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Background There is increased interest among oncology and palliative professionals in providing appropriately timed hospice services for cancer patients. End of life (EoL) metrics have been included in oncology quality programs, but accurate EoL data and benchmarks are hard to obtain.
Objective To improve EoL care by measuring patterns of care among recently deceased patients.
Methods Care utilization among deceased patients was analyzed by using software integrated with patient electronic health records. The data was verified by chart review.
Results Of 179 cancer deaths, tumor registry data differed from chart review in 7% of cases with regard to dates and/or location of death. Institutional EoL metrics were significantly affected by a large number of patients (37%) with advanced illnesses who had clinical diagnoses of cancer made at the end of life, but who had not been managed by oncologists. This population of patients who had not been managed by oncologists was older, less likely to use hospice, and more likely to use the intensive care unit than were oncologist-managed cancer patients. Among the patients of individual oncologists, the median stay in hospice ranged from 6-28 days. Data collection and chart review took an average of 27 minutes per case with combined efforts by a data analyst and oncology practitioner.
Limitations Single institution with comprehensive electronic medical record; some patients were treated outside of the system.
Conclusion Acquiring accurate data on EoL metrics is time consuming. Compared with chart review, other data sources have inaccuracies and include some patients who have not been managed by oncologists. Accurate attribution to individual physicians requires chart review by an experienced clinician.
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Background There is increased interest among oncology and palliative professionals in providing appropriately timed hospice services for cancer patients. End of life (EoL) metrics have been included in oncology quality programs, but accurate EoL data and benchmarks are hard to obtain.
Objective To improve EoL care by measuring patterns of care among recently deceased patients.
Methods Care utilization among deceased patients was analyzed by using software integrated with patient electronic health records. The data was verified by chart review.
Results Of 179 cancer deaths, tumor registry data differed from chart review in 7% of cases with regard to dates and/or location of death. Institutional EoL metrics were significantly affected by a large number of patients (37%) with advanced illnesses who had clinical diagnoses of cancer made at the end of life, but who had not been managed by oncologists. This population of patients who had not been managed by oncologists was older, less likely to use hospice, and more likely to use the intensive care unit than were oncologist-managed cancer patients. Among the patients of individual oncologists, the median stay in hospice ranged from 6-28 days. Data collection and chart review took an average of 27 minutes per case with combined efforts by a data analyst and oncology practitioner.
Limitations Single institution with comprehensive electronic medical record; some patients were treated outside of the system.
Conclusion Acquiring accurate data on EoL metrics is time consuming. Compared with chart review, other data sources have inaccuracies and include some patients who have not been managed by oncologists. Accurate attribution to individual physicians requires chart review by an experienced clinician.
Click on the PDF icon at the top of this introduction to read the full article.
Background There is increased interest among oncology and palliative professionals in providing appropriately timed hospice services for cancer patients. End of life (EoL) metrics have been included in oncology quality programs, but accurate EoL data and benchmarks are hard to obtain.
Objective To improve EoL care by measuring patterns of care among recently deceased patients.
Methods Care utilization among deceased patients was analyzed by using software integrated with patient electronic health records. The data was verified by chart review.
Results Of 179 cancer deaths, tumor registry data differed from chart review in 7% of cases with regard to dates and/or location of death. Institutional EoL metrics were significantly affected by a large number of patients (37%) with advanced illnesses who had clinical diagnoses of cancer made at the end of life, but who had not been managed by oncologists. This population of patients who had not been managed by oncologists was older, less likely to use hospice, and more likely to use the intensive care unit than were oncologist-managed cancer patients. Among the patients of individual oncologists, the median stay in hospice ranged from 6-28 days. Data collection and chart review took an average of 27 minutes per case with combined efforts by a data analyst and oncology practitioner.
Limitations Single institution with comprehensive electronic medical record; some patients were treated outside of the system.
Conclusion Acquiring accurate data on EoL metrics is time consuming. Compared with chart review, other data sources have inaccuracies and include some patients who have not been managed by oncologists. Accurate attribution to individual physicians requires chart review by an experienced clinician.
Click on the PDF icon at the top of this introduction to read the full article.