PubMed · 9534598
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A Morel. 1997. [Computerizing a documentation center].. https://pubmed.ncbi.nlm.nih.gov/9534598/
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BACKGROUND: Hospital discharge summaries communicate information necessary for continuing patient care. They are most commonly generated by voice dictation and are often of poor quality. The objective of this study was to compare discharge summaries created by voice dictation with those generated from a clinical database. METHODS: A randomized clinical trial was performed in which discharge summaries for patients discharged from a general internal medicine service at a tertiary care teaching hospital in Ottawa were created by voice dictation (151 patients) or from a database (142 patients). Patients had been admitted between September 1996 and June 1997. The trial was preceded by a baseline cohort study in which all summaries were created by dictation. For the database group, information on forms completed by housestaff was entered into a database and collated into a discharge summary. For the dictation group, housestaff dictated narrative letters. The proportion of patients for whom a summary was generated within 4 weeks of discharge was recorded. Physicians receiving the summary rated its quality, completeness, organization and timeliness on a 100-mm visual analogue scale. Housestaff preference was also determined. RESULTS: Patients in the database group and the dictation group were similar. A summary was much more likely to be generated within 4 weeks of discharge for patients in the database group than for those in the dictation group (113 [79.6%] v. 86 [57.0%]; p < 0.001). Summary quality was similar (mean rating 72.7 [standard deviation (SD) 19.3] v. 74.9 [SD 16.6]), as were assessments of completeness (73.4 [SD 19.8] v. 78.2 [SD 14.9]), organization (77.4 [SD 16.3] v. 79.3 [SD 17.2]) and timeliness (70.3 [SD 21.9] v. 66.2 [SD 25.6]). Many information items of interest were more likely to be included in the database-generated summaries. The database system created summaries faster and was preferred by housestaff. Dictated summaries in the baseline and randomized studies were similar, which indicated that the control group was not substantially different from the baseline cohort. INTERPRETATION: The database system significantly increased the likelihood that a discharge summary was created. Housestaff preferred the database system for summary generation. Physicians thought that the quality of summaries generated by the 2 methods was similar. The use of computer databases to create hospital discharge summaries is promising and merits further study and refinement.
The availability of large, population-based, automated, medical care databases provides unique opportunities for monitoring the safety of childhood vaccines. The authors assessed the quality of automated vaccination databases by comparing them with vaccinations documented in paper-based medical records at three large US West Coast health maintenance organizations (HMOs) participating in the Vaccine Safety DataLink (VSD) study, a Centers for Disease Control and Prevention collaborative study of childhood vaccine safety. The authors randomly selected 1% or 2% samples of VSD study populations (n = 1,224-2,577) for data quality analyses. Agreement between automated and abstracted vaccinations required identical triads of child identification number, vaccination date, and vaccine type. Separate analyses were conducted for each HMO and for each vaccine type administered between 1991 and 1995. Agreement was measured by three matching proportions: 1) the proportion of automated vaccinations present in the abstracted source, 2) the proportion of abstracted vaccinations present in the automated source, and 3) the proportion of vaccinations from either source present in both sources. Overall, for common childhood vaccines, proportion 1 ranged from 83% to 99%, proportion 2 ranged from 82% to 98%, and proportion 3 ranged from 70% to 97%. Lack of automated data was the most frequent type of discrepancy, followed by date mismatches and vaccine type mismatches. Vaccination exposure classification errors in the range reported here were found by mathematical modeling to only modestly bias measured medical outcome rate ratios toward the null hypothesis. The results of the data quality analyses support the usefulness of vaccination exposure data derived from these automated HMO vaccination databases.
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