Development and Initial Evaluation
INTRODUCTION
Documentation of clinical activities in patients’ medical records is an essential practice standard for pharmacists. This practice facilitates communication and assessment of interventions by health care peers and helps to ensure optimal patient care. In addition, this information can be used to help pharmacists improve their clinical practices through peer mentoring, allows qualitative assessment of interventions, and can be used as an educational tool for staff.
The information contained in medical record notes is rarely usable by external pharmacy stakeholders, such as hospital administrators. Therefore, an alternative source of information about clinical workload and health outcomes is required to demonstrate the effects of pharmacists’ involvement in patient care. Workload measurement systems have traditionally been used for assessing staffing levels, justifying clinical activities, and assessing impacts on patient outcomes. Unfortunately, many workload-measurement systems are inefficient, poorly utilized, and cumbersome to interpret. An ideal system for measuring the productivity of clinical pharmacists would be seamless, paperless, linked to patient outcomes, benchmarked to “best practices”, and weighted to account for patient acuity and the difficulty of different tasks.
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The David Thompson Health Region covers a large geographic region (60 000 km2) in central Alberta and serves approximately 300 000 people. It comprises 17 rural hospitals, a regional psychiatry hospital, and a referral community hospital. The referral hospital employs 18.1 full-time equivalent pharmacists for 350 acute care and 200 continuing care beds. At present, this health region maintains paper-based patient medical records but is participating in a provincial initiative to implement a standard computer system (developed and distributed by Meditech) to facilitate the sharing of pharmacy data, diagnostic information, and laboratory results among users in Alberta. Within that system, a computerized pharmacy documentation and workload measurement system has been developed to facilitate communication of pharmacists’ direct patient care activities to their colleagues and other health care professionals and to allow clinical workload quantification that is easy for pharmacists to perform and for administrators to interpret. Using the workload measurement system, pharmacists log their interventions numerically while they are creating electronic and hard-copy medical record notes. The pharmacists previously used a paper-based system for workload measurement, with the documentation being compiled by the health records department. However, the paper system was time-consuming, was used inconsistently by different pharmacists, was only available at the referral hospital, and resulted in a significant (6- to 18-month) delay in the reporting of workload results from health records.
In this article, we describe the new system for measuring pharmacist workload associated with patient care, which accompanies medical record documentation. We also describe quantitatively and qualitatively the interventions performed by pharmacists in the region’s community referral hospital, as well as the potential outcomes of the interventions. We hypothesized that implementation of an electronic workload measurement system would capture pharmacist interventions and their anticipated impact on patient outcomes. The primary objective of our study was to determine, using the workload measurement system, the number of interventions by staff pharmacists over a 6-month period (January to June 2006). The secondary objectives were to calculate the number of interventions per clinical shift for each pharmacist, to determine if residency training and years of work experience affected the number of drug-related problems (DRPs) reported, to quantify the nature of the interventions according to the category of DRP, to quantify the anticipated outcomes, and to determine the proportions of suggested interventions that were accepted and rejected by physicians. We also calculated the average number of anticipated outcomes per suggested intervention.
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