Dataset Information

A Patient Safety Toolkit for Family Practices.

ABSTRACT: OBJECTIVE:Major gaps remain in our understanding of primary care patient safety. We describe a toolkit for measuring patient safety in family practices. METHODS:Six tools were used in 46 practices. These tools were as follows: National Health Service Education for Scotland Trigger Tool, National Health Service Education for Scotland Medicines Reconciliation Tool, Primary Care Safequest, Prescribing Safety Indicators, Patient Reported Experiences and Outcomes of Safety in Primary Care, and Concise Safe Systems Checklist. RESULTS:Primary Care Safequest showed that most practices had a well-developed safety climate. However, the trigger tool revealed that a quarter of events identified were associated with moderate or substantial harm, with a third originating in primary care and avoidable. Although medicines reconciliation was undertaken within 2 days in more than 70% of cases, necessary discussions with a patient/carer did not always occur. The prescribing safety indicators identified 1435 instances of potentially hazardous prescribing or lack of recommended monitoring (from 92,649 patients). The Concise Safe Systems Checklist found that 25% of staff thought that their practice provided inadequate follow-up for vulnerable patients discharged from hospital and inadequate monitoring of noncollection of prescriptions. Most patients had a positive perception of the safety of their practice although 45% identified at least one safety problem in the past year. CONCLUSIONS:Patient safety is complex and multidimensional. The Patient Safety Toolkit is easy to use and hosted on a single platform with a collection of tools generating practical and actionable information. It enables family practices to identify safety deficits that they can review and change procedures to improve their patient safety across a key sets of patient safety issues.

SUBMITTER: Campbell SM

PROVIDER: S-EPMC7447126 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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A Patient Safety Toolkit for Family Practices.

Campbell Stephen M SM Bell Brian G BG Marsden Kate K Spencer Rachel R Kadam Umesh U Perryman Katherine K Rodgers Sarah S Litchfield Ian I Reeves David D Chuter Antony A Doos Lucy L Ricci-Cabello Ignacio I Gill Paramjit P Esmail Aneez A Greenfield Sheila S Slight Sarah S Middleton Karen K Barnett Jane J Moore Michael M Valderas Jose M JM Sheikh Aziz A Avery Anthony J AJ

Journal of patient safety 20200901 3

<h4>Objective</h4>Major gaps remain in our understanding of primary care patient safety. We describe a toolkit for measuring patient safety in family practices.<h4>Methods</h4>Six tools were used in 46 practices. These tools were as follows: National Health Service Education for Scotland Trigger Tool, National Health Service Education for Scotland Medicines Reconciliation Tool, Primary Care Safequest, Prescribing Safety Indicators, Patient Reported Experiences and Outcomes of Safety in Primary C ...[more]

PMID: 29461334

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Project description:MotivationPrincipal component analysis (PCA) of genetic data is routinely used to infer ancestry and control for population structure in various genetic analyses. However, conducting PCA analyses can be complicated and has several potential pitfalls. These pitfalls include (i) capturing linkage disequilibrium (LD) structure instead of population structure, (ii) projected PCs that suffer from shrinkage bias, (iii) detecting sample outliers and (iv) uneven population sizes. In this work, we explore these potential issues when using PCA, and present efficient solutions to these. Following applications to the UK Biobank and the 1000 Genomes project datasets, we make recommendations for best practices and provide efficient and user-friendly implementations of the proposed solutions in R packages bigsnpr and bigutilsr.ResultsFor example, we find that PC19-PC40 in the UK Biobank capture complex LD structure rather than population structure. Using our automatic algorithm for removing long-range LD regions, we recover 16 PCs that capture population structure only. Therefore, we recommend using only 16-18 PCs from the UK Biobank to account for population structure confounding. We also show how to use PCA to restrict analyses to individuals of homogeneous ancestry. Finally, when projecting individual genotypes onto the PCA computed from the 1000 Genomes project data, we find a shrinkage bias that becomes large for PC5 and beyond. We then demonstrate how to obtain unbiased projections efficiently using bigsnpr. Overall, we believe this work would be of interest for anyone using PCA in their analyses of genetic data, as well as for other omics data.Availability and implementationR packages bigsnpr and bigutilsr can be installed from either CRAN or GitHub (see https://github.com/privefl/bigsnpr). A tutorial on the steps to perform PCA on 1000G data is available at https://privefl.github.io/bigsnpr/articles/bedpca.html. All code used for this paper is available at https://github.com/privefl/paper4-bedpca/tree/master/code.Supplementary informationSupplementary data are available at Bioinformatics online.

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A Patient Safety Toolkit for Family Practices.

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A Patient Safety Toolkit for Family Practices.

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