Health Service Implementation Interventions: Costing and Evaluation

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Questions and Answers

Which method is the most accurate for determining intervention costs?

  • Retrospective data collection
  • Primary data collection
  • Prospective data collection (correct)
  • Epidemiological modeling

What is the challenge in determining the cost of HSIIs?

  • Lack of fidelity
  • Protective commercial interests
  • Both A and B (correct)
  • None of the above

What is the recommended approach when making assumptions in the evaluation report?

  • Keep them implicit
  • State them explicitly (correct)
  • Ignore them
  • None of the above

Which method can be used to relate process measures to health outcomes?

<p>Epidemiological modeling (B)</p> Signup and view all the answers

What is the challenge in calculating the economic impact from the societal perspective in low-income settings?

<p>Both A and B (C)</p> Signup and view all the answers

Which tool offers estimates for many priority health interventions?

<p>The Lives Saved Tool (LiST (A)</p> Signup and view all the answers

Which method is often more feasible and accurate than measuring patient health outcomes in HSIIs?

<p>Measuring process measures (B)</p> Signup and view all the answers

What can be complex when costing the effects for medical error reduction?

<p>Calculations involving multiple health outcomes (A)</p> Signup and view all the answers

Which methods can be used to address uncertainty in the link between processes and outcomes?

<p>Sensitivity analysis and Monte Carlo simulation (A)</p> Signup and view all the answers

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Study Notes

  • In HSIIs, measuring process measures is often more feasible and accurate than measuring patient health outcomes.
  • It can be difficult to determine the cost of HSIIs due to lack of fidelity and protective commercial interests.
  • Prospective data collection is the most accurate method for determining intervention costs.
  • Assumptions need to be stated explicitly in the evaluation report.
  • Costing of effects for medical error reduction can be complex and involve multiple health outcomes.
  • Economic impact from the societal perspective may be difficult to calculate in low-income settings.
  • Primary data collection can be expensive and challenging.
  • Epidemiological modeling can be used to relate process measures to health outcomes.
  • The Lives Saved Tool (LiST) offers estimates for many priority health interventions.
  • Sensitivity analysis and Monte Carlo simulation can be used to address uncertainty in the link between processes and outcomes.

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