Association of Patient and Visit Characteristics With Rate and Timing of Urologic Procedures for Patients Discharged From the Emergency Department With Renal Colic

Importance: Little is known about the timing of urologic interventions in patients with renal colic discharged from the emergency department. Understanding patients\u27 likelihood of a subsequent urologic intervention could inform decision-making in this population. Objectives: To examine the rate and timing of urologic procedures performed after an emergency department visit for renal colic and the factors associated with receipt of an intervention. Design, Setting, and Participants: This retrospective cohort study used the Massachusetts All Payers Claims Database to identify patients 18 to 64 years of age who were seen in a Massachusetts emergency department for renal colic from January 1, 2011, to October 31, 2014, Patients were identified via International Classification of Diseases, Ninth Revision codes, and all medical care was linked, enabling identification of subsequent health care use. Data analysis was performed from January 1, 2017, to December 31, 2018. Main Outcomes and Measures: The main outcome was receipt of urologic procedure within 60 days. Secondary outcomes included rates of return emergency department visit and urologic and primary care follow-up. Results: A total of 66218 unique index visits by 55314 patients (mean [SD] age, 42.6 [12.4] years; 33 590 [50.7%] female; 25 411 [38.4%] Medicaid insured) were included in the study. A total of 5851 patients (8.8%) had visits resulting in admission at the index encounter, and 1774 (2.7%) had visits resulting in a urologic procedure during that admission. Of the 60367 patient visits resulting in discharge from the emergency department, 3018 (5.0%) led to a urologic procedure within 7 days, 4407 (7.3%) within 14 days, 5916 (9.8%) within 28 days, and 7667 (12.7%) within 60 days. A total of 3226 visits (5.3%) led to a subsequent emergency department visit within 7 days and 6792 (11.3%) within 60 days. For the entire cohort (admitted and discharged patients), 39 189 (59.2%) had contact with a urologist or primary care practitioner within 60 days. Having Medicaid-only insurance was associated with lower rates of urologic procedures (odds ratio, 0.70; 95% CI, 0.66-0.74) and urologic follow-up (5.6% vs 8.8%; P \u3c .001) and higher rates of primary care follow-up (59.2% vs 47.2%; P \u3c .001) compared with patients with all other insurance types. Conclusions and Relevance: In this cohort study, most adult patients younger than 65 years who were discharged from the emergency department with a diagnosis of renal colic did not undergo a procedure or see a urologist within 60 days. This finding has implications for both the emergency department and outpatient treatment of these patients

Interpreting Statistics in the Urological Literature

Purpose: Knowledge of statistical terminology and the ability to critically interpret research findings are critical skills in the practice of evidence based medicine. Materials and Methods: We provide a series of nontechnical explanations of basic statistical concepts commonly encountered in the urological literature. In addition, we provide examples of common statistical pitfalls to increase awareness of limitations to consider when applying research findings to practice. Results: Statistical goals encountered in the urological literature can be broadly categorized as summarizing outcome variables, comparing 2 or more groups, measuring association among variables or predicting 1 variable from another. Errors frequently include the use of an inappropriate test for the data type of interest or using statistical testing in a manner that increases the likelihood of false-positive results. Such errors pose a threat to the validity of research findings and they may undermine study conclusions. Conclusions: Editors and reviewers alike should strive for high standards of statistical analysis and reporting, and promote the publication of high quality evidence in the urological literature. The understanding of basic statistical concepts and the principles of the hypothesis testing framework is essential to the critical appraisal process and, therefore, important to all urologists. Statistical literacy should be fostered through educational materials and courses in the urological community. Key Words: urology, statistics, evidence-based medicine K nowledge of statistical terminology and methods has a pivotal role in the conduct of clinical research and it is an essential tool for the urologist critically appraising the literature. 5 Curricular trends in undergraduate and graduate medical education now emphasize a basic knowledge of clinical research and statistical methods as part of a broader preparation for evidence based patient care. 6 -8 Despite these efforts recent evidence suggests that statistical literacy and a knowledge of clinical research methods among urologists may be suboptimal, as among other physicians. Studies in the urological literature and other subspecialties frequently contain statistical errors or they are underpowered. 9 -12 These errors threaten to undermine the validity of published studies and flawed investigations may influence medical practice in undesirable ways. RESULTS Outcome Measures Three types of outcome measures or variables are common in biomedical research, including continuous, categorical and time to event. 15 Continuous variables have values, such that the distance between the values 3 and 5, for example, is the same as the distance between 20 and 22 or the distance between 66 and 68. Examples of continuous measures are age in years, tumor size in cm and length of hospital stay in days. Categorical variables, of which dichotomous and ordinal are special cases, are measures that have 2 or more categories with no intrinsic numerical value, eg renal cell carcinoma histology (clear cell, papillary and other). Dichotomous (binary) variables have only 2 categories, eg side right/left or stone recurrence yes/no. Many specialized statistical procedures, such as logistic regression, are used for the analysis of dichotomous data. Ordinal variables are categorical variables in which the categories can be ordered. Examples in the urology literature are Gleason score and the visual analog pain scale. Time-to-event data are frequently found in oncological studies of mortality or disease recurrence. Examples are time to death or biochemical failure as well as time to stone passage and time to urethral stricture recurrence. 16,17 Summarizing Continuous Data The first question that should arise in the analysis of a continuous outcome variable is whether the data have a normal (also called Gaussian) distribution. Since normal distributions have a bell-shaped symmetry, an approximate assessment of normality can be made by making a histo- In contrast, SEM measures variability in the distribution of sample means from the population mean. Summarizing Nonnormal Continuous Data and Ordinal Data For nonnormal continuous data or ordinal data the median and IQR are often the preferred descriptive statistics. In these cases the median is preferred over the mean because the mean may be affected by outliers or a skewed distribution. For example, let us consider a simple case of 5 men with prostate cancer who have PSA 3.5, 3.5, 4.0, 4.5 and 4.5 ng/ml, respectively. In this case the mean and median are identical (4.0 ng/ml). However, if instead we have a group of men with PSA 3.5, 3.5, 4.0, 4.5 and 15.0 ng/ml, respectively, the mean becomes 6.1, while the median remains unchanged (4.0 ng/ml). In this case when an outlier is present, the median is less affected than the mean. IQR is the range of values from the 25th to the 75th percentile of the group of subjects and it gives the reader a sense of the variability in the data. Although SD characterizes the variance of distribution even for nonnormal distributions, it cannot be interpreted in the same way. SD values are easily interpretable only if the distribution is normal.

The Diagnosis and Management of Patients with Renal Colic across a Sample of US Hospitals: High CT Utilization Despite Low Rates of Admission and Inpatient Urologic Intervention

<div><p>Objectives</p><p>Symptomatic ureterolithiasis (renal colic) is a common Emergency Department (ED) complaint. Variation in practice surrounding the diagnosis and management of suspected renal colic could have substantial implications for both quality and cost of care as well as patient radiation burden. Previous literature has suggested that CT scanning has increased with no improvements in outcome, owing at least partially to the spontaneous passage of kidney stones in the majority of patients. Concerns about the rising medical radiation burden in the US necessitate scrutiny of current practices and viable alternatives. Our objective was to use data from a diverse sample of US EDs to examine rates of and variation in the use of CT scanning, admission, and inpatient procedures for patients with renal colic and analyze the influence of patient and hospital factors on the diagnostic testing and treatment patterns for patients with suspected renal colic.</p><p>Methods</p><p>We conducted a retrospective cohort study of adult patients who received a diagnosis of renal colic via a visit to an ED at 444 US hospitals participating in the Premier Healthcare Alliance database from 2009–2011. We modeled use of CT, admission, and inpatient urologic intervention as functions of both patient characteristics and hospital characteristics.</p><p>Results</p><p>Over the 2-year period, 307,612 patient visits met inclusion criteria. Among these patients, 254,211 (82.6%) had an abdominal CT scan, with 91.5% being non-contrast (“renal protocol”) CT scans. Nineteen percent of visits (58,266) resulted in admission or transfer, and 9.8% of visits (30,239) resulted in a urologic procedure as part of the index visit. On multivariable analysis male patients, Hispanic patients, uninsured patients, and privately insured patients were more likely to have a CT scan performed. Older patients and those covered by Medicare were more likely to be admitted, and once admitted, white patients and privately insured patients were more likely to have a urologic intervention. Only hospital region was associated with variation in CT rates, and this variation was minimal. Region and size of the hospital were associated with admission rates, and hospitals with more practicing urologists had higher intervention rates.</p><p>Conclusions</p><p>In this dataset, the majority of patients did not require admission or immediate intervention. Despite this, the large majority received CT scans, in a cohort representing 15–20% of all US ED visits. The CT rate was minimally variable at the hospital level, but the admission rates varied 2-fold, suggesting that hospital-level factors affect patient management. The high rate of CT usage coupled with the low rate of immediate intervention suggests that further research is warranted to identify patients who are at low risk for an immediate intervention, and could potentially be managed with ultrasound alone, expectant management, or delayed CT.</p></div

Adjusted associations between patient-level characteristics and CT scan use, admission, and inpatient intervention from hierarchical multivariable models.

<p>Adjusted associations between patient-level characteristics and CT scan use, admission, and inpatient intervention from hierarchical multivariable models.</p

Hospital characteristics and distribution of patients.

<p>(417 hospitals).</p

Distribution of risk-adjusted CT rates across hospitals.

<p>Distribution of risk-adjusted CT rates across hospitals.</p

Characteristics of renal colic patients.

<p>(307,612 subjects).</p

Risk-adjusted outcome rates based on the generalized linear regression model by Hospital Characteristics.

<p>Risk-adjusted outcome rates based on the generalized linear regression model by Hospital Characteristics.</p

Selection of sample of patients with renal colic from Premier cohort.

<p>Selection of sample of patients with renal colic from Premier cohort.</p