2006
DOI: 10.1177/014107680609900818
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Identifying Patients at High Risk of Emergency Hospital Admissions: A Logistic Regression Analysis

Abstract: Routine hospital episode statistics can be used to identify patients who are at high risk of suffering future multiple emergency hospital admissions. The potential cost savings in preventing a proportion of these subsequent admissions need to be compared with the costs of case management of these patients.

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Cited by 76 publications
(82 citation statements)
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“…Conditions contributing to admission included: significant co-morbidities in 95 patients (≥2 in 57, ≥4 co-morbidities in 24); palliative care (9); mental health disorders (3); dependency (30) and poor compliance (6). Only 14 admission were directly due to diabetes: hypoglycaemia (5); hyperglycaemia (6); DKA (2), infected foot ulcer (1).…”
Section: Resultsmentioning
confidence: 99%
“…Conditions contributing to admission included: significant co-morbidities in 95 patients (≥2 in 57, ≥4 co-morbidities in 24); palliative care (9); mental health disorders (3); dependency (30) and poor compliance (6). Only 14 admission were directly due to diabetes: hypoglycaemia (5); hyperglycaemia (6); DKA (2), infected foot ulcer (1).…”
Section: Resultsmentioning
confidence: 99%
“…Reasons for patient returns to the ED and predictors of future return for both hospital readmissions and repeated ED visits have been investigated primarily through use of administrative data, and a number of factors associated with increased rate of ED return have been identified. [5][6][7][8][9][10][11][12][13][14][15][16] These factors include patient descriptors such as older age, lack of family support, nonambulatory status, and arrival to the ED by ambulance. It is not clear, however, whether any of these factors are actually in the causal pathway of patient returns and to what extent they represent modifiable risk factors for intervention.…”
Section: Introduction Backgroundmentioning
confidence: 99%
“…Although the PIVOT study did not demonstrate a significant association between comorbidity and mortality at a median of 10 years, the results of the current study suggest that comorbidity does predict subsequent morbidity as reflected by nonelective hospital admissions. 9,10 Therefore, we suggest that incorporating an accurate comorbidity assessment into candidate selection may not only be useful at the time of treatment but should be considered even earlier in the decision-making process for PSA screening and prostate biopsy.…”
Section: Discussionmentioning
confidence: 99%
“…Acute hospital admission was used as a surrogate metric for the patient’s overall health status. 9,10 In particular, we believe comorbidity assessment before prostate biopsy may be helpful in deciding whether to perform a prostate biopsy.…”
Section: Introductionmentioning
confidence: 99%