Managing an Unhappy Patient

A clinical study has noted that one out of six patients is perceived as “difficult” by clinicians. Not surprisingly, patient dissatisfaction has to do with multiple factors, both within and outside the control of the surgeon. In the present times of electronic information and ratings, managing difficult patients is a critical skill—a patient's dissatisfactory review could adversely affect a practitioner's reputation built over years of meticulous practice. Patient expectations are often more pronounced in case of elective medical procedures such as hair transplants. The subject of managing an unhappy patient in the context of hair transplantation is, therefore, one that requires due enquiry and is the subject that this article seeks to explore.

A Simulation Model for Geriatric Education: Theory, Virtual Transformation and Quality Improvement

Delivery of effective healthcare for the geriatric population is often complex due to the interplay between physical, social, and emotional variables. It is well established that it is the interplay between chronic medical conditions, social determinants of health, function and geriatric syndromes that drives outcomes. This complexity makes it especially important for the healthcare team to take an interprofessional team approach to avoid fragmented care which can lead to patient dissatisfaction, an ineffective plan of care, and low-quality outcomes. However, effective teamwork is not innate to healthcare; it must be learned and developed over time through purposeful education. The literature on team training supports active learning pedagogies such as simulation-based education that has emerged as an effective way to translate teamwork education into practice. Participation in active learning such as simulation, provides learners with authentic experiences that become cognitive frames that can transition into real practice. Education of adult learners should be a scaffolding of experiences that build on one another. This approach can lead the learner from the acquisition of basic knowledge, skills, and attitudes, to higher levels of competency and clinical judgement. Simulation simultaneously engages cognitive, perceptual-motor, and affective learning, and when combined with effective debriefing can lead to higher levels of learning. Effective models with scaffolding of experiences using simulations for geriatric team training are lacking in the literature. We describe here the theoretical framework for such training, adaptions of in-person and virtual training models due to COVID-19 restrictions through rapid cycle quality improvement.

Classification Tree to Analyze Factors Connected with Post Operative Complications of Cataract Surgery in a Teaching Hospital

Background: Artificial intelligence (AI) is becoming ever more frequently applied in medicine and, consequently, also in ophthalmology to improve both the quality of work for physicians and the quality of care for patients. The aim of this study is to use AI, in particular classification tree, for the evaluation of both ocular and systemic features involved in the onset of complications due to cataract surgery in a teaching hospital. Methods: The charts of 1392 eyes of 1392 patients, with a mean age of 71.3 ± 8.2 years old, were reviewed to collect the ocular and systemic data before, during and after cataract surgery, including post-operative complications. All these data were processed by a classification tree algorithm, producing more than 260 million simulations, aiming to develop a predictive model. Results: Postoperative complications were observed in 168 patients. According to the AI analysis, the pre-operative characteristics involved in the insurgence of complications were: ocular comorbidities, lower visual acuity, higher astigmatism and intra-operative complications. Conclusions: Artificial intelligence application may be an interesting tool in the physician’s hands to develop customized algorithms that can, in advance, define the post-operative complication risk. This may help in improving both the quality and the outcomes of the surgery as well as in preventing patient dissatisfaction.

Indications for exchange or explantation of phakic implantable collamer lens with central port in patients with and without keratoconus

AIM: To evaluate the causes of phakic implantable collamer lens (ICL) exchange/explantation in patients with and without keratoconus (KC) at two tertiary hospitals in Riyadh, Saudi Arabia. METHODS: A retrospective chart review of all patients who underwent ICL (model V4c with central port) exchange/explantation was performed using the electronic medical record systems. All available preoperative and postoperative data were documented for each patient. RESULTS: Over 7y, 2283 ICL implantation procedures were performed; 46 implants (2%) required exchange (21 implants)/explantation (25 implants), of which 14 cases (30.4%) were patients with KC. Indications for ICL exchange/explantation in non-KC group were vault measurement, cataract formation, increased intraocular pressure, inaccurate refraction, and patient dissatisfaction in 22 (68.75%), 4 (12.5%), 3 (9.37%), 2 (6.25%), and 1 (3.12%) case, respectively. The most common indication for ICL exchange/explantation in the KC group was inaccurate vault sizing in 11 patients (78.57%), inaccurate refraction in 2 patients (14.28%), and patient dissatisfaction postoperatively in 1 (7.14%) case. CONCLUSION: ICL implantation results in predictable refractive outcomes over the long term with exchange/explantation rates comparable to previous literature. Improper vault size is the most common cause of ICL exchange/explantation among patients with or without KC.

Interruption of Initial Patient Assessment in the Emergency Department and its Effect on Patient Perception of Care Quality

ABSTRACT Background Triage is a critical first step in appropriately caring for patients in the emergency department. Patients’ assumptions of the care they will receive can be established in triage. Interruptions to this process can disrupt patient flow, cause errors and lead to patient dissatisfaction. The purpose of this study was to determine how the frequency and duration of interruptions during triage are associated with errors, patient satisfaction, and patient’s perception of the care they received. Methods Prospective, observational, cohort study conducted in the emergency department of a Level 1 trauma center. Interruptions were measured using time-and-motion observations of triage interviews performed by nurses and physicians. Patients were surveyed immediately after triage interviews were complete. Results Surveys were completed for 178 observations. 62.9% of the observations were interrupted between 1 and 5 times. While interruptions did not significantly influence patient satisfaction directly, interruptions positively influenced triage duration, which was negatively associated with patient satisfaction. Increased errors were associated with increasing frequency of triage interruptions. Triage interruptions were not associated with either patient satisfaction or perceived caregiver competence. Overall, the majority (76.6%) of patients were satisfied with their care; patient satisfaction was associated with the perceived competency of caregivers but was not associated with errors. Conclusion Interruptions are associated with increased errors and delays in patient care. Although increased triage duration adversely affected patient satisfaction, patients’ perceptions were not influenced by interruptions. While patient satisfaction is essential, the lack of association between patient satisfaction and errors suggests that using patient satisfaction as a measure of care quality may omit important safety information.

Patient Chief Complaint and Otolaryngology Referral Rationale: Discordance and Opportunities for Quality Improvement

Objective: As medical systems focus on patient satisfaction as an important care outcome, specialty clinics are tasked with continued improvement of patients’ experience. When patient expectations for a consultation differ from that of the specialty provider, dissatisfaction with the experience can occur. One source of differing expectations is discordance between the patient’s chief complaint and the clinical rationale for the consultation as requested by the referring provider. We sought to better understand when this discordance occurs, as well as factors contributing to this disorientation of patient and provider expectations in a safety net otolaryngology practice. Methods: A retrospective observational study was performed and records were examined from new patient consultations. Patient questionnaires, including self-reported chief concerns, were compared with the electronic referral documentation. A difference between the patient’s Chief Complaint (CC) and Referral Reason (RR) was defined as CC-RR Discordance. Medical records, pre-consultation patient communication, and scheduling data were also reviewed to evaluate contributing factors. Results: Of the 1155 consultations examined, 952 were included in the analysis. A CC-RR Discordance was found in 175 (18.4%) of new-patient encounters, including 117 (12.3%) that were unable to articulate a CC (unsure of the reason for the appointment), and 58 (6.1%) that stated a CC that was different than the RR. The rate of CC-RR Discordance was higher in patients with female sex ( P < .05), older age ( P < .001), and longer time intervals between referral and appointment ( P < .05). Lack of communication with the patient (instructions or referral notification) by the referring provider was not associated with CC-RR Discordance. Conclusions: Discordance between patient CC and the rationale for a consultation is common in this safety-net otolaryngology practice and may be an important source of patient dissatisfaction. Future opportunities for quality improvement include pre-consultation communication between the specialist and the patient and reducing time intervals between referral and appointment.

Patient Satisfaction and Hospital Quality of Care Evaluation in Malaysia Using SERVQUAL and Facebook

Social media sites, dubbed patient online reviews (POR), have been proposed as new methods for assessing patient satisfaction and monitoring quality of care. However, the unstructured nature of POR data derived from social media creates a number of challenges. The objectives of this research were to identify service quality (SERVQUAL) dimensions automatically from hospital Facebook reviews using a machine learning classifier, and to examine their associations with patient dissatisfaction. From January 2017 to December 2019, empirical research was conducted in which POR were gathered from the official Facebook page of Malaysian public hospitals. To find SERVQUAL dimensions in POR, a machine learning topic classification utilising supervised learning was developed, and this study’s objective was established using logistic regression analysis. It was discovered that 73.5% of patients were satisfied with the public hospital service, whereas 26.5% were dissatisfied. SERVQUAL dimensions identified were 13.2% reviews of tangible, 68.9% of reliability, 6.8% of responsiveness, 19.5% of assurance, and 64.3% of empathy. After controlling for hospital variables, all SERVQUAL dimensions except tangible and assurance were shown to be significantly related with patient dissatisfaction (reliability, p < 0.001; responsiveness, p = 0.016; and empathy, p < 0.001). Rural hospitals had a higher probability of patient dissatisfaction (p < 0.001). Therefore, POR, assisted by machine learning technologies, provided a pragmatic and feasible way for capturing patient perceptions of care quality and supplementing conventional patient satisfaction surveys. The findings offer critical information that will assist healthcare authorities in capitalising on POR by monitoring and evaluating the quality of services in real time.

The Impact of Patient Age on the Acceptability of Telemedicine in the Context of COVID-19

The objective of the study was to determine the extent to which patients from various age groups perceive telemedicine as a viable mode of healthcare delivery in the context of COVID-19. A RedCap survey was sent to patients in our OB/GYN outpatient clinics with in-person, telemedicine, re-scheduled or cancelled appointments between 3/11/20 to 5/11/20. Patients’ online responses were analyzed using a 5-point Likert scale. Statistical analysis was performed using Chi-Square and Fischer’s Exact Analysis with p < 0.05 considered significant. A total of 1083 patients completed the survey of whom 280 (25.9%) had a telemedicine appointment. Patients answered questions relating to their telemedicine visit. While older patients did encounter a higher proportion of technological difficulties (p<0.0001), younger patients, specifically those in the 25-34 age group, expressed greater dissatisfaction with their appointment being changed to telemedicine than older patients (p=0.02), and felt that telemedicine did not accomplish the same goals as an in-person visit (p=0.01). Nonetheless, all patients, regardless of age, were satisfied with the introduction to telemedicine (p=0.02) and the instructions provided to them prior to the visit (p=0.02). Connectivity issues seem to be the biggest obstacle to older patients particularly when there is absence of a reliable internet connection and a telemedicine-compatible device. Younger patients, though less satisfied, are more comfortable with new technology and with using telemedicine; they tend to experience less connectivity issues. Our focus going forward should be on finding ways to simplify the process, overcome the connectivity issues while addressing the main reasons leading to patient dissatisfaction.

Decreasing inpatient chemotherapy initiation delays at Memorial Regional Hospital.

225 Background: Between June and December 2019, hematology-oncology patients admitted for elective chemotherapy at Memorial Regional Hospital had a median delay of 10 hours to initiate chemotherapy infusion from time of admission. This contributes to increased cost to the healthcare system and patient dissatisfaction. By September 2020, elective inpatient median time from admission to chemotherapy initiation at Memorial Regional Hospital will be reduced by 20%. Methods: Multidisciplinary team formed to evaluate the time from admission to initiation of chemotherapy for patients who are electively admitted for chemotherapy in 8 Central based on time stamps available in the electronic health records. Patients electively admitted by a non MCI oncologist were excluded. Data collections included time stamp between each process from admission to administration of 1st chemotherapy. Longest time lapse between each process was counted as an occurrence/contributor to delay. Top 80% contributors identified from Pareto chart allowed team to identify countermeasures. Priority Matrix of implementation in PDSA cycle based on highest impact and ease of implementation. Statistical process control chart was developed. Results: (see table). Conclusions: PDSA Cycle 1, obtaining labs 24-48 hours prior to admission, resulted in a 10% reduction in chemotherapy initiation time. PDSA Cycle 2, enhancing “ok to treat” communication, resulted in a further reduction of time to treatment. The combination of PDSA Cycle 1 & 2 resulted in a 40% reduction in time to chemotherapy initiation, exceeding the planned aim of 20%. Balance measures reflected no reduction in the mean number of overnight stays between baseline and PDSA Cycle 2 (4 nights) that could contribute to a decreased cost. Results and recommendations to adopt at all inpatient oncology departments within the healthcare system will be presented to leadership for support. Data automation through collaborative efforts with information technology is in process to assist with continuous monitoring. Future state, the quality improvement tools gained from ASCO QTP will be utilized to evaluate and improve workflow issues in the outpatient oncology setting. Nationally recognized organizations are encouraged to propose a benchmark for admission time to first chemotherapy administration based on the evaluation of current available data. Additional studies are needed to evaluate chemotherapy treatment delays in other settings.[Table: see text]