Patient-Reported Outcomes and Total Health Care Expenditure in Prediction of Patient Satisfaction: Results From a National Study
Bibliographic record
Abstract
BACKGROUND: Health care quality is often linked to patient satisfaction. Yet, there is a lack of national studies examining the relationship between patient satisfaction, patient-reported outcomes, and medical expenditure. OBJECTIVE: The aim of this study is to examine the contribution of physical health, mental health, general health, and total health care expenditures to patient satisfaction using a longitudinal, nationally representative sample. METHODS: Using data from the 2010-2011 Medical Expenditure Panel Survey, analyses were conducted to predict patient satisfaction from patient-reported outcomes and total health care expenditures. The study sample consisted of adult participants (N=10,157), with sampling weights representative of 233.26 million people in the United States. RESULTS: The results indicated that patient-reported outcomes and total health care expenditure were associated with patient satisfaction such that higher physical and mental function, higher general health status, and higher total health care expenditure were associated with higher patient satisfaction. CONCLUSIONS: We found that patient-reported outcomes and total health care expenditure had a significant relationship with patient satisfaction. As more emphasis is placed on health care value and quality, this area of research will become increasingly needed and critical questions should be asked about what we value in health care and whether we can find a balance between patient satisfaction, outcomes, and expenditures. Future research should apply big data analytics to investigate whether there is a differential effect of patient-reported outcomes and medical expenditures on patient satisfaction across different medical specialties.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".