Background and objective The clinical note documents the clinician's information collection, problem assessment, clinical management, and its used for administrative purposes. Electronic health records (EHRs) are being implemented in clinical practices throughout the USA yet it is not known whether they improve the quality of clinical notes. The goal in this study was to determine if EHRs improve the quality of outpatient clinical notes.Materials and methods A five and a half year longitudinal retrospective multicenter quantitative study comparing the quality of handwritten and electronic outpatient clinical visit notes for 100 patients with type 2 diabetes at three time points: 6 months prior to the introduction of the EHR (before-EHR), 6 months after the introduction of the EHR (after-EHR), and 5 years after the introduction of the EHR (5-year-EHR). QNOTE, a validated quantitative instrument, was used to assess the quality of outpatient clinical notes. Its scores can range from a low of 0 to a high of 100. Sixteen primary care physicians with active practices used QNOTE to determine the quality of the 300 patient notes.Results The before-EHR, after-EHR, and 5-year-EHR grand mean scores (SD) were 52.0 (18.4), 61.2 (16.3), and 80.4 (8.9), respectively, and the change in scores for before-EHR to after-EHR and before-EHR to 5-year-EHR were 18% (p<0.0001) and 55% (p<0.0001), respectively. All the element and grand mean quality scores significantly improved over the 5-year time interval.Conclusions The EHR significantly improved the overall quality of the outpatient clinical note and the quality of all its elements, including the core and non-core elements. To our knowledge, this is the first study to demonstrate that the EHR significantly improves the quality of clinical notes.
Background and objectiveThe outpatient clinical note documents the clinician's information collection, problem assessment, and patient management, yet there is currently no validated instrument to measure the quality of the electronic clinical note. This study evaluated the validity of the QNOTE instrument, which assesses 12 elements in the clinical note, for measuring the quality of clinical notes. It also compared its performance with a global instrument that assesses the clinical note as a whole.Materials and methodsRetrospective multicenter blinded study of the clinical notes of 100 outpatients with type 2 diabetes mellitus who had been seen in clinic on at least three occasions. The 300 notes were rated by eight general internal medicine and eight family medicine practicing physicians. The QNOTE instrument scored the quality of the note as the sum of a set of 12 note element scores, and its inter-rater agreement was measured by the intraclass correlation coefficient. The Global instrument scored the note in its entirety, and its inter-rater agreement was measured by the Fleiss κ.ResultsThe overall QNOTE inter-rater agreement was 0.82 (CI 0.80 to 0.84), and its note quality score was 65 (CI 64 to 66). The Global inter-rater agreement was 0.24 (CI 0.19 to 0.29), and its note quality score was 52 (CI 49 to 55). The QNOTE quality scores were consistent, and the overall QNOTE score was significantly higher than the overall Global score (p=0.04).ConclusionsWe found the QNOTE to be a valid instrument for evaluating the quality of electronic clinical notes, and its performance was superior to that of the Global instrument.
BackgroundThe inability of patients to accurately and completely recount their clinical status between clinic visits reduces the clinician’s ability to properly manage their patients. One way to improve this situation is to collect objective patient information while the patients are at home and display the collected multi-day clinical information in parallel on a single screen, highlighting threshold violations for each channel, and allowing the viewer to drill down to any analog signal on the same screen, while maintaining the overall physiological context of the patient. All this would be accomplished in a way that was easy for the clinician to view and use.MethodsPatients used five mobile devices to collect six heart failure-related clinical variables: body weight, systolic and diastolic blood pressure, pulse rate, blood oxygen saturation, physical activity, and subjective input. Fourteen clinicians practicing in a heart failure clinic rated the display using the System Usability Scale that, for acceptability, had an expected mean of 68 (SD, 12.5). In addition, we calculated the Intraclass Correlation Coefficient of the clinician responses using a two-way, mixed effects model, ICC (3,1).ResultsWe developed a single-screen temporal hierarchical display (VISION) that summarizes the patient’s home monitoring activities between clinic visits. The overall System Usability Scale score was 92 (95% CI, 87-97), p < 0.0001; the ICC was 0.89 (CI, 0.79-0.97), p < 0.0001.ConclusionClinicians consistently found VISION to be highly usable. To our knowledge, this is the first single-screen, parallel variable, temporal hierarchical display of both continuous and discrete information acquired by patients at home between clinic visits that presents clinically significant information at the point of care in a manner that is usable by clinicians.
AbsTrAcTbackground A major justification for the clinical adoption of electronic health records (EHRs) was the expectation that it would improve the quality of medical care. No longitudinal study has tested this assumption. Objective We used hemoglobin A1c, a recognized clinical quality measure directly related to diabetes outcomes, to assess the effect of EHR use on clinical quality. Methods We performed a five-and-one-half-year multicentre longitudinal retrospective study of the A1c values of 537 type 2 diabetic patients. The same patients had to have been seen on at least three occasions: once approximately six months prior to EHR adoption (before-EHR), once approximately six months after EHR adoption (after-EHR) and once approximately five years after EHR adoption (five-years), for a total of 1,611 notes. results The overall mean confidence interval (CI) A1c values for the before-EHR, after-EHR and five-years were 7.07 (6.91 -7.23), 7.33 (7.14 -7.52) and 7.19 (7.06 -7.32), respectively. There was a small but significant increase in A1c values between before-EHR and after-EHR, p = .04; there were no other significant differences. There was a significant decrease in notes missing at least one A1c value, from 42% before-EHR to 16% five-years (p < .001). conclusion We found that based on patient's A1c values, EHRs did not improve the clinical quality of diabetic care in six months and five years after EHR adoption. To our knowledge, this is the first longitudinal study to directly assess the relationship between the use of an EHR and clinical quality.
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