Associations between Missed Colonoscopy Appointments and Multiple Prior Adherence Behaviors in an Integrated Healthcare System: An Observational Study.

BACKGROUND: Missed colonoscopy appointments delay screening and treatment for gastrointestinal disorders. Prior nonadherence with other care components may be associated with missed colonoscopy appointments. OBJECTIVE: To assess variability in prior adherence behaviors and their association with missed colonoscopy appointments. DESIGN: Retrospective cohort study. PARTICIPANTS: Patients scheduled for colonoscopy in an integrated healthcare system between January 2016 and December 2018. MAIN MEASURES: Prior adherence behaviors included: any missed outpatient appointment in the previous year; any missed gastroenterology clinic or colonoscopy appointment in the previous 2 years; and not obtaining a bowel preparation kit pre-colonoscopy. Other sociodemographic, clinical, and system characteristics were included in a multivariable model to identify independent associations between prior adherence behaviors and missed colonoscopy appointments. KEY RESULTS: The median age of the 57,590 participants was 61 years; 52.8% were female and 73.4% were white. Of 77,684 colonoscopy appointments, 3,237 (4.2%) were missed. Individuals who missed colonoscopy appointments were more likely to have missed a previous primary care appointment (62.5% vs. 38.4%), a prior gastroenterology appointment (18.4% vs. 4.7%) or not to have picked up a bowel preparation kit (42.4% vs. 17.2%), all p < 0.001. Correlations between the three adherence measures were weak (phi < 0.26). The rate of missed colonoscopy appointments increased from 1.8/100 among individuals who were adherent with all three prior care components to 24.6/100 among those who were nonadherent with all three care components. All adherence variables remained independently associated with nonadherence with colonoscopy in a multivariable model that included other covariates; adjusted odds ratios (with 95% confidence intervals) were 1.6 (1.5-1.8) for outpatient appointments, 1.9 (1.7-2.1) for gastroenterology appointments, and 3.1 (2.9-3.4) for adherence with bowel preparation kits, respectively. CONCLUSIONS: Three prior adherence behaviors were independently associated with missed colonoscopy appointments. Studies to predict adherence should use multiple, complementary measures of prior adherence when available.

App-Based Mindfulness for Attenuation of Subjective and Physiological Stress Reactivity in a Population With Elevated Stress: Randomized Controlled Trial.

BACKGROUND: Stress-related mental health disorders have steadily increased and contributed to a worldwide disease burden with up to 50% experiencing a stress-related mental health disorder worldwide. Data suggest that only approximately 20%-65% of individuals receive treatment. This gap in receiving treatment may be attributed to barriers such as limited treatment access, negative stigma surrounding mental health treatment, approachability (ie, not having a usual treatment plan or provider), affordability (ie, lack of insurance coverage and high treatment cost), and availability (ie, long waits for appointments) leaving those who need treatment without necessary care. To mitigate the limited access mental health treatment, there has been a rise in the application and study of digital mental health interventions. As such, there is an urgent need and opportunity for effective digital mental health interventions to alleviate stress symptoms, potentially reducing adverse outcomes of stress-related disorders. OBJECTIVE: This study examined if app-based guided mindfulness could improve subjective levels of stress and influence physiological markers of stress reactivity in a population with elevated symptoms of stress. METHODS: The study included 163 participants who had moderate to high perceived stress as assessed by the Perceived Stress Scale (PSS-10). Participants were randomly allocated to 1 of 5 groups: a digital guided program designed to alleviate stress (Managing Stress), a digital mindfulness fundamentals course (Basics), digitally delivered breathing exercises, an active control intervention (Audiobook), and a Waitlist Control group. The 3 formats of mindfulness interventions (Managing Stress, Basics, and Breathing) all had a total duration of 300 minutes spanning 20-30 days. Primary outcome measures were perceived stress using the PSS-10, self-reported sleep quality using the Pittsburgh Sleep Quality Index, and trait mindfulness using the Mindful Attention Awareness Scale. To probe the effects of physiological stress, an acute stress manipulation task was included, specifically the cold pressor task (CPT). Heart rate variability was collected before, during, and after exposure to the CPT and used as a measure of physiological stress. RESULTS: The results showed that PSS-10 and Pittsburgh Sleep Quality Index scores for the Managing Stress (all P<.001) and Basics (all P≤.002) groups were significantly reduced between preintervention and postintervention periods, while no significant differences were reported for the other groups. No significant differences among groups were reported for Mindful Attention Awareness Scale (P=.13). The physiological results revealed that the Managing Stress (P<.001) and Basics (P=.01) groups displayed reduced physiological stress reactivity between the preintervention and postintervention periods on the CPT. There were no significant differences reported for the other groups. CONCLUSIONS: These results demonstrate efficacy of app-based mindfulness in a population with moderate to high stress on improving self-reported stress, sleep quality, and physiological measures of stress during an acute stress manipulation task. TRIAL REGISTRATION: ClinicalTrials.gov NCT05832632; https://www.clinicaltrials.gov/ct2/show/NCT05832632.

Application of a Machine Learning Algorithm to Develop and Validate a Prediction Model for Ambulatory Non-Arrivals.

BACKGROUND: Non-arrivals to scheduled ambulatory visits are common and lead to a discontinuity of care, poor health outcomes, and increased subsequent healthcare utilization. Reducing non-arrivals is important given their association with poorer health outcomes and cost to health systems. OBJECTIVE: To develop and validate a prediction model for ambulatory non-arrivals. DESIGN: Retrospective cohort study. PATIENTS OR SUBJECTS: Patients at an integrated health system who had an outpatient visit scheduled from January 1, 2020, to February 28, 2022. MAIN MEASURES: Non-arrivals to scheduled appointments. KEY RESULTS: There were over 4.3 million ambulatory appointments from 1.2 million adult patients. Patients with appointment non-arrivals were more likely to be single, racial/ethnic minorities, and not having an established primary care provider compared to those who arrived at their appointments. A prediction model using the XGBoost machine learning algorithm had the highest AUC value (0.768 [0.767-0.770]). Using SHAP values, the most impactful features in the model include rescheduled appointments, lead time (number of days from scheduled to appointment date), appointment provider, number of days since last appointment with the same department, and a patient's prior appointment status within the same department. Scheduling visits close to an appointment date is predicted to be less likely to result in a non-arrival. Overall, the prediction model calibrated well for each department, especially over the operationally relevant probability range of 0 to 40%. Departments with fewer observations and lower non-arrival rates generally had a worse calibration. CONCLUSIONS: Using a machine learning algorithm, we developed a prediction model for non-arrivals to scheduled ambulatory appointments usable for all medical specialties. The proposed prediction model can be deployed within an electronic health system or integrated into other dashboards to reduce non-arrivals. Future work will focus on the implementation and application of the model to reduce non-arrivals.

Characterising Australian memory clinics: current practice and service needs informing national service guidelines.

BACKGROUND: Memory clinics (MCs) play a key role in accurate and timely diagnoses and treatment of dementia and mild cognitive impairment. However, within Australia, there are little data available on current practices in MCs, which hinder international comparisons for best practice, harmonisation efforts and national coordination. Here, we aimed to characterise current service profiles of Australian MCs. METHODS: The 'Australian Dementia Network Survey of Expert Opinion on Best Practice and the Current Clinical Landscape' was conducted between August-September 2020 as part of a larger-scale Delphi process deployed to develop national MC guidelines. In this study, we report on the subset of questions pertaining to current practice including wait-times and post-diagnostic care. RESULTS: Responses were received from 100 health professionals representing 60 separate clinics (45 public, 11 private, and 4 university/research clinics). The majority of participants were from clinics in metropolitan areas (79%) and in general were from high socioeconomic areas. While wait-times varied, only 28.3% of clinics were able to offer an appointment within 1-2 weeks for urgent referrals, with significantly more private clinics (58.3%) compared to public clinics (19.5%) being able to do so. Wait-times were less than 8 weeks for 34.5% of non-urgent referrals. Only 20.0 and 30.9% of clinics provided cognitive interventions or post-diagnostic support respectively, with 7.3% offering home-based reablement programs, and only 12.7% offering access to group-based education. Metropolitan clinics utilised neuropsychological assessments for a broader range of cases and were more likely to offer clinical trials and access to research opportunities. CONCLUSIONS: In comparison to similar countries with comprehensive government-funded public healthcare systems (i.e., United Kingdom, Ireland and Canada), wait-times for Australian MCs are long, and post-diagnostic support or evidence-based strategies targeting cognition are not common practice. The timely and important results of this study highlight a need for Australian MCs to adopt a more holistic service of multidisciplinary assessment and post-diagnostic support, as well as the need for the number of Australian MCs to be increased to match the rising number of dementia cases.

Primary Care Visits Are Timelier When Patients Choose Telemedicine: A Cross-Sectional Observational Study.

Introduction: Telemedicine could increase timely access to primary care-a key dimension of care quality. Methods: Among patient-scheduled appointments with their own primary care providers using the online portal in a large integrated health care delivery system, we measured the association between visit type (telemedicine or in-person) and appointment timeliness. We calculated the calendar days between the scheduling date and the actual appointment time. Results: Overall, 2,178,440 primary care visits were scheduled and 14% were done through telemedicine. The mean calendar days between the scheduling and the appointment time were 1.80 for telephone visits, 2.29 for video visits, and 3.52 for in-person visits. After multivariate adjustment, 66.61% (confidence interval [95% CI]: 66.44-66.79) of telephone visits, 56.58% (95% CI: 55.90-57.27) of video visits, and 46.49% (95% CI: 46.42-46.57) of in-person visits were scheduled to occur within 1 day of making the appointment. Conclusions: In a setting with comparable in-person and telemedicine scheduling availability, choosing telemedicine was associated with more timely access to primary care.

Consequences of the COVID-19 pandemic on lung cancer care and patient health in a German lung cancer center: results from a cross-sectional questionnaire.

BACKGROUND: The novel coronavirus SARS-CoV-2 has caused a global COVID-19 pandemic, leading to worldwide changes in public health measures. In addition to changes in the public sector (lockdowns, contact restrictions), hospitals modified care to minimize risk of infection and to mobilize resources for COVID-19 patients. Our study aimed to assess the impact of these measures on access to care and behaviour of patients with thoracic malignancies. METHODS: Thoracic oncology patients were surveyed in October 2020 using paper-based questionnaires to assess access to ambulatory care services and tumor-directed therapy during the COVID-19 pandemic. Additionally, behaviour regarding social distancing and wearing of face masks were assessed, as well as COVID-19 exposure, testing and vaccination. Results are presented as absolute and relative frequencies for categorical variables and means with standard deviation for numerical variables. We used t-test, and ANOVA to compare differences in metric variables and Chi2-test to compare proportions between groups. RESULTS: 93 of 245 (38%) patients surveyed completed the questionnaire. Respiration therapy and physical therapy were unavailable for 57% to 70% of patients during March/April. Appointments for tumor-directed therapy, tumor imaging, and follow-up care were postponed or cancelled for 18.9%, 13.6%, and 14.8% of patients, respectively. Patients reported their general health as mostly unaffected. The majority of patients surveyed did not report reducing their contacts with family. The majority reduced contact with friends. Most patients wore community masks, although a significant proportion reported respiratory difficulties during prolonged mask-wearing. 74 patients (80%) reported willingness to be vaccinated against SARS-CoV-2. CONCLUSIONS: This survey provides insights into the patient experience during the second wave of the COVID-19 pandemic in Munich, Germany. Most patients reported no negative changes to cancer treatments or general health; however, allied health services were greatly impacted. Patients reported gaps in social distancing, but were prepared to wear community masks. The willingness to get vaccinated against SARS-CoV-2 was high. This information is not only of high relevance to policy makers, but also to health care providers.

The effect of a public transportation expansion on no-show appointments.

OBJECTIVE: To test whether there were fewer missed medical appointments ("no-shows") for patients and clinics affected by a significant public transportation expansion. STUDY SETTING: A new light rail line was opened in a major metropolitan area in June 2014. We obtained electronic health records data from an integrated health delivery system in the area with over three million appointments at 97 clinics between 2013 and 2016. STUDY DESIGN: We used a difference-in-differences research design to compare whether no-show appointment rates differentially changed among patients and clinics located near versus far from the new light rail line after it opened. Models included fixed effects to account for underlying differences across clinics, patient zip codes, and time. DATA EXTRACTION METHODS: We obtained data from an electronic health records system representing all appointments scheduled at 97 outpatient clinics in this system. We excluded same-day, urgent care, and canceled appointments. PRINCIPAL FINDINGS: The probability of no-show visits differentially declined by 0.5 percentage points (95% confidence interval [CI]: -0.9 to -0.1), or 4.5% relative to baseline, for patients living near the new light rail compared to those living far from it, after the light rail opened. The effects were stronger among patients covered by Medicaid (-1.6 percentage points [95% CI: -2.4 to -0.8] or 9.5% relative to baseline). CONCLUSIONS: Improvements to public transit may improve access to health care, especially for people with low incomes.

Exploring the implications of the first COVID-19 lockdown on patients with melanoma: a national survey.

The impact of the COVID-19 pandemic upon care of malignant melanoma (MM) remains as yet poorly understood. We undertook a UK-wide national survey, in conjunction with a patient support group (Melanoma UK), to explore patient perceptions of the impact of the pandemic upon treatment and outpatient care of their MM. Our findings suggest that following the onset of COVID-19, a significant minority of treatments and appointments have been delayed, there has been a shift from face-to-face to virtual outpatient consultations and there may be a rise in psychological comorbidities in patients with MM. We would urge clinicians to consider mental health interventions as part of a holistic care package.

Treatment and Follow-up Care Associated With Patient-Scheduled Primary Care Telemedicine and In-Person Visits in a Large Integrated Health System.

Importance: Telemedicine visits can offer patients convenient access to a clinician, but it is unclear whether treatment differs from that with in-person visits or how often patients require in-person follow-up. Objective: To examine whether physician prescribing and orders differ between telemedicine and office visits, whether physicians conducting telemedicine visits are more likely to require in-person follow-up, and whether telemedicine visits are associated with more health events. Design, Setting, and Participants: This cohort study included all patients who scheduled primary care appointments through the patient portal of a large integrated health care delivery system newly implementing patient-scheduled video telemedicine visits from January 2016 to May 2018. Main Outcomes and Measures: Adjusted rates of any medication prescribed or laboratory tests or imaging ordered and rates of follow-up health care utilization (in-person visits, emergency department visits, and hospitalizations) within 7 days after the index visit, stratified by index primary care visit type, were generated using multivariable adjustment for patient, access, and clinical characteristics. Results: This study included 1 131 722 patients (611 821 [54%] female; mean [SD] age, 43 [22] years) with 2 178 440 total appointments (307 888 [14%] telemedicine), of which 13.5% were for patients younger than 18 years, 22.2% were for patients 65 years or older, and 54.9% were for female patients. After adjustment, 38.6% (95% CI, 38.0%-39.3%) of video visits, 34.7% (95% CI, 34.5%-34.9%) of telephone visits, and 51.9% (95% CI, 51.8%-52.0%) of office visits had any medication prescribed; laboratory tests or imaging were ordered for 29.2% (95% CI, 28.5%-29.8%) of video visits, 27.3% (95% CI, 27.1%-27.5%) of telephone visits, and 59.3% (95% CI, 59.3%-59.4%) of clinic visits. After adjustment, follow-up visits within 7 days occurred after 25.4% (95% CI, 24.7%-26.0%) of video visits, 26.0% (95% CI, 25.9%-26.2%) of telephone visits, and 24.5% (95% CI, 24.5%-24.6%) of office visits. Adjusted emergency department visits and rates of hospitalizations were not statistically significantly different by primary care index visit type. Conclusions and Relevance: In this cohort study of patient self-scheduled primary care telemedicine visits within ongoing patient-physician relationships, prescribing and orders were significantly lower for telemedicine visits than for clinic visits, with slightly higher follow-up office visits for telemedicine but no difference in health events (emergency department visits or hospitalizations). Video or telephone visits may be a convenient and efficient way to access primary care and address patient needs.

Hereditary Cancer Risk Using a Genetic Chatbot Before Routine Care Visits.

OBJECTIVE: To examine user uptake and experience with a clinical chatbot that automates hereditary cancer risk triage by collecting personal and family cancer history in routine women's health care settings. METHODS: We conducted a multicenter, retrospective observational study of patients who used a web-based chatbot before routine care appointments to assess their risk for hereditary breast and ovarian cancer, Lynch syndrome, and adenomatous polyposis syndromes. Outcome measures included uptake and completion of the risk-assessment and educational section of the chatbot interaction and identification of hereditary cancer risk as evaluated against National Comprehensive Cancer Network criteria. RESULTS: Of the 95,166 patients invited, 61,070 (64.2%) engaged with the clinical chatbot. The vast majority completed the cancer risk assessment (89.4%), and most completed the genetic testing education section (71.4%), indicating high acceptability among those who opted to engage. The mean duration of use was 15.4 minutes (SD 2 hours, 56.2 minutes) when gaps of inactivity longer than 5 minutes were excluded. A personal history of cancer was reported by 19.1% (10,849/56,656) and a family history of cancer was reported by 66.7% (36,469/54,652) of patients who provided the relevant information. One in four patients (14,850/54,547) screened with the chatbot before routine care appointments met National Comprehensive Cancer Network criteria for genetic testing. Among those who were tested, 5.6% (73/1,313) had a disease-causing pathogenic variant. CONCLUSION: A chatbot digital health tool can help identify patients at high risk for hereditary cancer syndromes before routine care appointments. This scalable intervention can effectively provide cancer risk assessment, engage patients with educational information, and facilitate a path toward preventive genetic testing. FUNDING SOURCE: Implementation of the chatbot in clinics was funded by industry support from commercial genetic testing laboratories Ambry, Invitae, and Progenity.

Improving Outpatient Infusion Clinic Wait Times at a Comprehensive Cancer Center.

PURPOSE: Many factors contribute to long wait times for patients on the day of their chemotherapy infusion appointments. Longer wait time leads to nonoptimal care, increased costs, and decreased patient satisfaction. We conducted a quality improvement project to reduce the infusion wait times at a Comprehensive Cancer Center. METHODS: A multidisciplinary working group of physicians, infusion center nurses, pharmacists, information technology analysts, the Chief Medical Officer, and patient advocates formed a working group. Wait times were analyzed, and the contributing factors to long wait time were identified. Plan-Do-Study-Act cycles were implemented and included labeling patients ready to treat earlier, loading premedications into the medication dispensing system, increasing the number of pharmacy staff, and improving communication using a secure messaging system. The outcome measure was time from patient appointment to initiation of first drug at the infusion center. The secondary outcome measure was patient wait time satisfaction on the basis of Press Ganey score. RESULTS: Postintervention, the mean time from appointment to initiation of first drug decreased 17.6 minutes (P < .001; 95% CI, 16.3 to 18.9), from 58.1 minutes to 40.5 minutes (43.5% decrease). Patient wait time satisfaction score increased 8.9 points (P < .001; 95% CI, 6.0 to 11.82), from 76.2 to 85.1 (11.7% increase). CONCLUSION: Exploring real-time data and using a classic quality improvement methodology allowed a Comprehensive Cancer Center to identify deficiencies and prevent delays in chemotherapy initiation. This significantly improved patient wait time and patient satisfaction.

Patient outcomes and costs associated with functional medicine-based care in a shared versus individual setting for patients with chronic conditions: a retrospective cohort study.

OBJECTIVE: To compare outcomes and costs associated with functional medicine-based care delivered in a shared medical appointment (SMA) to those delivered through individual appointments. DESIGN: A retrospective cohort study was performed to assess outcomes and cost to deliver care to patients in SMAs and compared with Propensity Score (PS)-matched patients in individual appointments. SETTING: A single-centre study performed at Cleveland Clinic Center for Functional Medicine. PARTICIPANTS: A total of 9778 patients were assessed for eligibility and 7323 excluded. The sample included 2455 patients (226 SMAs and 2229 individual appointments) aged ≥18 years who participated in in-person SMAs or individual appointments between 1 March 2017 and 31 December 2019. Patients had a baseline Patient-Reported Outcome Measurement Information System (PROMIS) Global Physical Health (GPH) score and follow-up score at 3 months. Patients were PS-matched 1:1 with 213 per group based on age, sex, race, marital status, income, weight, body mass index, blood pressure (BP), PROMIS score and functional medicine diagnostic category. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was change in PROMIS GPH at 3 months. Secondary outcomes included change in PROMIS Global Mental Health (GMH), biometrics, and cost. RESULTS: Among 213 PS-matched pairs, patients in SMAs exhibited greater improvements at 3 months in PROMIS GPH T-scores (mean difference 1.18 (95% CI 0.14 to 2.22), p=0.03) and PROMIS GMH T-scores (mean difference 1.78 (95% CI 0.66 to 2.89), p=0.002) than patients in individual appointments. SMA patients also experienced greater weight loss (kg) than patients in individual appointments (mean difference -1.4 (95% CI -2.15 to -0.64), p<0.001). Both groups experienced a 5.5 mm Hg improvement in systolic BP. SMAs were also less costly to deliver than individual appointments. CONCLUSION: SMAs deliver functional medicine-based care that improves outcomes more than care delivered in individual appointments and is less costly to deliver.

Factors Associated With Opting Out of Automated Text and Telephone Messages Among Adult Members of an Integrated Health Care System.

Importance: Health care systems deliver automated text or telephone messages to remind patients of appointments and to provide health information. Patients who receive multiple messages may demonstrate message fatigue by opting out of future messages. Objective: To assess whether the volume of automated text or interactive voice response (IVR) telephone messages is associated with the likelihood of patients requesting to opt out of future messages. Design, Setting, and Participants: This retrospective cohort study was conducted at Kaiser Permanente Colorado (KPCO), an integrated health care system. All adult members who received 1 or more automated text or IVR message between October 1, 2018, and September 30, 2019, were included. Exposures: Receipt of automated text or IVR messages. Main Outcomes and Measures: Message volume and opt-out rates obtained from messaging systems over 1 year. Results: Of the 428 242 adults included in this study, 59.7% were women, and 66.5% were White; the mean (SD) age was 52.3 (17.7) years. During the study period, 84.1% received 1 or more text messages (median, 4 messages; interquartile range, 2-8 messages) and 67.8% received 1 or more IVR messages (median, 3 messages; interquartile range, 1-6 messages). A total of 8929 individuals (2.5%) opted out of text messages, and 4392 (1.5%) opted out of IVR messages. In multivariable analyses, individuals who received 10 to 19.9 or 20 or more text messages per year had higher opt-out rates for text messages compared with those who received fewer than 2 messages per year (adjusted odds ratio [aOR]: 10-19.9 vs <2 messages, 1.27 [95% CI, 1.17-1.38]; ≥20 vs <2 messages, 3.58 [95% CI, 3.28-3.91]), whereas opt-out rates increased progressively in association with IVR message volume, with the highest rates among individuals who received 10.0 to 19.9 messages (aOR, 11.11; 95% CI, 9.43-13.08) or 20.0 messages or more (aOR, 49.84; 95% CI, 42.33-58.70). Individuals opting out of text messages were more likely to opt out of IVR messages (aOR, 4.07; 95% CI, 3.65-4.55), and those opting out of IVR messages were more likely to opt out of text messages (aOR, 5.92; 95% CI, 5.29-6.61). Conclusions and Relevance: In this cohort study among adult members of an integrated health care system, requests to discontinue messages were associated with greater message volume. These findings suggest that, to preserve the benefits of automated outreach, health care systems should use these messages judiciously to reduce message fatigue.

The evolving use of hyperbaric oxygen therapy during the COVID-19 pandemic.

The Sars-CoV-2 (COVID-19) pandemic has resulted in significant and unprecedented shifts in the delivery of health care services in the United States. Although wound care remains an essential service during the COVID-19 pandemic, the financial consequences and infectious disease ramifications of the pandemic have resulted in closure or limitation of hours in many outpatient wound and hyperbaric oxygen therapy (HBOT) centers. As HBOT patients often require daily treatment sessions for a period of months, it is necessary for facilities providing HBOT services to adjust to the COVID-19 pandemic while still maintaining availability of this important service. Modification of HBOT session timing and chamber decontamination procedures, utilisation of telehealth services for initial patient evaluations, and acceptance of novel patient populations and diagnoses are mechanisms by which HBOT centers can adapt to the evolving model of health care delivery throughout a pandemic. While COVID-19 is not a currently accepted indication for HBOT, patients may be referred for HBOT consultation due to the post-infectious sequelae of the virus, and thus HBOT facilities must be aware of the potential uses of this treatment for post-viral complications. By redefining paradigms for health care delivery during the COVID-19 pandemic, HBOT and wound centers can continue to provide high-quality and uninterrupted care to vulnerable patient populations.

Patient experience after modifying visit delivery during the COVID-19 pandemic.

OBJECTIVES: To describe real-time changes in medical visits (MVs), visit mode, and patient-reported visit experience associated with rapidly deployed care reorganization during the coronavirus disease 2019 (COVID-19) pandemic. STUDY DESIGN: Cross-sectional time series from September 29, 2019, through June 20, 2020. METHODS: Responding to official public health and clinical guidance, team-based systematic structural changes were implemented in a large, integrated health system to reorganize and transition delivery of care from office-based to virtual care platforms. Overall and discipline-specific weekly MVs, visit mode (office-based, telephone, or video), and associated aggregate measures of patient-reported visit experience were reported. A 38-week time-series analysis with March 8, 2020, and May 3, 2020, as the interruption dates was performed. RESULTS: After the first interruption, there was a decreased weekly visit trend for all visits (ß3 = -388.94; P < .05), an immediate decrease in office-based visits (ß2 = -25,175.16; P < .01), increase in telephone-based visits (ß2 = 17,179.60; P < .01), and increased video-based visit trend (ß3 = 282.02; P < .01). After the second interruption, there was an increased visit trend for all visits (ß5 = 565.76; P < .01), immediate increase in video-based visits (ß4 = 3523.79; P < .05), increased office-based visit trend (ß5 = 998.13; P < .01), and decreased trend in video-based visits (ß5 = -360.22; P < .01). After the second interruption, there were increased weekly long-term visit trends for the proportion of patients reporting "excellent" as to how well their visit needs were met for all visits (ß5 = 0.17; P < .01), telephone-based visits (ß5 = 0.34; P < .01), and video-based visits (ß5 = 0.32; P < .01). Video-based visits had the highest proportion of respondents rating "excellent" as to how well their scheduling and visit needs were met. CONCLUSIONS: COVID-19 required prompt organizational transformation to optimize the patient experience.

The Impact of Changes in Service Delivery in Patients With Colorectal Cancer During the Initial Phase of the COVID-19 Pandemic.

BACKGROUND: The Coronavirus disease 2019 (COVID-19) pandemic has imposed significant changes in cancer service delivery resulting in increased anxiety and distress in both patients and clinicians. We aimed to investigate how these changes have been perceived by patients diagnosed with colorectal cancer and identify determinants of increased anxiety. PATIENTS AND METHODS: An anonymized 32-item survey in the specialized lower gastrointestinal cancer outpatient clinics at a tertiary cancer center in North West England between May 18 and July 1, 2020. Self-reported anxiety was based on the General Anxiety Disorder-7 screening tool. RESULTS: Of 143 participants who completed the survey (response rate, 67%), 115 (82%) were male, and the median age group was 61 to 70 years. A total of 112 (78%) participants had telephone consultation (83% met needs), and 57 (40%) had radiologic scan results discussed over the phone (96% met needs). In total, 23 (18%) participants were considered to have anxiety (General Anxiety Disorder-7 score ≥ 5), with 7 (5.5%) scoring for moderate or severe anxiety. Those concerned about getting COVID-19 infection, and worried COVID-19 would have effect on their mental health, and affect their experience of cancer care, were most likely to have anxiety (P < .05, multivariate analysis). The majority did not feel they needed support during this phase of the pandemic. Participants felt that friends and family had been very supportive, but less so the primary care services (P < .05). CONCLUSIONS: The findings of this survey suggest that some of the service changes implemented may have already improved the overall experience of cancer care among patients with colorectal cancer at our institute. Reassuringly, the incidence of participants with moderate to severe anxiety levels during the peak of COVID-19 in the United Kingdom was much lower than anticipated. Importantly, patients were much more concerned about their cancer treatment than COVID-19, emphasizing the need to continue to provide comprehensive cancer care even with a "second wave" of COVID-19.

Implementation and Outcomes of Virtual Care Across a Tertiary Cancer Center During COVID-19.

Importance: The coronavirus disease 2019 (COVID-19) pandemic has burdened health care resources and disrupted care of patients with cancer. Virtual care (VC) represents a potential solution. However, few quantitative data support its rapid implementation and positive associations with service capacity and quality. Objective: To examine the outcomes of a cancer center-wide virtual care program in response to the COVID-19 pandemic. Design, Setting, and Participants: This cohort study applied a hospitalwide agile service design to map gaps and develop a customized digital solution to enable at-scale VC across a publicly funded comprehensive cancer center. Data were collected from a high-volume cancer center in Ontario, Canada, from March 23 to May 22, 2020. Main Outcomes and Measures: Outcome measures were care delivery volumes, quality of care, patient and practitioner experiences, and cost savings to patients. Results: The VC solution was developed and launched 12 days after the declaration of the COVID-19 pandemic. A total of 22 085 VC visits (mean, 514 visits per day) were conducted, comprising 68.4% (range, 18.8%-100%) of daily visits compared with 0.8% before launch (P < .001). Ambulatory clinic volumes recovered a month after deployment (3714-4091 patients per week), whereas chemotherapy and radiotherapy caseloads (1943-2461 patients per week) remained stable throughout. No changes in institutional or provincial quality-of-care indexes were observed. A total of 3791 surveys (3507 patients and 284 practitioners) were completed; 2207 patients (82%) and 92 practitioners (72%) indicated overall satisfaction with VC. The direct cost of this initiative was CAD$ 202 537, and displacement-related cost savings to patients totaled CAD$ 3 155 946. Conclusions and Relevance: These findings suggest that implementation of VC at scale at a high-volume cancer center may be feasible. An agile service design approach was able to preserve outpatient caseloads and maintain care quality, while rendering high patient and practitioner satisfaction. These findings may help guide the transformation of telemedicine in the post COVID-19 era.

Increasing Patient Access to MRI Examinations in an Integrated Multispecialty Practice.

A multidisciplinary team evaluated and improved the MRI processes within the authors' integrated health care system, with the aim to increase patient access to MRI. The authors created a SMART (specific, measurable, achievable, relevant, and time-based) goal of decreasing the average number of days to wait for MRI examination by 50%, from 15 to 7.5 days, while also creating capacity to meet demand for same-day and next-day MRI appointment requests. The current performance metrics and processes were compared with available benchmarking and best practice data. Several work groups were created to empower and support frontline teams to identify and capture improvement opportunities. Across all MRI processes, teams focused on creating standard work, advancing practice to top of scope, removing waste, improving communication, reducing rework, and improving patient experience. Patient access to MRI was monitored, measured as the average number of days to wait from the time of scheduling to the MRI examination and time to the third-available appointment. The authors also monitored secondary outcomes (patient satisfaction, throughput metrics) and a balancing measure (technical repeat examination rates). The access improved after intervention: the average number of days to wait for MRI access decreased from 14.2 days to 5.8 days after the intervention (-8.4 days, -59.2%, P < .0001) and third-available appointment decreased from 18 days to 0 days. Ten to 20 same-day and next-day appointments became routinely available. The throughput metrics improved, and balancing measures were not changed. This project resulted in significant improvements in patient access to MRI examinations. The findings demonstrate the value of a multidisciplinary team applying comprehensive improvement strategies to increase patient access to complex services, such as MRI. ©RSNA, 2021.