More than 1.53 million defects were reported in Korea Land & Housing Corp.'s public housing over five years, with defect rates rising alongside increased supply, prompting calls for quality improvements as government-led expansion continues.
#YonhapInfomax #KoreaLandHousingCorp #PublicHousing #DefectCases #HousingSupply #QualityImprovement #Economics #FinancialMarkets #Banking #Securities #Bonds #StockMarket
https://en.infomaxai.com/news/articleView.html?idxno=82607
Over 1.53 Million Defects Reported in LH Public Housing Over Past Five Years

More than 1.53 million defects were reported in Korea Land & Housing Corp.'s public housing over five years, with defect rates rising alongside increased supply, prompting calls for quality improvements as government-led expansion continues.

Yonhap Infomax

Say goodbye to paper-based processes! Discus QMS provides a centralized platform for electronic document management, ensuring version control and easy access.

Visit: https://zurl.co/vdvNH

#QualityImprovement #Efficiency #Automation #DigitalTransformation #Quality40

Discus QMS

Ensure compliance and streamline quality processes with Discus QMS. A robust solution for regulated industries, tailored for operational excellence.

Tired of inefficient quality processes? 🤔 Discus QMS simplifies quality management, reduces errors, and improves overall efficiency.

Visit: https://zurl.co/vdvNH

#QualityImprovement #SupplierQualityManagement #complaintmanagement #21CFRpart11 #QMSSystem #automated #CAPA

Discus QMS

Ensure compliance and streamline quality processes with Discus QMS. A robust solution for regulated industries, tailored for operational excellence.

Hospital Diagnostic Errors May Affect 7% of Patients

As many as 1 in 14 patients suffer harm due to diagnostic errors while in hospital, and most of these could be prevented, a study showed.

Medscape

Even though chronic pain is very common in people with cerebral palsy, it’s often not adequately treated or managed in regular clinical care. In this new podcast episode, Dr. Amy Bailes and Dr. Mary Gannotti discuss their ongoing CPARF-funded research focused on improving the quality of care for adults with cerebral palsy who experience pain.
https://cparf.org/cwp-s3-ep15/

#cerebralpalsy #research #science #neuroscience #pain #clinicalresearch #podcast #podcasts #scicomm #qualityimprovement

Episode Fifteen | Changing What’s Possible: The Disability Innovation Podcast | Season Three | Cerebral Palsy Alliance Research Foundation

Listen to Episode Thirteen, Season Three of Changing What’s Possible on Apple, Spotify, & Audible.

Getting ready for my first paper presentation at #ASEEannual. This paper is based on my work for my #KEEN Engineering Unleashed #Fellowship and the @i2lab this year! You can stop by C122 of the Convention Center at 3:30 pm PT to learn more.

#engineeringEducation #engEd #academia #academicMastodon #highered #dei #deiba #laboratory #instruction #UDL #HCD #EML #qualityImprovement #access #belonging

📢 @prereview & @JMIRPub joining forces once again to improve scholarly peer review! There is still time to join us for our next #LiveReview event on Mar 28 at 12:00 ET/16:00 UTC where we will be reviewing this @medrxivpreprint https://doi.org/10.1101/2023.05.24.23290382

Register: https://forms.gle/zYjUr3UKi6svrUes8

#xHealthSystemsandQualityImprovement #healthsystems #qualityimprovement #ReviewTogether

Reevaluation of the Variable Component of the Systematic Error Calls for Paradigm Change in Clinical Laboratory Quality Control

The existence of the variable component of the systematic error (VCSE) is known since 1963, but seems to be a kind of taboo: neither has definition in VIM, nor is present in equations, being considered transformed in time into random error. Present study using methods of mathematical statistics, computer simulations and examples from the day-to-day practice of the author makes an attempt to reevaluate its role and significance in the QC in clinical laboratory. “The bias” (which one?) it is a definitional uncertainty, because it is time-variable. Making clear distinction between bias measured in repeatability respective reproducibility within laboratory (RW) conditions as in case of standard deviations, and also separating constant and variable subcomponents of the systematic error, two sets of error parameters are obtained each set being consistent with the measurement conditions. The link between them is the time-variable VCSE function. The conditions of calculations and predictions based on them must be consistent with the conditions of their determination, to avoid the redundant use. Being consequent, several differences can be discovered between the constant and the variable component of the systematic error respective random phenomena, also between variable and random error components. The variable components of the systematic errors are cyclical, mostly predictable variations (shifts and drifts) in the daily mean. However, it is presented a direct method to determine the SD of the VCSE, its easiest calculation is possible from accurate values of sr and sRW. There are presented methods to calculate sr and sRW from long term data. As conclusion there is necessary a new paradigm of the QC in clinical laboratory based on the proposed error model. Motto “Everything Should Be Made as Simple as Possible, But Not Simpler” (A. Einstein) . ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study did not receive any funding ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present work are contained in the manuscript. * VIM : International Vocabulary of Metrology QC : Quality Control EQA : External Quality Assessment MU : measurement uncertainty TE : total measurement error RE : Random error component SE : Systematic error component VCSE(t) : Variable Component of Systematic Error in the moment t (a time-variable function) CCSE : Constant Component of Systematic Error SD : Standard Deviation (in general) sr : SD measured in constant, repeatability conditions sRW : SD measured in variable, reproducibility within laboratory conditions sVCSE : the SD calculable from the daily(run) mean (bias, VCSE(t)) values smean : the SD calculable from the monthly means CV : Coefficient of Variation, the SD expressed as percent of the mean of measurements CVr : CV measured in constant, repeatability conditions CVRW : CV measured in variable, reproducibility within laboratory conditions CVVCSE : CV of the VCSE(t), sVCSE expressed as percent of the target value B : bias B% : bias expressed as percent of the long-term mean of measurements ∆ B % : percent expressed bias variation in a shift (percent of the long-term mean value) Br(t) : (short term or within day) bias measured in repeatability conditions in the moment t (a time-variable function) BRW : long term mean bias, measured in RW conditions, a constant RMS : root mean square - the root of the arithmetic mean of squares (not to be confused with the RMSE) max□ (max index before) : the maximum value of a parameter in given conditions z : coefficient of confidence c : concentration or activity of a measurand n : number of measurements t : time or moment, expressed as run number Fcal : the slope factor of the linear calibration curve x : (control) measurement result xt : (control) measurement result in the moment t ![Graphic][1]</img> : mean of measurements ![Graphic][2]</img> : the daily (run) mean in the moment t (repeatability conditions) CLSI : Clinical and Laboratory Standards Institute ANOVA : analysis of variance V : variance, the square of the SD Vw : Variance within run (notation in CLSI EP15-A3), the square of sr Vb : Variance between runs (notation in CLSI EP15-A3), the square of sVCSE Vwl : Variance within laboratory (notation in CLSI EP15-A3), the square of sRW [1]: /embed/inline-graphic-19.gif [2]: /embed/inline-graphic-20.gif

medRxiv

November marks the exciting observance of Quality Month! It's a time when industries of all kinds shine a spotlight on the crucial role of quality management. Explore these Four Dynamic Steps to Elevate Quality in Your Workplace!

#QualityMonth #QualityManagement #QualityImprovement #ElevateQuality #WorkplaceExcellence #ContinuousImprovement #QualityFirst #QualityStandards #QualityAssurance #ProcessExcellence #QualityControl #OperationalExcellence

Members of the #ISOQOL_CP and #ISOQOL_PE discuss three case studies from the UK, USA, Australia collated to explore how adherence to PROMs can be evaluated and understood
https://link.springer.com/article/10.1007/s11136-023-03505-y

Focusing on #HelthCare systems, patients, clinical teams, and #QualityImprovement in measurement, the authors derive nine key recommendations for future research and practice (Table 3):
https://link.springer.com/article/10.1007/s11136-023-03505-y/tables/3

#ISOQOL #FeedbackSystems #PatientCentered #Psychometrics

Patient adherence to patient-reported outcome measure (PROM) completion in clinical care: current understanding and future recommendations - Quality of Life Research

Background Patient-reported outcome measures (PROMs) are increasingly being used as an assessment and monitoring tool in clinical practice. However, patient adherence to PROMs completions are typically not well documented or explained in published studies and reports. Through a collaboration between the International Society for Quality-of-Life Research (ISOQOL) Patient Engagement and QOL in Clinical Practice Special Interest Groups (SIGs) case studies were collated as a platform to explore how adherence can be evaluated and understood. Case studies were drawn from across a range of clinically and methodologically diverse PROMs activities. Results The case studies identified that the influences on PROMs adherence vary. Key drivers include PROMs administeration methods within a service and wider system, patient capacity to engage and clinician engagement with PROMs information. It was identified that it is important to evaluate PROMs integration and adherence from multiple perspectives. Conclusion PROM completion rates are an important indicator of patient adherence. Future research prioritizing an understanding of PROMs completion rates by patients is needed.

SpringerLink
Does anyone have a recommendation for a survey I can use to measure patient satisfaction for a Physician Quality Improvement project? #patientcare #patientsafety #Qualityimprovement