Evaluation of Patient No-Shows in a Tertiary Hospital: Focusing on Modes of Appointment-Making and Type of Appointment

Patients' intention to make an up-front payment at private outpatient clinics in Malaysia as a no-show reduction method

Regulating patients' no-show behavior is critical from the standpoints of sustainable medical services and operational efficiencies. The purpose of this study was to evaluate the patients' intention to make partial up-front payments at outpatient clinics. This was a cross-sectional study design introducing a self-administered questionnaire to 221 outpatients at a private health facility. The questionnaire measured the patient's demographic characteristics, perceived usefulness (PU), trust in the health facility, and intention to make upfront partial payments. Out of the total respondents, 57.4% were female. There were 34.8% Malays, 40.6% Chinese and 24.6% Indians. The majority (66.5%) of the respondents attained tertiary education. Nearly a third of the respondents (30.5%) reported an income between 3000 and 5000 Malaysian Ringgit (RM). Regarding payment mode, just more than half (51.1%) made self-payment, and 21.8% by guaranteed letter. A quarter (24.9%) waited more than 3 h for consultation and 59.6% visited the health facility more than 2 times in a year. Initial analysis showed that PU, trust, age, education, number of visits, and hours of waiting were significantly associated with the intention to make a partial payment. Multiple linear regression showed that perceived usefulness (B = 0.517, p < 0.001); trust in hospital management (B = 0.288, p < 0.001) and number of visits (B = 0.216, p < 0.001) were associated with the intention to make partial payment. Intention to make partial up-front payments is associated with higher perceived usefulness in making such payments and hospital trust. Visiting the health facility frequently was associated with a higher intention to make upfront partial payment. The result may guide further studies on potential remedies to no-show.

The impact of the COVID-19 pandemic on rates and predictors of missed hospital appointments in multiple outpatient clinics of The Royal Hospital, Sultanate of Oman: a retrospective study

BACKGROUND

The global outbreak of the COVID-19 pandemic resulted in significant changes in the delivery of health care services such as attendance of scheduled outpatient hospital appointments. This study aimed to evaluate the impact of COVID-19 on the rate and predictors of missed hospital appointment in the Sultanate of Oman.

METHODS

A retrospective single-centre analysis was conducted to determine the effect of COVID-19 on missed hospital appointments at various clinics at The Royal Hospital (tertiary referral hospital) in Muscat, Sultanate of Oman. The study population included scheduled face-to-face and virtual appointments between January 2019 and March 2021. Logistic regression models were used with interaction terms (post COVID-19) to assess changes in the predictors of missed appointments.

RESULTS

A total of 34, 3149 scheduled appointments was analysed (320,049 face-to-face and 23,100 virtual). The rate of missed face-to-face hospital appointments increased from 16.9% pre to 23.8% post start of COVID-19, particularly in early pandemic (40.5%). Missed hospital appointments were more frequent (32.2%) in virtual clinics (post COVID-19). Increases in missed face-to-face appointments varied by clinic (Paediatrics from 19.3% pre to 28.2% post; Surgery from 12.5% to 25.5%; Obstetrics & Gynaecology from 8.4% to 8.5%). A surge in the frequency of missed appointments was seen during national lockdowns for face-to-face and virtual appointments. Most predictors of missed appointments did not demonstrate any appreciable changes in effect (i.e., interaction term not statistically significant). Distance of patient residence to the hospital revealed no discernible changes in the relative effect pre and post COVID-19 for both face-to-face and virtual clinic appointments.

CONCLUSION

The rate of missed visits in most clinics was directly impacted by COVID-19. The case mix of patients who missed their appointments did not change. Virtual appointments, introduced after start of the pandemic, also had substantial rates of missed appointments and cannot be viewed as the single approach that can overcome the problem of missing hospital appointments.

Patient "No-Show" Increases the Risk of 90-Day Complications Following Primary Total Knee Arthroplasty: A Retrospective Cohort Study of 6,776 Patients

BACKGROUND

Patients who "no-show" (NS) clinical appointments are at a high risk of adverse health outcomes. The objective of this study was to evaluate and characterize the relationship between NS visits prior to primary total knee arthroplasty (TKA) and 90-day complications after TKA.

METHODS

We retrospectively reviewed 6,776 consecutive patients undergoing primary TKA. Study groups were separated based on whether patients who NS versus always attended their appointment. A NS was defined as an intended appointment that was not canceled or rescheduled ≤2 hours before the appointment in which the patient did not show. Data collected included total number of follow-up appointments prior to surgery, patient demographics, comorbidities, and 90-day postoperative complications.

RESULTS

Patients who have ≥3 NS appointments had 1.5 times increased odds of a surgical site infection (odds ratio (OR) 1.54, P = .002) compared to always attended patients. Patients who were ≤65 years old (OR: 1.41, P < .001), smokers (OR: 2.01, P < .001), and had a Charlson comorbidity index ≥3 (OR: 4.48, P < .001) were more likely to miss clinical appointments.

CONCLUSION

Patients who have ≥3 NS appointments prior to TKA had an increased risk for surgical site infection. Sociodemographic factors were associated with higher odds of missing a scheduled clinical appointment. These data suggest that orthopaedic surgeons should consider NS data as an important clinical decision-making tool to assess risk for postoperative complications to minimize complications following TKA.

Causes of Patient Nonattendance at Medical Appointments: Protocol for a Mixed Methods Study

BACKGROUND

Approximately one-third of patient appointments in Danish health care result in failures, leading to patient risk and sizable resource waste. Existing interventions to alleviate no-shows often target the patients. The underlying reason behind these interventions is a view that attendance or nonattendance is solely the patient's problem. However, these interventions often prove to be ineffective and can perpetuate social biases and health inequalities, leaving behind patients who are more vulnerable or disadvantaged (in terms of social, economical, and linguistic factors, etc). A more holistic understanding of no-shows is needed to optimize processes, reduce waste, and support patients who are vulnerable.

OBJECTIVE

This study aims to gain a deep and more comprehensive understanding of the causes, mechanisms, and recurring patterns and elements contributing to nonattendance at Danish hospitals in the Region of Southern Denmark. It emphasizes the patient perspective and analyzes the relational and organizational processes surrounding no-shows in health care. In addition, the study aims to identify effective communicative strategies and organizational processes that can support the development and implementation of successful interventions.

METHODS

The study uses mixed quantitative-qualitative methods, encompassing 4 analytical projects focusing on nonattendance patterns, patient knowledge and behavior, the management of hospital appointments, and in situ communication. To address the complexity of no-shows in health care, the study incorporates various data sources. The quantitative data sources include the electronic patient records, Danish central registries, Danish National Patient Registry, and Register of Medicinal Product Statistics. Baseline characteristics of patients at different levels are compared using chi-square tests and Kruskal-Wallis tests. The qualitative studies involve observational data, individual semistructured interviews with patients and practitioners, and video recordings of patient consultations.

RESULTS

This paper presents the protocol of the study, which was funded by the Novo Nordisk Foundation in July 2022. Recruitment started in February 2023. It is anticipated that the quantitative data analysis will be completed by the end of September 2023, with the qualitative investigation starting in October 2023. The first study findings are anticipated to be available by the end of 2024.

CONCLUSIONS

The existing studies of nonattendance in Danish health care are inadequate in addressing relational and organizational factors leading to hospital no-shows. Interventions have had limited effect, highlighting the Danish health care system's failure to accommodate patients who are vulnerable. Effective interventions require a qualitative approach and robust ethnographic data to supplement the description and categorization of no-shows at hospitals. Obtaining comprehensive knowledge about the causes of missed patient appointments will yield practical benefits, enhancing the safety, coherence, and quality of treatment in health care.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/46227.

Factors associated with appointment 'no-shows' at two tertiary level outpatient oculoplastic clinics

PURPOSE

Appointment no-shows in clinics can adversely impact patients and physicians alike. This study aimed to determine the rate and potential causes of missed appointments in oculoplastic clinics and compare a private practice and hospital-based academic setting.

METHODS

A retrospective review of patients who booked appointments for oculoplastic consultation, between August 2019 and January 2020 at two oculoplastic clinics was performed. Demographic and patient-specific characteristics of patients who failed to attend their appointment were identified. Data were analysed to determine and compare the no-show rates in both clinics and logistic regression was performed to determine factors associated with them.

RESULTS

The rate of missed appointments was 3% and 17% at the oculoplastic clinics of Lions Eye Institute (LEI, private practice) and Albany Medical Center (AMC, academic hospital-based office), respectively. Patients at the AMC clinic were more likely to be male, younger, have a lower household income, not carry private insurance, and suffer from trauma. Logistic regression analysis showed lower patient age to significantly increase the likelihood of no-shows in both clinics (p = .01 for LEI, p = .003 for AMC), and lead appointment time greater than 90 days to be a significant risk factor for no-shows at LEI (p = .01).

CONCLUSIONS

The no-show rate for oculoplastic appointments is 3% and 17% at LEI and AMC clinics, respectively. Our analysis shows that younger patients are more likely to miss appointments at both clinics, and an appointment lead time greater than 90 days is a significant risk factor for no-shows at LEI.

Reducing non-attendance in outpatient appointments: predictive model development, validation, and clinical assessment

Background

Non-attendance to scheduled hospital outpatient appointments may compromise healthcare resource planning, which ultimately reduces the quality of healthcare provision by delaying assessments and increasing waiting lists. We developed a model for predicting non-attendance and assessed the effectiveness of an intervention for reducing non-attendance based on the model.

Methods

The study was conducted in three stages: (1) model development, (2) prospective validation of the model with new data, and (3) a clinical assessment with a pilot study that included the model as a stratification tool to select the patients in the intervention. Candidate models were built using retrospective data from appointments scheduled between January 1, 2015, and November 30, 2018, in the dermatology and pneumology outpatient services of the Hospital Municipal de Badalona (Spain). The predictive capacity of the selected model was then validated prospectively with appointments scheduled between January 7 and February 8, 2019. The effectiveness of selective phone call reminders to patients at high risk of non-attendance according to the model was assessed on all consecutive patients with at least one appointment scheduled between February 25 and April 19, 2019. We finally conducted a pilot study in which all patients identified by the model as high risk of non-attendance were randomly assigned to either a control (no intervention) or intervention group, the last receiving phone call reminders one week before the appointment.

Results

Decision trees were selected for model development. Models were trained and selected using 33,329 appointments in the dermatology service and 21,050 in the pneumology service. Specificity, sensitivity, and accuracy for the prediction of non-attendance were 79.90%, 67.09%, and 73.49% for dermatology, and 71.38%, 57.84%, and 64.61% for pneumology outpatient services. The prospective validation showed a specificity of 78.34% (95%CI 71.07, 84.51) and balanced accuracy of 70.45% for dermatology; and 69.83% (95%CI 60.61, 78.00) for pneumology, respectively. The effectiveness of the intervention was assessed on 1,311 individuals identified as high risk of non-attendance according to the selected model. Overall, the intervention resulted in a significant reduction in the non-attendance rate to both the dermatology and pneumology services, with a decrease of 50.61% (p<0.001) and 39.33% (p=0.048), respectively.

Conclusions

The risk of non-attendance can be adequately estimated using patient information stored in medical records. The patient stratification according to the non-attendance risk allows prioritizing interventions, such as phone call reminders, to effectively reduce non-attendance rates.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-07865-y.