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Introduction / Åke Blomquist and Egon Jonsson -- Social health insurance: government funding of health care / Åke Blomquist -- Private financing outside the publicly funded system / Mark Stabile -- Prescription drug financing / Steve Morgan -- The economics of consumer-directed health care / Ching- To Albert Ma -- Medical saving accounts: promises and pitfalls / Jeremiah E. Hurley and G. Emmanuel Guindon -- Physician payment mechanisms / Pierre Thomas Léger -- Risk adjustment in health care markets: concepts and applications / Randall P. Ellis -- Inducing quality from health care providers in the presence of adverse selection / Jacob Glazer and Thomas G. McGuire -- Equity in health and health care in Canada in international perspective / Eddy van Doorslaer.

Abstract Widespread integration of market‐based incentives into healthcare systems calls for – and has elicited – increasing adoption of risk adjustment. By deterring selection, risk adjustment helps to assure fair and efficient payments among health insurers or capitated provider groups. However, since conventional risk adjustment allocates funds among regions or insurers according to current population health status, it does not reward – indeed, it penalizes – preventive efforts that improve population health. This prevention penalty of risk adjustment represents a hidden cost of unclear magnitude, undermining provider incentives for health promotion. We develop a theoretical model of selection and prevention demonstrating this problem with conventional risk adjustment and suggesting a simple alternative: risk adjustment should be linked to pay‐for‐performance for prevention.

BACKGROUND AND AIMS: We report on a cost analysis study, using population level data to determine the emergency service costs avoided from emergency overdose management at supervised consumption services (SCS). DESIGN: We completed a cost analysis from a payer's perspective. In this setting, there is a single-payer model of service delivery. SETTING: In Calgary, Canada, 'Safeworks Harm Reduction Program' was established in late 2017 and offers 24/7 access to SCS. The facility is a nurse-led service, available for client drop-in. We conducted a cost analysis for the entire duration of the program from November 2017 to January 2020, a period of 2 years and 3 months. METHODS: We assessed costs using the following factors from government health databases: monthly operational costs of providing services for drug consumption, cost of providing ambulance pre-hospital care for clients with overdoses who could not be revived at the facility, cost of initial treatment in an emergency department, and benefit of costs averted from overdoses that were successfully managed at the SCS. RESULTS: The proportion of clients who have overdosed at the SCS has decreased steadily for the duration of the program. The number of overdoses that can be managed on site at the SCS has trended upward, currently 98%. Each overdose that is managed at the SCS produces approximately $1600 CAD in cost savings, with a savings of over $2.3 million for the lifetime of the program. CONCLUSION: Overdose management at an SCS creates cost savings by offsetting costs required for managing overdoses using emergency department and pre-hospital ambulance services. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12954-022-00609-5.

ABSTRACT
BackgroundHospital length of stay (LOS) is a widely used measure for assessing cross-jurisdiction health system performance and informs resource allocation decisions. However, the accuracy of existing LOS risk adjustment models are limited, because they are mostly derived from administrative data, which mostly contain clinical/diagnostic information but lack detailed information on relevant demographic, socio-economic (SES), and self-reported health-related quality of life (HRQOL) risk factors, which have been shown to improve the accuracy of LOS risk adjustment models. The study investigates the relative contribution of demographic, socio-economic, and health status risk factors derived through data linkage in improving the accuracy of LOS risk adjustment models.
MethodsPopulation-based data on 8000 individuals hospitalized for coronary heart disease were obtained from Alberta Provincial Project on Outcomes Assessment in Coronary Heart Disease (APPROACH) registry and linked to Alberta Discharge Abstract Database (DAD). SES was measured using multi-domain measure of SES derived from area-level census information, while the health-related quality of life outcome was measured using the Seattle Angina Questionnaire. LOS risk adjustment model based on hierarchical logistic regression models was developed to assess relative impact of each SES measure and HRQOL measure improving the predictive accuracy of LOS adjustment models. The relative impact of each predictor was assessed by its adjusted odds ratio (OR) and improvement over the predictive accuracy of a reference model that included patients' clinical risk factors only.
ResultMore than 80% of the hospitalized individuals had prolonged LOS more than 10 days. The HRQOL and single-domain measures of SES had significant impact in accurately predicting LOS. But the inclusion of the multi-domain measure SES did not significantly improve the accuracy of LOS risk adjustment models
ConclusionUsing large population-based Canadian data, our study suggests that the inclusion of patients' SES and health status information through data linkage can improve the accuracy of LOS risk adjustment models. The development of more accurate risk adjustment models can aid the identification of individuals at risk of prolonged LOS and comparison of health system performance across several cross-jurisdictions.

Abstract Background Health decision-making requires evidence from high-quality data. As one example, the Discharge Abstract Database (DAD) compiles data from the majority of Canadian hospitals to form one of the most comprehensive and highly regarded administrative health databases available for health research, internationally. However, despite the success of this and other administrative health data resources, little is known about their history or the factors that have led to their success. The purpose of this paper is to provide an historical overview of Canadian administrative health data for health research to contribute to the institutional memory of this field. Methods We conducted a qualitative content analysis of approximately 20 key sources to construct an historical narrative of administrative health data in Canada. Specifically, we searched for content related to key events, individuals, challenges, and successes in this field over time. Results In Canada, administrative health data for health research has developed in tangent with provincial research centres. Interestingly, the lessons learned from this history align with the original recommendations of the 1964 Royal Commission on Health Services: (1) standardization, and (2) centralization of data resources, that is (3) facilitated through governmental financial support. Conclusions The overview history provided here illustrates the need for longstanding partnerships between government and academia, for classification, terminology and standardization are time-consuming and ever-evolving processes. This paper will be of interest to those who work with administrative health data, and also for countries that are looking to build or improve upon their use of administrative health data for decision-making.

BACKGROUND: Health decision-making requires evidence from high-quality data. As one example, the Discharge Abstract Database (DAD) compiles data from the majority of Canadian hospitals to form one of the most comprehensive and highly regarded administrative databases available for health research, internationally. However, despite the success of this and other administrative health data resources, little is known about their history or the factors that have led to their success. The purpose of this paper is to provide an historical overview of administrative data for health research in Canada to contribute to the institutional memory of this field. METHODS: We conducted a qualitative content analysis of approximately 20 key sources to construct an historical narrative of administrative health data in Canada. Specifically, we searched for content related to key events, individuals, challenges, and successes in this field over time. RESULTS AND DISCUSSION: In Canada, administrative data for health research has developed in tangent with provincial research centres. Interestingly, the lessons learned from this history align with the original recommendations of the 1964 Royal Commission on Health Services: (1) standardization, and (2) centralization of data resources, that is (3) facilitated through governmental financial support. CONCLUSIONS: The overview history provided here illustrates the need for longstanding partnerships between government and academia, for classification and standardization are time-consuming and ever-evolving processes. This paper will be of interest to those who work with administrative health data, and also for countries that are looking to build or improve upon their use of administrative health data for decision-making. ; At the time of writing KL was supported by a University of Calgary Achievers in Medical Sciences graduate recruitment scholarship and is currently an Alberta Innovates – Health Solutions graduate trainee. TTS is supported by an MSI Foundation New Investigator Grant and ...

Background: It is essential that clinical documentation and clinical coding be of high quality for the production of healthcare data. Objective: This study assessed qualitatively the strengths and barriers regarding clinical coding quality from the perspective of health information managers. Method: Ten health information managers and clinical coding quality coordinators who oversee clinical coders (CCs) were identified and recruited from nine provinces across Canada. Semi-structured interviews were conducted, which included questions on data quality, costs of clinical coding, education for health information management, suggestions for quality improvement and barriers to quality improvement. Interviews were recorded, transcribed and analysed using directed content analysis and informed by institutional ethnography. Results: Common barriers to clinical coding quality included incomplete and unorganised chart documentation, and lack of communication with physicians for clarification. Further, clinical coding quality suffered as a result of limited resources (e.g. staffing and budget) being available to health information management departments. Managers unanimously reported that clinical coding quality improvements can be made by (i) offering interactive training programmes to CCs and (ii) streamlining sources of information from charts. Conclusion: Although clinical coding quality is generally regarded as high across Canada, clinical coding managers perceived quality to be limited by incomplete and inconsistent chart documentation, and increasing expectations for data collection without equal resources allocated to clinical coding professionals. Implications: This study presents novel evidence for clinical coding quality improvement across Canada.

IntroductionCoded data serves a critical part in the process of identifying the resource allocation required for each department in a hospital and for research purposes. This paper attempts a cost-benefit analysis of the transition from ICD-9 health indicator coding system to ICD-10 coding system and quantify the economic impacts.
Objectives and ApproachThe hypothesis adopted by this paper is that the transition from ICD-9 to ICD-10 has been beneficial for the health system due better disease management, resulting in cost savings and facilitation of high quality health research. Analyzing the inflation-adjusted costs compared with the benefits accrued from implementing the new coding system would enable informed decision making for the stakeholders at government and other levels of health provision.
The methodology involves constructing 'benefit scenarios' via analysis of existing literature and interviewing coding managers; costs are evaluated using data collected on re-training coders and productivity losses during the transition phase.
ResultsAn example of a benefit scenario would take the form of cost savings associated with correctly identifying people with diabetes (due to coded charts), hence resulting in a decline in blood sugar (HbA1c) levels via better disease management. This in turn may cause reductions in other high blood-sugar related diseases and thus increase efficiency for government funding in the health care sector. Improved data quality in ICD-10 is expected to have resulted in gains from specificity due to increased sensitivity of data classification and grouping. Actual cost of re-training of coders and ICD-10 software provider fees are expected to be higher than the costs anticipated before ICD-10 implementation. Productivity losses in the transition phase are expected to have declined as coders became more adept at coding.
Conclusion/ImplicationsAn economic evaluation proves to be a vital part of eliciting whether the transition to the newer method of coding, ICD-10, has been beneficial to the end users of the data. It is important to understand the efficiency of resource allocation to healthcare and the financial implications such investments entail.

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.