The purpose of this clinical improvement project was to instill a streamlined process of identifying social determinants of health (SDOH) in our clinic’s diverse patient population and provide resources that address these barriers to health and well-being. At each clinic visit, patients self-identified SDOH through an easy-to-use Social Assessment Form. Using an online database, Community Relay (CR), providers had access to location-based community resources. In addition to accomplishing the above-mentioned goals, we were left with a more well-rounded understanding of our patients. Unique struggles were identified and barriers to care were revealed, allowing for more patient-centered medical care.

The amount of data available to healthcare practitioners is growing, and the rapid increase in available patient data is becoming a problem for healthcare practitioners, as they are often unable to fully survey and process the data relevant for the treatment or care of a patient. Consequently, there are currently several efforts to develop systems that can aid healthcare practitioners with reading and processing patient data and, in this way, provide them with a better foundation for decision-making about the treatment and care of patients. There are also efforts to develop algorithms that provide suggestions for such decisions. However, the development of these systems and algorithms raises several concerns related to the privacy of patients, the patient–practitioner relationship, and the autonomy of healthcare practitioners. The aim of this article is to provide a foundation for understanding the ethical challenges related to the development of a specific form of data-processing systems, namely clinical algorithms.

Introduction: Patients in our ED were dissatisfied with their waiting experience, which resulted in patient anxiety and complaints. In 8 months, we aimed to (1) improve patient satisfaction with the ED waiting experience from triage to physician initial assessment by a 15% improvement in patients who rate their experience very good/excellent on a Likert Scale, and (2) improve patient knowledge of ED wait time by a 50% increase in understanding on a Likert Scale. Methods: We co-designed a display with ED patients to notify those in the waiting room of their wait process and wait time. The intervention was selected after root cause diagnostics including: Fishbone exercise, Pareto Diagram, and Driver Diagram. The display was co-designed with ED patients and improved via PDSA cycles to establish information displayed and how to incorporate it into the waiting experience. After co-design, a low-fidelity display was piloted in the waiting room. Results: A family of measures were evaluated using patient/provider surveys and hospital data metrics. Outcome measures were (1) percentage of patients who rated their ED experience as very good/excellent on a Likert scale, and (2) patients who had a clear/very clear understanding of their wait time on a Likert scale. Process measures were the percentage of patients who (1) looked at the wait time display, and (2) felt they could communicate their wait time to others. Balancing measures were clerk/nurse satisfaction and self-reported interruptions of patients asking wait time. Outcomes were tracked using statistical process charts and run charts. Following display implementation, patient rating of their ED experience and patient understanding of wait time showed positive improvement. Clerks/nurses were also more satisfied with their jobs and self-reported interruptions decreased. Conclusion: A low-fidelity wait time display co-designed with patients improved patient satisfaction and understanding of ED wait times. We plan to develop an automated electronic display that resembles the low-fidelity display and evaluate the impact of the intervention on the established measures. This intervention has the potential to be sustainable, feasible for other EDs, and require minimal upkeep costs.

Introduction: Many emergency departments (EDs) have begun publishing wait times. This study seeks to develop an understanding of patients’ needs with respect to publishing ED wait times, which, to our knowledge, has not been described in the literature. Methods: We conducted a two-stage mixed methods study at a dual campus tertiary care academic center. First, we held focus group discussions comprising of 7 patient advocacy hospital committee members. Themes generated from focus group discussions were then utilized to create a patient survey. Focus groups were analyzed using content theme analysis. Hospital sites for survey administration were randomized and pre-assigned shifts were established to ensure a balance of weekdays, weekends, days, evenings, and overnights. All adult patients (age >18) in the waiting room were eligible, but excluded if they were directly referred to a specialty service or did not speak French or English. Survey data was analyzed using descriptive statistics. Results: We found 9 dominant focus group themes: definition of wait time, wait time posting, lack of communication, education in waiting room, patient expectations, utilization of the ED, patient behavior, physical comfort, and patient empowerment. Of the 240 patient questionnaires administered, 81.3% (195) wanted to know ED wait times before arrival to hospital and 90.8% (217) wanted ED wait times posted in the ED waiting room. The most popular choice for publishing wait times outside the ED was a website (46.7%) whereas, within the ED, patients were not particular about the specific display modality as long as times were displayed (39.6%). Overall, 76.7% (184) stated their satisfaction with the ED would be improved if wait times were posted. Conclusion: ED patients we surveyed strongly supported both the idea of having access to wait time information prior to arrival, as well as physical display of wait times in the waiting room.