Key result
Comorbidity, public insurance, longer stay, and extreme pediatric ages consistently track with unplanned readmission risk.
Why the study?
Evidence on risk factors associated with paediatric unplanned hospital readmissions needed to be synthesised.
Systematic Review
This review highlights the need for standardized measures of hospital discharge variables to develop valid risk prediction models for pediatric unplanned hospital readmissions.
Answers are grounded in this paper and cite their sources.
May guide targeted pediatric discharge planning; extends synthesis for standardized readmission prediction models.
OBJECTIVE: To synthesise evidence on risk factors associated with paediatric unplanned hospital readmissions (UHRs). DESIGN: Systematic review. DATA SOURCE: CINAHL, EMBASE (Ovid) and MEDLINE from 2000 to 2017. ELIGIBILITY CRITERIA: Studies published in English with full-text access and focused on paediatric All-cause, Surgical procedure and General medical condition related UHRs were included. DATA EXTRACTION AND SYNTHESIS: Characteristics of the included studies, examined variables and the statistically significant risk factors were extracted. Two reviewers independently assessed study quality based on six domains of potential bias. Pooling of extracted risk factors was not permitted due to heterogeneity of the included studies. Data were synthesised using content analysis and presented in narrative form. RESULTS: Thirty-six significant risk factors were extracted from the 44 included studies and presented under three health condition groupings. For All-cause UHRs, ethnicity, comorbidity and type of health insurance were the most frequently cited factors. For Surgical procedure related UHRs, specific surgical procedures, comorbidity, length of stay (LOS), age, the American Society of Anaesthesiologists class, postoperative complications, duration of procedure, type of health insurance and illness severity were cited more frequently. The four most cited risk factors associated with General medical condition related UHRs were comorbidity, age, health service usage prior to the index admission and LOS. CONCLUSIONS: This systematic review acknowledges the complexity of readmission risk prediction in paediatric populations. This review identified four risk factors across all three health condition groupings, namely comorbidity; public health insurance; longer LOS and patients<12 months or between 13-18 years. The identification of risk factors, however, depended on the variables examined by each of the included studies. Consideration should be taken into account when generalising reported risk factors to other institutions. This review highlights the need to develop a standardised set of measures to capture key hospital discharge variables that predict unplanned readmission among paediatric patients.
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Zhou et al. (2019) conducted a systematic review in Unplanned hospital readmissions in pediatric patients. Risk factors (comorbidity, public health insurance, length of stay, age) vs. Patients without these risk factors was evaluated on Risk factors associated with unplanned hospital readmissions. Comorbidity, public health insurance, longer length of stay, and age <12 months or 13-18 years were consistently identified as risk factors for unplanned hospital readmissions.
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