Patient centricity: lip service or genuine commitment? A qualitative examination of the pharmaceutical industry
Bibliographic record
Abstract
Purpose The purpose of this study is two-fold: first, to identify the degree of adoption of patient centricity in the pharmaceutical industry and second, to understand how the industry operationalizes this strategy. It is an important shift in the industry because of its central focus on the patient. Design/methodology/approach A content analysis was used based on publicly available documentation that includes industry publications, company and brand websites and clinical trial publications to identify the frequency of words used to describe patient centricity. Findings The key finding of this study is that the leading pharmaceutical firms overwhelmingly use patient support/access programs as the primary method of implementing patient centric strategies. Research limitations/implications Future research is needed to identify what impact these strategies have on patients; and whether or not these strategies have an impact on lowering drug prices and improved clinical outcomes for patients. Practical implications Future research is needed to identify what impact these strategies have on patients; and whether or not these strategies have an impact on lowering drug prices and improved clinical outcomes for patients. Limitations include the reliance on publicly available documentation. Social implications Pharmaceutical firms need to be aware that their publically available profile suggests a one-dimensional approach to patient centricity and this may influence the way patients, physicians and policymakers view their attitudes toward patients. This study is the first to systematically examine the activities of leading pharmaceutical firms with respect to the adoption and implementation of patient-centric strategies in a comprehensive fashion. Originality/value This study is the first to systematically examine the activities of leading pharmaceutical firms with respect to the adoption and implementation of patient-centric strategies in a comprehensive fashion.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".