Quality from the Patient’s Perspective: Implementation of an Established Patient-Reported Outcome Platform in a Multidisciplinary Skull Base Tumor Clinic
Bibliographic record
Abstract
Background: Utilization of patient-reported outcomes (PROs) in clinical care for skull base tumor patients treated in a multidisciplinary management team has been proposed to focus on outcomes most important to patients and to enhance shared decision making. Specific options for treatment, including endoscopic and open surgery as well as chemoradiation have both acute and long-term sequelae. Identification of how these treatments impact the individual patient has implications for both quality of care and the value of the treatment provided. Objective: The aim of the study is to assess the ability to implement real time PROs on an electronic platform within a multidisciplinary skull base clinic. Methods: Descriptive analysis of implementation of PROs for the skull base tumor program at a cancer center is given. Two validated instruments, the Skull Base Inventory (SBI), developed at the Princess Margaret Cancer Center, Toronto, CA and/or Head and Neck Patient Reported Outcomes (HNPROs) developed at Memorial Sloan Kettering Cancer Center, NY, NY were administered at baseline, after intervention, and at follow-up visits. All patients treated for sinonasal, pituitary, or anterior skull base pathology are eligible for electronic PROs assessment as a part of standard of care within a larger initiative of the Head and Neck Service at MSKCC. Results: Since July 2018, patients with pituitary, nasal cavity, and ethmoid pathology have received the SBI and those with malignancies of the maxillary sinus (or other head and neck malignancy) received the HNPROs. Automatic “time out” information technology settings prevent delivery of duplicate surveys. ICD-10 diagnosis codes were used to allow for domain-specific questionnaires based on the specific subsites. For example, a patient with a diagnosis of maxillary sinus cancer will receive questions that include inquiry about numbness, rhinorrhea, epiphora, vision, facial appearance, and cancer worry. Graphical reports provide representation of domains over time. From July 1, 2018 to July 1, 2019, 91 of 124 possible patients with anterior skull base pathology have submitted surveys within a broader context of 2,723 of 3,758 head and neck cancer (nonthyroid) patients having submitted surveys. A total of 76% completed the module on the institutional patient portal and 24% completed on a tablet at the time of physician visit. Median time to completion was 5 minutes. Conclusion: Integration of electronic sinonasal, pituitary, and skull base PROs as part of a multidisciplinary management team is feasible. This has the potential to provide important patient-specific data that can educate patient and clinician alike and assist in decision making. Over time, normative data can be gleaned to demonstrate what a large population of patients have experienced at different time points when pursuing specific treatment options. This can ultimately improve the quality of care and value provided per intervention.
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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 | 0.076 | 0.109 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".