Economic evaluation of implementation strategies in health care

Economic evaluations can inform decisions about the efficiency and allocation of resources to implementation strategies? strategies explicitly designed to inform care providers and patients about the best available research evidence and to enhance its use in their practices. These strategies are increasingly popular in health care, especially in light of growing concerns about quality of care and limits on resources. But such concerns have hardly motivated health authorities and other decision-makers to spend on some form of economic evaluation in their assessments of implementation strategies. This editorial addresses the importance of economic evaluation in the context of implementation science? particularly, how these analyses can be most efficiently incorporated into decision-making processes about implementation strategies

Cost data in implementation science: categories and approaches to costing

A lack of cost information has been cited as a barrier to implementation and a limitation of implementation research. This paper explains how implementation researchers might optimize their measurement and inclusion of costs, building on traditional economic evaluations comparing costs and effectiveness of health interventions. The objective of all economic evaluation is to inform decision-making for resource allocation and to measure costs that reflect opportunity costs-the value of resource inputs in their next best alternative use, which generally vary by decision-maker perspective(s) and time horizon(s). Analyses that examine different perspectives or time horizons must consider cost estimation accuracy, because over longer time horizons, all costs are variable; however, with shorter time horizons and narrower perspectives, one must differentiate the fixed and variable costs, with fixed costs generally excluded from the evaluation. This paper defines relevant costs, identifies sources of cost data, and discusses cost relevance to potential decision-makers contemplating or implementing evidence-based interventions. Costs may come from the healthcare sector, informal healthcare sector, patient, participant or caregiver, and other sectors such as housing, criminal justice, social services, and education. Finally, we define and consider the relevance of costs by phase of implementation and time horizon, including pre-implementation and planning, implementation, intervention, downstream, and adaptation, and through replication, sustainment, de-implementation, or spread

Area level impacts on emergency hospital admissions of the integrated care and support pioneer programme in England: difference-in-differences analysis.

OBJECTIVE: To examine whether any differential change in emergency admissions could be attributed to integrated care by comparing pioneer and non-pioneer populations from a pre-pioneer baseline period (April 2010 to March 2013) over two follow-up periods: to 2014/2015 and to 2015/2016. DESIGN: Difference-in-differences analysis of emergency hospital admissions from English Hospital Episode Statistics. SETTING: Local authorities in England classified as either pioneer or non-pioneer. PARTICIPANTS: Emergency admissions to all NHS hospitals in England with local authority determined by area of residence of the patient. INTERVENTION: Wave 1 of the integrated care and support pioneer programme announced in November 2013. PRIMARY OUTCOME MEASURE: Change in hospital emergency admissions. RESULTS: The increase in the pioneer emergency admission rate from baseline to 2014/2015 was smaller at 1.93% and significantly different from that of the non-pioneers at 4.84% (p=0.0379). The increase in the pioneer emergency admission rate from baseline to 2015/2016 was again smaller than for the non-pioneers but the difference was not statistically significant (p=0.1879). CONCLUSIONS: It is ambitious to expect unequivocal changes in a high level and indirect indicator of health and social care integration such as emergency hospital admissions to arise as a result of the changes in local health and social care provision across organisations brought about by the pioneers in their early years. We should treat any sign that the pioneers have had such an impact with caution. Nevertheless, there does seem to be an indication from the current analysis that there were some changes in hospital use associated with the first year of pioneer status that are worthy of further exploration

Effects of mental health status during adolescence on primary care costs in adulthood across three British cohorts

PURPOSE: This study examines the association between mental health problems in adolescence and general practice (GP) costs during adulthood up to age 50 in the UK. METHODS: We conducted secondary analyses of three British birth cohorts (individuals born in single weeks in 1946, 1958 and 1970). Data for the three cohorts were analysed separately. All respondents who participated in the cohort studies were included. Adolescent mental health status was assessed in each cohort using the Rutter scale (or, for one cohort, a forerunner of that scale) completed in interviews with parents and teachers when cohort members were aged around 16. Presence and severity of conduct and emotional problems were modelled as independent variables in two-part regression models in which the dependent variable was costs of GP services from data collection sweeps up to mid-adulthood. All analyses were adjusted for covariates (cognitive ability, mother's education, housing tenure, father's social class and childhood physical disability). RESULTS: Adolescent conduct and emotional problems, particularly when coexisting, were associated with relatively high GP costs in adulthood up to age 50. Associations were generally stronger in females than males. CONCLUSION: Associations between adolescent mental health problems and annual GP cost were evident decades later, to age 50, suggesting that there could be significant future savings to healthcare budgets if rates of adolescent conduct and emotional problems could be reduced. TRIAL REGISTRATION: Not applicable

Minimal modeling approaches to value of information analysis for health research.

Value of information (VOI) techniques can provide estimates of the expected benefits from clinical research studies that can inform decisions about the design and priority of those studies. Most VOI studies use decision-analytic models to characterize the uncertainty of the effects of interventions on health outcomes, but the complexity of constructing such models can pose barriers to some practical applications of VOI. However, because some clinical studies can directly characterize uncertainty in health outcomes, it may sometimes be possible to perform VOI analysis with only minimal modeling. This article 1) develops a framework to define and classify minimal modeling approaches to VOI, 2) reviews existing VOI studies that apply minimal modeling approaches, and 3) illustrates and discusses the application of the minimal modeling to 2 new clinical applications to which the approach appears well suited because clinical trials with comprehensive outcomes provide preliminary estimates of the uncertainty in outcomes. The authors conclude that minimal modeling approaches to VOI can be readily applied in some instances to estimate the expected benefits of clinical research