Development of a disease-based hospital-level diagnostic intensity index.

OBJECTIVES: Low-value care is associated with increased healthcare costs and direct harm to patients. We sought to develop and validate a simple diagnostic intensity index (DII) to quantify hospital-level diagnostic intensity, defined by the prevalence of advanced imaging among patients with selected clinical diagnoses that may not require imaging, and to describe hospital characteristics associated with high diagnostic intensity. METHODS: We utilized State Inpatient Database data for inpatient hospitalizations with one or more pre-defined discharge diagnoses at acute care hospitals. We measured receipt of advanced imaging for an associated diagnosis. Candidate metrics were defined by the proportion of inpatients at a hospital with a given diagnosis who underwent associated imaging. Candidate metrics exhibiting temporal stability and internal consistency were included in the final DII. Hospitals were stratified according to the DII, and the relationship between hospital characteristics and DII score was described. Multilevel regression was used to externally validate the index using pre-specified Medicare county-level cost measures, a Dartmouth Atlas measure, and a previously developed hospital-level utilization index. RESULTS: This novel DII, comprised of eight metrics, correlated in a dose-dependent fashion with four of these five measures. The strongest relationship was with imaging costs (odds ratio of 3.41 of being in a higher DII tertile when comparing tertiles three and one of imaging costs (95 % CI 2.02-5.75)). CONCLUSIONS: A small set of medical conditions and related imaging can be used to draw meaningful inferences more broadly on hospital diagnostic intensity. This could be used to better understand hospital characteristics associated with low-value care.

Development of a hospital coding intensity measure based on sepsis diagnoses.

Significant variation in coding intensity among hospitals has been observed and can lead to reimbursement inequities and inadequate risk adjustment for quality measures. Reliable tools to quantify hospital coding intensity are needed. We hypothesized that coded sepsis rates among patients hospitalized with common infections may serve as a useful surrogate for coding intensity and derived a hospital-level sepsis coding intensity measure using prevalence of "sepsis" primary diagnoses among patients hospitalized with urinary tract infection, cellulitis, and pneumonia. This novel measure was well correlated with the hospital mean number of discharge diagnoses, which has historically been used to quantify hospital-level coding intensity. However, it has the advantage of inferring hospital coding intensity without the strong association with comorbidity that the mean number of discharge diagnoses has. Our measure may serve as a useful tool to compare coding intensity across institutions.

Patient, provider, and system-level factors associated with preoperative cardiac testing: A systematic review.

BACKGROUND: Overuse of preoperative cardiac testing contributes to high healthcare costs and delayed surgeries. A large body of research has evaluated factors associated with variation in preoperative cardiac testing. However, patient, provider, and system-level factors associated with variation in testing have not been systematically studied. OBJECTIVE: To conduct a systematic review to better delineate the patient, provider, and system-level factors associated with variation in preoperative cardiac testing. METHODS: We included studies of an adult US population evaluating a patient, provider, or system-level factor associated with variation in preoperative cardiac testing for noncardiac surgery since 2012. Our search strategy used terms related to preoperative testing, diagnostic cardiac tests, and care variation with Ovid MEDLINE and Embase from inception through January 2023. We extracted study characteristics and factors associated with variation and qualitatively analyzed them. We assessed risk of bias using the Newcastle-Ottawa Scale and Evidence Project Risk of Bias tool. RESULTS: Twenty-eight articles met inclusion criteria. Older age and higher comorbidity were strongly associated with higher-intensity testing. The evidence for provider and system-level covariates was weaker. However, there was strong evidence that a focus on primary care and away from preoperative clinic and cardiac consultations was associated with less testing and that interventions to reduce low-value testing can be successful. CONCLUSIONS: There is significant interprovider and interhospital variation in preoperative cardiac testing, the correlates of which are not well-defined. Further work should aim to better understand these factors.

The Local Market of Major Teaching Hospitals.

OBJECTIVE: The purpose of this study was to describe the local communities served by major teaching hospitals. METHODS: Using a dataset of hospitals around the United States provided by the Association of American Medical Colleges, we identified major teaching hospitals (MTHs) using the Association of American Medical Colleges' definition of those with an intern-to-resident bed ratio above 0.25 and more than 100 beds. We defined the local geographic market surrounding these hospitals as the Dartmouth Atlas hospital service area (HSA). Using MATLAB R2020b software, data from each ZIP Code Tabulation Area from the US Census Bureau's 2019 American Community Survey 5-Year Estimate Data tables were grouped by HSA and attributed to each MTH. One-sample t tests were used to evaluate for statistical differences between the HSAs and the US average data. We further stratified the data into regions as defined by the US Census Bureau: West, Midwest, Northeast, and South. One-sample t tests were used to evaluate for statistical differences between MTH HSA regional populations with their respective US regional population. RESULTS: The local population surrounding 299 unique MTHs covered 180 HSAs and was 57% White, 51% female, 14% older than 65 years old, 37% with public insurance coverage, 12% with any disability, and 40% with at least a bachelor's degree. Compared with the overall US population, HSAs surrounding MTHs had higher percentages of female residents, Black/African American residents, and residents enrolled in Medicare. In contrast, these communities also showed higher average household and per capita income, higher percentages of bachelor's degree attainment, and lower rates of any disability or Medicaid insurance. CONCLUSIONS: Our analysis suggests that the local population surrounding MTHs is representative of the wide-ranging ethnic and economic diversity of the US population that is advantaged in some ways and disadvantaged in others. MTHs continue to play an important role in caring for a diverse population. To support and improve policy related to the reimbursement of uncompensated care and care of underserved populations, researchers and policy makers must work to better delineate and make transparent local hospital markets.

Reducing Overuse by Healthcare Systems: A Positive Deviance Analysis.

BACKGROUND: Healthcare in the USA is increasingly delivered by large healthcare systems that include one or more hospitals and associated outpatient practices. It is unclear what role healthcare systems play in driving or preventing overutilization of healthcare services in the USA. OBJECTIVE: To learn how high-value healthcare systems avoid overuse of services DESIGN: We identified "positive deviant" health systems using a previously constructed Overuse Index. These systems have much lower-than-average overuse of healthcare services. We confirmed that these health systems also delivered high-quality care. We conducted semi-structured interviews with executive leaders of these systems to validate a published framework for understanding drivers of overuse. PARTICIPANTS: Leaders at select healthcare systems in the USA. INTERVENTIONS: None APPROACH: We developed an interview guide and conducted semi-structured interviews. We iteratively developed a code book. Paired reviewers coded and reconciled each interview. We analyzed the interviews by applying constant comparative techniques. We mapped the emergent themes to provide the first empirical data to support a previously developed theoretical framework. KEY RESULTS: We interviewed 15 leaders from 10 diverse healthcare systems. Consistent with important domains from the overuse framework, themes from our study support the role of clinicians and patients in avoiding overuse. The leaders described how they create a culture of professional practice and how they modify clinicians' attitudes to facilitate high-value practices. They also described how their patients view healthcare consumption and the characteristics of their patient populations allowed them to practice high-value medicine. They described the role of quality metrics, insurance plan ownership, and alternative payment model participation as encouraging avoidance of overuse. CONCLUSIONS: Our qualitative analysis of positive deviant health systems supports the framework that is in the published literature, although health system leaders also described their financial structures as another important factor for reducing overuse and encouraging high-value care delivery.

Healthcare utilization differences between an apixaban-based and warfarin-based strategy for acute venous thromboembolism in patients with end-stage kidney disease.

INTRODUCTION: Evidence suggests that an apixaban-based strategy to treat acute venous thromboembolism (VTE) in patients with End-Stage Kidney Disease (ESKD) may be safer than a warfarin-based strategy. Apixaban has an additional advantage of not requiring bridging with heparin which often necessitates long hospitalizations for patients with ESKD. We sought to determine if an apixaban-based strategy is associated with less healthcare utilization than a warfarin-based strategy. MATERIAL AND METHODS: We employed a new-user, active-comparator retrospective cohort study using inverse probability of treatment weights (IPTW) to adjust for confounding demographic and clinical variables. Patients with ESKD newly initiated on either apixaban or warfarin for an acute VTE between 2014 and 2018 in the United States Renal Data System were included. Outcomes were presence of index hospitalization, length of index hospitalization, total hospital days, total hospital days excluding index hospitalization, total emergency department (ED) visits that did not result in hospitalization, and total skilled nursing facility days. RESULTS: At six months, patients who received apixaban were less likely to have an index hospitalization, had a shorter index hospitalization (median of 4.0 vs 8.0 days, p < 0.001), and had fewer total hospital days. The IPTW and index year-adjusted incidence rate ratios of total hospital days at one, three, and six months were 0.83 (95 % confidence intervals (CI) 0.79-0.86), 0.84 (95 % CI 0.81-0.88), and 0.88 (95 % CI 0.83-0.92) for apixaban compared to warfarin. CONCLUSION: Among patients with ESKD and VTE, resource utilization for an apixaban-based strategy appears to be lower than for a warfarin-based strategy.

Safety and effectiveness of apixaban versus warfarin for acute venous thromboembolism in patients with end-stage kidney disease: A national cohort study.

BACKGROUND: Patients with end-stage kidney disease (ESKD) are at significantly increased risk for both thrombosis and bleeding relative to those with normal renal function. The optimal therapy of venous thromboembolism (VTE) in patients with ESKD is unknown. OBJECTIVE: To compare the safety and effectiveness of apixaban relative to warfarin in patients with ESKD and acute VTE. DESIGN, SETTING AND PARTICIPANTS: New-user, active-comparator retrospective United States population-based cohort with inverse probability of treatment weighting, using the United States Renal Data System data from 2014 to 2018. We included adults with ESKD on hemodialysis or peritoneal dialysis who were newly initiated on apixaban or warfarin for an acute VTE. MAIN OUTCOME AND MEASURES: The coprimary outcomes were major bleeding, recurrent VTE, and all-cause mortality within 6 months of anticoagulant initiation. Secondary outcomes were intracranial hemorrhage and gastrointestinal bleeding. The primary analyses were based on intent-to-treat defined by the first drug received and accounted for competing risks of death. Sensitivity analyses included varied follow-up time, as-treated analyses, and dose-specific apixaban subgroups. RESULTS: The apixaban and warfarin cohorts included 2302 and 9263 patients, respectively. Apixaban was associated with a lower risk of major bleeding (hazard ratio [HR] 0.81, 95% confidence interval [CI]: 0.70-0.94), intracranial bleeding (HR 0.69, 95% CI 0.48-0.98), and gastrointestinal bleeding (HR 0.82, 95% CI 0.69-0.96). Recurrent VTE and all-cause mortality were not significantly different between the groups. CONCLUSION: Apixaban was associated with a lower risk of bleeding relative to warfarin when used to treat acute VTE in patients with ESKD on dialysis.

Characterizing the Relationship Between Hospital Google Star Ratings, Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) Scores, and Quality.

Google searches for hospitals typically yield a Google star rating (GSR). These ratings are an important source of information for consumers. The degree to which GSRs are associated with traditional quality measures has not been evaluated recently. We sought to characterize the relationship between a hospital's GSR, its Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) scores, and Centers for Medicare and Medicaid Services (CMS) quality measures. We found a moderate association between a hospital's GSR and its HCAHPS score. The relationship between a hospital's GSR and CMS quality measures was statistically significant, but the magnitude was quite low. Our findings suggest that consumers should not use GSRs as a hospital quality proxy.

Characterizing the Relationship Between Payer Mix and Diagnostic Intensity at the Hospital Level.

BACKGROUND: Overuse of diagnostic testing in the hospital setting contributes to high healthcare costs, yet the drivers of diagnostic overuse in this setting are not well-understood. If financial incentives play an important role in perpetuating hospital-level diagnostic overuse, then hospitals with favorable payer mixes might be more likely to exhibit high levels of diagnostic intensity. OBJECTIVES: To apply a previously developed hospital-level diagnostic intensity index to characterize the relationship between payer mix and diagnostic intensity. DESIGN: Cross-sectional analysis SUBJECTS: Acute care hospitals in seven states MAIN MEASURES: We utilized a diagnostic intensity index to characterize the level of diagnostic intensity at a given hospital (with higher index values and tertiles signifying higher levels of diagnostic intensity). We used two measures of payer mix: (1) a hospital's ratio of discharges with Medicare and Medicaid as the primary payer to those with a commercial insurer as the primary payer, (2) a hospital's disproportionate share hospital ratio. KEY RESULTS: A 5-fold increase in the Medicare or Medicaid to commercial insurance ratio was associated with an adjusted odds ratio of 0.24 (95% CI 0.16-0.36) of being in a higher tertile of the intensity index. A ten percentage point increase in the disproportionate share hospital ratio was associated with an adjusted odds ratio of 0.56 (95% CI 0.42-0.74) of being in a higher intensity index tertile. CONCLUSIONS: At the hospital level, a favorable payer mix is associated with higher diagnostic intensity. This suggests that financial incentives may be a driver of diagnostic overuse.

Changing patterns of use of implantable cardiac monitors from 2011 to 2018 for a large commercially-insured U.S. population.

ABSTRACT: Implantable cardiac monitors (ICMs) provide long-term electrocardiographic monitoring for a number of indications. However, frequencies of use by indication and temporal changes have not been characterized on a national scale. We sought to characterize overall use and changes between 2011 and 2018. We used generalized linear models to characterize the incidence rate per 1,000,000 patient-quarters at risk and an autoregressive integrated moving average model to account for autocorrelation in this time series data. We studied commercially-insured patients and their insured dependents in the IBM MarketScan Commercial Database who had an ICM placed. We described the characteristics of individuals who received ICMs and the frequency of placements into 3 guideline concordance groups. We estimated the mean change per quarter in ICM placements (mean quarterly change in incidence rate per 1,000,000 patient-quarters at risk) for quarter (Q)1 2011 through Q1 2014, Q1 2014 to Q2 2014, and Q2 2014 through Q4 2018 for each guideline concordance group. The most common indications for categorizable ICM placement were syncope (24%), atrial fibrillation (11%), and stroke (11%). For each of the 3 guideline concordance groups except guideline unaddressed inpatient ICM placements, there was a significant increase in use either during the Q1 2014 to Q2 2014 or the Q2 2014 through Q4 2018 periods. A significant portion of ICM placements were for indications that lack strong evidence, such as established atrial fibrillation. The incidence of ICM placement for most of the indications and settings increased after miniaturization and technical improvements.

Characterizing the relationship between diagnostic intensity and quality of care.

OBJECTIVES: The relationship between diagnostic intensity and quality of care has not been well-characterized at the hospital level. We performed an exploratory analysis to better delineate this relationship using a hospital-level diagnostic overuse index and accepted hospital quality metrics (readmissions and mortality). METHODS: We previously developed and published a hospital-level diagnostic overuse index. A hospital's overuse index value (which ranges from 0 to 0.986, with larger numbers indicating more overuse) was our predictor variable of interest. The outcome variables were excess readmission ratios and mortality rates for common medical conditions, which CMS publicly reports. The model controlled for Elixhauser comorbidity score, hospital bed size, hospital teaching status, and random effects that vary by state. RESULTS: We did not find a statistically significant relationship between our overuse index and the quality measures we evaluated. CONCLUSIONS: The lack of a significant relationship between diagnostic intensity and quality, at least as measured by our overuse index and the tested quality metrics, suggests that well-targeted efforts to reduce diagnostic overuse in hospitals may not adversely impact quality of care.

Development of a Simple Index to Measure Overuse of Diagnostic Testing at the Hospital Level Using Administrative Data.

OBJECTIVE: We developed a diagnostic overuse index that identifies hospitals with high levels of diagnostic intensity by comparing negative diagnostic testing rates for common diagnoses. METHODS: We prospectively identified candidate overuse metrics, each defined by the percentage of patients with a particular diagnosis who underwent a potentially unnecessary diagnostic test. We used data from seven states participating in the State Inpatient Databases. Candidate metrics were tested for temporal stability and internal consistency. Using mixed-effects ordinal regression and adjusting for regional and hospital characteristics, we compared results of our index with three Dartmouth health service area-level utilization metrics and three Medicare county-level cost metrics. RESULTS: The index was comprised of five metrics with good temporal stability and internal consistency. It correlated with five of the six prespecified overuse measures. Among the Dartmouth metrics, our index correlated most closely with physician reimbursement, with an odds ratio of 2.02 (95% CI, 1.11-3.66) of being in a higher tertile of the overuse index when comparing tertiles 3 and 1 of this Dartmouth metric. Among the Medicare county-level metrics, our index correlated most closely with standardized costs of procedures per capita, with an odds ratio of 2.03 (95% CI, 1.21-3.39) of being in a higher overuse index tertile when comparing tertiles 3 and 1 of this metric. CONCLUSIONS: We developed a novel overuse index that is preliminary in nature. This index is derived from readily available administrative data and shows some promise for measuring overuse of diagnostic testing at the hospital level.

Differences in Opioid Prescribing Among Generalist Physicians, Nurse Practitioners, and Physician Assistants.

OBJECTIVE: To determine if there are differences in opioid prescribing among generalist physicians, nurse practitioners (NPs), and physician assistants (PAs) to Medicare Part D beneficiaries. DESIGN: Serial cross-sectional analysis of prescription claims from 2013 to 2016 using publicly available data from the Centers for Medicare and Medicaid Services. SUBJECTS: All generalist physicians, NPs, and PAs who provided more than 10 total prescription claims between 2013 and 2016 were included. These prescribers were subsetted as practicing in a primary care, urgent care, or hospital-based setting. METHODS: The main outcomes were total opioid claims and opioid claims as a proportion of all claims in patients treated by these prescribers in each of the three settings of interest. Binomial regression was used to generate marginal estimates to allow comparison of the volume of claims by these prescribers with adjustment for practice setting, gender, years of practice, median income of the ZIP code, state fixed effects, and relevant interaction terms. RESULTS: There were 36,999 generalist clinicians (physicians, NPs, and PAs) with at least one year of Part D prescription drug claims data between 2013 and 2016. The number of adjusted total opioid claims across these four years for physicians was 660 (95% confidence interval [CI] = 660-661), for NPs was 755 (95% CI = 753-757), and for PAs was 812 (95% CI = 811-814). CONCLUSIONS: We find relatively high rates of opioid prescribing among NPs and PAs, especially at the upper margins. This suggests that well-designed interventions to improve the safety of NP and PA opioid prescribing, along with that of their physician colleagues, could be especially beneficial.

Frequency and Predictors of Polypharmacy in US Medicare Patients: A Cross-Sectional Analysis at the Patient and Physician Levels.

BACKGROUND: Polypharmacy in older patients increases the risk of medication-related adverse events and can be a marker of unnecessary care. OBJECTIVES: The aim of this study was to describe the frequency of polypharmacy among patients 65 years of age or older and identify factors associated with the occurrence of patient-level and physician-level polypharmacy. METHODS: We performed a cross-sectional analysis of 100% Medicare claims data from January 1, 2016 to December 31, 2016. All patients with continuous Medicare coverage (Parts A, B, and D) throughout 2016 who were 65 years of age or older and who were prescribed at least one medication for at least 30 days were included in the analysis. Each patient was attributed to the primary care physician who prescribed them the most medications. Physicians treating fewer than ten patients were excluded. We defined polypharmacy based on the highest number of concurrent medications at any point during the year. We used hierarchical linear regression to study patient- and physician-level characteristics associated with high prescribing rates. RESULTS: We identified 25,747,560 patients attributed to 147,879 primary care physicians. The patient-level mean [standard deviation (SD)] concurrent medication rate was 5.6 (3.3), and the physician-level mean (SD) was 5.6 (1.1). A total of 6108 physicians (4.1% of sample) had a mean concurrent number of medications greater than two SDs above the physician-level mean. At the patient level in the adjusted model, a history of HIV/AIDS, diabetes mellitus, solid organ transplant, and systolic heart failure were the comorbidities most strongly associated with polypharmacy. The relative difference in number of medications associated with these comorbidities were 1.89, 1.39, 1.32, and 1.06, respectively. At the physician level, increased time since medical school graduation and smaller practice size were associated with lower rates of polypharmacy. CONCLUSIONS: Patterns of high prescribing to older patients is common and measurable at the physician level. Addressing high outlier prescribers may represent an opportunity to reduce avoidable harm and excessive costs.

Contemporary Rates of Preoperative Cardiac Testing Prior to Inpatient Hip Fracture Surgery.

Hip fracture is a common reason for urgent inpatient surgery. In the past few years, several professional societies have identified preoperative echocardiography and stress testing for noncardiac surgeries as low-value diagnostics. We utilized data on hospitalizations with a primary diagnosis of hip fracture surgery between 2011 and 2015 from the State Inpatient Databases (SID) of Maryland, New Jersey, and Washington, combined with data on hospital characteristics from the American Hospital Association (AHA). We found that the rate of preoperative ischemic testing is surprisingly but encouragingly low (stress tests 1.1% and cardiac catheterizations 0.5%), which is consistent with studies evaluating the outpatient utilization of these tests for low-and intermediate-risk surgeries. The rate of echocardiograms was 12.6%, which was higher than other published reports. Our findings emphasize the importance of ensuring that quality improvement efforts are directed toward areas where quality improvement is, in fact, needed.

Characteristics of Syncope Admissions Among Hospitals of Varying Teaching Intensity.

OBJECTIVES: Previous work suggests that hospitals' teaching status is correlated with readmission rates, cost of care, and mortality. The degree to which teaching status is associated with the management of syncope has not been studied extensively. We sought to characterize the relation between teaching status and inpatient syncope management. METHODS: We created regression models to characterize the relation between teaching status and cardiac ischemic evaluations (cardiac catheterization and/or stress test) during syncope admissions. Admissions with a primary diagnosis of syncope in Maryland and Kentucky between 2007 and 2014 were included. RESULTS: The dataset included 71,341 syncope admissions at 151 hospitals. Overall, 15% of patients had an ischemic evaluation. There was a significantly lower likelihood of an ischemic evaluation at major teaching hospitals relative to nonteaching hospitals (adjusted odds ratio 0.75, 95% confidence interval 0.71-0.79), but a higher likelihood of an ischemic evaluation at minor teaching hospitals (adjusted odds ratio 1.21, 95% confidence interval 1.16-1.25). CONCLUSIONS: By definition, the syncope admissions included were unexplained or idiopathic cases, and thus likely to be lower-risk syncope cases. Those with a known etiology are coded by the cause of syncope, as dictated by coding guidelines. It is likely that many of these ischemic evaluations represent low-value care. Financial incentives and processes of care at major teaching hospitals may be driving this trend, and efforts should be made to better understand and replicate these at minor teaching and nonteaching hospitals.

Differences in Routine Laboratory Ordering Between a Teaching Service and a Hospitalist Service at a Single Academic Medical Center.

OBJECTIVES: Studies have shown that the overutilization of laboratory tests ("labs") for hospitalized patients is common and can cause adverse health outcomes. Our objective was to compare the ordering tendencies for routine complete blood counts (CBC) and chemistry panels by internal medicine residents and hospitalists. METHODS: This observational study included a survey of medicine residents and hospitalists and a retrospective analysis of labs ordering data. The retrospective data analysis comprised patients admitted to either the teaching service or nonteaching hospitalist service at a single hospital during 2014. The survey asked residents and hospitalists about their practices and preferences on labs ordering. The frequency and timing of one-time and daily CBC and basic chemistry panel ordering for teaching service and hospitalist patients were obtained from our data warehouse. The average number of CBCs per patient per day and chemistry panels per patient per day was calculated for both services and multivariate regression was performed to control for patient characteristics. RESULTS: Forty-four of 120 (37%) residents and 41 of 53 (77%) hospitalists responded to the survey. Forty-four (100%) residents reported ordering a daily CBC and chemistry panel rather than one-time labs at patient admission compared with 22 (54%) hospitalists (P < 0.001). For CBCs, teaching service patients averaged 1.72/day and hospitalist service patients averaged 1.43/day (P < 0.001). For basic chemistry panels, teaching service patients averaged 1.96/day and hospitalist service patients averaged 1.78/day (P < 0.001). Results were similar in multivariate regression models adjusting for patient characteristics. CONCLUSIONS: Residents' self-reported and actual use of CBCs and chemistry panels is significantly higher than that of hospitalists in the same hospital. Our results reveal an opportunity for greater supervision and improved instruction of cost-conscious ordering practices.