Individual Level Digital Determinants of Health and Technology Acceptance of Patient Portals: A Cross-Sectional Assessment.

BACKGROUND: Digital determinants of health (DDoH), including access to technological tools, digital health literacy, and internet access, function independently as barriers to health. Assessment for DDoH is not routine within most healthcare systems, although addressing DDoH could help mitigate differential health outcomes and the digital divide. OBJECTIVE: To assess the role of individual-level factors of DDoH on patient enrollment in and use of the patient portal. METHODS: A multi-modal, cross-sectional survey was developed and deployed to 11,424 individuals based on preferred mode and language documented within the Electronic Medical Record. Based on the Technology Acceptance Model, enrollment in the patient portal and intent to use the patient portal were the outcomes of interest. Perceived usefulness and ease of use were assessed to determine construct validity, and exploratory investigations included individual-level DDoH, including internet and device access, availability of technological support, medical complexity and symptom burden, individual relationship with the healthcare system, and digital health literacy. Counts (n) and proportions (%) were used to describe response categories and unadjusted and adjusted odds ratios are reported. RESULTS: This study included 1,850 respondents (11,424 invited; 16.2% response rate) who were majority female (58.3%), White (77.2%), and an average age of 63 years. In validation of the Technology Acceptance Model, measures of perceived ease of use (i.e., using the patient portal will require a lot of mental effort, patient portal will be very easy to use) and perceived usefulness (i.e., usefulness of the patient portal to send and receive messages with providers, schedule appointments, refill medications) were positively associated with both enrollment in and intent to use the patient portal. Within adjusted models, perceived ease of use and perceived usefulness constructs in addition to constructs of digital health literacy, knowing what health resources are available on the internet (aOR=3.5, 95% CI 1.8-6.6), portal ease of use (aOR=2.8, 95% CI 1.6, 5.0), and portal usefulness (aOR=2.4, 95% CI 1.4, 4.2) were significantly associated with patient portal enrollment. Other factors associated with patient portal enrollment and intent to use included being comfortable reading and speaking English, reported use of the internet to surf the web or to send / receive emails, home internet access, and access to technology devices (computer, tablet, smartphone, etc.). CONCLUSIONS: Assessing for and addressing individual-level DDoH, including digital health literacy, access to digital tools and technologies, and support of the relational aspects between patients, social support systems, and healthcare providers could help mitigate and reduce disparities in health. By focusing efforts to assess for and address individual-level DDoH, we have an opportunity to improve digitally driven healthcare delivery outcomes like access and experience, and structural outcomes like bias built within algorithms created with incomplete representation across communities.

Impact of Program Changes Including Telemedicine and Telephonic Care During the COVID-19 Pandemic in Preventing 30-Day Hospital Readmission for Patients in a Care Transitions Program.

INTRODUCTION/OBJECTIVES: To describe health outcomes of older adults enrolled in the Mayo Clinic Care Transitions (MCCT) program before and during the COVID-19 pandemic compared to unenrolled patients. METHODS: We conducted a retrospective cohort study of adults (age >60 years) in the MCCT program compared to a usual care control group from January 1, 2019, to September 20, 2022. The MCCT program involved a home, telephonic, or telemedicine visit by an advanced care provider. Outcomes were 30- and 180-day hospital readmissions, emergency department (ED) visit, and mortality. We performed a subgroup analysis after March 1, 2020 (during the pandemic). We analyzed data with Cox proportional hazards regression models and hazard ratios (HRs) with 95% CIs. RESULTS: Of the 1,012 patients total, 354 were in the MCCT program and 658 were in the usual care group with a mean (SD) age of 81.1 (9.1) years overall. Thirty-day readmission was 16.9% (60 of 354) for MCCT patients and 14.7% (97 of 658) for usual care patients (HR, 1.24; 95% CI, 0.88-1.75). During the pandemic, the 30-day readmission rate was 15.1% (28 of 186) for MCCT patients and 14.9% (68 of 455) for usual care patients (HR, 1.20; 95% CI, 0.75-1.91). There was no difference between groups for 180-day hospitalization, 30- or 180-day ED visit, and 30- or 180-day mortality. CONCLUSIONS: Numerous factors involving patients, providers, and health care delivery systems during the pandemic most likely contributed to these findings.

Implementation of eLearning solutions for patients with chronic pain conditions.

Background: Digital and mobile (mHealth) solutions are online or application-based services intended to support individuals with health needs. Despite evidence supporting the use of mHealth for patients with chronic pain, and the increasing desire of these types of solutions by both patients and providers, adoption of mHealth solutions remains limited. Implementation mapping can serve as a practical method to facilitate implementation and adoption of mHealth solutions within healthcare settings. Methods: Implementation mapping was used to develop implementation strategies based on contextual determinants organized within the Consolidated Framework for Implementation Research (CFIR) for mHealth eLearning solutions across an integrated, multi-site healthcare system. We describe our experience identifying stakeholders, delineating implementation facilitators and barriers, defining implementation outcomes using RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework, outlining initial implementation strategies, and iterating on implementation strategies. Results: A total of 30 implementation strategies were identified and implemented. Over the first year, primary and specialty care providers across all the clinical sites (n = 70) placed 2559 orders for the mHealth solution. Most patients reported receiving the mHealth eLearning module (74%), and most patients felt that the tool improved their knowledge regarding their condition (82%) and their ability to provide self-care related to the condition (73%). Conclusion: Practical applications of implementation science methods can help enable change within healthcare settings. Implementation mapping is an exercise that can engage stakeholders to facilitate the incorporation of new methods of care delivery, including mHealth solutions.

Development of a Visit Facilitator Role to Assist Physicians in an Ambulatory Consultative Medical Practice.

Objective: To decrease the electronic health record (EHR) clerical burden and improve patient/clinician satisfaction, allied health staff were trained as visit facilitators (VFs) to assist the physician in clinical and administrative tasks. Patients and Methods: From December 7, 2020, to October 11, 2021, patients with complex medical conditions were evaluated by an internal medicine physician in an outpatient general internal medicine (GIM) consultative practice at a tertiary care institution. A VF assisted with specific tasks before, during, and after the clinical visit. Presurvey and postsurvey assessments were performed to understand the effect of the VF on clinical tasks as perceived by the physician. Results: A total of 57 GIM physicians used a VF, and 41 (82%) physicians and 39 (79%) physicians completed the pre-VF and post-VF surveys, respectively. Physicians reported a significant reduction in time reviewing outside materials, updating pertinent information, and creating/modifying EHR orders (P<.05). Clinicians reported improved interactions with patients and on-time completion of clinical documentation. In the pre-VF survey, "too much time spent" was the most common response for reviewing outside material, placing/modifying orders, completing documentation/clinical notes, resolving in-baskets, completing dismissal letters, and completing tasks outside of work hours. In the post-VF survey, "too much time spent" was not the most common answer to any question. Satisfaction improved in all areas (P<.05). Conclusion: VFs significantly reduced the EHR clinical burden and improved GIM physician practice satisfaction. This model can potentially be used in a wide range of medical practices.

Effect of an Artificial Intelligence Decision Support Tool on Palliative Care Referral in Hospitalized Patients: A Randomized Clinical Trial.

CONTEXT: Palliative care services are commonly provided to hospitalized patients, but accurately predicting who needs them remains a challenge. OBJECTIVES: To assess the effectiveness on clinical outcomes of an artificial intelligence (AI)/machine learning (ML) decision support tool for predicting patient need for palliative care services in the hospital. METHODS: The study design was a pragmatic, cluster-randomized, stepped-wedge clinical trial in 12 nursing units at two hospitals over a 15-month period between August 19, 2019, and November 17, 2020. Eligible patients were randomly assigned to either a medical service consultation recommendation triggered by an AI/ML tool predicting the need for palliative care services or usual care. The primary outcome was palliative care consultation note. Secondary outcomes included: hospital readmissions, length of stay, transfer to intensive care and palliative care consultation note by unit. RESULTS: A total of 3183 patient hospitalizations were enrolled. Of eligible patients, A total of 2544 patients were randomized to the decision support tool (1212; 48%) and usual care (1332; 52%). Of these, 1717 patients (67%) were retained for analyses. Patients randomized to the intervention had a statistically significant higher incidence rate of palliative care consultation compared to the control group (IRR, 1.44 [95% CI, 1.11-1.92]). Exploratory evidence suggested that the decision support tool group reduced 60-day and 90-day hospital readmissions (OR, 0.75 [95% CI, 0.57, 0.97]) and (OR, 0.72 [95% CI, 0.55-0.93]) respectively. CONCLUSION: A decision support tool integrated into palliative care practice and leveraging AI/ML demonstrated an increased palliative care consultation rate among hospitalized patients and reductions in hospitalizations.

Cannabis in Cancer Survivors Who Report High Impact Chronic Pain: Findings from a 1500+ Patient Survey.

BACKGROUND: Chronic pain in cancer survivors negatively impacts quality of life. This study sought to investigate the relationship between high-impact chronic pain (HICP) -- defined as chronic pain that limits life or work activities on most days or every day in the past 3 months -- and cannabis in cancer survivors. METHODS: An electronic survey was developed in conjunction with the National Cancer Institute Comprehensive Cancer Centers in the United States. This survey was distributed to cancer survivors within a multi-site, single institution setting. RESULTS: The survey response rate was 23.0% (2304/10,000); 72.7% of these patients (1676/2304) did in fact have a confirmed cancer diagnosis. Among these cancer survivors, 16.5% (unweighted 278/1676) had HICP, and 12.4% (208/1676) reported cannabis use since their cancer diagnosis. The prevalence of past 30-day cannabis use was 12.3% (206/1676). Compared to cancer survivors without pain, those with HICP were more likely to believe in the benefits of cannabis (unweighted 92.1% vs. 74.7%; age-adjusted odds ratio [OR] = 3.1; 95% CI: 1.9-5.1) and less likely to believe in its risks (unweighted 48.2% vs. 58.4%; age-adjusted OR = 0.6; 95% CI: 0.4-0.7). CONCLUSIONS: Cancer survivors with HICP have a higher prevalence of cannabis use compared to those patients without pain. More research is needed to advance pain and symptom management among cancer survivors and to identify clinical scenarios in which benefit is greater than potential harm.

Patient preferences for telehealth services in a large multispecialty practice.

INTRODUCTION: Telehealth service provision has accelerated during the Coronavirus disease 2019 (COVID-19) pandemic. As the pandemic continues, clinical practices have discovered ways to resume operations. Opportunities exist to understand patient preferences for telehealth clinical services and to tailor offerings to different demographic groups. METHODS: We conducted a survey of patients receiving telehealth services through our outpatient practice to understand the types of healthcare services for which patients report preferences for telehealth. RESULTS: We received 551 survey responses (response rate = 20.8%; 551/2650). More than half of patients indicated being 'very likely' to use telehealth services to refill medication(s) (67.3%), prepare for an upcoming visit (66.1%), review test results (60.3%), or receive education (54.2%). Males had lower odds of preferring telehealth services for reviewing test results (odds ratio (OR) = 0.57; 95% confidence interval (CI): 0.34-0.94) or mental health issues (OR = 0.54; 95% CI: 0.38-0.77). Respondents who received a video visit were significantly more likely than those who received a telephone visit to report preferences for using telehealth for education, care plan discussions, long-term health issues, and mental health. DISCUSSION: Patient preferences for telehealth services vary by services provided and respondent demographics. Experience with telehealth increases the likelihood for future use of these services.

Provider Perspectives and Clinical Outcomes with Inpatient Telenephrology.

BACKGROUND AND OBJECTIVES: Despite the dramatic increase in the provision of virtual nephrology care, only anecdotal reports of outcomes without comparators to usual care exist in the literature. This study aimed to provide objective determination of clinical noninferiority of hybrid (telenephrology plus face-to-face) versus standard (face-to-face) inpatient nephrology care. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: This retrospective study compares objective outcomes in patients who received inpatient hybrid care versus standard nephrology care at two Mayo Clinic Health System community hospitals. Outcomes were then additionally compared with those patients receiving care at another Mayo Clinic Health System site where only standard care is available. Hospitalized adults who had nephrology consults from March 1, 2020 to February 28, 2021 were considered. Regression was used to assess 30-day mortality, length of hospitalization, readmissions, odds of being prescribed dialysis, and hospital transfers. Sensitivity analysis was performed using patients who had ≥50% of their care encounters via telenephrology. Structured surveys were used to understand the perspectives of non-nephrology hospital providers and telenephrologists. RESULTS: In total, 850 patients were included. Measured outcomes that included the number of hospital transfers (odds ratio, 1.19; 95% confidence interval, 0.37 to 3.82) and 30-day readmissions (odds ratio, 0.97; 95% confidence interval, 0.84 to 1.06), among others, did not differ significantly between controls and patients in the general cohort. Telenephrologists (n=11) preferred video consults (82%) to phone for communication. More than half (64%) of telenephrologists spent less time on telenephrology compared with standard care. Non-nephrology hospital providers (n=21) were very satisfied (48%) and satisfied (29%) with telenephrology response time and felt telenephrology was as safe as standard care (67%), while providing them enough information to make patient care decisions (76%). CONCLUSIONS: Outcomes for in-hospital nephrology consults were not significantly different comparing hybrid care versus standard care. Non-nephrology hospital providers and telenephrologists had favorable opinions of telenephrology and most perceived it is as safe and effective as standard care. PODCAST: This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2022_04_11_CJN13441021.mp3.

Improving time to palliative care review with predictive modeling in an inpatient adult population: study protocol for a stepped-wedge, pragmatic randomized controlled trial.

BACKGROUND: Palliative care is a medical specialty centered on improving the quality of life (QOL) of patients with complex or life-threatening illnesses. The need for palliative care is increasing and with that the rigorous testing of triage tools that can be used quickly and reliably to identify patients that may benefit from palliative care. METHODS: To that aim, we will conduct a two-armed stepped-wedge cluster randomized trial rolled out to two inpatient hospitals to evaluate whether a machine learning algorithm accurately identifies patients who may benefit from a comprehensive review by a palliative care specialist and decreases time to receiving a palliative care consult in hospital. This is a single-center study which will be conducted from August 2019 to November 2020 at Saint Mary's Hospital & Methodist Hospital both within Mayo Clinic Rochester in Minnesota. Clusters will be nursing units which will be chosen to be a mix of complex patients from Cardiology, Critical Care, and Oncology and had previously established relationships with palliative medicine. The stepped wedge design will have 12 units allocated to a design matrix of 5 treatment wedges. Each wedge will last 75 days resulting in a study period of 12 months of recruitment unless otherwise specified. Data will be analyzed with Bayesian hierarchical models with credible intervals denoting statistical significance. DISCUSSION: This intervention offers a pragmatic approach to delivering specialty palliative care to hospital patients in need using machine learning, thereby leading to high value care and improved outcomes. It is not enough for AI to be utilized by simply publishing research showing predictive performance; clinical trials demonstrating better outcomes are critically needed. Furthermore, the deployment of an AI algorithm is a complex process that requires multiple teams with varying skill sets. To evaluate a deployed AI, a pragmatic clinical trial can accommodate the difficulties of clinical practice while retaining scientific rigor. TRIAL REGISTRATION: ClinicalTrials.gov NCT03976297 . Registered on 6 June 2019, prior to trial start.

Central Sensitization Symptom Severity and Patient-Provider Relationships in a Community Setting.

INTRODUCTION: Central sensitization syndromes (CSS) comprise an overlapping group of clinical conditions with the core feature of "pain arising as a direct consequence of a lesion or disease affecting the somatosensory system." Patients with CSS are known to have challenging interactions with healthcare providers contributing to psychological distress and increased healthcare utilization. CSS symptom severity has been associated with psychologic comorbidities, but little is known about how symptom severity relates to provider interactions. METHODS: We performed a cross-sectional survey among patients with CSS in our primary care practices to examine the relationship between CSS symptom severity and experiences with doctors. RESULTS: A total of 775 respondents completed the survey (775/5000; 15.5%) with 72% reporting high CSS symptom severity. About 44% of respondents had a prior diagnosis of fibromyalgia, 72% had migraines, and 28% had IBS. Patients with high CSS symptom severity were more likely to report that doctor(s) had often/always told them that they don't need treatment when they feel like they do (OR = 3.6, 95% CI 1.9-7.5), that doctor(s) often/always don't understand them (OR = 3.1, 95% CI 1.9-5.4), and that doctor(s) often/always seem annoyed with them when compared with respondents with low-moderate CSS symptom severity (OR = 4.8, 95% CI 2.2-12.5). Patients with high CSS symptom severity were at greater than 5 times odds of reporting being told that their symptoms were "all in their head" when compared to patients with low-moderate symptom severity (OR = 5.4, 95% CI 3.3-9.0). CONCLUSION: Patients with CSS spectrum disorders experience frequent pain and decreased quality of life. A high degree of CSS symptom severity is associated with negative experiences with healthcare providers, which deters the establishment of a positive provider-patient relationship. Further research is needed to help understand symptom severity in CSS and harness the power of the therapeutic alliance as a treatment modality.

Real-World Clinical Outcomes of Bamlanivimab and Casirivimab-Imdevimab Among High-Risk Patients With Mild to Moderate Coronavirus Disease 2019.

BACKGROUND: Bamlanivimab and casirivimab-imdevimab are authorized for treatment of mild to moderate coronavirus disease 2019 (COVID-19) in high-risk patients. We compared the outcomes of patients who received these therapies to identify factors associated with hospitalization and other clinical outcomes. METHODS: Adult patients who received monoclonal antibody from 19 November 2020 to 11 February 2021 were selected and divided into those who received bamlanivimab (n = 2747) and casirivimab-imdevimab (n = 849). The 28-day all-cause and COVID-19-related hospitalizations were compared between the groups. RESULTS: The population included 3596 patients; the median age was 62 years, and 50% were female. All had ≥1 medical comorbidity; 55% had multiple comorbidities. All-cause and COVID-19-related hospitalization rates at 28 days were 3.98% and 2.56%, respectively. After adjusting for medical comorbidities, there was no significant difference in all-cause and COVID-19-related hospitalization rates between bamlanivimab and casirivimab-imdevimab (adjusted hazard ratios [95% confidence interval], 1.4 [.9-2.2] and 1.6 [.8-2.7], respectively). Chronic kidney, respiratory and cardiovascular diseases, and immunocompromised status were associated with higher likelihood of hospitalization. CONCLUSIONS: This observational study on the use of bamlanivimab and casirivimab-imdevimab in high-risk patients showed similarly low rates of hospitalization. The number and type of medical comorbidities are associated with hospitalizations after monoclonal antibody treatment.

Influence of Social and Cultural Factors on the Decision to Consent for Monoclonal Antibody Treatment among High-Risk Patients with Mild-Moderate COVID-19.

BACKGROUND: The clinical outcomes of patients who decline anti-spike monoclonal antibody therapies for coronavirus disease-2019 (COVID-19) is not known. Factors associated with the decision to accept or decline the offer for anti-spike monoclonal antibody therapies are not established. This study aimed to identify factors impacting the decision to consent for monoclonal antibody therapies and assess the differences in clinical outcomes of patients who accepted compared to those who declined these therapies. METHODS: This retrospective cohort study enrolled 2820 adult patients who were offered monoclonal antibody therapies, bamlanivimab and casirivimab-imdevimab, for COVID-19 at Mayo Clinic in the Midwest between 11/19/2020 and 12/31/2020. The primary endpoint is the decision to accept or decline monoclonal antibody treatment. Secondary endpoints were patient-level factors that could have impacted the decision to accept treatment (age, gender, race, ethnicity, primary language spoken, and medical comorbidities). The main clinical endpoint was hospitalization within 28 days of COVID-19 diagnosis. RESULTS: 59.1% (n = 1669) chose to accept monoclonal antibody therapy, and 40.9% (n = 1151) chose to decline the offer for treatment. Patients were more likely to accept treatment if they were non-Hispanic White, English speaking, identified a spouse or life partner, had a religious affiliation, and possessed more medical comorbidities. Overall, 28-day hospitalization rate was 2.6% (n = 72/2820) and was higher among those who declined (3.3%) than those who accepted monoclonal antibody therapy (2.0%; Rate Ratio = 0.62, 95% Confidence Interval, 0.39-0.98). CONCLUSIONS: Despite having more comorbidities, patients who accepted monoclonal antibody treatments had a lower rate of hospitalization compared to patients who declined treatment. Several social and cultural factors were associated with the decision to decline therapy, including race, language, ethnicity, and lack of social support. These findings can inform public health efforts to reduce social disparities in the treatment of COVID-19 and increase utilization of monoclonal antibody therapies in high risk populations.

Changes in social relationships during an initial "stay-at-home" phase of the COVID-19 pandemic: A longitudinal survey study in the U.S.

RATIONALE: Severe acute respiratory syndrome Coronavirus 2 (SARS CoV-2), the virus that causes COVID-19, and consequent social distancing directives have been observed to negatively impact social relationships but the impact of these changes on the quality of social relationships at a population level has not been explored. OBJECTIVE: To evaluate changes in social relationships in a U.S. population sample during a time of social distancing. METHODS: We deployed a matched, longitudinal survey design of the National Institutes of Health Adult Social Relationship Scales to assess the social aspects of emotional support, instrumental support, friendship, loneliness, perceived hostility, and perceived rejection from a time without social distancing (February 2018) to a time where social distancing directives were active (May 2020). Changes in social relationships were compared using paired t-tests, and generalized linear regression models were constructed to identify subpopulations experiencing differential changes in each subdomain of social relationships during social distancing. RESULTS: Within our sample population, individuals experienced an increased sense of emotional support, instrumental support, and loneliness, and decreased feelings of friendship and perceived hostility during a period of social distancing. Individuals with low self-rated health experienced a decreased sense of emotional support, and females experienced increased feelings of loneliness compared with males. CONCLUSIONS: Social distancing measurably impacts social relationships and may have a disproportionate impact on females and individuals with lower self-rated health. If novel emergent infectious diseases become more commonplace, social interventions may be needed to mitigate the potential adverse impact of social distancing on social relationships.

Effect of Integrated Gastroenterology Specialists in a Primary Care Setting: a Retrospective Cohort Study.

BACKGROUND: Gastrointestinal (GI) complaints are common in primary care practices. The patient-centered medical home (PCMH) may improve coordination and collaboration by facilitating coordination across healthcare settings and within the community, enhancing communication between providers, and focusing on quality of care delivery. OBJECTIVE: To investigate the effect of integrated community gastroenterology specialists (ICS-GI) model within a large primary care practice. DESIGN: Retrospective cohort with propensity-matched historic controls. PATIENTS: We identified 265 patients who had a visit with one of our ICS-GI specialists and matched them (1:2) to 530 similar patients seen prior to the implementation of the ICS-GI model. MAIN MEASURES: Frequency of diagnostic testing for GI indications, visits to our outpatient GI referral practice, emergency department and hospital utilization, and time to access of specialty care for the whole population and by GI condition group. KEY RESULTS: Patients seen in our ICS-GI model had similar outpatient care utilization (OR = 1.0, 95% CI 0.7-1.4, p = 0.90), were more likely to have visits in primary care (OR OR=1.5, 95% CI 1.1-2.2, p = 0.02), and were less likely to have visits to our GI outpatient referral practice (OR = 0.3, 95% CI 0.2-0.7, p < 0.0001). Condition-specific analyses show that all GI conditions experienced decreased visits to the outpatient GI referral practice outside of patients with GI neoplasm. Populations did not differ in emergency department, hospital, or diagnostic utilization. CONCLUSIONS: We observed that an embedded specialist in primary care model is associated with improved care coordination without compromising patient safety. The PCMH could be extended to include subspecialty care.

Helpfulness of Clinical Visit Summary Content From Multi-Specialty Care: A Mixed-Methods Assessment.

OBJECTIVE: We surveyed patients who visited multiple outpatient specialty practices to understand what summary content was most helpful with the goal of optimizing meaningful outpatient clinical visit summary content. MATERIALS AND METHODS: We constructed a survey instrument to measure delivery, use, and contents of clinical visit summaries. We surveyed patients who visited with at least 2 different outpatient medical specialties to understand preferences. RESULTS: Most patients in our sample valued the summary information they received, and retained it as healthcare documentation (84%) and/or quick reference in supporting self-care (70%). Patients most commonly reported that information on results of completed tests (91%) and treatment plan instructions (89%) were very helpful. Additionally, patients expressed the importance of online access to clinical visit summary information. DISCUSSION: Most patients used the clinical visit summary as healthcare documentation, and valued online availability of their summary information. Patients most often reported that information on results of recently completed tests and specific instructions on treatment plan were very helpful. Patients who sought further information after their visit most often looked to a provider and/or online. CONCLUSIONS: Patients valued clinical visit summary accessibility and as a reference tool to summarize care and provide next steps. Optimal clinical visit summaries might collate and integrate assessments and recommendations from multiple specialties into coherent care plans for patients.

Association of a Remotely Offered Infectious Diseases eConsult Service With Improved Clinical Outcomes.

We performed a case-control study to evaluate an electronic, asynchronous infectious diseases consultative service at 2 rural hospitals within our health system. Patients with consultation via this platform (n = 100) had a significantly decreased odds of death at 30 days compared with propensity-matched controls (n = 300; adjusted odds ratio, 0.3; 95% confidence interval, 0.2-0.7; P = .003).

Creation of a Patient-Centered Journey Map to Improve the Patient Experience: A Mixed Methods Approach.

OBJECTIVE: To use a mixed methods approach to focus quality improvement efforts to enhance patient experience through human-centered design. PATIENTS AND METHODS: A mixed method approach began with returned Press Ganey Medical Practice Surveys from a large, multidisciplinary, outpatient medicine practice from July 1, 2016, through June 30, 2017, using correlation and gap analysis. The second phase deployed human-centered design approaches to process map patient journeys and generate opportunities for care improvement and to generate a theoretical framework for designing optimal care experiences. RESULTS: Our outpatient medical practices have the greatest ability to improve patient experience scores by focusing on how care teams deliver and educate patients on medications, instructions for follow-up care, and explanations about problems or conditions. By leveraging communication, the expertise of our care team members, and connection between patients and care team members, we can employ a variety of observed opportunities to enhance patient experience. Specific opportunities include leveraging tools in the electronic health record, fostering connection through empathy between patients and members of the care team, and capitalizing on the expertise of nurses on the care team. CONCLUSION: A mixed methods approach to the analysis and observation of clinical care and business operations allows for the detection of opportunities with the highest potential impact for improvement when resources are constrained.

Patient attribution: why the method matters.

OBJECTIVES: To assess the impact of 5 commonly used patient attribution methods on measured healthcare cost, quality, and utilization metrics within an integrated healthcare delivery system. STUDY DESIGN: Cross-sectional analysis of administrative data of all patients attributed (by any of 5 methods) and/or paneled to a primary care provider (PCP) at Mayo Clinic Rochester (MCR) in 2011. METHODS: We retrospectively applied 5 attribution methods to MCR administrative data from January 1, 2010, to December 31, 2011. MCR is an integrated healthcare delivery system serving primary care and referral populations. The referral practice is geographically colocated but otherwise distinct from 6 primary care practice sites that include pediatric, internal medicine, and family medicine groups. Patients attributed by each method were compared on their concordance with PCP empanelment, quality measures, healthcare utilization, and total costs of care. RESULTS: The 5 methods attributed between 61,813 (42%) and 106,152 (72%) of paneled patients to a PCP at MCR, although not necessarily to the paneled PCP. There was marked variation in care utilization and total costs of care, but not quality measures, among patients attributed by the different methods and between those paneled versus not paneled. Patients with more primary care visits were more likely to be attributed by all methods. CONCLUSIONS: Reliable identification of the physician-patient relationship is necessary for accurate evaluation of healthcare processes, efficiencies, and outcomes. Optimization and standardization of attribution methods are therefore essential as health systems, payers, and policy makers seek to evaluate and improve the value of delivered care.

A Before and After Analysis of Health Care Utilization by Patients Enrolled in Opioid Controlled Substance Agreements for Chronic Noncancer Pain.

OBJECTIVE: To evaluate the impact of opioid controlled substance agreements (CSAs) enrollment on health care utilization. PATIENTS AND METHODS: We retrospectively evaluated health care utilization changes among 772 patients receiving long-term opioid therapy for chronic noncancer pain enrolled in a CSA between July 1, 2015, and December 31, 2015. We ascertained patient characteristics and utilization 12 months before and after CSA enrollment. Decreased utilization was defined as a decrease of 1 or more hospitalizations or emergency department visits and 3 or more outpatient primary and specialty care visits. Multivariate modeling assessed demographic characteristics associated with utilization changes. RESULTS: The 772 patients enrolled in an opioid CSA during the study period had a mean ± SD age of 63.5±14.9 years and were predominantly female, white, and married. The CSA enrollment was associated with decreased outpatient primary care visits (odds ratio [OR], 0.16; 95% CI, 0.14-0.19) and increased diagnostic radiology services (OR, 1.22; 95% CI, 1.02-1.47). After CSA enrollment, patients with greater comorbidity (Charlson Comorbidity Index score >3) were more likely to have reduced hospitalizations (adjusted OR, 2.8; 95% CI, 1.3-6.0; P=.008), reduced outpatient primary care visits (adjusted OR, 2.0; 95% CI, 1.2-3.2; P=.005), and reduced specialty care visits (adjusted OR, 2.0; 95% CI, 1.2-3.3; P=.006). CONCLUSION: For patients receiving long-term opioid therapy for chronic noncancer pain, CSA enrollment is associated with reductions in primary care visits and increased radiologic service utilization. Patients with greater comorbidity were more likely to have reductions in hospitalizations, outpatient primary care visits, and outpatient specialty clinic visits after CSA enrollment. The observational nature of the study does not allow the conclusion that CSA implementation is the primary reason for these observed changes.