The DACRIN data project: A process for harmonising data collection for clinical research in alcohol and other drugs services in New South Wales.

INTRODUCTION: Standardised data collection processes allow for harmonisation and comparison of data across different studies and services. This project aimed to develop a 'core dataset' to serve as the default collection when designing future studies and evaluations, building upon data routinely collected in clinical alcohol and other drugs (AOD) settings in NSW, Australia. METHODS: A working group was established, comprising clinicians, researchers, data managers and consumers from public sector and non-government organisation AOD services in the NSW Drug and Alcohol Clinical Research and Improvement Network. A series of Delphi meetings occurred to reach consensus on the data items to be included in the core dataset for three domains: demographics, treatment activity and substance use variables. RESULTS: There were 20-40 attendees at each meeting. An initial consensus criterion of having received >70% of the vote was established. Given the difficulty in reaching consensus for most items, subsequently, this was changed to eliminate items that received <5 votes, after which the item receiving the most votes would be selected. DISCUSSIONS AND CONCLUSIONS: This important process received considerable interest and buy-in across the NSW AOD sector. Ample opportunity for discussion and voting was provided for the three domains of interest, allowing participants to contribute their expertise and experience to inform decisions. As such, we believe the core dataset includes the best options currently available to collect data for these domains in the NSW AOD context, and potentially more broadly. This foundational study may inform other attempts to harmonise data across AOD services.

Trend in data errors after the implementation of an electronic medical record system: A longitudinal study in an Australian regional Drug and Alcohol Service.

OBJECTIVES: To investigate trends in data errors over the 40 months after the implementation of an electronic medical record (eMR) system in an Australian regional Drug and Alcohol (D&A) Service. METHODS: One hundred and twenty three error reports and data on occasions of service were obtained from the D&A Service. Statistical analysis was conducted to describe types of errors, to compare distribution of error types among different documentation forms, D&A Service sites and job roles. Error rates were also analysed. RESULTS: In the 40 months after the implementation, a total of 18,549 errors occurred. These errors were grouped into four types: mismatched data fields (54.5 %), duplicate medical record (1.8 %), date/time error (8.2 %) and blank field (35.4 %). The distribution of error types differed in the forms being completed, the sites and the job roles. Quarterly error rate increased from 28.8 errors per 100 occasions of service in Year 1 Quarter 1-40.6 in Quarter 3, then decreased to 18.1 in Quarter 4. It dropped to 6.6 in Year 2 Quarter 2 and continued to decrease to 2.5 in Year 4 Quarter 1. Monthly error rate was the highest at 44.6 in Month 8, fell to the lowest at 1.0 in Month 18 and remained at under 7.3 from Month 19 to Month 40. CONCLUSIONS: After the implementation of the eMR system, the error rate increased in the first three quarters before decreasing. It reached stability about one and a half years after implementation. There were significant differences in the error distribution among the documentation forms, sites and job roles. The findings of this study could be used by eMR trainers to tailor training sessions for specific sites and job roles. These findings might also be useful for managers of other D&A Services to plan for the implementation of new electronic documentation systems.