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.

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.

Differences by Physician Seniority in Race and Ethnicity and Insurance Coverage of Treated Patients.

This cross-sectional study investigates the share of patients who were members of racial and ethnic minority groups or Medicaid enrollees by physician seniority.

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.

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.

Trends in Ransomware Attacks on US Hospitals, Clinics, and Other Health Care Delivery Organizations, 2016-2021.

Importance: Anecdotal evidence suggests that health care delivery organizations face a growing threat from ransomware attacks that are designed to disrupt care delivery and may consequently threaten patient outcomes. Objective: To quantify the frequency and characteristics of ransomware attacks on health care delivery organizations. Design, Setting, and Participants: This cohort study used data from the Tracking Healthcare Ransomware Events and Traits database to examine the number and characteristics of ransomware attacks on health care delivery organizations from 2016 to 2021. Logistic and negative binomial regression quantified changes over time in the characteristics of ransomware attacks that affected health care delivery organizations. Main Outcomes and Measures: Date of ransomware attack, public reporting of ransomware attacks, personal health information (PHI) exposure, status of encrypted/stolen data following the attack, type of health care delivery organization affected, and operational disruption during the ransomware attack. Results: From January 2016 to December 2021, 374 ransomware attacks on US health care delivery organizations exposed the PHI of nearly 42 million patients. From 2016 to 2021, the annual number of ransomware attacks more than doubled from 43 to 91. Almost half (166 [44.4%]) of ransomware attacks disrupted the delivery of health care, with common disruptions including electronic system downtime (156 [41.7%]), cancellations of scheduled care (38 [10.2%]), and ambulance diversion (16 [4.3%]). From 2016 to 2021, ransomware attacks on health care delivery organizations increasingly affected large organizations with multiple facilities (annual marginal effect [ME], 0.08; 95% CI, 0.05-0.10; P < .001), exposed the PHI of more patients (ME, 66 385.8; 95% CI, 3400.5-129 371.2; P = .04), were less likely to be restored from data backups (ME, -0.04; 95% CI, -0.06 to -0.01; P = .002), were more likely to exceed mandatory reporting timelines (ME, 0.06; 95% CI, 0.03-0.08; P < .001), and increasingly were associated with delays or cancellations of scheduled care (ME, 0.02; 95% CI, 0-0.05; P = .02). Conclusions and Relevance: This cohort study of ransomware attacks documented growth in their frequency and sophistication. Ransomware attacks disrupt care delivery and jeopardize information integrity. Current monitoring/reporting efforts provide limited information and could be expanded to potentially yield a more complete view of how this growing form of cybercrime affects the delivery of health care.

PRescribing Interventions for Chronic pain using the Electronic health record (PRINCE): Study protocol.

BACKGROUND: Primary care is a frequent source of pain treatment and opioid prescribing. The objective of the Prescribing Interventions for Chronic Pain using the Electronic health record (PRINCE) study is to assess the effects of two behavioral economics-informed interventions embedded within the electronic health record (EHR) on guideline-concordant pain treatment and opioid prescribing decisions in primary care settings. METHODS: Setting: The setting for this study is 43 primary care clinics in Minnesota. DESIGN: The PRINCE study uses a cluster-randomized 2 × 2 factorial design to test the effects of two interventions. An adaptive design allows for the possibility of secondary randomization to test if interventions can be titrated while maintaining efficacy. INTERVENTIONS: One intervention alters the "choice architecture" within the EHR to nudge clinicians toward non-opioid treatments for opioid-naïve patients and toward tapering for patients currently receiving a "high risk" opioid. The other intervention integrates the prescription drug monitoring program (PDMP) directly within the EHR. OUTCOME: The primary outcome for opioid-naïve patients is whether an opioid is prescribed in a primary care visit without a non-opioid alternative pain treatment. The primary outcome for current opioid-using patients is whether opioid prescriptions were tapered with a documented rationale. DISCUSSION: The PRINCE study will provide real-world evidence on two approaches to improving pain treatment in primary care using the EHR. The adaptive study design strikes a balance between establishing intervention efficacy and testing whether efficacy varies with intervention intensity.

Effect of Integrating Access to a Prescription Drug Monitoring Program Within the Electronic Health Record on the Frequency of Queries by Primary Care Clinicians: A Cluster Randomized Clinical Trial.

Importance: Tools that are directly integrated with the electronic health record (EHR) workflow can reduce the hassle cost of certain guideline-concordant practices, such as querying a prescription drug monitoring program (PDMP) before prescribing opioids. Objective: To investigate the effect of integrating access to a PDMP within the EHR on the frequency of program queries by primary care clinicians. Design Settings and Participants: The PRINCE (Prescribing Interventions for Chronic Pain Using the Electronic Health Record) randomized trial used a factorial cluster design at the clinic level in 43 primary care clinics in Minnesota. In all, 309 clinicians participated; 161 clinicians were given EHR-integrated access to PDMP at the intervention clinics, and 148 clinicians had the usual access at the control clinics. The intervention went live on August 27, 2020, and data were collected through March 3, 2021. Intervention: Single sign-on access to the Minnesota PDMP was integrated into the EHR, allowing clinicians to query a patient's controlled substance prescription and dispensing history as recorded in the Minnesota PDMP directly from the patient's EHR record without logging into a separate web portal. Additionally, the integration tool alerted clinicians and reminded them to review the PDMP if a patient had 3 or more opioid prescriptions in the past year and 1 or more in the past 6 months. Clinics in the control group did not receive access to the EHR-integrated PDMP tool; instead, these participants logged into the PDMP web portal separately. Main Outcomes and Measures: Monthly PDMP query counts for primary care clinicians, overall and by modality (EHR-based, web-based, via a clinical delegate), adjusted for clinician characteristics, including type (physician, nurse practitioner, physician assistant), sex, and years in practice. Data were analyzed from August 2021 to May 2022. Results: Of the 43 participating clinics with 309 clinicians, 21 clinics with 161 clinicians (102 [63.4%] women; 114 [70.8%] physicians; tenure, 10.6 [4.4] years) received the PDMP integration intervention. Baseline unadjusted monthly PDMP query rates for the average clinician were 6.6 (95% CI, 4.4-9.9) vs 8.8 (95% CI, 6.0-13.1) queries in the control vs the PDMP integration group, respectively. During the intervention, PDMP query rates for the average clinician were 6.9 (95% CI, 4.7-10.3) vs 14.8 (95% CI, 10.0-22.0) queries among the control vs the PDMP integration group, respectively. Compared with the control group, the EHR-integrated PDMP tool produced a 60% greater increase in the relative change in monthly PDMP queries (95% CI, 51%-70%). An increase in PDMP queries via the EHR-integrated PDMP tool drove this increase, while web-based and delegate queries declined by 39% more among the intervention compared with the control group (95% CI, 34%-43%). Conclusions and Relevance: This cluster randomized clinical trial found that integrating access to the PDMP in the EHR increased PDMP-querying rates, suggesting that direct access reduced hassle costs and can dramatically improve adherence to guideline-concordant care practices among primary care clinicians. Trial Registration: ClinicalTrials.gov Identifier: NCT04601506.

Frequency Of Indirect Billing To Medicare For Nurse Practitioner And Physician Assistant Office Visits.

Nurse practitioners (NPs) and physician assistants (PAs) represent a growing share of the health care workforce, but much of the care they provide cannot be observed in claims data because of indirect (or "incident to") billing, a practice in which visits provided by an NP or PA are billed by a supervising physician. If NPs and PAs bill directly for a visit, Medicare and many private payers pay 85 percent of what is paid to a physician for the same service. Some policy makers have proposed eliminating indirect billing, but the possible impact of such a change is unknown. Using a novel approach that relies on prescriptions to identify indirectly billed visits, we estimated that the number of all NP or PA visits in fee-for-service Medicare data billed indirectly was 10.9 million in 2010 and 30.6 million in 2018. Indirect billing was more common in states with laws restricting NPs' scope of practice. Eliminating indirect billing would have saved Medicare roughly $194 million in 2018, with the greatest decrease in revenue seen among smaller primary care practices, which are more likely to use this form of billing.

The effect of a public transportation expansion on no-show appointments.

OBJECTIVE: To test whether there were fewer missed medical appointments ("no-shows") for patients and clinics affected by a significant public transportation expansion. STUDY SETTING: A new light rail line was opened in a major metropolitan area in June 2014. We obtained electronic health records data from an integrated health delivery system in the area with over three million appointments at 97 clinics between 2013 and 2016. STUDY DESIGN: We used a difference-in-differences research design to compare whether no-show appointment rates differentially changed among patients and clinics located near versus far from the new light rail line after it opened. Models included fixed effects to account for underlying differences across clinics, patient zip codes, and time. DATA EXTRACTION METHODS: We obtained data from an electronic health records system representing all appointments scheduled at 97 outpatient clinics in this system. We excluded same-day, urgent care, and canceled appointments. PRINCIPAL FINDINGS: The probability of no-show visits differentially declined by 0.5 percentage points (95% confidence interval [CI]: -0.9 to -0.1), or 4.5% relative to baseline, for patients living near the new light rail compared to those living far from it, after the light rail opened. The effects were stronger among patients covered by Medicaid (-1.6 percentage points [95% CI: -2.4 to -0.8] or 9.5% relative to baseline). CONCLUSIONS: Improvements to public transit may improve access to health care, especially for people with low incomes.

Trends in fall-related encounters and predictors of non-transport at a US Emergency Medical Services Agency.

Non-transport to a hospital after emergency medical services (EMS) encounters for falls is common. However, incident factors associated with non-transport have not been well studied, especially beyond older adults. The objectives of this study are to (1) describe trends in fall-related EMS utilisation among adult patients from 2010 to 2018; (2) describe incident characteristics by age; and (3) identify incident factors associated with non-transport following a fall. This retrospective observational study includes prehospital clinical records data on falls from a large ambulance service in Minnesota, USA. Multivariable logistic regression was used to assess the independent association between non-transport and the following factors: sex, age, race, previous fall-related EMS encounter, incident location and primary impression. Of 62,835 fall-related encounters studied, 14.7% (9,245) did not result in transport by EMS. Fall calls were less common among younger people and the location and medical conditions primarily treated by an EMS provider during a 9-1-1 call differed greatly from those occurring among patients 65 and older. Factors most strongly associated with an increased risk of non-transport in the multivariable model were a primary impression of 'No apparent illness/injury' (OR = 34.5, 95% CI = 30.7-38.7), falling in a public location (OR = 2.09, CI = 1.96-2.22) and having had a fall-related EMS encounter during the prior year (OR = 1.15, CI = 1.1-1.2). Falls that occur in public locations, in patients with a previous fall, or result in no clinical detection of apparent illness or injury have a significantly increased odds of non-transport. Non-transport fall incidents in the United States require significant agency resources. Knowledge about the incident factors associated with non-transport calls is informative for development of alternative models for prehospital care delivery and initiatives to better serve patients.

Taking the Pulse of Hospitals' Response to the New Price Transparency Rule.

As of January 1, 2021, most U.S. hospitals are required to publish pricing information on their website to promote more informed decision making by consumers regarding their care. In a nationally representative sample of 470 hospitals, we analyzed whether hospitals met price transparency information reporting requirements and the extent to which complete reporting was associated with ownership status, bed size category, system affiliation, and location in a metropolitan area. Fewer than one quarter of sampled hospitals met the price transparency information requirements of the new rule, which include five types of standard charges in machine-readable form and the consumer-shoppable display of 300 shoppable services. Our analyses of hospital reporting by organizational and market attributes revealed limited differences, with some exceptions for nonprofit and system-member hospitals demonstrating greater responsiveness with respect to the consumer-shoppable aspects of the rule.

The effect of Medicaid expansion on Medicaid participation, payer mix, and labor supply in primary care.

Evidence of increased health care utilization associated with the Medicaid expansion suggests that clinicians increased capacity to meet demand. However, little is known about the mechanism underlying this response. Using a novel source of all-payer data, we quantified clinicians' response to the Medicaid expansion - examining whether and how they changed their Medicaid participation decisions, payer mix, and overall labor supply. Primary care clinicians in expansion states provided an average of 49 additional appointments per year (a 21% relative increase) for patients insured by Medicaid, compared to clinicians in non-expansion states - with new-patient visits representing half (25 appointments) of this overall increase. Clinicians did not increase their labor supply to accommodate these additional appointments. They instead offset the 1.7 percentage point average increase in Medicaid payer mix with an equivalent reduction in commercial payer mix. However, this reduction in commercial patient share represented only a 2.8% relative decrease, with commercially insured patients still comprising the majority of the average clinician's patient panel. Subsample analyses revealed a larger increase in care for Medicaid patients among clinicians with high Medicaid participation preceding the eligibility expansion.

Evidence Of Respiratory Infection Transmission Within Physician Offices Could Inform Outpatient Infection Control.

Early in the COVID-19 pandemic, outpatient clinics throughout the US shifted toward virtual care to limit viral transmission in the office. However, as health care facilities have reopened, evidence about the risk of acquiring respiratory viral infections in medical office settings remains limited. To inform policy for reopening outpatient care settings, we analyzed rates of potential airborne disease transmission in medical office settings, focusing on influenza-like illness. We quantified whether exposed patients (that is, those seen in a medical office after a patient with influenza-like illness) were more likely to return with a similar illness in the next two weeks compared with nonexposed patients seen earlier in the day. Patients exposed to influenza-like illness in the medical office setting were more likely than nonexposed patients to revisit with a similar illness within two weeks (adjusted absolute difference: 0.7 per 1,000 patients). Similar patterns were not observed for exposure to urinary tract infection and back pain as noncontagious control conditions. These results highlight the potential threat of reopening outpatient clinics during the pandemic and the value of virtual visits for patients with suspected respiratory infections.

Travel, Treatment Choice, and Survival Among Breast Cancer Patients: A Population-Based Analysis.

Background: Travel distance to care facilities may shape urban-rural cancer survival disparities by creating barriers to specific treatments. Guideline-supported treatment options for women with early stage breast cancer involves considerations of breast conservation and travel burden: Mastectomy requires travel for surgery, whereas breast-conserving surgery (BCS) with adjuvant radiation therapy (RT) requires travel for both surgery and RT. This provides a unique opportunity to evaluate the impact of travel distance on surgical decisions and receipt of guideline-concordant treatment. Materials and Methods: We included 61,169 women diagnosed with early stage breast cancer between 2004 and 2013 from the Surveillance Epidemiology and End Results (SEER)-Medicare database. Driving distances to the nearest radiation facility were calculated by using Google Maps. We used multivariable regression to model treatment choice as a function of distance to radiation and Cox regression to model survival. Results: Women living farthest from radiation facilities (>50 miles vs. <10 miles) were more likely to undergo mastectomy versus BCS (odds ratio [OR]: 1.48, 95% confidence interval [CI]: 1.22-1.79). Among only those who underwent BCS, women living farther from radiation facilities were less likely to receive guideline-concordant RT (OR: 1.72, 95% CI: 1.32-2.23). These guideline-discordant women had worse overall (hazards ratio [HR]: 1.50, 95% CI: 1.42-1.57) and breast-cancer specific survival (HR: 1.44, 95% CI: 1.29-1.60). Conclusions: We report two breast cancer treatments with different clinical and travel implications to show the association between travel distance, treatment decisions, and receipt of guideline-concordant treatment. Differential access to guideline-concordant treatment resulting from excess travel burden among rural patients may contribute to rural-urban survival disparities among cancer patients.

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.

Nurse Practitioner Autonomy and Complexity of Care in Rural Primary Care.

The growing ranks of nurse practitioners (NPs) in rural areas of the United States have the potential to help alleviate existing primary care shortages. This study uses a nationwide source of claims- and EHR-data from 2017 to construct measures of NP clinical autonomy and complexity of care. Comparisons between rural and urban primary care practices reveal greater clinical autonomy for rural NPs, who were more likely to have an independent patient panel, to practice with less physician supervision, and to prescribe Schedule II controlled substances. In contrast, rural and urban NPs provided care of similar complexity. These findings provide the first claims- and EHR-based evidence for the commonly held perception that NPs practice more autonomously in rural areas than in urban areas.

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.