Gawaine Powell-Davies

Predictors of primary care referrals to a vascular disease prevention lifestyle program among participants in a cluster randomised trial

BackgroundCardiovascular disease accounts for a large burden of disease, but is amenable to prevention through lifestyle modification. This paper examines patient and practice predictors of referral to a lifestyle modification program (LMP) offered as part of a cluster randomised controlled trial (RCT) of prevention of vascular disease in primary care.MethodsData from the intervention arm of a cluster RCT which recruited 36 practices through two rural and three urban primary care organisations were used. In each practice, 160 eligible high risk patients were invited to participate. Practices were randomly allocated to intervention or control groups. Intervention practice staff were trained in screening, motivational interviewing and counselling and encouraged to refer high risk patients to a LMP involving individual and group sessions. Data include patient surveys; clinical audit; practice survey on capacity for preventive care; referral records from the LMP. Predictors of referral were examined using multi-level logistic regression modelling after adjustment for confounding factors.ResultsOf 301 eligible patients, 190 (63.1%) were referred to the LMP. Independent predictors of referral were baseline BMI ≥ 25 (OR 2.87 95%CI:1.10, 7.47), physical inactivity (OR 2.90 95%CI:1.36,6.14), contemplation/preparation/action stage of change for physical activity (OR 2.75 95%CI:1.07, 7.03), rural location (OR 12.50 95%CI:1.43, 109.7) and smaller practice size (1–3 GPs) (OR 16.05 95%CI:2.74, 94.24).ConclusionsProviding a well-structured evidence-based lifestyle intervention, free of charge to patients, with coordination and support for referral processes resulted in over 60% of participating high risk patients being referred for disease prevention. Contrary to expectations, referrals were more frequent from rural and smaller practices suggesting that these practices may be more ready to engage with these programs.Trial registrationACTRN12607000423415

Impact Evaluation of a System-Wide Chronic Disease Management Program on Health Service Utilisation: A Propensity-Matched Cohort Study

Background The New South Wales Health (NSW Health) Chronic Disease Management Program (CDMP) delivers interventions to adults at risk of hospitalisation for five target chronic conditions that respond well to ambulatory care: diabetes, hypertension, chronic obstructive pulmonary disease, congestive heart failure, and coronary artery disease. The intervention consists of two main components: (1) care coordination across sectors (acute, ambulatory, and community care from both public and private sectors) and clinical specialties, facilitated by program care coordinators, and (2) health coaching including management of lifestyle risk factors and medications and self-management. These components were broadly prescribed by the head office of NSW Health, which funded the program, and were implemented by regional health services (local health districts) in ways that best suited their own history, environment, workforce, and patient need. We used a propensity-matched cohort study to evaluate health service utilisation after enrolment in the CDMP. Methods and Findings The evaluation cohort included 41,303 CDMP participants enrolled between 1 January 2011 and 31 December 2013 who experienced at least one hospital admission or emergency department (ED) presentation for a target condition in the 12 mo preceding enrolment. Potential controls were selected from patients not enrolled in the CDMP but experiencing at least one hospital admission or ED presentation over the same period. Each CDMP patient in the evaluation cohort was matched to one control using 1:1 propensity score matching. The primary outcome was avoidable hospitalisations. Secondary outcomes included avoidable readmissions, avoidable bed days, unplanned hospitalisations, unplanned readmissions, unplanned bed days, ED presentations, and all-cause death. The primary analysis consisted of 30,057 CDMP participants and 30,057 matched controls with a median follow-up of 15 mo. Of those, 25,638 (85.3%) and 25,597 (85.2%) were alive by the end of follow-up in the CDMP and control groups, respectively. Baseline characteristics (including history of health service utilisation) were well balanced between the matched groups. In both groups, utilisation peaked just before the time of enrolment/matching, declined sharply immediately following enrolment, and then continued to decrease more gradually; however, after enrolment, avoidable and unplanned health service utilisation remained higher for CDMP participants compared to controls. The adjusted yearly rate of avoidable hospital admissions was 0.57 (95% CI 0.52 to 0.62) in the CDMP group versus 0.33 (95% CI 0.31 to 0.37) in the control group (adjusted rate ratio 1.70, 95% CI 1.62 to 1.79, p < 0.001). Significant increases in service utilisation were also observed for unplanned hospitalisations (1.42, 95% CI 1.37 to 1.47, p < 0.001) and ED presentations (1.37, 95% CI 1.32 to 1.42, p < 0.001) as well as avoidable (2.00, 95% CI 1.80 to 2.22, p < 0.001) and unplanned (1.51, 95% CI 1.40 to 1.62, p < 0.001) readmissions and avoidable (1.70, 95% CI 1.59 to 1.82, p < 0.001) and unplanned (1.43, 95% CI 1.36 to 1.49, p < 0.001) bed days. No evidence of a difference was seen for all-cause death (adjusted risk ratio 0.96, 95% CI 0.96 to 1.01, p = 0.10) or non-avoidable hospitalisations (all hospitalisations minus avoidable hospitalisations; adjusted rate ratio 1.03, 95% CI 0.97 to 1.10, p = 0.26). Despite the robustness of these results to sensitivity analyses, in the absence of a randomised control group, one cannot exclude the possibility of residual or unmeasured confounding that was not controlled for by the matching process and multivariable analyses. Conclusions Participation in the CDMP was associated with an increase in avoidable hospital admissions compared to matched controls but no difference in the rate of other types of hospitalisation or death. A possible explanation is that the program identified conditions that required participants to be hospitalised. Service utilisation decreased sharply following its peak for both groups. This finding reflects the natural tendency for high-risk patients to show reductions in use following intense phases of service utilisation and highlights that, despite the additional complexity, a carefully selected control group is essential when assessing the effectiveness of interventions on hospital use.

Context matters for primary health care access: a multi-method comparative study of contextual influences on health service access arrangements across models of primary health care

BackgroundEquitable access to primary health care (PHC) is an important component of integrated chronic disease management. Whilst context is known to influence access to PHC, it is poorly researched. The aim of this study was to determine the contextual influences associated with access arrangements in four Australian models of integrated PHC.MethodsA multi-method comparative case study design. Purposive sampling identified four models of PHC across six sites in two Australian states. Complexity theory informed the choice of contextual factors that influenced access arrangements, which were analysed across five dimensions: availability and accommodation, affordability, acceptability, appropriateness and approachability. Semi-structured interviews, document/website analysis and non-participant observation were used to collect data from clinicians, administrative staff and other key stakeholders. Within and cross-case thematic analysis identified interactions between context and access across sites.ResultsOverall, financial viability, objectives of the PHC model and relationships with the local hospital network (LHN) underpinned access arrangements. Local supply of general practitioners and financial viability were strong influences on availability of after-hours services. Influences on affordability were difficult to determine because all models had nil/low out-of-pocket costs for general practitioner services. The biggest influence on acceptability was the goal/objectives of the PHC model. Appropriateness and to a lesser degree affordability arrangements were influenced by the relationship with the LHN. The provision of regular outreach services was strongly influenced by perceived population need, referral networks and model objectives.ConclusionsThese findings provide valuable insights for policy makers charged with improving access arrangements in PHC services. A financially sustainable service underpins attempts to improve access that meets the needs of the service population. Smaller services may lack infrastructure and capacity, suggesting there may be a minimum size for enhancing access. Access arrangements may be facilitated by aligning the objectives between PHC, LHN and other stakeholder models. While some access arrangements are relatively easy to modify, improving resource intensive (e.g. acceptability) access arrangements for vulnerable and/or chronic disease populations will require federal and state policy levers with input from primary health networks and LHNs.