Study Design:
This descriptive study will develop and pilot test the tools for a multifaceted intervention to improve prescribing to patients with renal impairment in primary care. These tools include a chart audit tool, development of a group learning session and an electronic clinical decision support tool that will be incorporated into the electronic medical record.
Setting:
This study will be conducted at Stonechurch Family Health Centre, an academic family practice teaching site of McMaster University. Stonechurch Family Health Centre currently provides primary care to about 16,000 patients. There are three interdisciplinary clinical teams that include academic and community family physicians, nurse practitioners, registered nurses, RPNs, a pharmacist, social workers and other professionals. Approximately 9.5% of the patient population is elderly.
Stonechurch Family Health Centre uses the Open Source Clinical Application Resource (OSCAR) system as its electronic medical record (EMR). OSCAR was developed by Dr. David Chan and colleagues and has the benefit of integrating clinical practice with clinical knowledge and delivering necessary tools including pharmaceutical and other clinical reference at the point of care. OSCAR has been used at Stonechurch since April 2002 and the transition from paper chart to electronic records has been successfully completed for all practices within the practice site
Patient Sample Inclusion: Patients over age 65 who have been prescribed one or more of the targeted medications and who have a creatinine from within the previous year on record will be included.
Exclusions: patients on dialysis.
Intervention:
The proposed multifaceted intervention employs a combination of high and low technology strategies. Following a pre-intervention chart audit, personalized feedback about prescribing practices will be provided to prescribers. This data will be used to design a curriculum for a pharmacist-facilitated group learning session for providers about dose adjustments for patients with renal impairment. Principles from the educational session will be reinforced through an electronic medical record decision support tool. The tool will consist of a calculator that will allow prescribers to estimate creatinine clearance. Electronically delivered lab data will be used to populate appropriate fields in the creatinine clearance calculator in order to improve the ease of use of this decision support tool. Users will be prompted to supply missing data and will be advised about necessary dose adjustments for the targeted medications. The targeted medications are those that have already been determined through a consensus panel at the Centre for Evaluation of Medicines, McMaster University and for which dose adjustment guidelines are available and that are being utilized for another related project to improve dosing of medications in the long term care setting. The list of included medications and recommended dose adjustments are attached (Appendix 1).
Measurements:
Targetted prescriptions:
The number of prescriptions written for the targeted medications will be collected. Each prescription will be reviewed and categorized as appropriate or inappropriate by examining the drug regimen and creatinine clearance for the patient. Two people will independently review each prescription and discrepancies will be resolved through concensus. The appropriateness rating process will be pilot tested.
Number of patients for whom a prescription for the target drug was written, number of times the electronic decision support tool was accessed and the time between initiation of the decision support tool and electronic prescribing of the precriotion will be collected.
Prescriber knowledge and comfort with adjusting doses of medications will be measured in a Likert scale before and after the teaching session. Prescriber assessement of the ease of use of the decision support tool will be measured through a brief useability survey.
Outcomes:
The primary outcome will be a change in the number of appropriately written prescriptions for the targeted medications 3 and 6 months after the educational intervention and introduction of the clinical decision support tool.
Secondary outcomes will include:
* prescribers' perception of their knowledge of and comfort with adjusting doses of medications as measured in a Likert scale and their assessement of the ease of use of the decision support tool
* cost savings
* time for prescribers to use the decision support tool
* Number of times the decision support tool was used.
