Palliative care coding practices in Canada since the introduction of guidelines and the HSMR indicator

Fekri, Omid; Amuah, Joseph E.; Herasimovich, Viachaslau; Chaudhary, Zeerak; Leeb, Kira; Gurevich, Yana

doi:10.1136/bmjopen-2015-008753

Cited by 5 publications

(5 citation statements)

References 7 publications

(8 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In Canada, where HSMR findings are publicly reported nationwide since 2007,3 a 22% decrease in HSMR was observed between years 2006 and 2007 and 2012 and 2013. In the same period, crude mortality declined from 8.7% to 7.3% 4. Similar observations were made in other countries 5–7…”

Section: Introductionsupporting

confidence: 83%

“…All authors from the above-mentioned studies fairly concluded that these decreases might reflect improvements in the quality of care, but at least in some part could be explained by changes in coding whether or not reflecting adverse behaviour to manipulate the system. For example, in countries like Canada4 8 and the UK9 where palliative coding is accounted for in the HSMR modelling, frequency of palliative care coding has been reported to be increasing over time. The HSMR methodology and the publication of HSMR in the form of league tables10 or in formats that intuitively make the user compare individual hospitals have been extensively criticised 11–13.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Standardised mortality ratios as a user-friendly performance metric and trigger for quality improvement in a Flemish hospital network: multicentre retrospective study

Tambeur¹,

Stijnen²,

Boer³

et al. 2019

BMJ Open

View full text Add to dashboard Cite

ObjectiveTo illustrate the development and use of standardised mortality rates (SMRs) as a trigger for quality improvement in a network of 27 hospitals.DesignThis research was a retrospective observational study. The primary outcome was in-hospital mortality. SMRs were calculated for All Patient Refined—Diagnosis-Related Groups (APR-DRGs) that reflect 80% of the Flemish hospital network mortality. Hospital mortality was modelled using logistic regression. The metrics were communicated to the member hospitals using a custom-made R-Shiny web application showing results at the level of the hospital, patient groups and individual patients. Experiences with the metric and strategies for improvement were shared in chief medical officer meetings organised by the Flemish hospital network.Setting27 Belgian hospitals.Participants1 198 717 hospital admissions for registration years 2009–2016.ResultsPatient gender, age, comorbidity as well as admission source and type were important predictors of mortality. Altogether the SMR models had a C-statistic of 88%, indicating good discriminatory capability. Seven out of ten APR-DRGs with the highest percentage of hospitals statistically significantly deviating from the benchmark involved malignancy. The custom-built web application and the trusted environment of the Flemish hospital network created an interoperable strategy to get to work with SMR findings. Use of the web application increased over time, with peaks before and after key discussion meetings within the Flemish hospital network. A concomitant reduction in crude mortality for the selected APR-DRGs from 6.7% in 2009 to 5.9% in 2016 was observed.ConclusionsThis study reported on the phased approach for introducing SMR reporting to trigger quality improvement. Prerequisites for the successful use of quality metrics in hospital benchmarks are a collaborative approach based on trust among the participants and a reporting platform that allows stakeholders to interpret and analyse the results at multiple levels.

show abstract

Section: Introductionsupporting

confidence: 83%

Section: Introductionmentioning

confidence: 99%

Standardised mortality ratios as a user-friendly performance metric and trigger for quality improvement in a Flemish hospital network: multicentre retrospective study

Tambeur¹,

Stijnen²,

Boer³

et al. 2019

BMJ Open

View full text Add to dashboard Cite

show abstract

“…Clearly, patients admitted palliatively or treated on the end-of-life pathway are inherently more likely to die in hospital, regardless of the quality of hospital care. In 2004, the PC specialty code Z515 was introduced and was found to have a modest impact on HSMR 33. In our review, 16 patients were treated palliatively but none of them were PC coded.…”

Section: Resultsmentioning

confidence: 94%

A hundred heart failure deaths: lessons learnt from the Dr Foster heart failure hospital mortality alert

et al. 2019

View full text Add to dashboard Cite

BackgroundDespite advances in evidence-based pharmacotherapy, the latest National Heart Failure Audit (NHFA) has shown that in-hospital mortality of heart failure (HF) remains high with large interhospital variations. University Hospitals Coventry & Warwickshire, a tertiary cardiac centre, received a mortality alert of excess HF deaths based on a high Dr Foster hospital standardised mortality ratio (HSMR). This conflicted with our local NHFA data which showed lower than national average mortality rates.ObjectiveTo review various systemic and individual processes of care in patients admitted with HF and examine the validity of HSMR in HF.Design, setting, patientsA retrospective case note analysis was performed on a random sample of 100 HF deaths identified by Dr Foster from 2010 to 2016.MeasuresCase record reviews were performed on the following aspects of care: admission to appropriate wards, resuscitation status, palliative care input and National Confidential Enquiry into Patient Outcome and Death classification. Primary diagnosis coding, diagnostic accuracy and actual causes of death were examined to assess limitations of HSMR.ResultsDespite evidence of lower mortality on cardiology wards, only 28% of patients with acute HF were admitted to a cardiology-ward. Sixty four per cent were considered palliative but only 4.6% were referred to palliative care. The Do Not Attempt Resuscitation order was appropriate in 91% patients but only 74% had this in place. The primary diagnosis of HF was incorrectly coded in 34% while three cases were misdiagnosed.ConclusionHF may be coded as a cause of death in some cases where the cause is uncertain and misdiagnosed. Although HSMR has many limitations, it is a smoke alarm that should not be ignored.

show abstract

“…This secondary analysis of CIHI's hospital performance reporting shows that in-hospital mortality-indicators of hospital deaths (HSMR) and hospital deaths following major surgery-has significantly declined in Canada, which has been shown elsewhere. 20 Conversely, national rates of hospital readmission showed slight increases over time (but mostly non-statistically significant in trend analysis). Moreover, hospital readmission accounted for the majority of instances of weakening hospital performance.…”

Section: Discussionmentioning

confidence: 95%

Appropriateness, effectiveness and safety of care delivered in Canadian hospitals: a longitudinal assessment on the utility of publicly reported performance trend data between 2012–2013 and 2016–2017

2020

Self Cite

View full text Add to dashboard Cite

ObjectivesTo assess the utility of publicly reported performance trend results of Canadian hospitals (by hospital size/type and jurisdiction).DesignLongitudinal observational study.Setting489 hospitals in Canada between fiscal years 2012–2013 and 2016–2017.ParticipantsAnalysis focused on indicator results of individual Canadian hospitals.Primary and secondary outcomesEight outcome indicators of hospital performance: in-hospital mortality (2), readmissions (4) and adverse events (2). Performance trend outcomes of improving, weakening or no change over time. Comparators in performance by hospital size/type of above, below or same as average.ResultsAt the national level, between 2012–2013 and 2016–2017, Canadian hospitals largely reduced in-hospital mortality: hospital deaths (hospital standardised mortality ratio) −9%; hospital deaths following major surgery −11.1%. Conversely, readmission to hospital increased nationwide: medical 1.5%; obstetric 5%; patients aged 19 years and younger 4.6% and surgical 3%. In-hospital sepsis declined −7.1%. Approximately 10% of the 489 hospitals in this study had a trend of improving performance over time (n=49) in one or more indicators, and a similar number showed a weakening performance over time (n=52). Roughly half of the hospitals in this study (n=224) had no change in performance over time for at least four out of the eight indicators. No single hospital had an improving or weakening trend in more than two indicators. Teaching and larger-sized hospitals showed a higher ratio of improving performance compared with smaller-sized hospitals.ConclusionsAnalysis of Canadian hospital performance through eight indicators shows improvement of in-hospital mortality and in-hospital sepsis, but rising rates of readmissions. Subdividing the analysis by hospital size/type shows greater instances of improvement in teaching and larger-sized hospitals. There is no clear pattern of a particular province/territory with a significant number of hospitals with improving or weakening trends. The overall assessment of trends of improving and weakening as presented in this study can be used more systematically in monitoring progress.

show abstract

Palliative care coding practices in Canada since the introduction of guidelines and the HSMR indicator

Cited by 5 publications

References 7 publications

Standardised mortality ratios as a user-friendly performance metric and trigger for quality improvement in a Flemish hospital network: multicentre retrospective study

Standardised mortality ratios as a user-friendly performance metric and trigger for quality improvement in a Flemish hospital network: multicentre retrospective study

A hundred heart failure deaths: lessons learnt from the Dr Foster heart failure hospital mortality alert

Appropriateness, effectiveness and safety of care delivered in Canadian hospitals: a longitudinal assessment on the utility of publicly reported performance trend data between 2012–2013 and 2016–2017

Contact Info

Product

Resources

About