Pattern of prescribing psychotropics in the outpatient department of a tertiary psychiatric hospital
Bibliographic record
Abstract
Pattern of prescriptions for psychiatric patients varies which is influenced by patient variation, types of disorders, cultural and environmental influences, socioeconomic status, availability of drugs and psychiatrists own preference. The aim of this study was to determine the patterns of prescribing psychotropic drugs in psychiatry Outpatient Department (OPD) in a tertiary care hospital. The cross-sectional study was conducted in the OPD of National Institute of Mental Health (NIMH), Dhaka from January to June, 2016. In the study, the prescriptions prescribed by psychiatrists were considered as study population. Using convenient sampling method, data were collected by observation using checklist from selected 604 latest prescriptions prescribed by psychiatrists in OPD of NIMH for the patients coming there for treatment. The data on the psychotropic drugs collected for the study were antipsychotics, antidepressants, mood stabilizers and sedative-hypnotics. Results showed that a total of 1802 psychotropic drugs were prescribed with an average of 2.98 psychotropics per prescription. The most common drug group prescribed was antipsychotics (44.8%). Majority (49.7%) of the prescriptions contained 3 psychotropics simultaneously. Most common (27.8%) combination was that of antipsychotics and sedativehypnotics. Dosage regimen was twice/day for the majority (55.6%). There was a combination of oral and parenteral drugs in 48.3% of prescriptions. All the drugs were prescribed by brand names. There was no diagnosis written in 60.9% of the prescriptions. The prescription pattern was not rational and this should be intervened by educating prescribers about rational prescribing in psychiatry.Bang J Psychiatry June 2015; 29(1): 10-13
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".