Browsing by Author "Ghali, William A."
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- ItemOpen AccessA multi-step approach to developing a health system evaluation framework for community-based health care(2022-07-09) Ludlow, Natalie C.; de Grood, Jill; Yang, Connie; Murphy, Sydney; Berg, Shannon; Leischner, Rick; McBrien, Kerry A.; Santana, Maria J.; Leslie, Myles; Clement, Fiona; Cepoiu-Martin, Monica; Ghali, William A.; McCaughey, DeirdreAbstract Background Community-based health care (CBHC) is a shift towards healthcare integration and community services closer to home. Variation in system approaches harkens the need for a conceptual framework to evaluate outcomes and impacts. We set out to develop a CBHC-specific evaluation framework in the context of a provincial ministry of health planning process in Canada. Methods A multi-step approach was used to develop the CBHC evaluation framework. Modified Delphi informed conceptualization and prioritization of indicators. Formative research identified evaluation framework elements (triple aim, global measures, and impact), health system levels (tiers), and potential CBHC indicators (n = 461). Two Delphi rounds were held. Round 1, panelists independently ranked indicators on CBHC relevance and health system tiering. Results were analyzed by coding agreement/disagreement frequency and central tendency measures. Round 2, a consensus meeting was used to discuss disagreement, identify Tier 1 indicators and concepts, and define indicators not relevant to CBHC (Tier 4). Post-Delphi, indicators and concepts were refined, Tier 1 concepts mapped to the evaluation framework, and indicator narratives developed. Three stakeholder consultations (scientific, government, and public/patient communities) were held for endorsement and recommendation. Results Round 1 Delphi results showed agreement for 300 and disagreement for 161 indicators. Round 2 consensus resulted in 103 top tier indicators (Tier 1 = 19, Tier 2 = 84), 358 bottom Tier 3 and 4 indicators, non-CBHC measure definitions, and eight Tier 1 indicator concepts—Mortality/Suicide; Quality of Life, and Patient Reported Outcome Measures; Global Patient Reported Experience Measures; Cost of Care, Access to Integrated Primary Care; Avoidable Emergency Department Use; Avoidable Hospitalization; and E-health Penetration. Post Delphi results refined Tier 3 (n = 289) and 4 (n = 69) indicators, and identified 18 Tier 2 and 3 concepts. When mapped to the evaluation framework, Tier 1 concepts showed full coverage across the elements. ‘Indicator narratives’ depicted systemness and integration for evaluating CBHC. Stakeholder consultations affirmed endorsement of the approach and evaluation framework; refined concepts; and provided key considerations to further operationalize and contextualize indicators, and evaluate CBHC as a health system approach. Conclusions This research produced a novel evaluation framework to conceptualize and evaluate CBHC initiatives. The evaluation framework revealed the importance of a health system approach for evaluating CBHC.
- ItemOpen AccessAlcohol and Drug Use Disorders among Patients with Myocardial Infarction: Associations with Disparities in Care and Mortality(Public Library of Science (PLoS), 2013-09-11) Beck, Cynthia A.; Southern, Danielle A.; Saitz, Richard; Knudtson, Merril L.; Ghali, William A.
- ItemOpen AccessCoding mechanisms for diagnosis timing in the International Classification of Diseases, Version 11(2022-09-16) Sundararajan, Vijaya; Le Pogam, Marie-Annick; Southern, Danielle A.; Pincus, Harold A.; Ghali, William A.Abstract Background Diagnoses that arise after admission are of interest because they can represent complications of health care, acute conditions arising de novo, or acute decompensation of a chronic comorbidity occurring during the hospital stay. Three countries in the world have adopted diagnosis timing codes for a number of years. Their experience demonstrates the feasibility and utility of associating an International Classification of Diseases, Version 9 or International Classification of Diseases, Version 10 diagnostic code with information on diagnosis timing, either as part of a diagnostic field or as a separate field. However, diagnosis timing is not an integrated feature of these two classifications as it will be for International Classification of Diseases, Version 11. Methods We examine the different types of diagnosis timing that can be used to describe complex patients and present examples of how the new International Classification of Diseases, Version 11 codes may be used. Results Extension codes are one of the important new features of International Classification of Diseases, Version 11 and allow more specificity in diagnosis timing. Conclusion Imbedded and standardized diagnosis timing information is possible within the International Classification of Diseases, Version 11 classification system.
- ItemOpen AccessComparison of distance measures in spatial analytical modeling for health service planning(BioMed Central, 2009-11-06) Shahid, Rizwan; Bertazzon, Stefania; Knudtson, Merril L.; Ghali, William A.
- ItemOpen AccessDeriving Evidence for Healthcare Decision Makers: The Case of Patient Flow(2015-09-02) Yergens, Dean W; Ghali, William A.In an ideal world, decision makers in health systems would make optimal decisions in a timely manner, fully informed by relevant information and evidence delivered in a timely way. This paradigm of Evidence-informed Decision Making (EIDM) is one that health systems can realistically strive for, so that decision makers can be enabled with the best available evidence for informed operational, tactical and strategic decisions. Methods to generate and convey evidence-based information include various types of literature reviews; data collection and statistical analysis through existing data sources or primary data collection; and the timely presentation of data and information in various presentation formats, sometimes referred to as dashboards and/or scorecards. One particularly challenging area in the healthcare sector, where EIDM could be of benefit, is in the management of patient flow in acute care hospitals. This dissertation showcases a mixed methodology program of work, applied to several sub-studies examining several aspects of patient flow in acute care hospitals: 1) A scoping review on the topic of patient flow in hospitals demonstrated a wide body of literature, but an overall lack of hospital-wide approaches; 2) An analysis of existing administrative data examined sepsis patients admitted to the hospital via the emergency department (ED) and demonstrated that patient outcomes may be impacted by Intensive Care Unit (ICU) occupancy; 3) A narrative review on information dashboards; 4) An accompanying survey study of ward-level patient flow decision-makers demonstrated a variety of views (and some fundamental disagreement) on what dashboards and scorecards actually are, but also some general enthusiasm for their potential in an EIDM paradigm; 5) A scoping review exploring novel machine learning methods demonstrated their potential application around various patient flow concepts in hospital settings; 6) A systematic review and meta-analysis of Medical Assessment Units (MAUs), solicited by health system decision-makers, summarized existing published evidence on MAUs and their benefits; and finally 7) An accompanying national environmental scan survey study of existing MAU-like initiatives in Canada. This dissertation illustrates how a variety of methods can be used to support a paradigm of EIDM in the area of patient flow.
- ItemOpen AccessDoes Integrated Management of Childhood Illness (IMCI) Training Improve the Skills of Health Workers? A Systematic Review and Meta-Analysis(PLoS, 2013-06-12) Nguyen, Duyen Thi Kim; Leung, Karen K.; McIntyre, Lynn; Ghali, William A.; Sauve, Reg
- ItemOpen AccessExploring data reduction strategies in the analysis of continuous pressure imaging technology(2023-03-01) Peng, Mingkai; Southern, Danielle A.; Ocampo, Wrechelle; Kaufman, Jaime; Hogan, David B.; Conly, John; Baylis, Barry W.; Stelfox, Henry T.; Ho, Chester; Ghali, William A.Abstract Background Science is becoming increasingly data intensive as digital innovations bring new capacity for continuous data generation and storage. This progress also brings challenges, as many scientific initiatives are challenged by the shear volumes of data produced. Here we present a case study of a data intensive randomized clinical trial assessing the utility of continuous pressure imaging (CPI) for reducing pressure injuries. Objective To explore an approach to reducing the amount of CPI data required for analyses to a manageable size without loss of critical information using a nested subset of pressure data. Methods Data from four enrolled study participants excluded from the analytical phase of the study were used to develop an approach to data reduction. A two-step data strategy was used. First, raw data were sampled at different frequencies (5, 30, 60, 120, and 240 s) to identify optimal measurement frequency. Second, similarity between adjacent frames was evaluated using correlation coefficients to identify position changes of enrolled study participants. Data strategy performance was evaluated through visual inspection using heat maps and time series plots. Results A sampling frequency of every 60 s provided reasonable representation of changes in interface pressure over time. This approach translated to using only 1.7% of the collected data in analyses. In the second step it was found that 160 frames within 24 h represented the pressure states of study participants. In total, only 480 frames from the 72 h of collected data would be needed for analyses without loss of information. Only ~ 0.2% of the raw data collected would be required for assessment of the primary trial outcome. Conclusions Data reduction is an important component of big data analytics. Our two-step strategy markedly reduced the amount of data required for analyses without loss of information. This data reduction strategy, if validated, could be used in other CPI and other settings where large amounts of both temporal and spatial data must be analysed.
- ItemOpen AccessField testing a new ICD coding system: methods and early experiences with ICD-11 Beta Version 2018(2022-11-08) Eastwood, Cathy A.; Southern, Danielle A.; Khair, Shahreen; Doktorchik, Chelsea; Cullen, Denise; Ghali, William A.; Quan, HudeAbstract Objective A beta version (2018) of International Classification of Diseases, 11th Revision for MMS (ICD-11), needed testing. Field-testing involves real-world application of the new codes to examine usability. We describe creating a dataset and characterizing the usability of ICD-11 code set by coders. We compare ICD-11 against ICD-10-CA (Canadian modification) and a reference standard dataset of diagnoses. Real-world usability encompasses code selection and time to code a complete inpatient chart using ICD-11 compared with ICD-10-CA. Methods and results A random sample of inpatient records previously coded using ICD-10-CA was selected from hospitals in Calgary, Alberta (N = 2896). Nurses examined these charts for conditions and healthcare-related harms. Clinical coders re-coded the same charts using ICD-11 codes. Inter-rater reliability (IRR) and coding time improved with ICD-11 coding experience (23.6 to 9.9 min average per chart). Code structure comparisons and challenges encountered are described. Overall, 86.3% of main condition codes matched. Coder comments regarding duplicate codes, missing codes, code finding issues enabled improvements to the ICD-11 Browser, Coding Tool, and Reference Guide. Training is essential for solid IRR with 17,000 diagnostic categories in the new ICD-11. As countries transition to ICD-11, our coding experiences and methods can inform users for implementation or field testing.
- ItemOpen AccessGeography and access to health services: a multimethod exploration of a centralized preoperative assessment clinic(2006) Seidel, Judy; Ghali, William A.
- ItemOpen AccessHealth surveillance for acute myocardial infarction in Canada: a comparison of administrative and laboratory data case definitions(2005) Galbraith, Phoebe Diane; Ghali, William A.
- ItemOpen AccessICD-11: A catalyst for advancing patient safety surveillance globally(2023-03-09) Forster, Alan J.; Chute, Christopher G.; Pincus, Harold A.; Ghali, William A.Abstract The World Health Organization’s (WHO) international classification of disease version 11 (ICD-11) contains several features which enable improved classification of patient safety events. We have identified three suggestions to facilitate adoption of ICD-11 from the patient safety perspective. One, health system leaders at national, regional, and local levels should incorporate ICD-11 into all approaches to monitor patient safety. This will allow them to take advantage of the innovative patient safety classification methods embedded in ICD-11 to overcome several limitations related to existing patient safety surveillance methods. Two, application developers should incorporate ICD-11 into software solutions. This will accelerate adoption and utility of software-enabled clinical and administrative workflows relevant to patient safety management. This is enabled as a result of the ICD-11 application programming interface (or API) developed by the WHO. Third, health system leaders should adopt the ICD-11 using a continuous improvement framework. This will help leaders at national, regional and local levels to take advantage of specific existing initiatives which will be strengthened by ICD-11, including peer review comparisons, clinician engagement, and alignment of front-line safety efforts with post marketing surveillance of medical technologies. While the investment to adopt ICD-11 will be considerable, these will be offset by reducing the ongoing costs related to a lack of accurate routine information.
- ItemOpen AccessInterpreting and coding causal relationships for quality and safety using ICD-11(2023-11-16) Januel, Jean-Marie; Southern, Danielle A.; Ghali, William A.Abstract Many circumstances necessitate judgments regarding causation in health information systems, but these can be tricky in medicine and epidemiology. In this article, we reflect on what the ICD-11 Reference Guide provides on coding for causation and judging when relationships between clinical concepts are causal. Based on the use of different types of codes and the development of a new mechanism for coding potential causal relationships, the ICD-11 provides an in-depth transformation of coding expectations as compared to ICD-10. An essential part of the causal relationship interpretation relies on the presence of “connecting terms,” key elements in assessing the level of certainty regarding a potential relationship and how to proceed in coding a causal relationship using the new ICD-11 coding convention of postcoordination (i.e., clustering of codes). In addition, determining causation involves using documentation from healthcare providers, which is the foundation for coding health information. The coding guidelines and examples (taken from the quality and patient safety domain) presented in this article underline how new ICD-11 features and coding rules will enhance future health information systems and healthcare.
- ItemOpen AccessReference management software for systematic reviews and meta-analyses: an exploration of usage and usability(BioMed Central, 2013-11-15) Lorenzetti, Diane; Ghali, William A.
- ItemOpen AccessThe relationship between urban environment and the inflammatory bowel diseases: a systematic review and meta-analysis(BioMed Central, 2012) Kaplan, Gilaad G.; Soon, Ing Shian; Molodecky, Natalie A.; Rabi, Doreen M.; Ghali, William A.; Barkema, Herman W.
- ItemOpen AccessThe Seamless Transfer-of-Care Protocol: a randomized controlled trial assessing the efficacy of an electronic transfer-of-care communication tool(BioMed Central, 2012-11-21) Okoniewska, Barbara M.; Santana, Maria J.; Holroyd-Leduc, Jayna M.; Flemons, W. Ward; O'Beirne, Maeve; White, Deborah; Clement, Fiona M.; Forster, Alan; Ghali, William A.
- ItemOpen AccessSocio-economic status and diabetes: disease burden, clinical profiles and quality of care(2006) Rabi, Doreen; Ghali, William A.
- ItemOpen AccessThe three-part model for coding causes and mechanisms of healthcare-related adverse events(2022-02-24) Southern, Danielle A.; Harrison, James E.; Romano, Patrick S.; Le Pogam, Marie-Annick; Pincus, Harold A.; Ghali, William A.Abstract ICD-11 provides a promising new way to capture healthcare-related harm or injury. In this paper, we elaborate on the framework for describing healthcare-related events where there is a presumed causal link between an event and underlying healthcare-related factors. The three-part model for describing healthcare-related harm or injury in ICD-11 consists of (1) a healthcare-related activity that is the cause of injury or other harm (selected from Chapter 23 of ICD-11); (2) a mode or mechanism of injury or harm, related to the underlying cause (also from Chapter 23 of ICD-11); and (3) the harmful consequences of the event to the patient, selected from any of Chapters 1 through 22 of ICD-11 (most importantly, the injury or harm experienced by the patient). Concepts from these three elements are linked/clustered through postcoordination to reflect the three-part model in a single coded expression. ICD-11 contains many novel features, and the three-part model described here for healthcare-related adverse events is a notable example.
- ItemOpen AccessVisualizing the 11th Classification of Diseases(2019-10-05) Aseniero, Bon Adriel; Knudsen, Søren; Ghali, William A.; Carpendale, SheelaghWe designed and implemented an interactive artistic data visualization of the 11th International Classification of Diseases (ICD-11). Our visualization primarily showcases the structure of the ICD-11, showing how the different codes fall into the main disease categories (chapters) and subcategories. This is our preliminary approach in the design and study of artistic visualizations for exploring the ICD-11, as well as aid in its awareness campaign.