Teaching and Safety-Net Hospital Penalization in the Hospital-Acquired Condition Reduction Program.

Importance: The Hospital-Acquired Condition Reduction Program (HACRP) evaluates acute care hospitals on the occurrence of patient safety events and health care-associated infections. Since its implementation, several studies have raised concerns about the overpenalization of teaching and safety-net hospitals, and although several changes in the program's methodology have been applied in the last few years, whether these changes reversed the overpenalization of teaching and safety-net hospitals is unknown. Objective: To determine hospital characteristics associated with HACRP penalization and penalization reversal. Design, Setting, and Participants: This retrospective cross-sectional study assessed data from 3117 acute care hospitals participating in the HACRP. The HACRP penalization and hospital characteristics were obtained from Hospital Compare (2020 and 2021), the Inpatient Prospective Payment System impact file (2020), and the American Hospital Association annual survey (2018). Exposures: Hospital characteristics, including safety-net status and teaching intensity (no teaching and very minor, minor, major, and very major teaching levels). Main Outcomes and Measures: The primary outcome was HACRP penalization (ie, hospitals that fell within the worst quartile of the program's performance). Multivariable models initially included all covariates, and then backward stepwise variable selection was used. Results: Of 3117 hospitals that participated in HACRP in 2020, 779 (25.0%) were safety-net hospitals and 1090 (35.0%) were teaching institutions. In total, 771 hospitals (24.7%) were penalized. The HACRP penalization was associated with safety-net status (odds ratio [OR], 1.41 [95% CI, 1.16-1.71]) and very major teaching intensity (OR, 1.94 [95% CI, 1.15-3.28]). In addition, non-federal government hospitals were more likely to be penalized than for-profit hospitals (OR, 1.62 [95% CI, 1.23-2.14]), as were level I trauma centers (OR, 2.05 [95% CI, 1.43-2.96]) and hospitals located in the New England region (OR, 1.65 [95% CI, 1.12-2.43]). Safety-net hospitals with major teaching levels were twice as likely to be penalized as non-safety-net nonteaching hospitals (OR, 2.15 [95% CI, 1.14-4.03]). Furthermore, safety-net hospitals penalized in 2020 were less likely (OR, 0.64 [95% CI, 0.43-0.96]) to revert their HACRP penalization status in 2021. Conclusions and Relevance: Findings from this cross-sectional study indicated that teaching and safety-net hospital status continued to be associated with overpenalization in the HACRP despite recent changes in its methodology. Most of these hospitals were also less likely to revert their penalization status. A reevaluation of the program methodology is needed to avoid depleting resources of hospitals caring for underserved populations.

Describing characteristics of adults with and without congenital heart defects hospitalized with COVID-19.

BACKGROUND: We sought to describe patient characteristics in adults with and without congenital heart defects (CHDs) during hospitalization for COVID-19. METHODS: We analyzed data collected by Optum®, a nationally representative database of electronic medical records, for 369 adults with CHDs and 41,578 without CHDs hospitalized for COVID-19 between January 1, 2020, and December 10, 2020. We used Poisson regression to describe and compare epidemiologic characteristics, heart-related conditions, and severe outcomes between these two groups. RESULTS: The distributions of many epidemiologic characteristics were similar between the two groups, but patients with CHDs were significantly more likely to be current or former smokers compared to patients without CHDs (risk ratio [RR]: 1.5, 95% confidence interval [CI]: 1.2, 1.8). Patients with CHDs were also significantly more likely to have heart failure, stroke, acute arrhythmia, myocardial injury, acute pulmonary hypertension, venous thromboembolism, and obesity documented at the time of the COVID-19 hospitalization (RR range: 1.5-4.7) but not respiratory failure. Patients with CHDs (7 days) had a significantly longer median length of stay than those without CHDs (5 days; p < .001) and were significantly more likely to have an intensive care unit (ICU) admission (RR: 1.6, 95 CI: 1.2-1.9). CONCLUSIONS: Our description of patients among a large population improves our understanding of the clinical course of COVID-19 among adults with CHDs. Adults with CHD appear to be at greater risk for more severe CHD, including greater risk of ICU admission and longer length of hospital stays.

Microcephaly inpatient hospitalization and potential Zika outbreak in Texas: A cost and predicted economic burden analysis.

OBJECTIVE: Estimate inpatient hospitalization costs for patients with microcephaly, and predict cost increases due to a potential Zika virus outbreak. METHODS: We identified Texas-wide inpatient hospitalization discharge records (2008-2015), for newborns and non-newborns with microcephaly. We estimated the cost of each hospitalization by applying cost-to-charge ratios on the actual hospitalization charge. For comparison, newborn visits for patients without microcephaly were also identified, and hospital costs were compared between patients with and without microcephaly. We estimated costs for microcephaly during the first year of life following a Zika outbreak (possible 1-50% increase in birth prevalence) in Texas. RESULTS: There were 8005 microcephaly hospitalizations ($203,899,042; total cost). The median admission cost for newborns with microcephaly (N = 1393) was higher compared to those without microcephaly ($6751 vs $725, p < 0.001). Microcephaly hospitalizations of newborns had a lower median cost compared to non-newborns ($6751 vs $9754, p < 0.001). Based on these observed hospitalization costs, we estimated that a potential Zika virus outbreak in Texas could result in an additional $1-6 million per year for hospitalizations. CONCLUSION: Hospitalizations of patients with microcephaly are associated with high costs. An increase in microcephaly prevalence due to a Zika outbreak in Texas could have a considerable impact on health care costs.

Achieving Adherence After First-Line Antihypertensive Treatment: Should Fixed-Dose Combinations Receive Priority?

Data on the long-term outcomes of the use of fixed-dose combinations (FDCs) or free-pill combinations (FPCs), titration of doses, and switching are currently unavailable for identifying a preferred strategy for adherence. In the lack of these evidences, adherence can be a useful guiding criteria. The authors conducted a retrospective cohort study using the BlueCross BlueShield of Texas (2008-2012) database to compare adherence among 5998 patients who received treatment modifications (TMs). Results of the propensity score-adjusted model indicate that FDC and uptitration strategies have higher odds of adherence compared with the switch strategy (P<.05). Among patients with a history of poor adherence, the odds of adherence were up to 26% higher for the FDC strategy compared with alternative strategies (P<.05). Factors including age, number of comedications, first-line drug class, and health services utilization are associated with adherence. In conclusion, FDCs should be prioritized for TM, particularly if the patient has a history of poor adherence.

Patterns of treatment modifications among newly treated hypertensive patients: does choice of modification strategy affect likelihood of treatment discontinuation?

OBJECTIVES: Treatment modifications--addition, uptitration, switching, and downtitration--are necessary to address issues such as unattained blood pressure goals, adverse drug events, drug cost, or patient dissatisfaction which lead to treatment discontinuation. This study assessed the patterns of treatment modifications, and compared the rates of treatment modification and time-to-treatment modification across five antihypertensive drug classes (ADCs). Additionally, the association between treatment modification strategies and the likelihood of treatment discontinuation was assessed. METHODS: This is a retrospective cohort study using the BlueCross-BlueShield of Texas commercial claims database (2008-2012). Treatment modifications that occurred within 1 year of starting hypertension treatment were identified. Patients who received treatment modifications were followed for 12 months to determine if and when they discontinued treatment. Cox regression models were used to determine the likelihood of treatment modification and treatment discontinuation. RESULTS: About 48.5% of patients received treatment modifications within 1 year of treatment initiation. Rates of treatment modification were significantly different across ADCs; angiotensin-converting enzyme inhibitor and angiotensin receptor blocker users were less likely to receive treatment modifications compared with other ADCs. Mean time-to-treatment modification was more than 100 days for adding and uptitrating, and more than 140 days for switching and downtitrating. Patients intensifying treatment by adding medications were about 25% (vs. uptitration) and 50% (vs. switching) less likely to discontinue treatment. CONCLUSION: Treatment modifications are common among newly treated hypertensive patients, and the rates vary significantly across ADCs. In the real world, treatment modifications occur much later than the 30-day timeline recommended by guidelines. Addition of drugs may be a preferred approach for intensifying treatment of patients at a high risk of treatment discontinuation.