> For the complete documentation index, see [llms.txt](https://docs.nested-knowledge.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.nested-knowledge.com/get-started/demo-nests/economic-tlr-caregiving-cost-effectiveness-of-alzheimers-and-dementia.md). # Economic TLR: Caregiving Cost-effectiveness of Alzheimer's and Dementia A walkthrough of the economic targeted literature review on caregiving cost-effectiveness of Alzheimer's and dementia. ### About This Review As dementia progresses, caregiving needs intensify — and caregiving models become one of the biggest levers on both patient outcomes and total cost of care. This nest is a targeted literature review (TLR) of economic evaluations and cost analyses of dementia caregiving, asking a specifically economic question: are caregiving interventions and care models cost-effective, and where does the value come from? This is the nest to open if your work centers on building an economic case rather than a clinical one — total costs, cost components, QALYs, and ICERs, viewed from both payer and societal perspectives. It's built to show how a nest's tag hierarchy and Dashboard can be shaped specifically around the outputs an HTA submission or cost-effectiveness model actually needs. Want to move straight to a Q\&A with the evidence? Jump to Synthesis Chat ### Search The review draws from PubMed via API and Embase via file import. **Smart Search** generated AI-assisted queries for PubMed. Building precise search queries by hand is one of the slower parts of any review — Smart Search compresses that step so the team can move to screening faster after thorough checking. Economic TLRs like this one are typically scoped more narrowly than a clinical SLR — searching for economic evaluations and cost analyses specifically, rather than every RCT on a therapeutic class — because the question isn't "does the intervention work," it's "what does it cost, and against what benefit." That narrower scope is part of what keeps a TLR fast enough to support planning timelines. **Try it yourself:** Run Smart Search against a related disease area and compare the queries it generates to the ones already in this nest.

Smart Search queries for dementia caregiving cost-effectiveness. — Smart Search queries for the economic review.

**See also:** [Literature Search](/review-workflow/literature-search.md), [Smart Search](/review-workflow/literature-search/ai-tools-in-search/smart-search.md), and [Import Search Files](/review-workflow/literature-search/add-search/import-search-files.md) ### Screening Exclusion-based Screening criteria was defined. Records were screened separately at abstract and full-text level (**Two Pass Screening**), with two independent reviewers per record and a third reviewer adjudicating any disagreement (**Dual Screening**). After training, **Robot Screener** filled one of the two reviewer seats. Only available in Abstract Screening. This combination matters for a review of this scale and stakes: two independent decisions per record catch errors a single reviewer would miss, and adjudication resolves disagreement with a documented, third-party judgment. Robot Screener demonstrates how an automated reviewer participates the same way a human reviewer does — it answers the same criteria and reaches its own decision, but it never has the final word. A second reviewer and a human adjudicator are still required before any record's fate is settled. **Try it yourself:** Select Adjudicate Screening under Abstract Screening. View a study with two screening decisions under the Abstract Screenings tab to compare human vs Robot Screener decision side-by-side.

Abstract screening decisions from a reviewer and Robot Screener. — Compare reviewer and Robot Screener decisions during abstract screening.

**See also:** [Configure Screening](/review-workflow/screening/configure-screening.md), [Robot Screener](/review-workflow/screening/exclusion-based-screening/robot-screener.md), and [Adjudicate Records](/review-workflow/screening/adjudicate-records.md) ### Tagging and Extraction **Adaptive Smart Tags** captured cost components — medical, long-term care, and informal care — alongside QALYs and incremental cost-effectiveness ratios (ICERs), across studies spanning multiple geographies and both payer and societal perspectives. Economic outcomes are reported in wildly inconsistent formats from study to study: different currencies, time horizons, perspectives, and cost categories. A tag hierarchy purpose-built for this review's outcomes — rather than a generic clinical extraction template — is what makes it possible to pull directly comparable cost components and ICERs out of that inconsistency, study after study, without re-deriving the structure each time. **Try it yourself:** Examine applied tags using the icon or open a study in Tagging to view extracted data.

Tagging view showing extracted cost-effectiveness data. — Extracted economic data in Tagging.

Tagging view showing applied economic tags for a study. — Applied economic tags for an included study.

**See also:** [Configure Tagging](/review-workflow/tagging/configure-tagging.md), [Adaptive Smart Tags](/review-workflow/tagging/ai-tools-in-tagging/adaptive-smart-tags.md), and [Apply Tags](/review-workflow/tagging/apply-tags.md) ### Study Inspector **Study Inspector** lets a reviewer check the whole set of included economic evaluations at once, rather than study by study — useful here because cost studies vary so much in perspective, geography, and time horizon that spotting patterns, or gaps, across the full set matters as much as any single extraction. A health economist using this nest would use Study Inspector to, for example: filter to only societal-perspective studies before building a Dashboard view meant for a societal-perspective argument; check which included studies report an ICER at all, since not every cost analysis does; or export the subset of U.S.-based studies through Download from Inspector to compare directly against a specific willingness-to-pay threshold. **Try it yourself:** Filter to studies from a single geography, and see how the ICER range narrows compared with the full multi-geography set.

Study Inspector showing included dementia caregiving economic evaluations. — Study Inspector for the economic evidence set.

**See also:** [Study Inspector](/review-workflow/study-inspector.md), [Filters Available in Study Inspector](/review-workflow/study-inspector/filter-studies/filters-available-in-study-inspector.md), and [Download from Inspector](/review-workflow/study-inspector/download-from-inspector.md) ### Synthesis However a nest is built, opening **Synthesis** surfaces the same set of views automatically, drawing on whatever's already been completed elsewhere in the nest — none of it needs to be built from scratch. **Qualitative Synthesis** generates on its own from applied tags, giving a synthesis-ready view of how those tags translate into findings. The **PRISMA** chart auto-populates the same way from screening decisions, producing a live, auditable count of records at each stage without anyone building it by hand. **Quantitative Synthesis** and **Critical Appraisal** visuals appear alongside these two, but only where that stage was actually completed in the nest — a review that skipped Meta-Analytical Extraction, for instance, simply won't have a Quantitative Synthesis view to show. **Synthesis Chat** is available immediately regardless of how much of the nest is populated — it's a conversational way to query whatever data exists so far, not a view that waits on a specific stage finishing. **Dashboard** is the one exception: it has to be built rather than generated, so it only appears if someone has configured one in this nest. **Smart Insights** are built here– they are generated AI-written text summaries from the extracted data, drawn together into a competitive landscape narrative. **See also:** [Synthesis](/review-workflow/synthesis.md), [Qualitative Synthesis](/review-workflow/synthesis/navigate-synthesis-outputs/qualitative-synthesis.md), [PRISMA Chart](/review-workflow/synthesis/navigate-synthesis-outputs/prisma-chart.md), [Meta-Analytical Extraction](/review-workflow/meta-analytical-extraction.md), [Quantitative Synthesis](/review-workflow/synthesis/navigate-synthesis-outputs/quantitative-synthesis.md), [Critical Appraisal](/review-workflow/critical-appraisal.md), [Critical Appraisal Outputs](/review-workflow/synthesis/navigate-synthesis-outputs/critical-appraisal-outputs.md), [Synthesis Chat](/review-workflow/synthesis/navigate-synthesis-outputs/synthesis-chat.md), [Dashboard Editor](/review-workflow/synthesis/set-up-synthesis-outputs/dashboard-editor.md), and [Smart Insights](/review-workflow/synthesis/set-up-synthesis-outputs/smart-insights.md) #### Dashboard The cost components, QALYs, and ICERs captured in Tagging are organized in **Dashboard**, supported by **Smart Insights**, into the summary view a reviewer would actually use to compare interventions and care settings at a glance. As with every nest, Dashboard is a synthesis-side tool, not a data-collection one: it aggregates and displays what Tagging has already captured, rather than gathering anything new. If a cost figure on Dashboard looks off, the fix is in the Adaptive Smart Tags extraction behind it, not in Dashboard itself. **Try it yourself:** Maximise the study insight cards to interact with the data, or download table cards to view data in Excel.

Dashboard summarizing cost components, QALYs, and ICERs. — Dashboard summary of extracted economic data.

**See also:** [Dashboard Editor](/review-workflow/synthesis/set-up-synthesis-outputs/dashboard-editor.md), [Dashboard in Synthesis](/review-workflow/synthesis/navigate-synthesis-outputs/dashboard-in-synthesis.md), and [Smart Insights](/review-workflow/synthesis/set-up-synthesis-outputs/smart-insights.md) #### Synthesis Chat **Synthesis Chat** is a direct way to query this nest's cost data without building a Dashboard view first — ask it which interventions were reported as cost-saving outright, rather than merely cost-effective, and it answers from the studies actually extracted here. **Try it yourself:** Ask Synthesis Chat what evidence exists for a specific care setting — home-based care, for example — and see how it distinguishes that from the residential-care findings.

Synthesis Chat answering a dementia caregiving cost question. — Synthesis Chat response based on extracted economic data.

**See also:** [Synthesis Chat](/review-workflow/synthesis/navigate-synthesis-outputs/synthesis-chat.md) ### Next Steps


Start A Pilot Trial	Set up a pilot trial of Nested Knowledge.	Start a Pilot Trial
Core Concepts	Understand the objects and terminology used in Nested Knowledge.	Core Concepts
Nest Setup	Learn how to set up your review in Nested Knowledge.	Nest Setup
Quickstart	Start building your first nest.	Quickstart

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