Does the All Wales Universal Orthodontic Referral Form enable accurate triage of new NHS orthodontic patients? A service evaluation.

Introduction This study was designed to investigate the accuracy of clinical information provided by referring general dental practitioners (GDPs) following the introduction of a standardised referral form across Wales (the All Wales Universal Orthodontic Referral Form [AWUORF]) and to see whether the information given could be reliably used to screen the referrals.Aim To evaluate whether priority cases were being readily identified and whether inappropriate referrals could be minimised, thereby potentially reducing waiting lists.Method A service evaluation involving the retrospective study of 200 consecutive referrals to a specialist practice over a three-month period. A descriptive data analysis was undertaken.Results The GDPs had successfully identified the main complaint in 156 (78%) of the referrals. Of the 44 (22%) clinically inaccurate referrals, there was no impact on the patient in terms of referral pathway in 32 (16%) cases, but in the remaining 12 (6%), 5 (2.5%) cases were prioritised unnecessarily and the remaining 7 (3.5%) would have been seen more quickly had the GDP provided the relevant clinical information. The appropriateness of referral in terms of eligibility of the patient to receive NHS-funded orthodontic treatment was high with only 18 (9%) patients failing to meet the criteria.Conclusion The AWUORF successfully guides the GDP to make appropriate referrals and enables accurate triage in the majority of cases.

Factors associated with unplanned readmissions in a major Australian health service.

Objective The aim of the present study was to gain an understanding of the factors associated with unplanned hospital readmission within 28 days of acute care discharge from a major Australian health service. Methods A retrospective study of 20575 acute care discharges from 1 August to 31 December 2015 was conducted using administrative databases. Patient, index admission and readmission characteristics were evaluated for their association with unplanned readmission in ≤28 days. Results The unplanned readmission rate was 7.4% (n=1528) and 11.1% of readmitted patients were returned within 1 day. The factors associated with increased risk of unplanned readmission in ≤28 days for all patients were age ≥65 years (odds ratio (OR) 1.3), emergency index admission (OR 1.6), Charlson comorbidity index >1 (OR 1.1-1.9), the presence of chronic disease (OR 1.4) or complications (OR 1.8) during the index admission, index admission length of stay (LOS) >2 days (OR 1.4-1.8), hospital admission(s) (OR 1.7-10.86) or emergency department (ED) attendance(s) (OR 1.8-5.2) in the 6 months preceding the index admission and health service site (OR 1.2-1.6). However, the factors associated with increased risk of unplanned readmission ≤28 days changed with each patient group (adult medical, adult surgical, obstetric and paediatric). Conclusions There were specific patient and index admission characteristics associated with increased risk of unplanned readmission in ≤28 days; however, these characteristics varied between patient groups, highlighting the need for tailored interventions. What is known about the topic? Unplanned hospital readmissions within 28 days of hospital discharge are considered an indicator of quality and safety of health care. What does this paper add? The factors associated with increased risk of unplanned readmission in ≤28 days varied between patient groups, so a 'one size fits all approach' to reducing unplanned readmissions may not be effective. Older adult medical patients had the highest rate of unplanned readmissions and those with Charlson comorbidity index ≥4, an index admission LOS >2 days, left against advice and hospital admission(s) or ED attendance(s) in the 6 months preceding index admission and discharge from larger sites within the health service were at highest risk of unplanned readmission. What are the implications for practitioners? One in seven discharges resulted in an unplanned readmission in ≤28 days and one in 10 unplanned readmissions occurred within 1 day of discharge. Although some patient and hospital characteristics were associated with increased risk of unplanned readmission in ≤28 days, statistical modelling shows there are other factors affecting the risk of readmission that remain unknown and need further investigation. Future work related to preventing unplanned readmissions in ≤28 days should consider inclusion of health professional, system and social factors in risk assessments.

Factors associated with unplanned readmissions within 1 day of acute care discharge: a retrospective cohort study.

BACKGROUND: Unplanned hospital readmissions are a quality and safety indicator. In Australian, 8% to 11.1% of unplanned readmissions occur ≤1 day of acute care discharge. The aim of this study was to explore the reasons for unplanned hospital readmissions ≤1 day of acute care discharge, and determine what proportion of such unplanned hospital readmissions were potentially preventable. METHODS: A retrospective exploratory cohort design was used to conduct this two phase study. In Phase 1, organisational data from 170 readmissions ≤1 day and 1358 readmissions between 2 and 28 days were compared using the Cochran-Mantel-Haenszel test. Binary logistic regression was used to examine factors associated with unplanned readmission ≤1 day. In Phase 2, a medical record audit of 162 Phase 1 readmissions ≤1 day was conducted and descriptive statistics used to summarise the study data. Index discharges occurred between 1 August and 31 December 2015. RESULTS: In Phase 1, unplanned readmissions ≤1 day were more likely in paediatric patients (< 0.001); index discharges on weekends (p = 0.006), from short stay unit (SSU) (p < 0.001) or against health professional advice (p = 0.010); or when the readmission was for a Diagnosis Related Group (p < 0.001). The significant predictors of unplanned readmission ≤1 day were index discharge against advice or from SSU, and 1-5 hospital admissions in the 6 months preceding index admission. In Phase 2, 88.3% readmissions were unpreventable and 11.7% were preventable. The median patient age was 57 years and comorbidities were uncommon (3.1%). Most patients (94.4%) lived at home and with others (78.9%). Friday was the most common day of index discharge (17.3%) and Saturday was the most common day of unplanned readmission (19.1%). The majority (94.4%) of readmissions were via the emergency department: 58.5% were for a like diagnosis and pain was the most common reason for readmission. CONCLUSIONS: Advanced age, significant comorbidities and social isolation did not feature in patients with an unplanned readmission ≤1 day. One quarter of patients were discharged on a Friday or weekend, one quarter of readmissions occurred on a weekend, and pain was the most common reason for readmission raising issues about access to services and weekend discharge planning.