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Design is a highly nonlinear chaotic dynamic process with many possible solutions, some of which can be creative. The chaotic nonlinearity of design dynamics triggers mental stresses in designers, whose creativity happens only when their mental stresses are at an optimal level. Following a deductive approach, this paper investigates how knowledge can contribute to designer creativity by uncovering knowledge's (good and bad) roles in the design process, based on which three ways are recommended to use knowledge properly in design. The assumption is that all designs follow one governing equation, which is a recursive integration of three basic design activities: formulation, evaluation and synthesis. The difference between designs of various fields and different kinds (routine, innovative and creative) lies in the range, content, size and nature of the design space in which the design governing equation works. The design governing equation implies a nonlinear chaotic design dynamics, whose solutions are sensitive to its initial conditions and can be routine, innovative or creative. The design governing equation is solved and reformulated by the designer's creativity capability. Therefore, design researchers, practitioners and educators should cohesively look at both designer's knowledge/experience and the designer's creative thinking process. [ABSTRACT FROM AUTHOR]

Objective: To estimate rates of revision surgery after insertion of mesh midurethral slings and explore whether physician specialty, annual operative volume, or hospital type are associated with this outcome.Methods: A population-based retrospective cohort of women undergoing midurethral sling procedures over a 13-year interval (2004-2017) in Alberta, Canada was created using administrative health data. The primary outcome was subsequent surgery for revision of midurethral sling, defined by a composite of surgical procedures. Exposures included annual number of midurethral sling procedures performed by the surgeon, surgeon specialty, facility type, patient age, and concomitant prolapse repair. Mixed effects logistic regression using linear spines was used to test a-priori hypothesis that annual surgical volume would be inversely related in a nonlinear fashion to risk of revision.Results: In the cohort of 19,511 women, cumulative rates of revision surgery were 3.84% (95% CI 3.54-4.17) at 5 years and 5.26% (95% CI 4.82-5.74) at 10 years. The first year after midurethral sling placement was the most vulnerable window, with 0.40% (95% CI 0.31-0.49) undergoing revision within 30 days and 2.15% (95% CI 1.95-3.52) within 1 year. Concomitant prolapse repairs (odds ratio [OR] 1.24, 95% CI 1.04-1.48) and surgeon's annual volume were associated with revision. After 50 cases per year, odds of revision declined with each additional case (OR 0.99/case, 95% CI 0.98-0.99, OR 0.91/10 cases, 95% CI 0.84-0.98) and plateaued at 110 cases per year. Surgeon specialty, hospital type, and patient age were not associated with outcome.Conclusion: One in 20 women undergo revision surgery within 10 years after midurethral sling placement. Higher physician surgical volume is associated with decreased risk, with the decline occurring at a threshold of 50 cases annually. Minimum caseload parameters for surgeons performing midurethral sling procedures may improve quality of these procedures.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. [ABSTRACT FROM AUTHOR]

Question: Are there ways to mitigate the challenges associated with imperfect data validity in Patient Safety Indicator (PSI) report cards?Findings: Applying a methodological framework on simulated PSI report card data, we compare the adjusted PSI rates of three hospitals with variable quality of data and coding. This framework combines (i) a measure of PSI rates using existing algorithms; (ii) a medical record review on a small random sample of charts to produce a measure of hospital-specific data validity and (iii) a simple Bayesian calculation to derive estimated true PSI rates. For example, the estimated true PSI rate, for a theoretical hospital with a moderately good quality of coding, could be three times as high as the measured rate (for example, 1.4% rather than 0.5%). For a theoretical hospital with relatively poor quality of coding, the difference could be 50-fold (for example, 5.0% rather than 0.1%).Meaning: Combining a medical chart review on a limited number of medical charts at the hospital level creates an approach to producing health system report cards with estimates of true hospital-level adverse event rates. [ABSTRACT FROM AUTHOR]

Background: There are ethno-cultural differences in cardiac patients' adherence to medications. It is unclear why this occurs. We thus aimed to generate an in-depth understanding about the decision-making process and potential ethno-cultural differences, of white, Chinese, and south Asian cardiac patients when making the decision to adhere to a medication regimen. Methods: A hierarchical descriptive decision-model was generated based on previous qualitative work, pilot tested, and revised to be more parsimonious. The final model was examined using a novel group of 286 cardiac patients, using their self-reported adherence as the reference. Thereafter, each node was examined to identify decision-making constructs that might be more applicable to white, Chinese or south Asian groups. Results: Non-adherent south Asians were most likely to identify a lack of receipt of detailed medication information, and less confidence and trust in the health care system and health care professionals. Both Chinese and south Asian participants were less likely to be adherent when they had doubts about western medicine (eg, the effects and safety of the medication). Being able to afford the cost of medications was associated with increased adherence. Being away from home reduced the likelihood of adherence in each group. The overall model had 67.1% concordance with the participants' initial self-reported adherence, largely due to participants' overreporting adherence. Conclusion: These identified elements of the decision-making process are generally not considered in traditionally used medication adherence questionnaires. Importantly these elements are modifiable and ought to be the focus of both interventions and measurement of medication adherence. [ABSTRACT FROM AUTHOR]

Background: Though pharmacy claims data are commonly used to study medication adherence, there remains no standard operational definition for adherence especially for patients on multiple medications. Even when studies use the same terminology, the actual methods of calculating adherence can differ drastically. It is unclear whether the use of different definitions results in different conclusions regarding adherence and associated outcomes. The objective of our study was to compare adherence rates and associations with mortality using different operational definitions of adherence, and using various methods of handling concurrent medication use. Methods: We conducted a cohort study of patients aged ≥65 years from Manitoba, Canada, with incident hypertension diagnosed in 2004 and followed to 2009. We calculated adherence rates to anti-hypertensive medications using different operational definitions of medication adherence (including interval and prescription based medication possession ratios [MPR] and proportion of days covered [PDC]). For those on concurrent medications, we calculated adherence rates using the different methods of handling concurrent medication use, for each definition. We used logistic regression to determine the association between adherence and mortality for each operational definition. Results: Among 2199 patients, 24.1% to 90.5% and 71.2% to 92.7% were considered adherent when using fixed interval and prescription-based interval medication possession ratios [MPRi and MPRp] respectively, depending on how concurrent medications were handled. Adherence was inversely associated with death, with the strongest association for MPRp measures. This association was significant only when considering adherence to any antihypertensive [aOR 0.70, 95% CI 0.51, 0.97], or when the mean of the class-specific MPRp's [adjusted OR 0.71, 95% CI 0.53, 0.95] was used. No significant association existed when the highest or lowest class-specific MPRp was used as the adherence estimate. Conclusion: The range of adherence estimates varies widely depending on the operational definition used. Given less variation in adherence rates and their stronger association against mortality, we recommend using prescriptionbased MPR's to define medication adherence. [ABSTRACT FROM AUTHOR]

A systematic scoping review of health system Performance and Quality Indicators (PQI) related literature for evaluating publicly funded home care programming was conducted. Through the scoping review we identify PQIs, map these based on quadrants of the Institute for Healthcare Improvement's (IHI) Quadruple Aim, classify these PQIs under general "areas of focus" categories, and present recommendations for use. We selected all articles that identified, referenced, proposed, and/or described at least 1 PQI to measure home care service programming. Minimum inclusion criteria were a description of 1 or more PQIs designed to evaluate and/or measure home care programming, outcomes of home care clients and/or caregivers, or overall system impacts of home care service provision. The review identified 3,475 citations. A review of the abstracts led to the retrieval of 510 full-text articles for assessment of which 105 articles were selected for detailed review and extraction of identified PQIs. Of the 105 identified articles a total of 829 unique PQIs were gathered. Based on the IHI Quadruple Aim, 661 unique measures were identified as Clinical Outcome, 35 as Healthcare Provider Satisfaction, 99 Patient Experience, and 34 in the Financial/Sustainability quadrants. Many patient outcome specific PQIs exist, followed by patient experience measures. Very few PQIs exist in the financial or healthcare provider experience quadrants. The lack of indicators across all the IHI Quadruple Aim quadrants is an opportunity for further development supporting home care quality oversight. [ABSTRACT FROM AUTHOR]

Background: Survey research in healthcare is an important tool to collect information about healthcare delivery, service use and overall issues relating to quality of care. Unfortunately, physicians are often a group with low survey response rates and little research has looked at response rates among physician specialists. For these reasons, the purpose of this project was to explore survey response rates among physician specialists in a large metropolitan Canadian city. Methods: As part of a larger project to look at physician payment plans, an online survey about medical billing practices was distributed to 904 physicians from various medical specialties. The primary method for physicians to complete the survey was via the Internet using a well-known and established survey company (www.surveymonkey.com). Multiple methods were used to encourage survey response such as individual personalized email invitations, multiple reminders, and a draw for three gift certificate prizes were used to increase response rate. Descriptive statistics were used to assess response rates and reasons for non-response. Results: Overall survey response rate was 35.0%. Response rates varied by specialty: Neurology/neurosurgery (46.6%); internal medicine (42.9%); general surgery (29.6%); pediatrics (29.2%); and psychiatry (27.1%). Non-respondents listed lack of time/survey burden as the main reason for not responding to our survey. Conclusions: Our survey results provide a look into the challenges of collecting healthcare research where response rates to surveys are often low. The findings presented here should help researchers in planning future survey based studies. Findings from this study and others suggest smaller monetary incentives for each individual may be a more appropriate way to increase response rates. [ABSTRACT FROM AUTHOR]

Objective To compare ethnic and sex difference in the incidence of newly diagnosed hypertension, and subsequent risk of cardiovascular disease outcomes among South Asian, Chinese and white patients. Methods We identified patients with newly diagnosed hypertension aged =20 years. Patients were followed for 1-9 years for all-cause mortality and cardiovascular disease with myocardial infarction, heart failure and stroke. Cox proportional hazard models stratified by sex and adjusted for age, median income and co-morbid conditions, were constructed to determine the independent association between ethnicity and the development of the combined cardiovascular endpoint as well as death. Results There were 39 175 South Asian (49.4% men, 34.4% age =65), 49 892 Chinese (48.1% men, 36.7% age =65) and 841 277 white (47.9% men, 38.8% age =65) patients with newly diagnosed hypertension. Age and sex adjusted incidence of hypertension was highest in South Asian patients and lowest in Chinese patients. Compared with white patients, South Asian and Chinese patients had a lower mortality (adjusted HR (aHR) 0.91 and 0.66) and risk of cardiovascular disease outcomes (aHR 0.94 and 0.49). Compared to men, women had significantly lower mortality (aHR: 0.83 for Chinese, 0.78 for South Asian and 0.77 for white) and cardiovascular disease outcomes (0.72 for Chinese, 0.63 for South Asian and 0.65 for white). Conclusions South Asian patients had higher rates of hypertension compared to the other ethnic groups. South Asian and Chinese patients had a lower risk of death and developing cardiovascular outcomes compared to whites. Women with hypertension have a better prognosis than men regardless of ethnicity. [ABSTRACT FROM AUTHOR]

With advances in the effectiveness of treatment and disease management, the contribution of chronic comorbid diseases (comorbidities) found within the Charlson comorbidity index to mortality is likely to have changed since development of the index in 1984. The authors reevaluated the Charlson index and reassigned weights to each condition by identifying and following patients to observe mortality within 1 year after hospital discharge. They applied the updated index and weights to hospital discharge data from 6 countries and tested for their ability to predict in-hospital mortality. Compared with the original Charlson weights, weights generated from the Calgary, Alberta, Canada, data (2004) were 0 for 5 comorbidities, decreased for 3 comorbidities, increased for 4 comorbidities, and did not change for 5 comorbidities. The C statistics for discriminating in-hospital mortality between the new score generated from the 12 comorbidities and the Charlson score were 0.825 (new) and 0.808 (old), respectively, in Australian data (2008), 0.828 and 0.825 in Canadian data (2008), 0.878 and 0.882 in French data (2004), 0.727 and 0.723 in Japanese data (2008), 0.831 and 0.836 in New Zealand data (2008), and 0.869 and 0.876 in Swiss data (2008). The updated index of 12 comorbidities showed good-to-excellent discrimination in predicting in-hospital mortality in data from 6 countries and may be more appropriate for use with more recent administrative data. [ABSTRACT FROM AUTHOR]

Background. Nurse telephone advice (NTA) lines, a major initiative in primary health care reform, provide symptom triage and health information. Compliance studies utilizing database analysis are frequently limited to a defined population, such as children or Emergency Department (ED) users. [ABSTRACT FROM PUBLISHER]

Part of the strategic response to HIV in Cameroon, West Africa, has been the institutionalisation of voluntary testing and counselling (VCT) for HIV services across the country. The study addresses the general level of awareness and use of VCT centres in Cameroon. The data were extracted from the national, cross-sectional, 2004 Cameroon Demographic and Health Survey (DHS). The survey collected information on respondents' demographic characteristics and awareness and utilisation of VCT services, through a standard behavioural surveillance survey, administered in face-to-face interviews with males aged 15 years or older and females aged 15 to 49 years. Chi-square and logistic regression were employed for data analysis. A total of 5 280 males and 10 656 females responded to the 2004 Cameroon DHS. More of the male than female respondents had a secondary or higher education (51.8% versus 39%), slightly more of the males than females resided in urban areas (57.3% versus 54.8%), and males were more likely than females to have heard of VCT centres (37.8% versus 26.8%) and were also much more likely to have had an HIV test at a VCT centre (5.9% males versus 1.3% females). The findings indicate that awareness and use of centres offering VCT for HIV is very low in Cameroon. Further research in Cameroon is needed to assess individuals' reasons for not using VCT, as well as studies to identify patterns of information flow regarding the dissemination of knowledge about HIV and AIDS and about VCT centres. [ABSTRACT FROM AUTHOR]

Objective. The goal of this study was to assess the validity of the International Classification of Disease, 10th Version (ICD-10) administrative hospital discharge data and to determine whether there were improvements in the validity of coding for clinical conditions compared with ICD-9 Clinical Modification (ICD-9-CM) data. Methods. We reviewed 4,008 randomly selected charts for patients admitted from January 1 to June 30, 2003 at four teaching hospitals in Alberta, Canada to determine the presence or absence of 32 clinical conditions and to assess the agreement between ICD-10 data and chart data. We then recoded the same charts using ICD-9-CM and determined the agreement between the ICD-9-CM data and chart data for recording those same conditions. The accuracy of ICD-10 data relative to chart data was compared with the accuracy of ICD-9-CM data relative to chart data. Results. Sensitivity values ranged from 9.3 to 83.1 percent for ICD-9-CM and from 12.7 to 80.8 percent for ICD-10 data. Positive predictive values ranged from 23.1 to 100 percent for ICD-9-CM and from 32.0 to 100 percent for ICD-10 data. Specificity and negative predictive values were consistently high for both ICD-9-CM and ICD-10 databases. Of the 32 conditions assessed, ICD-10 data had significantly higher sensitivity for one condition and lower sensitivity for seven conditions relative to ICD-9-CM data. The two databases had similar sensitivity values for the remaining 24 conditions. Conclusions. The validity of ICD-9-CM and ICD-10 administrative data in recording clinical conditions was generally similar though validity differed between coding versions for some conditions. The implementation of ICD-10 coding has not significantly improved the quality of administrative data relative to ICD-9-CM. Future assessments like this one are needed because the validity of ICD-10 data may get better as coders gain experience with the new coding system. [ABSTRACT FROM AUTHOR]

There is debate about whether therapies that reduce mortality in acute myocardial infarction (AMI) will increase the risk for heart failure. In this study, an inception cohort of patients hospitalized with AMIs from April 1, 1994, to March 31, 1999 (without previous diagnoses of heart failure or myocardial infarction), were followed for a mean of 32 months to explore whether invasive coronary revascularization during the index AMI hospitalization was associated with a trade-off between reduced mortality in the short term and increased heart failure in the intermediate term. Of 13,472 patients (mean age 65 ± 13 years, 70% men), 3,278 (24%) underwent invasive coronary revascularization during their index AMI hospitalizations. Patients who underwent invasive revascularization during their index AMI hospitalizations were less likely to die (171 of 3,278 [5%] vs 1,688 of 10,194 [17%], p <0.0001) and were less likely to develop heart failure, either during the AMI hospitalization (571 of 3,278 [17%] vs 2,422 of 10,194 [24%], p <0.0001) or after discharge (144 of 3,278 [4%] vs 754 of 10,194 [7%], p <0.0001). These associations persisted after covariate adjustment (for heart failure, hazard ratio 0.68, 95% confidence interval 0.56 to 0.81; for death or heart failure, hazard ratio 0.60, 95% confidence interval 0.51 to 0.70). In conclusion, invasive coronary revascularization during AMI hospitalization is associated with lower rates of death and subsequent heart failure; there is no trade-off of 1 outcome for the other. [Copyright &y& Elsevier]

Epilepsy imposes a significant burden on society. The objective of this study was to estimate health resource utilization (HRU) over a 1-year period in epilepsy patients, using administrative databases. Three administrative databases (inpatient, emergency, and physician claims) were used to identify epilepsy cases. HRU variables included general physician (GP) and emergency (ER) visits, physician billings, hospitalizations, and length of stay (LOS). Logistic regression was used to determine the association between demographic variables and HRU variations. Among the 1,431 patients with a mean age of 37.5 ± 17.3 years, 56 (4%) were aboriginal. Ninety-six percent of patients saw a GP or a specialist (outpatient visit), 12% were hospitalized, and 8% visited the ER. Younger patients were more likely to see a neurologist (OR = 1.7, 95% CI 1.3–2.3), visit the ER (OR = 4.9, 95% CI 3.2–7.4), or be hospitalized (OR = 2.9, 95% CI 2.0–4.3). Females were less likely to see a GP but more likely to see a neurologist. Aboriginals were more likely than nonaboriginals to visit the ER (OR = 2.3, 95% CI 1.1–5.0) or be hospitalized (OR = 2.8, 95% CI 1.5–5.1) but less likely to see a neurologist (OR = 0.3, 95% CI 0.2–0.6). Welfare status and residence location (urban vs. rural) were not associated with HRU level. We demonstrated the feasibility of using administrative databases to assess HRU in epilepsy. We also uncovered disparities in HRU by age, gender, and by aboriginal status, suggesting possible internal or external barriers to specialized care in some groups. [ABSTRACT FROM AUTHOR]

Context • Although epidemiological studies have reported protective effects of religion and spirituality on mental health, it is unknown whether spirituality can be used as an intervention to improve psychological well-being. Objective • To evaluate the efficacy of a home study-based spirituality program on mood disturbance in emotionally distressed patients. Design, Setting, and Participants • A non-blinded, randomized, wait list-controlled trial of 165 individuals with mood disturbance [score of >40 on the Profile of Mood States (POMS)] were recruited from primary care clinics in a Canadian city between August 2000 and March 2001. Interventions • Participants were randomized to a spirituality group (an 8-week audiotaped spirituality home-study program), a mindfulness meditation-based stress reduction group (attendance at facilitated classes for 8 weeks), or a wait-list control group (no intervention for 12 weeks). Main Outcome Measures • Primary outcomes were mood disturbance, measured using POMS, and quality of life, measured using the 5F-36, a short-form health survey with 36 questions. The POMS and the SF-36 were completed at baseline, at 8 weeks, and at 12 weeks. Results • At the end of the 8-week intervention period, the mean POMS score improvement was -43.1 (-45.7%) for the spirituality group, -22.6 (-26.3%) for the meditation group, and -10.3 (11.3%) for the control group (P<.001 for spirituality vs control group; P=.034 for spirituality vs meditation group). Mean improvement in the SF-36 mental component summary score was 14.4 (48.6%) for the spirituality group, 7.1 (22.3%) for the meditation group, and 4.7 (16.1%) for the control group (P<.001 for spirituality vs control group; P=.029 for spirituality vs meditation group). At 12 weeks, POMS and SF-36 scores remained significantly different from baseline for the spirituality group. [ABSTRACT FROM AUTHOR]

Purpose: To assess the effects of hospital care by a specialist or nonspecialist physician, and by volume of treated patients, on mortality among hospitalized patients with newly diagnosed heart failure. Methods: Data describing heart failure patients in Alberta, Canada, from April 1, 1994, to March 31, 2000, were extracted from hospital abstracts and analyzed using hierarchical regression, with adjustment for patient demographic characteristics, comorbid conditions, physician volume, physician specialty, and hospital volume. Results: There were 16,162 hospital discharges for heart failure. Nonspecialist physicians were predominantly in the two lowest-volume quartiles (93%) and specialists were predominantly in the two highest-volume quartiles (68%). Considering the effects of volume alone and after adjustment for comorbidity, for each 10 additional hospital patients treated by a physician, the odds ratio for in-hospital mortality was 0.97 (95% confidence interval [CI]: 0.95 to 0.98), and the odds ratio for 1-year mortality was 0.99 (95% CI: 0.98 to 0.999). In analyses that considered both volume and specialty, the odds of in-hospital mortality decreased by 4% for each 10 additional in-hospital patients treated by a physician (odds ratio [OR] = 0.96; 95% CI: 0.95 to 0.98). In these same analyses, the odds ratio for in-hospital mortality was 1.32 (95% CI: 1.13 to1.53) for general practitioners with specialist consultation and 1.32 (95% CI: 1.08 to 1.61) for specialists compared with general practitioners without specialist consultations. At 1 year, mortality was not associated significantly with the volume of in-hospital patients treated, or with the specialty of the treating physician. Conclusion: Treatment by high-volume physicians during hospitalization for newly diagnosed heart failure was associated with a decrease in mortality, but these benefits did not persist at 1 year. The increased mortality noted in patients treated by specialists may be due to residual confounding or unmeasured comorbidity. [Copyright &y& Elsevier]

Objective: Canadian administrative hospital discharge data contain a diagnosis-type indicator for each coded diagnosis that allows researchers to distinguish complications from pre-existing diagnoses. Given that the validity of diagnosis-type indicators is unknown, we conducted a detailed chart review to evaluate the accuracy of diagnosis-type indicators for flagging complications.Study design and setting: We obtained administrative hospital discharge data for 1,200 randomly selected adult inpatient separations in Calgary, Alberta, occurring between April 1, 1996 and March 31, 1997. Each discharge record contains up to 16 diagnoses and 16 corresponding diagnosis-type indicators (value of “2” = complication). The corresponding medical charts were reviewed for evidence of diagnoses and complications. A complication was defined as a new diagnosis arising after the start of hospitalization. We determined the extent to which the diagnosis-type indicator in the administrative data agreed with the chart reviewer''s assessment (criterion standard) of whether a diagnosis was a complication or not.Results: The agreement for complications between the two databases varied greatly across 12 conditions studied (kappa range: 0–0.72) and was often low (kappa <0.20 for six conditions). Sensitivity ranged from 0 to 57.1% (higher than 50% for only two conditions), indicating a tendency for complications to often be miscoded as baseline comorbidities. In contrast, specificity was generally high (range: 99.0–100%), suggesting that pre-existing conditions were usually appropriately coded as such in the administrative data.Conclusion: The validity of diagnosis-type indicators in Canadian administrative discharge data appears to be poor for some types of complications. This is likely to be of greatest concern in studies that rely solely on diagnosis-type indicators to define complications as outcomes. [Copyright &y& Elsevier]

Home care services are provided to about 10% of those admitted to hospital for acute myocardial infarction and about 20% of those discharged from hospital. The use of home care in patients with an acute myocardial infarction is growing in Alberta over the brief time span of this four year study. Those that received home care prior to a hospitalization for acute myocardial infarction were “old and frail” with a high mortality rate during and after hospitalization. The provision of home care after hospitalization selected those patients that stay in hospital longer and required more hospital care. Background: The use of home care before and after hospitalization for acute myocardial infarction is described. Methods: Hospital discharge abstracts were used to identify patients hospitalized in Alberta, Canada for acute myocardial infarction which were then linked to home care administrative data. Results: There were 12,648 patients with acute myocardial infarction from April 1, 1995 until March 31, 1999. Home care within 60 days prior to hospitalization was provided for 8.7% of patients with acute myocardial infarctions (n = 1097) which significantly (p = 0.023) increased from 7.6% in the fiscal year 1995/6 to 9.5% in the fiscal year 1998/9. Home care within 60 days after hospitalization was provided to 16.4% of patients with acute myocardial infarctions (n = 2076) which significantly (p < 0.000) increased from 14.1% in the fiscal year 1995/6 to 18.1% in fiscal year 1998/9. Recipients of home care were significantly older, had more comorbidities, and greater severity of illness, but were less likely to undergo coronary artery revascularization during hospitalization. After multivariate adjustment, length of hospital stay, 60 day re-admissions, and mortality were higher in those receiving home care post hospitalization. Nearly half of those receiving home care prior to hospitalization died within one year. 80% of those receiving home care prior to admission also received home care services after hospitalization. Conclusion: Those patients who received home care prior to a hospitalization for acute myocardial infarction were “old and frail” with a high mortality rate during and after hospitalization. The provision of home care after hospitalization selected those patients that stay in hospital longer and required more hospital care. [ABSTRACT FROM PUBLISHER]

Background: To update appropriateness ratings for carotid endarterectomy using the best clinical evidence and to develop a tool to audit the procedure's use. Methods: A nine-member expert panel drawn from all the Canadian Specialist societies that are involved in the care of patients with carotid artery disease, used the RAND Appropriateness Methodology to rate scenarios where carotid endarterectomy may be performed. A 9-point rating scale was used that permits the categorization of the use of carotid endarterectomy as appropriate, uncertain, or inappropriate. A descriptive analysis was undertaken of the final results of the panel meeting. A database and code were then developed to rate all carotid endarterectomies performed in a Western Canadian Health region from 1997 to 2001. Results: All scenarios for severe symptomatic stenosis (70-99%) were determined to be appropriate. The ratings for moderate symptomatic stenosis (50-69%) ranged from appropriate to inappropriate. It was never considered appropriate to perform endarterectomy for mild stenosis (0-49%) or for chronic occlusions. Endarterectomy for asymptomatic carotid disease was thought to be of uncertain benefit at best. The majority of indications for the combination of endarterectomy either prior to, or at time of coronary artery bypass grafting were inappropriate. The audit tool classified 98.0% of all cases. Conclusions: These expert panel ratings, based on the best evidence currently available, provide a comprehensive and updated guide to appropriate use of carotid endarterectomy. The resulting audit tool can be downloaded by readers from the Internet and immediately used for hospital audits of carotid endarterectomy appropriateness. [ABSTRACT FROM AUTHOR]

Background: Only a few small studies have explored the association between various physical illnesses and suicide in the elderly and they have produced inconsistent results. Thus, we undertook this larger study to more definitively assess the association between elderly suicide and physical illness.Methods: This case-control study compared the proportion with physical illnesses among 822 cases who committed suicide with that among 944 controls who died due to motor vehicle accident at age 55 years or over in Alberta, Canada.Results: Compared to the motor vehicle accident deaths, the elderly who committed suicide were more likely to have cancer, ischemic heart disease, chronic pulmonary disease, peptic ulcer, prostatic disorder, depression and other psychiatric illnesses. There was no significant difference in the proportion of cerebrovascular disease and diabetes mellitus between the case and control groups before adjustment of demographic and clinical characteristics. After adjustment of these variables, the elderly with any of the following illnesses were more likely to die by suicide than those without the illness: cancer (adjusted odds ratio [95% confidence interval]: 1.73 [1.16-2.58]), prostatic disorder (excluding prostatic cancer, 1.70 [1.16-2.49]), chronic pulmonary disease among the married (1.86 [1.22-2.83]), depression (6.70 [4.72-9.50]) or other psychiatric illness (2.16 [1.68-2.76]). There was no evidence that ischemic heart disease, cerebrovascular disease, peptic ulcer and diabetes mellitus might be associated with suicide in the elderly.Conclusions: Cancer, prostatic disorder, chronic pulmonary disease among the married and psychiatric illness appear to be associated with suicide among the elderly. [ABSTRACT FROM AUTHOR]

Presents a study to compare the mean of covariates method to the less widely used corrected group prognosis method in an analysis evaluating survival in patients with and without diabetes. Context; Objective; Design, setting, and patients; Main outcome measures; Results; Conclusions.

OBJECTIVES: To determine the frequency with which commonly coded clinical variables are complications, as opposed to baseline comorbidities, and to compare the results of 2 risk-adjusted outcome analyses for coronary artery bypass graft surgery for which we either (a) ignored, or (b) used the available “diagnosis-type indicator.” DESIGN: Analysis of existing administrative data. SETTING: Twenty-three Canadian hospitals. PATIENTS: A total of 50,357 coronary artery bypass graft surgery cases. MEASUREMENTS AND MAIN RESULTS: Among 21 clinical variables whose definitions involve the diagnosis-type indicator, 14 were predominantly (≥97%) baseline risk factors when present. Seven variables were often complication diagnoses: renal disease (when present, 13% coded as complications), recent myocardial infarction (15%), peptic ulcer disease (15%), congestive heart failure (17%), cerebrovascular disease (26%), hemiplegia (34%), and severe liver disease (35%). The results of risk adjustment analyses predicting in-hospital mortality differed when the diagnosis-type indicator was either used or ignored, and as a result, adjusted hospital mortality rates and rankings changed, often dramatically, with rankings increasing for 10 hospitals, decreasing for 9 hospitals, and remaining the same for only 4 hospitals. CONCLUSIONS: The results of analyses performed using the diagnosis-type indicator in Canadian administrative data differ considerably from analyses that ignore the indicator. The widespread introduction of such an indicator should be considered in other countries, because risk-adjustment analyses performed without a diagnosis-type indicator may yield misleading results. [ABSTRACT FROM AUTHOR]

Purpose: Diabetes is a recognized risk factor for the development of cardiac disease, but its importance as a prognostic factor among patients with known cardiovascular disease is less clear. We evaluated survival in patients with and without diabetes who underwent cardiac catheterization for presumed coronary artery disease.Subjects and Methods: We analyzed data from a prospective cohort study that captures detailed clinical information and longitudinal outcomes for all patients who undergo cardiac catheterization in Alberta, Canada. We studied 11,468 patients, 1959 (17%) of whom had diabetes. Logistic regression was used to model predictors of 1-year mortality, and proportional hazards analysis was used to model predictors of survival up to 3 years after cardiac catheterization.Results: One-year mortality was 7.6% for patients with diabetes versus 4.1% for those without diabetes (odds ratio = 1.9, 95% confidence interval [CI]: 1.6 to 2.3). After adjusting for other characteristics of the patients, including comorbid conditions, previous cardiac history, coronary anatomy, and renal function, the odds ratio for 1-year mortality was 1.1 (95% CI: 0.8 to 1.3). Similarly, the adjusted hazard ratio for longer term mortality was 1. 2 (95% CI: 1.0 to 1.4, mean follow-up of 702 days).Conclusions: These results suggest that there is little or no independent association between diabetes and mortality for up to 3 years after cardiac catheterization. Estimates of short- to intermediate-term prognosis for diabetic patients with coronary artery disease should be based on the presence of other prognostic factors associated with diabetes. [ABSTRACT FROM AUTHOR]

Objective: To determine differences by gender among elderly persons who commit suicide on demographic characteristics, place of suicide, suicide method, previous suicide behaviour, and precipitant stressor.Method: This study included completed suicides of individuals aged 55 years and over during 1984-1995 in Alberta (n = 920). Information was abstracted from suicide records of medical examiners.Results: Relative to elderly female suicides, elderly males who commit suicide characteristically use guns to commit suicide (43.8%), are single (12.5%), live in rural areas (46.7%), and have a lower frequency of previous suicide attempts (16.5%). Physical illness and financial difficulty as precipitant stressors of suicide are significantly more frequent among males (40.3% and 8.7% respectively) than females (29.9% and 1.8% respectively). Mental illness as a precipitant stressor is more common among females, 35.8% for women and 15.3% for men.Conclusions: Lethal methods of suicide and physical illness and financial difficulty as precipitant stressors of suicide are more common among elderly males than females who commit suicide. [ABSTRACT FROM AUTHOR]

Presents a study that examined observed and risk-adjusted death rates for 23 Canadian hospitals performing coronary artery bypass grafting (CABG). Methods; Results; Interpretation.

Examines Canadian trends in rates of in-hospital death after coronary artery bypass grafting (CABG) and compares provicial risk-adjusted death rates. Methods; Results; Interpretation and conclusions.

Objective: We aimed to identify existing hypertension risk prediction models developed using traditional regression-based or machine learning approaches and compare their predictive performance. Methods: We systematically searched MEDLINE, EMBASE, Web of Science, Scopus, and the grey literature for studies predicting the risk of hypertension among the general adult population. Summary statistics from the individual studies were the C-statistic, and a random-effects meta-analysis was used to obtain pooled estimates. The predictive performance of pooled estimates was compared between traditional regression-based models and machine learning-based models. The potential sources of heterogeneity were assessed using meta-regression, and study quality was assessed using the PROBAST (Prediction model Risk Of Bias ASsessment Tool) checklist. Results: Of 14,778 articles, 52 articles were selected for systematic review and 32 for meta-analysis. The overall pooled C-statistics was 0.75 [0.73–0.77] for the traditional regression-based models and 0.76 [0.72–0.79] for the machine learning-based models. High heterogeneity in C-statistic was observed. The age (p = 0.011), and sex (p = 0.044) of the participants and the number of risk factors considered in the model (p = 0.001) were identified as a source of heterogeneity in traditional regression-based models. Conclusion: We attempted to provide a comprehensive evaluation of hypertension risk prediction models. Many models with acceptable-to-good predictive performance were identified. Only a few models were externally validated, and the risk of bias and applicability was a concern in many studies. Overall discrimination was similar between models derived from traditional regression analysis and machine learning methods. More external validation and impact studies to implement the hypertension risk prediction model in clinical practice are required. [ABSTRACT FROM AUTHOR]

Objective: Effective management of hypertension requires not only medical intervention but also significant patient self-management. The challenge, however, lies in the diversity of patients' personal barriers to managing their condition. The objective of this research is to identify and categorize personalized barriers to hypertension self-management using the TASKS framework (Task, Affect, Skills, Knowledge, Stress). This study aims to enhance patient-centered strategies by aligning support with each patient's specific needs, recognizing the diversity in their unique circumstances, beliefs, emotional states, knowledge levels, and access to resources. This research is based on observations from a single study focused on eight patients, which may have been a part of a larger project. Results: The analysis of transcripts from eight patients and the Global Hypertension Practice Guidelines revealed 69 personalized barriers. These barriers were distributed as follows: emotional barriers (49%), knowledge barriers (24%), logical barriers (17%), and resource barriers (10%). The findings highlight the significant impact of emotional and knowledge-related challenges on hypertension self-management, including difficulties in home blood pressure monitoring and the use of monitoring tools. This study emphasizes the need for tailored interventions to address these prevalent barriers and improve hypertension management outcomes. [ABSTRACT FROM AUTHOR]

Background: This study, part of a multi-study program, aimed to identify a core set of cost-based quality and performance indicators using a modified Delphi research approach. Conceptually, this core set of cost-based indicators is intended for use within a broader health system performance framework for evaluating home care programming in Canada. Methods: This study used findings from a recently published scoping review identifying 34 cost-focused home care program PQIs. A purposive and snowball technique was employed to recruit a national panel of system-level operational and content experts in home care. We collected data through progressive surveys and engagement sessions. In the first round of surveying, the panel scored each indicator on Importance, Actionable, and Interpretable criteria. The panel set the second round of ranking the remaining indicators' consensus criteria. The panel ranked by importance their top five indicators from operational and system perspectives. Indicators selected by over 50% of the panel were accepted as consensus. Results: We identified 13 panellists. 12 completed the first round which identified that 30 met the predetermined inclusion criteria. Eight completed the ranking exercise, with one of the eight completing one of two components. The second round resulted in three PQIs meeting the consensus criteria: one operational and two systems-policy-focused. The PQIs: "Average cost per day per home care client," "Home care service cost (mean) per home care client 1y, 3y and 7y per health authority and provincially and nationally", and "Home care funding as a percent of overall health care expenditures." Conclusions: The findings from this study offer a crucial foundation for assessing operational and health system outcomes. Notably, this research pioneers identifying key cost-based PQIs through a national expert panel and modified Delphi methodology. This study contributes to the literature on PQIs for home care and provides a basis for future research and practice. These selected PQIs should be applied to future research to test their applicability and validity within home care programming and outcomes. Researchers should apply these selected PQIs in future studies to evaluate their applicability and validity within home care programming and outcomes. Highlights: This study aimed to identify a set of financial performance and quality indicators (PQIs) for evaluating home care in Canada. The researchers used a modified multi-phased Delphi research approach with endorsed consensus on three PQIs from the 34 reviewed. One PQI is operational, while the other two are systems-policy-focused. This study was motivated by the need to measure and improve the financial sustainability and efficiency of home care services in Canada. It contributes to the literature on PQIs for home care and provides a basis for future research and practice. This research is novel as it is the first to identify key cost-based PQIs through a national expert panel and modified Delphi methodology for use within a broader health system measurement framework, such as the Institute for Healthcare Improvement Quadruple Aim framework. The indicators identified in this study may provide an essential foundation for measuring operational and health system outcomes and require further engagement at local and regional levels, further development, and conceptual application within established health system performance frameworks. Evaluating the potential adoption and implementation of evidence-based PQIs is essential to measuring and improving home care system programming, including indicators reflective of the acceptability and potential usefulness of measures by population groups as an important future step. [ABSTRACT FROM AUTHOR]

Implementation is ubiquitous. The identification of barriers to implementation is critical for achieving implementation success. This paper introduces and discusses a deductive theory-based framework, TASKS, to guide the identification of implementation barriers. The TASKS framework deals with the relationships between a Task and the task implementer's Affect, Skills, and Knowledge, based on the inversed U-shaped mental Stress-mental effort relation. The TASKS framework classifies implementation barriers into four categories: 1) emotion barriers, 2) logic barriers, 3) knowledge barriers, and 4) resources barriers. The TASKS framework detects barriers to implementation following three steps, 1) identifying the ideal TASKS components, 2) modelling the implementer's mental capability, and 3) detecting barriers to implementation. The TASKS framework can be applied to a wide range of disciplines for effective and efficient task implementation. [ABSTRACT FROM AUTHOR]

Background: The International Classification of Diseases (ICD) is widely used by clinical coders worldwide for clinical coding morbidity data into administrative health databases. Accordingly, hospital data quality largely depends on the coders' skills acquired during ICD training, which varies greatly across countries. Objective: To characterise the current landscape of international ICD clinical coding training. Method: An online questionnaire was created to survey the 194 World Health Organization (WHO) member countries. Questions focused on the training provided to clinical coding professionals. The survey was distributed to potential participants who met specific criteria, and to organisations specialised in the topic, such as WHO Collaborating Centres, to be forwarded to their representatives. Responses were analysed using descriptive statistics. Results: Data from 47 respondents from 26 countries revealed disparities in all inquired topics. However, most participants reported clinical coders as the primary person assigning ICD codes. Although training was available in all countries, some did not mandate training qualifications, and those that did differed in type and duration of training, with college or university degree being most common. Clinical coding certificates most frequently entailed passing a certification exam. Most countries offered continuing training opportunities, and provided a range of support resources for clinical coders. Conclusion: Variability in clinical coder training could affect data collection worldwide, thus potentially hindering international comparability of health data. Implications: These findings could encourage countries to improve their resources and training programs available for clinical coders and will ultimately be valuable to the WHO for the standardisation of ICD training. [ABSTRACT FROM AUTHOR]

The article discusses the routine collection of data for healthcare management which rises concerns on the inconsistencies of reported results. The author argues that studies that employ routinely collected health data must be reported based on the Reporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statement and checklist.

Background: Physician chart documentation can facilitate patient care decisions, reduce treatment errors, and inform health system planning and resource allocation activities. Although accurate and complete patient chart data supports quality and continuity of patient care, physician documentation often varies in terms of timeliness, legibility, clarity and completeness. While many educational and other approaches have been implemented in hospital settings, the extent to which these interventions can improve the quality of documentation in emergency departments (EDs) is unknown.Methods: We conducted a systematic review to assess the effectiveness of approaches to improve ED physician documentation. Peer reviewed electronic databases, grey literature sources, and reference lists of included studies were searched to March 2015. Studies were included if they reported on outcomes associated with interventions designed to enhance the quality of physician documentation.Results: Nineteen studies were identified that report on the effectiveness of interventions to improve physician documentation in EDs. Interventions included audit/feedback, dictation, education, facilitation, reminders, templates, and multi-interventions. While ten studies found that audit/feedback, dictation, pharmacist facilitation, reminders, templates, and multi-pronged approaches did improve the quality of physician documentation across multiple outcome measures, the remaining nine studies reported mixed results.Conclusions: Promising approaches to improving physician documentation in emergency department settings include audit/feedback, reminders, templates, and multi-pronged education interventions. Future research should focus on exploring the impact of implementing these interventions in EDs with and without emergency medical record systems (EMRs), and investigating the potential of emerging technologies, including EMR-based machine-learning, to promote improvements in the quality of ED documentation. [ABSTRACT FROM AUTHOR]

Background: Hypertension is a common chronic condition affecting nearly a quarter of Canadians. Hypertension surveillance in Canada typically relies on administrative data and/or national surveys. Routinely-captured data from primary care electronic medical records (EMRs) are a complementary source for chronic disease surveillance, with longitudinal patient-level details such as sociodemographics, blood pressure, weight, prescribed medications, and behavioural risk factors. As EMR data are generated from patient care and administrative tasks, assessing data quality is essential before using for secondary purposes. This study evaluated the quality of primary care EMR data from one province in Canada within the context of hypertension surveillance.Methods: We conducted a cross-sectional, descriptive study using primary care EMR data collected by two practice-based research networks in Alberta, Canada. There were 48,377 adults identified with hypertension from 53 clinics as of June 2018. Summary statistics were used to examine the quality of data elements considered relevant for hypertension surveillance.Results: Patient year of birth and sex were complete, but other sociodemographic information (ethnicity, occupation, education) was largely incomplete and highly variable. Height, weight, body mass index and blood pressure were complete for most patients (over 90%), but a small proportion of outlying values indicate data inaccuracies were present. Most patients had a relevant laboratory test present (e.g. blood glucose/glycated hemoglobin, lipid profile), though a very small proportion of values were outside a biologically plausible range. Details of prescribed antihypertensive medication, such as start date, strength, dose, frequency, were mostly complete. Nearly 80% of patients had a smoking status recorded, though only 66% had useful information (i.e. categorized as current, past, or never), and less than half had their alcohol use described; information related to amount, frequency or duration was not available.Conclusions: Blood pressure and prescribed medications in primary care EMR data demonstrated good completeness and plausibility, and contribute valuable information for hypertension epidemiology and surveillance. The use of other clinical, laboratory, and sociodemographic variables should be used carefully due to variable completeness and suspected data errors. Additional strategies to improve these data at the point of entry and after data extraction (e.g. statistical methods) are required. [ABSTRACT FROM AUTHOR]

Background: Primary care electronic medical record (EMR) data are emerging as a useful source for secondary uses, such as disease surveillance, health outcomes research, and practice improvement. These data capture clinical details about patients' health status, as well as behavioural risk factors, such as smoking. While the importance of documenting smoking status in a healthcare setting is recognized, the quality of smoking data captured in EMRs is variable. This study was designed to test methods aimed at improving the quality of patient smoking information in a primary care EMR database.Methods: EMR data from community primary care settings extracted by two regional practice-based research networks in Alberta, Canada were used. Patients with at least one encounter in the previous 2 years (2016-2018) and having hypertension according to a validated definition were included (n = 48,377). Multiple imputation was tested under two different assumptions for missing data (smoking status is missing at random and missing not-at-random). A third method tested a novel pattern matching algorithm developed to augment smoking information in the primary care EMR database. External validity was examined by comparing the proportions of smoking categories generated in each method with a general population survey.Results: Among those with hypertension, 40.8% (n = 19,743) had either no smoking information recorded or it was not interpretable and considered missing. Those with missing smoking data differed statistically by demographics, clinical features, and type of EMR system used in the clinic. Both multiple imputation methods produced fully complete smoking status information, with the proportion of current smokers estimated at 25.3% (data missing at random) and 12.5% (data missing not-at-random). The pattern-matching algorithm classified 18.2% of patients as current smokers, similar to the population-based survey (18.9%), but still resulted in missing smoking information for 23.6% of patients. The algorithm was estimated to be 93.8% accurate overall, but varied by smoking status category.Conclusion: Multiple imputation and algorithmic pattern-matching can be used to improve EMR data post-extraction but the recommended method depends on the purpose of secondary use (e.g. practice improvement or epidemiological analyses). [ABSTRACT FROM AUTHOR]

Background: Non-alcoholic fatty liver disease (NAFLD) describes a spectrum of chronic fattening of liver that can lead to fibrosis and cirrhosis. Diabetes has been identified as a major comorbidity that contributes to NAFLD progression. Health systems around the world make use of administrative data to conduct population-based prevalence studies. To that end, we sought to assess the accuracy of diabetes International Classification of Diseases (ICD) coding in administrative databases among a cohort of confirmed NAFLD patients in Calgary, Alberta, Canada. Methods: The Calgary NAFLD Pathway Database was linked to the following databases: Physician Claims, Discharge Abstract Database, National Ambulatory Care Reporting System, Pharmaceutical Information Network database, Laboratory, and Electronic Medical Records. Hemoglobin A1c and diabetes medication details were used to classify diabetes groups into absent, prediabetes, meeting glycemic targets, and not meeting glycemic targets. The performance of ICD codes among these groups was compared to this standard. Within each group, the total numbers of true positives, false positives, false negatives, and true negatives were calculated. Descriptive statistics and bivariate analysis were conducted on identified covariates, including demographics and types of interacted physicians. Results: A total of 12,012 NAFLD patients were registered through the Calgary NAFLD Pathway Database and 100% were successfully linked to the administrative databases. Overall, diabetes coding showed a sensitivity of 0.81 and a positive predictive value of 0.87. False negative rates in the absent and not meeting glycemic control groups were 4.5% and 6.4%, respectively, whereas the meeting glycemic control group had a 42.2% coding error. Visits to primary and outpatient services were associated with most encounters. Conclusion: Diabetes ICD coding in administrative databases can accurately detect true diabetic cases. However, patients with diabetes who meets glycemic control targets are less likely to be coded in administrative databases. A detailed understanding of the clinical context will require additional data linkage from primary care settings. [ABSTRACT FROM AUTHOR]

Background: Though pharmacy claims data are commonly used to study medication adherence, there remains no standard operational definition for adherence especially for patients on multiple medications. Even when studies use the same terminology, the actual methods of calculating adherence can differ drastically. It is unclear whether the use of different definitions results in different conclusions regarding adherence and associated outcomes. The objective of our study was to compare adherence rates and associations with mortality using different operational definitions of adherence, and using various methods of handling concurrent medication use.Methods: We conducted a cohort study of patients aged ≥65 years from Manitoba, Canada, with incident hypertension diagnosed in 2004 and followed to 2009. We calculated adherence rates to anti-hypertensive medications using different operational definitions of medication adherence (including interval and prescription based medication possession ratios [MPR] and proportion of days covered [PDC]). For those on concurrent medications, we calculated adherence rates using the different methods of handling concurrent medication use, for each definition. We used logistic regression to determine the association between adherence and mortality for each operational definition.Results: Among 2199 patients, 24.1% to 90.5% and 71.2% to 92.7% were considered adherent when using fixed interval and prescription-based interval medication possession ratios [MPRi and MPRp] respectively, depending on how concurrent medications were handled. Adherence was inversely associated with death, with the strongest association for MPRp measures. This association was significant only when considering adherence to any anti-hypertensive [aOR 0.70, 95% CI 0.51, 0.97], or when the mean of the class-specific MPRp's [adjusted OR 0.71, 95% CI 0.53, 0.95] was used. No significant association existed when the highest or lowest class-specific MPRp was used as the adherence estimate.Conclusion: The range of adherence estimates varies widely depending on the operational definition used. Given less variation in adherence rates and their stronger association against mortality, we recommend using prescription-based MPR's to define medication adherence. [ABSTRACT FROM AUTHOR]

Abstract Background Clinical practice guidelines (CPGs) have the potential to improve quality of care. However, implementation of CPGs into the clinical care of people with epilepsy is less than optimal. This study aimed to examine barriers and facilitators to the use of CPGs for the care of people with epilepsy. Methods A cross-sectional survey of Canadian neurologists was conducted to evaluate CPG use, barriers and facilitators of CPG use, and factors associated with CPG use among neurologists. The barriers and facilitators of CPG use among neurologists that manage people with epilepsy were compared with those who do not. Results Of 311 responders (response rate = 38.7%), 78.7% indicated that they manage people with epilepsy. Neurologists that manage people with epilepsy did not differ from those who do not with regard to demographic characteristics nor in the proportion that report using CPGs in their clinical practice. The barriers and facilitators of CPG use were largely similar between neurologist that do and do not manage people with epilepsy; except applicability of CPGs tended to be less commonly endorsed as a barrier to CPG use by those who manage people with epilepsy compared with those who do not. Conclusions This study suggests that knowledge, applicability, motivation, resources, and targeting of CPGs to appropriate audience are barriers and facilitators of CPG use among neurologists who manage people with epilepsy. The similarity between barriers and facilitators of CPG use among neurologists who manage people with epilepsy compared with those who do not provides support for the use of a knowledge translation (KT) strategy tailored to these barriers and facilitators of CPG use, and targeted towards neurologists. Implementation of epilepsy CPGs has the potential to improve the quality of care for people with epilepsy. [ABSTRACT FROM AUTHOR]

Background: Population based surveillance of surgical site infections (SSIs) requires precise case-finding strategies. We sought to develop and validate machine learning models to automate the process of complex (deep incisional/organ space) SSIs case detection. Methods: This retrospective cohort study included adult patients (age ≥ 18 years) admitted to Calgary, Canada acute care hospitals who underwent primary total elective hip (THA) or knee (TKA) arthroplasty between Jan 1st, 2013 and Aug 31st, 2020. True SSI conditions were judged by the Alberta Health Services Infection Prevention and Control (IPC) program staff. Using the IPC cases as labels, we developed and validated nine XGBoost models to identify deep incisional SSIs, organ space SSIs and complex SSIs using administrative data, electronic medical records (EMR) free text data, and both. The performance of machine learning models was assessed by sensitivity, specificity, positive predictive value, negative predictive value, F1 score, the area under the receiver operating characteristic curve (ROC AUC) and the area under the precision–recall curve (PR AUC). In addition, a bootstrap 95% confidence interval (95% CI) was calculated. Results: There were 22,059 unique patients with 27,360 hospital admissions resulting in 88,351 days of hospital stay. This included 16,561 (60.5%) TKA and 10,799 (39.5%) THA procedures. There were 235 ascertained SSIs. Of them, 77 (32.8%) were superficial incisional SSIs, 57 (24.3%) were deep incisional SSIs, and 101 (42.9%) were organ space SSIs. The incidence rates were 0.37 for superficial incisional SSIs, 0.21 for deep incisional SSIs, 0.37 for organ space and 0.58 for complex SSIs per 100 surgical procedures, respectively. The optimal XGBoost models using administrative data and text data combined achieved a ROC AUC of 0.906 (95% CI 0.835–0.978), PR AUC of 0.637 (95% CI 0.528–0.746), and F1 score of 0.79 (0.67–0.90). Conclusions: Our findings suggest machine learning models derived from administrative data and EMR text data achieved high performance and can be used to automate the detection of complex SSIs. Highlights: The incidence rates of surgical site infections following total hip and knee arthroplasty were 0.5 and 0.52 per 100 surgical procedures. The incidence of SSIs varied significantly between care facilities (ranging from 0.53 to 1.71 per 100 procedures). The optimal machine learning model achieved a ROC AUC of 0.906 (95% CI 0.835–0.978), PR AUC of 0.637 (95% CI 0.528–0.746), and F1 score of 0.79 (0.67–0.90). [ABSTRACT FROM AUTHOR]

Background: Survey research in healthcare is an important tool to collect information about healthcare delivery, service use and overall issues relating to quality of care. Unfortunately, physicians are often a group with low survey response rates and little research has looked at response rates among physician specialists. For these reasons, the purpose of this project was to explore survey response rates among physician specialists in a large metropolitan Canadian city.Methods: As part of a larger project to look at physician payment plans, an online survey about medical billing practices was distributed to 904 physicians from various medical specialties. The primary method for physicians to complete the survey was via the Internet using a well-known and established survey company (www.surveymonkey.com). Multiple methods were used to encourage survey response such as individual personalized email invitations, multiple reminders, and a draw for three gift certificate prizes were used to increase response rate. Descriptive statistics were used to assess response rates and reasons for non-response.Results: Overall survey response rate was 35.0%. Response rates varied by specialty: Neurology/neurosurgery (46.6%); internal medicine (42.9%); general surgery (29.6%); pediatrics (29.2%); and psychiatry (27.1%). Non-respondents listed lack of time/survey burden as the main reason for not responding to our survey.Conclusions: Our survey results provide a look into the challenges of collecting healthcare research where response rates to surveys are often low. The findings presented here should help researchers in planning future survey based studies. Findings from this study and others suggest smaller monetary incentives for each individual may be a more appropriate way to increase response rates. [ABSTRACT FROM AUTHOR]

Background: Stroke has emerged as a significant and escalating health problem for Asian populations. We compared risk factors, quality of care and risk of death or recurrent stroke in South Asian, East Asian and White patients with acute ischemic and hemorrhagic stroke.Methods: Retrospective analysis was performed on consecutive patients with ischemic stroke or intracerebral hemorrhage admitted to 12 stroke centers in Ontario, Canada (July 2003-March 2008) and included in the Registry of the Canadian Stroke Network database. The database was linked to population-based administrative databases to determine one-year risk of death or recurrent stroke.Results: The study included 253 South Asian, 513 East Asian and 8231 White patients. East Asian patients were more likely to present with intracerebral hemorrhage (30%) compared to South Asian (17%) or White patients (15%) (p<0.001). Time from stroke to hospital arrival was similarly poor with delays >2 hours for more than two thirds of patients in all ethnic groups. Processes of stroke care, including thrombolysis, diagnostic imaging, antithrombotic medications, and rehabilitation services were similar among ethnic groups. Risk of death or recurrent stroke at one year after ischemic stroke was similar for patients who were White (27.6%), East Asian (24.7%, aHR 0.97, 95% CI 0.78-1.21 vs. White), or South Asian (21.9%, aHR 0.91, 95% CI 0.67-1.24 vs. White). Although risk of death or recurrent stroke at one year after intracerebral hemorrhage was higher in East Asian (35.5%) and White patients (47.9%) compared to South Asian patients (30.2%) (p=0.002), these differences disappeared after adjustment for age, sex, stroke severity and comorbid conditions (aHR 0.89 [0.67-1.19] for East Asian vs White and 0.99 [0.54-1.81] for South Asian vs. White).Conclusion: After stratification by stroke type, stroke care and outcomes are similar across ethnic groups in Ontario. Enhanced health promotion is needed to reduce delays to hospital for all ethnic groups. [ABSTRACT FROM AUTHOR]

Background: Administrative health data are increasingly used for research and surveillance to inform decision-making because of its large sample sizes, geographic coverage, comprehensivity, and possibility for longitudinal follow-up. Within Canadian provinces, individuals are assigned unique personal health numbers that allow for linkage of administrative health records in that jurisdiction. It is therefore necessary to ensure that these data are of high quality, and that chart information is accurately coded to meet this end. Our objective is to explore the potential barriers that exist for high quality data coding through qualitative inquiry into the roles and responsibilities of medical chart coders.Methods: We conducted semi-structured interviews with 28 medical chart coders from Alberta, Canada. We used thematic analysis and open-coded each transcript to understand the process of administrative health data generation and identify barriers to its quality.Results: The process of generating administrative health data is highly complex and involves a diverse workforce. As such, there are multiple points in this process that introduce challenges for high quality data. For coders, the main barriers to data quality occurred around chart documentation, variability in the interpretation of chart information, and high quota expectations.Conclusions: This study illustrates the complex nature of barriers to high quality coding, in the context of administrative data generation. The findings from this study may be of use to data users, researchers, and decision-makers who wish to better understand the limitations of their data or pursue interventions to improve data quality. [ABSTRACT FROM AUTHOR]

Background: We describe the implementation of an intervention in Alberta in support of the Choosing Wisely Canada recommendation against population screening for vitamin D deficiency (as determined by serum total 25-hydroxyvitamin D testing). We hypothesized that the introduction of a specialized requisition for vitamin D testing would reduce the annual number of vitamin D tests performed. Methods: We performed a cross-sectional observational study that included all vitamin D tests ordered in Alberta between Apr. 1, 2015, and Mar. 31, 2016. There were no exclusion criteria. A special requisition for ordering vitamin D tests in Alberta was introduced on Apr. 1, 2015. Using an interrupted time series model, we compared predicted versus observed vitamin D test volumes for the 12-month period following the introduction of the new requisition. The sole outcome measure was the monthly change in volume of vitamin D testing. In addition, we calculated any cost savings as a result of reduced testing. Results: Over the first 12 months of the intervention, there was a reduction in the number of tests ordered from a predicted 342 477 tests to 29 525 tests (91.4% reduction). This decrease represented a direct spending decrease of Can$938 856-$1 564 760 per year in Alberta. Interpretation: A provincially led implementation of a Choosing Wisely Canada recommendation resulted in a large and sustained reduction in serum total 25-hydroxyvitamin D testing in Alberta. This study shows that provincially led interventions based on Choosing Wisely Canada recommendations can result in substantial reductions in laboratory tests. [ABSTRACT FROM AUTHOR]

Background: The new International Classification of Diseases, Eleventh Revision for Mortality and Morbidity Statistics (ICD-11) was developed and released by the World Health Organization (WHO) in June 2018. Because ICD-11 incorporates new codes and features, training materials for coding with ICD-11 are urgently needed prior to its implementation. Objective: This study outlines the development of ICD-11 training materials, training processes and experiences of clinical coders while learning to code using ICD-11. Method: Six certified clinical coders were recruited to code inpatient charts using ICD-11. Training materials were developed with input from experts from the Canadian Institute for Health Information and the WHO, and the clinical coders were trained to use the new classification. Monthly team meetings were conducted to enable discussions on coding issues and to select the correct ICD-11 codes. The training experience was evaluated using qualitative interviews, a questionnaire and a coding quiz. Results: total of 3011 charts were coded using ICD-11. In general, clinical coders provided positive feedback regarding the training program. The average score for the coding quiz (multiple choice, True/False) was 84%, suggesting that the training program was effective. Feedback from the coders enabled the ICD-11 code content, electronic tooling and terminologies to be updated. Conclusion: This study provides a detailed account of the processes involved with training clinical coders to use ICD-11. Important findings from the interviews were reported at the annual WHO conferences, and these findings helped improve the ICD-11 browser and reference guide. [ABSTRACT FROM AUTHOR]

Presents a letter to the editor in response to a study of ethnicity in relation to the development of neural tube effects by Joel Ray and associates, that was published in a previous issue of the "Canadian Medical Association Journal."

Risk prediction models are frequently used to identify individuals at risk of developing hypertension. This study evaluates different machine learning algorithms and compares their predictive performance with the conventional Cox proportional hazards (PH) model to predict hypertension incidence using survival data. This study analyzed 18,322 participants on 24 candidate features from the large Alberta's Tomorrow Project (ATP) to develop different prediction models. To select the top features, we applied five feature selection methods, including two filter-based: a univariate Cox p-value and C-index; two embedded-based: random survival forest and least absolute shrinkage and selection operator (Lasso); and one constraint-based: the statistically equivalent signature (SES). Five machine learning algorithms were developed to predict hypertension incidence: penalized regression Ridge, Lasso, Elastic Net (EN), random survival forest (RSF), and gradient boosting (GB), along with the conventional Cox PH model. The predictive performance of the models was assessed using C-index. The performance of machine learning algorithms was observed, similar to the conventional Cox PH model. Average C-indexes were 0.78, 0.78, 0.78, 0.76, 0.76, and 0.77 for Ridge, Lasso, EN, RSF, GB and Cox PH, respectively. Important features associated with each model were also presented. Our study findings demonstrate little predictive performance difference between machine learning algorithms and the conventional Cox PH regression model in predicting hypertension incidence. In a moderate dataset with a reasonable number of features, conventional regression-based models perform similar to machine learning algorithms with good predictive accuracy. [ABSTRACT FROM AUTHOR]

Qualitative data analysis is produced frequently in healthcare settings, which is a time-consuming and skilled analytic task. The use of qualitative research findings in clinical settings takes years, which is sometimes obsolete knowledge as the health context is dynamic. Artificial Intelligence (AI)-based qualitative data analysis might present with rapid analysis of text-based data in real-time, thereby empowering qualitative researchers to expedite their analysis and facilitate timely use of the research findings. We tested an AI-based method to complement the manual analysis of text-based data from the verbatim transcripts of seven mall managers' interviews. First, we prepared text data into a machine-calculable format and employed BERT model to extract sentence-level features in our case. Second, we implement TF-IDF-based keywords mining techniques to extract the main candidate themes from the interview transcripts to support text-based analysis, including: 1) primary cluster detection algorithm, and 2) keyword extraction algorithm. The extracted core themes provide qualitative researchers with a more comprehensive overview of the qualitative data. Most of the sentences clustered in meaningful short topics or sentences carrying independent and clear information. The extracted topics and clustered sentences reduced qualitative researchers' workload by condensing and identifying meaningful concepts and naming them. This method combining contextualized word embeddings, unsupervised clustering, and keyword extraction techniques can significantly reduce the overall workload and time consumed in qualitative research using conventional methods. [ABSTRACT FROM AUTHOR]

Background: Case identification is important for health services research, measuring health system performance and risk adjustment, but existing methods based on manual chart review or diagnosis codes can be expensive, time consuming or of limited validity. We aimed to develop a hypertension case definition in electronic medical records (EMRs) for inpatient clinical notes using machine learning. Methods: A cohort of patients 18 years of age or older who were discharged from 1 of 3 Calgary acute care facilities (1 academic hospital and 2 community hospitals) between Jan. 1 and June 30, 2015, were randomly selected, and we compared the performance of EMR phenotype algorithms developed using machine learning with an algorithm based on the Canadian version of the International Statistical Classification of Diseases and Related Health Problems , 10th Revision (ICD), in identifying patients with hypertension. Hypertension status was determined by chart review, the machine-learning algorithms used EMR notes and the ICD algorithm used the Discharge Abstract Database (Canadian Institute for Health Information). Results: Of our study sample (n = 3040), 1475 (48.5%) patients had hypertension. The group with hypertension was older (median age of 71.0 yr v. 52.5 yr for those patients without hypertension) and had fewer females (710 [48.2%] v. 764 [52.3%]). Our final EMR-based models had higher sensitivity than the ICD algorithm (> 90% v. 47%), while maintaining high positive predictive values (> 90% v. 97%). Interpretation: We found that hypertension tends to have clear documentation in EMRs and is well classified by concept search on free text. Machine learning can provide insights into how and where conditions are documented in EMRs and suggest nonmachine-learning phenotypes to implement. [ABSTRACT FROM AUTHOR]

Background: Prognostic information for patients with hypertension is largely based on population averages. The purpose of this study was to compare the performance of four machine learning approaches for personalized prediction of incident hospitalization for cardiovascular disease among newly diagnosed hypertensive patients. Methods: Using province-wide linked administrative health data in Alberta, we analyzed a cohort of 259,873 newly-diagnosed hypertensive patients from 2009 to 2015 who collectively had 11,863 incident hospitalizations for heart failure, myocardial infarction, and stroke. Linear multi-task logistic regression, neural multi-task logistic regression, random survival forest and Cox proportional hazard models were used to determine the number of event-free survivors at each time-point and to construct individual event-free survival probability curves. The predictive performance was evaluated by root mean squared error, mean absolute error, concordance index, and the Brier score. Results: The random survival forest model has the lowest root mean squared error value at 33.94 and lowest mean absolute error value at 28.37. Machine learning methods provide similar discrimination and calibration in the personalized survival prediction of hospitalizations for cardiovascular events in patients with hypertension. Neural multi-task logistic regression model has the highest concordance index at 0.8149 and lowest Brier score at 0.0242 for the personalized survival prediction. Conclusions: This is the first personalized survival prediction for cardiovascular diseases among hypertensive patients using administrative data. The four models tested in this analysis exhibited a similar discrimination and calibration ability in predicting personalized survival prediction of hypertension patients. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]