Continuous training as a key to increase the accuracy of administrative data

Abstract

The aim of this study was to evaluate the impact of a program of training, education and awareness on the accuracy of the data collected from hospital discharge abstracts. Four random samples of hospital discharge abstracts relating to four different periods were studied. The evaluation of the impact of systematic training and education activities was performed by checking the quality of abstracting information from the medical records. The analysis was carried out at the Istituto Dermopatico dell'Immacolata, a research hospital (335 beds) in Rome, Italy, which specializes in dermatology, plastic and vascular surgery. Error rates in discharge abstracts were subdivided into six categories: selection of the wrong principal diagnosis (type A); low specificity of the principal diagnosis (type B); incomplete reporting of secondary diagnoses (type C); selection of the wrong principal procedure (type D); low specificity of the principal procedure (type E); incomplete reporting of procedures (type F). A specific rate for errors modifying classification in diagnosis related groups (DRG) was then estimated and the effect of re-abstracting on the case-mix index evaluated. Error types A, B, C, E and F dropped from 8.5% to 2%, 15.8 to 4.9, 31.8 to 13.1,4.1 to 0.3 and 22 to 2.6%, respectively. Error type D was 0.7 both in the first (the baseline) and fourth periods of analysis. All differences in error types were statistically significant. In 1999 8.3% of cases were assigned to a different DRG after re-abstracting as compared with 24.3% in the third quarter of 1994, 23.8% in the first quarter of 1995 and 5.5% in September-October 1997. Continuous training and feedback of information to departments have shown to be successful in improving the quality of abstracting information at patient level from the medical record. These positive results were facilitated by the introduction of a prospective payment system to finance inpatient hospital activity. The effort to increase administrative data quality at hospital level facilitates the use of those data sets for internal quality management activities.

Coder perspectives on physician-related barriers to producing high-quality administrative data: a qualitative study

“…[11][12][13][14][15][16][17] However, coders constitute only part of the equation in coding quality; their output depends on the quality of the input, which is physician documentation of a patient's course in hospital. As physician researchers, we acknowledge that many of the identified physician-related barriers are structural and systemic, extending beyond the control of physicians alone.…”

“…3,[6][7][8][9][10] Most studies on barriers to coding that result in highquality administrative data have focused on coder-related barriers concerning their training, knowledge and evaluation standards. [11][12][13][14][15][16][17] One barrier that is consistently described by coders is the lack of precise documentation in clinical charts, 1,13,18 which accounts for half of the disagreements in diagnostic codes among coders. 10 Although physicians provide the main sources of chart documentation, the role that they play in determining the quality of coded data remains unknown.…”

The association of the number of comorbidities and complications with length of stay, hospital mortality and LOS high outlier, based on administrative data

“…The peer review organization system for coding behavior and DPC creep will be in demand, just like in other countries that are already Fig. 2 Hospital mortality (per 1,000 cases) and number of comorbidities and complications, stratified by treatment group (medical or surgery) and major diagnostic category utilizing those kinds of case-mix classification systems [16][17][18][19]. Third, there was a limitation of coding slots in the DPC dataset, whereby only seven secondary diagnoses (four comorbidities and three complications) could be listed.…”

Systemic factors of errors in the case identification process of the national routine health information system: A case study of Modified Field Health Services Information System in the Philippines

“…Continuous training is known as an effective method of improving the accuracy of data [30]. However, in low-resource settings, one limitation of a sustainable system operation is the small number of training opportunities [5].…”