3 resultados para financial data processing

em DigitalCommons@The Texas Medical Center


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Objective. Long Term Acute Care Hospitals (LTACs) are subject to Medicare rules because they accept Medicare and Medicaid patients. In October 2002, Medicare changed the LTAC reimbursement formulas, from a cost basis system to a Prospective Payment System (PPS). This study examines whether the PPS has negatively affected the financial performance of the LTAC hospitals in the period following the reimbursement change (2003-2006), as compared to the period prior to the change (1999-2003), and if so, to what extent. This study will also examine whether the PPS has resulted in a decreased average patient length of stay (LOS) in the LTAC hospitals for the period of 2003-2006 as compared to the prior period of 1999-2003, and if so, to what extent. ^ Methods. The study group consists of two large LTAC hospital systems, Kindred Healthcare Inc. and Select Specialty Hospitals of Select Medical Corporation. Financial data and operational indicators were reviewed, tabulated and dichotomized into two groups, covering the two periods: 1999-2002 and 2003-2006. The financial data included net annual revenues, net income, revenue per patient per day and profit margins. It was hypothesized that the profit margins for the LTAC hospitals were reduced because of the new PPS. Operational indicators, such as annual admissions, annual patient days, and average LOS were analyzed. It was hypothesized that LOS for the LTAC hospitals would have decreased. Case mix index, defined as the weighted average of patients’ DRGs for each hospital system, was not available to cast more light on the direction of LOS. ^ Results. This assessment found that the negative financial impacts did not materialize; instead, financial performance improved during the PPS period (2003-2006). The income margin percentage under the PPS increased for Kindred by 24%, and for Select by 77%. Thus, the study’s working hypothesis of reduced income margins for the LTACs under the PPS was contradicted. As to the average patient length of stay, LOS decreased from 34.7 days to 29.4 days for Kindred, and from 30.5 days to 25.3 days for Select. Thus, on the issue of LTAC shorter length of stay, the study’s working hypothesis was confirmed. ^ Conclusion. Overall, there was no negative financial effect on the LTAC hospitals during the period of 2003-2006 following Medicare implementation of the PPS in October 2002. On the contrary, the income margins improved significantly. ^ During the same period, LOS decreased following the implementation of the PPS. This was consistent with the LTAC hospitals’ pursuit of financial incentives.^

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Objective. Long Term Acute Care Hospitals (LTACs) are subject to Medicare rules because they accept Medicare and Medicaid patients. In October 2002, Medicare changed the LTAC reimbursement formulas, from a cost basis system to a Prospective Payment System (PPS). This study examines whether the PPS has negatively affected the financial performance of the LTAC hospitals in the period following the reimbursement change (2003–2006), as compared to the period prior to the change (1999–2003), and if so, to what extent. This study will also examine whether the PPS has resulted in a decreased average patient length of stay (LOS) in the LTAC hospitals for the period of 2003–2006 as compared to the prior period of 1999-2003, and if so, to what extent. ^ Methods. The study group consists of two large LTAC hospital systems, Kindred Healthcare Inc. and Select Specialty Hospitals of Select Medical Corporation. Financial data and operational indicators were reviewed, tabulated and dichotomized into two groups, covering the two periods: 1999–2002 and 2003–2006. The financial data included net annual revenues, net income, revenue per patient per day and profit margins. It was hypothesized that the profit margins for the LTAC hospitals were reduced because of the new PPS. Operational indicators, such as annual admissions, annual patient days, and average LOS were analyzed. It was hypothesized that LOS for the LTAC hospitals would have decreased. Case mix index, defined as the weighted average of patients’ DRGs for each hospital system, was not available to cast more light on the direction of LOS. ^ Results. This assessment found that the negative financial impacts did not materialize; instead, financial performance improved during the PPS period (2003–2006). The income margin percentage under the PPS increased for Kindred by 24%, and for Select by 77%. Thus, the study’s working hypothesis of reduced income margins for the LTACs under the PPS was contradicted. As to the average patient length of stay, LOS decreased from 34.7 days to 29.4 days for Kindred, and from 30.5 days to 25.3 days for Select. Thus, on the issue of LTAC shorter length of stay, the study’s working hypothesis was confirmed. ^ Conclusion. Overall, there was no negative financial effect on the LTAC hospitals during the period of 2003–2006 following Medicare implementation of the PPS in October 2002. On the contrary, the income margins improved significantly. ^ During the same period, LOS decreased following the implementation of the PPS. This was consistent with the LTAC hospitals’ pursuit of financial incentives. ^

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Clinical Research Data Quality Literature Review and Pooled Analysis We present a literature review and secondary analysis of data accuracy in clinical research and related secondary data uses. A total of 93 papers meeting our inclusion criteria were categorized according to the data processing methods. Quantitative data accuracy information was abstracted from the articles and pooled. Our analysis demonstrates that the accuracy associated with data processing methods varies widely, with error rates ranging from 2 errors per 10,000 files to 5019 errors per 10,000 fields. Medical record abstraction was associated with the highest error rates (70–5019 errors per 10,000 fields). Data entered and processed at healthcare facilities had comparable error rates to data processed at central data processing centers. Error rates for data processed with single entry in the presence of on-screen checks were comparable to double entered data. While data processing and cleaning methods may explain a significant amount of the variability in data accuracy, additional factors not resolvable here likely exist. Defining Data Quality for Clinical Research: A Concept Analysis Despite notable previous attempts by experts to define data quality, the concept remains ambiguous and subject to the vagaries of natural language. This current lack of clarity continues to hamper research related to data quality issues. We present a formal concept analysis of data quality, which builds on and synthesizes previously published work. We further posit that discipline-level specificity may be required to achieve the desired definitional clarity. To this end, we combine work from the clinical research domain with findings from the general data quality literature to produce a discipline-specific definition and operationalization for data quality in clinical research. While the results are helpful to clinical research, the methodology of concept analysis may be useful in other fields to clarify data quality attributes and to achieve operational definitions. Medical Record Abstractor’s Perceptions of Factors Impacting the Accuracy of Abstracted Data Medical record abstraction (MRA) is known to be a significant source of data errors in secondary data uses. Factors impacting the accuracy of abstracted data are not reported consistently in the literature. Two Delphi processes were conducted with experienced medical record abstractors to assess abstractor’s perceptions about the factors. The Delphi process identified 9 factors that were not found in the literature, and differed with the literature by 5 factors in the top 25%. The Delphi results refuted seven factors reported in the literature as impacting the quality of abstracted data. The results provide insight into and indicate content validity of a significant number of the factors reported in the literature. Further, the results indicate general consistency between the perceptions of clinical research medical record abstractors and registry and quality improvement abstractors. Distributed Cognition Artifacts on Clinical Research Data Collection Forms Medical record abstraction, a primary mode of data collection in secondary data use, is associated with high error rates. Distributed cognition in medical record abstraction has not been studied as a possible explanation for abstraction errors. We employed the theory of distributed representation and representational analysis to systematically evaluate cognitive demands in medical record abstraction and the extent of external cognitive support employed in a sample of clinical research data collection forms. We show that the cognitive load required for abstraction in 61% of the sampled data elements was high, exceedingly so in 9%. Further, the data collection forms did not support external cognition for the most complex data elements. High working memory demands are a possible explanation for the association of data errors with data elements requiring abstractor interpretation, comparison, mapping or calculation. The representational analysis used here can be used to identify data elements with high cognitive demands.