COVID-19 Admission Rates and Changes in Care Quality in US Hospitals.

Importance: Unprecedented increases in hospital occupancy rates during COVID-19 surges in 2020 caused concern over hospital care quality for patients without COVID-19. Objective: To examine changes in hospital nonsurgical care quality for patients without COVID-19 during periods of high and low COVID-19 admissions. Design, Setting, and Participants: This cross-sectional study used data from the 2019 and 2020 Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project State Inpatient Databases. Data were obtained for all nonfederal, acute care hospitals in 36 states with admissions in 2019 and 2020, and patients without a diagnosis of COVID-19 or pneumonia who were at risk for selected quality indicators were included. The data analysis was performed between January 1, 2023, and March 15, 2024. Exposure: Each hospital and week in 2020 was categorized based on the number of COVID-19 admissions per 100 beds: less than 1.0, 1.0 to 4.9, 5.0 to 9.9, 10.0 to 14.9, and 15.0 or greater. Main Outcomes and Measures: The main outcomes were rates of adverse outcomes for selected quality indicators, including pressure ulcers and in-hospital mortality for acute myocardial infarction, heart failure, acute stroke, gastrointestinal hemorrhage, hip fracture, and percutaneous coronary intervention. Changes in 2020 compared with 2019 were calculated for each level of the weekly COVID-19 admission rate, adjusting for case-mix and hospital-month fixed effects. Changes during weeks with high COVID-19 admissions (≥15 per 100 beds) were compared with changes during weeks with low COVID-19 admissions (<1 per 100 beds). Results: The analysis included 19 111 629 discharges (50.3% female; mean [SD] age, 63.0 [18.0] years) from 3283 hospitals in 36 states. In weeks 18 to 48 of 2020, 35 851 hospital-weeks (36.7%) had low COVID-19 admission rates, and 8094 (8.3%) had high rates. Quality indicators for patients without COVID-19 significantly worsened in 2020 during weeks with high vs low COVID-19 admissions. Pressure ulcer rates increased by 0.09 per 1000 admissions (95% CI, 0.01-0.17 per 1000 admissions; relative change, 24.3%), heart failure mortality increased by 0.40 per 100 admissions (95% CI, 0.18-0.63 per 100 admissions; relative change, 21.1%), hip fracture mortality increased by 0.40 per 100 admissions (95% CI, 0.04-0.77 per 100 admissions; relative change, 29.4%), and a weighted mean of mortality for the selected indicators increased by 0.30 per 100 admissions (95% CI, 0.14-0.45 per 100 admissions; relative change, 10.6%). Conclusions and Relevance: In this cross-sectional study, COVID-19 surges were associated with declines in hospital quality, highlighting the importance of identifying and implementing strategies to maintain care quality during periods of high hospital use.

Catholic Hospital Affiliation and Postpartum Contraceptive Care and Subsequent Deliveries.

Importance: In recent years, the number of Catholic hospitals has grown, raising concerns about access to contraception. The association between living in an area in which the closest hospital is Catholic and the probability of postpartum contraception and subsequent deliveries is unknown. Objective: To assess whether living in an area in which the closest hospital was Catholic was associated with the probability of postpartum contraception and subsequent deliveries. Design, Setting, and Participants: This cohort study used data from the Healthcare Cost and Utilization Project's State Inpatient Databases, State Emergency Department Databases, and State Ambulatory Surgery and Services Databases for 11 states (California, Florida, Georgia, Missouri, Nebraska, Nevada, New York, South Carolina, Tennessee, Vermont, and Wisconsin). Female patients with a delivery from 2016 to 2019 who lived within 20 miles of a nonfederal acute care hospital were included, with patients followed up for 1 to 3 years. Coarsened exact matching was used to match patients based on the county-level percentage of the population affiliated with Catholic churches and urbanicity, and the zip code-level number of hospitals within 5 and 20 miles, median household income, and percentage of the population by race and ethnicity. Data were analyzed from April 2022 to November 2023. Exposures: Residence in a zip code in which the closest hospital was Catholic. Main Outcomes and Measures: Probabilities of delivery at a Catholic hospital, surgical sterilization within 1 year of delivery, receipt of long-acting reversible contraception at delivery, and subsequent delivery within 3 years. Results: The sample consisted of 4 101 443 deliveries (1 301 792 after matching), with 14.5% of patients living in exposed zip codes (ie, where the closest hospital was Catholic). Living in exposed zip codes was associated with a 21.26-percentage point (pp) increase in the probability of delivery at a Catholic hospital (95% CI, 19.50 to 23.02 pp; 237.3% relative to the mean in unexposed zip codes; P < .001). Additionally, comparing exposed vs unexposed zip codes, the probability of surgical sterilization at delivery decreased by 0.95 pp (95% CI, -1.14 to -0.76 pp; P < .001) and the probability of sterilization in the year after discharge further decreased by 0.21 pp (95% CI, -0.29 to -0.13; P < .001). Subsequent deliveries within 3 years increased 0.47 pp (95% CI, -0.03 to 0.97 pp; 2.3% relative to the mean in unexposed zip codes; P = .07). Conclusions and Relevance: This cohort study finds that living in a zip code in which the closest hospital was Catholic was associated with a modest decrease in the probability of postpartum surgical sterilizations and a modest increase in the probability of subsequent deliveries.

Interruptions in Insurance Coverage and Prescription Drug Utilization: Evidence from Kentucky.

This study examined how interruptions in insurance coverage affect purchases of prescription drugs for young adults. It used data spanning 2014 to 2018 from Kentucky's prescription drug monitoring program, which tracked the universe of federally-regulated (Schedule II-V) prescription drugs dispensed in the state. The study employed a regression discontinuity design based on the age limit at 26 for dependent insurance coverage for children. At age 26, the probability of purchasing a prescription decreased by 5%, with all subcategories of prescriptions affected. The share of generic prescriptions increased for stimulants (the only category observed with substantial branded prescriptions). By age 27, prescription purchases returned to levels observed at 25, but the share purchased with public insurance and the generic share for stimulants remained higher. The findings suggest that interruptions in insurance coverage decrease prescription drug utilization by young adults and that public insurance programs such as Medicaid are important for resuming treatment.

The consequences of firm scope and scale on patient access to healthcare.

OBJECTIVE: The aim was to quantify changes in the market structure of primary care physicians and examine its relationship with access to care. DATA SOURCES AND STUDY SETTING: We created measures of market structure from a 5% sample of Medicare fee-for-service claims and examined access to care using nationally representative data from the Medical Expenditure Panel Survey (MEPS). Our study spanned from 2008 to 2019. STUDY DESIGN: We used a linear probability model to estimate the relationship between access to care and two measures of market structure: concentration, measured by the Herfindahl-Hirschman Index (HHI), and vertical integration, measured by the market share of multispecialty firms. Our model controlled for year and ZIP code fixed effects, respondents' demographics and health status, and other measures of market structure. DATA COLLECTION/EXTRACTION METHODS: All adult respondents in the MEPS were included. PRINCIPAL FINDINGS: The percentage of people living in concentrated ZIP codes (HHI above 1500) increased from 37% in 2008 to 53% in 2019. During the same period, the median market share of multispecialty firms rose from 30% to 48%. Respondents in highly concentrated ZIP codes (HHI over 2500) were 5.9 percentage points (95% CI: -1.4 to -10.4) less likely to report having access to immediate care than respondents in unconcentrated ZIP codes. The association was largest among Medicaid beneficiaries, a 17.3 percentage point reduction (95% CI: -5.1 to -29.4). When we applied a model that was robust to biases from treatments with staggered timing, the estimated association remained negative but was not statistically significant. We found no association between HHI and indicators for having a usual source of care and annual checkups. The multispecialty market share was negatively associated with checkups, but not other measures of access. CONCLUSIONS: Increases in concentration may reduce some types of access to healthcare. These effects appear most pronounced among Medicaid beneficiaries.

COVID-19 Admission Rates and Changes in US Hospital Inpatient and Intensive Care Unit Occupancy.

Importance: The COVID-19 pandemic had unprecedented effects on hospital occupancy, with consequences for hospital operations and patient care. Previous studies of occupancy during COVID-19 have been limited to small samples of hospitals. Objective: To measure the association between COVID-19 admission rates and hospital occupancy in different US areas and at different time periods during 2020. Design, Setting, and Participants: This cross-sectional study used data from the Healthcare Cost and Utilization Project State Inpatient Databases (2019-2020) for patients in nonfederal acute care hospitals in 45 US states, including the District of Columbia. Data analysis was performed between September 1, 2022, and April 30, 2023. Exposures: Each hospital and week in 2020 was categorized based on the number of COVID-19 admissions per 100 beds (<1 [low], 1-4.9, 5-9.9, 10-14.9, or ≥15 [high]). Main Outcomes and Measures: The main outcomes were inpatient and intensive care unit (ICU) occupancy. We used regression analysis to estimate the average change in occupancy for each hospital-week in 2020 relative to the same hospital week in 2019. Results: This study included 3960 hospitals and 54 355 916 admissions. Of the admissions in the 40 states used for race and ethnicity analyses, 15.7% were for Black patients, 12.9% were for Hispanic patients, 62.5% were for White patients, and 7.2% were for patients of other race or ethnicity; 1.7% of patients were missing these data. Weekly COVID-19 admission rates in 2020 were less than 4 per 100 beds for 63.9% of hospital-weeks and at least 10 in only 15.9% of hospital-weeks. Inpatient occupancy decreased by 12.7% (95% CI, 12.1% to 13.4%) during weeks with low COVID-19 admission rates and increased by 7.9% (95% CI, 6.8% to 9.0%) during weeks with high COVID-19 admission rates. Intensive care unit occupancy rates increased by 67.8% (95% CI, 60.5% to 75.3%) during weeks with high COVID-19 admissions. Increases in ICU occupancy were greatest when weighted to reflect the experience of Hispanic patients. Changes in occupancy were most pronounced early in the pandemic. During weeks with high COVID-19 admissions, occupancy decreased for many service lines, with occupancy by surgical patients declining by 43.1% (95% CI, 38.6% to 47.2%) early in the pandemic. Conclusions and Relevance: In this cross-sectional study of US hospital discharges in 45 states in 2020, hospital occupancy decreased during weeks with low COVID-19 admissions and increased during weeks with high COVID-19 admissions, with the largest changes occurring early in the pandemic. These findings suggest that surges in COVID-19 strained ICUs and were associated with large decreases in the number of surgical patients. These occupancy fluctuations may have affected quality of care and hospital finances.

Mandatory prescription drug monitoring programs and overlapping prescriptions of opioids and benzodiazepines: Evidence from Kentucky.

BACKGROUND: In response to the opioid epidemic, many states implemented mandates requiring providers to check prescription drug monitoring programs (PDMPs) before prescribing opioids. We examine how overlapping benzodiazepine and opioid prescriptions changed after Kentucky implemented a PDMP mandate in July 2012. METHODS: We conducted an interrupted time series analysis using monthly data from Kentucky's PDMP from 2010 to 2016. Separate analyses were conducted for overlapping prescriptions from a single provider or multiple providers, and by sex and age group. We also conducted an individual-level longitudinal analysis that compared changes in utilization patterns after the mandate went into effect to changes in earlier periods during which the mandate was not in effect. RESULTS: Kentucky's PDMP mandate was associated with an immediate 7.5 % decline in the rate of overlapping benzodiazepine and opioid prescriptions and a significant change in the trend from increasing to decreasing. Approximately half of the immediate effect in level terms was explained by decreases in overlapping prescriptions written by a single provider. Our longitudinal analysis suggests that over one year the mandate reduced initiation of overlapping prescriptions by 29.3 % and reduced continuation of overlapping prescriptions by 9.4 %. The effects of the policy were largest for women and men aged 36-50. CONCLUSIONS: Though not the main rationale for the policy, Kentucky's PDMP mandate reduced overlapping prescriptions of benzodiazepines and opioids. Further efforts to reduce overlapping prescriptions should consider the effects on populations such as women over 50, who have high rates of overlapping prescriptions.

The Effects of the Medicaid Expansion on Hospital Utilization, Employment, and Capital.

In recent years, hospitals reacted to changes in demand caused by the Affordable Care Act Medicaid expansions. We conducted a difference-in-differences analysis that compared changes to hospital demand and supply in Medicaid expansion and nonexpansion states. We used 2010-2016 data from the American Hospital Association and the Healthcare Cost Report Information System to quantify changes to hospital utilization and characterize how hospitals adjusted labor and capital inputs. During the period studied, the Medicaid expansion was associated with increases in emergency department visits and other outpatient hospital visits. We find strong evidence that hospitals met increases in demand by hiring nursing staff and weaker evidence that they increased hiring of technicians and investments in equipment. We found no evidence that hospitals adjusted hiring of physicians, support staff, or investments in other capital inputs.

Provider Compliance With Kentucky's Prescription Drug Monitoring Program's Mandate To Query Patient Opioid History.

Forty states mandate that providers query their patients' prescription histories in the state's prescription drug monitoring program (PDMP) before prescribing controlled substances. However, little is known about providers' use of PDMPs, either with or without a mandate. We measured the share of opioid prescriptions with PDMP queries in Kentucky from 2010 to 2018, before and after the implementation of the first comprehensive PDMP mandate in the US. Providers queried the PDMP for 12 percent of opioid prescriptions before the mandate; after the mandate, they queried for 56 percent of prescriptions. The share of prescriptions queried was lowest for patients without recent opioid use (3 percent before the mandate, 25 percent after) and highest for pain management specialists (31 percent before, 72 percent after). Over time, high-compliance providers reduced prescribing to the riskiest patients, whereas low-compliance providers continued to prescribe to them. Although the share of prescriptions queried greatly increased after the mandate, compliance remained incomplete, including for patients with high-risk patterns of opioid use.

How well do doctors know their patients? Evidence from a mandatory access prescription drug monitoring program.

Many opioid control policies target the prescribing behavior of health care providers. In this paper, we study the first comprehensive state-level policy requiring providers to access patients' opioid history before making prescribing decisions. We compare prescribers in Kentucky, which implemented this policy in 2012, to those in a control state, Indiana. Our main difference-in-differences analysis uses the universe of prescriptions filled in the two states to assess how the information provided affected prescribing behavior. We find that a significant share of low-volume providers stopped prescribing opioids altogether after the policy was implemented, though this change accounted for a small share of the reduction in total volume. The most important margin of response was to prescribe opioids to fewer patients. Although providers disproportionately discontinued treating patients whose opioid histories showed the use of multiple providers, there were also economically meaningful reductions for patients without multiple providers and single-use acute patients.