The Perioperative Quality Improvement Programme (PQIP Patient Study): Protocol for a UK Multicentre, Prospective Cohort Study to Measure, Report and Improve Quality and Outcomes of Major Surgery

التفاصيل البيبلوغرافية
العنوان: The Perioperative Quality Improvement Programme (PQIP Patient Study): Protocol for a UK Multicentre, Prospective Cohort Study to Measure, Report and Improve Quality and Outcomes of Major Surgery
المؤلفون: Abigail E Vallance, S Ramani Moonesinghe, Olga Tucker, Arun Sahni, Katie Samuel, Giuseppe Aresu, Aleksandra Ignacka, Irene Leeman, R. Jonathan T. Wilson, Matthew Bedford, Christine Taylor, Rachel Baumber, Jose Lourtie, James Bedford, James Goodwin, Sharon Drake, Alexandra Brent, Duncan Wagstaff, David Anthony Gilhooly, Dermot McGuckin, Peter Martin, Helen Ellicott, Maria Chazapis, M. Swart, Dominic Olive, Martin Cripps, Kylie Edwards, Dorian Martinez, Helena Smith, Andrew J. Swift, Cecilia Vindrola-Padros, Pritam Singh, Cristel Santos, Anne-Marie Bougeard, Georgina Singleton, Jenny Dorey, Michael P. W. Grocott, Karen Williams, Ravinder S. Vohra, Naomi Fulop, Samantha R Warnakulasuriya
بيانات النشر: Research Square Platform LLC, 2021.
سنة النشر: 2021
مصطلحات موضوعية: Protocol (science), Measure (data warehouse), medicine.medical_specialty, Quality management, business.industry, media_common.quotation_subject, Perioperative, Patient study, Emergency medicine, medicine, Quality (business), Prospective cohort study, business, media_common
الوصف: Background Major surgery accounts for a substantial proportion of health service activity and resource consumption, due not only to the primary procedure, but also the short and long-term implications of perioperative complications. It is likely that both compliance with best practice processes and outcomes from major surgery vary substantially between hospitals and therefore could be targets for quality improvement. Methods The Perioperative Quality Improvement Programme (PQIP) patient study is a multi-centre prospective cohort study which recruits participants undergoing major inpatient non-cardiac surgery with three main aims: to measure and improve processes of care and outcome from major surgery; to implement and evaluate a complex intervention aiming to enhance the use of data for improvement by clinical teams; and to create a national database to support collaborative research and efficient study design. The prospective dataset combines variables for risk adjustment, process measures and both objective and patient reported outcome data. Longer-term outcomes are collected through linkage to national administrative datasets (mortality and readmissions). PQIP deploys a theoretically underpinned improvement methodology to support the use of data for improvement by perioperative clinicians, incorporating action research principles to enable changes to be made in response to user feedback. Dissemination of interim findings (non-inferential) form a part of the improvement methodology and are provided to participating centres at regular intervals, including near-real-time feedback of key process measures. Inferential analyses will be published in the peer-reviewed literature, supported by a multi-modal communications strategy to patients, public, policy makers and academic audiences as well as clinicians. Discussion PQIP is the first national effort in the UK to measure and report risk-adjusted complications, patient-reported outcome and mortality rates for patients undergoing major surgery across multiple surgical specialties in the UK. Its main limitation is the risk of sampling bias due to the requirement for patient consent, and because local resource constraints may lead hospitals to recruit a convenience sample, rather than a truly random sample. We will evaluate this risk by using Hospital Episode Statistics (HES) to identify all patients undergoing PQIP eligible procedures, and undertaking sensitivity analyses comparing common data points in the PQIP sample and the HES population. As the purpose of PQIP is to support quality improvement and research as opposed to quality assurance or institutional comparisons, even if they exist, such sampling biases are unlikely to materially affect the ability of the programme to achieve its aims.
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::7f33f0fe1aad9f9706042333a4304926Test
https://doi.org/10.21203/rs.3.rs-708161/v1Test
حقوق: OPEN
رقم الانضمام: edsair.doi...........7f33f0fe1aad9f9706042333a4304926
قاعدة البيانات: OpenAIRE