Publications

Rationale: Patients receiving prolonged mechanical ventilation experience low survival rates and incur high healthcare costs. However, little is known about how to optimally organize and manage their care.Objectives: To identify a set of effective care practices for patients receiving prolonged mechanical ventilation.Methods: We performed a focused ethnographic evaluation at eight long-term acute care hospitals in the United States ranking in either the lowest or highest quartile of risk-adjusted mortality in at least four of the five years between 2007 and 2011.Measurements and Main Results: We conducted 329 hours of direct observation, 196 interviews, and 39 episodes of job shadowing. Data were analyzed using thematic content analysis and a positive-negative deviance approach. We found that high- and low-performing hospitals differed substantially in their approach to care. High-performing hospitals actively promoted interdisciplinary communication and coordination using a range of organizational practices, including factors related to leadership (e.g., leaders who communicate a culture of quality improvement), staffing (e.g., lower nurse-to-patient ratios and ready availability of psychologists and spiritual care providers), care protocols (e.g., specific yet flexible respiratory therapy-driven weaning protocols), team meetings (e.g., interdisciplinary meetings that include direct care providers), and the physical plant (e.g., large workstations that allow groups to interact). These practices were believed to facilitate care that is simultaneously goal directed and responsive to individual patient needs, leading to more successful liberation from mechanical ventilation and improved survival.Conclusions: High-performing long-term acute care hospitals employ several organizational practices that may be helpful in improving care for patients receiving prolonged mechanical ventilation.

BACKGROUND: After non-fatal opioid overdoses, opioid prescribing patterns are often unchanged and the use of medications for opioid use disorder (MOUDs) remains low. Whether such prescribing differs by race/ethnicity remains unknown.

OBJECTIVE: To assess the association of race/ethnicity with the prescribing of opioids and MOUDs after a non-fatal opioid overdose.

DESIGN: Retrospective cohort study.

PARTICIPANTS: Patients prescribed ≥ 1 opioid from July 1, 2010, to September 30, 2015, with a non-fatal opioid overdose in the Veterans Health Administration (VA).

MAIN MEASURES: Primary outcomes were the proportion of patients prescribed: (1) any opioid during the 30 days before and after overdose and (2) MOUDs within 30 days after overdose by race and ethnicity. We conducted difference-in-difference analyses using multivariable regression to assess whether the change in opioid prescribing from before to after overdose differed by race/ethnicity. We also used multivariable regression to test whether MOUD prescribing after overdose differed by race/ethnicity.

KEY RESULTS: Among 16,210 patients with a non-fatal opioid overdose (81.2% were white, 14.3% black, and 4.5% Hispanic), 10,745 (66.3%) patients received an opioid prescription (67.1% white, 61.7% black, and 65.9% Hispanic; p < 0.01) before overdose. After overdose, the frequency of receiving opioids was reduced by 18.3, 16.4, and 20.6 percentage points in whites, blacks, and Hispanics, respectively, with no significant difference-in-difference in opioid prescribing by race/ethnicity (p = 0.23). After overdose, 526 (3.2%) patients received MOUDs (2.9% white, 4.6% black, and 5.5% Hispanic; p < 0.01). Blacks (adjusted OR (aOR) 1.6; 95% CI 1.2, 1.9) and Hispanics (aOR 1.8; 95% CI 1.2, 2.6) had significantly larger odds of receiving MOUDs than white patients.

CONCLUSIONS: In a national cohort of patients with non-fatal opioid overdose in VA, there were no racial/ethnic differences in changes in opioid prescribing after overdose. Although blacks and Hispanics were more likely than white patients to receive MOUDs in the 30 days after overdose, less than 4% of all groups received such therapy.

OBJECTIVES: Shared decision making is essential to deprescribing unnecessary or harmful medications in older adults, yet patients' and caregivers' perspectives on medication value and how this affects their willingness to discontinue a medication are poorly understood. We sought to identify the most significant factors that impact the perceived value of a medication from the perspective of patients and caregivers.

DESIGN: Qualitative study using focus groups conducted in September and October 2018.

SETTING: Participants from the Pepper Geriatric Research Registry (patients) and the Pitt+Me Registry (caregivers) maintained by the University of Pittsburgh.

PARTICIPANTS: Six focus groups of community-dwelling adults aged 65 years or older, or their caregivers, prescribed five or more medications in the preceding 12 months.

MEASUREMENTS: We sought to identify (1) general views on medication value and what makes medication worth taking; (2) how specific features such as cost or side effects impact perceived value; and (3) reactions to clinical scenarios related to deprescribing.

RESULTS: We identified four themes. Perceived effectiveness was the primary factor that caused participants to consider a medication to be of high value. Participants considered a medication to be of low value if it adversely affected quality of life. Participants also cited cost when determining value, especially if it resulted in material sacrifices. Participants valued medications prescribed by providers with whom they had good relationships rather than valuing level of training. When presented with clinical scenarios, participants ably weighed these factors when determining the value of a medication and indicated whether they would adhere to a deprescribing recommendation.

CONCLUSION: We identified that perceived effectiveness, adverse effects on quality of life, cost, and a strong relationship with the prescriber influenced patients' and caregivers' views on medication value. These findings will enable prescribers to engage older patients in shared decision making when deprescribing unnecessary medications and will allow health systems to incorporate patient-centered assessment of value into systems-based deprescribing interventions. J Am Geriatr Soc 68:746-753, 2020.

BACKGROUND: As healthcare reimbursement shifts from being volume to value-focused, new delivery models aim to coordinate care and improve quality. The patient-centered medical home (PCMH) model is one such model that aims to deliver coordinated, accessible healthcare to improve outcomes and decrease costs. It is unclear how the types of delivery systems in which PCMHs operate differentially impact outcomes. We aim to describe economic, utilization, quality, clinical, and patient satisfaction outcomes resulting from PCMH interventions operating within integrated delivery and finance systems (IDFS), government systems including Veterans Administration, and non-integrated delivery systems.

METHODS: We searched PubMed, the Cochrane Library, and Embase from 2004 to 2017. Observational studies and clinical trials occurring within the USA that met PCMH criteria (as defined by the Agency for Healthcare Research and Quality), addressed ambulatory adults, and reported utilization, economic, clinical, processes and quality of care, or patient satisfaction outcomes.

RESULTS: Sixty-four studies were included. Twenty-four percent were within IDFS, 29% were within government systems, and 47% were within non-IDFS. IDFS studies reported decreased emergency department use, primary care use, and cost relative to other systems after PCMH implementation. Government systems reported increased primary care use relative to other systems after PCMH implementation. Clinical outcomes, processes and quality of care, and patient satisfaction were assessed heterogeneously or infrequently.

DISCUSSION: Published articles assessing PCMH interventions generally report improved outcomes related to utilization and cost. IDFS and government systems exhibit different outcomes relative to non-integrated systems, demonstrating that different health systems and populations may be particularly sensitive to PCMH interventions. Both the definition of PCMH interventions and outcomes measured are heterogeneous, limiting the ability to perform direct comparisons or meta-analysis.

OBJECTIVE: To identify sociodemographic profiles of patients prescribed high-dose opioids.

DESIGN: Cross-sectional cohort study.

SETTING/PATIENTS: Veterans dually-enrolled in Veterans Health Administration and Medicare Part D, with ≥1 opioid pre-scription in 2012.

MAIN OUTCOME MEASURES: We identified five patient-level demographic characteristics and 12 community variables re-flective of region, socioeconomic deprivation, safety, and internet connectivity. Our outcome was the proportion of vet-erans receiving >120 morphine milligram equivalents (MME) for ≥90 consecutive days, a Pharmacy Quality Alliance measure of chronic high-dose opioid prescribing. We used classification and regression tree (CART) methods to identify risk of chronic high-dose opioid prescribing for sociodemographic subgroups.

RESULTS: Overall, 17,271 (3.3 percent) of 525,716 dually enrolled veterans were prescribed chronic high-dose opioids. CART analyses identified 35 subgroups using four sociodemographic and five community-level measures, with high-dose opioid prescribing ranging from 0.28 percent to 12.1 percent. The subgroup (n = 16,302) with highest frequency of the outcome included veterans who were with disability, age 18-64 years, white or other race, and lived in the Western Census region. The subgroup (n = 14,835) with the lowest frequency of the outcome included veterans who were with-out disability, did not receive Medicare Part D Low Income Subsidy, were >85 years old, and lived in communities within the second and sixth to tenth deciles of community public assistance.

CONCLUSIONS: Using CART analyses with sociodemographic and community-level variables only, we identified sub-groups of veterans with a 43-fold difference in chronic high-dose opioid prescriptions. Interactions among disability, age, race/ethnicity, and region should be considered when identifying high-risk subgroups in large populations.

IMPORTANCE: Low-value care is associated with harm among patients and with wasteful health care spending but has not been well characterized in the Veterans Health Administration.

OBJECTIVES: To characterize the frequency of and variation in low-value diagnostic testing for 4 common conditions at Veterans Affairs medical centers (VAMCs) and to examine the correlation between receipt of low-value testing for each condition.

DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study used Veterans Health Administration data from 127 VAMCs from fiscal years 2014 to 2015. Data were analyzed from April 2018 to March 2020.

EXPOSURES: Continuous enrollment in Veterans Health Administration during fiscal year 2015.

MAIN OUTCOMES AND MEASURES: Receipt of low-value testing for low back pain, headache, syncope, and sinusitis. For each condition, sensitive and specific criteria were used to evaluate the overall frequency and range of low-value testing, adjusting for sociodemographic and VAMC characteristics. VAMC-level variation was calculated using median adjusted odds ratios. The Pearson correlation coefficient was used to evaluate the degree of correlation between low-value testing for each condition at the VAMC level.

RESULTS: Among 1 022 987 veterans, the mean (SD) age was 60 (16) years, 1 008 336 (92.4%) were male, and 761 485 (69.8%) were non-Hispanic White. A total of 343 024 veterans (31.4%) were diagnosed with low back pain, 79 176 (7.3%) with headache, 23 776 (2.2%) with syncope, and 52 889 (4.8%) with sinusitis. With the sensitive criteria, overall and VAMC-level low-value testing frequency varied substantially across conditions: 4.6% (range, 2.7%-10.1%) for sinusitis, 12.8% (range, 8.6%-22.6%) for headache, 18.2% (range, 10.9%-24.6%) for low back pain, and 20.1% (range, 16.3%-27.7%) for syncope. With the specific criteria, the overall frequency of low-value testing across VAMCs was 2.4% (range, 1.3%-5.1%) for sinusitis, 8.6% (range, 6.2%-14.6%) for headache, 5.6% (range, 3.6%-7.7%) for low back pain, and 13.3% (range, 11.3%-16.8%) for syncope. The median adjusted odds ratio ranged from 1.21 for low back pain to 1.40 for sinusitis. At the VAMC level, low-value testing was most strongly correlated for syncope and headache (ρ = 0.56; P < .001) and low back pain and headache (ρ = 0.48; P < .001).

CONCLUSIONS AND RELEVANCE: In this cohort study, low-value diagnostic testing was common, varied substantially across VAMCs, and was correlated between veterans' receipt of different low-value tests at the VAMC level. The findings suggest a need to address low-value diagnostic testing, even in integrated health systems, with robust utilization management practices.

Despite implementation of the Affordable Care Act (ACA), many Americans remain uninsured and receive care in free clinics. It is unknown what free clinic attendees in Pennsylvania know about health insurance expansion or what they perceive as barriers in enrolling in health insurance. The objective of this study was to assess the perceptions and experiences of free clinic patients from southwestern Pennsylvania when applying for health insurance after implementation of the ACA. We designed and implemented a survey of patients at three free clinics within Allegheny County, Pennsylvania from September 2016 to February 2017. Our survey included 22-items, 7 sociodemographic questions and 15 questions regarding the patient's health status and their perspectives related to obtaining health insurance. Data was obtained from 203 patient surveys; 110 (55.3%) of the respondents were men and 99 (48.8%) were African American. There were 48 respondents (24.1%) who did not report any income at the time of the study, and of those that did report an income, 92 (46.2%) respondents reported an income below 133% of the federal poverty level. The main barriers patients faced when applying for health insurance were: (1) lack of knowledge about health insurance (n = 127, 58.1%), (2) cost of health coverage (n = 85, 41.9%), (3) lack of resources (n = 83, 40.4%), and (4) lack of enrollment documentation (n = 43, 23.8%). Significant work is needed to better educate patients about their eligibility and options for health insurance. Free clinics can play a key role in eliminating barriers to health insurance enrollment.