A cross-sectional study assessing concordance with advance care directives in a rural health district.

OBJECTIVE: To measure compliance with Advance Care Directives (ACDs) for decedents in a rural setting. DESIGN: Observational, cross-sectional medical records audit comparing requests in ACDs with actual outcomes. SETTING: Rural Australian coastal district. PARTICIPANTS: People who had an ACD, died during the study period (30 May 2020 to 15 December 2021) and participated in a local research project. MAIN OUTCOME MEASURE(S): Compliance was measured by comparing stated requests in the ACD with outcomes recorded in medical records. This included the place of death and a list of 'unacceptable interventions'. RESULTS: Sixty-eight people met the inclusion criteria (age range of 46-92 [mean 67 years; median 74 years]; 42 [62%] male). The main cause of death was cancer (n = 48; 71%). Preferred place of death was not stated in 16 ACDs. Compliance with documented preferred place of death was 63% (33/52): 48% (16/33) when the preferred place of death was home; 78% (7/9) when sub-acute was preferred; and 100% (10/10) when hospital was preferred. Compliance was 100% with 'unacceptable interventions'. CONCLUSION: These results demonstrate strong compliance with rural patients' requests in ACDs, particularly 'unacceptable interventions'. Home was the most common preferred place of death, but the compliance measure (48%) was the lowest in this study. This requires further exploration.

COPD in Africa: risk factors, hospitalisation, readmission and associated outcomes-a systematic review and meta-analysis.

BACKGROUND: This review aims to synthesise available evidence on the prevalence of chronic obstructive pulmonary disease (COPD), associated risk factors, hospitalisations and COPD readmissions in Africa. METHOD: Using the Met-Analyses and Systematic Reviews of Observational Studies guideline, electronic databases were searched from inception to 1 October 2021. The quality of studies was assessed using the Newcastle-Ottawa Scale. Evidence from retrieved articles was synthesised, and a random-effect model meta-analysis was conducted. The protocol was registered on PROSPERO. RESULTS: Thirty-nine studies met the inclusion criteria, with 13 included in the meta-analysis. The prevalence of COPD varied between the Global Initiative for Chronic Obstructive Lung Disease (2%-24%), American Thoracic Society/European Respiratory Society (1%-17%) and Medical Research Council chronic bronchitis (2%-11%) criteria, respectively. Increasing age, wheezing and asthma were consistent risk factors for COPD from studies included in the narrative synthesis. Our meta-analysis indicated that prior tuberculosis ((OR 5.98, 95% CI 4.18 to 8.56), smoking (OR 2.80, 95% CI: 2.19 to 3.59) and use of biomass fuel (OR 1.52, 95% CI: 1.39 to 1.67)) were significant risk factors for COPD. Long-term oxygen therapy (HR 4.97, 95% CI (1.04 to 23.74)) and frequent hospitalisation (≥3 per year) (HR 11.48, 95% CI (1.31 to 100.79)) were risk factors associated with 30-day COPD readmission. CONCLUSION: This study not only highlights specific risk factors for COPD risk in Africa but also demonstrates the paucity and absence of research in several countries in a continent with substantial COPD-related mortality. Our findings contribute towards the development of evidence-based clinical guidelines for COPD in Africa.PROSPERO registration numberCRD42020210581.

Hospital nurse-staffing models and patient- and staff-related outcomes.

BACKGROUND: Nurses comprise the largest component of the health workforce worldwide and numerous models of workforce allocation and profile have been implemented. These include changes in skill mix, grade mix or qualification mix, staff-allocation models, staffing levels, nursing shifts, or nurses' work patterns. This is the first update of our review published in 2011. OBJECTIVES: The purpose of this review was to explore the effect of hospital nurse-staffing models on patient and staff-related outcomes in the hospital setting, specifically to identify which staffing model(s) are associated with: 1) better outcomes for patients, 2) better staff-related outcomes, and, 3) the impact of staffing model(s) on cost outcomes. SEARCH METHODS: CENTRAL, MEDLINE, Embase, two other databases and two trials registers were searched on 22 March 2018 together with reference checking, citation searching and contact with study authors to identify additional studies. SELECTION CRITERIA: We included randomised trials, non-randomised trials, controlled before-after studies and interrupted-time-series or repeated-measures studies of interventions relating to hospital nurse-staffing models. Participants were patients and nursing staff working in hospital settings. We included any objective reported measure of patient-, staff-related, or economic outcome. The most important outcomes included in this review were: nursing-staff turnover, patient mortality, patient readmissions, patient attendances at the emergency department (ED), length of stay, patients with pressure ulcers, and costs. DATA COLLECTION AND ANALYSIS: We worked independently in pairs to extract data from each potentially relevant study and to assess risk of bias and the certainty of the evidence. MAIN RESULTS: We included 19 studies, 17 of which were included in the analysis and eight of which we identified for this update. We identified four types of interventions relating to hospital nurse-staffing models:- introduction of advanced or specialist nurses to the nursing workforce;- introduction of nursing assistive personnel to the hospital workforce;- primary nursing; and- staffing models.The studies were conducted in the USA, the Netherlands, UK, Australia, and Canada and included patients with cancer, asthma, diabetes and chronic illness, on medical, acute care, intensive care and long-stay psychiatric units. The risk of bias across studies was high, with limitations mainly related to blinding of patients and personnel, allocation concealment, sequence generation, and blinding of outcome assessment.The addition of advanced or specialist nurses to hospital nurse staffing may lead to little or no difference in patient mortality (3 studies, 1358 participants). It is uncertain whether this intervention reduces patient readmissions (7 studies, 2995 participants), patient attendances at the ED (6 studies, 2274 participants), length of stay (3 studies, 907 participants), number of patients with pressure ulcers (1 study, 753 participants), or costs (3 studies, 617 participants), as we assessed the evidence for these outcomes as being of very low certainty. It is uncertain whether adding nursing assistive personnel to the hospital workforce reduces costs (1 study, 6769 participants), as we assessed the evidence for this outcome to be of very low certainty. It is uncertain whether primary nursing (3 studies, > 464 participants) or staffing models (1 study, 647 participants) reduces nursing-staff turnover, or if primary nursing (2 studies, > 138 participants) reduces costs, as we assessed the evidence for these outcomes to be of very low certainty. AUTHORS' CONCLUSIONS: The findings of this review should be treated with caution due to the limited amount and quality of the published research that was included. We have most confidence in our finding that the introduction of advanced or specialist nurses may lead to little or no difference in one patient outcome (i.e. mortality) with greater uncertainty about other patient outcomes (i.e. readmissions, ED attendance, length of stay and pressure ulcer rates). The evidence is of insufficient certainty to draw conclusions about the effectiveness of other types of interventions, including new nurse-staffing models and introduction of nursing assistive personnel, on patient, staff and cost outcomes. Although it has been seven years since the original review was published, the certainty of the evidence about hospital nurse staffing still remains very low.

Hospital length of stay variation and comorbidity of mental illness: a retrospective study of five common chronic medical conditions.

BACKGROUND: With the increasing burden of mental illness globally, it is becoming common for hospitalised patients with chronic medical conditions to have a comorbidity of mental illness. This combination could prolong length of stay (LOS) of this patient cohort. We conducted an investigation in Tasmania, Australian hospitals to characterise this cohort and assess if co-morbidity of mental illness is a distinguishing factor that generates LOS variation across different chronic medical conditions. METHODS: The retrospective study analysed 16,898 admissions of patients with a primary diagnosis of one of five chronic medical conditions: lung or colorectal cancer, chronic obstructive pulmonary disease (COPD), type II diabetes, ischaemic heart disease (IHD) and stroke. Data were from July 2010 to June 2015, across four hospitals that collectively cover 95% of public hospital admissions in Tasmania, Australia. Descriptive statistics were used to compare characteristics of patients between the scenarios of with and without co-morbidity of mental illness. We used negative binomial regression models to assess whether co-morbidity of mental illness, along with its sub-types, after adjustment for potential confounding variables, associated with LOS variation in patients of each medical condition. Based on the adjusted LOS variation, we estimated differences in bed days' use between patients with and without comorbidity of mental illness. RESULTS: Patients with co-morbidity of mental illness were significantly younger in comparison to patients without mental illness. With each medical condition, patients with comorbidity of mental illness had incurred higher bed days' use than for those without mental illness. In cancer and stroke cohorts, co-morbidity of mental illness unfavourably affected the LOS variation by as high as 97% (CI: 49.9%-159%) and 109% (78%-146%), respectively. Though mental and behavioural disorders due to psychoactive substances was a dominant sub-type of mental illness across the medical conditions, it contributed significant unfavourable LOS variation only in the stroke patients i.e. 36.3% (CI: 16.2%-59.9%). CONCLUSIONS: Mental illness consistently produced unfavourable LOS variation. Upskilling of healthcare teams and greater reporting and analysis of LOS variation for this patient cohort, and the sub-cohorts within it, are necessary to provide improved medical care and achieve system efficiencies.

How do small rural primary health care services sustain themselves in a constantly changing health system environment?

BACKGROUND: The ability to sustain comprehensive primary health care (PHC) services in the face of change is crucial to the health of rural communities. This paper illustrates how one service has proactively managed change to remain sustainable. METHODS: A 6-year longitudinal evaluation of the Elmore Primary Health Service (EPHS) located in rural Victoria, Australia, is currently underway, examining the performance, quality and sustainability of the service. Threats to, and enablers of, sustainability have been identified from evaluation data (audit of service indicators, community surveys, key stakeholder interviews and focus groups) and our own observations. These are mapped against an overarching framework of service sustainability requirements: workforce organisation and supply; funding; governance, management and leadership; service linkages; and infrastructure. RESULTS: Four years into the evaluation, the evidence indicates EPHS has responded effectively to external and internal changes to ensure viability. The specific steps taken by the service to address risks and capitalise on opportunities are identified. CONCLUSIONS: This evaluation highlights lessons for health service providers, policymakers, consumers and researchers about the importance of ongoing monitoring of sentinel service indicators; being attentive to changes that have an impact on sustainability; maintaining community involvement; and succession planning.