PP19.009 Simplifying serious illness communication with the preparing or deciding (POD) model
Bibliographic record
Abstract
Background/Methods For the setting of serious illness communication, there continues to be variable understandings of, and definitions used, for the terms advance care planning (ACP) and goals of care discussions. Aiming to clarify as well as improve serious illness communication, consensus definitions along with several education resources, programs and quality improvement interventions have been developed. Our collective experience however is that confusion regarding these communication tasks persists. As more people are living with serious illnesses, the need to provide clear guidance to clinicians grows increasingly urgent. Results The Preparing or Deciding (POD) Model is a framework that helps clinicians understand the overall purpose, tasks, specific outcomes and their role in serious illness communication. It posits that at a high level, conversations with seriously ill people are about either preparing or deciding. In practice, during any interaction involving serious illness, a clinician asks themselves: Is a treatment or care decision needed? If yes, conversational approaches that support decision-making processes are needed. If no, focus is on preparing patients and families for progressing illness and future decision-making. The POD Model frames preparing or deciding as mutually exclusive, contrasting many clinicians who conflate the two and rely on ACP (preparing) for decision-making about interventions that may or may not be offered. This approach is ineffective; advance directives frequently fail to guide decision-making or improve the delivery of goal-consistent care. Despite jurisdictional differences in clinical and legal frameworks that support serious illness decision making, the POD Model applies universally, is applicable in every care setting and to all healthcare practitioners. Discussion The POD Model guides clinicians to support decision-making when appropriate, and otherwise understand that conversations addressing serious illness are to prepare. When clinicians better understand their role in serious illness communication, individuals and systems can more effectively move improvement efforts forward.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.136 | 0.056 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".