Automated Text Message-Based Program and Use of Acute Health Care Resources After Hospital Discharge: A Randomized Clinical Trial.

Importance: Postdischarge outreach from the primary care practice is an important component of transitional care support. The most common method of contact is via telephone call, but calls are labor intensive and therefore limited in scope. Objective: To test whether a 30-day automated texting program to support primary care patients after hospital discharge reduces acute care revisits. Design, Setting, and Participants: A 2-arm randomized clinical trial was conducted from March 29, 2022, through January 5, 2023, at 30 primary care practices within a single academic health system in Philadelphia, Pennsylvania. Patients were followed up for 60 days after discharge. Investigators were blinded to assignment, but patients and practice staff were not. Participants included established patients of the study practices who were aged 18 years or older, discharged from an acute care hospitalization, and considered medium to high risk for adverse health events by a health system risk score. All analyses were conducted using an intention-to-treat approach. Intervention: Patients in the intervention group received automated check-in text messages from their primary care practice on a tapering schedule for 30 days following discharge. Any needs identified by the automated messaging platform were escalated to practice staff for follow-up via an electronic medical record inbox. Patients in the control group received a standard transitional care management telephone call from their practice within 2 business days of discharge. Main Outcomes and Measures: The primary study outcome was any acute care revisit (readmission or emergency department visit) within 30 days of discharge. Results: Of the 4736 participants, 2824 (59.6%) were female; the mean (SD) age was 65.4 (16.5) years. The mean (SD) length of index hospital stay was 5.5 (7.9) days. A total of 2352 patients were randomized to the intervention arm and 2384 were randomized to the control arm. There were 557 (23.4%) acute care revisits in the control group and 561 (23.9%) in the intervention group within 30 days of discharge (risk ratio, 1.02; 95% CI, 0.92-1.13). Among the patients in the intervention arm, 79.5% answered at least 1 message and 41.9% had at least 1 need identified. Conclusions and Relevance: In this randomized clinical trial of a 30-day postdischarge automated texting program, there was no significant reduction in acute care revisits. Trial Registration: ClinicalTrials.gov Identifier: NCT05245773.

Implementation of Health IT for Cancer Screening in US Primary Care: Scoping Review.

BACKGROUND: A substantial percentage of the US population is not up to date on guideline-recommended cancer screenings. Identifying interventions that effectively improve screening rates would enhance the delivery of such screening. Interventions involving health IT (HIT) show promise, but much remains unknown about how HIT is optimized to support cancer screening in primary care. OBJECTIVE: This scoping review aims to identify (1) HIT-based interventions that effectively support guideline concordance in breast, cervical, and colorectal cancer screening provision and follow-up in the primary care setting and (2) barriers or facilitators to the implementation of effective HIT in this setting. METHODS: Following scoping review guidelines, we searched MEDLINE, CINAHL Plus, Web of Science, and IEEE Xplore databases for US-based studies from 2015 to 2021 that featured HIT targeting breast, colorectal, and cervical cancer screening in primary care. Studies were dual screened using a review criteria checklist. Data extraction was guided by the following implementation science frameworks: the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework; the Expert Recommendations for Implementing Change taxonomy; and implementation strategy reporting domains. It was also guided by the Integrated Technology Implementation Model that incorporates theories of both implementation science and technology adoption. Reporting was guided by PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). RESULTS: A total of 101 studies met the inclusion criteria. Most studies (85/101, 84.2%) involved electronic health record-based HIT interventions. The most common HIT function was clinical decision support, primarily used for panel management or at the point of care. Most studies related to HIT targeting colorectal cancer screening (83/101, 82.2%), followed by studies related to breast cancer screening (28/101, 27.7%), and cervical cancer screening (19/101, 18.8%). Improvements in cancer screening were associated with HIT-based interventions in most studies (36/54, 67% of colorectal cancer-relevant studies; 9/14, 64% of breast cancer-relevant studies; and 7/10, 70% of cervical cancer-relevant studies). Most studies (79/101, 78.2%) reported on the reach of certain interventions, while 17.8% (18/101) of the included studies reported on the adoption or maintenance. Reported barriers and facilitators to HIT adoption primarily related to inner context factors of primary care settings (eg, staffing and organizational policies that support or hinder HIT adoption). Implementation strategies for HIT adoption were reported in 23.8% (24/101) of the included studies. CONCLUSIONS: There are substantial evidence gaps regarding the effectiveness of HIT-based interventions, especially those targeting guideline-concordant breast and colorectal cancer screening in primary care. Even less is known about how to enhance the adoption of technologies that have been proven effective in supporting breast, colorectal, or cervical cancer screening. Research is needed to ensure that the potential benefits of effective HIT-based interventions equitably reach diverse primary care populations.

Expiration of State Licensure Waivers and Out-of-State Telemedicine Relationships.

This cross-sectional study compares the use of telemedicine in states where COVID-19 pandemic­related licensure waivers expired vs states where waivers continued.

Geographic cohorting by clinical care team: a narrative review.

BACKGROUND AND OBJECTIVE: Geographic cohorting refers to localization of inpatients to designated hospital areas (typically a unit or a set of beds) based on specified criteria. One such criterion that has been commonly discussed and studied since the early days of the hospitalist movement in the US is a patient's assigned clinical care team. Because implementing cohorting of this type requires substantial operational investment, it is important to understand the benefits and the tradeoffs associated with bringing patients into closer spatial proximity with their full team of providers and allowing clinicians to work within a defined clinical space. METHODS: We conducted a narrative review of the evidence around geographic cohorting of patients by clinical care team. We performed a comprehensive search of the PubMed, Embase, Cinahl and Scopus databases, identifying relevant English language articles. We used an inductive approach to developing thematic domains for categorization of article content. KEY CONTENT AND FINDINGS: We reviewed eighteen articles published between 2008 and 2022, and identified four thematic outcomes domains: patient-centered outcomes, communication, efficiency, and satisfaction. The existing literature demonstrates associations with improved communication and staff satisfaction. The data regarding patient outcomes and overall work efficiency, on the other hand, are equivocal and, in general, limited by study methodology. CONCLUSIONS: Geographic cohorting of inpatients according to clinical care team offers some promise for improved workplace culture. More rigorously designed studies are needed, however, to understand its impact on patient outcomes, and there should be added attention paid to throughput metrics and tradeoffs that often limit its implementation.

Receipt of Out-of-State Telemedicine Visits Among Medicare Beneficiaries During the COVID-19 Pandemic.

Importance: Early in the COVID-19 pandemic, states implemented temporary changes allowing physicians without a license in their state to provide care to their residents. There is an ongoing debate at both the federal and state levels on whether to change licensure rules permanently to facilitate out-of-state telemedicine use. Objective: To describe out-of-state telemedicine use during the pandemic. Design, Setting, and Participants: This cross-sectional study of telemedicine visits included all patients with traditional Medicare from January through June 2021. Main Outcomes and Measures: Telemedicine visits from January through June 2021 where the patient's home address and the physician's practice address were in different states. Results: In describing which patients and specialties were using out-of-state telemedicine, we focused on the period between January to June 2021. We chose this period because it was after the turmoil of the early pandemic, when vaccines became widely available and the health care system had stabilized, but before many of the temporary licensing regulations began to lapse by mid-2021. In the first half of 2021, there were 8 392 092 patients with a telemedicine visit and, of these, 422 547 (5.0%) had 1 or more out-of-state telemedicine visits. Those who lived in a county close to a state border (within 15 miles) accounted for 57.2% of all out-of-state telemedicine visits. Among the out-of-state visits in this time period, 64.3% were with a primary care or mental health clinician. For 62.6% of all out-of-state visits, a prior in-person visit occurred between the same patient and clinician between March 2019 and the visit. The demographics and conditions treated were similar for within-state and out-of-state telemedicine visits, with several notable exceptions. Among those with a telemedicine visit, people in rural communities were more likely to receive out-of-state telemedicine care (33.8% vs 21.0%), and there was high of out-of-state telemedicine use for cancer care (9.8% of all telemedicine visits for cancer care). Conclusions and Relevance: The findings of this cross-sectional study suggest that licensure restrictions of out-of-state telemedicine would have had the largest effect on patients who lived near a state border, those in rural locales, and those who received primary care or mental health treatment.

Evaluation of an Automated Text Message-Based Program to Reduce Use of Acute Health Care Resources After Hospital Discharge.

Importance: Posthospital contact with a primary care team is an established pillar of safe transitions. The prevailing model of telephone outreach is usually limited in scope and operationally burdensome. Objective: To determine whether a 30-day automated texting program to support primary care patients after hospital discharge is associated with reductions in the use of acute care resources. Design, Setting, and Participants: This cohort study used a difference-in-differences approach at 2 academic primary care practices in Philadelphia from January 27 through August 27, 2021. Established patients of the study practices who were 18 years or older, were discharged from an acute care hospitalization, and received the usual transitional care management telephone call were eligible for the study. At the intervention practice, 604 discharges were eligible and 430 (374 patients, of whom 46 had >1 discharge) were enrolled in the intervention. At the control practice, 953 patients met eligibility criteria. The study period, including before and after the intervention, ran from August 27, 2020, through August 27, 2021. Exposure: Patients received automated check-in text messages from their primary care practice on a tapering schedule during the 30 days after discharge. Any needs identified by the automated messaging platform were escalated to practice staff for follow-up via an electronic medical record inbox. Main Outcomes and Measures: The primary study outcome was any emergency department (ED) visit or readmission within 30 days of discharge. Secondary outcomes included any ED visit or any readmission within 30 days, analyzed separately, and 30- and 60-day mortality. Analyses were based on intention to treat. Results: A total of 1885 patients (mean [SD] age, 63.2 [17.3] years; 1101 women [58.4%]) representing 2617 discharges (447 before and 604 after the intervention at the intervention practice; 613 before and 953 after the intervention at the control practice) were included in the analysis. The adjusted odds ratio (aOR) for any use of acute care resources after implementation of the intervention was 0.59 (95% CI, 0.38-0.92). The aOR for an ED visit was 0.77 (95% CI, 0.45-1.30) and for a readmission was 0.45 (95% CI, 0.23-0.86). The aORs for death within 30 and 60 days of discharge at the intervention practice were 0.92 (95% CI, 0.23-3.61) and 0.63 (95% CI, 0.21-1.85), respectively. Conclusions and Relevance: The findings of this cohort study suggest that an automated texting program to support primary care patients after hospital discharge was associated with significant reductions in use of acute care resources. This patient-centered approach may serve as a model for improving postdischarge care.

An accelerated hospital observation pathway to reduce length of stay for patients with COVID-19.

OBJECTIVES: Strategies to maintain hospital capacity during the COVID-19 pandemic included reducing hospital length of stay (LOS) for infected patients. We sought to evaluate the association between LOS and enrollment in the COVID Accelerated Care Pathway, which consisted of a hospital observation protocol and postdischarge automated text message-based monitoring. STUDY DESIGN: Retrospective matched cohort study of patients hospitalized from December 14, 2020, to January 31, 2021. METHODS: Participants were patients who presented to the emergency department with acute infection due to COVID-19, required hospitalization, and met pathway inclusion criteria. Participants were compared with a propensity score-matched cohort of patients with COVID-19 admitted to the same hospital during the 7 weeks preceding and following pathway implementation. RESULTS: There were 44 patients in the intervention group and 83 patients in the propensity score-matched cohort. The mean (SD) hospital LOS for patients in the intervention group was 1.7 (2.6) days compared with 3.9 (2.3) days for patients in the matched cohort (difference, -2.2 days; 95% CI, -3.3 to -1.1). In the intervention group, 2 patients (5%; 95% CI, 0%-15%) were rehospitalized within 14 days compared with 8 (10%; 95% CI, 4%-17%) in the matched cohort. CONCLUSIONS: Patients with COVID-19 who were managed through an accelerated hospital observation protocol and postdischarge monitoring service had reduced hospital LOS compared with patients receiving standard care. Hospital preparedness for future public health emergencies may involve the design of pathways that reduce the time that patients spend in the hospital, lower cost, and ensure continued recovery upon discharge.

Trends in Receipt of Help at Home After Hospital Discharge Among Older Adults in the US.

Importance: With declining use of institutional postacute care, more patients are going directly home after hospital discharge. The consequences on the amount of help needed at home after discharge are unknown. Objective: To estimate trends in the frequency and duration of receipt of help with activities of daily living (ADLs) among older adults discharged home. Design, Setting, and Participants: Repeated cross-sectional study of a national sample of community-dwelling older adults who returned home after hospital discharge from 2011 to 2017. Participants included respondents to National Health and Aging Trends Study (NHATS), an annual population-based, nationally representative survey of Medicare beneficiaries, who were 69 years or older and were discharged from an acute care hospital to home during the years of the study. A nationally representative sample was estimated using NHATS' analytic weights. Unweighted frequencies and weighted and unweighted percentages are reported. The analysis was conducted from September 2020 to October 2021. Exposures: Discharge from an acute care hospitalization. Main Outcomes and Measures: Receipt of help with ADLs during the 3 months after hospital discharge. Results: Of the 3591 survey participants who were discharged home from an acute care hospital during the study period, 53.3% were female, 54.8% were married or living with a partner, and the mean (SD) age was 78.5 (7.0) years. Of these, 1710 (44.1%) reported receiving help within 3 months of discharge. Compared with people not receiving help, those receiving help were older (mean [SD] years, 79.7 [7.5] years vs 77.6 [6.3] years), had worse self-rated health at baseline (47.1% with fair or poor health vs 26.5%) and were more likely to have dementia (21.8% vs 5.5%). The percentage of respondents who reported receiving help increased during the study period from 38.1% of hospital discharges in 2011 to 51.5% in 2017. For those who were independent in their ADLs before hospitalization, the percentage receiving help after discharge more than doubled over the study period increasing from 9.3% receiving help in 2011 to 31.8% in 2017. Among patients who did not receive Medicare-reimbursed home health, the percentage receiving help also increased from 22.1% to 28.1%. Among those who received help after discharge, the need for help slowly declined to prehospitalization levels over the ensuing 9 months. Conclusions and Relevance: In this cross-sectional study, older adults' receipt of help at home after hospital discharge increased from 2011 to 2017, including patients relying on non-Medicare funded sources of care. As payers steer patients away from inpatient postacute care facilities, policymakers will need to pay attention to this shifting burden of care.

Trends in Post-Acute Care Utilization During the COVID-19 Pandemic.

OBJECTIVE: To examine the effect of the COVID-19 pandemic on post-acute care utilization and spending. DESIGN: We used a large national multipayer claims data set from January 2019 through October 2020 to examine trends in posthospital discharge location and spending. SETTING AND PARTICIPANTS: We identified and included 975,179 hospital discharges who were aged ≥65 years. METHODS: We summarized postdischarge utilization and spending in each month of the study: (1) the percentage of patients discharged from the hospital to home for self-care and to the 3 common post-acute care locations: home with home health, skilled nursing facility (SNF), and inpatient rehabilitation; (2) the rate of discharge to each location per 100,000 insured members in our cohort; (3) the total amount spent per month in each post-acute care location; and (4) the percentage of spending in each post-acute care location out of the total spending across the 3 post-acute care settings. RESULTS: The percentage of patients discharged from the hospital to home or to inpatient rehabilitation did not meaningfully change during the pandemic whereas the percentage discharged to SNF declined from 19% of discharges in 2019 to 14% by October 2020. Total monthly spending declined in each of the 3 post-acute care locations, with the largest relative decline in SNFs of 55%, from an average of $42 million per month in 2019 to $19 million in October 2020. Declines in total monthly spending were smaller in home health (a 41% decline) and inpatient rehabilitation (a 32% decline). As a percentage of all post-acute care spending, spending on SNFs declined from 39% to 31%, whereas the percentage of post-acute care spending on home health and inpatient rehabilitation both increased. CONCLUSIONS AND IMPLICATIONS: Changes in posthospital discharge location of care represent a significant shift in post-acute care utilization, which persisted 9 months into the pandemic. These shifts could have profound implications on the future of post-acute care.

Short-Stay Hospitalizations for Patients with COVID-19: A Retrospective Cohort Study.

OBJECTIVE: Patients requiring hospital care for COVID-19 may be stable for discharge soon after admission. This study sought to describe patient characteristics associated with short-stay hospitalization for COVID-19. METHODS: We performed a retrospective cohort study of patients with COVID-19 admitted to five United States hospitals from March to December 2020. We used multivariable logistic regression to identify patient characteristics associated with short hospital length-of-stay. RESULTS: Of 3103 patients, 648 (20.9%) were hospitalized for less than 48 h. These patients were significantly less likely to have an age greater than 60, diabetes, chronic kidney disease; emergency department vital sign abnormalities, or abnormal initial diagnostic testing. For patients with no significant risk factors, the adjusted probability of short-stay hospitalization was 62.4% (95% CI 58.9-69.6). CONCLUSION: Identification of candidates for early hospital discharge may allow hospitals to streamline throughput using protocols that optimize the efficiency of hospital care and coordinate post-discharge monitoring.

Tackling the unknowns in understanding and management of hospital acquired anemia.

Hospital acquired anemia (HAA) has been a recognized entity for nearly 50 years. Despite multiple hypotheses, a mechanistic understanding is lacking, and targeted interventions have not yet yielded significantly impactful results. Known risk factors include advanced age, multiple co-morbidities, low bone marrow reserve, admission to the intensive care unit, and frequent phlebotomy. However, confounding variables in many studies continues to complicate the identification of additional risk factors. Improved understanding of iron metabolism, erythropoiesis, and the erythroid iron restriction response in the last few decades, as well as the recent demonstration of poor outcomes correlating with increased transfusion have refocused attention on HAA. While retrospective database studies provide ample correlative data between 1) HAA and poor outcomes; 2) reduction of phlebotomy volume and decrease in transfusion requirement; and 3) over-transfusion and increased mortality, no causal link between reduced phlebotomy volume, decreased rates of HAA, and improved mortality or other relevant outcomes have been definitely established. Here, we review the current state of knowledge and provide a summary of potential directions to understand and mitigate HAA. There are at present no clear guidelines on whether and when to evaluate hospitalized patients for underlying causes of anemia. We thus provide a guide for clinicians in general practice toward identifying patients at the highest risk for HAA, decreasing blood loss through phlebotomy to the greatest degree feasible, and evaluating and treating reversible causes of anemia in a targeted population.

Trends in Outpatient Care and Use of Telemedicine After Hospital Discharge in a Large Commercially Insured Population.

This cross-sectional study examines changes in use of telemedicine vs in-person care among a commercially insured population durring the COVID-19 pandemic.

Severity of illness and the weekend mortality effect: a retrospective cohort study.

BACKGROUND: Weekend admission to the hospital has been found to be associated with higher in-hospital mortality rates, but the cause for this phenomenon remains controversial. US based studies have been limited in their characterization of the weekend patient population, making it difficult to draw conclusions about the implications of this effect. METHODS: A retrospective cohort study, examining de-identified, patient level data from 2015 to 2017 at US academic medical centers submitting data to the Vizient database, comparing demographic and clinical risk profiles, as well as mortality, cost and length of stay, between weekend and weekday patient populations. Between-group differences in mortality were assessed using the chi-square test for categorical measures and Wilcoxon rank-sum test for continuous measures. Logistic regression models were used to test the multivariate association of weekend admission and other patient-level factors with death, LOS, etc. RESULTS: We analyzed 10,365,605 adult inpatient encounters. Within the weekend patient population, 30.6% of patients were categorized as having either a major or extreme risk of mortality on admission, as compared to 23.7% on weekdays (p < 0.001). We found a significantly increased unadjusted mortality rate associated with weekend admission (OR 1.46; 95% CI 1.45-1.47) which was substantially attenuated after adjusting for disease severity and other demographic covariates, though remained significant (OR 1.05; 95% CI 1.04-1.06). In the subgroup of non-elective admissions, the unadjusted OR for death was 1.14 (95% CI 1.13-1.15), and the adjusted OR was 1.04 (95% CI 1.03-1.05). Weekend admission was associated with a longer median LOS (4 vs 3 days in the weekday group; p < 0.01), but a lower median cost ($8224 vs $9999 dollars in the weekday group; p < 0.01). CONCLUSION: The patient population admitted on weekends is proportionally higher risk than the population admitted on weekdays, and the observed weekend mortality effect is largely attributable to this risk imbalance.

Corrigendum to "Community-Acquired Cavitary Pseudomonas Pneumonia Linked to Use of a Home Humidifier".

[This corrects the article DOI: 10.1155/2017/5474916.].

Community-Acquired Cavitary Pseudomonas Pneumonia Linked to Use of a Home Humidifier.

Pseudomonas aeruginosa is an opportunistic pathogen that rarely causes pneumonia in otherwise healthy patients. We describe a case of community-acquired P. aeruginosa pneumonia in a previously healthy individual who likely acquired the infection from a home humidifier.