Analysis of interrupted time series mortality trends: an example to evaluate regionalized perinatal care.

Gillings, Dennis B.; D, Makuc; Siegel, Earl

doi:10.2105/ajph.71.1.38

Cited by 192 publications

(136 citation statements)

References 12 publications

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“…Segmented regression analysis of interrupted time series data allows for the assessment of long-term effects on an outcome attributable to a specific event in time, i.e., the implementation of an intervention. In interrupted time series, the level and trend of the preintervention segment serve as the controls for the postintervention segment, providing a methodologically acceptable design for measuring the effect of an intervention (15,36). Total volume of fluoroquinolone use was measured and controlled for in the analysis, allowing for examination of the effect on resistance observed for both levofloxacin and gatifloxacin independent of changes in overall fluoroquinolone use.…”

Section: Methodsmentioning

confidence: 99%

Using Interrupted Time Series Analysis To Assess Associations of Fluoroquinolone Formulary Changes with Susceptibility of Gram-Negative Pathogens and Isolation Rates of Methicillin-Resistant Staphylococcus aureus

Bosso

Mauldin

2006

Antimicrob Agents Chemother

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The use of fluoroquinolones has been linked to increasing bacterial resistance and infection and/or colonization with already resistant pathogens both as a risk factor and based on volume of use. Changes in individual fluoroquinolones used in an institution may also be related to these clinical problems. Interrupted time series analysis, which allows for assessment of the associations of an outcome attributable to a specific event in time, was used to study the effect of changes in our hospital's fluoroquinolone formulary on fluoroquinolone susceptibility rates in select gram-negative pathogens and the methicillin-resistant Staphylococcus aureus (MRSA) isolation rate. Susceptibility rates to ciprofloxacin were considered for the period of 1993 through 2004, while the MRSA isolation rate was assessed from 1995 through 2004. Levofloxacin was added to the formulary in 1999, and gatifloxacin was substituted for levofloxacin in 2001. Statistically significant changes in the already declining rates of susceptibility of Pseudomonas aeruginosa (P, 0.042) and Escherichia coli (P, 0.004) to ciprofloxacin and in the already rising MRSA isolation rate (P, 0.001) were associated with the addition of levofloxacin to the formulary. Substitution of gatifloxacin for levofloxacin on the formulary was associated with reversals in the downward trend in E. coli susceptibility to ciprofloxacin and the upward trend in MRSA isolation rate. No associations were detected on susceptibility of Klebsiella pneumoniae or Proteus mirabilis to ciprofloxacin. These findings suggest that potential changes in susceptibility to fluoroquinolones and isolation of MRSA may vary by both drug and organism.

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Section: Methodsmentioning

confidence: 99%

Using Interrupted Time Series Analysis To Assess Associations of Fluoroquinolone Formulary Changes with Susceptibility of Gram-Negative Pathogens and Isolation Rates of Methicillin-Resistant Staphylococcus aureus

Bosso

Mauldin

2006

Antimicrob Agents Chemother

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“…These cases were selected to complement the ITS analysis described in Chapter 7, Summary of findings for the rapid process improvement workshops included in the interrupted time series. 126,127 The selection criteria were related to the availability of sufficient pre-and post-intervention data to provide sufficient power for the ITS analysis. At least two team members were present throughout the workshops to provide complementary insights, check for consistency and ensure accuracy.…”

Section: Observationsmentioning

confidence: 99%

“…ITS analysis is most effective in detecting the impact of the intervention when the intervention takes place over a short period of time, as opposed to being spread over time. 126 ITS analysis is the strongest observational design for evaluating the impact of interventions and takes into account the trend in outcome measures as well as the pre-intervention level. 127 At the micro level, the impact of selected RPIWs was evaluated using a controlled ITS design.…”

Section: Interrupted Time Seriesmentioning

confidence: 99%

A mixed-methods evaluation of transformational change in NHS North East

Hunter

Erskine

Hicks

et al. 2014

Health Services and Delivery Research

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BackgroundThe North East Transformation System (NETS) was conceived as an experiment in adopting large-scale transformational change across a NHS region in England. Although the NHS in the North East performs well, the health of the population ranks among the poorest in the country. The NETS was viewed as a means of addressing this conundrum. It comprised three components: Vision, Compact and Method.ObjectivesThe evaluation study comprised six elements: a literature review; an evaluation of the evolution and impact of the NETS; an identification of the factors facilitating, and/or acting as barriers to, successful change; an assessment of the role of the NETS project team; establishing how far the changes introduced through the NETS became embedded and sustained; and an evaluation of the impact of the NETS on end users.DesignThe research comprised a longitudinal mixed-methods study conducted over 3.5 years. Research methods included 68 semistructured interviews, observation, two focus groups, documentary analysis and interrupted time series (ITS) analysis. The ITS component comprised analysis of five rapid process improvement workshops in two of the sites.SettingThe research setting was the NHS North East region until its abolition in April 2013 following the UK government’s NHS changes. Fourteen sites were selected for the study, comprising primary care trusts as commissioners, and provider trusts including mental health, community, acute care and ambulance services.ParticipantsThe study respondents were members of staff in the 14 sites drawn from different levels of their organisations.InterventionsThe NETS comprised a complex set of interventions aimed at improving the efficiency and effectiveness of care pathways for staff and patients.Main outcome measuresThe ‘receptive contexts for change’ framework was used to evaluate the transformational change process and its outcomes.Data sourcesQualitative parts of the study drew on semistructured interviews, focus groups, observation and documents. Quantitative parts of the study used routinely collected NHS data.ResultsTransformational change in a complex system takes time and demands consistency, constancy of purpose and organisational stability. The NETS was seriously disrupted by the NHS changes announced in July 2010. Progress was sustained at four of the study sites, but slowed or ceased at the other sites. Leadership style was found to be critical to the success of transformational change.ConclusionsThe NETS was a bold and ambitious initiative which succeeded in bringing about real and lasting change in some parts of the North East. However, it was unable to fully realise its vision and purpose partly because of the widespread reorganisation of the NHS by the new coalition government.Future workThere is a need to develop new methods to understand how change occurs, or fails, in complex settings like the NHS. There is a need for more in-depth studies in those sites that were able to implement and sustain change. This would inform future policy and practice. The results of the quantitative analyses were less conclusive than those obtained by qualitative methods. Further development of mixed-methods approaches would provide additional support for evidence-based decision-making.FundingThe National Institute for Health Research Health Services and Delivery Research programme.

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“…The presence of seasonal and long-term trends complicates interrupted time series designs, but accounting for such factors in the pre-intervention period is the crucial assumption for the validity of any interrupted time series analysis [36,37,44,45]. We used an algorithm [41] to select the most parsimonious model based on pre-recession trends in each demographic group, and it seems plausible that our results differ from prior studies because the pre-intervention trends differ substantially by demographic group.…”

Section: Discussionmentioning

confidence: 99%