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      General practitioner follow-up after hospitalisation in Central and Eastern Sydney, Australia: access and impact on health services

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          Abstract

          ObjectivesGeneral practitioner (GP) follow-up after a hospital admission is an important indicator of integrated care. We examined the characteristics of patients who saw a GP within 2 weeks of hospital discharge in the Central and Eastern Sydney (CES) region, Australia, and the relationship between GP follow-up and subsequent hospitalisation. MethodsThis data linkage study used a cohort of 10240 people from the 45 and Up Study who resided in CES and experienced an overnight hospitalisation in the 5 years following recruitment (2007–14). Characteristics of participants who saw a GP within 2 weeks of discharge were compared with those who did not using generalised linear models. Time to subsequent hospitalisation was compared for the two groups using Cox proportional hazards regression models stratified by prior frequency of GP use. ResultsWithin 2 weeks of discharge, 64.3% participants saw a GP. Seeing a GP within 2 weeks of discharge was associated with lower rates of rehospitalisation for infrequent GP users (i.e. <8 visits in year before the index hospitalisation; hazard ratio (HR) 0.83; 95% confidence interval (CI) 0.70–0.97) but not frequent GP users (i.e. ≥8 plus visits; HR 1.02; 95% CI 0.90–1.17). ConclusionThe effect of seeing a GP on subsequent hospitalisation was protective but differed depending on patient care needs. What is known about the topic?There is general consensus among healthcare providers that primary care is a significant source of ongoing health care provision. What does this paper add?This study explored the relationship between GP follow-up after an uncomplicated hospitalisation and its effect on rehospitalisation. What are the implications for practitioners?Discharge planning and the transfer of care from hospital to GP through discharge arrangements have substantial benefits for both patients and the health system.

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          Investigation of relative risk estimates from studies of the same population with contrasting response rates and designs

          Background There is little empirical evidence regarding the generalisability of relative risk estimates from studies which have relatively low response rates or are of limited representativeness. The aim of this study was to investigate variation in exposure-outcome relationships in studies of the same population with different response rates and designs by comparing estimates from the 45 and Up Study, a population-based cohort study (self-administered postal questionnaire, response rate 18%), and the New South Wales Population Health Survey (PHS) (computer-assisted telephone interview, response rate ~60%). Methods Logistic regression analysis of questionnaire data from 45 and Up Study participants (n = 101,812) and 2006/2007 PHS participants (n = 14,796) was used to calculate prevalence estimates and odds ratios (ORs) for comparable variables, adjusting for age, sex and remoteness. ORs were compared using Wald tests modelling each study separately, with and without sampling weights. Results Prevalence of some outcomes (smoking, private health insurance, diabetes, hypertension, asthma) varied between the two studies. For highly comparable questionnaire items, exposure-outcome relationship patterns were almost identical between the studies and ORs for eight of the ten relationships examined did not differ significantly. For questionnaire items that were only moderately comparable, the nature of the observed relationships did not differ materially between the two studies, although many ORs differed significantly. Conclusions These findings show that for a broad range of risk factors, two studies of the same population with varying response rate, sampling frame and mode of questionnaire administration yielded consistent estimates of exposure-outcome relationships. However, ORs varied between the studies where they did not use identical questionnaire items.
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            Doubly robust estimation of causal effects.

            Doubly robust estimation combines a form of outcome regression with a model for the exposure (i.e., the propensity score) to estimate the causal effect of an exposure on an outcome. When used individually to estimate a causal effect, both outcome regression and propensity score methods are unbiased only if the statistical model is correctly specified. The doubly robust estimator combines these 2 approaches such that only 1 of the 2 models need be correctly specified to obtain an unbiased effect estimator. In this introduction to doubly robust estimators, the authors present a conceptual overview of doubly robust estimation, a simple worked example, results from a simulation study examining performance of estimated and bootstrapped standard errors, and a discussion of the potential advantages and limitations of this method. The supplementary material for this paper, which is posted on the Journal's Web site (http://aje.oupjournals.org/), includes a demonstration of the doubly robust property (Web Appendix 1) and a description of a SAS macro (SAS Institute, Inc., Cary, North Carolina) for doubly robust estimation, available for download at http://www.unc.edu/~mfunk/dr/.
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              Frequent attenders to an emergency department: a study of primary health care use, medical profile, and psychosocial characteristics.

              We describe, in comparison with a control group, frequent attenders to an emergency department in terms of their general health service use and their clinical, psychological, and social profiles. One hundred frequent attenders (those who had made > or =4 visits in the previous year) and 100 nonfrequent attenders matched for sex, age, and triage category were interviewed in the ED. Data were gathered on health service use, mental health (by using the General Health Questionnaire-12 item), and perceived social support (by using the Multidimensional Scale of Perceived Social Support). Patients' general practitioners were contacted to validate attendance data. Medical charts were searched for evidence of psychological problems and alcohol or drug abuse. In the overall sample of 200 patients, 32% were female, and the mean age was 55 years (SD 20). Frequent attenders had made more visits to their general practitioner in the past year compared with control patients (median 12 versus 3 visits); a higher proportion of frequent attenders had used public health nursing services, community welfare services, social work services, addiction counseling, and psychiatric services in the past year. Frequent attenders had made more other hospital visits and had spent more nights in the hospital than control patients. General Health Questionnaire-12 item scores were higher for frequent attenders than control patients, indicating poorer mental health. Frequent attenders had lower levels of perceived social support. Frequent attenders to the ED are also heavy users of general practice services, other primary care services, and other hospital services. General Medical Services-eligible patients (84% of frequent attenders) frequently attend the ED, even though they have free access to primary care. Frequent attenders are a psychosocially vulnerable group, and service providers and policy makers need to take account of this vulnerable patient profile as they endeavor to meet their service needs.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Australian Health Review
                Aust. Health Review
                CSIRO Publishing
                0156-5788
                2021
                2021
                : 45
                : 2
                : 247
                Article
                10.1071/AH19285
                445d756e-921d-458e-9446-4e58159e9f0e
                © 2021
                Product
                Self URI (article page): http://www.publish.csiro.au/?paper=AH19285

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