Mitigation of SARS-CoV-2 transmission at a large public university.

In Fall 2020, universities saw extensive transmission of SARS-CoV-2 among their populations, threatening health of the university and surrounding communities, and viability of in-person instruction. Here we report a case study at the University of Illinois at Urbana-Champaign, where a multimodal "SHIELD: Target, Test, and Tell" program, with other non-pharmaceutical interventions, was employed to keep classrooms and laboratories open. The program included epidemiological modeling and surveillance, fast/frequent testing using a novel low-cost and scalable saliva-based RT-qPCR assay for SARS-CoV-2 that bypasses RNA extraction, called covidSHIELD, and digital tools for communication and compliance. In Fall 2020, we performed >1,000,000 covidSHIELD tests, positivity rates remained low, we had zero COVID-19-related hospitalizations or deaths amongst our university community, and mortality in the surrounding Champaign County was reduced more than 4-fold relative to expected. This case study shows that fast/frequent testing and other interventions mitigated transmission of SARS-CoV-2 at a large public university.

Improving care for individuals with serious infections who inject drugs.

Background: Hospitalizations for serious infections requiring long-term intravenous (IV) antimicrobials related to injection drug use have risen sharply over the last decade. At our rural tertiary care center, opportunities for treatment of underlying substance use disorders were often missed during these hospital admissions. Once medically stable, home IV antimicrobial therapy has not traditionally been offered to this patient population due to theoretical concerns about misuse of long-term IV catheters, leading to discharges with suboptimal treatment regimens, lengthy hospital stays, or care that is incongruent with patient goals and preferences. Methods: A multidisciplinary group of clinicians and patients set out to redesign and improve care for this patient population through a health care innovation process, with a focus on increasing the proportion of patients who may be discharged on home IV therapy. Baseline assessment of current experience was established through retrospective chart review and extensive stakeholder analysis. The innovation process was based in design thinking and facilitated by a health care delivery improvement incubator. Results: The components of the resulting intervention included early identification of hospitalized people who inject drugs with serious infections, a proactive psychiatry consultation service for addiction management for all patients, a multidisciplinary care conference to support decision making around treatment options for infection and substance use, and care coordination/navigation in the outpatient setting with a substance use peer recovery coach and infectious disease nurse for patients discharged on home IV antimicrobials. Patients discharged on home IV therapy followed routine outpatient parenteral antimicrobial therapy (OPAT) protocols and treatment protocols for addiction with their chosen provider. Conclusion: An intervention developed through a design-thinking-based health care redesign process improved patient-centered care for people with serious infections who inject drugs.

Multidisciplinary treatment of opioid use disorder in primary care using the collaborative care model.

Background: Treatment of opioid use disorder (OUD) is highly effective, but access is limited and care is often fragmented. Treatment in primary care can improve access to treatment and address psychiatric and physical co-morbidities in a holistic, efficient, and non-stigmatizing way. The Collaborative Care Model (CCM) of behavioral health integration into primary care has been widely disseminated and shown to improve outcomes and lower costs when studied for depression, but its use in treating substance use disorders has not been well documented. Methods: We used a mixed-methods approach to examine the impact of implementing multidisciplinary treatment of OUD in our health system's five primary care clinics using the framework of the CCM, with care shared between the primary care clinician (PCP), behavioral health clinician, and medical assistant. The implementation included staff education, creation of electronic health record tools, and implementation support, and was evaluated using data from the electronic health record, the medical staff office, and a clinician survey. Results: Over the last 2 years of implementation, the number of waivered providers increased from 11 to 35, providers prescribing for 5 or more patients increased from 2 to 18, and patients initiated on buprenorphine increased from 4/month to 18/month. 180-day treatment retention was 53%, and 81% of patients had consistently negative urine drug testing. Psychiatric and medical comorbidities were common, 70 and 44%, respectively. Although PCPs who prescribed buprenorphine found working in this model enjoyable and effective, the majority of non-waivered PCPs remained reluctant to participate. Conclusions: In our experience, treatment of OUD in primary care utilizing the CCM effectively addresses OUD and commonly comorbid anxiety and depression, and leads to an expansion of treatment. Successful implementation of OUD treatment requires addressing negative attitudes and perceptions.

Multi-level Influences on Breast Cancer Screening in Primary Care.

BACKGROUND: Use of breast cancer screening is influenced by factors associated with patients, primary care providers, practices, and health systems. OBJECTIVE: We examined the relative effects of these nested levels on four breast cancer screening metrics. DESIGN: A web-based survey was completed at 15 primary care practices within two health systems representing 306 primary care providers (PCPs) serving 46,944 women with a primary care visit between 1/2011-9/2014. Analyses occurred between 1/2017 and 5/2017. MAIN MEASURES: Across four nested levels (patient, PCP, primary care practice, and health system), frequency distributions and adjusted rates of primary care practice characteristics and survey results for four breast screening metrics (percent screened overall, and percent screened age 40-49, 50-74, and 75+) were reported. We used hierarchical multi-level mixed and random effects analysis to assess the relative influences of PCP, primary care practice, and health system on the breast screening metrics. KEY RESULTS: Overall, the proportion of women undergoing breast cancer screening was 73.1% (73.4% for ages 40-49, 76.5% for 50-74, and 51.1% for 75+). Patient ethnicity and number of primary care visits were strongly associated with screening rates. After adjusting for woman-level factors, 24% of the overall variation among PCPs was attributable to the primary care practice level, 35% to the health system level, and 41% to the residual variation among PCPs within practice. No specific provider-level characteristics were found to be statistically significant determinants of screening rates. CONCLUSIONS: After accounting for woman-level characteristics, the remaining variation in breast cancer screening was largely due to provider and health system variation.

Impact of numeracy on understanding of prostate cancer risk reduction in PSA screening.

Prostate-specific antigen (PSA) screening for prostate cancer in men of average risk remains controversial. Patients' ability to incorporate risk reduction data into their decision-making may depend on their numeracy. We assessed the impact of patients' numeracy on their understanding of the risk reduction benefits of PSA screening. Men attending a general internal medicine clinic were invited to complete a survey. Four versions of the survey each included a three-item numeracy test and PSA risk reduction data, framed one of four ways: absolute (ARR) versus relative risk reduction (RRR), with or without baseline risk (BR). Respondents were asked to adjust their perceived risk of prostate-cancer mortality using the data presented. Accuracy of risk reduction was evaluated relative to how risk data were framed. Among a total of 200 respondents, a majority incorrectly answered one or more of the numeracy items. Overall accuracy of risk adjustment was only 20%. Accuracy varied with data framing: when presented with RRR, respondents were 13% accurate without BR and 31% accurate with BR; when presented with ARR, they were 0% accurate without BR and 35% accurate with BR. Including BR data significantly improved accuracy for both RRR (P = 0.03) and ARR groups (P < 0.01). Accuracy was significantly related to numeracy; numeracy scores of 0, 1, 2, and 3 were associated with accuracy rates of six, five, nine, and 36 percent, respectively (P < 0.01). Overall, numeracy was significantly associated with the accuracy of interpreting quantitative benefits of PSA screening. Alternative methods of communicating risk may facilitate shared decision-making in the use of PSA screening for early detection of prostate cancer.

Alignment of breast cancer screening guidelines, accountability metrics, and practice patterns.

OBJECTIVES: Breast cancer screening guidelines and metrics are inconsistent with each other and may differ from breast screening practice patterns in primary care. This study measured breast cancer screening practice patterns in relation to common evidence-based guidelines and accountability metrics. STUDY DESIGN: Cohort study using primary data collected from a regional breast cancer screening research network between 2011 and 2014. METHODS: Using information on women aged 30 to 89 years within 21 primary care practices of 2 large integrated health systems in New England, we measured the proportion of women screened overall and by age using 2 screening definition categories: any mammogram and screening mammogram. RESULTS: Of the 81,352 women in our cohort, 54,903 (67.5%) had at least 1 mammogram during the time period, 48,314 (59.4%) had a screening mammogram. Women aged 50 to 69 years were the highest proportion screened (82.4% any mammogram, 75% screening indication); 72.6% of women at age 40 had a screening mammogram with a median of 70% (range = 54.3%-84.8%) among the practices. Of women aged at least 75 years, 63.3% had a screening mammogram, with the median of 63.9% (range = 37.2%-78.3%) among the practices. Of women who had 2 or more mammograms, 79.5% were screened annually. CONCLUSIONS: Primary care practice patterns for breast cancer screening are not well aligned with some evidence-based guidelines and accountability metrics. Metrics and incentives should be designed with more uniformity and should also include shared decision making when the evidence does not clearly support one single conclusion.

Responses to a Decision Aid on Prostate Cancer Screening in Primary Care Practices.

INTRODUCTION: Prostate-specific antigen (PSA) testing remains controversial, with most guidelines recommending shared decision making. This study describes men's PSA screening preferences before and after viewing a decision aid and relates these preferences to subsequent clinician visit content. METHODS: Men were recruited from two health systems in 2009-2013. Participants answered a questionnaire before and after decision aid viewing addressing PSA screening preferences and five basic knowledge questions. At one health system, participants also answered a survey after a subsequent clinician visit. Data were analyzed in 2014. RESULTS: One thousand forty-one predominantly white, well-educated men responded to the pre- and post-viewing questionnaire (25% and 29% response rates at the two sites). After viewing, the proportion of patients leaning away from PSA screening increased significantly (p<0.001), with 386 (38%) leaning toward PSA screening versus 436 (43%) before viewing; 174 (17%) unsure versus 319 (32%) before; and 448 (44%) leaning away versus 253 (25%) before. Higher knowledge scores were associated with being more likely to lean against screening and less likely to be unsure (p<0.001). Among 278 men who also completed a questionnaire after a subsequent clinician visit, participants who planned to discuss PSA screening with their clinicians were significantly more likely to report such discussions than participants who did not (148/217 [68%] vs 16/46 [35%], respectively [p<0.001]). CONCLUSIONS: A decision aid reduces men's interest in PSA screening, particularly among the initially unsure. Men who plan to discuss PSA screening with their clinician after a decision aid are more likely to do so.

Use of a web-based survey to facilitate shared decision making for patients eligible for cancer screening.

OBJECTIVE: Our aim was to facilitate shared decision making (SDM) during preventive visits by utilizing a web-based survey system to offer colorectal cancer (CRC) and prostate cancer screening decision aids (DAs) to appropriately identified patients prior to the visit. METHODS: Patients completed a web-based questionnaire before their preventive medicine appointment. Age- and gender-appropriate patients completed additional questions to determine eligibility for CRC or prostate-specific antigen (PSA) screening. Eligible patients were offered a choice of video or print DA, and completed questions assessing their knowledge, values, and preferences regarding the screening decision. Responses were summarized and fed forward to clinician and patient reports. RESULTS: Overall, 11,493 CRC and 4,384 PSA questionnaires were completed. Patient responses were used to identify those eligible for cancer-screening DAs: 2,187 (19 %) for CRC and 2,962 (68 %) for PSA; 15 % of eligible patients requested a DA. Many patients declined a DA because they indicated they "already know enough to make their decision" (34 % for CRC, 46 % for PSA). CONCLUSION: A web-based questionnaire provides an efficient means to identify patients eligible for cancer screening decisions and to offer them DAs before an appointment. Pre-visit use of DAs along with reports giving feedback to patients and clinicians provides an opportunity for SDM to occur at the visit.

Strategies for distributing cancer screening decision aids in primary care.

OBJECTIVE: Decision aids (DAs) have been shown to facilitate shared decision making about cancer screening. However, little data exist on optimal strategies for dissemination. Our objective was to compare different decision aid distribution models. METHODS: Eligible patients received video decision aids for prostate cancer (PSA) or colon cancer screening (CRC) through 4 distribution methods. Outcome measures included DA loans (N), % of eligible patients receiving DA, and patient and provider satisfaction. RESULTS: Automatically mailing DAs to all age/gender appropriate patients led to near universal receipt by screening-eligible patients, but also led to ineligible patients receiving DAs. Three different elective (non-automatic) strategies led to low rates of receipt. Clinician satisfaction was higher when patients viewed the DA before the visit, and this model facilitated implementation of the screening choice. Regardless of timing or distribution method, patient satisfaction was high. CONCLUSIONS: An automatic DA distribution method is more effective than relying on individual initiative. Enabling patients to view the DA before the visit is preferred. PRACTICE IMPLICATIONS: Systematically offering DAs to all eligible patients before their appointments is the ideal strategy, but may be challenging to implement.