Physician Work Hours and the Gender Pay Gap - Evidence from Primary Care.

BACKGROUND: The gender gap in physician pay is often attributed in part to women working fewer hours than men, but evidence to date is limited by self-report and a lack of detail regarding clinical revenue and gender differences in practice style. METHODS: Using national all-payer claims and data from electronic health records, we conducted a cross-sectional analysis of 24.4 million primary care office visits in 2017 and performed comparisons between female and male physicians in the same practices. Our primary independent variable was physician gender; outcomes included visit revenue, visit counts, days worked, and observed visit time (interval between the initiation and the termination of a visit). We created multivariable regression models at the year, day, and visit level after adjustment for characteristics of the primary care physicians (PCPs), patients, and types of visit and for practice fixed effects. RESULTS: In 2017, female PCPs generated 10.9% less revenue from office visits than their male counterparts (-$39,143.2; 95% confidence interval [CI], -53,523.0 to -24,763.4) and conducted 10.8% fewer visits (-330.5 visits; 95% CI, -406.6 to -254.3) over 2.6% fewer clinical days (-5.3 days; 95% CI, -7.7 to -3.0), after adjustment for age, academic degree, specialty, and number of sessions worked per week, yet spent 2.6% more observed time in visits that year than their male counterparts (1201.3 minutes; 95% CI, 184.7 to 2218.0). Per visit, after adjustment for PCP, patient, and visit characteristics, female PCPs generated equal revenue but spent 15.7% more time with a patient (2.4 minutes; 95% CI, 2.1 to 2.6). These results were consistent in subgroup analyses according to the gender and health status of the patients and the type and complexity of the visits. CONCLUSIONS: Female PCPs generated less visit revenue than male colleagues in the same practices owing to a lower volume of visits, yet spent more time in direct patient care per visit, per day, and per year. (Funded in part by the Robert Wood Johnson Foundation.).

Association of Evaluation and Management Payment Policy Changes With Medicare Payment to Physicians by Specialty.

Importance: US primary care physicians (PCPs) have lower mean incomes than specialists, likely contributing to workforce shortages. In 2021, the Centers for Medicare & Medicaid Services increased payment for evaluation and management (E/M) services and relaxed documentation requirements. These changes may have reduced the gap between primary care and specialist payment. Objectives: To simulate the effect of the E/M payment policy change on total Medicare physician payments while holding volume constant and to compare these simulated changes with observed changes in total Medicare payments and E/M coding intensity, before (July-December 2020) and after (July-December 2021) the E/M payment policy change. Design, Setting, and Participants: Retrospective observational study of US office-based physicians who were in specialties with 5000 or more physicians billing Medicare and who had 50 or more fee-for-service Medicare visits before and after the E/M payment policy change. Exposures: E/M payment policy changes. Main Outcomes and Measures: Outcomes included physician-level simulated volume-constant payment change, total observed Medicare payment change, and share of high-intensity (ie, level 4 or 5) E/M visits before and after the E/M payment policy change. For each specialty, the median change in each outcome was reported. The payment gap between primary care and specialty physicians was calculated as the difference between total Medicare payments to the median primary care and median specialty physician. Results: The study population included 180 624 physicians. Repricing 2020 services yielded a simulated volume-constant payment change ranging from a 3.3% (-$4557.0) decrease for the median radiologist to an 11.0% ($3683.1) increase for the median family practice physician. After the E/M payment change, the median high-intensity share of E/M visits increased for physicians of nearly all specialties, ranging from a -4.4 percentage point increase (dermatology) to a 17.8 percentage point increase (psychiatry). The median change in total Medicare payments by specialty ranged from -4.2% (-$1782.9) for general surgery to 12.1% ($3746.9) for family practice. From July-December 2020 to July-December 2021, the payment gap between the median primary care physician and the median specialist shrank by $825.1, from $40 259.8 to $39 434.7 (primary care, $41 193.3 in July-December 2020 and $45 962.4 in July-December 2021; specialist, $81 453.1 in July-December 2020 and $85 397.1 in July-December 2021)-a relative decrease of 2.0%. Conclusions and Relevance: Among US office-based physicians receiving Medicare payments in 2020 and 2021, E/M payment policy changes were associated with changes in Medicare payment by specialty, although the payment gap between primary care physicians and specialists decreased only modestly. The findings may have been influenced by the COVID-19 pandemic, and further research in subsequent years is needed.

Factors associated with patient trust in their clinicians: Results from the Healthy Work Place Study.

BACKGROUND: Patient trust in their clinicians is an important aspect of health care quality, but little evidence exists on what contributes to patient trust. PURPOSE: The aim of this study was to determine workplace, clinician, and patient correlates of patient trust in their clinician. METHODOLOGY/APPROACH: The sample used baseline data from the Healthy Work Place trial, a randomized trial of 34 Midwest and East Coast primary care practices to explore factors associated with patient trust in their clinicians. A multivariate "best subset" regression modeling approach was used, starting with an item pool of 45 potential variables. Over 7 million models were tested, with a best subset of correlates determined using standard methods for scale optimization. Skewed variables were transformed to the fifth power using a Box-Cox algorithm. RESULTS: The final model of nine variables explained 38% of variance in patient trust at the patient level and 49% at the clinician level. Trust was related mainly to several aspects of care variables (including satisfaction with explanations, overall satisfaction with provider, and learning about their medical conditions and their clinician's personal manner), with lesser association with patient characteristics and clinician work conditions. CONCLUSION: Trust appears to be primarily related to what happens between clinicians and patients in the examination room. PRACTICE IMPLICATIONS: System changes such as patient-centered medical homes may have difficulty succeeding if the primacy of physician-patient interactions in inspiring patient trust and satisfaction is not recognized.

Measuring Primary Care Exam Length Using Electronic Health Record Data.

BACKGROUND: Physicians' time with patients is a critical input to care, but is typically measured retrospectively through survey instruments. Data collected through the use of electronic health records (EHRs) offer an alternative way to measure visit length. OBJECTIVE: To measure how much time primary care physicians spend with their patients, during each visit. RESEARCH DESIGN: We used a national source of EHR data for primary care practices, from a large health information technology company. We calculated exam length and schedule deviations based on timestamps recorded by the EHR, after implementing sequential data refinements to account for non-real-time EHR use and clinical multitasking. Observational analyses calculated and plotted the mean, median, and interquartile range of exam length and exam length relative to scheduled visit length. SUBJECTS: A total of 21,010,780 primary care visits in 2017. MEASURES: We identified primary care visits based on physician specialty. For these visits, we extracted timestamps for EHR activity during the exam. We also extracted scheduled visit length from the EHR's practice management functionality. RESULTS: After data refinements, the average primary care exam was 18.0 minutes long (SD=13.5 min). On average, exams ran later than their scheduled duration by 1.2 minutes (SD=13.5 min). Visits scheduled for 10 or 15 minutes were more likely to exceed their allotted time than visits scheduled for 20 or 30 minutes. CONCLUSIONS: Time-stamped EHR data offer researchers and health systems an opportunity to measure exam length and other objects of interest related to time.

Abrupt Discontinuation of Long-term Opioid Therapy Among Medicare Beneficiaries, 2012-2017.

BACKGROUND: With mounting pressure to reduce opioid use, concerns exist about abrupt withdrawal of treatment for the millions of Americans using long-term opioid therapy (LTOT). However, little is known about how patients are tapered from LTOT nationally. OBJECTIVE: Measure national patterns of LTOT discontinuation and adherence to recommended tapering speed. DESIGN: Observational study of Medicare Part D from 2012 to 2017. PARTICIPANTS: Using claims for a 20% sample of Medicare beneficiaries, we included patients on LTOT for 1 year or more, defined as those with ≥ 4 consecutive quarters with > 60 days of opioids supplied in each quarter. MAIN MEASURES: Our primary outcome was discontinuation of LTOT, defined as at least 60 consecutive days without opioids supplied. We additionally examined whether discontinuation of LTOT was "tapered" or "abrupt" by comparing LTOT users' daily MME dose in the last month of therapy to their average daily dose in a baseline period of 7 to 12 months before discontinuation. By the last month of therapy, patients with "abrupt" discontinuation had a < 50% reduction in their average daily dose at baseline. KEY RESULTS: From 2012 to 2017, there were 258,988 LTOT users, 17,617 of whom discontinued therapy. Adjusted rates of LTOT discontinuation increased from 5.7% of users in 2012 to 8.5% in 2017, a 49% relative increase (p < 0.001). There was a similar increase in annual discontinuation rate for LTOT users on lower (26-90 MME, 5.8% to 8.7%, p < 0.001) vs. higher doses (> 90 MME, 5.3% to 7.7%, p < 0.001). The majority of LTOT discontinuations were stopped abruptly, and increased over time (70.1% to 81.2%, 2012-2017, p < 0.001). CONCLUSIONS: Medicare beneficiaries on LTOT were increasingly likely to have their therapy discontinued from 2012 to 2017. The vast majority of discontinuing users, even those on high doses, had less than 50% reduction in dose, which is inconsistent with existing guidelines.

Where Trust Flourishes: Perceptions of Clinicians Who Trust Their Organizations and Are Trusted by Their Patients.

PURPOSE: Trust is an essential component of health care. Clinicians need to trust organizational leaders to provide a safe and effective work environment, and patients need to trust their clinicians to deliver high-quality care while addressing their health care needs. We sought to determine perceived characteristics of clinics by clinicians who trust their organizations and whose patients have trust in them. METHODS: We used baseline data from the Healthy Work Place trial, a randomized trial of interventions to improve work life in 34 Midwest and East Coast primary care clinics, to identify clinic characteristics associated with high clinician and patient trust. RESULTS: The study included 165 clinicians with 1,132 patients. High trust by clinicians with patients who trusted them was found for 34% of 162 clinicians with sufficient data for modeling. High clinician-high patient trust occurred when clinicians perceived their organizational cultures to have (1) an emphasis on quality (odds ratio [OR] 4.95; 95% CI, 2.02-12.15; P <.001), (2) an emphasis on communication and information (OR 3.21; 95% CI, 1.33-7.78; P = .01), (3) cohesiveness among clinicians (OR 2.29; 95% CI, 1.25-4.20; P = .008), and (4) values alignment between clinicians and leaders (OR 1.86; 95% CI, 1.23-2.81; P = .003). CONCLUSION: Addressing organizational culture might improve the trust of clinicians whose patients have high trust in them.

Practice Patterns of Physicians and Nurse Practitioners in Primary Care.

BACKGROUND: Primary care practices increasingly include nurse practitioners (NPs), in addition to physicians. Little is known about how the patient mix and clinical activities of colocated physicians and NPs compare. OBJECTIVES: To describe the clinical activities of NPs, compared with physicians. RESEARCH DESIGN: We used claims and electronic health record data from athenahealth Inc., on primary care practices in 2017 and a cross-sectional analysis with practice fixed effects. SUBJECTS: Patients receiving treatment from physicians and NPs within primary care practices. MEASURES: First, we measured patient characteristics (payer, age, sex, race, chronic condition count) and visit characteristics (new patient, scheduled duration, same-day visit, after-hours visit). Second, we measured procedures performed and diagnoses recorded during each visit. Finally, we measured daily quantity (visit volume, minutes scheduled for patient care, total work relative value units billed) of care. RESULTS: Relative to physicians, NPs treated younger and healthier patients. NPs also had a larger share of patients who were female, non-White, and covered by Medicaid, commercial insurance, or no insurance. NPs scheduled longer appointments and treated more patients on a same-day or after-hours basis. On average, "overlapping" services-those performed by NPs and physicians within the same practice-represented 92% of all service volume. The small share of services performed exclusively by physicians reflected greater clinical intensity. On a daily basis, NPs provided fewer and less intense visits than physicians within the same practice. CONCLUSIONS: Our findings suggest considerable overlap between the clinical activities of colocated NPs and physicians, with some differentiation based on intensity of services provided.

Time Pressure During Primary Care Office Visits: a Prospective Evaluation of Data from the Healthy Work Place Study.

BACKGROUND: The relationship between worklife factors, clinician outcomes, and time pressure during office visits is unclear. OBJECTIVE: To quantify associations between time pressure, workplace characteristics ,and clinician outcomes. DESIGN: Prospective analysis of data from the Healthy Work Place randomized trial. PARTICIPANTS: 168 physicians and advanced practice clinicians in 34 primary care practices in Upper Midwest and East Coast. MAIN MEASURES AND METHODS: Time pressure was present when clinicians needed more time than allotted to provide quality care. Other metrics included work control, work pace (calm to chaotic), organizational culture and clinician satisfaction, stress, burnout, and intent to leave the practice. Hierarchical analysis assessed relationships between time pressure, organizational characteristics, and clinician outcomes. Adjusted differences between clinicians with and without time pressure were expressed as effect sizes (ESs). KEY RESULTS: Sixty-seven percent of clinicians needed more time for new patients and 53% needed additional time for follow-up appointments. Time pressure in new patient visits was more prevalent in general internists than in family physicians (74% vs 55%, p < 0.05), women versus men (78% vs 55%, p < 0.01), and clinicians with larger numbers of complex psychosocial (81% vs 59%, p < 0.01) and Limited English Proficiency patients (95% vs 57%, p < 0.001). Time pressure in new patient visits was associated with lack of control, clinician stress, and intent to leave (ESs small to moderate, p < 0.05). Time pressure in follow-up visits was associated with chaotic workplaces and burnout (small to moderate ESs, p's < 0.05). Time pressure improved over time in workplaces with values alignment and an emphasis on quality. CONCLUSIONS: Time pressure, more common in women and general internists, was related to chaos, control and culture, and stress, burnout, and intent to leave. Future studies should evaluate these findings in larger and more geographically diverse samples.

The extent and growth of prior authorization in Medicare Advantage.

OBJECTIVES: To assess trends in the use of prior authorization requirements among Medicare Advantage (MA) plans. STUDY DESIGN: Descriptive quantitative analysis. METHODS: Data were from the CMS MA benefit and enrollment files for 2009-2019, supplemented with area-level data on demographic and provider market characteristics. For each service category, we calculated the annual share of MA enrollees in plans requiring at least some prior authorization and plotted trends over time. We mapped the county-level share of MA enrollees exposed to prior authorization in 2009 vs 2019. We quantified the association between local share of MA enrollees exposed to prior authorization and characteristics of that county in the same year. Finally, we plotted the share of MA enrollees exposed to prior authorization requirements over time for the 6 largest MA carriers. RESULTS: From 2009 to 2019, the share of MA enrollees in plans requiring prior authorization for any service remained stable. By service category, the share of MA enrollees exposed to prior authorization ranged from 30.7% (physician specialist services) to 72.2% (durable medical equipment) in 2019, with most service categories requiring prior authorization more often over time. Several area-level demographic and provider market characteristics were associated with prior authorization requirements, but these associations weakened over time. The use of prior authorization varied widely across plans. CONCLUSIONS: In 2019, roughly 3 in 4 MA enrollees were in a plan requiring prior authorization. Service-level, area-level, and carrier-level patterns suggest a wide range of approaches to prior authorization requirements.

What happens to rural hospitals during a ransomware attack? Evidence from Medicare data.

PURPOSE: Hospitals are increasingly the target of cybersecurity threats, including ransomware attacks. Little is known about how ransomware attacks affect care at rural hospitals. METHODS: We used data on hospital ransomware attacks from the Tracking Healthcare Ransomware Events and Traits database, linked to American Hospital Association survey data and Medicare fee-for-service (FFS) claims data from 2016 to 2021. We measured Medicare FFS volume and revenue in the inpatient, outpatient, and emergency room setting-at the hospital-week level. We then conducted a stacked event study analysis, comparing hospital volume and revenue at ransomware-attacked and nonattacked hospitals before and after attacks. FINDINGS: Ransomware attacks severely disrupted hospital operations-with comparable effects observed at rural versus urban hospitals. During the first week of the attack, inpatient admissions volume fell by 14.7% at rural hospitals (P = .04) and 16.9% at urban hospitals (P = .01)-recovering to preattack levels within 2-3 weeks. Outpatient visits fell by 35.3% at rural hospitals (P<.01) and 22.0% at urban hospitals (P = .03) during the first week. Emergency room visits fell by 10.0% at rural hospitals (P = .04) and 19.3% at urban hospitals (P = .01). Travel time and distance to the closest nonattacked hospital was 4-7 times greater for rural ransomware-attacked hospitals than for urban ransomware-attacked hospitals. CONCLUSIONS: Ransomware attacks disrupted hospital operations in rural and urban areas. Disruptions of similar magnitudes may be more detrimental in rural areas, given the greater distances patients must travel to receive care and the outsized impact that lost revenue may have on rural hospital finances.

Clinical and healthcare use outcomes after cessation of long term opioid treatment due to prescriber workforce exit: quasi-experimental difference-in-differences study.

OBJECTIVE: To examine the association between prescriber workforce exit, long term opioid treatment discontinuation, and clinical outcomes. DESIGN: Quasi-experimental difference-in-differences study SETTING: 20% sample of US Medicare beneficiaries, 2011-18. PARTICIPANTS: People receiving long term opioid treatment whose prescriber stopped providing office based patient care or exited the workforce, as in the case of retirement or death (n=48 079), and people whose prescriber did not exit the workforce (n=48 079). MAIN OUTCOMES: Discontinuation from long term opioid treatment, drug overdose, mental health crises, admissions to hospital or emergency department visits, and death. Long term opioid treatment was defined as at least 60 days of opioids per quarter for four consecutive quarters, attributed to the plurality opioid prescriber. A difference-in-differences analysis was used to compare individuals who received long term opioid treatment and who had a prescriber leave the workforce to propensity-matched patients on long term opioid treatment who did not lose a prescriber, before and after prescriber exit. RESULTS: Discontinuation of long term opioid treatment increased from 132 to 229 per 10 000 patients who had prescriber exit from the quarter before to the quarter after exit, compared with 97 to 100 for patients who had a continuation of prescriber (adjusted difference 1.22 percentage points, 95% confidence interval 1.02 to 1.42). In the first quarter after provider exit, when discontinuation rates were highest, a transient but significant elevation was noted between the two groups of patients in suicide attempts (adjusted difference 0.05 percentage points (95% confidence interval 0.01 to 0.09)), opioid or alcohol withdrawal (0.14 (0.01 to 0.27)), and admissions to hospital or emergency department visits (0.04 visits (0.01 to 0.06)). These differences receded after one to two quarters. No significant change in rates of overdose was noted. Across all four quarters after prescriber exit, an increase was reported in the rate of mental health crises (0.39 percentage points (95% confidence interval 0.08 to 0.69)) and opioid or alcohol withdrawal (0.31 (0.014 to 0.58)), but no change was seen for drug overdose (-0.12 (-0.41 to 0.18)). CONCLUSIONS: The loss of a prescriber was associated with increased occurrences of discontinuation of long term opioid treatment and transient increases in adverse outcomes, such as suicide attempts, but not other outcomes, such as overdoses. Long term opioid treatment discontinuation may be associated with a temporary period of adverse health impacts after accounting for unobserved confounding.

Artificial intelligence in Medicare: utilization, spending, and access to AI-enabled clinical software.

OBJECTIVES: In 2018, CMS established reimbursement for the first Medicare-covered artificial intelligence (AI)-enabled clinical software: CT fractional flow reserve (FFRCT) to assist in the diagnosis of coronary artery disease. This study quantified Medicare utilization of and spending on FFRCT from 2018 through 2022 and characterized adopting hospitals, clinicians, and patients. STUDY DESIGN: Analysis, using 100% Medicare fee-for-service claims data, of the hospitals, clinicians, and patients who performed or received coronary CT angiography with or without FFRCT. METHODS: We measured annual trends in utilization of and spending on FFRCT among hospitals and clinicians from 2018 through 2022. Characteristics of FFRCT-adopting and nonadopting hospitals and clinicians were compared, as well as the characteristics of patients who received FFRCT vs those who did not. RESULTS: From 2018 to 2022, FFRCT billing volume in Medicare increased more than 11-fold (from 1083 to 12,363 claims). Compared with nonbilling hospitals, FFRCT-billing hospitals were more likely to be larger, part of a health system, nonprofit, and financially profitable. FFRCT-billing clinicians worked in larger group practices and were more likely to be cardiac specialists. FFRCT-receiving patients were more likely to be male and White and less likely to be dually enrolled in Medicaid or receiving disability benefits. CONCLUSIONS: In the initial 5 years of Medicare reimbursement for FFRCT, growth was concentrated among well-resourced hospitals and clinicians. As Medicare begins to reimburse clinicians for the use of AI-enabled clinical software such as FFRCT, it is crucial to monitor the diffusion of these services to ensure equal access.

Association of Primary Care Visit Length With Potentially Inappropriate Prescribing.

Importance: Time is a valuable resource in primary care, and physicians and patients consistently raise concerns about inadequate time during visits. However, there is little evidence on whether shorter visits translate into lower-quality care. Objective: To investigate variations in primary care visit length and quantify the association between visit length and potentially inappropriate prescribing decisions by primary care physicians. Design, Setting, and Participants: This cross-sectional study used data from electronic health record systems in primary care offices across the US to analyze adult primary care visits occurring in calendar year 2017. Analysis was conducted from March 2022 through January 2023. Main Outcomes and Measures: Regression analyses quantified the association between patient visit characteristics and visit length (measured using time stamp data) and the association between visit length and potentially inappropriate prescribing decisions, including inappropriate antibiotic prescriptions for upper respiratory tract infections, coprescribing of opioids and benzodiazepines for painful conditions, and prescriptions that were potentially inappropriate for older adults (based on the Beers criteria). All rates were estimated using physician fixed effects and were adjusted for patient and visit characteristics. Results: This study included 8 119 161 primary care visits by 4 360 445 patients (56.6% women) with 8091 primary care physicians; 7.7% of patients were Hispanic, 10.4% were non-Hispanic Black, 68.2% were non-Hispanic White, 5.5% were other race and ethnicity, and 8.3% had missing race and ethnicity. Longer visits were more complex (ie, more diagnoses recorded and/or more chronic conditions coded). After controlling for scheduled visit duration and measures of visit complexity, younger, publicly insured, Hispanic, and non-Hispanic Black patients had shorter visits. For each additional minute of visit length, the likelihood that a visit resulted in an inappropriate antibiotic prescription changed by -0.11 percentage points (95% CI, -0.14 to -0.09 percentage points) and the likelihood of opioid and benzodiazepine coprescribing changed by -0.01 percentage points (95% CI, -0.01 to -0.009 percentage points). Visit length had a positive association with potentially inappropriate prescribing among older adults (0.004 percentage points; 95% CI, 0.003-0.006 percentage points). Conclusions and Relevance: In this cross-sectional study, shorter visit length was associated with a higher likelihood of inappropriate antibiotic prescribing for patients with upper respiratory tract infections and coprescribing of opioids and benzodiazepines for patients with painful conditions. These findings suggest opportunities for additional research and operational improvements to visit scheduling and quality of prescribing decisions in primary care.

Characteristics of short-term acute care hospitals that experienced a ransomware attack from 2016 to 2021.

As cybercrime increasingly targets the health care sector, hospitals face the growing threat of ransomware attacks. Ransomware is a type of malicious software that prevents users from accessing their electronic systems-demanding payment to restore access. In response, momentum is gathering to enact policy that will help hospitals strengthen their cybersecurity defenses. However, to design effective policy, it is crucial to understand the characteristics of hospitals associated with the risk of ransomware attack. In this paper, we compare the characteristics of ransomware-attacked and non-attacked short-term acute care hospitals in the United States. Using data from the American Hospital Association's Annual Survey and the Healthcare Cost Report Information System, we found that ransomware-attacked hospitals were larger, had higher net operating revenue, were more likely to be financially profitable, and more likely to provide trauma, emergency, and obstetric care than non-attacked hospitals. Measures of information technology sophistication did not vary between ransomware-attacked and non-attacked hospitals. These results can be used to tailor policy interventions in order to most effectively respond to and prevent cybercrime in health care.

Provision of evaluation and management visits by nurse practitioners and physician assistants in the USA from 2013 to 2019: cross-sectional time series study.

OBJECTIVE: To examine the proportion of healthcare visits are delivered by nurse practitioners and physician assistants versus physicians and how this has changed over time and by clinical setting, diagnosis, and patient demographics. DESIGN: Cross-sectional time series study. SETTING: National data from the traditional Medicare insurance program in the USA. PARTICIPANTS: Of people using Medicare (ie, those older than 65 years, permanently disabled, and people with end stage renal disease), a 20% random sample was taken. MAIN OUTCOME MEASURES: The proportion of physician, nurse practitioner, and physician assistant visits in the outpatient and skilled nursing facility settings delivered by physicians, nurse practitioners, and physician assistants, and how this proportion varies by type of visit and diagnosis. RESULTS: From 1 January 2013 to 31 December 2019, 276 million visits were included in the sample. The proportion of all visits delivered by nurse practitioners and physician assistants in a year increased from 14.0% (95% confidence interval 14.0% to 14.0%) to 25.6% (25.6% to 25.6%). In 2019, the proportion of visits delivered by a nurse practitioner or physician assistant varied across conditions, ranging from 13.2% for eye disorders and 20.4% for hypertension to 36.7% for anxiety disorders and 41.5% for respiratory infections. Among all patients with at least one visit in 2019, 41.9% had one or more nurse practitioner or physician assistant visits. Compared with patients who had no visits from a nurse practitioner or physician assistant, the likelihood of receiving any care was greatest among patients who were lower income (2.9% greater), rural residents (19.7%), and disabled (5.6%). CONCLUSION: The proportion of visits delivered by nurse practitioners and physician assistants in the USA is increasing rapidly and now accounts for a quarter of all healthcare visits.