Incarceration and emergency department visit frequency as predictors for missing day of cataract surgery at County hospital

Abstract

Background:

Understanding the factors associated with patient no-shows is essential for healthcare providers to develop strategies to optimize patient care, as these can delay care and increase cost. This retrospective study aimed to identify factors associated with higher likelihood of patients missing their scheduled cataract surgery appointments at a county hospital.

Methods:

A retrospective chart review was performed using data collected from the surgery schedule and electronic medical record on patients aged 18–100 years scheduled for cataract surgery at Eskenazi Hospital between January 1, 2022, and December 31, 2022. Logistic regression was used to compare factors of age, race, ethnicity, primary spoken and written language, insurance status, best-corrected visual acuity and number of admissions to the emergency department of the same hospital in the preceding year to attendance of cataract surgery on scheduled date.

Results:

This study found that in the studied population (n = 242), being incarcerated was a statistically significant predictor of missing the scheduled cataract surgery appointment (OR 6.14, 95% CI 1.14–33.16, p = 0.035). In addition, having at least one emergency department visit in the prior year (OR 6.50, CI 1.83–23.1, p = 0.004) was found to be significant, with a greater difference in patients who had at least three emergency department visits in the prior year (OR 13.2, CI 3.21–52.6, p < 0.001). Other studied factors were not found to be statistically significant predictors of missing the surgery appointment, although having best-corrected vision of count fingers or worse neared statistical significance of predicting missing cataract surgery appointment. These findings may potentially direct targeted intervention strategies to improve access to cataract care.

Plain language summary

Factors Predicting Missing Day of Cataract Surgery at County Hospital

Purpose of this study

Patients missing their scheduled day of surgery can result in delays in care and increased healthcare costs. This study aimed to identify potential risk factors associated with a patient missing their scheduled cataract surgery. Understanding such risk factors may help reduce future missed surgery days, improve patient outcomes, and/or reduce healthcare costs.

How this study was done

Researchers in this study gathered data from patients aged 18–100 who were scheduled for cataract surgery over a 1 year period. Potential risk factors were identified and data were analyzed to see if one or more of the identified risk factors were more likely to be seen in a patient who missed their scheduled surgery date.

Findings from this study

The study showed that patients experiencing incarceration were more likely to also miss their scheduled surgery date and that patients who missed their scheduled surgery date were more likely to have visited the emergency department in the year leading up to their surgery date. No other identified potential risk factors showed association with missing one’s surgery date, though being able to only count fingers or detect hand motion or light before surgery appeared to approach association.

Implications of study findings

This study allows a greater understanding of who may be more likely to miss their scheduled surgery date in the population served by the hospital where these patients have received care. With this knowledge, informed interventions can be made to prevent or reduce missed surgery dates in patients experiencing incarceration or those who have more emergency room visits in the year prior, ultimately improving quality of care for the patients and financial waste by the hospital.

Keywords

Cataract surgery incarceration no-show demographics best-corrected visual acuity

Introduction

Cataract surgery is one of the most commonly performed surgical procedures worldwide and is crucial in improving visual function and quality of life for millions of individuals.¹ The need for cataract surgery will continue to grow over the coming decades, due to aging populations worldwide. However, the efficiency and effectiveness of cataract delivery services are contingent upon patient compliance and attendance on the scheduled day of surgery. Patient no-shows, where patients fail to appear for their scheduled surgery, can disrupt surgical schedules, increase costs, and have implications for patient outcomes such as discontinued care process, longer wait times, and potential increase in emergency department visits.^2,3 Disease progression and delayed diagnoses associated with surgery no-shows can increase costs of care for both patients and health systems, reliance on public health insurance, and risk of complications in future surgeries.^4
–7 Delayed access to elective surgery can similarly result in losses in quality of life and productivity for the affected patient, which can have significant societal implications when considered at-scale.

Understanding the factors associated with patient no-shows is essential for healthcare providers to develop strategies to minimize their occurrence and optimize patient care. Previous studies have identified various factors associated with patient no-show rates, including demographic factors such as age, sex, and socioeconomic status, though evidence examining their relationship to outpatient cataract surgery attendance is limited.^8
–10

Sex disparities in healthcare utilization and attendance for medical appointments have been reported in various medical specialties. Several studies have shown that women are more likely to attend medical appointments than men.^8,10 However, the evidence regarding sex differences in no-show rates for surgical procedures, such as cataract surgery, is inconsistent. Clarifying the impact of sex on no-show rates may help develop targeted interventions to improve attendance and outcomes.

Age is a well-established factor associated with healthcare utilization and attendance. Older adults often have more complex healthcare needs and may face barriers such as mobility issues, transportation difficulties, and caregiver availability, which can affect their ability to attend medical appointments.^9,11 While those who receive cataract surgery are typically elderly, average age for cataract surgery has been found to vary based on geographic region by nearly 20 years difference.¹² For example, patients in Lansing, Michigan and Aurora, Illinois, on average, received cataract surgery at 59.9–60.1 years, while those in Rochester, New York and Binghamton, New York received cataract surgery at 77.0–79.6 years.¹² Previous studies have examined the impact of age on attendance for medical appointments; however, research specifically investigating the influence of age on no-show rates for cataract surgery has not been well-reported in the literature.

Several studies have found that non-English speakers are less likely to show up to their appointment.^13
–16 Effective communication between healthcare providers and patients is essential for ensuring optimal patient care. Language barriers can hinder communication and contribute to misunderstandings, leading to decreased patient satisfaction and potentially compromising patient outcomes. In a multicultural society, it is essential to explore whether language barriers contribute to no-show rates for surgical procedures such as cataract surgery, particularly in settings serving populations with diverse linguistic backgrounds.

Previous studies have shown African American and Hispanic patients to have higher rates of no show in medical clinics^17,18 and less likely to attend glaucoma follow-up visits at a county hospital.¹⁹ Patients identifying as black were less likely than their white counterparts to undergo cataract surgery at 5 years from diagnosis.²⁰ Visual Acuity and No-Show Rates Visual impairment due to cataracts can significantly impact an individual's quality of life, independence, and ability to perform daily activities. Best-corrected visual acuity (BCVA) is an important clinical measure used to assess the severity of visual impairment and determine the need for cataract surgery.²¹ While the relationship between visual impairment and healthcare utilization has been explored in previous studies,^22,23 the impact of BCVA on no-show rates for cataract surgery could benefit from further investigation.

Patients who frequently visit the emergency department may have complex healthcare needs and face barriers to accessing timely and appropriate care. Previous research has shown that patients with high rates of emergency department utilization may also be more likely to miss scheduled medical appointments.²⁴ The aim of this retrospective review is to identify demographic and clinical factors associated with patient nonattendance among patients undergoing cataract surgery at this county hospital between January 1, 2022, and December 31, 2022. Specifically, we investigated the influence of sex, age, primary spoken and written language, best-corrected visual acuity (BCVA) at the preoperative appointment, and the number of emergency department visits in the prior year on patient attendance on day of cataract surgery. With this knowledge we hope to develop targeted interventions to optimize patient attendance, improve surgical efficiency, and enhance patient outcomes.

Methods

Study design

This retrospective cohort study aimed to compare various demographic and preoperative factors of patients who attended their scheduled cataract surgery at a county hospital versus those who missed their scheduled surgery. Data were extracted from scheduling records, patient information records, and operating logs within the hospital electronic medical record (EMR) system. No-showing day of surgery was determined by comparing the surgical schedule to evidence of attending appointment on this day in the EMR; because the schedule is updated until 24 h before surgery, this included cancelations within 24 h of surgery. Best-corrected visual acuity was collected from documented preoperative visit notes within this EMR. Patients who missed day of surgery were contacted via phone call with an IRB-approved survey to qualitatively assess potential barriers to care. These results were analyzed and reported separately. The reporting of this study conforms to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement²⁵ [SUPPLEMENTARY FILE 1].

Study population

The study included patients aged 18–100 who were scheduled for cataract surgery at Eskenazi Hospital between January 1, 2022, and December 31, 2022 (n = 242). Patients with combined procedures (glaucoma surgery, retina surgery, etc.) were excluded, as were patients whose preoperative visits were completed at a different location. If a patient underwent two cataract surgeries within the study period, only the first surgery was included. Two cohorts were defined: patients who attended their scheduled cataract surgery appointment (n = 231) and those who missed their scheduled cataract surgery appointment or rescheduled within 24 h (n = 11). Due to incarceration, death and other difficulties in correspondence, only two survey responses from this cohort were collected.

Preoperative workflow

The workflow for patients undergoing cataract surgery for the time studied was as follows. Patients were initially examined in clinic and approved for cataract surgery by an attending ophthalmologist. They would then return for a preoperative visit with the operating resident for examination and lens calculations. After meeting with the resident, the patient would speak with a scheduler in the same clinic, who provided a written form with their surgery date and time in their preferred language. Automated calls in the patients’ preferred language occurred at 72, 48, and 24 h prior to the day of surgery. In addition, the patients were contacted the day before surgery by a member of the preoperative team, with use of an interpreter if indicated, to confirm the time of surgery for the following day as well as to discuss preoperative preparation, such as oral intake, medication instructions, postoperative appointment dates and other questions the patient may have. Patients with interpreter needs were identified by inclusion of preferred spoken/written language in the EMR, each of which was included in the cohort comparisons below.

Data collection

Data were collected retrospectively from EMRs in Epic Hyperspace, from Epic Systems Corporation. The following variables were extracted for each patient: age, sex, race (self-declared), ethnicity (self-declared), preferred spoken language (self-declared), preferred written language (self-declared), best-corrected visual acuity at the preoperative visit, and number of emergency department visits in the 1 year preceding the date of the scheduled surgery. No records were excluded due to missing values. The demographic information from the patient population gathered was compared to the demographic information of the surrounding county (Marion) and Medicare data in the same year in order to assess for differences in the treated population and local and national populations. The average age of patients undergoing cataract surgery in Marion County as a whole in the year 2022 is not available for comparison to this study population.

Outcome measures

The primary outcome measure was the odds of attending cataract surgery, calculated using odds ratios (ORs) with 95% confidence intervals (CI). Secondary outcomes included reasons for nonattendance from the qualitative survey.

Statistical analysis

Descriptive statistics were used to summarize demographic and clinical characteristics of the study cohorts. OR was used in univariate analysis using MDCalc software after consultation with members of the Department of Biostatistics at Indiana University. Multiple logistic regression was conducted using R and RStudio Version 4.2.1 to explore the relationship between significant predictor variables (independent variables) and odds of not attending date of surgery (dependent variable). LogMAR was used to represent visual acuity as a continuous variable (logMAR = −1 × log₁₀(Snellen denominator/Snellen numerator)).

Ethical considerations

This study was conducted in accordance with the principles of the Declaration of Helsinki. Institutional Review Board (IRB) approval was obtained from Indiana University (Protocol #17934) prior to data collection. Patient confidentiality was maintained throughout the study by anonymizing all collected data.

Results

Baseline patient demographics

The results for this study are summarized in Table 1. The study population scheduled for cataract surgery at Eskenazi Hospital (n = 242) had an average age of 63.8 (± 11.8) years. Sex distribution showed a slight predominance of females (50.8%) compared to males (49.2%). Race and ethnicity were reported separately, with most common self-reported races including white (46.7%) and black (33.1%); 31.4% of this study population separately self-reported ethnicity as Hispanic. When examining language preference, a substantial proportion of the present study population identified as having a non-English preference (35.1%) in either spoken (35.1%) or written (33.5%) communication. Comparable data in the Medicare population was not available. Languages encountered in this study included American Sign Language, Burmese, English, French, Haitian Creole, Nepalese, Punjabi, Spanish, Tigrinya and Yoruba.

Table 1.

Odds ratio calculations for missing day of surgery compared with prevalence of specified factors. BCVA = best-corrected visual acuity in operative eye, ED = emergency department, MCR = Medicare (any), MCD = Medicaid.

	n = 242	Odds Ratio	95% CI	p-value
Demographics	Men	1.86	0.53–6.52	0.333
	Women	0.538	0.15–1.88	0.333
	Black	1.17	0.33–4.10	0.812
	White	1.39	0.41–4.69	0.595
	Hispanic	0.812	0.21–3.15	0.763
	Other	0.645	0.08–5.22	0.681
Language	Spoken Language Other than English	0.681	0.18–2.64	0.579
	Written Language Other than English	0.736	0.19–2.85	0.657
	Spanish	0.958	0.25–3.72	0.95
Insurance Status	Inmate	6.14	1.14–33.16	0.035
	Medicare (MCR) only	0.697	0.04–12.48	0.806
	Medicaid (MCD) only	2.81	0.14–57.76	0.502
	Health Advantage	0.967	0.25–3.76	0.961
	Private	0.459	0.06–3.68	0.463
Preoperative Vision	BCVA better than 20/40	0.756	0.09–6.14	0.793
	20/40–20/70	0.221	0.03–1.78	0.154
	20/80–20/400	0.899	0.23–3.49	0.878
	Counting fingers (CF) or worse	3.13	0.92–10.62	0.067

Cohort comparisons

Inmate status was found to have a statistically significant association with missing day of surgery (OR 6.14, 95% CI 1.14–33.16, p = 0.035). In addition, having at least one emergency department visit in the prior year was found to be associated with missing day of surgery (OR 6.50, CI 1.83–23.1, p = 0.004) with this association even stronger for patients who had at least three emergency department visits in the prior year (OR 13.2, CI 3.21–52.6, p < 0.001). The interpretation of these associations should be tempered, given the small sample sizes producing relatively wide confidence intervals. Other studied factors (sex, race, ethnicity, BCVA, language and insurance status excluding that provided by detention facilities) were not found to be statistically significant predictors of missing the surgery appointment. A statistically significant proportion of the variance in odds of not attending surgery was explained by the multiple logistic regression model including logMAR and number of ED visits within 1 year, with X2 (2) = 9.595, p = 0.008 (Akaike information criterion (AIC) = 85.9). Initially, the odds of not attending surgery were significantly predicted by logMAR (β = 0.88, SE = 0.38, z = 2.30, p = 0.021) and number of ED visits within 1 year (β = 0.06, SE = 0.03, z = 2.11, p = 0.035). Assumption of linearity was met for logMAR (p > 0.05), but not for number of ED visits within 1 year (p = 0.004). To address non-linearity, number of ED visits within 1 year was log-transformed using the natural log. The new model maintained significance (X2 (2) = 17.31, p = 0.001) and appeared to be a better fit of the data with AIC reduced to 78.1. In the log-transformed model, the odds of not attending surgery were significantly predicted by loge(ED visits within 1 year) (β = 1.06, SE = 0.31, z = 3.43, p < 0.001), while logMAR showed marginally significant prediction of odds of missing surgery (β = 0.77, SE = 0.41, z = 1.91, p = 0.057). While this trends toward significance, it should not be overinterpreted. These results indicate that, while controlling for logMAR, number of ED visits within 1 year is a strong predictor of likelihood of missing surgery, with a 2.89 (eβ) increase in odds of missing surgery with each one-unit increase in loge(ED visits within 1 year). Assumption of linearity was met for logMAR and loge(ED visits within 1 year) within 1 year (p > 0.05). Durbin-Watson testing showed independence of residuals (DW = 1.99, p = 0.446). Upward deviations in the upper tail on Q-Q plot evaluating normality in the distribution of residuals indicate the presence of some outliers. This was further supported by violation of the equal variances of residuals assumption, with residuals showing greater variance at greater predicted probabilities of not attending surgery. The outlier of 71 ED visits within 1 year was identified using Cook’s Distance testing and determined to be a true value. A sensitivity test conducting the model without this outlier showed an increase in the magnitude of the regression coefficient and degree of significance for number of ED visits within 1 year (β = 0.21, SE = 0.08, z = 2.59, p = 0.009), while ability of logMAR to significantly predict odds of not attending surgery was lost (β = 0.64, SE = 0.41, z = 1.55, p = 0.121). Although this number of admissions within a one-year period is not typical, the decision to continue with interpretation of the model which includes the outlier was made in an effort to preserve real-world observations. The loss of significance logMAR value suggests this variable may not be a robust predictor of odds of not attending surgery and its significance in the full model should not be overinterpreted Figure 1.

Figure 1.

Predicted probability (P = elog-odds/(1 + elog-odds)) of missing surgery as a function of log-transformed number of ED visits within 1 year.

Survey results

Of the 11 patients who missed day of surgery, two survey responses were obtained. Survey was not attempted for seven patients due to status at the time of the study as deceased (n = 5) or incarcerated (n = 2); as well, one had a listed reason for surgery cancelation already available in the EMR. Three patients were contacted; two consented to complete the survey and one was unable to be contacted. For the patient with the cancelation on day of surgery, uncontrolled hypertension was cited in the EMR. Of the patients who consented to complete the survey, one stated that they had no transportation on day of surgery; the other attributed the cancelation to a change in medical status. A qualitative analysis was not possible due to the low number of respondents and the limited information obtained, though thematically these results were consistent with factors identified in the formal analysis as well as those noted in the discussion. Specifically, systemic barriers including scheduling and transportation may be present in incarcerated individuals and a higher rate of ED visits in the nonattendance cohort would be consistent with cancelation for uncontrolled medical illness and a 45% 2-year mortality in this group.

Discussion

The purpose of this study was to attempt to identify subpopulations within the county hospital population who were at higher risk of no-showing the day of cataract surgery, with patients who were incarcerated and having at least 1 emergency department visit in the previous year being at highest risk. The study population at our county hospital as a whole was found to have notable differences compared to Wu et al’s study of Medicare data from 2002 to 2012,²⁶ whose group also studied cataract surgery attendance, as well as the Marion County Census data from 2022.²⁷ The population undergoing cataract surgery at our county hospital differed in potentially important ways from the Medicare data ²⁶ and the general Marion County population for the same year.²⁷ Our population of those scheduled for cataract surgery was on average younger at 63.8 years compared to 73.7 years reported in the Medicare data.²⁶ The present study had a less pronounced difference in females compared to males scheduled for cataract surgery than the difference in the Medicare study (female 59.1%).²⁶ The population in the present study was more likely to identify as black or Hispanic than cataract patients in the Medicare population ²⁶ or the residents of Marion County.²⁷ In addition, a significant portion preferred a non-English language (35.1% spoken) compared to the Marion County study showing 6.2% of population with limited English language proficiency.²⁸ These differences between our population, Marion County, and Medicare are summarized in Table 2.

Table 2.

Demographic characteristics of patients included in this study and comparisons to Marion County Census Data (2022) and Medicare Part B patient data.

	Study Population (n = 242)	Marion County^27,28	Medicare Data
Age at time of surgery (years)	63.8 ± 11.8	No data	73.7
Male (%)	49.2%	48.6%	40.9%
Female (%)	50.8%	51.4%	59.1%
White (%)	46.7%	55.7%	87.6%
Black (%)	33.1%	28.8%	7.3%
Other (%)	2.5%	4.2%	3.5%
Hispanic (%)	31.4%	10.9%	1.6%
Non-English Preferred	35.1% Spoken33.5% Written	6.2%(limited English proficiency)	No data

Interestingly, despite these differences in our county hospital population from these reference populations, no racial, ethnic or linguistic factors were found to correlate to a greater odds of missing day of surgery. Similarly, no insurance status, including Health Advantage (prior program for uninsured patients in Marion County), was found to be significantly correlated with missing day of surgery. Summarized, despite the patient population in this study having numerous demographic differences compared to reference populations, none of these differences appear to correlate to a greater odds of missing surgery. It is possible that the limited sample of no-shows (n = 11) resulted in the study being under-powered to detect more subtle differences reported in prior studies looking at these factors in other clinical contexts.^{9–16,29–31}

Emergency department visits in the prior year in patients in the present study for any reason were found to be most highly correlated with missing day of surgery, with this association even closer when examining patients who visited the emergency department more than 3 times in the preceding year. It is not clear whether number of emergency room visits functions as a marker for severity of comorbidities, access to care in general, or if there is another correlation yet to be elucidated; however, the 45% 2-year mortality rate in the group who missed surgery and the fact that of those who missed surgery and were able to be contacted or evaluated through the EMR, 2/3 patients missed due to changes in medical status may both support the hypothesis that these patients may in general be sicker. These patients may be identified in the future as a group warranting closer follow-up and improved access to primary care; however, greater study would be indicated before further interpretation would be valid. Further studies may make use of additional indices of health such as comorbid metabolic or chronic diseases obtained through hospital problem lists or chart review, body mass index (BMI), Montreal Cognitive Assessment (MoCA), Charlson Comorbidity Index or other functional aging index in order to help identify patients who may require greater assistance in attending appointments.³²

Although not initially an aim of this study, incarcerated status was reflected in the insurance of our patients and was found to be correlated with a greater odds of missing day of surgery. Barriers to care in this population differ substantially from the non-incarcerated outpatient population, most saliently in that these patients are unable to schedule or transport themselves. Incarceration is associated with decreased access to care and greater loss to clinic follow-up and challenges to medication adherence relative to patients not experiencing incarceration.³³ Incarcerated patients have also been found to experience greater rates of post-surgical complications among various surgical specialties.³⁴ Access of incarcerated individuals to ophthalmic care at our site, especially those already scheduled, is therefore worth investigating further.

Limitations of this study include retrospective design, very limited survey results obtained from the survey portion and proximity to the start of the covid-19 pandemic, when operating volume at this location for elective procedures was dramatically reduced. Whether this was the patient’s first cataract surgery (including outside of the study period) was not assessed, which could impact the patient’s familiarity with the clinic and preoperative process and confound the results if patients with less familiarity were less likely to attend. Similarly, binocular vision was not assessed, as the patient’s functional vision could potentially be a confounding factor; for instance, a patient with bilateral BCVA at CF or worse may perceive a greater benefit to attending surgery or, alternatively, may have more difficulty navigating the preoperative process without assistance. In addition, no adjustment was made for patients with multifactorial vision loss; those with concurrent ocular disease limiting postoperative visual prognosis may not behave similarly to those whose vision loss is presumed to be secondary to cataract only. Finally, lead time to surgery date was not evaluated. Previous studies have indicated that longer wait times to outpatient procedures may increase the risk of nonattendance.^35
–37 It is possible that factors evaluated in this study, including delays caused by obtaining insurance coverage through hospital programs, may contribute to longer wait times and therefore act as a confounding variable. While it was not examined in this study, future studies may consider the use of ZIP codes as a surrogate for socioeconomic status, though conclusions made using this method may be limited due to significant socioeconomic heterogeneity within given ZIP codes, outdated or incomplete information including shifting demographic, or varied access to transportation within a code designation.

Studies examining social determinants of health and their relationship to missing clinic can be found for many specialties^{10,13
–18,29
–31} as well as in ophthalmology.¹⁹ Looking specifically at ophthalmology services, one study through the UK health service examined cancelation of all ophthalmic cases in a one-year period, with the most common causes of cancelation of cataract surgery being miscellaneous (22%), failure of patient to attend (16%), patient unsafe for anesthesia (16%), or patient sickness (13%),³⁸ though further analysis within and between subgroups was not performed. In one Chinese study, common reasons for same-day surgical cancelation included patient absence, systemic illness and inadequate preoperative evaluation³⁹ as well as refusal to be seen;⁴⁰ similar findings have been reported in India.⁴¹ Reasons for missing cataract surgery in rural Africa were different, however, with more prevalent concerns regarding cost and fear of the procedure itself noted in Swaziland⁴² and Ethiopia.⁴¹ Notably, systemic reasons for missing surgery would be expected to vary between and potentially within countries, making these studies critical to perform locally.

Although studies examining ophthalmic surgery attendance in the United States are much more limited, factors known to predict missing clinic visits such as transportation barriers, health literacy or socioeconomic status may be just as relevant to study in cataract surgery patients in similar county hospital settings. Wongtangman et al. developed a prediction tool for cancelation within 24 h of any surgery,⁴³ though given the wide variety of possible systemic barriers as well as wide variability in preoperative practice patterns for cataract surgery,^12,43 this may not be generalizable to all populations. In addition, cataract surgery often does not require general anesthesia⁴³ and can take as little as 3–8 min operating time at a refractive practice;⁴⁴ these different requirements may result in different predominating problems to assess than other elective surgeries. Given the functional and economic burden to patients with visually significant cataracts¹, it is critical that systemic problems limiting access to care be evaluated at all levels.

For the patient subpopulations in this study identified to be at greater risk of missing cataract surgery, next steps may include targeted interventions for the identified subpopulations at risk of missing day of surgery; specifically those who are incarcerated and those with ED visits in the preceding year. For the former, evaluation of the process of scheduling with and transport from facilities may elucidate points of system failures, with revisions in the process assessed for improved compliance rates. The patients in the latter group may benefit from closer planning with particular attention to any noted barriers to care that can be addressed or mitigated prior to day of surgery, if at all possible.

This study suggests incarcerated patients and those with at least one emergency room visit were more likely to miss their day of cataract surgery; if generalizable, this would suggest potential populations with greater difficulty obtaining treatment for the most common cause of reversible blindness. However, more work needs to be done to assess potential reasons for disparities in cataract care among the population at large to ensure equitable access to surgical care.

Supplemental Material

sj-docx-1-map-10.1177_27550834251359809 – Supplemental material for Incarceration and emergency department visit frequency as predictors for missing day of cataract surgery at County hospital

Supplemental material, sj-docx-1-map-10.1177_27550834251359809 for Incarceration and emergency department visit frequency as predictors for missing day of cataract surgery at County hospital by Patrick Wurster, Margaret Tharp, Kathleen Ho and Jennifer Eikenberry in The Journal of Medicine Access

Footnotes

Acknowledgements

Not-Applicable.

ORCID iD

Patrick Wurster

Ethical considerations

The Indiana University Institutional Review Board approved the study 17934 and consent to participate was waived because of minimal risk to chart review.

Author contributions

Patrick Wurster: Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Project administration; Writing – original draft; Writing – review & editing.

Margaret Tharp: Data curation; Formal analysis; Investigation; Writing – original draft; Writing – review & editing.

Kathleen Ho: Data curation; Formal analysis; Writing – original draft; Writing – review & editing.

Jennifer Eikenberry: Conceptualization; Data curation; Investigation; Supervision; Writing – review & editing.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Dr. Jennifer Eikenberry receives a stipend from Dompe for unrelated research on graft vs host disease.

Data availability statement

The data that support the findings of this study are available on request from the corresponding author, JE. The data are not publicly available due to their containing information that could compromise the privacy of research participants.

The Journal of Medicine Access Incarceration and Emergency Department Visit Frequency as Predictors for Missing Day of Cataract Surgery at County Hospital

The Journal of Medicine Access

Supplemental material

Supplemental material for this article is available online.

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