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Julian Bell
Julian Bell

Total Cost Management Framework Pdf 17


Our definition of downstream costs is different from traditional clinical cost-effectiveness analytic methods [13, 14]. We suggest separating implementation strategy and intervention costs from subsequent downstream cost impacts of the intervention. Many implementation studies measure the implementation and intervention costs, but not further downstream costs. This is sometimes justified because prior research showed that increasing intervention use was cost-effective, with effective implementation leading to improved health outcomes that extend life. Future costs reflect resources associated with future changes that arise from an intervention and its implementation. For example, a seemingly simple prevention effort such as an implementation trial to improve the use of nicotine replacement therapy for smoking cessation might center on whether the implementation trial increased the costs of delivering nicotine replacement therapy, assuming that the downstream benefits of smoking cessation are known. There is a danger, however, in assuming the intervention is cost-effective, because by adding implementation costs, in many cases, the cost-effectiveness of the intervention could decrease [15]. Incorporating future costs and savings into the analysis may counterbalance the implementation costs based on subsequent reduction in lung and heart disease. Any implementation strategy and intervention could lead to intended and unintended consequences in the near and longer term that should be measured. When enumerating intervention and downstream costs, it is possible to include the identical costs or cost components in multiple categories. However, this should be avoided because it can lead to double counting and a biased, overestimated total cost.




Total Cost Management Framework Pdf 17



Traditional methods in economic evaluation suggest excluding research and development costs of the implementation strategies or interventions themselves. Research-specific activities that were essential to designing and developing the original implementation generally should be excluded, sometimes called pre-implementation or design components [9, 28]. For example, we would exclude the time required for survey completion or laboratory tests that were only used for evaluating implementation study outcomes, if those surveys or laboratory tests would not be part of usual care [3, 29]. Two exceptions to this approach may be considered. The first is when the stakeholder wants to know the total cost of implementation, including these research-specific and sunk costs. The second is when there are research activities required for implementation planning or adaptation within a specific context. In both cases, these costs should be included.


In the long term, when scale of production can see large changes in variation, all costs can be considered variable [30]. In the short run, fixed costs should be excluded from the evaluation because they create no opportunity cost. There are two challenges with this approach. First, it is often possible to convert fixed costs to variable costs. For example, a hospital can convert inpatient beds to an outpatient clinic, or it could sell the space. In doing so, the hospital is converting the fixed costs into another type of fixed cost or a variable asset. Second, many implementation scientists use shorter time horizons, or a range of time horizons, where some costs may be fixed or variable, depending on the time horizon. In analysis with very short time horizons, fixed costs cannot be converted. However, as the time horizon increases, one has more options for converting fixed costs to variable, and this creates substantial analytic complexity. New healthcare evidence and interventions often prompt organizations and practitioners to reallocate inputs that can be changed immediately and reconsider what care and services to produce from all available resources, especially in the long run. Including fixed costs inappropriately would bias the total costs upwards. Implementation analyses should differentiate between fixed and variable costs whenever possible. Typically, fixed costs should be excluded from the evaluation unless the analysis uses a time horizon where the fixed costs may be converted to variable costs.


Micro-costing has been used widely in the health economics literature. This involves tracking all of the inputs used to make a product or provide a service. Costs are estimated by multiplying the quantity of these inputs by their input costs. Many implementation studies will estimate costs using micro-costing methods, which can vary in their precision. The term micro-costing methods refers to a set of similar methods with different names, such as time and motion (TM) studies or time-driven activity-based costing (TD-ABC). Both TM and TD-ABC involve tracking the time it takes to conduct activities. Often process maps are linked to specific activities, resources, and events and their frequencies are calculated. The time for each activity is multiplied by appropriate wage rates and then summed to estimate total costs [33]. Micro-costing is most frequently used to estimate the cost of an implementation strategy.


Micro-costing is prohibitively time consuming for estimating the cost of an inpatient stay. Fortunately, some organizations track labor and supply costs using activity-based cost (ABC) accounting databases to estimate their production costs. These systems track the variable costs provided to each patient. These databases also track fixed, capital costs, including equipment and space, and hospital overhead (e.g., utilities, human resources, security). ABC databases have become the gold standard for estimating healthcare costs in economic evaluation [35]. These systems estimate the production cost and often include subtotals that can be useful for implementation researchers. While beneficial for the specific system costs, the potential limitation of ABC systems is that the production costs reflect only that specific organization or health system and all its unique attributes.


As a rule, implementation scientists should sum the total costs of an implementation strategy and its impacts (and perhaps by stakeholder perspective) within an explicit time period (Table 1). This may be insufficient if such total costs vary across sites, however, because most decision-makers want to know what it would cost to adopt a strategy or program in their setting. Most costs will vary by some parameter (e.g., number of clinical staff, sites, participants) and over time. Implementation scientists will need to explore and report on such variation, so that decision-makers can anticipate or model the cost of the implementation strategy in new settings (or time periods).


In a study comparing group-based versus individual-based multidimensional-treatment foster care, the authors measured costs of feasibility, planning meetings, selection of service providers, staff training, fidelity monitoring and review, site visits, and feedback by stages of progress toward implementation [9]. By capturing subtotaled resources used (e.g., staff hours by job type, office space) and unit prices (e.g., wage rates, rent) and subtotaled implementation costs by week or month and by activity type (e.g., meetings, training), the analyst can conduct a more detailed analysis of costs. In particular, it would allow learning about such cost aspects as site-level variation in multi-site studies and whether costs change over time, potentially due to learning or efficiencies.


Ideally, implementation scientists should report both total intervention implementation costs and more granular cost measures. Because implementation strategies often target behavior change for organizations or professionals, the cost per practice or organization, per professional, or per end-user may be suitable metrics for the decision-maker. However, the major limitation of such denominators is the inability to attribute costs to a patient or participant and therefore to a subsequent health outcome; ultimately, the goal of implementing evidence-based interventions is to improve health outcomes and population health.


Oracle Tuxedo is #1 application server for C, C++, COBOL, Java and dynamic language applications in private cloud or traditional data center environments. Oracle Tuxedo provides a highly reliable and linearly scalable platform to develop, deploy and manage mission-critical applications. Oracle Tuxedo provides optimized communication among applications written in multiple programming languages (C, C++, COBOL, Java, PHP, Python and Ruby), which co-exist in the same container. Oracle Tuxedo includes various tools for application development, deployment and management to lower total cost of ownership.


Assigning clear roles and responsibilities for managing third-party relationships and integrating the bank's third-party risk management process with its enterprise risk management framework enables continuous oversight and accountability.


Conversely, strategic risk can arise if a bank does not use third parties when it is prudent to do so. For example, a bank may introduce strategic risk when it does not leverage third parties that possess greater expertise than the bank does internally, when the third party can more cost effectively supplement internal expertise, or when the third party is more efficient at providing a service with better risk management than the bank can provide internally.


You can use the billing and cost management APIs in many scenarios to answer cost-related and usage-related questions. Common scenarios and how to use the different APIs to achieve those scenarios are outlined below.


A core definition of total quality management (TQM) describes a management approach to long-term success through customer satisfaction. In a TQM effort, all members of an organization participate in improving processes, products, services, and the culture in which they work.


TQM can be summarized as a management system for a customer-focused organization that involves all employees in continual improvement. It uses strategy, data, and effective communications to integrate the quality discipline into the culture and activities of the organization. Many of these concepts are present in modern quality management systems, the successor to TQM. Here are the 8 principles of total quality management:


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