Objectives: Pulmonary function tests (PFTs) are essential for diagnosis, management, and follow-up of a wide range of respiratory conditions as they provide quantitative insights into various aspects of lung function. Precision in ordering and scheduling PFTs, like any test, is crucial as errors can lead to misdiagnoses, delayed treatments, unnecessary retesting, inflated healthcare costs, and potentially compromised patient care. Hence, the aim of this quality improvement initiative was to reduce the PFT ordering error rate to below 5% by redesigning the ordering workflow and implementing a standardized order set tailored to specific clinical scenarios. Methods: The quality improvement initiative was implemented from August 2023 to March 2024. Data was collected from the electronic medical record (EMR) using predefined operational definitions to identify incorrect PFT orders and scheduling errors. A redesigned orderset was created to align with specific clinical presentations, including symptoms, suspected diagnosis, confirmed diagnosis, and presurgical evaluation. Scheduling was also restructured to match the expected testing time for each category. Education sessions were conducted with ordering providers, and ongoing feedback loops were established. Results: Among 575 preintervention PFT orders, 130 (22.6%) contained errors. Following implementation, review of 607 postintervention orders showed a reduction in error rates to 4.1%, representing an ∼80% improvement ( P <0.01). There was no increase in unnecessary testing, supporting the effectiveness of the intervention without unintended negative consequences. Conclusions: Implementation of a knowledge-based CDSS with standardized order sets significantly reduced PFT ordering errors and variability, improving guideline adherence and care quality. Continued refinement and integration with evolving technologies are essential for broader applicability.
Impact of a Disease-Focused Electronic Health Record Dashboard on Clinical Staff Efficiency in Previsit Patient Review in an Ambulatory Pulmonary Hypertension Care Clinic
Abstract Objectives We aimed to improve the operational efficiency of clinical staff, including physicians and allied health professionals, in the previsit review of patients by implementing a disease-focused dashboard within the electronic health record system. The dashboard was tailored to the unique requirements of the clinic and patient population. Methods A prospective quality improvement study was conducted at an accredited pulmonary hypertension (PH) clinic within a large academic center, staffed by two full time physicians and two allied health professionals. Physicians' review time before and after implementation of the PH dashboard was measured using activity log data derived from an EHR database. The review time for clinic staff was measured through direct observation, with review method—either conventional or newly implemented dashboard—randomly assigned. Results Over the study period, the median number of patients reviewed by physicians per day increased slightly from 5.50 (interquartile range [IQR]: 1.35) before to 5.95 (IQR: 0.85) after the implementation of the PH dashboard (p = 0.535). The median review time for the physicians decreased with the use of the dashboard, from 7.0 minutes (IQR: 1.55) to 4.95 minutes (IQR: 1.35; p < 0.001). Based on the observed timing of 70 patient encounters among allied clinical staff, no significant difference was found for experienced members (4.65 minutes [IQR: 2.02] vs. 4.43 minutes [IQR: 0.69], p = 0.752), while inexperienced staff saw a significant reduction in review time after familiarization with the dashboard (5.06 minutes [IQR: 1.51] vs. 4.12 minutes [IQR: 1.99], p = 0.034). Subjective feedback highlighted the need for further optimization of the dashboard to align with the workflow of allied health staff to achieve similar efficiency benefits. Conclusion A disease-focused dashboard significantly reduced physician previsit review time while that for clinic staff remained unchanged. Validation studies are necessary with our patient populations to explore further qualitative impacts on patient care efficiency and long-term benefits on workflow.