Quantifying Effect of a Hospital’s Caseload for a Surgical Specialty on That of Another Hospital Using Multi-Attribute Market Segments

Patients in Iowa Counties Lacking Hospitals With Labor and Delivery Services Disproportionately Receive Care at Level III Maternal Care Hospitals When Undergoing Cesarean Delivery: A Retrospective Longitudinal Study

Introduction Many obstetrical patients from rural areas in the United States lack hospitals that provide labor and delivery care. Our objective was to examine the effects of such patients on caseloads of cesarean deliveries at Iowa hospitals with level III maternal care, as defined by the Iowa Department of Public Health (e.g., with obstetric anesthesiologists). Methods This retrospective longitudinal study included every discharge with cesarean delivery in the state of Iowa from October 2015 through June 2021. There were N=60,534 such deliveries from 76 hospitals, of which three were level III, and the rest were level I or II. Poisson regression models with robust variance estimation and controlling for geography, maternal risk factors, and insurance, were used to evaluate the binary outcome of whether patients received care at the university level III hospital in Eastern Iowa, or not. Similar models were also developed for care at the two private level III hospitals in Central Iowa, or not. Differences in the mean probabilities of receiving care at the level III hospitals were then estimated using logistic regression, with results reported in units of changes in cases per week at the hospitals. Results Statewide, the university level III hospital performed 7.4% of the cesarean deliveries, and the two private level III hospitals performed 23.4%. Patients from counties in which no cesarean deliveries were performed during the quarter of the year when they underwent a cesarean delivery disproportionately received care at level III hospitals versus levels I and II hospitals. Lower 99% confidence limits for incremental risk ratios were 1.46 and 4.20, respectively. Cesarean deliveries among patients residing in counties where no hospital had a labor and delivery ward were distributed unequally between the counties of the hospitals with level III maternal care. There were approximately 1.09 (standard error 0.10) extra cesarean deliveries per week at the university hospital versus 5.81 (standard error 0.11) at the private hospitals. The 1.09 vs 5.81 difference was caused, in part, by the effects of insurance and other hospitals with similar services. Conclusions Patients residing in counties without labor and delivery care disproportionately go to level III hospitals. These results can help anesthesiologists, obstetricians, and analysts at hospitals with large tertiary (level III) programs interpret their annual increases in total obstetric anesthesia activity.

Surgeon Variation in Perioperative Opioid Prescribing and Medium- or Long-term Opioid Utilization after Total Knee Arthroplasty: A Cross-sectional Analysis

BACKGROUND

Whether a particular surgeon's opioid prescribing behavior is associated with prolonged postoperative opioid use is unknown. This study tested the hypothesis that the patients of surgeons with a higher propensity to prescribe opioids are more likely to utilize opioids long-term postoperatively.

METHODS

The study identified 612,378 Medicare fee-for-service patients undergoing total knee arthroplasty between January 1, 2011, and December 31, 2016. "High-intensity" surgeons were defined as those whose patients were, on average, in the upper quartile of opioid utilization in the immediate perioperative period (preoperative day 7 to postoperative day 7). The study then estimated whether patients of high-intensity surgeons had higher opioid utilization in the midterm (postoperative days 8 to 90) and long-term (postoperative days 91 to 365), utilizing an instrumental variable approach to minimize confounding from unobservable factors.

RESULTS

In the final sample of 604,093 patients, the average age was 74 yr (SD 5), and there were 413,121 (68.4%) females. A total of 180,926 patients (30%) were treated by high-intensity surgeons. On average, patients receiving treatment from a high-intensity surgeon received 36.1 (SD 35.0) oral morphine equivalent (morphine milligram equivalents) per day during the immediate perioperative period compared to 17.3 morphine milligram equivalents (SD 23.1) per day for all other patients (+18.9 morphine milligram equivalents per day difference; 95% CI, 18.7 to 19.0; P < 0.001). After adjusting for confounders, receiving treatment from a high-intensity surgeon was associated with higher opioid utilization in the midterm opioid postoperative period (+2.4 morphine milligram equivalents per day difference; 95% CI, 1.7 to 3.2; P < 0.001 [11.4 morphine milligram equivalents per day vs. 9.0]) and lower opioid utilization in the long-term postoperative period (-1.0 morphine milligram equivalents per day difference; 95% CI, -1.4 to -0.6; P < 0.001 [2.8 morphine milligram equivalents per day vs. 3.8]). While statistically significant, these differences are clinically small.

CONCLUSIONS

Among Medicare fee-for-service patients undergoing total knee arthroplasty, surgeon-level variation in opioid utilization in the immediate perioperative period was associated with statistically significant but clinically insignificant differences in opioid utilization in the medium- and long-term postoperative periods.

EDITOR’S PERSPECTIVE

Building a Brain Tumor Practice: Objective Analysis of Referral Patterns and Implications for the Growth of a Subspecialty Surgical Program

Introduction Growth of surgical caseload among specialties with a large contribution margin is an important financial objective for hospitals. In this study, we examined the diversity of referral patterns to a neurosurgeon over an eight-year interval and examined practice attributes related to surgical growth. Methods The electronic records of all patients undergoing an intracranial surgical procedure between August 2011 and August 2019 by an academic neurosurgeon were reviewed retrospectively. The Herfindahl-Hirschman index (HHI) was used to assess the distribution of referrals among community physicians who referred such patients; a value of HHI <0.15 indicates diversity. The yearly HHI trend was evaluated using meta-regression. Results The neurosurgeon's brain surgery caseload progressively increased on an annual basis from 1.4 to 12.5 cases per week between 2012 and 2018. Among the 1540 cases referred by 1775 different physicians, 78% were from three counties in southeast Florida and 8.1% from two counties in southwest Florida. The HHI declined between 2013 and 2018 by 0.023 per year (0.0046 standard error [SE], p = 0.0073) with the estimated value 0.0063 (0.0014 SE) < 0.15 in 2018 (p < 0.0001). The findings indicate that the base of referring physicians was highly diverse and that growth in caseload was accompanied by significantly less concentration of referrals. Conclusion Surgical growth in the neurosurgeon's practice resulted from a small number of referrals from many physicians, not from many referrals from a small number of physicians. Few physicians referred a sufficient number of patients to warrant attribution of the referral itself to personal knowledge of their patients' eventual outcomes. Rather, factors promoting timely access to patient care appear to have been the driving force for growth.

The Risks to Patient Privacy from Publishing Data from Clinical Anesthesia Studies

In this article, we consider the privacy implications of posting data from small, randomized trials, observational studies, or case series in anesthesia from a few (e.g., 1-3) hospitals. Prior to publishing such data as supplemental digital content, the authors remove attributes that could be used to re-identify individuals, a process known as "anonymization." Posting health information that has been properly "de-identified" is assumed to pose no risks to patient privacy. Yet, computer scientists have demonstrated that this assumption is flawed. We consider various realistic scenarios of how the publication of such data could lead to breaches of patient privacy. Several examples of successful privacy attacks are reviewed, as well as the methods used. We survey the latest models and methods from computer science for protecting health information and their application to posting data from small anesthesia studies. To illustrate the vulnerability of such published data, we calculate the "population uniqueness" for patients undergoing one or more surgical procedures using data from the State of Texas. For a patient selected uniformly at random, the probability that an adversary could match this patient's record to a unique record in the state external database was 42.8% (SE < 0.1%). Despite the 42.8% being an unacceptably high level of risk, it underestimates the risk for patients from smaller states or provinces. We propose an editorial policy that greatly reduces the likelihood of a privacy breach, while supporting the goal of transparency of the research process.

“Opt Out” and Access to Anesthesia Care for Elective and Urgent Surgeries among U.S. Medicare Beneficiaries

Background

In 2001, the Centers for Medicare and Medicaid Services issued a rule allowing U.S. states to “opt out” of the regulations requiring physician supervision of nurse anesthetists in an effort to increase access to anesthesia care. Whether “opt out” has successfully achieved this goal remains unknown.

Methods

Using Medicare administrative claims data, we examined whether “opt out” reduced the distance traveled by patients, a common measure of access, for patients undergoing total knee arthroplasty, total hip arthroplasty, cataract surgery, colonoscopy/sigmoidoscopy, esophagogastroduodenoscopy, appendectomy, or hip fracture repair. In addition, we examined whether “opt out” was associated with an increase in the use of anesthesia care for cataract surgery, colonoscopy/sigmoidoscopy, or esophagogastroduodenoscopy. Our analysis used a difference-in-differences approach with a robust set of controls to minimize confounding.

Results

“Opt out” did not reduce the percentage of patients who traveled outside of their home zip code except in the case of total hip arthroplasty (2.2% point reduction; P = 0.007). For patients travelling outside of their zip code, “opt out” had no significant effect on the distance traveled among any of the procedures we examined, with point estimates ranging from a 7.9-km decrease for appendectomy (95% CI, −19 to 3.4; P = 0.173) to a 1.6-km increase (95% CI, −5.1 to 8.2; P = 0.641) for total hip arthroplasty. There was also no significant effect on the use of anesthesia for esophagogastroduodenoscopy, appendectomy, or cataract surgery.

Conclusions

“Opt out” was associated with little or no increased access to anesthesia care for several common procedures.

Predicting orthopedic surgeons' preferences for peripheral nerve blocks for their patients

BACKGROUND

A 2002 survey of 468 Canadian orthopedic surgeons found that the "two principal reasons regional anesthesia is not favored" are "delays in operating rooms" and "unpredictable success." We reanalyzed the data from the study to evaluate whether these concerns were the best predictors of an individual surgeon's willingness to use peripheral nerve blocks for their patients.

METHODS

Of the five procedures included in the survey, three had relevant questions for our reanalysis of the results: arthroscopic shoulder surgery, arthroscopic anterior cruciate ligament reconstruction, and total knee replacement.

RESULTS

A surgeon's preference for peripheral nerve block for him or herself strongly predicted his or her anesthetic preference for patients (all P < 0.001). Concordance rates were 89% for arthroscopic shoulder surgery, 87% for anterior cruciate ligament reconstruction, and 93% for total knee replacement. There was almost no incremental predictive value for the surgeon's preference for patients from the surgeon's perception of the times to perform a block (P > or = 0.27) or perception of block success rate (P > or = 0.30). There was also almost no direct predictive value for the surgeon's preference for patients from the surgeon's perception of the times to perform a block (Kendall's tau < or = 0.04, P > or = 0.28) or perception of block success rate (Kendall's tau < or = 0.02, P > or = 0.24). An economically important percentage of surgeons (37%, 95% confidence interval: 32%-41%) would choose a peripheral nerve block for their own surgery for some, but not all, of the procedures (i.e., for 1 or 2 versus 0 or 3).

CONCLUSIONS

A surgeon's preference for peripheral nerve blocks for his or her own surgery predicted a surgeon's preference for his or her patients. Perceptions of delays and success rate did not add sufficient incremental information to the surgeon's preferences to be of economic importance. These results are important to better forecast the net economic impact on an anesthesia group of a regional block team.

Application of a Similarity Index to State Discharge Abstract Data to Identify Opportunities for Growth of Surgical and Anesthesia Practices

INTRODUCTION

Most surgical and anesthesia groups are interested in expanding their practices and recruiting more patients. Methods have been developed to help hospitals identify surgical specialties with the potential for growth by determining whether the hospital is performing fewer of certain types of procedures than expected in a given specialty. However, these methods are not appropriate for physicians who may practice at more than one hospital and want to determine the potential for growth in their regions.

METHODS

We examined potential markets for growth of surgical and anesthesia practices in Iowa and New York State using state discharge abstract data. Several patient demographic groups and several surgical specialties were examined. Each state was divided into regions, and data were analyzed three ways: (1) A similarity index compared each region to the rest of the state. (2) The number of procedures performed on patients who left their home regions for care was determined. (3) A similarity index compared procedures performed on patients who left their home regions for care with procedures performed on patients who remained within their home regions.

RESULTS

The methods successfully identified several geographic regions with previously unrecognized growth potential. Access to care was limited in these regions. The methods correctly showed few opportunities for growth in geographic regions where expansion was already known to be unlikely.

CONCLUSIONS

A count of the number of procedures performed on patients who left their home regions, in combination with the similarity index, is a useful method for screening state discharge abstract data to identify geographic regions where surgical and anesthesia practices could grow.

Tactical Increases in Operating Room Block Time Based on Financial Data and Market Growth Estimates from Data Envelopment Analysis

BACKGROUND

Data envelopment analysis (DEA) is an established technique that hospitals and anesthesia groups can use to understand their potential to grow different specialties of inpatient surgery. Often related decisions such as recruitment of new physicians are made promptly. A practical challenge in using DEA in practice for this application has been the time to obtain access to and preprocess discharge data from states.

METHODS

A case study is presented to show how results of DEA are linked to financial analysis for purposes of deciding which surgical specialties should be provided more resources and institutional support, including the allocation of additional operating room (OR) block time on a tactical (1 yr) time course. State discharge abstract databases were used to study how to perform and present the DEA using data from websites of the United States' (US) Healthcare Cost and Utilization Project (HCUPNet) and Census Bureau (American FactFinder).

RESULTS

DEA was performed without state discharge data by using census data with federal surgical rates adjusted for age and gender. Validity was assessed based on multiple criteria, including: satisfaction of statistical assumptions, face validity of results for hospitals, differentiation between efficient and inefficient hospitals on other measures of how much surgery is done, and correlation of estimates of each hospital's potential to grow the workload of each of eight specialties with estimates obtained using unrelated statistical methods.

CONCLUSIONS

A hospital can choose specialties to target for expanded OR capacity based on its financial data, its caseloads for specific specialties, the caseloads from hospitals previously examined, and surgical rates from federal census data.