PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
November 17, 1990BMJ111 citationsOpen Access

Measuring readmission rates.

MCMike ChambersACAileen Clarke

Key Points

Key points are not available for this paper at this time.

Abstract

OBJECTIVE: To assess the feasibility of extracting data on readmissions and readmission rates from Körner data for use as health service indicators. DESIGN: Retrospective analysis of inpatient Körner data for January 1988 to April 1989. SETTING: Three districts in North East Thames region. MAIN OUTCOME MEASURES: Number of readmissions after index discharge for all acute specialties combined and by specialty (general medicine, general surgery, gynaecology, trauma and orthopaedics, and geriatrics); readmission rates at 28 days after index discharge; and rates standardised for age group and sex by specialty and by consultant. RESULTS: All specialties showed an early peak in number of admissions, which levelled off by 28 days. Readmission rates at 28 days were appreciably lower in surgical specialties than in medical specialties (for example, general surgery 4.1% v geriatric medicine 15.1%). They were related to age and sex of the patient. Rates standardised for these variables did not significantly differ by district. Likewise, significant differences in standardised rates were not obtained for consultants within a specialty in one district. CONCLUSIONS: Readmission rates may be measured with Körner data. The pattern of readmissions with time means that readmission rates should be measured at not more than 28 days after the index discharge; the rates require standardisation for age and sex. Annual comparisons of standardised rates may be made among districts for combinations of specialties; those among individual consultants or specialties are unlikely to be statistically valid.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Chambers et al. (1990) studied this question.

synapsesocial.com/papers/6a70e4872163a0a01bc51831https://doi.org/10.1136/bmj.301.6761.1134
Ask AI
Helpful
Bookmark
Share
View Full Paper