otherwise stated. Results for Canada do not include deaths outside of acute care hospitals. UK data are limited to England and is presented at trust-level (i.e. multiple hospitals). Source: OECD Hospital Performance Data Collection 2017. 12 http://dx.doi.org/10.1787/888933603716

Table 6.1. Number of hospitals by AMI admissions based on unlinked data, 2013-2015 (or nearest years)

AMI admissions CAN DNK FIN ISR IRE ITA KOR LVA NOR SVN SWE GBR

> 300 151 21 21 21 20 336 67 6 35 3 62 142

50-300 158 7 0 5 8 160 83 11 17 7 4 8

< 50 261 1 0 0 6 328 155 5 2 4 0 59

12 http://dx.doi.org/10.1787/888933606262

6.21. Thirty-day mortality after admission to hospital for AMI based on linked and unlinked data, 2013-2015 (or nearest years)

Based on unlinked data Based on linked data Age, sex, co-morbidity standardised mortality rates per 100 admissions of adults aged 45 years and over 40

Italy Israel Korea Latvia Finland Norway Canada Ireland Sweden Denmark Slovenia ited Kingdom Un

Note: The width of each line in the figure represents the number of hospitals (frequency) with the corresponding rate. Data for Canada not linked to death statistics. UK data are limited to England and presented at trust level (i.e. multiple hospitals). Ordered by inter quartile range of admission-based data. Rates based on linked data are also standardised for previous AMI. Source: OECD Hospital Performance Data Collection 2017. 12 http://dx.doi.org/10.1787/888933603735 Health at a Glance 2017 © OECD 2017 113 From: Health at a Glance 2017 OECD Indicators

Access the complete publication at: https://doi.org/10.1787/health_glance-2017-en

Please cite this chapter as:

OECD (2017), “Hospital mortality rates”, in Health at a Glance 2017: OECD Indicators, OECD Publishing, Paris.

DOI: https://doi.org/10.1787/health_glance-2017-35-en

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