An Internet-Based Method for Extracting Nursing Home Resident Sedative Medication Data From Pharmacy Packing Systems: Descriptive Evaluation

Background: Inappropriate use of sedating medication has been reported in nursing homes for several decades. The ReducingUse of Sedatives (RedUSe) project was designed to address this issue through a combination of audit, feedback, staff education,and medication review. The project significantly reduced sedative use in a controlled trial of 25 Tasmanian nursing homes. Toexpand the project to 150 nursing homes across Australia, an improved and scalable method of data collection was required. Thispaper describes and evaluates a method for remotely extracting, transforming, and validating electronic resident and medicationdata from community pharmacies supplying medications to nursing homes.Objective: The aim of this study was to develop and evaluate an electronic method for extracting and enriching data onpsychotropic medication use in nursing homes, on a national scale.Methods: An application uploaded resident details and medication data from computerized medication packing systems in thepharmacies supplying participating nursing homes. The server converted medication codes used by the packing systems toAustralian Medicines Terminology coding and subsequently to Anatomical Therapeutic Chemical (ATC) codes for grouping.Medications of interest, in this case antipsychotics and benzodiazepines, were automatically identified and quantified during theupload. This data was then validated on the Web by project staff and a “champion nurse” at the participating home.Results: Of participating nursing homes, 94.6% (142/150) had resident and medication records uploaded. Facilitating an uploadfor one pharmacy took an average of 15 min. A total of 17,722 resident profiles were extracted, representing 95.6% (17,722/18,537)of the homes’ residents. For these, 546,535 medication records were extracted, of which, 28,053 were identified as antipsychoticsor benzodiazepines. Of these, 8.17% (2291/28,053) were modified during validation and verification stages, and 4.75%(1398/29,451) were added. The champion nurse required a mean of 33 min website interaction to verify data, compared with 60min for manual data entry.Conclusions: The results show that the electronic data collection process is accurate: 95.25% (28,053/29,451) of sedativemedications being taken by residents were identified and, of those, 91.83% (25,762/28,053) were correct without any manualintervention. The process worked effectively for nearly all homes. Although the pharmacy packing systems contain some invalidpatient records, and data is sometimes incorrectly recorded, validation steps can overcome these problems and provide sufficientlyaccurate data for the purposes of reporting medication use in individual nursing homes