Lead time for appointment and the no-show rate in an ophthalmology clinic

Predictors of No-Show Status: An Analysis of Pediatric Ophthalmology Patients at an Academic Ophthalmology Department in the United States

PURPOSE

To identify pediatric patient and appointment characteristics associated with no-show status at a tertiary care pediatric ophthalmology clinic within a U.S. academic ophthalmology department.

METHODS

A cross-sectional retrospective chart review was performed for all pediatric patients with a scheduled ophthalmology appointment at the Penn State Eye Center between April 1, 2022 and March 31, 2023. A multivariate logistic regression analysis assessed associations between appointment nonattendance and patient characteristics.

RESULTS

Of 8,083 scheduled visits, 1,445 (17.9%) were no-shows. Factors associated with no-show status included appointment type (new vs return odds ratio [OR]: 1.43, 95% CI: 1.26 to 1.63, P < .001); lower median household income (< $41,374 vs > $68,957 OR: 1.89, 95% CI: 1.40 to 2.55, P < .001; $41,374 to $68,957 vs > $68,957 OR: 1.27, 95% CI: 1.12 to 1.44, P < .001); non-private insurance (self-pay vs private: OR: 5.65, 95% CI: 3.87 to 8.24, P < .001, Medicaid vs private: OR: 2.17, 95% CI: 2.32 to 3.16, P < .001); commute distance 10 to 30 miles vs < 5 miles (OR: 1.49, 95% CI: 1.11 to 1.99, P = .008); race: unavailable vs White (OR: 2.18, 95% CI: 1.66 to 2.85, P < .001), Black vs White (OR: 1.86, 95% CI:1.53 to 2.27, P < .001), Other vs White (OR: 1.47, 95% CI: 1.27 to 1.70, P < .001); ethnicity: Hispanic vs non-Hispanic (OR: 1.92, 95% CI: 1.62 to 2.27, P < .001); and language preference: Spanish vs English (OR: 1.86, 95% CI: 1.49 to 2.32, P < .001), Nepali vs English (OR: 1.60, 95% CI: 1.06 to 2.43, P = .027), other vs English (OR: 1.83, 95% CI: 1.35 to 2.49, P < .001). Appointment reminders (phone call, P = .013); text message, P < .001; other, P = .013) all resulted in a greater propensity to show, but email communication alone did not (P = .674).

CONCLUSIONS

Certain patient and appointment characteristics that are linked to a higher rate of no-show status can inform targeted initiatives to improve health care outcomes, resource utilization, and clinical efficiency in the pediatric ophthalmology community. [J Pediatr Ophthalmol Strabismus. 20XX;X(XX):XXX-XXX.].

Evaluating the Relationship between Neighborhood-Level Social Vulnerability and Patient Adherence to Ophthalmology Appointments

PURPOSE

To examine the association between neighborhood-level social vulnerability and adherence to scheduled ophthalmology appointments.

METHODS

In this retrospective cohort study, records of all patients ≥18 years scheduled for an ophthalmology appointment between September 12, 2020, and February 8, 2021, were reviewed. Primary exposure is neighborhood-level Social Vulnerability Index (SVI) based on the patient's residential location. SVI is a rank score of 15 social factors into four themes (socioeconomic status, household composition/disability, minority status/language, and housing type/transportation), ranging from 0 to 1.0, with higher ranks indicating greater social vulnerability. The overall SVI score and each theme were analyzed separately as the primary exposure of interest in multivariable logistic regression models that controlled for age, sex, appointment status (new or established), race, and distance from clinic. The primary outcome, non-adherence, was defined as missing more than 25% of scheduled appointments.

RESULTS

Of 8,322 patients (41% non-Hispanic Black, 24% Hispanic, 22% non-Hispanic White) with scheduled appointments, 28% were non-adherent. Non-adherence was associated with greater social vulnerability (adjusted odds ratio [aOR] per 0.01 increase in overall SVI = 2.46 [95% confidence interval, 1.99, 3.06]) and each SVI theme (socioeconomic status: aOR = 2.38 [1.94, 2.91]; household composition/disability: aOR = = 1.51 [1.26, 1.81]; minority status/language: aOR = 2.03 [1.55, 2.68]; housing type/transportation: aOR = 1.41 [1.16, 1.73]).

CONCLUSION

Neighborhood-level social vulnerability is associated with greater risk of non-adherence to scheduled ophthalmology appointments, controlling for individual characteristics. Multi-level intervention strategies that incorporate neighborhood-level vulnerabilities are needed to reduce disparities in access to ophthalmology care.

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.

Racial, Ethnic, and Socioeconomic Disparities Drive Appointment No-Show in Patients with Chronic Eye Disease

BACKGROUND

Visit no-shows (NS) reduce clinic efficiency and effective resource allocation. Inadequate follow-up among patients with chronic eye disease increases risk of disease progression. Our study identifies demographic, medical, and socioeconomic characteristics that increase odds of NS among patients with chronic eye conditions at high risk of vision-threatening complications.

METHODS

This is a retrospective case-control study of data abstracted over a 5-year period (January 2013-December 2018) in an urban academic ophthalmology practice. Follow-up appointments of patients ≥ 18 years of age with a diagnosis of glaucoma, diabetic retinopathy, or age-related macular degeneration were included. Age, sex, race, ethnicity, language preference, zip code, and relevant medical history were recorded. A multivariate mixed logistic regression model was utilized to determine any association between demographic factors and visit NS.

RESULTS

A total of 106,652 visits for 4,598 unique patients were included in this study. Of these, 13,240 (12.4%) visits were NS. Patient characteristics that increased the odds of NS included Hispanic ethnicity (p < 0.0001), Black race (p < 0.0001), and a history of mental illness (p < 0.0001). Socioeconomic factors that increased the odds of NS included median household income < $40,000 (p = 0.002), Medicare insurance (p < 0.0001), and Medicaid insurance (p < 0.0001).

CONCLUSIONS

Our results highlight the influence of ethnic, racial, medical, and socioeconomic characteristics on appointment NS among patients with chronic eye disease. Future interventions aimed at reducing appointment NS could channel resources to the at-risk populations identified in this analysis to improve access to care for those who need it most.

Impact of United States 2017 Immigration Policy changes on missed appointments at two Massachusetts Safety-Net Hospitals

INTRODUCTION

Studies have shown mixed findings regarding the impact of immigration policy changes on immigrants' utilization of primary care.

METHODS

We used a difference-in-differences analysis to compare changes in missed primary care appointments over time across two groups: patients who received care in Spanish, Portuguese, or Haitian Creole, and non-Hispanic, white patients who received care in English.

RESULTS

After adjustment for age, sex, race, insurance, hospital system, and presence of chronic conditions, immigration policy changes were associated with an absolute increase in the missed appointment prevalence of 0.74 percentage points (95% confidence interval: 0.34, 1.15) among Spanish, Portuguese and Haitian-Creole speakers. We estimated that missed appointments due to immigration policy changes resulted in lost revenue of over $185,000.

CONCLUSIONS

We conclude that immigration policy changes were associated with a significant increase in missed appointments among patients who receive medical care in languages other than English.

Predictors of No-Show in Neurology Clinics

In this study, we aim to identify predictors of a no-show in neurology clinics at our institution. We conducted a retrospective review of neurology clinics from July 2013 through September 2018. We compared odds ratio of patients who missed appointments (no-show) to those who were present at appointments (show) in terms of age, lead-time, subspecialty, race, gender, quarter of the year, insurance type, and distance from hospital. There were 60,012 (84%) show and 11,166 (16%) no-show patients. With each day increase in lead time, odds of no-show increased by a factor of 1.0019 (p < 0.0001). Odds of no-show were higher in younger (p ≤ 0.0001, OR = 0.49) compared to older (age ≥ 60) patients and in women (p < 0.001, OR = 1.1352) compared to men. They were higher in Black/African American (p < 0.0001, OR = 1.4712) and lower in Asian (p = 0.03, OR = 0.6871) and American Indian/Alaskan Native (p = 0.055, OR = 0.6318) as compared to White/Caucasian. Patients with Medicare (p < 0.0001, OR = 1.5127) and Medicaid (p < 0.0001, OR = 1.3354) had higher odds of no-show compared to other insurance. Young age, female, Black/African American, long lead time to clinic appointments, Medicaid/Medicare insurance, and certain subspecialties (resident and stroke clinics) are associated with high odds of no show. Possible suggested interventions include better communication and flexible appointments for the high-risk groups as well as utilizing telemedicine.

Prevalence and factors associated with missed hospital appointments: a retrospective review of multiple clinics at Royal Hospital, Sultanate of Oman

OBJECTIVES

Missed hospital appointments pose a major challenge for healthcare systems. There is a lack of information about drivers of missed hospital appointments in non-Western countries and extent of variability between different types of clinics. The aim was to evaluate the rate and predictors of missed hospital appointments and variability in drivers between multiple outpatient clinics.

SETTING

Outpatient clinics in the Royal hospital (tertiary referral hospital in Oman) between 2014 and 2018.

PARTICIPANTS

All patients with a scheduled outpatient clinic appointment (N=7 69 118).

STUDY DESIGN

Retrospective cross-sectional analysis.

PRIMARY AND SECONDARY OUTCOME MEASURES

A missed appointment was defined as a patient who did not show up for the scheduled hospital appointment without notifying or asking for the appointment to be cancelled or rescheduled. The outcomes were the rate and predictors of missed hospital appointments overall and variations by clinic. Conditional logistic regression compared patients who attended and those who missed their appointment.

RESULTS

The overall rate of missed hospital appointments was 22.3%, which varied between clinics (14.0% for Oncology and 30.3% for Urology). Important predictors were age, sex, service costs, patient's residence distance from hospital, waiting time and appointment day and season. Substantive variability between clinics in ORs for a missed appointment was present for predictors such as service costs and waiting time. Patients aged 81-90 in the Diabetes and Endocrine clinic had an adjusted OR of 0.53 for missed appointments (95% CI 0.37 to 0.74) while those in Obstetrics and Gynaecology had OR of 1.70 (95% CI 1.11 to 2.59). Adjusted ORs for longer waiting times (>120 days) were 2.22 (95% CI 2.10 to 2.34) in Urology but 1.26 (95% CI 1.18 to 1.36) in Oncology.

CONCLUSION

Predictors of a missed appointment varied between clinics in their effects. Interventions to reduce the rate of missed appointments should consider these factors and be tailored to clinic.

[Adherence to anti-VEGF treatment-Considerations and practical recommendations]

BACKGROUND

Numerous studies have identified a lack of treatment adherence as an important factor that often conflicts with the necessary number of anti-VEGF injections and therefore a better functional result.

OBJECTIVE

This article discusses approaches and possible measures to reduce the risk of late and infrequent intravitreal injections leading to the major issue of undertreatment.

MATERIAL AND METHOD

In the course of an expert dialogue, relevant parameters of treatment adherence and variables were identified. Meaningful processes were structured and assigned to organizational areas.

RESULTS

The compilation of meaningful measures enables practitioners to optimize their own implementation in different areas. Regular monitoring measures can identify the extent of treatment interruption and discontinuation. For specific indicators (treatments per time interval, longest pause interval, minimum coverage per unit time, delay) an effect on the development of visual function was demonstrated. Organizational measures, training of teams and referring physicians, redundant and iterative information transfer to patients have been proven in the experience of experts. The firm integration of these processes into the structures is facilitated by working with checklists.

CONCLUSION

An optimization of the processes is possible to improve the adherence and the functional results; however, interventional studies showing how adherence and persistence can be increased in the German treatment setting are still lacking.

Shorter outpatient wait-times for buprenorphine are associated with linkage to care post-hospital discharge

BACKGROUND

Inpatient addiction consult services (ACS) lower barriers to accessing medications for opioid use disorder (MOUD), however not every patient recommended for MOUD links to outpatient care. We hypothesized that fewer days between discharge date and outpatient appointment date was associated with improved linkage to buprenorphine treatment among patients evaluated by an ACS.

METHODS

We extracted appointment and demographic data from electronic medical records and conducted retrospective chart review of adults diagnosed with opioid use disorder (OUD) evaluated by an ACS in Boston, MA between July 2015 and August 2017. These patients were initiated on or recommended buprenorphine treatment on discharge and provided follow-up appointment at our hospital post-discharge. Multivariable logistic regression assessed whether arrival to the appointment post-discharge was associated with shorter wait-times (0-1 vs. 2+ days).

RESULTS

In total, 142 patients were included. Among patients who had wait-times of 0-1 day, 63 % arrived to their appointment compared to wait-times of 2 or more days (42 %). There were no significant differences between groups based on age, gender, distance of residence from the hospital, insurance status, co-occurring alcohol use disorder diagnosis, or discharge with buprenorphine prescription. After adjusting for covariates, patients with 0-1 day of wait-time had 2.6 times the odds of arriving to their appointment [95 % CI 1.3-5.5] compared to patients who had 2+ days of wait-time.

CONCLUSION

For hospitalized patients with OUD evaluated for initiating MOUD, same- and next-day appointments are associated with increased odds of linkage to outpatient MOUD care post-discharge compared to waiting two or more days.

Prevalence and predictors of no-shows to physical therapy for musculoskeletal conditions

OBJECTIVES

Chronic pain affects 50 million Americans and is often treated with non-pharmacologic approaches like physical therapy. Developing a no-show prediction model for individuals seeking physical therapy care for musculoskeletal conditions has several benefits including enhancement of workforce efficiency without growing the existing provider pool, delivering guideline adherent care, and identifying those that may benefit from telehealth. The objective of this paper was to quantify the national prevalence of no-shows for patients seeking physical therapy care and to identify individual and organizational factors predicting whether a patient will be a no-show when seeking physical therapy care.

DESIGN

Retrospective cohort study.

SETTING

Commercial provider of physical therapy within the United States with 828 clinics across 26 states.

PARTICIPANTS

Adolescent and adult patients (age cutoffs: 14-117 years) seeking non-pharmacological treatment for musculoskeletal conditions from January 1, 2016, to December 31, 2017 (n = 542,685). Exclusion criteria were a primary complaint not considered an MSK condition or improbable values for height, weight, or body mass index values. The study included 444,995 individuals.

PRIMARY AND SECONDARY OUTCOME MEASURES

Prevalence of no-shows for musculoskeletal conditions and predictors of patient no-show.

RESULTS

In our population, 73% missed at least 1 appointment for a given physical therapy care episode. Our model had moderate discrimination for no-shows (c-statistic:0.72, all appointments; 0.73, first 7 appointments) and was well calibrated, with predicted and observed no-shows in good agreement. Variables predicting higher no-show rates included insurance type; smoking-status; higher BMI; and more prior cancellations, time between visit and scheduling date, and between current and previous visit.

CONCLUSIONS

The high prevalence of no-shows when seeking care for musculoskeletal conditions from physical therapists highlights an inefficiency that, unaddressed, could limit delivery of guideline-adherent care that advocates for earlier use of non-pharmacological treatments for musculoskeletal conditions and result in missed opportunities for using telehealth to deliver physical therapy.

Healthcare disparities contribute to missed follow-up visits after cataract surgery in the USA: results from the perioperative care for intraocular lens study

OBJECTIVE

To identify factors that contribute to missed cataract surgery follow-up visits, with an emphasis on socioeconomic and demographic factors.

METHODS

In this retrospective cohort study, patients who underwent cataract extraction by phacoemulsification at Massachusetts Eye and Ear between 1 January and 31 December 2014 were reviewed. Second eye cases, remote and international patients, patients with foreign insurance and combined cataract cases were excluded.

RESULTS

A total of 1931 cases were reviewed and 1089 cases, corresponding to 3267 scheduled postoperative visits, were included. Of these visits, 157 (4.8%) were missed. Three (0.3%) postoperative day 1, 40 (3.7%) postoperative week 1 and 114 (10.5%) postoperative month 1 visits were missed. Age<30 years (adjusted OR (aOR)=8.2, 95% CI 1.9 to 35.2) and ≥90 years (aOR=5.7, 95% CI 2.0 to 15.6) compared with patients aged 70-79 years, estimated travel time of >2 hours (aOR=3.2, 95% CI 1.4 to 7.4), smokers (aOR=2.7, 95% CI 1.6 to 4.8) and complications identified up to the postoperative visit (aOR=1.4, 95% CI 1.0 to 2.1) predicted a higher rate of missed visits. Ocular comorbidities (aOR=0.7, 95% CI 0.5 to 1.0) and previous visit best-corrected visual acuity (BCVA) of 20/50-20/80 (aOR=0.4, 95% CI 0.3 to 0.7) and 20/90-20/200 (aOR=0.4, 95% CI 0.2 to 0.9), compared with BCVA at the previous visit of 20/40 or better, predicted a lower rate of missed visits. Gender, race/ethnicity, language, education, income, insurance, alcohol use and season of the year were not associated with missed visits.

CONCLUSIONS

Medical factors and demographic characteristics, including patient age and distance from the hospital, are associated with missed follow-up visits in cataract surgery. Additional studies are needed to identify disparities in cataract postoperative care that are population-specific. This information can contribute to the implementation of policies and interventions for addressing them.

Application of Machine Learning to Predict Patient No-Shows in an Academic Pediatric Ophthalmology Clinic

Patient "no-shows" are missed appointments resulting in clinical inefficiencies, revenue loss, and discontinuity of care. Using secondary electronic health record (EHR) data, we used machine learning to predict patient no-shows in follow-up and new patient visits in pediatric ophthalmology and to evaluate features for importance. The best model, XGBoost, had an area under the receiver operating characteristics curve (AUC) score of 0.90 for predicting no-shows in follow-up visits. The key findings from this study are: (1) secondary use of EHR data can be used to build datasets for predictive modeling and successfully predict patient no-shows in pediatric ophthalmology, (2) models predicting no-shows for follow-up visits are more accurate than those for new patient visits, and (3) the performance of predictive models is more robust in predicting no-shows compared to individual important features. We hope these models will be used for more effective interventions to mitigate the impact ofpatient no-shows.

Sustainable waiting time reductions after introducing the STAT model for access and triage: 12-month follow up of a stepped wedge cluster randomised controlled trial

Background

Timely access is a challenge for providers of outpatient and community-based health services, as seen by the often lengthy waiting lists to manage demand. The Specific Timely Appointments for Triage (STAT) model, an alternative approach for managing access and triage, reduced waiting time by 34% in a stepped wedge cluster randomised controlled trial involving 8 services and more than 3000 participants. Follow up periods ranged from 3 to 10 months across the participating services in accordance with the stepped wedge design. This study aimed to determine whether outcomes were sustained for a full 12 months after implementation of the STAT model at each site.

Methods

Routinely collected service data were obtained for a total of 12 months following implementation of the STAT model at each of the 8 services that participated in a stepped wedge cluster randomised controlled trial. The primary outcome was time to first appointment. Secondary outcomes included non-attendance rates, time to second appointment and service use over 12 weeks. Outcomes were compared to pre-intervention data from the original trial, modelled using generalised linear mixed effects models accounting for clustering of sites.

Results

A 29% reduction in waiting time could be attributed to STAT over 12 months, compared to 34% in the original trial. A reduction in variability in waiting time was sustained. There were no significant changes in time to second appointment or in the number of missed appointments in the extended follow up period.

Conclusions

STAT is an effective strategy for reducing waiting time in community-based outpatient services. At 12 months, small reductions in the overall effect are apparent, but reductions in variability are sustained, suggesting that people who previously waited the longest benefit most from the STAT model.

Trial registration

This is a 12-month follow up of a stepped wedge cluster randomised controlled trial that was registered with the Australia and New Zealand Clinical Trials Registry (ACTRN12615001016527).

Cost and Visit Duration of Same-Day Access at an Academic Ophthalmology Department vs Emergency Department

Importance

Convenient outpatient access for ophthalmology patients seeking urgent care could offer savings compared with an emergency department (ED) visit.

Objective

To evaluate the costs and visit durations of same-day access (SDA) in an ophthalmology department at an academic medical center vs ED care.

Design, Setting, and Participants

This single-center study was a retrospective quality improvement analysis of an institutional electronic medical record system at the Wilmer Eye Institute clinics and the Johns Hopkins Hospital ED. On June 1, 2015, the Wilmer Eye Institute and Johns Hopkins Hospital initiated an official policy of providing SDA to patients calling for appointments (ie, the same-day project). All ophthalmology clinic locations created same-day appointment slots for at least 1 practitioner. In recognition of seasonal variations in patient visit volumes, the 10 months before implementation (August 1, 2014, to May 31, 2015) were compared with complementary periods in 2015 to 2016 and 2016 to 2017.

Main Outcomes and Measures

The study tabulated encounters, charges, and visit length for outpatients seen on the same day or by previously scheduled appointments. For the ED patients, volume, diagnoses, charges, and length of stay data were collected. The numbers of SDA patients who indicated urgency were tabulated.

Results

The number of SDA patients increased from 22 781 to 26 579 for the first year after SDA implementation. The mean charge was $258 (95% CI, $250-$266; median, $184; interquartile range [IQR], $175-$320), and the mean clinic transit time was 1.55 hours (95% CI, 1.54-1.57 hours; median, 1.28 hours). For patients seeking eye care in the ED, the mean professional fee was $401 (95% CI, $390-$411; median, $360; IQR, $255-$500), the mean (SD) total hospital charge was $1040 ($999) (95% CI, $729-$1079; median, $1002; IQR, $334-$1429), and the mean length of stay was 7.30 hours (95% CI, 7.01-7.57 hours; median, 7.20 hours). The top 4 ophthalmic diagnoses for ED patients were conjunctivitis, cornea abrasion, iritis, and visual loss, which were unchanged after SDA implementation. In calendar year 2017, a total of 4062 SDA patients reported urgency; their estimated savings in charges compared with an ED visit were $580 866 in professional fees and $3 176 484 in hospital charges.

Conclusions and Relevance

Same-day access appears to be less expensive and to require less time in the health care system than a visit to the ED for an ophthalmic diagnosis. Substantial savings in time and money might be achieved if urgent eye care is delivered in the clinic rather than the ED.

Military Health System Access to Care: Performance and Perceptions

Introduction: Access to care (ATC) is an important component of providing quality healthcare. Clinics need to be able to accurately measure access; however, patients’ reports of access may be different from performance-based data gathered using administrative measures. The purpose of this research is to examine the relationship between ATC administrative data and patient survey results. Materials and Methods: This is a retrospective study performed in military medical treatment facilities. Survey data were obtained from the Joint Outpatient Experience Survey (JOES), and administrative data were collected from the Military Health System Data Repository. The data period was from May 2016 through March 2017 for 135 parent Military Treatment Facilities. This study was approved under the Defense Health Agency Internal Review Board (IRB number: CDO-15-2025). The analyses compare JOES ATC measures to administrative ATC measures. Overall correlation analyses and multivariate regression analyses were performed in order to generate observable correlations between access and healthcare measures (both administrative measures and patient survey items). Results: Results show moderate correlations between the facilities’ ATC survey items and administrative measures. These correlations were affected by the composition of the facility patient mix. The patient-based ATC measures from the JOES survey are related to administrative ATC measures collected and monitored by the facilities. In each final regression model, the coefficients for the ATC administrative variables were significant and negative which indicates that as the wait time for an appointment increases, patients’ ratings of the time between scheduling and appointment dates declines and patients’ assessments of being able to see a provider declines as well. Conclusions: Measuring ATC is a vital step in ensuring the health of patients and the provision of high quality care. Both patient surveys and administrative data are widely used for measuring ATC. This study found statistically significant moderate associations between survey and administrative ATC measures, which remained significant even after controlling for patient characteristics of the facilities. These study results suggest that administrative data can provide an accurate assessment of access; however, survey items can be useful for diagnosing potential issues with access, such as call center scheduling and provider availability. Future studies should explore the gaps in research surrounding best practices at facilities which have high patient experience with access, and look at other survey measures related to access, such as telephone resources and web-based communication programs.

Understanding Why Patients No-Show: Observations of 2.9 Million Outpatient Imaging Visits Over 16 Years

PURPOSE

To understand why patients "no-show" for imaging appointments, and to provide new insights for improving resource utilization.

MATERIALS AND METHODS

We conducted a retrospective analysis of nearly 2.9 million outpatient examinations in our radiology information system from 2000 to 2015 at our multihospital academic institution. No-show visits were identified by the "reason code" entry "NOSHOW" in our radiology information system. We restricted data to radiography, CT, mammography, MRI, ultrasound, and nuclear medicine examinations that included all studied variables. These variables included modality, patient age, appointment time, day of week, and scheduling lead time. Multivariate logistic regression was used to identify factors associated with no-show visits.

RESULTS

Out of 2,893,626 patient visits that met our inclusion criteria, there were 94,096 no-shows during the 16-year period. Rates of no-show visits varied from 3.36% in 2000 to 2.26% in 2015. The effect size for no-shows was strongest for modality and scheduling lead time. Mammography had the highest modality no-show visit rate of 6.99% (odds ratio [OR] 5.38, P < .001) compared with the lowest modality rate of 1.25% in radiography. Scheduling lead time greater than 6 months was associated with more no-show visits than scheduling within 1 week (OR 3.18, P < .001). Patients 60 years and older were less likely to miss imaging appointments than patients under 40 (OR 0.70, P < .001). Mondays and Saturdays had significantly higher rates of no-show than Sundays (OR 1.52 and 1.51, P < .001).

CONCLUSION

Modality type and scheduling lead time were the most predictive factors of no-show. This may be used to guide new interventions such as targeted reminders and flexible scheduling.

Getting patients in the door: medical appointment reminder preferences

PURPOSE

Between 23% and 34% of outpatient appointments are missed annually. Patients who frequently miss medical appointments have poorer health outcomes and are less likely to use preventive health care services. Missed appointments result in unnecessary costs and organizational inefficiencies. Appointment reminders may help reduce missed appointments; particular types may be more effective than other types. We used a survey with a discrete choice experiment (DCE) to learn why individuals miss appointments and to assess appointment reminder preferences.

METHODS

We enrolled a national sample of adults from an online survey panel to complete demographic and appointment habit questions as well as a 16-task DCE designed in Sawtooth Software's Discover tool. We assessed preferences for four reminder attributes - initial reminder type, arrival of initial reminder, reminder content, and number of reminders. We derived utilities and importance scores.

RESULTS

We surveyed 251 adults nationally, with a mean age of 43 (range 18-83) years: 51% female, 84% White, and 8% African American. Twenty-three percent of individuals missed one or more appointments in the past 12 months. Two primary reasons given for missing an appointment include transportation problems (28%) and forgetfulness (26%). Participants indicated the initial reminder type (21%) was the most important attribute, followed by the number of reminders (10%). Overall, individuals indicated a preference for a single reminder, arriving via email, phone call, or text message, delivered less than 2 weeks prior to an appointment. Preferences for reminder content were less clear.

CONCLUSION

The number of missed appointments and reasons for missing appointments are consistent with prior research. Patient-centered appointment reminders may improve appointment attendance by addressing some of the reasons individuals report missing appointments and by meeting patients' needs. Future research is necessary to determine if preferred reminders used in practice will result in improved appointment attendance in clinical settings.

Benchmarking the Wilmer general eye services clinics: baseline metrics for surgical and outpatient clinic volume in an educational environment

BACKGROUND

The Wilmer General Eye Services (GES) at the Johns Hopkins Hospital is the clinic where residents provide supervised comprehensive medical and surgical care to ophthalmology patients. The clinic schedule and supervision structure allows for a progressive increase in trainee responsibility, with graduated autonomy and longitudinal continuity of care over the three years of ophthalmology residency training. This study sought to determine the number of cases the GES contributes to the resident surgical experiences. In addition, it was intended to create benchmarks for patient volumes, cataract surgery yield and room utilization as part of an educational initiative to introduce residents to metrics important for practice management.

METHODS

The electronic surgical posting system database was explored to determine the numbers of cases scheduled for patients seen by residents in the GES. In addition, aggregated residents' self-reported Accreditation Council for Graduate Medical Education (ACGME) surgical logs were collected for comparison. Finally transactional databases were queried to determine clinic volumes of new and established patients. The proportion of resident surgeries (1(st) surgeon and assistant) provided by GES patients, cataract surgery yield and new patient rates were calculated. Data was collected from July 1(st), 2014 until March 31(st), 2015 for all 16 residents (6 third year, 5 second year and 5 first year).

RESULTS

The percentage of cataract, oculoplastics, cornea and glaucoma surgeries in which a resident was 1(st) surgeon and the patient came from the GES was 91.3, 76.1, 65.6, and 93.9 respectively. The new patient rate was 28.1% and room utilization was 50.4%. Cataract surgery yield was 29.2 DISCUSSION: The GES provides a significant proportion of primary surgeon opportunities for the residents, and in some instances, the majority of cases. Compared to benchmarks available for private practices, the new patient rate is high while the cataract surgery yield is low. The room utilization is lower than the 85% preferred by the hospital system. These are the first benchmarks of this type for an academic resident ophthalmology practice in the United States.

CONCLUSIONS

Our study suggests that resident-hosted clinics can provide the majority of surgical opportunities for ophthalmology trainees, particulary with regard to cataract cases. However, because our study is the first academic resident practice to publish metrics of the type used in private practices, it is impossible to determine where our clinic stands compared to other training programs. Therefore, the authors strongly encourage ophthalmology training programs to explore and publish practice metrics. This will permit the creation of a benchmarking program that could be used to quantify efforts at enhancing ophthalmic resident education.