Combining Drive Time and Urologist Density to Understand Access to Urologic Care

Effect of Distance From Fertility Center on Utilization of Fertility Preservation Referral in Men

PURPOSE

Fertility preservation (FP) is underutilized in males with cancer or other diseases requiring gonadotoxic therapies. We sought to evaluate whether patient distance from FP center affected rates of providing a semen analysis after referral.

MATERIALS AND METHODS

We performed a retrospective analysis of all males who were referred for FP at a single institution between 2013 and 2021. A multiple logistic regression model was conducted with semen sample submission as the variable of interest. Predictor variables were disease type, distance, and payment method. Secondary outcomes were number of semen samples submitted and number of vials collected.

RESULTS

Records of 461 males referred to our center were analyzed. Of these patients, 326 (71%) provided a semen sample after referral and 135 (30%) did not. Further distance from our center was associated with lower odds of submitting a semen sample (OR, 0.85; 95% CI, 0.75 to 0.97; P < .05). For patients who submitted at least one sample, distance did not affect the total number of samples submitted but was associated with a small increase in total vials cryopreserved.

CONCLUSION

Men referred for FP exhibit a high rate of sperm cryopreservation. Further distance from FP center was associated with decreased odds to provide semen sample after referral. Our model estimated a 15% decrease in odds of collection with every doubling of distance from our center. Efforts must be made to improve FP utilization for patients traveling far distances, but distance alone should not preclude referral.

How far will they go? Distance and driving times that north American men travel to see a reproductive urologist

Male factor infertility affects about 50% of infertile couples. However, male factor infertility is largely under-evaluated due to multiple reasons. This study is to determine the time men travel for fertility evaluation, and factors associated with driving longer. Data from the Andrology Research Consortium were analysed. Driving distance and time were calculated by comparing "patient postal code" with "clinic postal code", then stratified into quartiles. Patients with the longest driving times (> 75th percentile [Q4]) were compared with those having shorter driving times. Logistic regression analysis was used to identify factors associated with longer driving times. Sixteen clinics and 3029 men were included. The median driving distance was 18.1 miles, median driving time was 32 min, and Q4 driving time was 49 min. Factors correlated with having Q4 driving time were age > 30 years, native Indian and Caucasian race, body mass index (BMI) > 30 kg/m² , history of miscarriage, children with previous partner, self-referral, prior vasectomy, and prior marijuana use. On logistic regression, males aged < 30 years were more likely to be in Q4 for driving time versus older males. Blacks and Asians were less likely to travel further than Caucasians. Overweight/obese men, those having children with previous partner, and with prior vasectomy were more likely to be in Q4 travelling time. Factors correlated with longer driving times include younger age, native Indian and Caucasian race, higher BMI, children with prior partner, and prior vasectomy. These may reflect groups that drive long distances for reproductive care. The study provides an opportunity to better access these groups and minimise their barriers to fertility care.

Using GIS to Understand Healthcare Access Variations in Flood Situation in Surabaya

This paper proposes to identify the variation of accessibility to healthcare facilities based on vulnerability assessments of floods by using open source data. The open source data comprises Open Street Map (OSM), world population, and statistical data. The accessibility analysis is more focused on vulnerable populations that might be affected by floods. Therefore, a vulnerability assessment is conducted beforehand to identify the location where the vulnerable population is located. A before and after scenario of floods is applied to evaluate the changes of healthcare accessibility. A GIS Network Analyst is chosen as the accessibility analysis tool. The results indicate that the most vulnerable population lives in the Asemrowo district. The service area analysis showed that 94% of the West of Surabaya was well-serviced in the before scenario. Otherwise, the decrement of service area occurs at the city center in the after scenario. Thus, the disaster manager can understand which vulnerable area is to be more prioritized in the evacuation process.

Geriatric conditions and treatment burden following diagnosis of non-muscle- invasive bladder cancer in older adults: A population-based analysis

INTRODUCTION

Treatment burden is emerging as an important patient-centered outcome for older adults with cancer who concurrently manage geriatric conditions. Our objective was to evaluate the contribution of geriatric conditions to treatment burden in older adults with non-muscle invasive bladder cancer (NMIBC).

METHODS

We identified 73,395 Medicare beneficiaries age 66+ diagnosed with NMIBC (Stage <II) in SEER-Medicare (2001-2014). The primary outcome was treatment burden, defined as health system contact days in the year following NMIBC diagnosis. Explanatory variables were the following geriatric conditions: multimorbidity (≥ 2 chronic conditions), functional dependency, falls, depression, cognitive impairment, weight loss, and urinary incontinence. We used negative binomial regression to model the association between individual geriatric conditions and treatment burden while adjusting for covariates.

RESULTS

At baseline, 64% had multimorbidity and median 3 conditions (IQR 0-5). Prevalence of other geriatric conditions ranged from 5.9%-15.2%. Adjusted mean health system contact was 8.9 days (95% CI 8.6-9.2). Multimorbidity had the largest effect size (adjusted mean 11.8 contact days (95% CI 8.3-8.8)). Each additional chronic condition conferred a 13% increased average number of health system contact (adjusted IRR 1.132, 95% CI 1.129-1.135). Regardless of number of chronic conditions, rural patients consistently had more treatment burden than urban counterparts.

DISCUSSION

In this population-based cohort of older NMIBC patients, multimorbidity and rurality were strongly associated with treatment burden in the year following NMIBC diagnosis. These findings highlight the need for interventions that reduce treatment burden due to geriatric conditions among the growing population of older adults with cancer, particularly in rural areas.