Turbocharging Networks in the Public Sector

Networks have come to occupy a key position in the strategic armoury of the government, business and community sectors and now have impact on a broad array of policy and management arenas. An emphasis on relationships, trust and mutuality mean that networks function on a different operating logic to the conventional processes of government and business. It is therefore important that organizational members of networks are able to adopt the skills and culture necessary to operate successfully under these distinctive kinds of arrangements. Because networks function from a different operational logic to traditional bureaucracies, public sector organizations may experience difficulties in adapting to networked arrangements. Networks are formed to address a variety of social problems or meet capability gaps within organizations. As such they are often under pressure to quickly produce measurable outcomes and need to form rapidly and come to full operation quickly. This paper presents a theoretical exploration of how diverse types of networks are required for different management and policy situations and draws on a set of public sector case studies to understand/demonstrate how these various types of networked arrangements may be ‘turbo-charged’ so that they more quickly adopt the characteristics necessary to deliver required outcomes.

Injury prevention in Queensland : report to Queensland Injury Prevention Council

Injury is the fourth leading cause of death in Australia. Injury rates in Queensland are amongst the highest in Australia and 21.5% of people surveyed for this research reported that their lifestyle or that of an immediate family member had been permanently affected by injury. Injury results in over 40,000 hospital admissions and 200,000 attendances at hospital Emergency Departments in Queensland each year. Queensland's death rate from injuries is higher than the national average, with consistently higher rates of deaths related to transport injuries. Queensland statistics also show higher than national average rates of injuries due to falls, homicide and accidental drowning. (Pike, Muller, Baade & Ward, 2000) In 2000-01 injuries represented over $4 billion (or 8%) of total health system expenditure, and 185,000 disability-adjusted life years (DALYs), or 7% of the total morbidity burden of disease and injury in Australia in 2003. (Begg, Vos, Barker, Stevenson, Stanley & Lopez, 2007). Injury is one of seven key health areas identified by the Commonwealth, state and territory governments for priority attention as National Health Priority Areas

The STRATIFY tool and clinical judgment were poor predictors of falling in an acute hospital setting

Objective: To compare the effectiveness of the STRATIFY falls tool with nurses’ clinical judgments in predicting patient falls. Study Design and Setting: A prospective cohort study was conducted among the inpatients of an acute tertiary hospital. Participants were patients over 65 years of age admitted to any hospital unit. Sensitivity, specificity, and positive predictive value (PPV) and negative predictive values (NPV) of the instrument and nurses’ clinical judgments in predicting falls were calculated. Results: Seven hundred and eighty-eight patients were screened and followed up during the study period. The fall prevalence was 9.2%. Of the 335 patients classified as being ‘‘at risk’’ for falling using the STRATIFY tool, 59 (17.6%) did sustain a fall (sensitivity50.82, specificity50.61, PPV50.18, NPV50.97). Nurses judged that 501 patients were at risk of falling and, of these, 60 (12.0%) fell (sensitivity50.84, specificity50.38, PPV50.12, NPV50.96). The STRATIFY tool correctly identified significantly more patients as either fallers or nonfallers than the nurses (P50.027). Conclusion: Considering the poor specificity and high rates of false-positive results for both the STRATIFY tool and nurses’ clinical judgments, we conclude that neither of these approaches are useful for screening of falls in acute hospital settings.