Tiered Physician Network Plans and Patient Choices of Specialist Physicians.

Importance: Tiered physician network (TPN) health plans sort physicians into tiers based on their cost and quality, and patients pay lower copays for visits with physicians in the lower-cost and better-quality tiers. When the plans are first introduced, they lead patients to seek care from higher-value physicians. Objectives: To examine whether TPNs are associated with patient choice of physician when the plans have been in place for 8 to 12 years and whether there are inequities in patient out-of-pocket costs associated with inequities in access to physicians in lower-copay tiers. Design, Setting, and Participants: This cross-sectional study comprising 46 645 physicians and 585 399 patients in TPNs, including 54 683 patients who had a new patient visit with a physician in a TPN, used health insurance claims data from a large employer purchaser from July 1, 2014, to June 30, 2019. Statistical analysis was performed from November 2020 to August 2023. Exposure: Evaluation and management visit with a physician in a TPN. Main Outcomes and Measures: Main outcomes were new patient market share per physician-carrier-zip code-year, distance from centroid of patient zip code to centroid of zip code of nearest low- or medium-copay physician, and mean TPN physician office visit copay per patient. A regression discontinuity design was used to estimate the association of a physician's tier ranking, and a difference-in-differences analysis was used to estimate the association of copayment differences across tiers with market share among new patients. Equity in access was measured by comparing travel distance to the nearest physician in a low-copay or medium-copay tier and mean copayments across patient incomes. Results: The main analysis sample included 46 645 physician-carrier-zip code-year observations, 9506 (20.4%) of which were in the low-copay tier, 31 798 (68.2%) in the medium-copay tier, and 5341 (11.5%) in the high-copay tier. The 54 683 new patients in the sample had a mean (SD) age of 46.4 (16.7) years and included 33 542 women (61.3%). There was no association of having a worse tier ranking (0.045 percentage points [95% CI, -0.058 to 0.148 percentage points]) or of copayment differences between tiers (0.001 percentage points [95% CI, -0.002 to 0.004 percentage points]) with physician market share among new patients. The patients with the lowest income paid slightly lower mean (SD) copayments for office visits to a TPN physician than the patients with high income ($48.08 [$16.42] vs $51.59 [$16.79], a 6.8% difference). Conclusions and Relevance: In this cross-sectional study of TPN health plans, there was no association between physician tier ranking and physician market share among any group of patients. These findings suggest there are limitations in TPNs' steering of patients toward high-value physicians. These plans were not associated with exacerbated health inequity in this setting.

Out-of-Pocket Spending for Asthma-Related Care Among Commercially Insured Patients, 2004-2016.

BACKGROUND: Out-of-pocket (OOP) health care costs can cause financial burden and deferred care for many Americans. Little is known about OOP spending for asthma-related care among the commercially insured. OBJECTIVES: To analyze OOP spending for asthma-related care overall, across types of care, and by income. METHODS: Using enrollment, claims, and geocoded census tract data on income from a large US commercial health plan from 2004 to 2016, we measured inflation-adjusted OOP spending for individuals with asthma ages 4 to 64 years (n = 1,986,769). We estimated annual asthma-related OOP spending over time, and average total, asthma-related, asthma type of care, and asthma medication spending by income. We measured trends in median OOP cost per medication. Linear regression models were adjusted for patient covariates and deductible level. RESULTS: Asthma-related OOP spending decreased over time both for patients enrolled in high-deductible health plans and for those in traditional plans. High-deductible plan enrollment increased from 7% to 54%. Compared with patients living in high-income areas, patients in the lowest-income areas had similar annual total and asthma-related OOP spending, but spent 30% less on controller medications and a higher proportion of their asthma-related OOP spending on inpatient and emergency care (10% vs 3%; P < .001). Asthma-related OOP spending represented a higher proportion of household income for patients in lower-income areas. CONCLUSIONS: Patients with asthma living in the lowest-income areas have greater cost burden, lower spending on controller medications, and greater spending on high-acuity care than higher-income counterparts.

Admission Practices And Cost Of Care For Opioid Use Disorder At Residential Addiction Treatment Programs In The US.

The use of acute, short-term residential care for opioid use disorder has grown rapidly, with policy makers advocating to increase the availability of "treatment beds." However, there are concerns about high costs and misleading recruitment practices. We conducted an audit survey of 613 residential programs nationally, posing as uninsured cash-paying individuals using heroin and seeking addiction treatment. One-third of callers were offered admission before clinical evaluation, usually within one day. Most programs required up-front payments, with for-profit programs charging more than twice as much ($17,434) as nonprofits ($5,712). Recruitment techniques (for example, offering paid transportation) were used frequently by for-profit, but not nonprofit, programs. Practices including admission offers during the call, high up-front payments, and recruitment techniques were common even among programs with third-party accreditation and state licenses. These findings raise concerns that residential programs, including accredited and licensed ones, may be admitting a clinically and financially vulnerable population for costly treatment without assessing appropriateness for other care settings.

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.

Association of eConsult Implementation With Access to Specialist Care in a Large Urban Safety-Net System.

Importance: Accessing specialty care continues to be a persistent problem for patients who use safety-net health systems. To address this access barrier, hospital systems have begun to implement electronic referral systems using eConsults, which allow clinicians to submit referral requests to specialty clinics electronically and enable specialty reviewers to resolve referrals, if appropriate, through electronic dialogue without an in-person visit. Objective: Measure the effect of implementing an eConsult program on access to specialty care. Design Setting and Participants: Using an interrupted time series design with data from 2016 to 2020, this study analyzed 50 260 referral requests submitted during the year before and the year after eConsult implementation at 19 New York City Health + Hospitals (NYC H+H) specialty clinics that spanned 7 NYC H+H hospital facilities and 6 unique specialties. Exposures: Referral request was submitted to a specialty clinic in the year following eConsult implementation. Main Outcomes and Measures: Main outcomes included the fraction of referral requests resolved without an in-person visit following eConsult implementation; and, among requests triaged to have an in-person visit, the fraction of referrals with a successfully scheduled appointment, mean wait time to a specialty appointment, and the fraction of referral requests with a completed specialty visit. Changes associated with eConsult implementation were estimated using multivariate linear regression adjusting for patient age, gender, and specialty clinic fixed effects. Results: Across 19 NYC H+H specialty clinics, 26 731 referral requests were submitted in the year before and 23 529 referrals were submitted in the year after eConsult implementation. Following eConsult implementation, 13% of all requests were resolved electronically. Among requests requiring a follow-up visit, the fraction with an appointment successfully scheduled increased by 15.8%, from 66.5% to 82.3% (P < .001). The mean time to an appointment decreased from 61.0 days pre-eConsult to 54.1 days post-eConsult, an adjusted 8.2-day shorter wait time (or 13.3% reduction) following eConsult adoption (P < .001). The percentage of referrals with a completed follow-up visit with a specialist within 90 days of the request did not change (38.4% vs 37.9%, P = .07). Changes in outcomes were mitigated during months when most clinics underwent an electronic health record transition after implementing eConsult. Conclusions and Relevance: In this quality improvement study, implementation of eConsults at a large multi-specialty safety-net system was associated with improvements in appointment scheduling rates and wait times. Despite an additional electronic health record transition, eConsults are a promising health care delivery tool for increasing access to specialty care.

Association of Peer Comparison Emails With Electronic Health Record Documentation of Cancer Stage by Oncologists.

Importance: Systematically capturing cancer stage is essential for any serious effort by health systems to monitor outcomes and quality of care in oncology. However, oncologists do not routinely record cancer stage in machine-readable structured fields in electronic health records (EHRs). Objective: To evaluate whether a peer comparison email intervention that communicates an oncologist's performance on documenting cancer stage relative to that of peer physicians was associated with increased likelihood that stage was documented in the EHR. Design, Setting, and Participants: This 12-month, randomized quality improvement pilot study aimed to increase oncologist staging documentation in the EHR. The pilot study was performed at Massachusetts General Hospital Cancer Center from October 1, 2018, to September 30, 2019. Participants included 56 oncologists across 3 practice sites who treated patients in the ambulatory setting and focused on diseases that use standardized staging systems. Data were analyzed from July 2, 2019, to March 5, 2020. Interventions: Peer comparison intervention with as many as 3 emails to oncologists during 6 months that displayed the oncologist's staging documentation rate relative to all oncologists in the study sample. Main Outcomes and Measures: The primary outcome was patient-level documentation of cancer stage, defined as the likelihood that a patient's stage of disease was documented in the EHR after the patient's first (eg, index) ambulatory visit during the pilot period. Results: Among the 56 oncologists participating (32 men [57%]), receipt of emails with peer comparison data was associated with increased likelihood of documentation of cancer stage using the structured field in the EHR (23.2% vs 13.0% of patient index visits). In adjusted analyses, this difference represented an increase of 9.0 (95% CI, 4.4-13.5) percentage points (P = .002) in the probability that a patient's cancer stage was documented, a relative increase of 69% compared with oncologists who did not receive peer comparison emails. The association increased with each email that was sent, ranging from a nonsignificant 4.0 (95% CI, -0.8 to 8.8) percentage points (P = .09) after the first email to a statistically significant 11.2 (95% CI, 4.9-17.4) percentage points (P = .003) after the third email . The association was concentrated among an oncologist's new patients (increase of 11.8 [95% CI, 6.2-17.4] percentage points; P = .001) compared with established patients (increase of 1.6 [95% CI, -2.9 to 6.1] percentage points; P = .44) and persisted for 7 months after the email communications stopped. Conclusions and Relevance: In a quality improvement pilot trial, peer comparison emails were associated with a substantial increase in oncologist use of the structured field in the EHR to document stage of disease.

Access to Office-Based Buprenorphine Treatment in Areas With High Rates of Opioid-Related Mortality: An Audit Study.

Background: Improving access to treatment for opioid use disorder is a national priority, but little is known about the barriers encountered by patients seeking buprenorphine-naloxone ("buprenorphine") treatment. Objective: To assess real-world access to buprenorphine treatment for uninsured or Medicaid-covered patients reporting current heroin use. Design: Audit survey ("secret shopper" study). Setting: 6 U.S. jurisdictions with a high burden of opioid-related mortality (Massachusetts, Maryland, New Hampshire, West Virginia, Ohio, and the District of Columbia). Participants: From July to November 2018, callers contacted 546 publicly listed buprenorphine prescribers twice, posing as uninsured or Medicaid-covered patients seeking buprenorphine treatment. Measurements: Rates of new appointments offered, whether buprenorphine prescription was possible at the first visit, and wait times. Results: Among 1092 contacts with 546 clinicians, schedulers were reached for 849 calls (78% response rate). Clinicians offered new appointments to 54% of Medicaid contacts and 62% of uninsured-self-pay contacts, whereas 27% of Medicaid and 41% of uninsured-self-pay contacts were offered an appointment with the possibility of buprenorphine prescription at the first visit. The median wait time to the first appointment was 6 days (interquartile range [IQR], 2 to 10 days) for Medicaid contacts and 5 days (IQR, 1 to 9 days) for uninsured-self-pay contacts. These wait times were similar regardless of clinician type or payer status. The median wait time from first contact to possible buprenorphine induction was 8 days (IQR, 4 to 15 days) for Medicaid and 7 days (IQR, 3 to 14 days) for uninsured-self-pay contacts. Limitation: The survey sample included only publicly listed buprenorphine prescribers. Conclusion: Many buprenorphine prescribers did not offer new appointments or rapid buprenorphine access to callers reporting active heroin use, particularly those with Medicaid coverage. Nevertheless, wait times were not long, implying that opportunities may exist to increase access by using the existing prescriber workforce. Primary Funding Source: National Institute on Drug Abuse.