Search

Your search keyword '"Katz, Alan"' showing total 43 results
Start Over Author "Katz, Alan" Publisher swansea university
43 results on '"Katz, Alan"'

4. Documenting First Nations Access to COVID Vaccines: A whole-population linked administrative data study.

Author

Nickel, Nathan C., primary, Phillips-Beck, Wanda, additional, Star, Leona, additional, Okechukwu, Ekuma, additional, Taylor, Carole, additional, Balogun, Oludolapo Deborah, additional, Brownell, Marni, additional, Casidsid, Hera, additional, Chartier, Mariette, additional, Chateau, Dan, additional, Enns, Jennifer, additional, Katz, Alan, additional, Lavoie, Josee, additional, Lix, Lisa, additional, Mahar, Alyson, additional, Romanescu, Razvan, additional, and Urquia, Marcelo, additional

Published
2022
Full Text
View/download PDF

5. A population data-driven approach to identifying ‘Long COVID’ cases in support of diagnosis and treatment.

Author

Enns, Jennifer, primary, Katz, Alan, additional, Yogendran, Marina, additional, Urquia, Marcelo, additional, Muthukumarana, Saman, additional, Matharaarachchi, Surani, additional, Singer, Alexander, additional, Nickel, Nathan, additional, Star, Leona, additional, Cavett, Teresa, additional, Keynan, Yoav, additional, Lix, Lisa, additional, and Sanchez-Ramirez, Diana, additional

Published
2022
Full Text
View/download PDF

6. Experiences of Red River Métis Accessing COVID Vaccines: A partnership-based, whole-population linked administrative data study.

Author

Nickel, Nathan C., primary, Sanguins, Julianne, additional, Ekuma, Okechukwu, additional, Taylor, Carole, additional, Eze, Nkiruka, additional, Balogun, Oludolapo Deborah, additional, Casidsid, Hera, additional, Brownell, Marni, additional, Chartier, Mariette, additional, Chartrand, Francis, additional, Chateau, Daniel, additional, Driedger, Michelle, additional, Enns, Jennifer, additional, Katz, Alan, additional, Klos, Olena, additional, Lix, Lisa, additional, Mahar, Alyson, additional, Neault, Rachelle, additional, and Urquia, Marcelo, additional

Published
2022
Full Text
View/download PDF

21. No Strings Attached: Evaluating an Unconditional Prenatal Income Supplement Using Linked Administrative Data

Author

Brownell, Marni, Chartier, Mariette, Nickel, Nathan, Chateau, Dan, Sarkar, Joykrishna, Burland, Elaine, Jutte, Doug, Taylor, Carole, Santos, Rob, and Katz, Alan

Subjects
lcsh:HB848-3697, lcsh:Demography. Population. Vital events, Article
Abstract

Objective Perinatal outcomes have improved overall in developed countries over the last several decades but remain poor for disadvantaged populations. In Manitoba, Canada, the Healthy Baby Prenatal Benefit (HBPB), a cash transfer to low-income pregnant women, was introduced with the goal of improving perinatal outcomes. The objective of this study was to use linked administrative and program datasets to determine whether this unconditional income supplement was associated with improved birth outcomes for a low-income population. Approach This study used data from the PATHS Data Resource, which contains population-level health and social service records as well as program data for approximately 600,000 children in Manitoba, Canada, over a 30-year period, linkable at the individual level. All mother-newborn pairs, from 2003-2010, who met the following criteria were included for analyses: i) the mother was on social assistance (i.e., low income); ii) the infant was born in hospital; and, iii) the pair had a newborn risk screen (n=14,591), documenting factors such as prenatal alcohol and tobacco exposure and maternal and family characteristics. Low-income women who received HBPB (exposed, 10,738) were compared with low-income women who did not receive HBPB (unexposed, 3,853) on several outcomes: low birth weight, preterm, small- and large-for-gestational age, 5-minutes Apgar scores, breastfeeding initiation, neonatal readmission, and newborn hospital length of stay (LOS). Covariates from the risk screens were used to develop propensity scores to construct Inverse Probability of Treatment Weights, to balance differences between exposed and unexposed groups in regression models. Gamma sensitivity analyses assessed sensitivity to unmeasured confounding. Population attributable and preventable fractions were calculated. Results HBPB exposure was associated with reductions in low birth weight (adjusted risk ratio, aRR=0.71, 95% CI=0.63, 0.81), preterm (aRR=0.76 (0.69, 0.84)) and small-for-gestational age (aRR=0.90 (0.81, 0.99)) births and increases in breastfeeding (aRR=1.06 (1.03, 1.09)) and large-for-gestational age births (aRR=1.13 (1.05, 1.23)). For vaginal births, HBPB was associated with shortened LOS (mean=2.86, p

Published
2017

22. Do socially complex patients seek primary care from clinics specifically designed to meet their needs?

Author

Katz, Alan, Chateau, Dan, Taylor, Carole, and Valdivia, Jeff

Subjects
lcsh:HB848-3697, lcsh:Demography. Population. Vital events, Article
Abstract

Objectives To determine the relationship between known social complexity and model of primary care service delivery Approach The impacts of the social determinants of health are well described. To understand the contribution of specific factors on primary care service use we linked social data in the Population Health Research Data Repository at the Manitoba Centre for Health Policy to health system data. We included all patients visiting a Winnipeg clinic at least three times between 2010 and 2013. We allocated each participant to the primary care provider providing the majority of their care; and each provider was assigned to the model of care where they provided the majority of their clinical care. We developed eleven new indicators to describe social complexity such as: children in care, low income quintile, income assistance (welfare), high residential mobility, and involvement with the justice system. Results The cohort included 626,264 unique individuals of whom 53.1% were female. The majority of participants received their care from the fee for service (FFS) model (511,763) followed by 76,261 assigned to “reformed FFS”. 16,536 and 12,178 were assigned to the 2 team-based care alternative funded models and 9,526 to the teaching clinic model. Patients with social complexities, except for newcomers, were more likely to attend the alternative funded clinics. The patients these clinics served were generally very complex with over 15% having more than 5 complexities compared to less than 5% of those attending the FFS models. Twice as many patients in the FFS models (60%) had no complexities compared to the alternative funded models. Conclusion The availability of social data in population health repositories provides new opportunities to understand the distribution of these social factors amongst care providers and the impact of each on the health of populations. This new understanding can support focused interventions to address specific social risk factors and provide the evidence to support different models of primary care service delivery.

Published
2017

23. Chronic Disease Case Definitions for Electronic Medical Records: A Canadian Validation Study

Author

Lix, Lisa, Singer, Alexander, Katz, Alan, Yogendran, Marina, and Al-Azazi, Saeed

Subjects
lcsh:HB848-3697, lcsh:Demography. Population. Vital events, Article
Abstract

Objectives Canadians are investing heavily in electronic medical records (EMRs) to inform primary care practice improvements. The Canadian Primary Care Sentinel Surveillance Network (CPCSSN) is a national practice-based network that has enrolled more than one million patients to date. Accurate CPCSSN EMR data are essential for unbiased research about chronic disease prevention and management. The study purpose was to test the accuracy of chronic disease case definitions in EMR data from one CPCSSN site. Approach This study linked CPCSSN EMR data, hospital records, physician billing claims, prescription drug records, and population registration files for the province of Manitoba. Individuals who had at least one encounter with a CPCSSN practice between 1998 and 2012, were at least 18 years of age, and had a minimum of two years of healthcare coverage before and after the study index date were included. Separate cohorts were defined for the following chronic diseases: chronic obstructive pulmonary disease (COPD), depression, diabetes, hypertension, and osteoarthritis. Validated case definitions based on diagnoses in physician and hospital records and prescription drug data were used estimate sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and kappa of each EMR chronic disease case definition. Results More than 74,000 individuals were included in each cohort, except for COPD which had 51,000. Approximately half of each cohort was comprised of urban residents. The average age ranged from 45.9 years for individuals with depression to 65.3 years for individuals with COPD. Hypertension had the highest prevalence (22.0%) in EMR data followed by depression (14.6%). Estimates of agreement (i.e., kappa) for EMR and administrative data ranged from 0.47 for COPD to 0.58 for diabetes. Sensitivity of the EMR data was lowest for COPD (37.4%; 95% CI 36.0-38.8) and highest for diabetes (57.6%; 95% confidence interval [CI] 56.6-58.6). PPV estimates were lowest for osteoarthritis (66.9%; 95% CI 66.0-67.8) and highest for hypertension (78.3%; 95% CI 77.7-78.9). Specificity estimates were consistently above 90% and NPV estimates were always greater than 80%. Validity estimates for the EMR case definitions were associated with demographic and comorbidity characteristics of the study cohorts. Conclusions Validity of EMR data, when compared to administrative health data, for ascertaining five different chronic diseases was fair to good; it varied with the disease under investigation. Further research is needed to identify methods for improving the accuracy of chronic disease case definitions in EMR data.

Published
2017

35. Building a Pan-Canadian Real World Health Data Network

Author

Smith, Mark, primary, Schull, Michael, additional, McGrail, Kimberlyn, additional, Katz, Alan, additional, Diverty, Brent, additional, McDonald, Ted, additional, Victor, Charles, additional, Lix, Lisa, additional, and Paprica, Alison, additional

Published
2018
Full Text
View/download PDF

42. Orthopedic and ophthalmology surgical service forecast modelling in Manitoba: Research approach for a data linkage study.

Author

Katz A, Owczar H, Taylor C, Bowes JM, and Soodeen RA

Subjects
Humans, Manitoba, Forecasting, Hospitals, Ophthalmology, Orthopedics
Abstract

Background: The healthcare system in Manitoba, Canada has faced long wait times for many surgical procedures and investigations, including orthopedic and ophthalmology surgeries. Wait times for surgical procedures is considered a significant barrier to accessing healthcare in Canada and can have negative health outcomes for patients. We developed models to forecast anticipated surgical procedure demands up to 2027. This paper explores the opportunities and challenges of using administrative data to describe forecasts of surgical service delivery., Methods: This study used whole population linked administrative health data to predict future orthopedic and ophthalmology surgical procedure demands up to 2027. Procedure codes (CCI) from hospital discharge abstracts and medical claims data were used in the modelling. A Seasonal Autoregressive Integrated Moving Average model provided the best fit to the data from April 1, 2004 to March 31, 2020., Results: Initial analyses of only hospital-based procedures excluded a significant portion of provider workload, namely those services provided in clinics. We identified 500,732 orthopedic procedures completed between April 1, 2004 and March 31, 2020 (349,171 procedures identified from hospital discharge abstracts and 151,561 procedures from medical claims). Procedure volumes for these services are expected to rise 17.7% from 2020 (36,542) to 2027 (43,011), including the forecasted 43.9% increase in clinic-based procedures. Of the 660,127 ophthalmology procedures completed between April 1, 2004 and March 31, 2020, 230,717 procedures were identified from hospital discharge abstracts and 429,410 from medical claims. Models forecasted a 27.7% increase from 2020 (69,598) to 2027 (88,893) with most procedures being performed in clinics., Conclusion: Researchers should consider including multiple datasets to add information that may have been missing from the presumed data source in their research approach. Confirming the completeness of the data is critical in modelling accurate predictions. Forecast modelling techniques have evolved but still require validation., Competing Interests: Statement of conflict of interest: The authors have no conflicts of interest to declare.

Published
2023
Full Text
View/download PDF

43. Developing and Validating a Primary Care EMR-based Frailty Definition using Machine Learning.

Author

Tyler Williamson P, Aponte-Hao S, Mele B, Lethebe BC, Leduc C, Thandi M, Katz A, and Wong ST

Abstract

Introduction: Individuals who have been identified as frail have an increased state of vulnerability, often leading to adverse health events, increased health spending, and potentially detrimental outcomes., Objective: The objective of this work is to develop and validate a case definition for frailty that can be used in a primary care electronic medical record database., Methods: This is a cross-sectional validation study using data from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) in Southern Alberta. 52 CPCSSN sentinels assessed a random sample of their own patients using the Rockwood Clinical Frailty scale, resulting in a total of 875 patients to be used as reference standard. Patients must be over the age of 65 and have had a clinic visit within the last 24 months. The case definition for frailty was developed using machine learning methods using CPCSSN records for the 875 patients., Results: Of the 875 patients, 155 (17.7%) were frail and 720 (84.2%) were not frail. Validation metrics of the case definition were: sensitivity and specificity of 0.28, 95% CI (0.21 to 0.36) and 0.94, 95% CI (0.93 to 0.96), respectively; PPV and NPV of 0.53, 95% CI (0.42 to 0.64) and 0.86, 95% CI (0.83 to 0.88), respectively., Conclusions: The low sensitivity and specificity results could be because frailty as a construct remains under-developed and relatively poorly understood due to its complex nature. These results contribute to the literature by demonstrating that case definitions for frailty require expert consensus and potentially more sophisticated algorithms to be successful., Competing Interests: Conflicts of Interest.: None to declare.

Published
2020
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results