PubMed Health⌕ Search

PubMed · 3410834

Data omitted from psychiatric consultation notes.

Abstract

To assess how often psychiatric consultants omit written data from their consultation notes, the authors reviewed 78 initial consultation notes written by second-year psychiatric residents. Data considered essential for an adequate psychiatric evaluation were typically omitted. Categories that were observed to have the highest frequencies of missing data included family history of psychiatric illness (60.3%), history of substance abuse (44.9%), marital status (37.2%), previous psychotropic drug use (35.9%), previous psychiatric treatment (26.9%), and patient history of psychiatric illness (24.4%). The frequencies of omissions were significantly (p less than .001, except for the last item, p less than .01) higher than those from the consultation notes written by a second cohort of psychiatric residents who used a worksheet that listed data categories. The authors' findings argue for the use of worksheets delineating data categories to ensure that clinicians write adequate consultation notes.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

G W Small, F I Fawzy. 1988. Data omitted from psychiatric consultation notes.. https://pubmed.ncbi.nlm.nih.gov/3410834/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Probability estimation when some observations are grouped.

This paper considers the use of additional questions for decreasing survey non-response rates and an approach for estimating a probability based on the results obtained. In a survey, the respondents are asked to answer an original question and follow-up questions, where the answers for the follow-up questions are grouped answers for the original question. For example, respondents are asked to provide an exact number of incidents, but in cases of 'Do not know' or 'Refuse' responses, they are subsequently asked to pick an answer from a less specific categorical scale. The new estimator obtains smaller variance asymptotically and does not depend on a distribution family. This method is applied to income questions in a survey regarding injury prevention and behaviours. Another application is survey data on intimate partner violence, where some amendments were applied for incorporating post-stratification weights and for using non-random grouping. For additional illustration, an example of parameter estimation on artificially generated data is presented.

Data Collection↗