Guideline-discordant inhaler regimens after COPD hospitalization: associations with rurality, drive time to care, and fragmented care - a United States cohort study

Background

Many patients receive guideline-discordant inhaler regimens after chronic obstructive pulmonary disease (COPD) hospitalization. Geography and fragmented care across multiple providers likely influence prescription of guideline-discordant inhaler regimens, but these have not been comprehensively studied. We assessed patient-level differences in guideline-discordant inhaler regimens by rurality, drive time to pulmonary specialty care, and fragmented care.

Methods

Retrospective cohort analysis using national Veterans Health Administration (VA) data among patients who received primary care and prescriptions from the VA. Patients hospitalized for COPD exacerbation between 2017 and 2020 were assessed for guideline-discordant inhaler regimens in the subsequent 3 months. Guideline-discordant inhaler regimens were defined as short-acting inhaler/s only, inhaled corticosteroid (ICS) monotherapy, long-acting beta-agonist (LABA) monotherapy, ICS + LABA, long-acting muscarinic antagonist (LAMA) monotherapy, or LAMA + ICS. Rural residence and drive time to the closest pulmonary specialty care were obtained from geocoded addresses. Fragmented care was defined as hospitalization outside the VA. We used multivariable logistic regression models to assess associations between rurality, drive time, fragmentated care, and guideline-discordant inhaler regimens. Models were adjusted for age, sex, race/ethnicity, Charlson Comorbidity Index, Area Deprivation Index, and region.

Findings

Of 33,785 patients, 16,398 (48.6%) received guideline-discordant inhaler regimens 3 months after hospitalization. Rural residents had higher odds of guideline-discordant inhalers regimens compared to their urban counterparts (adjusted odds ratio [aOR] 1.18 [95% CI: 1.12-1.23]). The odds of receiving guideline-discordant inhaler regimens increased with longer drive time to pulmonary specialty care (aOR 1.38 [95% CI: 1.30-1.46] for drive time >90 min compared to <30 min). Fragmented care was also associated with higher odds of guideline-discordant inhaler regimens (aOR 1.56 [95% CI: 1.48-1.63]).

Interpretation

Rurality, long drive time to care, and fragmented care were associated with greater prescription of guideline-discordant inhaler regimens after COPD hospitalization. These findings highlight the need to understand challenges in delivering evidence-based care.

Funding

NIHNCATS grants KL2TR002492 and UL1TR002494.

Prediction of In-hospital Mortality Among Intensive Care Unit Patients Using Modified Daily Laboratory-based Acute Physiology Score, Version 2

BACKGROUND

Mortality prediction for intensive care unit (ICU) patients frequently relies on single ICU admission acuity measures without accounting for subsequent clinical changes.

OBJECTIVE

Evaluate novel models incorporating modified admission and daily, time-updating Laboratory-based Acute Physiology Score, version 2 (LAPS2) to predict in-hospital mortality among ICU patients.

RESEARCH DESIGN

Retrospective cohort study.

PATIENTS

ICU patients in 5 hospitals from October 2017 through September 2019.

MEASURES

We used logistic regression, penalized logistic regression, and random forest models to predict in-hospital mortality within 30 days of ICU admission using admission LAPS2 alone in patient-level and patient-day-level models, or admission and daily LAPS2 at the patient-day level. Multivariable models included patient and admission characteristics. We performed internal-external validation using 4 hospitals for training and the fifth for validation, repeating analyses for each hospital as the validation set. We assessed performance using scaled Brier scores (SBS), c -statistics, and calibration plots.

RESULTS

The cohort included 13,993 patients and 107,699 ICU days. Across validation hospitals, patient-day-level models including daily LAPS2 (SBS: 0.119-0.235; c -statistic: 0.772-0.878) consistently outperformed models with admission LAPS2 alone in patient-level (SBS: 0.109-0.175; c -statistic: 0.768-0.867) and patient-day-level (SBS: 0.064-0.153; c -statistic: 0.714-0.861) models. Across all predicted mortalities, daily models were better calibrated than models with admission LAPS2 alone.

CONCLUSIONS

Patient-day-level models incorporating daily, time-updating LAPS2 to predict mortality among an ICU population performs as well or better than models incorporating modified admission LAPS2 alone. The use of daily LAPS2 may offer an improved tool for clinical prognostication and risk adjustment in research in this population.

Sociodemographic and Geographic Risk Factors for All-Cause Mortality in Patients with COPD

Background

Chronic obstructive pulmonary disease (COPD) is a leading cause of mortality worldwide. Identifying both individual and community risk factors associated with higher mortality is essential to improve outcomes. Few population-based studies of mortality in COPD include both individual characteristics and community risk factors.

Objective

We used geocoded, patient-level data to describe the associations between individual demographics, neighborhood socioeconomic status, and all-cause mortality.

Methods

We performed a nationally representative retrospective cohort analysis of all patients enrolled in the Veteran Health Administration with at least one ICD-9 or ICD-10 code for COPD in 2016-2019. We obtained demographic characteristics, comorbidities, and geocoded residential address. Area Deprivation Index and rurality were classified using individual geocoded residential addresses. We used logistic regression models to assess the association between these characteristics and age-adjusted all-cause mortality.

Results

Of 1,106,163 COPD patients, 33.4% were deceased as of January 2021. In age-adjusted models, having more comorbidities, Black/African American race (OR 1.09 [95% CI: 1.08-1.11]), and higher neighborhood disadvantage (OR 1.30 [95% CI: 1.28-1.32]) were associated with all-cause mortality. Female sex (OR 0.67 [95% CI: 0.65-0.69]), Asian race (OR 0.64, [95% CI: 0.59-0.70]), and living in a more rural area were associated with lower odds of all-cause mortality. After adjusting for age, comorbidities, neighborhood socioeconomic status, and rurality, the association with Black/African American race reversed.

Conclusion

All-cause mortality in COPD patients is disproportionately higher in patients living in poorer neighborhoods and urban areas, suggesting the impact of social determinants of health on COPD outcomes. Black race was associated with higher age-adjusted all-cause mortality, but this association was abrogated after adjusting for gender, socioeconomic status, comorbidities, and urbanicity. Future studies should focus on exploring mechanisms by which disparities arise and developing interventions to address these.

Prediction of in-hospital mortality among intensive care unit patients using modified daily Laboratory-based Acute Physiology Scores, version 2 (LAPS2)

Background

Mortality prediction for intensive care unit (ICU) patients frequently relies on single acuity measures based on ICU admission physiology without accounting for subsequent clinical changes.

Objectives

Evaluate novel models incorporating modified admission and daily, time-updating Laboratory-based Acute Physiology Scores, version 2 (LAPS2) to predict in-hospital mortality among ICU patients.

Research design

Retrospective cohort study.

Subjects

All ICU patients in five hospitals from October 2017 through September 2019.

Measures

We used logistic regression, penalized logistic regression, and random forest models to predict in-hospital mortality within 30 days of ICU admission using admission LAPS2 alone in patient-level and patient-day-level models, or admission and daily LAPS2 at the patient-day level. Multivariable models included patient and admission characteristics. We performed internal-external validation using four hospitals for training and the fifth for validation, repeating analyses for each hospital as the validation set. We assessed performance using scaled Brier scores (SBS), c-statistics, and calibration plots.

Results

The cohort included 13,993 patients and 120,101 ICU days. The patient-level model including the modified admission LAPS2 without daily LAPS2 had an SBS of 0.175 (95% CI 0.148-0.201) and c-statistic of 0.824 (95% CI 0.808-0.840). Patient-day-level models including daily LAPS2 consistently outperformed models with modified admission LAPS2 alone. Among patients with <50% predicted mortality, daily models were better calibrated than models with modified admission LAPS2 alone.

Conclusions

Models incorporating daily, time-updating LAPS2 to predict mortality among an ICU population perform as well or better than models incorporating modified admission LAPS2 alone.

Drive Time and Receipt of Guideline-Recommended Screening, Diagnosis, and Treatment

IMPORTANCE

Many patients do not receive recommended services. Drive time to health care services may affect receipt of guideline-recommended care, but this has not been comprehensively studied.

OBJECTIVE

To assess associations between drive time to care and receipt of guideline-recommended screening, diagnosis, and treatment interventions.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study used administrative data from the National Veterans Health Administration (VA) data merged with Medicare data. Eligible participants were patients using VA services between January 2016 and December 2019. Women ages 65 years or older without underlying bone disease were assessed for osteoporosis screening. Patients with new diagnosis of chronic obstructive pulmonary disease (COPD) indicated by at least 2 encounter codes for COPD or at least 1 COPD-related hospitalization were assessed for receipt of diagnostic spirometry. Patients hospitalized for ischemic heart disease were assessed for cardiac rehabilitation treatment.

EXPOSURES

Drive time from each patient's residential address to the closest VA facility where the service was available, measured using geocoded addresses.

MAIN OUTCOMES AND MEASURES

Binary outcome at the patient level for receipt of osteoporosis screening, spirometry, and cardiac rehabilitation. Multivariable logistic regression models were used to assess associations between drive time and receipt of services.

RESULTS

Of 110 780 eligible women analyzed, 36 431 (32.9%) had osteoporosis screening (mean [SD] age, 66.7 [5.4] years; 19 422 [17.5%] Black, 63 403 [57.2%] White). Of 281 130 patients with new COPD diagnosis, 145 249 (51.7%) had spirometry (mean [SD] age, 68.2 [11.5] years; 268 999 [95.7%] men; 37 834 [13.5%] Black, 217 608 [77.4%] White). Of 73 146 patients hospitalized for ischemic heart disease, 11 171 (15.3%) had cardiac rehabilitation (mean [SD] age, 70.0 [10.8] years; 71 217 [97.4%] men; 15 213 [20.8%] Black, 52 144 [71.3%] White). The odds of receiving recommended services declined as drive times increased. Compared with patients with a drive time of 30 minutes or less, patients with a drive time of 61 to 90 minutes had lower odds of receiving osteoporosis screening (adjusted odds ratio [aOR], 0.90; 95% CI, 0.86-0.95) and spirometry (aOR, 0.90; 95% CI, 0.88-0.92) while patients with a drive time of 91 to 120 minutes had lower odds of receiving cardiac rehabilitation (aOR, 0.80; 95% CI, 0.74-0.87). Results were similar in analyses restricted to urban patients or patients whose primary care clinic was in a tertiary care center.

CONCLUSIONS AND RELEVANCE

In this retrospective cohort study, longer drive time was associated with less frequent receipt of guideline-recommended services across multiple components of care. To improve quality of care and health outcomes, health systems and clinicians should adopt strategies to mitigate travel burden, even for urban patients.

Anesthesia Care for Cataract Surgery in Medicare Beneficiaries

Importance

Cataract surgery in the US is routinely performed with anesthesia care, whereas anesthesia care for other elective, low-risk, outpatient procedures is applied more selectively.

Objective

To identify predictors of anesthesia care in Medicare beneficiaries undergoing cataract surgery and evaluate anesthesia care for cataract surgery compared with other elective, low-risk, outpatient procedures.

Design, Setting, and Participants

This population-based, retrospective observational cohort study included Medicare beneficiaries 66 years or older who underwent cataract surgery in 2017. The data were analyzed from August 2020 through May 2021.

Interventions (for clinical trials) or Exposures (for observational studies)

Anesthesia care during elective, low-risk, outpatient procedures.

Main Outcomes and Measures

Prevalence of anesthesia care during cataract surgery compared with other low-risk procedures; association of anesthesia care with patient, clinician, and health system characteristics; and proportion of patients experiencing a systemic complication within 7 days of cataract surgery compared with patients undergoing other low-risk procedures.

Results

Among 36 652 cataract surgery patients, the mean (SD) age was 74.7 (6.1) years; 21 690 (59.2%) were female; 2200 (6.6%) were Black and 32 049 (87.4%) were White. Anesthesia care was more common among patients undergoing cataract surgery compared with patients undergoing other low-risk procedures (89.8% vs range of <1% to 70.2%). Neither the patient's age (adjusted odds ratio, 1.01; 95% CI, 1.00-1.02; P = .01) nor Charlson Comorbidity Index (CCI) score (CCI of ≥3: adjusted odds ratio, 1.06; 95% CI, 0.95-1.18; P = .28; reference, CCI score of 0-1) was strongly associated with anesthesia care for cataract surgery, but a model comprising a single variable identifying the ophthalmologist predicted anesthesia care with a C statistic of 0.96. Approximately 6.0% of ophthalmologists never used anesthesia care, 76.6% always used anesthesia care, and 17.4% used it for only a subset of patients. Fewer cataract surgery patients experienced systemic complications within 7 days (2833 [7.7%]), even when limited to patients of ophthalmologists who never used anesthesia care (108 [7.4%]), than patients undergoing other low-risk procedures (range, 13.2%-52.2%).

Conclusions and Relevance

The results of this cohort study suggest that systemic complications occurred less frequently after cataract surgery compared with other elective, low-risk, outpatient procedures during which anesthesia care was less commonly used. Anesthesia care was not associated with patient characteristics, such as older age or worse health status, but with the ophthalmologists' usual approach to cataract surgery sedation. The study findings suggest an opportunity to use anesthesia care more selectively in patients undergoing cataract surgery.

COVID-19 Vaccination Of People Experiencing Homelessness And Incarceration In Minnesota

We used data from a statewide public health-health system collaboration to describe trends in COVID-19 vaccination rates by racial and ethnic groups among people experiencing homelessness or incarceration in Minnesota. Vaccination completion rates among the general population and people incarcerated in state prisons were substantially higher than those among people experiencing homelessness or jail incarceration.

Minnesota Electronic Health Record Consortium COVID-19 Project: Informing Pandemic Response Through Statewide Collaboration Using Observational Data

OBJECTIVE

Robust disease and syndromic surveillance tools are underdeveloped in the United States, as evidenced by limitations and heterogeneity in sociodemographic data collection throughout the COVID-19 pandemic. To monitor the COVID-19 pandemic in Minnesota, we developed a federated data network in March 2020 using electronic health record (EHR) data from 8 multispecialty health systems.

MATERIALS AND METHODS

In this serial cross-sectional study, we examined patients of all ages who received a COVID-19 polymerase chain reaction test, had symptoms of a viral illness, or received an influenza test from January 3, 2016, through November 7, 2020. We evaluated COVID-19 testing rates among patients with symptoms of viral illness and percentage positivity among all patients tested, in aggregate and by zip code. We stratified results by patient and area-level characteristics.

RESULTS

Cumulative COVID-19 positivity rates were similar for people aged 12-64 years (range, 15.1%-17.6%) but lower for adults aged ≥65 years (range, 9.3%-10.7%). We found notable racial and ethnic disparities in positivity rates early in the pandemic, whereas COVID-19 positivity was similarly elevated across most racial and ethnic groups by the end of 2020. Positivity rates remained substantially higher among Hispanic patients compared with other racial and ethnic groups throughout the study period. We found similar trends across area-level income and rurality, with disparities early in the pandemic converging over time.

PRACTICE IMPLICATIONS

We rapidly developed a distributed data network across Minnesota to monitor the COVID-19 pandemic. Our findings highlight the utility of using EHR data to monitor the current pandemic as well as future public health priorities. Building partnerships with public health agencies can help ensure data streams are flexible and tailored to meet the changing needs of decision makers.

Effectiveness of BNT162b2 and mRNA-1273 Second Doses and Boosters for SARS-CoV-2 infection and SARS-CoV-2 Related Hospitalizations: A Statewide Report from the Minnesota Electronic Health Record Consortium

Using vaccine data combined with electronic health records, we report that mRNA boosters provide greater protection than a two-dose regimen against SARS-CoV-2 infection and related hospitalizations. The benefit of a booster was more evident in the elderly and those with comorbidities. These results support the case for COVID-19 boosters.

Recent Trends in Admission Diagnosis and Related Mortality in the Medically Critically Ill

PURPOSE

With decades of declining ICU mortality, we hypothesized that the outcomes and distribution of diseases cared for in the ICU have changed and we aimed to further characterize them.

STUDY DESIGN AND METHODS

A retrospective cohort analysis of 287,154 nonsurgical-critically ill adults, from 237 U.S. ICUs, using the manually abstracted Cerner APACHE Outcomes database from 2008 to 2016 was performed. Surgical patients, rare admission diagnoses (<100 occurrences), and low volume hospitals (<100 total admissions) were excluded. Diagnoses were distributed into mutually exclusive organ system/disease-based categories based on admission diagnosis. Multi-level mixed-effects negative binomial regression was used to assess temporal trends in admission, in-hospital mortality, and length of stay (LOS).

RESULTS

The number of ICU admissions remained unchanged (IRR 0.99, 0.98-1.003) while certain organ system/disease groups increased (toxicology [25%], hematologic/oncologic [55%] while others decreased (gastrointestinal [31%], pulmonary [24%]). Overall risk-adjusted in-hospital mortality was unchanged (IRR 0.98, 0.96-1.0004). Risk-adjusted ICU LOS (Estimate -0.06 days/year, -0.07 to -0.04) decreased. Risk-adjusted mortality varied significantly by disease.

CONCLUSION

Risk-adjusted ICU mortality rate did not change over the study period, but there was evidence of shifting disease burden across the critical care population. Our data provides useful information regarding future ICU personnel and resource needs.

Beyond Access: Factors Associated With Spirometry Underutilization Among Patients With a Diagnosis of COPD in Urban Tertiary Care Centers

Rationale

Many patients with suspected chronic obstructive pulmonary disease (COPD) do not undergo spirometry to confirm the diagnosis. Underutilization is often attributed to barriers to accessing spirometry.

Objective

Our objective wasto identify factors associated with spirometry underutilization for patients who are less likely to face access barriers related to travel, insurance, and availability of spirometry.

Methods

A retrospective analysis was conducted of patients enrolled in the Veterans Health Administration and living in urban areas with a new diagnosis of COPD between 2012 to 2015, reducing out-of-pocket cost and travel barriers, respectively. We included only patients whose primary care clinic was located in an academically affiliated tertiary level facility with spirometry available. We used logistic regression to estimate associations between patient characteristics and receipt of spirometry within 2 years before or after COPD diagnosis.

Results

Of 24,300 patients, 59.7% had spirometry. Compared to patients <55 years, patients 75-84 years had an adjusted odds ratio (aOR) of undergoing spirometry of 0.80 (95% confidence interval [CI]:0.72-0.90), while patients ≥85 years had an aOR of 0.47 (95%CI: 0.40-0.54). Compared to patients with a Charlson Comorbidity Index (CCI) ≥3, patients with a CCI of 0 had an aOR of 0.60 (95%CI:0.54-0.67). Patients who had not seen a pulmonary specialist had lower odds of receiving spirometry (aOR 0.38 [95%CI:0.35-0.41]).

Conclusion

Spirometry underutilization persists among patients who are less likely to have access barriers related to travel, insurance, and availability of spirometry. Spirometry underutilization is associated with older age, not having received pulmonary care, and having fewer comorbidities. COPD care quality initiatives will need to address these factors.

The association of multimodal analgesia and high-risk opioid discharge prescriptions in opioid-naive surgical patients

BACKGROUND

Opioids and multimodal analgesia are widely administered to manage postoperative pain. However, little is known on how improvements in inpatient pain control are correlated with high-risk (> 90 daily OME) discharge opioid prescriptions for opioid naïve surgical patients.

METHODS

We conducted a retrospective observational study of adult opioid-naïve patients undergoing surgery from June 2012 through December 2018 at a large academic medical center. We used multivariate logistic regression to assess whether multimodal analgesic drugs consumed in the 24 h prior to discharge was associated with a reduction in high-risk opioid discharge prescriptions. We identified other risk factors for receiving a high-risk discharge opioid prescription.

RESULTS

Among the 32,511 patients, 83% of patients were discharged with an opioid prescription. In 2013, 34.1% of patients with a discharge opioid prescription received a high-risk prescription and this declined to 17.7% by 2018. Use of multimodal analgesic agents during the final 24 h of hospitalization increased each year, with over 80% receiving at least one multimodal analgesic agent by 2018. The median OME consumed in the 24 h prior to discharge peaked in 2013 at 31 and steadily decreased to 19.8 by 2018. There was a significant association between the use of acetaminophen in the 24 h prior to discharge and a high-risk prescription at discharge (p < 0.01). OMEs consumed in the 24 h prior to discharge was a significant predictor of receiving a high-risk discharge prescription, even at low doses. Other factors associated with receipt of a high-risk discharge opioid prescription included male gender, race, history of anxiety disorder, and discharge service.

DISCUSSION

Use of multimodal analgesia regimens in hospitalized surgical patients in the 24 h prior to hospital discharge increased between 2012 and 2018. Simultaneously, opioid use prior to hospital discharge decreased. Despite these gains, approximately one in five discharge prescriptions was high-risk (> 90 daily OME). In addition, we found that prescribing of discharge opioids above inpatient opioid requirements remains common in opioid naive surgical patients.

CONCLUSION

Providers should account for pre-discharge opioid consumption and use of multimodal analgesia when considering the total and daily OME's that may be appropriate for an individual surgical patient on the discharge opioid prescription.

Racial and Ethnic Disparities in Hospital Admissions from COVID-19: Determining the Impact of Neighborhood Deprivation and Primary Language

BACKGROUND

Despite past and ongoing efforts to achieve health equity in the USA, racial and ethnic disparities persist and appear to be exacerbated by COVID-19.

OBJECTIVE

Evaluate neighborhood-level deprivation and English language proficiency effect on disproportionate outcomes seen in racial and ethnic minorities diagnosed with COVID-19.

DESIGN

Retrospective cohort study SETTING: Health records of 12 Midwest hospitals and 60 clinics in Minnesota between March 4, 2020, and August 19, 2020 PATIENTS: Polymerase chain reaction-positive COVID-19 patients EXPOSURES: Area Deprivation Index (ADI) and primary language MAIN MEASURES: The primary outcome was COVID-19 severity, using hospitalization within 45 days of diagnosis as a marker of severity. Logistic and competing-risk regression models assessed the effects of neighborhood-level deprivation (using the ADI) and primary language. Within race, effects of ADI and primary language were measured using logistic regression.

RESULTS

A total of 5577 individuals infected with SARS-CoV-2 were included; 866 (n = 15.5%) were hospitalized within 45 days of diagnosis. Hospitalized patients were older (60.9 vs. 40.4 years, p < 0.001) and more likely to be male (n = 425 [49.1%] vs. 2049 [43.5%], p = 0.002). Of those requiring hospitalization, 43.9% (n = 381), 19.9% (n = 172), 18.6% (n = 161), and 11.8% (n = 102) were White, Black, Asian, and Hispanic, respectively. Independent of ADI, minority race/ethnicity was associated with COVID-19 severity: Hispanic patients (OR 3.8, 95% CI 2.72-5.30), Asians (OR 2.39, 95% CI 1.74-3.29), and Blacks (OR 1.50, 95% CI 1.15-1.94). ADI was not associated with hospitalization. Non-English-speaking (OR 1.91, 95% CI 1.51-2.43) significantly increased odds of hospital admission across and within minority groups.

CONCLUSIONS

Minority populations have increased odds of severe COVID-19 independent of neighborhood deprivation, a commonly suspected driver of disparate outcomes. Non-English-speaking accounts for differences across and within minority populations. These results support the ongoing need to determine the mechanisms that contribute to disparities during COVID-19 while also highlighting the underappreciated role primary language plays in COVID-19 severity among minority groups.

Characterizing COVID-19 clinical phenotypes and associated comorbidities and complication profiles

PURPOSE

Heterogeneity has been observed in outcomes of hospitalized patients with coronavirus disease 2019 (COVID-19). Identification of clinical phenotypes may facilitate tailored therapy and improve outcomes. The purpose of this study is to identify specific clinical phenotypes across COVID-19 patients and compare admission characteristics and outcomes.

METHODS

This is a retrospective analysis of COVID-19 patients from March 7, 2020 to August 25, 2020 at 14 U.S. hospitals. Ensemble clustering was performed on 33 variables collected within 72 hours of admission. Principal component analysis was performed to visualize variable contributions to clustering. Multinomial regression models were fit to compare patient comorbidities across phenotypes. Multivariable models were fit to estimate associations between phenotype and in-hospital complications and clinical outcomes.

RESULTS

The database included 1,022 hospitalized patients with COVID-19. Three clinical phenotypes were identified (I, II, III), with 236 [23.1%] patients in phenotype I, 613 [60%] patients in phenotype II, and 173 [16.9%] patients in phenotype III. Patients with respiratory comorbidities were most commonly phenotype III (p = 0.002), while patients with hematologic, renal, and cardiac (all p<0.001) comorbidities were most commonly phenotype I. Adjusted odds of respiratory, renal, hepatic, metabolic (all p<0.001), and hematological (p = 0.02) complications were highest for phenotype I. Phenotypes I and II were associated with 7.30-fold (HR:7.30, 95% CI:(3.11-17.17), p<0.001) and 2.57-fold (HR:2.57, 95% CI:(1.10-6.00), p = 0.03) increases in hazard of death relative to phenotype III.

CONCLUSION

We identified three clinical COVID-19 phenotypes, reflecting patient populations with different comorbidities, complications, and clinical outcomes. Future research is needed to determine the utility of these phenotypes in clinical practice and trial design.

Emergency Department Length of Stay and Mortality in Critically Injured Patients

OBJECTIVE

Multicenter data from 2 decades ago demonstrated that critically ill and injured patients spending more than 6 hours in the emergency department (ED) before transfer to the intensive care unit (ICU) had higher mortality rates. A contemporary analysis of ED length of stay in critically injured patients at American College of Surgeons' Trauma Quality Improvement Program (ACS-TQIP) centers was performed to test whether prolonged ED length of stay is still associated with mortality.

METHODS

This was an observational cohort study of critically injured patients admitted directly to ICU from the ED in ACS-TQIP centers from 2010-2015. Spending more than 6 hours in the ED was defined as prolonged ED length of stay. Patients with prolonged ED length of stay were matched to those with non-prolonged ED length of stay and mortality was compared.

MAIN RESULTS

A total of 113,097 patients were directly admitted from the ED to the ICU following injury. The median ED length of stay was 167 minutes. Prolonged ED length of stay occurred in 15,279 (13.5%) of patients. Women accounted for 29.4% of patients with prolonged ED length of stay but only 25.8% of patients with non-prolonged ED length of stay, P < 0.0001. Mortality rates were similar after matching-4.5% among patients with prolonged ED length of stay versus 4.2% among matched controls. Multivariable logistic regression of the matched cohorts demonstrated prolonged ED length of stay was not associated with mortality. However, women had higher adjusted mortality compared to men Odds Ratio = 1.41, 95% Confidence Interval 1.28 -1.61, P < 0.0001.

CONCLUSION

Prolonged ED length of stay is no longer associated with mortality among critically injured patients. Women are more likely to have prolonged ED length of stay and mortality.

Electronic health records systems and hospital clinical performance: a study of nationwide hospital data

OBJECTIVE

Electronic health records (EHRs) were expected to yield numerous benefits. However, early studies found mixed evidence of this. We sought to determine whether widespread adoption of modern EHRs in the US has improved clinical care.

METHODS

We studied hospitals reporting performance measures from 2008-2015 in the Centers for Medicare and Medicaid Services Hospital Compare database that also reported having an EHR in the American Hospital Association 2015 IT supplement. Using interrupted time-series analysis, we examined the association of EHR implementation, EHR vendor, and Meaningful Use status with 11 process measures and 30-day hospital readmission and mortality rates for heart failure, pneumonia, and acute myocardial infarction.

RESULTS

A total of 1246 hospitals contributed 8222 hospital-years. Compared to hospitals without EHRs, hospitals with EHRs had significant improvements over time on 5 of 11 process measures. There were no substantial differences in readmission or mortality rates. Hospitals with CPSI EHR systems performed worse on several process and outcome measures. Otherwise, we found no substantial improvements in process measures or condition-specific outcomes by duration of EHR use, EHR vendor, or a hospital's Meaningful Use Stage 1 or Stage 2 status.

CONCLUSION

In this national study of hospitals with modern EHRs, EHR use was associated with better process of care measure performance but did not improve condition-specific readmission or mortality rates regardless of duration of EHR use, vendor choice, or Meaningful Use status. Further research is required to understand why EHRs have yet to improve standard outcome measures and how to better realize the potential benefits of EHR systems.

Is Better Patient Knowledge Associated with Different Treatment Preferences? A Survey of Patients with Stable Coronary Artery Disease

BACKGROUND

In stable coronary artery disease (CAD), shared decision-making (SDM) is encouraged when deciding whether to pursue percutaneous coronary intervention (PCI) given similar cardiovascular outcomes between PCI and medical therapy. However, it remains unclear whether improving patient-provider communication and patient knowledge, the main tenets of SDM, changes patient preferences or the treatment chosen. We explored the relationships between patient-provider communication, patient knowledge, patient preferences, and the treatment received.

METHODS

We surveyed stable CAD patients referred for elective cardiac catheterization at seven hospitals from 6/2016 to 9/2018. Surveys assessed patient-provider communication, medical knowledge, and preferences for treatment and decision-making. We verified treatments received by chart review. We used linear and logistic regression to examine relationships between patient-provider communication and knowledge, knowledge and preference, and preference and treatment received.

RESULTS

Eighty-seven patients completed the survey. More discussion of the benefits and risks of both medical therapy and PCI associated with higher patient knowledge scores (β=0.28, p<0.01). Patient knowledge level was not associated with preference for PCI (OR=0.78, 95% CI 0.57-1.03, p=0.09). Black patients had more than four times the odds of preferring medical therapy to PCI (OR=4.49, 1.22-18.45, p=0.03). Patients preferring medical therapy were not significantly less likely to receive PCI (OR=0.67, 0.16-2.52, p=0.57).

CONCLUSIONS

While communicating the risks of PCI may improve patient knowledge, this knowledge may not affect patient treatment preferences. Rather, other factors such as race may be significantly more influential on a patient's treatment preferences. Furthermore, patient preferences are still not well reflected in the treatment received. Improving shared decision-making in stable CAD therefore may require not only increasing patient education but also better understanding and including a patient's background and pre-existing beliefs.

Out-of-Pocket Costs for Novel Guideline-Directed Diabetes Therapies Under Medicare Part D

This study examines cost sharing for novel second-line diabetes treatment agents under Medicare Part D.

Changes in Drug List Prices and Amounts Paid by Patients and Insurers

IMPORTANCE

High out-of-pocket drug costs can cause patients to skip treatment and worsen outcomes, and high insurer drug payments could increase premiums. Drug wholesale list prices have doubled in recent years. However, because of manufacturer discounts and rebates, the extent to which increases in wholesale list prices are associated with amounts paid by patients and insurers is poorly characterized.

OBJECTIVE

To determine whether increases in wholesale list prices are associated with increases in amounts paid by patients and insurers for branded medications.

DESIGN, SETTING, AND PARTICIPANTS

Cross-sectional retrospective study analyzing pharmacy claims for patients younger than 65 years in the IBM MarketScan Commercial Database and pricing data from SSR Health, LLC, between January 1, 2010, and December 31, 2016. Pharmacy claims analyzed represent claims of employees and dependents participating in employer health benefit programs belonging to large employers. Rebate data were estimated from sales data from publicly traded companies. Analysis focused on the top 5 patent-protected specialty and 9 traditional brand-name medications with the highest total drug expenditures by commercial insurers nationwide in 2014. Data were analyzed from July 2017 to July 2020.

EXPOSURES

Calendar year.

MAIN OUTCOMES AND MEASURES

Changes in inflation-adjusted amounts paid by patients and insurers for branded medications.

RESULTS

In this analysis of 14.4 million pharmacy claims made by 1.8 million patients from 2010-2016, median drug wholesale list price increased by 129% (interquartile range [IQR], 78%-133%), while median insurance payments increased by 64% (IQR, 28%-120%) and out-of-pocket costs increased by 53% (IQR, 42%-82%). The mean percentage of wholesale list price accounted for by discounts increased from 17% in 2010 to 21% in 2016, and the mean percentage of wholesale list price accounted for by rebates increased from 22% in 2010 to 24% in 2016. For specialty medications, median patient out-of-pocket costs increased by 85% (IQR, 73%-88%) from 2010 to 2016 after adjustment for inflation and 42% (IQR, 25%-53%) for nonspecialty medications. During that same period, insurer payments increased by 116% for specialty medications (IQR, 100%-127%) and 28% for nonspecialty medications (IQR, 5%-34%).

CONCLUSIONS AND RELEVANCE

This study's findings suggest that drug list prices more than doubled over a 7-year study period. Despite rising manufacturer discounts and rebates, these price increases were associated with large increases in patient out-of-pocket costs and insurer payments.

Variation in Arterial and Central Venous Catheter Use in Pediatric Intensive Care Units

OBJECTIVE

Describe patient and hospital characteristics associated with Arterial Catheter (AC) or Central Venous Catheter (CVC) use among pediatric intensive care units (ICUs).

DESIGN

Hierarchical mixed effects analyses were used to identify patient and hospital characteristics associated with AC or CVC placement. The ICU adjusted median odds ratios (ICU-AMOR) for the admission ICU, marginal R², and conditional intraclass correlation coefficient were reported.

SETTING

166 PICUs in the Virtual PICU Systems (VPS, LLC) Database.

PATIENTS

682,791 patients with unscheduled admissions to the PICU.

INTERVENTION

None.

MEASURES AND MAIN RESULTS

ACs were placed in (median, [interquartile range]) 8.2% [4.9%-11.3%] of admissions, and CVCs were placed in 14.9% [10.4%-19.3%] of admissions across cohort ICUs. Measured patient characteristics explained about 25% of the variability in AC and CVC placement. Higher Pediatric Index of Mortality 2 (PIM2) illness severity scores were associated with increased odds of placement (Odds Ratio (95th% Confidence Interval)) AC: 1.88 (1.87-1.89) and CVC: 1.82 (1.81-1.83) per 1 unit increase in PIM2 score. Primary diagnoses of cardiovascular, gastrointestinal, hematology/oncology, infectious, renal/genitourinary, rheumatology, and transplant were associated with increased odds of AC or CVC placement compared to a primary respiratory diagnosis. Presence of in-house attendings 24/7 was associated with increased odds of AC placement 1.32 (1.11-1.57). Admission ICU explained 4.9% and 3.5% of the variability in AC or CVC placement, respectively. The ICU-AMOR showed a patient would have a median increase in odds of 55% and 43% for AC or CVC placement, respectively, if the same patient moved from an ICU with lower odds of placement to an ICU with higher odds of placement.

CONCLUSIONS

Variation in AC or CVC use exists among PICUs. The admission ICU was more strongly associated with AC than with CVC placement. Further study is needed to understand unexplained variation in AC and CVC use.

Racial/Ethnic Disparities in Hospital Admissions from COVID-19 and Determining the Impact of Neighborhood Deprivation and Primary Language

Background Despite past and ongoing efforts to achieve health equity in the United States, persistent disparities in socioeconomic status along with multilevel racism maintain disparate outcomes and appear to be amplified by COVID-19. Objective Measure socioeconomic factors and primary language effects on the risk of COVID-19 severity across and within racial/ethnic groups. Design Retrospective cohort study. Setting Health records of 12 Midwest hospitals and 60 clinics in the U.S. between March 4, 2020 to August 19, 2020. Patients PCR+ COVID-19 patients. Exposures Main exposures included race/ethnicity, area deprivation index (ADI), and primary language. Main Outcomes and Measures The primary outcome was COVID-19 severity using hospitalization within 45 days of diagnosis. Logistic and competing-risk regression models (censored at 45 days and accounting for the competing risk of death prior to hospitalization) assessed the effects of neighborhood-level deprivation (using the ADI) and primary language. Within race effects of ADI and primary language were measured using logistic regression. Results 5,577 COVID-19 patients were included, 866 (n=15.5%) were hospitalized within 45 days of diagnosis. Hospitalized patients were older (60.9 vs. 40.4 years, p<0.001) and more likely to be male (n=425 [49.1%] vs. 2,049 [43.5%], p=0.002). Of those requiring hospitalization, 43.9% (n=381), 19.9% (n=172), 18.6% (n=161), and 11.8% (n=102) were White, Black, Asian, and Hispanic, respectively. Independent of ADI, minority race/ethnicity was associated with COVID-19 severity; Hispanic patients (OR 3.8, 95% CI 2.72-5.30), Asians (OR 2.39, 95% CI 1.74-3.29), and Blacks (OR 1.50, 95% CI 1.15-1.94). ADI was not associated with hospitalization. Non-English speaking (OR 1.91, 95% CI 1.51-2.43) significantly increased odds of hospital admission across and within minority groups. Conclusions Minority populations have increased odds of severe COVID-19 independent of neighborhood deprivation, a commonly suspected driver of disparate outcomes. Non-English-speaking accounts for differences across and within minority populations. These results support the continued concern that racism contributes to disparities during COVID-19 while also highlighting the underappreciated role primary language plays in COVID-19 severity across and within minority groups.

Characterizing COVID-19 Clinical Phenotypes and Associated Comorbidities and Complication Profiles

BACKGROUND

There is limited understanding of heterogeneity in outcomes across hospitalized patients with coronavirus disease 2019 (COVID-19). Identification of distinct clinical phenotypes may facilitate tailored therapy and improve outcomes.

OBJECTIVE

Identify specific clinical phenotypes across COVID-19 patients and compare admission characteristics and outcomes.

DESIGN, SETTINGS, AND PARTICIPANTS

Retrospective analysis of 1,022 COVID-19 patient admissions from 14 Midwest U.S. hospitals between March 7, 2020 and August 25, 2020.

METHODS

Ensemble clustering was performed on a set of 33 vitals and labs variables collected within 72 hours of admission. K-means based consensus clustering was used to identify three clinical phenotypes. Principal component analysis was performed on the average covariance matrix of all imputed datasets to visualize clustering and variable relationships. Multinomial regression models were fit to further compare patient comorbidities across phenotype classification. Multivariable models were fit to estimate the association between phenotype and in-hospital complications and clinical outcomes. Main outcomes and measures: Phenotype classification (I, II, III), patient characteristics associated with phenotype assignment, in-hospital complications, and clinical outcomes including ICU admission, need for mechanical ventilation, hospital length of stay, and mortality.

RESULTS

The database included 1,022 patients requiring hospital admission with COVID-19 (median age, 62.1 [IQR: 45.9-75.8] years; 481 [48.6%] male, 412 [40.3%] required ICU admission, 437 [46.7%] were white). Three clinical phenotypes were identified (I, II, III); 236 [23.1%] patients had phenotype I, 613 [60%] patients had phenotype II, and 173 [16.9%] patients had phenotype III. When grouping comorbidities by organ system, patients with respiratory comorbidities were most commonly characterized by phenotype III (p=0.002), while patients with hematologic (p<0.001), renal (p<0.001), and cardiac (p<0.001) comorbidities were most commonly characterized by phenotype I. The adjusted odds of respiratory (p<0.001), renal (p<0.001), and metabolic (p<0.001) complications were highest for patients with phenotype I, followed by phenotype II. Patients with phenotype I had a far greater odds of hepatic (p<0.001) and hematological (p=0.02) complications than the other two phenotypes. Phenotypes I and II were associated with 7.30-fold (HR: 7.30, 95% CI: (3.11-17.17), p<0.001) and 2.57-fold (HR: 2.57, 95% CI: (1.10-6.00), p=0.03) increases in the hazard of death, respectively, when compared to phenotype III.

CONCLUSION

In this retrospective analysis of patients with COVID-19, three clinical phenotypes were identified. Future research is urgently needed to determine the utility of these phenotypes in clinical practice and trial design.

Ambulatory Health Care Service Use and Costs Among Commercially Insured US Adults With Congenital Heart Disease

This study examines the ambulatory health care use and costs of adults with congenital heart disease in the US.

The Opioid Epidemic Blunted the Mortality Benefit of Medicaid Expansion

Although the Affordable Care Act's Medicaid expansion reduced uninsurance, less is known about its impact on mortality, especially in the context of the opioid epidemic. We conducted a difference-in-differences study comparing trends in mortality between expansion and nonexpansion states from 2011 to 2016 using the Centers for Disease Control and Prevention mortality data. We analyzed all-cause deaths, health care amenable deaths, drug overdose deaths, and deaths from causes other than drug overdose among adults aged 20 to 64 years. Medicaid expansion was associated with a 2.7% reduction (p = .020) in health care amenable mortality, and a 1.9% reduction (p = .042) in mortality not due to drug overdose. However, the expansion was not associated with any change in all-cause mortality (0.2% reduction, p = .84). In addition, drug overdose deaths rose more sharply in expansion versus nonexpansion states. The absence of all-cause mortality reduction until drug overdose deaths were excluded indicate that the opioid epidemic had a mitigating impact on any potential lives saved by Medicaid expansion.

Medicare Part D and Cost-Sharing for Antiretroviral Therapy and Preexposure Prophylaxis

IMPORTANCE

The 2019 federal Ending the HIV Epidemic initiative requires a vast expansion of access to antiretroviral therapy (ART) and preexposure prophylaxis (PrEP) for HIV treatment and prevention. However, high prices for ART and PrEP can reduce their affordability and use. Medicare covers 1 in 4 persons living with HIV, and the Medicare Part D drug benefit imposes complicated cost-sharing between patients and other stakeholders.

OBJECTIVE

To determine how the Medicare Part D design distributes the cost burden for ART and PrEP between patients, insurance plans, manufacturers, and Medicare.

DESIGN AND SETTING

Nationwide cross-sectional analyses of first quarter 2019 Medicare formulary and pricing files for 3326 Part D plans were performed. These files contain drug benefit data, including prices and cost-sharing requirements.

MAIN OUTCOMES AND MEASURES

For 18 ART and 2 PrEP regimens, the out-of-pocket costs for patients and the cost borne by plans, manufacturers, and Medicare were projected for 1 year of treatment or prevention under a 2019 standard Medicare Part D insurance plan. Analyses assumed that patients used the ART or PrEP regimen and no other medications.

RESULTS

In 2019, ART prices ranged from $24 010 to $46 770 annually (median price, $35 780), with patients projected to pay 9% to 14% of the cost ($3270-$4350), insurance plans 18% to 24% ($5340-$8450), manufacturers 6% to 11% ($2370-$2750), and Medicare 53% to 67% ($12 770-$31 270). The price of PrEP was $20 570 annually, with patients contributing 15% ($2990), insurance plans 22% ($4570), manufacturers 13% ($2750), and Medicare 50% ($10 260). For beneficiaries with low-income subsidies that cover all patient cost-sharing, Medicare would assume 67% to 76% of ART costs and 65% of PrEP costs.

CONCLUSIONS AND RELEVANCE

Medicare Part D mandates universal ART and PrEP coverage, but high prices (>$35 000 annually for ART and>$20 000 annually for PrEP) and the design of Part D can jeopardize affordability for patients and place most of the cost burden on taxpayers. Under a standard Medicare Part D benefit, patients pay $3000 to $4000 out-of-pocket yearly, unless they qualify for low-income subsidies, and half to two-thirds of the cost of ART and PrEP is borne by Medicare rather than insurance plans or manufacturers. To end the HIV epidemic by 2030, it appears that policies must address both high drug prices and revamp Medicare Part D cost-sharing.

How care decisions are made among interdisciplinary providers caring for critically injured patients: A qualitative study

BACKGROUND

Injury is the leading cause of death in people under 45 years of age in the United States; however, how care decisions occur in critical injury is poorly understood. This exploratory study sought to generate hypotheses about how care decisions are made among interdisciplinary providers caring for patients who have been critically injured.

METHODS

This was a qualitative study conducted at two intensive care units in a level 1 trauma center in an urban, teaching, safety-net hospital. Semistructured interviews consisted of case scenarios with competing clinical priorities presented to 25 interdisciplinary providers, elucidating how decisions are approached. Responses were recorded, transcribed, and coded. Thematic analysis was conducted to discover central themes. Category formulation and sorting was done for data reduction and thematic structuring of the data. The range and central tendency of these themes are reported.

RESULTS

The central theme for how care decisions are made among interdisciplinary providers was through the distribution of shared responsibility. The distribution of shared responsibility depended on interdisciplinary communication to navigate the two subthemes of time and roles. Time had to be navigated carefully, because it was both an opportunity for data acquisition and consensus building but also a pressure to decisively progress care. Roles were distinct but interchangeable and consisted of experts, actualizers, and questioners.

CONCLUSION

Care decisions are made in the context of shared responsibility among interdisciplinary providers. Interdisciplinary communication is a means of establishing roles and navigating time to distribute shared responsibility among interdisciplinary providers.

Identifying tests related to breast cancer care in claims data

To develop a method for calculating rates of testing for breast cancer recurrence in patients who have already undergone initial treatment for breast cancer, we calculated rates in a cohort of Medicare breast cancer patients and an age-matched noncancer cohort. We first used only tests with claims including diagnosis codes indicating invasive breast cancer and then used all tests regardless of diagnosis code. For each method, we calculated testing rates in the breast cancer cohort above the background rate in the noncancer population. The two methods provided similar estimates of testing prevalence and frequency, with exception of prevalence of CT.

Geographic Variation in Postoperative Imaging for Low-Risk Breast Cancer

Background: The objective of this study was to examine the presence and magnitude of US geographic variation in use rates of both recommended and high-cost imaging in young patients with early-stage breast cancer during the 18 month period after surgical treatment of their primary tumor. Methods: Using the Truven Health MarketScan Commercial Database, a descriptive analysis was conducted of geographic variation in annual rates of dedicated breast imaging and high-cost body imaging of 36,045 women aged 18 to 64 years treated with surgery for invasive unilateral breast cancer between 2010 and 2012. Multivariate hierarchical analysis examined the relationship between likelihood of imaging and patient characteristics, with metropolitan statistical area (MSA) serving as a random effect. Patient characteristics included age group, BRCA1/2 carrier status, family history of breast cancer, combination of breast surgery type and radiation therapy, drug therapy, and payer type. All MSAs in the United States were included, with areas outside MSAs within a given state aggregated into a single area for analytic purposes. Results: Descriptive analysis of rates of imaging use and intensity within MSA regions revealed wide geographic variation, irrespective of treatment cohort or age group. Increased probability of recommended postoperative dedicated breast imaging was primarily associated with age and treatment including both surgery and radiation therapy, followed by MSA region (odds ratio, 1.42). Increased probability of PET use-a high-cost imaging modality for which postoperative routine use is not recommended in the absence of specific clinical findings-was primarily associated with surgery type followed by MSA region (odds ratio, 1.82). Conclusions: In patients with breast cancer treated for low-risk disease, geography has effects on the rates of posttreatment imaging, suggesting that some patients are not receiving beneficial dedicated breast imaging, and high-cost nonbreast imaging may not be targeted to those groups most likely to benefit.

Age- and Lesion-Related Comorbidity Burden Among US Adults With Congenital Heart Disease: A Population-Based Study

Background As patients with congenital heart disease (CHD) are living longer, understanding the comorbidities they develop as they age is increasingly important. However, there are no published population-based estimates of the comorbidity burden among the US adult patients with CHD. Methods and Results Using the IBM MarketScan commercial claims database from 2010 to 2016, we identified adults aged ≥18 years with CHD and 2 full years of continuous enrollment. These were frequency matched with adults without CHD within categories jointly defined by age, sex, and dates of enrollment in the database. A total of 40 127 patients with CHD met the inclusion criteria (mean [SD] age, 36.8 [14.6] years; and 48.2% were women). Adults with CHD were nearly twice as likely to have any comorbidity than those without CHD (P<0.001). After adjusting for covariates, patients with CHD had a higher prevalence risk ratio for "previously recognized to be common in CHD" (risk ratio, 9.41; 95% CI, 7.99-11.1), "other cardiovascular" (risk ratio, 1.73; 95% CI, 1.66-1.80), and "noncardiovascular" (risk ratio, 1.47; 95% CI, 1.41-1.52) comorbidities. After adjusting for covariates and considering interaction with age, patients with severe CHD had higher risks of previously recognized to be common in CHD and lower risks of other cardiovascular comorbidities than age-stratified patients with nonsevere CHD. For noncardiovascular comorbidities, the risk was higher among patients with severe than nonsevere CHD before, but not after, the age of 40 years. Conclusions Our data underscore the unique clinical needs of adults with CHD compared with their peers. Clinicians caring for CHD may want to use a multidisciplinary approach, including building close collaborations with internists and specialists, to help provide appropriate care for the highly prevalent noncardiovascular comorbidities.

A Revised Estimate of Costs Associated With Routine Preoperative Testing in Medicare Cataract Patients With a Procedure-Specific Indicator

Importance

Routine preoperative medical testing is not recommended for patients undergoing low-risk surgery, but testing is common before surgery. A 30-day preoperative testing window is conventionally used for study purposes; however, the extent of routine testing that occurs prior to that point is unknown.

Objective

To improve on existing cost estimates by identifying all routine preoperative testing that takes place after the decision is made to perform cataract surgery.

Design, Setting, and Participants

This cross-sectional study assessed preoperative care in a 50% sample of Medicare beneficiaries older than 66 years who underwent ambulatory cataract surgery in 2011. Data analysis was completed from March 2016 to October 2017.

Main Outcomes and Measures

Using ocular biometry as a procedure-specific indicator to mark the start of the routine preoperative testing window, we measured testing rates in the interval between ocular biometry and cataract surgery and compared this with testing rates in the 6 months preceding biometry. We estimated the total cost of testing that occurred between biometry and cataract surgery.

Results

A total of 440 857 patients underwent cataract surgery. A total of 423 710 (96.1%) had an ocular biometry claim before index surgery, of whom 264 514 (60.0%) were female; the mean (SD) age of the cohort was 76.1 (6.2) years. A total of 111 998 (25.4%) underwent surgery more than 30 days after biometry. Among patients with a biometry claim, the mean number of tests/patient/month increased from 1.1 in the baseline period to 1.7 in the interval between biometry and cataract surgery. Although preoperative testing peaked in all patients in the 30 days preceding surgery (1.8 tests/patient/month), the subset of patients with no overlap between postbiometry and presurgery periods experienced increased testing rates to 1.8 tests per patient per month in the 30 days after biometry, regardless of the elapsed time between biometry and surgery. The total estimated cost of routine preoperative testing in the full cohort was $22.7 million; we estimate that routine preoperative testing costs Medicare up to $45.4 million annually.

Conclusions and Relevance

In this study of Medicare beneficiaries, routine preoperative medical testing occurs more often and is costlier than has been reported previously. Extra costs are attributable to testing that occurs prior to the 30-day window preceding surgery. As a cost-cutting measure, routine preoperative medical testing should be avoided in patients with cataracts throughout the interval between ocular biometry and cataract surgery.

The costs of dementia subtypes to California Medicare fee-for-service, 2015

INTRODUCTION

Dementia is among the costliest of medical conditions, but it is not known how these costs vary by dementia subtype.

METHODS

The effect of dementia diagnosis subtype on direct health care costs and utilization was estimated using 2015 California Medicare fee-for-service data. Potential drivers of increased costs in Lewy body dementia (LBD), in comparison to Alzheimer's disease, were tested.

RESULTS

3,001,987 Medicare beneficiaries were identified, of which 8.2% had a dementia diagnosis. Unspecified dementia was the most common diagnostic category (59.6%), followed by Alzheimer's disease (23.2%). LBD was the costliest subtype to Medicare, on average, followed by vascular dementia. The higher costs in LBD were explained in part by falls, urinary incontinence or infection, depression, anxiety, dehydration, and delirium.

DISCUSSION

Dementia subtype is an important predictor of health care costs. Earlier identification and targeted treatment might mitigate the costs associated with co-occurring conditions in LBD.

Validation of Prediction Models for Critical Care Outcomes Using Natural Language Processing of Electronic Health Record Data

Importance

Accurate prediction of outcomes among patients in intensive care units (ICUs) is important for clinical research and monitoring care quality. Most existing prediction models do not take full advantage of the electronic health record, using only the single worst value of laboratory tests and vital signs and largely ignoring information present in free-text notes. Whether capturing more of the available data and applying machine learning and natural language processing (NLP) can improve and automate the prediction of outcomes among patients in the ICU remains unknown.

Objectives

To evaluate the change in power for a mortality prediction model among patients in the ICU achieved by incorporating measures of clinical trajectory together with NLP of clinical text and to assess the generalizability of this approach.

Design, Setting, and Participants

This retrospective cohort study included 101 196 patients with a first-time admission to the ICU and a length of stay of at least 4 hours. Twenty ICUs at 2 academic medical centers (University of California, San Francisco [UCSF], and Beth Israel Deaconess Medical Center [BIDMC], Boston, Massachusetts) and 1 community hospital (Mills-Peninsula Medical Center [MPMC], Burlingame, California) contributed data from January 1, 2001, through June 1, 2017. Data were analyzed from July 1, 2017, through August 1, 2018.

Main Outcomes and Measures

In-hospital mortality and model discrimination as assessed by the area under the receiver operating characteristic curve (AUC) and model calibration as assessed by the modified Hosmer-Lemeshow statistic.

Results

Among 101 196 patients included in the analysis, 51.3% (n = 51 899) were male, with a mean (SD) age of 61.3 (17.1) years; their in-hospital mortality rate was 10.4% (n = 10 505). A baseline model using only the highest and lowest observed values for each laboratory test result or vital sign achieved a cross-validated AUC of 0.831 (95% CI, 0.830-0.832). In contrast, that model augmented with measures of clinical trajectory achieved an AUC of 0.899 (95% CI, 0.896-0.902; P < .001 for AUC difference). Further augmenting this model with NLP-derived terms associated with mortality further increased the AUC to 0.922 (95% CI, 0.916-0.924; P < .001). These NLP-derived terms were associated with improved model performance even when applied across sites (AUC difference for UCSF: 0.077 to 0.021; AUC difference for MPMC: 0.071 to 0.051; AUC difference for BIDMC: 0.035 to 0.043; P < .001) when augmenting with NLP at each site.

Conclusions and Relevance

Intensive care unit mortality prediction models incorporating measures of clinical trajectory and NLP-derived terms yielded excellent predictive performance and generalized well in this sample of hospitals. The role of these automated algorithms, particularly those using unstructured data from notes and other sources, in clinical research and quality improvement seems to merit additional investigation.

Pneumocystis jirovecii pneumonia (PJP) prophylaxis patterns among patients with rheumatic diseases receiving high-risk immunosuppressant drugs

INTRODUCTION/OBJECTIVES

Pneumocystis jirovecii pneumonia (PJP) is a rare but potentially fatal opportunistic infection; however, consensus varies around which conditions or medications confer a level of risk sufficient to justify antibiotic prophylaxis for PJP. We used electronic health record (EHR) data to assess the current patterns of PJP prophylaxis, PJP outcomes, and prophylaxis-related adverse events among patients with rheumatic diseases who were receiving high-risk immunosuppressant drugs.

METHODS

Data derive from the EHR of a large health system. We included new immunosuppressant users with diagnoses of vasculitis, myositis, or systemic lupus erythematosus. We calculated the proportion of patients who received PJP prophylaxis for each diagnosis and drug combination. We also calculated the number of PJP infections and the number of antibiotic adverse drug events (ADEs) per patient-year of exposure.

RESULTS

We followed 316 patients for 23.2 + /- 14.2 months. Overall, 124 (39%) of patients received prophylactic antibiotics for PJP. At least 25% of patients with the highest risk conditions (e.g. vasculitis) or highest risk immunosuppressants (e.g. cyclophosphamide) did not receive PJP prophylaxis. We found no cases of PJP infection over 640 patient-years of follow up, including among those not receiving prophylaxis, and an overall incidence rate of ADEs of 2.2% per patient-year.

CONCLUSIONS

PJP prophylaxis for patients with rheumatic conditions is inconsistent, with one quarter of patients who have high risk conditions or high risk immunosuppressants not receiving prophylaxis. However, given extremely low rates of PJP infection, but detectable ADEs to prophylactic antibiotics, our findings suggest that evidence to guide more personalized risk assessments are needed to inform PJP prophylaxis.

Accurate and interpretable intensive care risk adjustment for fused clinical data with generalized additive models

Risk adjustment models for intensive care outcomes have yet to realize the full potential of data unlocked by the increasing adoption of EHRs. In particular, they fail to fully leverage the information present in longitudinal, structured clinical data - including laboratory test results and vital signs - nor can they infer patient state from unstructured clinical narratives without lengthy manual abstraction. A fully electronic ICU risk model fusing these two types of data sources may yield improved accuracy and more personalized risk estimates, and in obviating manual abstraction, could also be used for real-time decision-making. As a first step towards fully "electronic" ICU models based on fused data, we present results of generalized additive modeling applied to a sample of over 36,000 ICU patients. Our approach outperforms those based on the SAPS and OASIS systems (A UC: 0.908 vs. 0.794 and 0.874), and appears to yield more granular and easily visualized risk estimates.

Geographic and Hospital Variation in Cost of Lumbar Laminectomy and Lumbar Fusion for Degenerative Conditions

BACKGROUND

Spinal surgery costs vary significantly across hospitals and regions, but there is insufficient understanding of what drives this variation.

OBJECTIVE

To examine the factors underlying the cost variation for lumbar laminectomy/discectomy and lumbar fusions.

METHODS

We obtained patient information (age, gender, race, severity of illness, risk of mortality, population of county of residence, median zipcode income, insurance status, elective vs nonelective admission, length of stay) and hospital data (region, hospital type, bed size, wage index) for all patients who underwent lumbar laminectomy/discectomy (n = 181 267) or lumbar fusions (n = 433 364) for degenerative conditions in the 2001 to 2013 National Inpatient Sample database. We performed unadjusted and adjusted analyses to determine which factors affect cost.

RESULTS

Mean costs for lumbar laminectomy/discectomy and lumbar fusion increased from $8316 and $21 473 in 2001 (in inflation-adjusted 2013 dollars), to $11 405 and $29 438, respectively, in 2013. There was significant regional variation in cost, with the West being the most expensive region across all years and showing the steepest increase in cost over time. After adjusting for patient and hospital factors, the West was 23% more expensive than the Northeast for lumbar laminectomy/discectomy, and 25% more expensive than the Northeast for lumbar fusion ( P < .01). Higher wage index, smaller hospital bed size, and rural/urban nonteaching hospital type were also associated with higher cost for lumbar laminectomy/discectomy and fusion ( P < .01).

CONCLUSION

After adjusting for patient factors and wage index, the Western region, hospitals with smaller bed sizes, and rural/urban nonteaching hospitals were associated with higher costs for lumbar laminectomy/discectomy and lumbar fusion.

Correction to: Hydroxychloroquine dosing in immune-mediated diseases: implications for patient safety

The given and family name of a co-author R. Adams Dudley was swapped in the published article. The correct given name is R. Adams and the family name is Dudley.

Trends in Utilization and Cost of Cervical Spine Surgery Using the National Inpatient Sample Database, 2001 to 2013

STUDY DESIGN

A retrospective review.

OBJECTIVE

The aim of this study was to determine national rates of cervical spine surgery and to examine factors that underlie cost variation.

SUMMARY OF BACKGROUND DATA

There has been an increase in the rate and cost of spinal surgery over the past decades, but there is little understanding of the drivers of cost variation at the national level.

METHODS

We analyzed 419,830 patients who underwent cervical spine surgery (anterior cervical fusion, posterior cervical fusion, posterior cervical decompression, combined anterior/posterior cervical fusion) for degenerative conditions in the 2001 to 2013 NIS database. We determined the rates of surgery by time and geographic region, and then created univariate and multivariate models to evaluate the effect of these factors on total hospital costs: patient age, gender, race, insurance, income, county of residence, elective versus nonelective case, length of stay, risk of mortality, severity of illness, hospital bed size, wage index, hospital type, and geographic region.

RESULTS

The most common type of cervical spine surgery was anterior fusion (80.6% of all surgeries). The national rates of all cervical spine surgery decreased slightly from 2001 to 2013 (75.34 to 72.20 per 100,000 adults), while the mean inflation-adjusted cost increased 64%, from $11,799 to $19,379, during this time period. Multivariate analyses showed that older age, male gender, black/other race, private insurance, greater risk of mortality/severity of illness, and longer length of stay were associated with higher costs. The wage index was positively correlated with cost, and hospitals in the western U.S. were 27% more expensive than those in the Northeast.

CONCLUSION

The rate of cervical spine surgery decreased slightly, while the mean case cost increased at a rate double that of inflation from 2001 to 2013. Even after controlling for patient and hospital factors including wage index, there was significant geographic variation in the cost for cervical spine surgery.

LEVEL OF EVIDENCE

3.

Association Between Surgeon Scorecard Use and Operating Room Costs

Importance

Despite the significant contribution of surgical spending to health care costs, most surgeons are unaware of their operating room costs.

Objective

To examine the association between providing surgeons with individualized cost feedback and surgical supply costs in the operating room.

Design, Setting, and Participants

The OR Surgical Cost Reduction (OR SCORE) project was a single-health system, multihospital, multidepartmental prospective controlled study in an urban academic setting. Intervention participants were attending surgeons in orthopedic surgery, otolaryngology-head and neck surgery, and neurological surgery (n = 63). Control participants were attending surgeons in cardiothoracic surgery, general surgery, vascular surgery, pediatric surgery, obstetrics/gynecology, ophthalmology, and urology (n = 186).

Interventions

From January 1 to December 31, 2015, each surgeon in the intervention group received standardized monthly scorecards showing the median surgical supply direct cost for each procedure type performed in the prior month compared with the surgeon's baseline (July 1, 2012, to November 30, 2014) and compared with all surgeons at the institution performing the same procedure at baseline. All surgical departments were eligible for a financial incentive if they met a 5% cost reduction goal.

Main Outcomes and Measures

The primary outcome was each group's median surgical supply cost per case. Secondary outcome measures included total departmental surgical supply costs, case mix index-adjusted median surgical supply costs, patient outcomes (30-day readmission, 30-day mortality, and discharge status), and surgeon responses to a postintervention study-specific health care value survey.

Results

The median surgical supply direct costs per case decreased 6.54% in the intervention group, from $1398 (interquartile range [IQR], $316-$5181) (10 637 cases) in 2014 to $1307 (IQR, $319-$5037) (11 820 cases) in 2015. In contrast, the median surgical supply direct cost increased 7.42% in the control group, from $712 (IQR, $202-$1602) (16 441 cases) in 2014 to $765 (IQR, $233-$1719) (17 227 cases) in 2015. This decrease represents a total savings of $836 147 in the intervention group during the 1-year study. After controlling for surgeon, department, patient demographics, and clinical indicators in a mixed-effects model, there was a 9.95% (95% CI, 3.55%-15.93%; P = .003) surgical supply cost decrease in the intervention group over 1 year. Patient outcomes were equivalent or improved after the intervention, and surgeons who received scorecards reported higher levels of cost awareness on the health care value survey compared with controls.

Conclusions and Relevance

Cost feedback to surgeons, combined with a small departmental financial incentive, was associated with significantly reduced surgical supply costs, without negatively affecting patient outcomes.

Analysis of National Rates, Cost, and Sources of Cost Variation in Adult Spinal Deformity

BACKGROUND

Several studies suggest significant variation in cost for spine surgery, but there has been little research in this area for spinal deformity.

OBJECTIVE

To determine the utilization, cost, and factors contributing to cost for spinal deformity surgery.

METHODS

The cohort comprised 55 599 adults who underwent spinal deformity fusion in the 2001 to 2013 National Inpatient Sample database. Patient variables included age, gender, insurance, median income of zip code, county population, severity of illness, mortality risk, number of comorbidities, length of stay, elective vs nonelective case. Hospital variables included bed size, wage index, hospital type (rural, urban nonteaching, urban teaching), and geographical region. The outcome was total hospital cost for deformity surgery. Statistics included univariate and multivariate regression analyses.

RESULTS

The number of spinal deformity cases increased from 1803 in 2001 (rate: 4.16 per 100 000 adults) to 6728 in 2013 (rate: 13.9 per 100 000). Utilization of interbody fusion devices increased steadily during this time period, while bone morphogenic protein usage peaked in 2010 and declined thereafter. The mean inflation-adjusted case cost rose from $32 671 to $43 433 over the same time period. Multivariate analyses showed the following patient factors were associated with cost: age, race, insurance, severity of illness, length of stay, and elective admission (P &lt; .01). Hospitals in the western United States and those with higher wage indices or smaller bed sizes were significantly more expensive (P &lt; .05).

CONCLUSION

The rate of adult spinal deformity surgery and the mean case cost increased from 2001 to 2013, exceeding the rate of inflation. Both patient and hospital factors are important contributors to cost variation for spinal deformity surgery.

Analysis of Cost Variation in Craniotomy for Tumor Using 2 National Databases

BACKGROUND

There is a significant increase and large variation in craniotomy costs. However, the causes of cost differences in craniotomies remain poorly understood.

OBJECTIVE

To examine the patient and hospital factors that underlie the cost variation in tumor craniotomies using 2 national databases: the National Inpatient Sample (NIS) and Vizient, Inc. (Irving, Texas).

METHODS

For 41 483 patients who underwent primary surgery for supratentorial brain tumors from 2001 to 2013 in the NIS, we created univariate and multivariate models to evaluate the effect of several patient factors and hospital factors on total hospital cost. Similarly, we performed multivariate analysis with 15 087 cases in the Vizient 2012 to 2015 database.

RESULTS

In the NIS, the mean inflation-adjusted cost per tumor craniotomy increased 30%, from $23 021 in 2001 to $29 971 in 2013. In 2001, the highest cost region was the Northeast ($24 486 ± $1184), and by 2013 the western United States was the highest cost region ($36 058 ± $1684). Multivariate analyses with NIS data showed that male gender, white race, private insurance, higher mortality risk, higher severity of illness, longer length of stay, elective admissions, higher wage index, urban teaching hospitals, and hospitals in the western United States were associated with higher tumor craniotomy costs (all P &lt; .05). Multivariate analyses with Vizient data confirmed that longer length of stay and the western United States were significantly associated with higher costs (P &lt; .001).

CONCLUSION

After controlling for patient/clinical factors, hospital type, bed size, and wage index, hospitals in the western United States had higher costs than those in other parts of the country, based on analyses from 2 separate national databases.

Using health-system-wide data to understand hepatitis B virus prophylaxis and reactivation outcomes in patients receiving rituximab

Hepatitis B virus (HBV) reactivation in the setting of rituximab use is a potentially fatal but preventable safety event. The rate of HBV screening and proportion of patients at risk who receive antiviral prophylaxis in patients initiating rituximab is unknown.We analyzed electronic health record (EHR) data from 2 health systems, a university center and a safety net health system, including diagnosis grouper codes, problem lists, medications, laboratory results, procedures codes, clinical encounter notes, and scanned documents. We identified all patients who received rituximab between 6/1/2012 and 1/1/2016. We calculated the proportion of rituximab users with inadequate screening for HBV according to the Centers for Disease Control guidelines for detecting latent HBV infection before their first rituximab infusion during the study period. We also assessed the proportion of patients with positive hepatitis B screening tests who were prescribed antiviral prophylaxis. Finally, we characterized safety failures and adverse events.We included 926 patients from the university and 132 patients from the safety net health system. Sixty-one percent of patients from the university had adequate screening for HBV compared with 90% from the safety net. Among patients at risk for reactivation based on results of HBV testing, 66% and 92% received antiviral prophylaxis at the university and safety net, respectively.We found wide variations in hepatitis B screening practices among patients receiving rituximab, resulting in unnecessary risks to patients. Interventions should be developed to improve patient safety procedures in this high-risk patient population.