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      Transforming community health services for children and young people who are ill: a quasi-experimental evaluation

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          Abstract

          Background

          Children’s community nursing (CCN) services support children with acute, chronic, complex and end-of-life care needs in the community.

          Objectives

          This research examined the impact of introducing and expanding CCN services on quality, acute care and costs.

          Methods

          A longitudinal, mixed-methods, case study design in three parts. The case studies were in five localities introducing or expanding services. Part 1: an interrupted time series (ITS) analysis of Hospital Episode Statistics on acute hospital admission for common childhood illness, and bed-days and length of stay for all conditions, including a subset for complex conditions. The ITS used between 60 and 84 time points (monthly data) depending on the case site. Part 2: a cost–consequence analysis using activity data from CCN services and resource-use data from a subset of families ( n = 32). Part 3: in-depth interviews with 31 parents of children with complex conditions using services in the case sites and a process evaluation of service change with 41 NHS commissioners, managers and practitioners, using longitudinal in-depth interviews, focus groups and documentary data.

          Findings

          Part 1: the ITS analysis showed a mixed pattern of impact on acute activity, with the greatest reductions in areas that had rates above the national average before CCN services were introduced and significant reductions in some teams in acute activity for children with complex conditions. Some models of CCN appear to have more potential for impact than others. Part 2: the cost–consequence analysis covered only part of the CCN teams’ activity. It showed some potential savings from reduced admissions and bed-days, but none that was greater than the total cost of the services. Part 3: three localities implemented services as planned, one achieved partial service change and one was not able to achieve any service change. Organisational stability, finance, medical stakeholder support, competition, integration with primary care and visibility influenced the planning and implementation of new and expanded CCN services. Feeling supported to manage their ill child at home was a key outcome of using services for parents. Various service features contributed to this and were important in different ways at different times. Other outcomes included being able to avoid hospital care, enabling the child to stay in school, and getting respite. Although parents judged that care was of high quality when teams enabled them to feel supported, reassured and secure in managing their ill child at home, this did not depend on a constant level of contact from teams.

          Limitations

          Delays in service reconfigurations required adaptation of research activity across sites. Use of administrative data, such as Hospital Episode Statistics, for research purposes is technically difficult and imposed some limitations on both the ITS and the cost–consequence analyses.

          Conclusions

          Large, generic CCN teams that integrate acute admission avoidance for all children with support for children with complex conditions and highly targeted teams for children with complex conditions offer the possibility of supporting children more appropriately at home while also making some difference to acute activity. This possibility remains to be tested further.

          Future work

          Further work should refine the evidence on outcomes of services by looking at outcomes in promising models, value for money and measuring quality-based outcomes.

          Funding

          The National Institute for Health Research Health Services and Delivery Research Programme.

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          Most cited references41

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          Methods for estimating confidence intervals in interrupted time series analyses of health interventions.

          Interrupted time series (ITS) is a strong quasi-experimental research design, which is increasingly applied to estimate the effects of health services and policy interventions. We describe and illustrate two methods for estimating confidence intervals (CIs) around absolute and relative changes in outcomes calculated from segmented regression parameter estimates. We used multivariate delta and bootstrapping methods (BMs) to construct CIs around relative changes in level and trend, and around absolute changes in outcome based on segmented linear regression analyses of time series data corrected for autocorrelated errors. Using previously published time series data, we estimated CIs around the effect of prescription alerts for interacting medications with warfarin on the rate of prescriptions per 10,000 warfarin users per month. Both the multivariate delta method (MDM) and the BM produced similar results. BM is preferred for calculating CIs of relative changes in outcomes of time series studies, because it does not require large sample sizes when parameter estimates are obtained correctly from the model. Caution is needed when sample size is small.
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            Process Transformation: Limitations to Radical Organizational Change within Public Service Organizations

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              Realist RCTs of complex interventions - an oxymoron.

              Bonell et al. discuss the challenges of carrying out randomised controlled trials (RCTs) to evaluate complex interventions in public health, and consider the role of realist evaluation in enhancing this design (Bonell, Fletcher, Morton, Lorenc, & Moore, 2012). They argue for a "synergistic, rather than oppositional relationship between realist and randomised evaluation" and that "it is possible to benefit from the insights provided by realist evaluation without relinquishing the RCT as the best means of examining intervention causality." We present counter-arguments to their analysis of realist evaluation and their recommendations for realist RCTs. Bonell et al. are right to question whether and how (quasi-)experimental designs can be improved to better evaluate complex public health interventions. However, the paper does not explain how a research design that is fundamentally built upon a positivist ontological and epistemological position can be meaningfully adapted to allow it to be used from within a realist paradigm. The recommendations for "realist RCTs" do not sufficiently take into account important elements of complexity that pose major challenges for the RCT design. They also ignore key tenets of the realist evaluation approach. We propose that the adjective 'realist' should continue to be used only for studies based on a realist philosophy and whose analytic approach follows the established principles of realist analysis. It seems more correct to call the approach proposed by Bonell and colleagues 'theory informed RCT', which indeed can help in enhancing RCTs. Copyright © 2013 Elsevier Ltd. All rights reserved.
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                Author and article information

                Journal
                Health Services and Delivery Research
                Health Serv Deliv Res
                National Institute for Health Research
                2050-4349
                2050-4357
                September 2016
                September 2016
                : 4
                : 25
                : 1-222
                Affiliations
                [1 ]Social Policy Research Unit, University of York, York, UK
                [2 ]Department of Health Sciences, University of York, York, UK
                [3 ]Hull York Medical School, University of York, York, UK
                [4 ]Centre for Health Economics, University of York, York, UK
                [5 ]Public Health England, York, UK
                Article
                10.3310/hsdr04250
                cdb86a5a-d6bc-42cd-8ae2-224cdc2e9952
                © 2016

                Free to read

                http://www.nationalarchives.gov.uk/doc/non-commercial-government-licence/non-commercial-government-licence.htm

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