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Healthcare cost, quality, practices
Research Guide
What is Healthcare cost, quality, practices?
Healthcare cost, quality, practices refers to strategies and initiatives aimed at reducing the overuse of low-value health care services, particularly in the United States, through concepts like 'Choosing Wisely', de-implementation of unnecessary practices, and efforts to address health care waste, physician perspectives, patient engagement, and quality improvement to impact costs.
This field encompasses 41,078 works focused on reducing overuse of low-value care services. Key areas include the 'Choosing Wisely' campaign, health care waste reduction, and de-implementation of unnecessary medical practices. Growth rate over the past five years is not available in the provided data.
Topic Hierarchy
Research Sub-Topics
Choosing Wisely Campaign Effectiveness
This sub-topic evaluates the impact of the Choosing Wisely initiative on reducing low-value care through physician education and guideline dissemination. Researchers conduct cluster-randomized trials and cost analyses.
De-Implementation of Low-Value Practices
This sub-topic studies strategies to discontinue unnecessary medical interventions like excessive imaging or antibiotics via behavioral interventions. Researchers develop frameworks for audit and feedback systems.
Physician Perspectives on Medical Overuse
This sub-topic explores barriers and facilitators to reducing overuse from clinicians' viewpoints using qualitative interviews and surveys. Researchers identify cognitive biases and systemic pressures.
Patient Engagement in Reducing Low-Value Care
This sub-topic investigates shared decision-making tools and communication strategies to empower patients against unnecessary services. Researchers test decision aids in randomized trials.
Economic Burden of Healthcare Waste
This sub-topic quantifies costs of low-value services using claims data and models their impact on national budgets. Researchers project savings from targeted interventions.
Why It Matters
Reducing overuse of low-value care directly lowers health care costs while maintaining or improving quality, as seen in initiatives targeting medical overuse in the US. For instance, Obermeyer et al. (2019) in "Dissecting racial bias in an algorithm used to manage the health of populations" revealed that a widely used commercial algorithm underestimated health needs for Black patients compared to White patients at the same risk level, leading to sicker Black patients receiving fewer resources and highlighting inequities that inflate costs through inefficient allocation. Patient decision aids, as reviewed by Stacey et al. (2017) in "Decision aids for people facing health treatment or screening decisions", increase knowledge, clarify values, and promote active roles in decision-making, reducing unnecessary interventions. Methodological tools like the Cochrane risk of bias assessment by Higgins et al. (2011) in "The Cochrane Collaboration's tool for assessing risk of bias in randomised trials" ensure reliable evidence for de-implementation, while reporting guidelines in "Strengthening the reporting of observational studies in epidemiology (STROBE) statement" by von Elm et al. (2007) support quality improvement by enhancing research utility.
Reading Guide
Where to Start
"The Cochrane Collaboration's tool for assessing risk of bias in randomised trials" by Higgins et al. (2011), as it provides a foundational method (32,763 citations) to evaluate evidence quality essential for understanding practices aimed at reducing low-value care.
Key Papers Explained
Higgins et al. (2011) in "The Cochrane Collaboration's tool for assessing risk of bias in randomised trials" establishes bias assessment for trials, which von Elm et al. (2007) in "Strengthening the reporting of observational studies in epidemiology (STROBE) statement" extends to observational studies for comprehensive evidence quality. Stacey et al. (2017) in "Decision aids for people facing health treatment or screening decisions" applies such evidence to patient engagement tools that reduce overuse. Obermeyer et al. (2019) in "Dissecting racial bias in an algorithm used to manage the health of populations" uses robust methods to expose biases affecting cost and quality practices. Institute of Medicine (2000) in "To Err Is Human" lays groundwork for error reduction strategies underpinning modern quality efforts.
Paper Timeline
Most-cited paper highlighted in red. Papers ordered chronologically.
Advanced Directions
Current frontiers involve applying bias assessment tools and decision aids to de-implement low-value care under 'Choosing Wisely', with emphasis on addressing algorithmic biases identified by Obermeyer et al. (2019). No recent preprints or news coverage available, so focus remains on established high-citation works like KDIGO 2024 guidelines by Stevens et al. for chronic kidney disease management.
Papers at a Glance
| # | Paper | Year | Venue | Citations | Open Access |
|---|---|---|---|---|---|
| 1 | The Cochrane Collaboration's tool for assessing risk of bias i... | 2011 | BMJ | 32.8K | ✓ |
| 2 | Global burden of 369 diseases and injuries in 204 countries an... | 2020 | The Lancet | 18.0K | ✓ |
| 3 | To Err Is Human | 2000 | National Academies Pre... | 14.1K | ✕ |
| 4 | Strengthening the reporting of observational studies in epidem... | 2007 | BMJ | 9.0K | ✓ |
| 5 | Global, regional, and national life expectancy, all-cause mort... | 2016 | The Lancet | 6.6K | ✓ |
| 6 | Decision aids for people facing health treatment or screening ... | 2017 | Cochrane Database of S... | 6.5K | ✓ |
| 7 | KDIGO 2024 Clinical Practice Guideline for the Evaluation and ... | 2024 | Kidney International | 6.4K | ✓ |
| 8 | Global, regional, and national burden of chronic kidney diseas... | 2020 | The Lancet | 6.1K | ✓ |
| 9 | EQ-SD: a measure of health status from the EuroQol Group | 2001 | Annals of Medicine | 5.4K | ✓ |
| 10 | Dissecting racial bias in an algorithm used to manage the heal... | 2019 | Science | 5.3K | ✓ |
Frequently Asked Questions
What is the focus of healthcare cost, quality, practices research?
This field centers on strategies to reduce overuse of low-value health care services in the US, including 'Choosing Wisely' and de-implementation of unnecessary practices. It addresses health care waste, physician perspectives, patient engagement, and quality improvement to lower costs. The cluster includes 41,078 works.
How do decision aids improve healthcare practices?
Decision aids make people more knowledgeable, better informed about values, and clearer on risks compared to usual care. They promote active decision-making roles and accurate risk perceptions. Stacey et al. (2017) in "Decision aids for people facing health treatment or screening decisions" provide evidence across various contexts.
What methodological tools assess quality in healthcare research?
The Cochrane Collaboration’s tool evaluates risk of bias in randomised trials by addressing flaws in design, conduct, analysis, and reporting. Higgins et al. (2011) in "The Cochrane Collaboration's tool for assessing risk of bias in randomised trials" (32,763 citations) makes this process clearer and more accurate. STROBE guidelines by von Elm et al. (2007) improve reporting of observational studies.
Why do algorithms exhibit racial bias in healthcare management?
A widely used algorithm assigns the same risk level to Black patients who are sicker than White patients, leading to under-allocation of care. Obermeyer et al. (2019) in "Dissecting racial bias in an algorithm used to manage the health of populations" identified this bias in US health care systems. It affects resource distribution and cost efficiency.
What is the role of patient engagement in reducing low-value care?
Patient engagement supports de-implementation of unnecessary services and quality improvement. It aligns with 'Choosing Wisely' to address overuse and waste. Decision aids enhance this by improving knowledge and participation, as shown by Stacey et al. (2017).
How does 'To Err Is Human' relate to healthcare quality?
"To Err Is Human" by Institute of Medicine (2000) presents a strategy for governments, health personnel, industry, and consumers to reduce medical errors. It emphasizes holistic approaches to improve safety and quality. The report has 14,061 citations.
Open Research Questions
- ? How can racial biases in health management algorithms be eliminated to ensure equitable resource allocation across populations?
- ? What specific de-implementation strategies most effectively reduce overuse of low-value care without compromising patient outcomes?
- ? In what ways do physician perspectives influence the adoption of 'Choosing Wisely' recommendations in clinical practice?
- ? How do patient decision aids scale to address health care waste on a national level?
- ? What metrics best measure the impact of quality improvement initiatives on overall health care costs?
Recent Trends
The field maintains 41,078 works with no specified five-year growth rate.
High-citation papers like "The Cochrane Collaboration's tool for assessing risk of bias in randomised trials" by Higgins et al. (2011, 32,763 citations) and Global Burden studies by Vos et al. (2020, 17,989 citations) dominate, indicating sustained focus on evidence quality and disease burden informing cost and overuse reduction.
No recent preprints or news available.
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