bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Importance and Usefulness of Corporate Annual Reports in Malaysia
Authors: Mohd. Ghazali Nazli Anum 
Published: September 2018

The purpose of this study is to examine the perceived importance and usefulness of corporate annual reports in Malaysia and to determine if there is a difference between the perceptions of preparers and users of corporate annual reports. Data for this study were collected using a questionnaire survey conducted in late 2006 and early 2007. Preparers are represented by chief financial officers while users by investment analysts. The mean scores for preparers and users are compared using the independent samples t test and the non-parametric Mann-Whitney test to determine if there are any statistically significant differences in their opinions. The findings reveal that preparers rank the annual report as the most important source of corporate information. Users, on the other hand, rank the annual report as the second most important after the visits to companies. However, the difference in the mean scores of preparers and those of users on the importance of annual reports is not significant at 5 percent level. The difference in the mean scores for the visits to companies is, on the other hand, statistically significant at 5 percent level. An implication for this finding is whether the annual report serves the information needs of analysts for decision-making purposes. An opportunity thus arises for future research to examine information needs of analysts and if there is a gap between information provided in annual reports and that required by analysts. Keywords: corporate annual reports; disclosure; Malaysia; transparency
The Impact of Government Debt Issuance on Short-Term interest rates in Indonesia
Authors: Adiningsih Sri 
Published: September 2018

This paper analyzes whether the expansionary fiscal policy funded by issuing debt instruments in financial markets will increase short-term interest rates. If the expansionary fiscal policy increases interest rates, which decrease private spending especially investment, crowding out occurs. This is interesting because global economic crisis has encouraged many countries to run large budget deficits to stimulate the economy. Indonesia has also run budget deficit during this crisis and even in years before. The impact of such a policy can be significant because Indonesia’s debt market is still narrow and shallow. Therefore, its capability of absorbing the government debt instruments without influencing the private sector funding is limited. This study tests whether the crowding out occurs in Indonesia using a time series econometric model inspired by Cebula and Cuellar’s model. The Cointegration Regression and Error Correction Model (ECM) are used in this study. Monthly data from April 2000 to December 2008 are used for overnight real interbank call money interest rates, real net government bond issues in trading, real narrow money supply, real rate of one-month Certificate of Bank Indonesia, growth of Gross Domestic Product, and real net international capital flows. This empirical study shows that the crowding out problem occurred in Indonesia during the period. This indicates that financing budget deficit in Indonesia by issuing debt instruments in the financial markets has a negative impact on the private sector.
Does the Mandatory Adoption of IFRS Improve the Association between Accruals and Cash Flows? Evidence from Accounting Estimates
Authors: Downes Jimmy F. , Kang Tony , Kim Sohyung , Lee Cheol 
Published: September 2018

SYNOPSIS
We investigate the effect of mandatory International Financial Reporting Standards (IFRS) adoption in the European Union on the association between accounting estimates and future cash flows, a key concept of accounting quality within the International Accounting Standard Board conceptual framework. We find that the predictive value of accounting estimates improves after IFRS adoption. This improvement is largely driven by specific types of accounting estimates, such as accounts receivable, depreciation, and amortization expense. We also find that the improvement is concentrated in countries with larger differences between pre-IFRS domestic GAAP and IFRS. Our findings suggest that IFRS allow managers to exercise their judgment to provide information about future cash flows through the more subjective/judgmental portion of accounting accruals.
JEL Classifications: M16; M49; O52.
Data Availability: The data used in this study are from public sources identified in the study.
Association of Albuminuria With Intraglomerular Hydrostatic Pressure and Insulin Resistance in Subjects With Impaired Fasting Glucose and/or Impaired Glucose Tolerance
Authors: Tsuda Akihiro , Ishimura Eiji , Uedono Hideki , Ochi Akinobu , Nakatani Shinya , Morioka Tomoaki , Mori Katsuhito , Uchida Junji , Emoto Masanori , Nakatani Tatsuya , Inaba Masaaki 
Published: September 2018

OBJECTIVE
Little is known about the relationships between insulin resistance, intrarenal hemodynamics, and urinary albumin excretion (UAE) in humans with impaired fasting glucose (IFG) and/or impaired glucose tolerance (IGT). The aim of the current study was to examine intrarenal hemodynamic abnormalities, insulin resistance, and UAE in subjects with IFG or IGT. We hypothesized that intrarenal hemodynamic abnormalities would be associated with insulin resistance.

RESEARCH DESIGN AND METHODS
Fifty-four kidney donors underwent 75-g oral glucose tolerance and inulin and para-aminohippuric acid clearance testing. Insulin sensitivity index (ISI) was evaluated by the Matsuda index. Intrarenal hemodynamic parameters were calculated by the Gomez formulae.

RESULTS
Of the 54 subjects, 33 exhibited IFG or IGT and 31 exhibited normal glucose tolerance (NGT). Glomerular hydrostatic pressure (Pglo) and UAE were significantly higher in the IFG or IGT subjects with obesity (P = 0.015 and 0.0001, respectively). Log ISI correlated significantly and negatively with Pglo (r = −0.351, P = 0.009) in all subjects. In multiple regression analyses among all subjects, log ISI was associated significantly and independently with Pglo (β = −0.316, P = 0.015), after adjustment for age, sex, and systolic blood pressure. Further, BMI (β = 0.517, P = 0.0004), Pglo (β = 0.420, P = 0.004), and log ISI (β = −0.366, P = 0.008) were each associated significantly and independently with UAE after adjustment.

CONCLUSIONS
We demonstrated that increased insulin resistance is associated with increased Pglo and UAE in IFG or IGT subjects. These hemodynamic burdens and insulin resistance may cause injury to the glomeruli even in subjects with IFG or IGT.
Stats NZ Integrated Data Population Explorer Prototype – using data visualisation to increase usability of large scale, complex and messy data
Authors: Lefebre Aaron , Ashby Lucy , McDowell Anna , Blackburn Andrea 
Published: September 2018

IntroductionStats NZ works with a range of organisations to provide the world-leading Integrated Data Infrastructure (IDI) to help improve New Zealanders’ lives. IDI is a critical tool in our government’s efforts to reduce poverty, improve health, and provide a growing, inclusive economy. It enables evidence-based insights, and measurement of government services.
Objectives and ApproachUsers currently need a large degree of technical capability to access and use the IDI. Our Population Explorer Prototype is an integrated data digital product designed to increase the use and improve the usability of the IDI by reducing barriers for current researchers and new customer groups.
ResultsThe Population Explorer Prototype makes it easier and more efficient for new and existing users to gain insights from data by shifting from having to repeatedly carry out complex coding to get information in tables, to being able to “point and click” to see information in a range of visual, easy-to-understand formats. There is wide excitement in the data community about this product’s potential and implementing user feedback has been a key part of improving the product.
Conclusion/ImplicationsWe have only scratched the surface of what is possible with integrated data, and the Population Explorer Prototype is the next frontier. The Population Explorer Prototype will unleash the power of data to change peoples’ lives to a wider range of researchers, while protecting privacy and security.
Ontario case costing: A catalyst for transforming Ontario’s health system into a value-based model
Authors: Zheng Jianing 
Published: September 2018

IntroductionCase costing is the only source of integrated financial, clinical, and utilization data at the patient level in Ontario. This accounting tool improves funding and performance management processes and tracks health care service costs for informed decision making based on quality and value.
Objectives and ApproachThe only source of integrated financial, clinical, and utilization data at the patient level, case costing provides a clear picture of each patient in terms of where the patient received care, who was the provider, what type of care was provided, and the total cost to treat each patient.
Case costing is a critical tool for system-wide planning by providing a province-wide view of cost and clinical variations. Health organizations can compare costs associated with service utilization to identify organizational variances among peers. Identifying the source of these variances drives effective resource utilization and management while delivering high-quality care.
ResultsCase costing provides a range of benefits and uses:

Improved benchmarking and performance measurement processes by comparing utilization and costs among various clinical practices with similar clinical outcomes and measuring performance internally and externally to understand efficiencies and outcomes against peers.
Providing critical information for innovative care initiatives, such as the Bundled Care Model. The bundled care model improves efficiency through more integrated use of resources, reduced variation in access to services, and improved patient outcomes through seamless transitions across the care continuum. Case costing informs funding allocations in the hospital sector with expected expansion to home care funding.
More sophisticated planning and forecasting, such as impact analysis by modeling the adoption of new physicians or technologies within facilities to determine cost and volume impact.

Conclusion/ImplicationsAdministrators, clinicians, and health service organizations use case costing data for informing best practices and improving efficiency. By helping users to understand the cost of care at patient and provider levels across the patient journey, case costing has been a catalyst for enabling value-based care.
Use of linked electronic health records to evaluate cardiovascular risk prediction models in Ontario, Canada
Authors: Sivaswamy Atul , Khan Anam , Tu Karen , Azizi Paymon , Ko Dennis , Tu Jack 
Published: September 2018

IntroductionElectronic health records (EHR) contain individual-level clinical information not found in traditional administrative databases. As part of the CANHEART-Strategy for Patient Oriented Research (SPOR) initiative, we created a linked EHR-administrative data cohort that enables us to measure the Framingham and ACC/AHA Pooled Cohort cardiovascular risk prediction scores in Ontario, Canada.
Objectives and ApproachAn EHR primary care cohort was created using the Electronic Medical Record Administrative data Linked Database (EMRALD) database, which contains the blood pressure and lipid values, weight and height measures, prescriptions and smoking status of up to 350,000 patients in Ontario, Canada. We enriched the lipid information through linkage to the Ontario Laboratory Information System, which is a repository of 90%+ of all lipid tests in Ontario. Individual-level information on co-morbidities, hospitalizations and mortality attributed to cardiovascular causes (e.g. myocardial infarction, stroke, cardiovascular mortality) were obtained through linkage to provincial health administrative and vital statistics databases using CANHEART methodology (www.canheart.ca).
ResultsPatients were entered into the cohort between 2008 and 2014 if they had measurements for blood pressure and lipids (total cholesterol and high-density lipoprotein) taken within a year of each other during this accrual window. The earliest such group of values was chosen and determined the individual’s index date. Age, sex, smoking, diabetes and anti-hypertensive treatment status were extracted from EHR or administrative data to calculate the two scores. Patients were excluded if not aged 40-75 on the index date or if they had a history of cardiovascular disease. A cohort of 84,628 Ontario residents (mean age 55.0 years) had the elements required to calculate both scores. Follow-up for outcome events were done through record linkage to the end of 2014, with a mean follow-up of 3.62 years.
Conclusion/ImplicationsThe creation of this cohort will allow for the validation of the Framingham and AHA/ACC Pooled Cohort equations in the diverse Ontario population. It would also enable the possible development of a new ‘made-in-Canada’ cardiovascular risk prediction model.
Linking Emergency Medical Services and Health System Data: Optimal Strategy and Bias Mitigation
Authors: Blanchard Ian , Ronksley Paul E , Quan Hude , Li Bing , Doig Christopher 
Published: September 2018

IntroductionEmergency Medical Services (EMS) systems dispatch paramedics to emergencies in the community. For critically ill patients, paramedic interventions and transport destination decisions may impact outcomes. Research is needed to inform paramedic care, but linking EMS data to health system outcomes is a barrier. Limited research exists on EMS data linkage.
Objectives and ApproachTo optimize linkage of EMS data (fiscal year 2016/17) to the National Ambulatory Care Reporting System/Sunrise Clinical Manager datasets and assess bias. A random sample of EMS records were deterministically linked on provincial health number (PHN), transport destination, and EMS/emergency department arrival/presentation times ≤2hrs. Linked data were manually verified using last name, sex, date of birth, and hospital file number. For patients that remained unlinked (based on the variables listed above), further linkage attempts were made using additional variables. The combination of variables that optimized sensitivity/positive predictive value/f-measure were used to link the fiscal year. Linked/unlinked groups were descriptively compared.
ResultsWhile results are still pending (available April, 2018), we hypothesize that there may be inherent differences in the clinical and encounter characteristics of patients that were linked versus unlinked. Patient identifiers such as PHN and name are important for linkage, but are not always collected on EMS events that require immediate treatment and rapid transport, yet these patients may be the most critically ill.
Conclusion/ImplicationsAs more EMS systems attempt to systematically link their data to health system outcome, these results will be important to mitigate potential bias.
Strengths and Barriers to Coding Hospital Chart Information from Health Information Manager Perspectives: A Qualitative Study
Authors: Doktorchik Chelsea , Lu Mingshan , Ringham Cathy , Quan Hude , Eastwood Catherine 
Published: September 2018

IntroductionIt is essential that clinical documentation and data coding be of high quality for the production of healthcare data for research or administrative purposes. However, there is a limited understanding of the facilitators and barriers of coded data quality and strategies to improve it.
Objectives and ApproachOur objective was to qualitatively assess what influences coded data quality from the perspective of health information managers who are responsible for the work of coding specialists. Nine health information managers and/or coding quality coordinators who oversee coding specialists were identified and recruited from nine provinces across Canada to participate in this study. Semi-structured interviews were conducted which asked questions on participant demographics, responsibilities, data quality, costs and budget of coding, continuing education for Health Information Management (HIM), suggestions for quality improvement, and barriers to quality improvement. Interviews were recorded and transcribed, and analyzed using Directed Content Analysis methodology.
ResultsInterviewees were primarily responsible for managing staff, quality assurance, audits, reporting, budget, data collection, and transcription. Managers reported that the experienced coders under their employ strengthened coding quality. Common barriers to coding quality included incomplete and unorganized chart documentation, which led to undercoding, and lack of communication and access to physicians for clarification when needed. Further, coding quality suffered as a result of limited resources (e.g. staffing and budget) being available to HIM departments for an ever-expanding workload, that was commonly due to increasingly complex charts and additional project data. Managers unanimously reported that coding quality improvements can be made by 1) making interactive training programs available to coding specialists, and 2) streamlining sources of information from charts (i.e., transitioning to standardized electronic charting).
Conclusion/ImplicationsAlthough coding quality is generally regarded as high across Canada, quality can be hampered by incomplete and inconsistent chart documentation, lack of resources (e.g. financial support, staff, education), and inconsistent coding standards across hospitals and provinces. This study presents novel evidence for coding quality improvement across Canada.
Identifying and Prioritizing Low Value Care in British Columbia Using Three Administrative Health Data Assets
Authors: Soril Lesley , Mitton Craig , Seixas Brayan , Bryan Stirling , Clement Fiona 
Published: September 2018

IntroductionClinical recommendations and/or lists of low value care (i.e., health technologies that provide little to clinical benefit for certain patient groups) have garnered attention internationally through campaigns such as Choosing Wisely. However, uptake of such recommendations at the healthcare system-level remains challenging in the absence of routine, data-driven processes.
Objectives and ApproachThe objective of this work was to develop and implement a process, leveraging administrative health data assets and lists of ‘low value’ care, to identify and prioritize technologies at the healthcare system-level for reassessment and potential disinvestment. The British Columbia (BC) healthcare system was selected as the pilot site to test the process. Three provincial administrative health databases were used to examine the extent of low value care across the system: the discharge abstract database (DAD); the Medical Service Plan (MSP) physician claims database; and the MSP laboratory database.
ResultsOver 1300 recommendations of low value technologies (i.e., from the National Institute for Health and Care Excellence “do not do” recommendations, low value technologies in the Australian Medical Benefits Schedule, and Choosing Wisely “Top 5” lists) were identified. Using appropriate coding systems for BC’s administrative health data (e.g., International Classification of Diseases), low value technologies were queried to examine frequencies and costs of technology use between fiscal years 2010/11 and 2014/15. This information was used to rank technologies based high budgetary impact, defined as total in-hospital and claims expenditures exceeding $1M in any fiscal year examined. Clinical experts reviewed the ranked technologies prior to dissemination and stakeholder action. Pilot testing resulted in the prioritization of 9 candidate technologies for reassessment in the BC healthcare system.
Conclusion/ImplicationsThis work demonstrates the feasibility and strength of using administrative data to identify low value care at the healthcare system-level and prioritize candidates for reassessment. Faced with increasing pressure to control exorbitant costs, while maintaining quality of care, this process has been adopted and operationalized by the BC Ministry of Health.
A bayesian way to correct for measurement error in drug risk estimates from EHR data.
Authors: Lavigne Maxime , Goulden Robert , Habib Bettina , Joseph Lawrence , Girard Nadyne , Buckeridge David , Tamblyn Robyn 
Published: September 2018

IntroductionData from electronic medical records is now readily available and records information needed in pharmacoepidemiological studies not usually found in administrative data such as risk factors and biometrics. Yet, EMR data leads to measurement error due to primary non-adherence. Bayesian bias correction could provide corrected estimates from administrative data.
Objectives and ApproachWe present a method for correcting risk estimates from EMR data using linked data. In our example, we estimate the risk of cardiovascular events from oral-hypoglycemics in patients with type-2 diabetes in Boston, Quebec, and the UK between 2009 and 2012. Using linked EMR and administrative data in Quebec, we compute a positive and negative predicting value of prescription on dispensation for each class of oral-hypoglycemics. The cardiovascular risk is then analysed using a bayesian Weibull survival model adjusted for potential confounders. A similar model is then computed that accounts for exposure measurement error using the PPV and NPV.
ResultsThe Quebec and Boston cohorts have similar sizes with 1197 and 2346 patients, but the UK was bigger at 41370 patients. In Quebec's data, there were important differences in PPV and NPV by class of oral-hypoglycemics with PPVs for Biguanides at 0.81, Sulphonylureas at 0.65, and others at 0.50. The pattern for NPV differed with the same classes having respectively values of 0.56, 0.97, and 0.99. Estimates from the naïve model are typical of similar analysis but compared to their correction, they were generally overprecise and biased towards the null. The adjusted estimated were adequately representing the increased uncertainty with hazard ratios for Sulphonylureas going from 1.72 (1.22, 2.41) to 3.19 (1.36, 5.93), and from 1.09 (0.86, 1.39) to 1.05 (0.45, 2.16) for no drugs
Conclusion/ImplicationsBayesian adjustment for measurement error allowed us to use linked data to regenerate uncertainty and to correct the bias in our risk estimates. Our approach was impacted by the observed low predictive value of prescribing, by reduced transportability of our PPV and NPV estimates, and other sources of bias.