Systematic identification of metastatic population subsets for advance care planning (ACP) discussions: A scalable approach using electronic health record (EHR) technology
| Autor: | Cynthia Taniguchi, Susan Ash-Lee, Kevin Donald Olson, Deb Harrison, Sabrina Q. Mikan, J. Russell Hoverman, Aimee Ginsburg Arlen |
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| Rok vydání: | 2013 |
| Předmět: |
Advance care planning
Cancer Research medicine.medical_specialty education.field_of_study Service (systems architecture) Pathology business.industry Population Alternative medicine Context (language use) Oncology Data extraction Family medicine Health care Medicine business education End-of-life care |
| Zdroj: | Journal of Clinical Oncology. 31:243-243 |
| ISSN: | 1527-7755 0732-183X |
| DOI: | 10.1200/jco.2013.31.31_suppl.243 |
| Popis: | 243 Background: Comprehensive cancer care embraces the concept of having timely discussions with patients about end of life care preferences regarding treatment interventions. Physicians and healthcare teams are frequently challenged with identifying patients who are clinically appropriate for these discussions and subsequent management of ACP work within the context of clinic resource capacity. A data extraction process is needed to systematically identify cancer population subsets for ACP based on clinical data elements maintained within an EHR database. Methods: Seven cancer center sites of service participated in a 90-day pilot study for delivering ACP services to discrete patient populations who it was believed would most benefit from ACP. Electronic methodology was developed and tested through the pilot process to systematically identify those patients having documented evidence of designated clinical criteria, including metastatic disease status. Metastatic status was determined using five clinical data elements. EHR technology enabled further targeting by cancer diagnoses and allowed this program to be scalable to individual practice capacity. Additional filtering capability was incorporated to exclude non-applicable patient records. Results: On a weekly basis, each pilot site received a report of eligible patients based on clinical criteria and practice-specific diagnoses. During the 90-day pilot period, sites collectively identified an average of 871 patients per week who met clinically-based selection criteria. Once a patient was identified, physicians were able to determine if the patient was appropriate for ACP introduction. The systematic patient identification process allowed ACP to be easily integrated into mainstream practice workflow. Conclusions: EHR technology is invaluable for strategically identifying cancer patient population subsets for clinically appropriate delivery of ACP services. Automated notification of eligible patients and the ability to filter the population enabled practices to engage the ACP process wholly within the scope of comprehensive cancer care delivery. |
| Databáze: | OpenAIRE |
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