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The report draws on existing primary care data sources and provides shared-learning content with structured links and resources. It is intended for PQLs and informed by local LIST and MCN colleagues to facilitate collation and local contextual use.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/template/","Template",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/template/paper-templates/","Paper 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the purpose of the cluster data and intelligence report for type 2 diabetes in adults?","Question",{"text":63,"@type":64},"It provides information through a standard report template to support quality discussions and quality improvement planning at practice, cluster, HSCP, and board level.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"Who is the report intended for and how should it be used?",{"text":68,"@type":64},"It is intended for PQLs to share with practice teams and for discussion at cluster level on a voluntary basis, using the explained collation process supported by local LIST and MCN colleagues.",{"name":70,"@type":61,"acceptedAnswer":71},"What data sources does the report draw on?",{"text":72,"@type":64},"It draws on existing primary care data sources, including SCI-Diabetes datasets, STU prescribing data, and the Atlas of Variation dataset for core laboratory test usage.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},253906,1789271689,{"code":4,"msg":82,"data":83},"success",[84,89,94,99,104,109,114,119,123],{"id":85,"doc_module":22,"doc_module_name":25,"category_name":86,"show_sort_weight":87,"slug":88},11,"Presentations",90,"presentations",{"id":90,"doc_module":22,"doc_module_name":25,"category_name":91,"show_sort_weight":92,"slug":93},12,"Resumes",80,"resumes",{"id":95,"doc_module":22,"doc_module_name":25,"category_name":96,"show_sort_weight":97,"slug":98},14,"Invoices",70,"invoices",{"id":100,"doc_module":22,"doc_module_name":25,"category_name":101,"show_sort_weight":102,"slug":103},15,"Posters",60,"posters",{"id":105,"doc_module":22,"doc_module_name":25,"category_name":106,"show_sort_weight":107,"slug":108},16,"Social 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for Primary Care  \n􀀅􀀇􀀈􀀉  \nFor Action  \nGeneral practice PQL and CQL’s Diabetes MCN leads  \nPHS LIST HSCP’s  \nNHS Boards Primary Care Leads  \nFor Information  \nScottish General Practitioners Committee Royal College of General Practitioners 12th June 2023  \nPolicy Enquiries to:  \nDavid Ross  \nPrimary Care Division 1 East Rear St Andrew’s House Edinburgh  \nEH1 3DG  \n[David.Ross@gov.scot](David.Ross@gov.scot)  \nDear Colleagues  \nCLUSTER DATA AND INTELLIGENCE REPORT – TYPE 2 DIABETES MELLITUS IN ADULTS  \nPurpose  \n1. This Circular encloses information regarding a cluster data and intelligence report for type 2 diabetes in adults. It can be used to support quality discussions at practice and cluster level.  \nBackground  \n2. GP Cluster working has been gradually evolving since their introduction in 2016. Their role and function was set out in the 2017 framework and further supported by the national guidance for clusters in 2019.  \n3. A key founding principle of the Framework was to “utilise GP Clusters as the means of establishing peer-led, values driven quality improvement activity with both a focus on practice based (intrinsic) quality and contribution to system based (extrinsic) quality.”  \n4. Taking this into account , the national Improving Together Advisory Group has worked with key stakeholders (including Practice Quality Leads (PQL) and Cluster Quality Leads (CQL)) to design and develop a national standard data and intelligence report template for type 2 diabetes in adults , recognising the high prevalence and major contributory factor for premature mortality. It is anticipated that this will be the first in a series of such reports for key long-term conditions (LTC) .  \n5. The report draws on existing primary care data sources, with opportunities for shared learning via report content and links to resources in a standard format.  \nWho is this for?  \n6. This report is intended for PQLs to share with the practice team,(noting patient identifiable data on SCI-diabetes is only accessible at practice level through a protected password) and for discussion at cluster level. It is for use on a voluntary basis.  \n7. Collation of data for each practice and cluster is explained in the report, and should be facilitated by local LIST and MCN colleagues, allowing practice teams and clusters the opportunity to use this data in the practice and local context.  \n8. This should also provide opportunities for wider discussion and shared learning across CQLs and clusters at HSCP, Board and national level, supported by HSCPs, List teams and the diabetes MCN.  \nAction  \n8. Practices and clusters are asked to  \n• Note the contents of this circular and consider using this report to facilitate quality improvement discussions at practice, cluster, HSCP and board level  \n9. MCN leads, PHS LIST analysts and HSCPs are asked to  \n• Facilitate collation of local data and support any identified areas for quality improvement activity  \nYours sincerely,  \nDr Susan Gallacher  \nDeputy Director of General Practice Policy Primary Care Directorate  \nCluster data and intelligence report Type 2 diabetes mellitus in adults  \nJune 2023  \nContents  \n1. How to use this report ....................................................................................... 2  \n2. Introduction ........................................................................................................ 3  \n3. Cluster details .................................................................................................... 6  \n4. Demographics – population profile.................................................................. 6  \n5. Diabetes Data ..................................................................................................... 9  \n5.1 SCI-Diabetes datasets-Key care process measures................................... 9  \n5.2 STU prescribing dataset-Key prescribing indicators.................................. 14  \n5.3 Atlas of Variation dataset – core la","cbCaidnCd7BncCod","https://ap.wps.com/l/cbCaidnCd7BncCod","pdf",1951126,28,"English","# How to use this report\n# Introduction\n# Cluster details\n# Demographics – population profile\n# Diabetes Data\n## SCI-Diabetes datasets-Key care process measures\n## STU prescribing dataset-Key prescribing indicators\n## Atlas of Variation dataset – core laboratory test usage\n# The patient journey\n## LTC management – the journey\n## Supporting Self-Management\n## Models and resources\n# Prediabetes and prevention\n# Cluster feedback\n# Tools, resources and local links","[{\"question\":\"What is the purpose of the cluster data and intelligence report for type 2 diabetes in adults?\",\"answer\":\"It provides information through a standard report template to support quality discussions and quality improvement planning at practice, cluster, HSCP, and board level.\"},{\"question\":\"Who is the report intended for and how should it be used?\",\"answer\":\"It is intended for PQLs to share with practice teams and for discussion at cluster level on a voluntary basis, using the explained collation process supported by local LIST and MCN colleagues.\"},{\"question\":\"What data sources does the report draw on?\",\"answer\":\"It draws on existing primary care data sources, including SCI-Diabetes datasets, STU prescribing data, and the Atlas of Variation dataset for core laboratory test usage.\"}]","CLUSTER DATA AND INTELLIGENCE REPORT - TYPE 2 DIABETES MELLITUS IN ADULTS - June 2023 | PDF",10]