Inpatient Addiction Medicine Consultation and Post-Hospital Substance Use Disorder Treatment Engagement: a Propensity-Matched Analysis.

BACKGROUND: Hospitalizations due to medical and surgical complications of substance use disorder (SUD) are rising. Most hospitals lack systems to treat SUD, and most people with SUD do not engage in treatment after discharge. OBJECTIVE: Determine the effect of a hospital-based addiction medicine consult service, the Improving Addiction Care Team (IMPACT), on post-hospital SUD treatment engagement. DESIGN: Cohort study using multivariable analysis of Oregon Medicaid claims comparing IMPACT patients with propensity-matched controls. PARTICIPANTS: 18-64-year-old Oregon Medicaid beneficiaries with SUD, hospitalized at an Oregon hospital between July 1, 2015, and September 30, 2016. IMPACT patients (n = 208) were matched to controls (n = 416) using a propensity score that accounted for SUD, gender, age, race, residence region, and diagnoses. INTERVENTIONS: IMPACT included hospital-based consultation care from an interdisciplinary team of addiction medicine physicians, social workers, and peers with lived experience in recovery. IMPACT met patients during hospitalization; offered pharmacotherapy, behavioral treatments, and harm reduction services; and supported linkages to SUD treatment after discharge. OUTCOMES: Healthcare Effectiveness Data and Information Set (HEDIS) measure of SUD treatment engagement, defined as two or more claims on two separate days for SUD care within 34 days of discharge. RESULTS: Only 17.2% of all patients were engaged in SUD treatment before hospitalization. IMPACT patients engaged in SUD treatment following discharge more frequently than controls (38.9% vs. 23.3%, p < 0.01; aOR 2.15, 95% confidence interval [CI] 1.29-3.58). IMPACT participation remained associated with SUD treatment engagement when limiting the sample to people who were not engaged in treatment prior to hospitalization (aOR 2.63; 95% CI 1.46-4.72). CONCLUSIONS: Hospital-based addiction medicine consultation can improve SUD treatment engagement, which is associated with reduced substance use, mortality, and other important clinical outcomes. National expansion of such models represents an opportunity to address an enduring gap in the SUD treatment continuum.

Process Improvement Initiative for the Perioperative Management of Patients With a Cardiovascular Implantable Electronic Device.

BACKGROUND: Economic, personnel, and procedural challenges often complicate and interfere with efficient and safe perioperative care of patients with cardiovascular implantable electronic devices (CIEDs). In the context of a process improvement initiative, we created and implemented a comprehensive anesthesiologist-run perioperative CIED service to respond to all routine requests for perioperative CIED consultations at a large academic medical center. This study was designed to determine whether this new care model was associated with improved operating room efficiency, reduced institutional cost, and adequate patient safety. METHODS: We included patients with a CIED and a concurrent cohort of patients with the same eligibility criteria but without a CIED who underwent first-case-of-the-day surgery during the periods between February 1, 2008, and August 17, 2010 (preintervention) and between March 4, 2012, and August 1, 2014 (postintervention). The primary end point was delay in first-case-of-the day start time. We used multiple linear regression to compare delays in start times during the preintervention and postintervention periods and to adjust for potential confounders. A patient safety database was queried for CIED-related complications. Cost analysis was based on labor minutes saved and was calculated using nationally published administrative estimates. RESULTS: A total of 18,148 first-case surgical procedures were performed in 15,100 patients (preintervention period-7293 patients and postintervention period-7807 patients). Of those, 151 (2.1%) patients had a CIED in the preintervention period, and 146 (1.9%) had a CIED in the postintervention period. After adjustment for imbalances in baseline characteristics (age, American Society of Anesthesiologists physical status, and surgical specialty), the difference in mean first-case start delay between the postintervention and preintervention periods in the cohort of patients with a CIED was -16.7 minutes (95% confidence interval [CI], -26.1 to -7.2). The difference in mean delay between the postintervention and preintervention periods in the cohort without a CIED was -4.7 minutes (95% CI, -5.4 to -3.9). There were 3 CIED-related adverse events during the preintervention period and none during the postintervention period. Based on reduction in first-case start delay, the intervention was associated with cost savings (estimated institutional savings $14,102 annually, or $94.06 per CIED patient), with a return on investment ratio of 2.18 over the course of the postintervention period. CONCLUSIONS: Based on our experience, specially trained anesthesiologists can provide efficient and safe perioperative care for patients with CIEDs. Other centers may consider implementing a similar strategy as our specialty adopts the perioperative surgical home model.

Primary Prevention of Weight Gain Among New Bus Operators: Results of the "Success & Health Impacts For Transit operators during Onboarding" (SHIFT Onboard) Pilot Study.

OBJECTIVE: This study aimed to test the feasibility and efficacy of an enhanced onboarding intervention to prevent weight gain and support the early job success of new bus operators. METHODS: Control participants ( n = 9) completed usual practice new employee training and onboarding. Intervention participants ( n = 14) completed five supplemental trainings and four online challenges during their first year. Primary outcomes were body weight, dietary behaviors, physical activity, and sleep duration/quality. Early job success was evaluated with measures of newcomer adjustment. RESULTS: The difference between intervention and control participants in body weight change at 12-month was -6.71 lb (Cohen's d = -1.35). Differences in health behavior changes were mixed, but newcomer adjustment changes favored the intervention group. CONCLUSIONS: Results support the feasibility of enhanced onboarding for bus operators to prevent worsening health while simultaneously advancing their success as new employees.

Disparities in telephone and video telehealth engagement during the COVID-19 pandemic.

OBJECTIVE: The COVID-19 pandemic and subsequent expansion of telehealth may be exacerbating inequities in ambulatory care access due to institutional and structural barriers. We conduct a repeat cross-sectional analysis of ambulatory patients to evaluate for demographic disparities in the utilization of telehealth modalities. MATERIALS AND METHODS: The ambulatory patient population at Oregon Health & Science University (Portland, OR, USA) is examined from June 1 through September 30, in 2019 (reference period) and in 2020 (study period). We first assess for changes in demographic representation and then evaluate for disparities in the utilization of telephone and video care modalities using logistic regression. RESULTS: Between the 2019 and 2020 periods, patient video utilization increased from 0.2% to 31%, and telephone use increased from 2.5% to 25%. There was also a small but significant decline in the representation males, Asians, Medicaid, Medicare, and non-English speaking patients. Amongst telehealth users, adjusted odds of video participation were significantly lower for those who were Black, American Indian, male, prefer a non-English language, have Medicaid or Medicare, or older. DISCUSSION: A large portion of ambulatory patients shifted to telehealth modalities during the pandemic. Seniors, non-English speakers, and Black patients were more reliant on telephone than video for care. The differences in telehealth adoption by vulnerable populations demonstrate the tendency toward disparities that can occur in the expansion of telehealth and suggest structural biases. CONCLUSION: Organizations should actively monitor the utilization of telehealth modalities and develop best-practice guidelines in order to mitigate the exacerbation of inequities.

Statewide Real-Time Tracking of Beds and Ventilators During Coronavirus Disease 2019 and Beyond.

This brief report describes the rapid deployment of a real-time electronic tracking board for all hospitals in the state of Oregon. In preparation for the coronavirus disease 2019 surge on hospital resources, and in collaboration across health systems, with health authorities and an industry partner, we combined existing infrastructures to create the first automated tracking board for our entire state, including bed types by health system and geographic area, and with granularity to the individual unit level for each participating hospital. At the time of submission, we have a live snapshot of 87% of beds in the state, including real-time ventilator data across eight health systems. The tracking board allows for rapid assessment of available bed and ventilator resources and pulls electronic health record data that is created through normal care processes rather than relying upon manual entry. It is updated every 5 minutes and is drillable from state to unit level. Together these factors make the data actionable, which is essential in a crisis. The new tracking system integrates seamlessly with our preexisting statewide, manually updated tracking board via bidirectional data sharing to ensure existing processes across the state can continue. This new tool allows any health system in our state to visualize occupancy by type and location in real time. Amid pandemic uncertainty, having a reliable tool for tracking critical hospital resources will enhance our statewide ability to maintain healthcare functionality in a world with coronavirus disease 2019.

Higher Quality, Lower Cost with an Innovative Geriatrics Consultation Service.

OBJECTIVES: To design a value-driven, interprofessional inpatient geriatric consultation program coordinated with systems-level changes and studied outcomes and costs. DESIGN: Propensity-matched case-control study of older adults hospitalized at an academic medical center (AMC) who did or did not receive geriatric consultation. SETTING: Single tertiary-care AMC in Portland, Oregon. PARTICIPANTS: Adults aged 70 and older who received an inpatient geriatric consultation (n=464) and propensity-matched controls admitted before development of the consultation program (n=2,381). Pre- and postintervention controls were also incorporated into cost difference-in-difference analyses. MEASUREMENTS: Daily charges, total charges, length of stay (LOS), 30-day readmission, intensive care unit (ICU) days, Foley catheter days, total medication doses per day, high-risk medication doses per day, advance directive and Physician Orders for Life Sustaining Treatment (POLST) documentation, restraint orders, discharge to home, and mortality. RESULTS: On average, individuals who received a geriatric consultation had $611 lower charges per day than those without a consultation (p=.02). They spent on average 0.36 fewer days in the ICU (p<.001). They were less likely to have restraint orders (20.0% vs 27.9%, p<0.001), more likely to have a POLST (58.2% vs 44.6%, p<.001), and more likely to be discharged to home (33.4% vs 28.2%, p=.03). They received fewer doses of antipsychotics, benzodiazepines, and antiemetics (10, 5, and 7 fewer doses per 100 patient-days, respectively) and had lower in-hospital mortality (2.4% vs 4%, p=.01). There was no difference in hospital LOS or 30-day readmission. CONCLUSION: Our consultation program resulted in significant reductions in daily charges, ICU days, potentially inappropriate medication use, and use of physical restraints and increased end-of-life planning. This model has potential for dissemination to other institutions operating in resource-scarce, value-driven settings.

Implementation of the sepsis risk score for chorioamnionitis-exposed newborns.

BACKGROUND: To prevent early onset sepsis (EOS), ~10% of neonates receive antibiotics based on CDC recommendations regarding chorioamnionitis exposure. A sepsis risk score (SRS) predicts EOS and spares unnecessary evaluation and treatment. LOCAL PROBLEM: Chorioamnionitis-exposed neonates utilize significant resources. METHODS: An SRS algorithm was implemented to decrease resource utilization in chorioamnionitis-exposed neonates ≥35 weeks'. Outcome measures included antibiotic exposure, time in NICU, laboratory evaluations, and length of stay (LOS). Balancing measures were missed cases of EOS and readmissions. Data were assessed using run charts. INTERVENTIONS: Plan-Do-Study-Act cycles were utilized to process map, implement and reinforce the algorithm. RESULTS: A number of 356 patients met inclusion criteria. After algorithm implementation, antibiotic exposure reduced from 95 to 9%, laboratory evaluation from 96 to 22%, NICU observation from 73 to 10%. LOS remained unchanged. No missed cases of EOS, nor sepsis readmissions. CONCLUSIONS: Algorithm implementation decreased antibiotic and resource utilization without missing cases of EOS.

Comparison of EHR-based diagnosis documentation locations to a gold standard for risk stratification in patients with multiple chronic conditions.

OBJECTIVE: To measure variation among four different Electronic Health Record (EHR) system documentation locations versus 'gold standard' manual chart review for risk stratification in patients with multiple chronic illnesses. METHODS: Adults seen in primary care with EHR evidence of at least one of 13 conditions were included. EHRs were manually reviewed to determine presence of active diagnoses, and risk scores were calculated using three different methodologies and five EHR documentation locations. Claims data were used to assess cost and utilization for the following year. Descriptive and diagnostic statistics were calculated for each EHR location. Criterion validity testing compared the gold standard verified diagnoses versus other EHR locations and risk scores in predicting future cost and utilization. RESULTS: Nine hundred patients had 2,179 probable diagnoses. About 70% of the diagnoses from the EHR were verified by gold standard. For a subset of patients having baseline and prediction year data (n=750), modeling showed that the gold standard was the best predictor of outcomes on average for a subset of patients that had these data. However, combining all data sources together had nearly equivalent performance for prediction as the gold standard. CONCLUSIONS: EHR data locations were inaccurate 30% of the time, leading to improvement in overall modeling from a gold standard from chart review for individual diagnoses. However, the impact on identification of the highest risk patients was minor, and combining data from different EHR locations was equivalent to gold standard performance. The reviewer's ability to identify a diagnosis as correct was influenced by a variety of factors, including completeness, temporality, and perceived accuracy of chart data.

Implementing federal health reform in the States: who is included and excluded and what are their characteristics?

OBJECTIVE: To estimate the characteristics and number of nonelderly adults eligible and ineligible for Affordable Care Act (ACA) expansions. DATA SOURCES AND SETTINGS: Two secondary data sources are used in this analysis: the 2008 Panel of the Survey of Income and Program Participation (SIPP) and the 2009 American Community Survey (ACS). STUDY DESIGN: We use multiple imputation to incorporate model-based uncertainty into the prediction of immigration status into the ACS from the SIPP. Key variables include place of birth, year of entry to the U.S., and health insurance coverage. DATA COLLECTION/EXTRACTING METHODS: No primary data are used in this study. PRINCIPLE FINDINGS: We estimate that potentially 3.5 million nonelderly adults will be excluded from the ACA Medicaid Expansion and 2 million from the health insurance exchanges because of their immigration status. We also find significant differences in estimates of excluded nonelderly adults across states. CONCLUSIONS: Over 15 percent of income-eligible uninsured nonelderly adults will be potentially excluded from the ACA coverage expansions due to their immigration status. Policy makers must be careful to exclude ineligible nonelderly adults before estimating the impact of the ACA on coverage rates.

Counting uninsurance and means-tested coverage in the American community survey: a comparison to the current population survey.

OBJECTIVE: To compare health insurance coverage estimates from the American Community Survey (ACS) to the Current Population Survey (CPS-ASEC). DATA SOURCES/STUDY SETTING: The 2008 ACS and CPS-ASEC, 2009. STUDY DESIGN: We compare age-specific national rates for all coverage types and state-level rates of uninsurance and means-tested coverage. We assess differences using t-tests and p-values, which are reported at <.05, <.01, and <.001. An F-test determines whether differences significantly varied by state. PRINCIPAL FINDINGS: Despite substantial design differences, we find only modest differences in coverage estimates between the surveys. National direct purchase and state-level means-tested coverage levels for children show the largest differences. CONCLUSIONS: We suggest that the ACS is well poised to become a useful tool to health services researchers and policy analysts, but that further study is needed to identify sources of error and to quantify its bias.