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Jayasinghe RT, Ahern S, Maharaj AD, Romero L, Ruseckaite R. Identifying Existing Guidelines, Frameworks, Checklists, and Recommendations for Implementing Patient-Reported Outcome Measures: Protocol for a Scoping Review. JMIR Res Protoc 2024; 13:e52572. [PMID: 38771621 DOI: 10.2196/52572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 12/19/2023] [Accepted: 03/11/2024] [Indexed: 05/22/2024] Open
Abstract
BACKGROUND Implementing patient-reported outcome measures (PROMs) to measure and evaluate health outcomes is increasing worldwide. Along with this emerging trend, it is important to identify which guidelines, frameworks, checklists, and recommendations exist, and if and how they have been used in implementing PROMs, especially in clinical quality registries (CQRs). OBJECTIVE This review aims to identify existing publications, as well as publications that discuss the application of actual guidelines, frameworks, checklists, and recommendations on PROMs' implementation for various purposes such as clinical trials, clinical practice, and CQRs. In addition, the identified publications will be used to guide the development of a new guideline for PROMs' implementation in CQRs, which is the aim of the broader project. METHODS A literature search of the databases MEDLINE, Embase, CINAHL, PsycINFO, and Cochrane Central Register of Controlled Trials will be conducted since the inception of the databases, in addition to using Google Scholar and gray literature to identify literature for the scoping review. Predefined inclusion and exclusion criteria will be used for all phases of screening. Existing publications of guidelines, frameworks, checklists, recommendations, and publications discussing the application of those methodologies for implementing PROMs in clinical trials, clinical practice, and CQRs will be included in the final review. Data relating to bibliographic information, aim, the purpose of PROMs use (clinical trial, practice, or registries), name of guideline, framework, checklist and recommendations, the rationale for development, and their purpose and implications will be extracted. Additionally, for publications of actual methodologies, aspects or domains of PROMs' implementation will be extracted. A narrative synthesis of included publications will be conducted. RESULTS The electronic database searches were completed in March 2024. Title and abstract screening, full-text screening, and data extraction will be completed in May 2024. The review is expected to be completed by the end of August 2024. CONCLUSIONS The findings of this scoping review will provide evidence on any existing methodologies and tools for PROMs' implementation in clinical trials, clinical practice, and CQRs. It is anticipated that the publications will help us guide the development of a new guideline for PROMs' implementation in CQRs. TRIAL REGISTRATION PROSPERO CRD42022366085; https://tinyurl.com/bdesk98x. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/52572.
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Affiliation(s)
| | - Susannah Ahern
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Ashika D Maharaj
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Lorena Romero
- The Ian Potter Library, Alfred Hospital, Melbourne, Australia
| | - Rasa Ruseckaite
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
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Parker KJ, Hickman LD, McDonagh J, Lindley RI, Ferguson C. The prototype of a frailty learning health system: The HARMONY Model. Learn Health Syst 2024; 8:e10401. [PMID: 38633027 PMCID: PMC11019377 DOI: 10.1002/lrh2.10401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 11/02/2023] [Accepted: 11/06/2023] [Indexed: 04/19/2024] Open
Abstract
Introduction Rapid translation of research findings into clinical practice through innovation is critical to improve health systems and patient outcomes. Access to efficient systems of learning underpinned with real-time data are the future of healthcare. This type of health system will decrease unwarranted clinical variation, accelerate rapid evidence translation, and improve overall healthcare quality. Methods This paper aims to describe The HARMONY model (acHieving dAta-dRiven quality iMprovement to enhance frailty Outcomes using a learNing health sYstem), a new frailty learning health system model of implementation science and practice improvement. The HARMONY model provides a prototype for clinical quality registry infrastructure and partnership within health care. Results The HARMONY model was applied to the Western Sydney Clinical Frailty Registry as the prototype exemplar. The model networks longitudinal frailty data into an accessible and useable format for learning. Creating local capability that networks current data infrastructures to translate and improve quality of care in real-time. Conclusion This prototype provides a model of registry data feedback and quality improvement processes in an inpatient aged care and rehabilitation hospital setting to help reduce clinical variation, enhance research translation capacity, and improve care quality.
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Affiliation(s)
- Kirsten J. Parker
- School of Nursing, Faculty of Science, Medicine & HealthUniversity of WollongongWollongongNew South WalesAustralia
- Centre for Chronic and Complex Care ResearchBlacktown HospitalWestern Sydney Local Health DistrictBlacktownNew South WalesAustralia
| | | | - Julee McDonagh
- School of Nursing, Faculty of Science, Medicine & HealthUniversity of WollongongWollongongNew South WalesAustralia
- Centre for Chronic and Complex Care ResearchBlacktown HospitalWestern Sydney Local Health DistrictBlacktownNew South WalesAustralia
| | - Richard I. Lindley
- Centre for Chronic and Complex Care ResearchBlacktown HospitalWestern Sydney Local Health DistrictBlacktownNew South WalesAustralia
- Westmead Applied Research CentreUniversity of SydneyWestmeadNew South WalesAustralia
| | - Caleb Ferguson
- School of Nursing, Faculty of Science, Medicine & HealthUniversity of WollongongWollongongNew South WalesAustralia
- Centre for Chronic and Complex Care ResearchBlacktown HospitalWestern Sydney Local Health DistrictBlacktownNew South WalesAustralia
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Hansen J, Ahern S, Earnest A. Evaluations of statistical methods for outlier detection when benchmarking in clinical registries: a systematic review. BMJ Open 2023; 13:e069130. [PMID: 37451708 PMCID: PMC10351235 DOI: 10.1136/bmjopen-2022-069130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 06/26/2023] [Indexed: 07/18/2023] Open
Abstract
OBJECTIVES Benchmarking is common in clinical registries to support the improvement of health outcomes by identifying underperforming clinician or health service providers. Despite the rise in clinical registries and interest in publicly reporting benchmarking results, appropriate methods for benchmarking and outlier detection within clinical registries are not well established, and the current application of methods is inconsistent. The aim of this review was to determine the current statistical methods of outlier detection that have been evaluated in the context of clinical registry benchmarking. DESIGN A systematic search for studies evaluating the performance of methods to detect outliers when benchmarking in clinical registries was conducted in five databases: EMBASE, ProQuest, Scopus, Web of Science and Google Scholar. A modified healthcare modelling evaluation tool was used to assess quality; data extracted from each study were summarised and presented in a narrative synthesis. RESULTS Nineteen studies evaluating a variety of statistical methods in 20 clinical registries were included. The majority of studies conducted application studies comparing outliers without statistical performance assessment (79%), while only few studies used simulations to conduct more rigorous evaluations (21%). A common comparison was between random effects and fixed effects regression, which provided mixed results. Registry population coverage, provider case volume minimum and missing data handling were all poorly reported. CONCLUSIONS The optimal methods for detecting outliers when benchmarking clinical registry data remains unclear, and the use of different models may provide vastly different results. Further research is needed to address the unresolved methodological considerations and evaluate methods across a range of registry conditions. PROSPERO REGISTRATION NUMBER CRD42022296520.
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Affiliation(s)
- Jessy Hansen
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Susannah Ahern
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Arul Earnest
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
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Cadilhac DA, Marion V, Andrew NE, Breen SJ, Grabsch B, Purvis T, Morrison JL, Lannin NA, Grimley RS, Middleton S, Kilkenny MF. A Stepped-Wedge Cluster-Randomized Trial to Improve Adherence to Evidence-Based Practices for Acute Stroke Management. Jt Comm J Qual Patient Saf 2022; 48:653-664. [PMID: 36307360 DOI: 10.1016/j.jcjq.2022.09.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 09/18/2022] [Accepted: 09/21/2022] [Indexed: 12/30/2022]
Abstract
BACKGROUND There is limited evidence regarding the optimal design and composition of multifaceted quality improvement programs to improve acute stroke care. The researchers aimed to test the effectiveness of a co-designed multifaceted intervention (STELAR: Shared Team Efforts Leading to Adherence Results) directed at hospital clinicians for improving acute stroke care tailored to the local context using feedback of national registry indicator data. METHODS STELAR was a stepped-wedge cluster trial (partial randomization) using routinely collected Australian Stroke Clinical Registry data from Victorian hospitals segmented in two-month blocks. Each hospital (cluster) contributed control data from May 2017 and data for the intervention phase from July 2017 until September 2018. The intervention was multifaceted, delivered predominantly in two educational outreach workshops by experienced, external improvement facilitators, consisting of (1) feedback of registry data to identify practice gaps and (2) interprofessional education, barrier assessment, and documentation of an agreed action plan initiated by local clinical leaders appointed as change champions for prioritized clinical indicators. The researchers provided additional outreach support by e-mail/telephone for two months. Multilevel, multivariable regression models were used to assess change in a composite outcome of indicators selected for actions plans (primary outcome) and individual indicators (secondary outcome). Patient survival and disability 90-180 days after stroke were also compared. RESULTS Nine hospitals (clusters) participated, and 144 clinicians attended 18 intervention workshops. The control phase included 1,001 patients (median age 76.7 years; 47.4% female, 64.7% ischemic stroke), and the intervention phase 2,146 patients (median age 74.9 years; 44.2% female, 73.8% ischemic stroke). Compared to the control phase, the median score for the composite outcome for the intervention phase was 17% greater for the indicators included in the hospitals' action plans (range 3% to 30%, p = 0.016) and overall for the 10 indicators 6% greater (range 3% to 10%, p < 0.001). Compared to the control phase, patients in the intervention phase more often received stroke unit care (odds ratio [OR] 1.39, 95% confidence interval [CI] 1.05-1.84), were discharged on antithrombotic medications (OR 1.87, 95% CI 1.50-2.33), and received a discharge care plan (OR 1.27, 95% CI 1.05-1.53). Patient outcomes were unchanged. CONCLUSION External quality improvement facilitation using workshops and remote support, aligned with routine monitoring via registries, can improve acute stroke care.
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Gawthorne J, Fasugba O, Levi C, Mcinnes E, Ferguson C, Mcneil JJ, Cadilhac DA, Everett B, Fernandez R, Fry M, Goldsmith H, Hickman L, Jackson D, Maguire J, Murray E, Perry L, Middleton S. Are clinicians using routinely collected data to drive practice improvement? A cross-sectional survey. Int J Qual Health Care 2021; 33:6382278. [PMID: 34613386 DOI: 10.1093/intqhc/mzab141] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 09/13/2021] [Accepted: 10/06/2021] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Clinical registry participation is a measure of healthcare quality. Limited knowledge exists on Australian hospitals' participation in clinical registries and whether this registry data informs quality improvement initiatives. OBJECTIVE To identify participation in clinical registries, determine if registry data inform quality improvement initiatives, and identify registry participation enablers and clinicians' educational needs to improve use of registry data to drive practice change. METHODS A self-administered survey was distributed to staff coordinating registries in seven hospitals in New South Wales, Australia. Eligible registries were international-, national- and state-based clinical, condition-/disease-specific and device/product registries. RESULTS Response rate was 70% (97/139). Sixty-two (64%) respondents contributed data to 46 eligible registries. Registry reports were most often received by nurses (61%) and infrequently by hospital executives (8.4%). Less than half used registry data 'always' or 'often' to influence practice improvement (48%) and care pathways (49%). Protected time for data collection (87%) and benchmarking (79%) were 'very likely' or 'likely' to promote continued participation. Over half 'strongly agreed' or 'agreed' that clinical practice improvement training (79%) and evidence-practice gap identification (77%) would optimize use of registry data. CONCLUSIONS Registry data are generally only visible to local speciality units and not routinely used to inform quality improvement. Centralized on-going registry funding, accessible and transparent integrated information systems combined with data informed improvement science education could be first steps to promote quality data-driven clinical improvement initiatives.
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Affiliation(s)
- Julie Gawthorne
- St Vincent's Hospital Sydney, Victoria Street, Darlinghurst, NSW 2010, Australia.,Nursing Research Institute, St Vincent's Health Network Sydney, St Vincent's Hospital Melbourne and Australian Catholic University, Level 5 deLacy Building, Victoria Street, Darlinghurst, NSW 2010, Australia
| | - Oyebola Fasugba
- Nursing Research Institute, St Vincent's Health Network Sydney, St Vincent's Hospital Melbourne and Australian Catholic University, Level 5 deLacy Building, Victoria Street, Darlinghurst, NSW 2010, Australia
| | - Chris Levi
- School of Medicine and Public Health, University of Newcastle, University Drive, Callaghan, NSW 2308, Australia
| | - Elizabeth Mcinnes
- Nursing Research Institute, St Vincent's Health Network Sydney, St Vincent's Hospital Melbourne and Australian Catholic University, Level 5 deLacy Building, Victoria Street, Darlinghurst, NSW 2010, Australia
| | - Caleb Ferguson
- Western Sydney Nursing & Midwifery Research Centre, Western Sydney Local Health District, Western Sydney University, Marcel Crescent, Blacktown, NSW 2148, Australia
| | - John J Mcneil
- School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Melbourne, VIC 3004, Australia
| | - Dominique A Cadilhac
- Translational Public Health and Evaluation Division, School of Clinical Sciences, Monash University, Level 3 Hudson Institute Building, 27-31 Wright Street, Clayton, VIC 3168, Australia.,Stroke Division, The Florey Institute of Neuroscience and Mental Health, 245 Burgundy Street, Heidelberg, VIC 3084, Australia
| | - Bronwyn Everett
- School of Nursing and Midwifery, Western Sydney University, Building EB.LG Room 81, Parramatta South Campus, Victoria Rd, Rydalmere, NSW 2116, Australia
| | - Ritin Fernandez
- School of Nursing, Faculty of Science, Medicine and Health, University of Wollongong, Northfields Avenue, Wollongong, NSW 2522, Australia
| | - Margaret Fry
- Royal North Shore Hospital, Reserve Road, St Leonards, Sydney, NSW 2065, Australia.,School of Nursing and Midwifery, Faculty of Health, University of Technology Sydney, 235 Jones Street, Ultimo, NSW 2007, Australia
| | - Helen Goldsmith
- Centre for Applied Nursing Research, South Western Sydney Local Health District, Ingham Institute Level 3, 1 Campbell Street, Liverpool, NSW 2170, Australia
| | - Louise Hickman
- School of Nursing and Midwifery, Faculty of Health, University of Technology Sydney, 235 Jones Street, Ultimo, NSW 2007, Australia
| | - Deborah Jackson
- School of Nursing and Midwifery, Faculty of Health, University of Technology Sydney, 235 Jones Street, Ultimo, NSW 2007, Australia
| | - Jane Maguire
- School of Nursing and Midwifery, Faculty of Health, University of Technology Sydney, 235 Jones Street, Ultimo, NSW 2007, Australia
| | - Edel Murray
- St Vincent's Health Australia, Level 22, 100 William Street, Woolloomooloo, NSW 2010, Australia
| | - Lin Perry
- School of Nursing and Midwifery, Faculty of Health, University of Technology Sydney, 235 Jones Street, Ultimo, NSW 2007, Australia.,Prince of Wales Hospital, South East Sydney Local Health District, 320-346 Barker St, Randwick, NSW 2031, Australia
| | - Sandy Middleton
- St Vincent's Hospital Sydney, Victoria Street, Darlinghurst, NSW 2010, Australia.,Nursing Research Institute, St Vincent's Health Network Sydney, St Vincent's Hospital Melbourne and Australian Catholic University, Level 5 deLacy Building, Victoria Street, Darlinghurst, NSW 2010, Australia
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Vishwanath S, Pellegrini B, Parker E, Earnest A, Kalbasi S, Gartoulla P, Elder E, Farrell G, Moore C, Cooter RD, Ahern S, McNeil JJ, Hopper I. Breast Device Surgery in Australia: Early Results from the Australian Breast Device Registry. J Plast Reconstr Aesthet Surg 2021; 74:2719-2730. [PMID: 33931327 DOI: 10.1016/j.bjps.2021.03.035] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 03/03/2021] [Accepted: 03/13/2021] [Indexed: 11/19/2022]
Abstract
BACKGROUND The Australian Breast Device Registry (ABDR) is a clinical quality registry designed to monitor the performance of breast devices; and the quality and safety of breast device surgery. OBJECTIVE To report on breast device surgery characteristics across Australia. METHODS Participants were registered patients in the ABDR from 2012 to 2018. Results are described using percentages, mean and median. Revision rates were calculated using survival analysis methods. RESULTS A total of 37,603 patients were registered and had undergone reconstruction (post-cancer 15.1%, risk-reducing mastectomy 3.4% and developmental deformity 2.4%) or cosmetic augmentation (74.7%) procedures. The majority of breast implant devices were silicone filled with textured surface (reconstruction 74.0% and augmentation 64.0%). Sub-pectoral plane was the most common for both reconstruction (60.1%) and augmentation (76.6%) procedures. For reconstruction surgery, the most common surgical incision was previous mastectomy scar (44.0%) and inframammary (31.8%), and for augmentation, it was inframammary (83.4%). Intraoperative/postoperative antibiotic usage for reconstruction was 85.8% and augmentation was 89.4%. Revision incidence due to complication at 12 months post-cancer reconstruction was 5.1%, risk-reducing reconstruction 5.7% and developmental deformity implants 4.5%. Revision incidence due to complication at 12 months after augmentation procedure was 1.1%. Patient-reported outcome measures (PROMs) indicate high levels of satisfaction at 1 year for augmentation and reconstruction procedures. CONCLUSION We report on early data from the ABDR and reflect on the uptake of the registry by surgeons and patients. The registry also benefits from international collaborative approaches to addressing challenges and is committed to facilitate international post-market surveillance.
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Affiliation(s)
- Swarna Vishwanath
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Breanna Pellegrini
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Emily Parker
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Arul Earnest
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Saeid Kalbasi
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Pragya Gartoulla
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Elisabeth Elder
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia; Westmead Breast Cancer Institute, Australia; University of Sydney, Sydney, Australia; Breast Surgeons of Australia & New Zealand, Australia
| | - Gillian Farrell
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia; Cabrini Hospital - Brighton, Australia; Peter McCallum Cancer Centre, Melbourne, Australia; Australian Society of Plastic Surgeons, Australia
| | - Colin Moore
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia; Australasian College of Cosmetic Surgery, Australia
| | - Rodney D Cooter
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Susannah Ahern
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - John J McNeil
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Ingrid Hopper
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
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Prang KH, Maritz R, Sabanovic H, Dunt D, Kelaher M. Mechanisms and impact of public reporting on physicians and hospitals' performance: A systematic review (2000-2020). PLoS One 2021; 16:e0247297. [PMID: 33626055 PMCID: PMC7904172 DOI: 10.1371/journal.pone.0247297] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 02/04/2021] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Public performance reporting (PPR) of physician and hospital data aims to improve health outcomes by promoting quality improvement and informing consumer choice. However, previous studies have demonstrated inconsistent effects of PPR, potentially due to the various PPR characteristics examined. The aim of this study was to undertake a systematic review of the impact and mechanisms (selection and change), by which PPR exerts its influence. METHODS Studies published between 2000 and 2020 were retrieved from five databases and eight reviews. Data extraction, quality assessment and synthesis were conducted. Studies were categorised into: user and provider responses to PPR and impact of PPR on quality of care. RESULTS Forty-five studies were identified: 24 on user and provider responses to PPR, 14 on impact of PPR on quality of care, and seven on both. Most of the studies reported positive effects of PPR on the selection of providers by patients, purchasers and providers, quality improvement activities in primary care clinics and hospitals, clinical outcomes and patient experiences. CONCLUSIONS The findings provide moderate level of evidence to support the role of PPR in stimulating quality improvement activities, informing consumer choice and improving clinical outcomes. There was some evidence to demonstrate a relationship between PPR and patient experience. The effects of PPR varied across clinical areas which may be related to the type of indicators, level of data reported and the mode of dissemination. It is important to ensure that the design and implementation of PPR considered the perspectives of different users and the health system in which PPR operates in. There is a need to account for factors such as the structural characteristics and culture of the hospitals that could influence the uptake of PPR.
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Affiliation(s)
- Khic-Houy Prang
- Centre for Health Policy, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Australia
| | - Roxanne Maritz
- Centre for Health Policy, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Australia
- Rehabilitation Services and Care Unit, Swiss Paraplegic Research, Nottwil, Switzerland
- Department of Health Sciences and Health Policy, University of Lucerne, Lucerne, Switzerland
| | - Hana Sabanovic
- Centre for Health Policy, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Australia
| | - David Dunt
- Centre for Health Policy, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Australia
| | - Margaret Kelaher
- Centre for Health Policy, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Australia
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Biswas S, Dinh D, Lucas M, Duffy SJ, Brennan AL, Liew D, Cox N, Nadurata V, Reid CM, Lefkovits J, Stub D. Incidence and Predictors of Unplanned Hospital Readmission after Percutaneous Coronary Intervention. J Clin Med 2020; 9:jcm9103242. [PMID: 33050476 PMCID: PMC7600497 DOI: 10.3390/jcm9103242] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 09/25/2020] [Accepted: 10/03/2020] [Indexed: 11/24/2022] Open
Abstract
Unplanned readmissions to hospital after percutaneous coronary intervention (PCI) pose a significant burden to the healthcare system and are potentially preventable. In this study, we sought to determine the incidence of, and risk factors for, unplanned hospital readmissions within 30 days following PCI. We prospectively collected data on 28,488 patients undergoing PCI between 2013 and 2019, who were enrolled in the state-wide multi-centre Victorian Cardiac Outcomes Registry. Patients’ data were then linked to data from the Victorian Department of Health administrative database that records statewide hospital admissions. Disease diagnosis codes were used to identify cause of readmission. Patients who had an unplanned readmission were further divided into those who had a cardiac vs. non-cardiac cause for readmission. Overall, 3059 patients (10.7%) had an unplanned hospital readmission within 30 days of PCI, of which 1848 patients (60.4%) were readmitted for primarily cardiac diagnoses. Independent predictors of both 30-day unplanned cardiac and non-cardiac readmissions post-PCI were female sex, having ≥1 admission in the 12 months prior to PCI, acute coronary syndrome presentation, having any in-hospital complication and being discharged on an oral anticoagulant (all p < 0.05). A stepwise increase in readmission risk was observed with increasing number of admissions from 1 to ≥4 admissions in the 12 months prior to PCI. In conclusion, a substantial proportion of patients undergoing PCI have unexpected readmissions to hospital in the 30 days following PCI. Targeted strategies for patients with risk factors for readmission may be useful to reduce this significant burden to the healthcare system.
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Affiliation(s)
- Sinjini Biswas
- School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Australia; (S.B.); (D.D.); (M.L.); (S.J.D.); (A.L.B.); (D.L); (C.M.R.); (J.L.)
- Department of Cardiology, The Alfred Hospital, Melbourne 3004, Australia
| | - Diem Dinh
- School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Australia; (S.B.); (D.D.); (M.L.); (S.J.D.); (A.L.B.); (D.L); (C.M.R.); (J.L.)
| | - Mark Lucas
- School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Australia; (S.B.); (D.D.); (M.L.); (S.J.D.); (A.L.B.); (D.L); (C.M.R.); (J.L.)
| | - Stephen J. Duffy
- School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Australia; (S.B.); (D.D.); (M.L.); (S.J.D.); (A.L.B.); (D.L); (C.M.R.); (J.L.)
- Department of Cardiology, The Alfred Hospital, Melbourne 3004, Australia
| | - Angela L. Brennan
- School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Australia; (S.B.); (D.D.); (M.L.); (S.J.D.); (A.L.B.); (D.L); (C.M.R.); (J.L.)
| | - Danny Liew
- School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Australia; (S.B.); (D.D.); (M.L.); (S.J.D.); (A.L.B.); (D.L); (C.M.R.); (J.L.)
- Department of General Medicine, The Alfred Hospital, Melbourne 3004, Australia
| | - Nicholas Cox
- Department of Cardiology, Western Health, Melbourne 3021, Australia;
- Department of Medicine—Western Health, The University of Melbourne, Melbourne 3021, Australia
| | | | - Christopher M. Reid
- School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Australia; (S.B.); (D.D.); (M.L.); (S.J.D.); (A.L.B.); (D.L); (C.M.R.); (J.L.)
- School of Public Health, Curtin University, Perth 6102, Australia
| | - Jeffrey Lefkovits
- School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Australia; (S.B.); (D.D.); (M.L.); (S.J.D.); (A.L.B.); (D.L); (C.M.R.); (J.L.)
- Department of Cardiology, Royal Melbourne Hospital, Melbourne 3050, Australia
| | - Dion Stub
- School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Australia; (S.B.); (D.D.); (M.L.); (S.J.D.); (A.L.B.); (D.L); (C.M.R.); (J.L.)
- Department of Cardiology, The Alfred Hospital, Melbourne 3004, Australia
- Department of Cardiology, Western Health, Melbourne 3021, Australia;
- Baker IDI Heart and Diabetes Institute, Melbourne 3004, Australia
- Correspondence: ; Tel.: +61-3-9076-3263
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9
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Ahern S, Evans S, Hopper I, Zalcberg J. Towards a strategy for clinical quality registries in Australia. AUST HEALTH REV 2020; 43:284-287. [PMID: 29415798 DOI: 10.1071/ah17201] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2017] [Accepted: 12/13/2017] [Indexed: 11/23/2022]
Abstract
The healthcare value of Australian clinical quality registries (CQRs) has recently been highlighted by the Australian Commission of Safety and Quality in Health Care (ACSQHC) as being similar to the benefits of CQRs reported internationally. However, the development of CQRs in Australia is currently limited by a lack of coordination and strategic planning, leading to governance and funding processes that are varied and non-sustainable. Despite this, Australia has achieved recognised success with exemplar clinical registries where funding has been sustained at least partly by public funds. To this end, Australia can learn from international CQR governance and funding models to support CQR sustainability, most notably those from European and Scandinavian countries. Further, following the release of the ACSQHC's prioritised domains for CQRs and anticipated funding from the Medical Research Future Fund, the ACSQHC is well positioned to lead a national strategic approach for clinical registries. Together with medical leadership and engagement, operational and data management support from the jurisdictions and financial support from both the public and private sectors, a prioritised and coordinated approach may soon become a reality.
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Affiliation(s)
- Susannah Ahern
- School of Public Health and Preventive Medicine, Monash University, 553St Kilda Road, Melbourne, Vic. 3004, Australia.
| | - Sue Evans
- School of Public Health and Preventive Medicine, Monash University, 553St Kilda Road, Melbourne, Vic. 3004, Australia.
| | - Ingrid Hopper
- School of Public Health and Preventive Medicine, Monash University, 553St Kilda Road, Melbourne, Vic. 3004, Australia.
| | - John Zalcberg
- School of Public Health and Preventive Medicine, Monash University, 553St Kilda Road, Melbourne, Vic. 3004, Australia.
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Toward International Harmonization of Breast Implant Registries: International Collaboration of Breast Registry Activities Global Common Data Set. Plast Reconstr Surg 2020; 146:255-267. [PMID: 32740572 DOI: 10.1097/prs.0000000000006969] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND The Poly Implant Prothèse incident and breast implant-associated anaplastic large cell lymphoma have pointed to the need for uniform registries for breast implants as key features to monitoring the outcomes of breast implant surgeries internationally. The purpose of this study was to identify and harmonize common data elements collected by breast implant registries across the International Collaboration of Breast Registry Activities (ICOBRA) global consortium. METHODS The authors convened an international group of surgeons, consumers, nurses, registry experts, and regulators to review the data points. A modified Delphi approach was applied, to rate the importance of each point on a six-point Likert scale. RESULTS Data points from six national breast implant registries were divided into categories: clinical, implant-related, patient-reported findings; operation details and implanting technique details; patient characteristics; unique device identifiers; unique patient identifiers; and clinical demographics. A total of 52 data points collected by over 33 percent of national registries were identified. After five rounds, 34 data points formed the final set with agreed definitions. The group recognized the critical importance of additional elements that are currently not uniformly collected (e.g., patient-reported outcomes and long-term data) and set out the process for the dynamic global set updates driven by evidence gaps. CONCLUSIONS The authors defined internationally agreed on common data elements and definitions used in breast implant registries. This collaboration will allow data sets to be combined, enabling an effective global early warning system of implant-related problems and further work on data sets.
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Ruseckaite R, Maharaj AD, Krysinska K, Dean J, Ahern S. Developing a Preliminary Conceptual Framework for Guidelines on Inclusion of Patient Reported-Outcome Measures (PROMs) in Clinical Quality Registries. PATIENT-RELATED OUTCOME MEASURES 2019; 10:355-372. [PMID: 31849553 PMCID: PMC6911317 DOI: 10.2147/prom.s229569] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Accepted: 11/27/2019] [Indexed: 11/25/2022]
Abstract
Purpose Patient-centred and value-based health-care organisations are increasingly recognising the importance of the patient perspective in the measurement and evaluation of health outcomes. This has been primarily implemented using patient-reported outcome measures (PROMs). Clinical quality registries (CQRs) are specifically designed to improve direct clinical care, benchmark health-care provision and inform health service planning and policy. Despite CQRs having incorporated the patient perspective to support the evaluation of health-care provision, no evidence-based guidelines for inclusion of PROMs in CQRs exist. This has led to substantial heterogeneity in capturing and reporting PROMs within this setting. This publication is the first in a series describing the development of evidence-informed guidelines for PROMs inclusion within CQRs in Australia. Methods This study consisted of three components: 1) a literature review of existing evidence of guidelines, enablers, barriers, and lessons learnt of PROMs use within the CQRs setting; 2) a survey of Australian CQRs to determine current practices for PROMs use and reporting; and 3) development of a preliminary conceptual framework for PROMs inclusion in CQRs. Results Content analysis of the literature review and survey of 66 Australian registries elicited eight categories for the conceptual framework. The framework covers eight components: rationale, setting, ethics, selection of PROMs, administration, data management, statistical methods, feedback, and reporting. Conclusion We developed a preliminary conceptual framework, which classified findings, from both the literature and the survey, into broad categories ranging from initial development to outcome dissemination providing the structure for development of guidelines in the next phase of this project, engaging national and international leaders in health-related quality of life research, clinicians, researchers, patient advocates and consumers.
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Affiliation(s)
- Rasa Ruseckaite
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Ashika D Maharaj
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Karolina Krysinska
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Joanne Dean
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Susannah Ahern
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
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12
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Ahern S, Evans SM, Hopper I, Earnest A. Clinical quality registries for clinician‐level reporting: strengths and limitations. Med J Aust 2018. [DOI: 10.5694/mja17.00644] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Affiliation(s)
- Susannah Ahern
- Monash University, Melbourne, VIC
- University of Melbourne, Melbourne, VIC
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13
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Sypek MP, Jose MD, McDonald SP. Clinical quality registries for clinician-level reporting: strengths and limitations. Med J Aust 2018; 208:322-323. [PMID: 29642821 DOI: 10.5694/mja17.00581] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Accepted: 07/04/2017] [Indexed: 11/17/2022]
Affiliation(s)
- Matthew P Sypek
- Australia and New Zealand Dialysis and Transplant Registry, Adelaide, SA
| | | | - Stephen P McDonald
- Australia and New Zealand Dialysis and Transplant Registry, Adelaide, SA
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14
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Brown WA, MacCormick AD, McNeil JJ, Caterson ID. Bariatric Surgery Registries: Can They Contribute to Improved Outcomes? Curr Obes Rep 2017; 6:414-419. [PMID: 29076029 DOI: 10.1007/s13679-017-0286-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
PURPOSE OF REVIEW Clinical registries systematically collect prospective information about patients with a particular medical condition, who have had a medical device implanted or who have undergone a particular procedure. When these variables are collected with pre-defined quality indices included, the benched-marked risk-adjusted data may be a valuable resource for providing feedback on outcomes, including performance, to practitioners, patients, health services and device manufacturers. RECENT FINDINGS There are examples of feedback from clinical registries positively influencing patient care. The Australian National Joint Registry identified a poorly performing hip prosthesis which was ultimately withdrawn from the market. Feedback from the Victorian State Prostate Cancer Registry has contributed to improved patient care and fewer positive surgical margins noted over a 5-year reporting period. There are several national and regional registries collecting information on patients undergoing bariatric surgery, however, few currently focus on quality outcome measures. Whilst, current bariatric registries have contributed to improved understanding of some of the clinical situations relating to bariatric surgery, as well as developing composite risk scores and measuring quality cultures, they have not as yet demonstrably directly influenced patient care. This may reflect the fact that many of the registries do not hold data that are mature enough for proper analysis, but may also reflect problems with systematic data collection, bias from missing results and lack of appropriate funding. It will be important in the future that bariatric surgery registries actively seek to measure and validate their contribution to patient outcomes.
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Affiliation(s)
- Wendy A Brown
- Bariatric Surgery Registry, Monash University School of Public Health and Preventive Medicine, Melbourne, Australia.
- Monash University Department of Surgery, Alfred Hospital, Melbourne, Australia.
- Centre for Obesity Research and Education, Monash University School of Public Health and Preventive Medicine, Melbourne, Australia.
| | - Andrew D MacCormick
- Bariatric Surgery Registry, Monash University School of Public Health and Preventive Medicine, Melbourne, Australia
- Department of Surgery, University of Auckland, Auckland, New Zealand
| | - John J McNeil
- Bariatric Surgery Registry, Monash University School of Public Health and Preventive Medicine, Melbourne, Australia
| | - Ian D Caterson
- Bariatric Surgery Registry, Monash University School of Public Health and Preventive Medicine, Melbourne, Australia
- Boden Institute, Charles Perkins Centre, University of Sydney, Sydney, Australia
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