A critical analysis of discovery health's claims-based risk adjustment of mortality rates in South African private sector hospitals
S. Afr. med. j. (Online)
;
113(1): 13-16, 2023. tables
Article
in English
| AIM
| ID: biblio-1412820
ABSTRACT
In 2019, Discovery Health published a risk adjustment model to determine standardised mortality rates across South African private hospital systems, with the aim of contributing towards quality improvement in the private healthcare sector. However, the model suffers from limitations due to its design and its reliance on administrative data. The publication's aim of facilitating transparency is unfortunately undermined by shortcomings in reporting. When designing a risk prediction model, patient-proximate variables with a sound theoretical or proven association with the outcome of interest should be used. The addition of key condition-specific clinical data points at the time of hospital admission will dramatically improve model performance. Performance could be further improved by using summary risk prediction scores such as the EUROSCORE II for coronary artery bypass graft surgery or the GRACE risk score for acute coronary syndrome. In general, model reporting should conform to published reporting standards, and attempts should be made to test model validity by using sensitivity analyses. In particular, the limitations of machine learning prediction models should be understood, and these models should be appropriately developed, evaluated and reported.
Full text:
Available
Index:
AIM (Africa)
Main subject:
Hospital Mortality
/
Private Sector
/
Risk Adjustment
/
Quality Improvement
Type of study:
Etiology study
/
Practice guideline
/
Prognostic study
/
Risk factors
Limits:
Female
/
Humans
/
Male
Language:
English
Journal:
S. Afr. med. j. (Online)
Year:
2023
Type:
Article
Institution/Affiliation country:
Department of Health Research Methods, Evidence and Impact, Faculty of Health Sciences, McMaster University, Hamilton/CA
/
Netcare Ltd/ZA
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