Perceptions of the Doctor-Patient Relationship Among Patients in a Private, Secondary-Level Hospital in Southern India
Bibliographic record
Abstract
Introduction An epidemic of non-communicable diseases (NCDs) in India is fueling a growing demand for primary care and hospitalization services. Difficulties in coordinating inpatient and outpatient care create significant barriers to providing high-quality medical care. In this paper, we describe patient experiences, perceptions, and expectations of doctor-patient relationships in a secondary-level private hospital in Karnataka, India. Methods We conducted a cross-sectional, mixed-method needs assessment with surveys and in-depth interviews at Dr. TMA Pai Hospital (TMAPH), a secondary-level, private sector hospital in Karnataka, India. Inclusion criteria included all adults over 18 years old hospitalized at TMAPH in the past year. Patients were consecutively recruited from August 2019-October 2019 and asked to rate aspects of their relationship with their primary care provider (PCP). Descriptive statistics and multivariable logistic regression were used to analyze predictors of the doctor-patient relationship. Patients were interviewed regarding their perceptions of care coordination and doctor-patient relationships. General Thematic Analysis was utilized to analyze qualitative data and develop themes. Quantitative and qualitative findings were then merged to interpret the various dimensions of doctor-patient relationships. Results A total of 150 patients (47.3% male) enrolled. Ten patients underwent qualitative interviews. The median patient age was 67 years (IQR 56–76). 112 (74.7%) of patients identified a PCP either at or outside of TMAPH. 89% had diabetes and/or hypertension. Compared to patients without a PCP, having a PCP led to a significantly higher adjusted odds of always spending optimal time with their doctors (aOR 2.7, 95% CI 1.1–6.8, p = 0.04), and always receiving clear instructions on managing their medical conditions (aOR 2.5, 95% CI 1.0–6.1, p = 0.04). The following themes were developed from patient interviews: (1) patients trusted and respected their PCP believing they were receiving high quality care; and (2) despite perceived fragmentation in care, patients spoke favorably of their relationships with their doctors. Conclusions Among a sample of recently hospitalized patients, those with a PCP reported more positive doctor-patient relationships, though rates of dissatisfaction with doctors were still high. Further research and strategies are required to optimize continuity of care and doctor-patient relationships across the entire continuum of outpatient and inpatient care.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".