Explanation & Elaboration

17. Interpretation

1. Explores possible reasons for differences between observed and expected outcomes
2. Draws inferences consistent with the strength of the data about causal mechanisms and size of observed changes, paying particular attention to components of the intervention and context factors that helped determine the intervention's effectiveness (or lack thereof), and types of settings in which this intervention is most likely to be effective
3. Suggests steps that might be modified to improve future performance
4. Reviews issues of opportunity cost and actual financial cost of the intervention

Example

"...There are at least 2 plausible explanations or the significant reductions in hospital-wide mortality and code rate outside of the pediatric ICU [Intensive Care Unit] setting witnessed at our hospital vs. other pediatric hospitals. First, LPCH [Lucile Packard Children's Hospital] serves a particularly high risk population of hospitalized children. ...As a result, we speculate that LPCH has a higher proportion of children at risk for codes on its medical and surgical wards than do children's hospitals with lower case mix indexes. ...This difference in case mix index likely explains why this study found significant improvements in code rate and mortality rate only when including patients who met RRT [rapid response team] criteria, and why the study by Brilli et al found a significant decrease in code rate per 1000 patient-days only when using a single tailed statistical test. ... A second possible explanation for our improved outcomes is that our postintervention period is substantially longer than both Melbourne's (12 months) and Cincinnati's (8 months).

"T]hese improved outcomes have continued despite turnover among the resident physicians, nurses, and other staff, suggesting that the team rather than the education associated with the rollout is more likely the source of the improvements.... This explanation is supported by the decrease in RRT calls during the 19- month intervention period to levels below the effective threshold suggested by the Institute for Healthcare Improvement (20-25 calls per 1000 discharges).

"... Strategies other than an RRT that identify and respond to patients earlier in the course of a decompensation could have the same effect as an RRT. For example, 1 potential strategy to decrease codes outside of the ICU [intensive care unit] setting suggested by Winters et al is the integration of hospitalists. We are in a good position to evaluate a hospitalist intervention at a local level, because we introduced a medical-surgical ward hospitalist service 26 months (July 2003) before RRT implementation. Assuming that there was no delayed effect, the introduction of the hospitalist service, although valuable for multiple reasons, did not affect either mortality rate or code rate outside of the ICU setting....

"... Future research should focus on replicating these findings in other pediatric inpatient settings, including settings where children are treated in predominantly adult-focused hospitals, developing efficient methods for implementing RRTs, and evaluating the cost effectiveness of this intervention.

"...At LPCH, the RRT program was designed and implemented with no additional increase in funding for staffing, a decision supported by the time allocation required for calls during the first 19 months of the intervention." [40]

Elaboration

An improvement project is typically focused on identifying an association between an intervention(s) and some outcomes. The nature and degree of the change in outcome may arise from theory, research, or prior improvement studies and is usually stated in the Introduction section of the paper see Item 5.Intended Improvement and/or Item 6. Study Question.  If the actual outcome deviates from the expected outcome or if the outcome is different than that observed in other published studies (as in the example above), the interpretation should include a discussion of the factors that prevented the expected outcome from occurring. In quality improvement studies, the explanation should include the situation factors (context) that may have led to these differences.

The interpretation section elaborates on the information reported earlier in the results section by describing the practical implications of findings. A statistical difference in outcomes is not sufficient as an explanation, so the internal and external implications of the findings should be explored. Competing theories and other causes of the outcomes should be investigated, such as the discussion regarding hospitalists in the example. Sources of bias and confounding are often addressed in Item 16. Limitations section, but may be introduced here also. The intricacies about the various interventions and the contextual factors that may interact with the interventions in other settings could also be noted.

The interpretation often includes "lessons learned," observations, and suggestions for improving the implementation of the interventions in other organizations. This may include the following:
• Background or cultural elements that should be in place before attempting implementation of the intervention.
• Suggested sequence of steps for implementation
• Possible adaptations of the interventions
• Additional studies that could reinforce or enhance the findings

The example includes a description of the possible future exploration regarding RRTs. This helps the reader identify where these current findings may and may not be applicable, thus enhancing the ability to interpret the context of the results.

Finally, it is often helpful to include some information that is relevant to the business case for the intervention that could help readers with the decision whether to adopt the change. One way to do this is to describe the resource and cost information associated with the reported study as in the above example. The authors also may describe the financial implications of the change in outcomes observed in the study. Authors should be aware of the intricacies and details that are required for an in depth economic analysis. The ISPOR RCT-CEA guidelines for cost-effectiveness studies that are alongside clinical trials may be helpful. [41]

References

40. Sharek PJ, Parast LM, Leong K, et al. Effect of a rapid response team on hospital-wide mortality and code rates outside the ICU in a Children's Hospital. JAMA : the journal of the American Medical Association. 2007;298(19):2267-2274.

41. Ramsey S, Willke R, Briggs A, et al. Good Research Practices for Cost-Effectiveness Analysis Alongside Clinical Trials: The ISPOR RCT-CEA Task Force Report. Value in Health. 2005;8(5):521-533.

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