title: Initial Development of a Computer Algorithm to Identify Patients With Breast and Lung Cancer Having Poor Prognosis in a Safety Net Hospital.
abstract: BACKGROUND
  Physicians often have difficulty with prognostication and identification of patients who are in need of counseling about options for care at the end of life. Consequently, the objective of this study was to describe the initial stages in development of a computerized algorithm that will identify breast and lung cancer patients most in need of counseling about care options, including advance care planning, palliative care, and hospice.
  
  
  METHODS
  Clinical and non-clinical data were extracted from the electronic medical record of breast and lung cancer patients admitted to a large, urban hospital for the year 2010. These data were used to create an electronic (e-EOL) algorithm designed to identify advanced cancer patients who could benefit from in-depth discussion about end-of-life care options.
  
  
  RESULTS
  There were 369 eligible breast (42%) and lung (58%) cancer patients identified by ICD-9 code. The e-EOL algorithm identified 53 (14%) patients that met assigned criteria (presence of metastatic disease and albumin < 2.5 g/dl). The sensitivity, specificity, and positive predictive value of the first generation algorithm were 21%, 96%, and 91% when compared to physician expert chart review. Survival analysis showed that 6-month survival for algorithm positive cases was 46% versus 78% for algorithm negative cases, and 1-year survival was 32% versus 72%, respectively.
  
  
  CONCLUSIONS
  Initial testing of the e-EOL algorithm appears to be promising. Other markers of advanced illness will added to the algorithm to improve its test operating characteristics so it may be used to identify patients with poor prognosis in real time.
authors.affiliation: Division of Geriatric Medicine, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA ramona.rhodes@utsouthwestern.edu.
authors.forename: Ramona L
authors.initials: RL
authors.lastname: Rhodes
authors.affiliation: Department of Medicine, Weill Cornell Medical College, New York, NY, USA.
authors.forename: Sabiha
authors.initials: S
authors.lastname: Kazi
authors.affiliation: Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA.
authors.forename: Lei
authors.initials: L
authors.lastname: Xuan
authors.affiliation: Parkland Center for Clinical Innovation, Dallas, TX, USA Division of General Internal Medicine, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA.
authors.forename: Ruben
authors.initials: R
authors.lastname: Amarasingham
authors.affiliation: Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA Division of General Internal Medicine, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA.
authors.forename: Ethan A
authors.initials: EA
authors.lastname: Halm
mesh_terms: D032722:Advance Care Planning / Q000458:organization & administration; D000465:Algorithms; D001943:Breast Neoplasms / Q000503:physiopathology* / Q000628:therapy; D003658:Decision Making, Computer-Assisted; D057286:Electronic Health Records; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data; D017051:Hospice Care / Q000458:organization & administration; D006760:Hospitalization / Q000706:statistics & numerical data; D006786:Hospitals, Urban; D006801:Humans; D008175:Lung Neoplasms / Q000503:physiopathology* / Q000628:therapy; D008297:Male; D008875:Middle Aged; D010166:Palliative Care / Q000458:organization & administration; D011237:Predictive Value of Tests; D011379:Prognosis; D064876:Safety-net Providers / Q000706:statistics & numerical data*; D012709:Serum Albumin; D012959:Socioeconomic Factors; D016019:Survival Analysis; D013727:Terminal Care
chemical_list: D012709:Serum Albumin
keywords: cancer; electronic medical record; end-of-life care; health information technology; palliative care; prognosis; safety net