Patient-reported experiences and outcomes following hospital care are associated with risk of readmission among adults with chronic health conditions.

This study quantifies the association between patient reported measures (PRMs) and readmission to inform efforts to improve hospital care. A retrospective, cross-sectional study was conducted with adults who had chronic obstructive pulmonary disease (COPD) or congestive heart failure (CHF) and were admitted for acute care in a public hospital in New South Wales, Australia for any reason (n = 2394 COPD and 2476 CHF patients in 2018-2020). Patient- level survey data were linked with inpatient data for one year prior to risk-adjust outcomes and after discharge to detect all cause unplanned readmission to a public or private hospital. Ninety-day readmission rates for respondents with COPD or CHF were 17% and 19%. Crude rates for adults with COPD were highest among those who reported that hospital care and treatment helped "not at all" (28%), compared to those who responded, "to some extent" (20%) or "definitely" (15%). After accounting for patient characteristics, adults with COPD or CHF who said care and treatment didn't help at all were at twice the risk of readmission compared to those who responded that care and treatment helped "definitely" (Hazard ratio for COPD 1.97, CI: 1.17-3.32; CHF 2.07, CI 1.25-3.42). Patients who offered the most unfavourable ratings of overall care, understandable explanations, organised care, or preparedness for discharge were at a 1.5 to more than two times higher risk of readmission. Respect and dignity, effective and clear communications, and timely and coordinated care also matter. PRMs are strong predictors of readmission even after accounting for risk related to age and co-morbidities. More moderate ratings were associated with attenuation of risk, and the most positive ratings were associated with the lowest readmission rate. These results suggest that increasing each patient's positive experiences progressively reduces the risk of adults with chronic conditions returning to acute care.

Association between number of replacements and readmissions following total knee and total hip replacements in New South Wales' public hospitals.

BACKGROUND: Total knee and total hip replacement are common and resource-intensive procedures. Complications are associated with worse outcomes and can add to the health care costs, particularly if associated with readmission. The aims of this study were to inform quality improvement by reporting on the extent of variation in readmissions across public hospitals and investigating the association between hospital volume and readmissions. METHODS: This retrospective population-based cohort study used linked, admitted patient data for a census of all admissions to public and private hospitals. Adults who had an acute hospitalization for total knee or total hip replacement elective surgery and were discharged alive between 1 July 2015 and 30 June 2018 were included. Hospital volumes and risk standardized readmission ratios were calculated, and readmissions included acute hospitalizations following discharge and returns to acute care from non-acute settings within 60 days. RESULTS: In 2015-2018, one in 10 patients were readmitted following total knee or total hip replacement (11.9 and 10.6 per 100 hospitalizations) an increase of 4.9% and 13.1% respectively, compared to 2012-2015. The majority of hospitals had risk standardized readmission ratios no different than expected. The median annual hospital volume was 170 total knee (interquartile range 116-247) and 93 total hip (interquartile range 61-141) procedures with no evidence of a meaningful association between hospital volume and readmissions. CONCLUSION: Readmissions rates for total knee and total hip replacements are increasing. While hospital volume varies, it was not associated with readmission after adjusting for risk factors and any non-linear association.

Is the weekend effect really ubiquitous? A retrospective clinical cohort analysis of 30-day mortality by day of week and time of day using linked population data from New South Wales, Australia.

OBJECTIVE: To examine the associations between day of week and time of admission and 30-day mortality for six clinical conditions: ischaemic and haemorrhagic stroke, acute myocardial infarction, pneumonia, chronic obstructive pulmonary disease and congestive heart failure. DESIGN: Retrospective population-based cohort analyses. Hospitalisation records were linked to emergency department and deaths data. Random-effect logistic regression models were used, adjusting for casemix and taking into account clustering within hospitals. SETTING: All hospitals in New South Wales, Australia, from July 2009 to June 2012. PARTICIPANTS: Patients admitted to hospital with a primary diagnosis for one of the six clinical conditions examined. OUTCOME MEASURES: Adjusted ORs for all-cause mortality within 30 days of admission, by day of week and time of day. RESULTS: A total of 148 722 patients were included in the study, with 17 721 deaths within 30 days of admission. Day of week of admission was not associated with significantly higher likelihood of death for five of the six conditions after adjusting for casemix. There was significant variation in mortality for chronic obstructive pulmonary disease by day of week; however, this was not consistent with a strict weekend effect (Thursday: OR 1.29, 95% CI 1.12 to 1.48; Friday: OR 1.25, 95% CI 1.08 to 1.44; Saturday: OR 1.18, 95% CI 1.02 to 1.37; Sunday OR 1.05, 95% CI 0.90 to 1.22; compared with Monday). There was evidence for a night effect for patients admitted for stroke (ischaemic: OR 1.30, 95% CI 1.17 to 1.45; haemorrhagic: OR 1.58, 95% CI 1.40 to 1.78). CONCLUSIONS: Mortality outcomes for these conditions, adjusted for casemix, do not vary in accordance with the weekend effect hypothesis. Our findings support a growing body of evidence that questions the ubiquity of the weekend effect.

The impact of blood-borne viruses on cause-specific mortality among opioid dependent people: An Australian population-based cohort study.

BACKGROUND: Blood-borne viruses (BBV) are prevalent among people with opioid dependence but their association with cause-specific mortality has not been examined at the population-level. METHODS: We formed a population-based cohort of 29,571 opioid substitution therapy (OST) registrants in New South Wales, Australia, 1993-2007. We ascertained notifications of infection and death by record linkage between the Pharmaceutical Drugs of Addiction System (OST data), registers of hepatitis C (HCV), hepatitis B (HBV) and human immunodeficiency virus (HIV) diagnoses, and the National Death Index. We used competing risks regression to quantify associations between notification for BBV infection and causes of death. BBV status, age, year, OST status, and OST episodes were modelled as time-dependent covariates; sex was a fixed covariate. RESULTS: OST registrants notified with HCV infection were more likely to die from accidental overdose (subdistribution hazard ratio, 95% Confidence Interval: 1.7, 1.5-2.0), cancer (2.0, 1.3-3.2) and unintentional injury (1.4, 1.0-2.0). HBV notification was associated with a higher hazard of mortality due to unintentional injury (2.1, 1.1-3.9), cancer (2.8, 1.5-5.5), and liver disease (2.1, 1.0-4.3). Liver-related mortality was higher among those notified with HIV only (11, 2.5-50), HCV only (5.9, 3.2-11) and both HIV and HCV (15, 3.2-66). Registrants with an HIV notification had a higher hazard of cardiovascular-related mortality (4.0, 1.6-9.9). CONCLUSIONS: Among OST registrants, BBVs are a direct cause of death and also a marker of behaviours that can result in unintended death. Ongoing and enhanced BBV prevention strategies and treatment, together with targeted education strategies to reduce risk, are justified.

The association between the density of retail tobacco outlets, individual smoking status, neighbourhood socioeconomic status and school locations in New South Wales, Australia.

AIM: We explored the association between the density of tobacco outlets and neighbourhood socioeconomic status, and between neighbourhood tobacco outlet density and individual smoking status. We also investigated the density of tobacco outlets around primary and secondary schools in New South Wales (NSW). METHODS: We calculated the mean density of retail tobacco outlets registered in NSW between 2009 and 2011, using kernel density estimation with an adaptive bandwidth. We used generalised ordered logistic regression model to explore the association between socioeconomic status and density of tobacco outlets. The association between neighbourhood tobacco outlet density and individuals' current smoking status was investigated using random-intercept generalised linear mixed models. We also calculated the median tobacco outlet density around NSW schools. RESULTS: More disadvantaged Census Collection Districts (CDs) were significantly more likely to have higher tobacco outlet densities. After adjusting for neighbourhood socioeconomic status and participants' age, sex, country of birth and Aboriginal status, neighbourhood mean tobacco outlet density was significantly and positively associated with individuals' smoking status. The median of tobacco outlet density around schools was significantly higher than the state median. CONCLUSION: Policymakers could consider exploring a range of strategies that target tobacco outlets in proximity to schools, in more disadvantaged neighbourhoods and in areas of existing high tobacco outlet density.

Competing risk analysis of mortality from invasive cutaneous melanoma in New South Wales: a population-based study, 1988-2007.

OBJECTIVE: Accurate estimates of risk of death from melanoma, based on the most recent information, are desirable, especially if secular improvements in survival have occurred. This study aims to investigate prognostic factors and temporal changes in mortality from primary invasive cutaneous melanoma (CM) and to predict cumulative probabilities of death from CM. METHODS: Cases of CM from the NSW Central Cancer Registry (NSWCCR) diagnosed in 1988-2007 were analysed. We used Fine and Gray competing risks models to investigate prognostic factors associated with CM mortality, along with period effects of year of diagnosis. Adjusted cumulative probabilities of CM death were then estimated. RESULTS: Of 52,330 CM cases, 5291 (10%) died from CM and 8290 (16%) from other causes. Patients with tumours thicker than 4 mm had 9.5 times the risk of death from CM compared to those with tumours 1 mm or less (subhazard ratio [SHR] 9.52; 95%CI:8.42-10.77). Risk of melanoma death was 31% lower in 2003-2007 compared to 1988-1992 (SHR 0.69; 95%CI: 0.63-0.76). Other risk factors for CM mortality included older age and male gender. Assuming the estimated period effect for a diagnosis in 2003-2007 applies now, the predicted probability of CM death within 10 years of diagnosis of a tumour 4+ mm thick is 26% in males and 19% in females. CONCLUSION: This study highlights the importance of awareness and early detection and shows a significant improvement in survival from CM since 1988.

Analysis and impact of delays in ambulance to emergency department handovers.

OBJECTIVES: Delays in the clinical handover of patient care from emergency medical services (EMS) to the ED because of ED crowding are a substantial problem for many EMS systems. This study was conducted to quantify handover delays experienced by the Ambulance Service of New South Wales (ASNSW), and to investigate patient and system factors associated with handover delay. METHODS: A retrospective study of EMS dispatch and ambulance patient care records was conducted for all patients transported by ASNSW in January/April/July/October 2009. Patient characteristics and time intervals were summarised using descriptive statistics, with handover delay categorised as <30 min, 30-60 min and ≥60 min. Times are reported as HH:MM:SS. Partial proportional odds models were used to investigate factors associated with delays. RESULTS: Of 141 381 transports, 12.5% of patients experienced a handover delay of 30-60 min, and 5% a delay of ≥60 min. The median handover interval was 00:15:46 (IQR 00:08:58-00:24:52, maximum 08:43:13). Patients transported to large hospitals were more likely to experience a delay of ≥30 min (odds ratio [OR] 14.57, 95% CI 11.41-18.60) or ≥60 min (OR 15.75, 95% CI 12.27-20.23) than those transported to small hospitals. Patients in major cities were more likely to experience delays than those in other areas, and patients ≥65 years were more likely to experience delays than those <16 years. Delays were most likely in winter. Cardiac and major trauma patients had the lowest likelihood of experiencing delays. CONCLUSIONS: Handover delays are relatively common at the EMS/ED interface in New South Wales, and are most pronounced at large hospitals, in urban areas and during winter.