ArticleThe American journal of hospice & palliative care2016
Initial Development of a Computer Algorithm to Identify Patients With Breast and Lung Cancer Having Poor Prognosis in a Safety Net Hospital.
Article in The American journal of hospice & palliative care, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Do Patient-Centered Medical Homes Improve Health Behaviors, Outcomes, and Experiences of Low-Income Patients? A Systematic Review and Meta-Analysis.Health services research · 2018Pooled it
- Understanding Underuse of Advance Care Planning Among a Cohort of African American Patients With Advanced Cancer: Formative Research That Examines Gaps in Intent to Discuss Options for Care.The American journal of hospice & palliative care · 2019Article
- Examining the Association between Healthcare Utilization and Clinical Characteristics among Cancer Patients in a Safety Net Health System.Journal of palliative medicine · 2019Article
- A systematic review of the use of the electronic health record for patient identification, communication, and clinical support in palliative care.JAMIA open · 2018Article
- Predictors of Placement of Inpatient Palliative Care Consult Orders Among Patients With Breast, Lung, and Colon Cancer in a Safety Net Hospital System.The American journal of hospice & palliative care · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
backgroundPhysicians 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.
methodsClinical 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.
resultsThere 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.
conclusionsInitial 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.