SynthesisGenetics in medicine : official journal of the American College of Medical Genetics2019
Developing a genetic services assessment tool to inform quality improvement efforts in state genetic service delivery.
Synthesis in Genetics in medicine : official journal of the American College of Medical Genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- An introduction to Delphi studies and consensus methods for genetic counselors.Journal of genetic counseling · 2025Article
- Genetic Testing for Cancer Risk and Perceived Importance of Genetic Information Among US Population by Race and Ethnicity: a Cross-sectional Study.Journal of racial and ethnic health disparities · 2024Article
- Barriers and Facilitators to Genetic Service Delivery Models: Scoping Review.Interactive journal of medical research · 2021Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe Institute of Medicine recommended the utilization of metrics to improve quality in health care, although they have rarely been used in genetics. This study developed and tested a set of metrics for a quality assessment tool for genetic services
methodsA systematic review of literature, guidelines, and consensus statements identified candidate measures for a possible assessment tool. An expert panel conducted a modified Delphi technique to rank the metrics. Ratings were computed to generate a score for each metric, creating a set of metrics for consensus discussions, pilot testing, and feasibility testing in eight Midwestern states.
resultsThe panel reduced 61 candidate metrics to 21 for pilot testing in two states, which further limited and refined the set to 16 metrics. These 16 were categorized into five domains: service capacity, access to care, data systems, performance reporting, and workforce. Further feasibility testing in one Regional Genetics Collaborative identified the tool's usefulness and barriers to implementation.
conclusionsThese quality metrics for both clinical and public health genetics across the lifespan may help medical professionals and policymakers evaluate quality and cost-effectiveness of genetic services on a statewide basis and stimulate outcome-oriented, health services research in medical genetics and genomics.
Indexed as
Identifiers
30214070What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.