The Impact of a Machine Learning Early Warning Score on Hospital Mortality: A Multicenter Clinical Intervention Trial.

OBJECTIVES: To determine the impact of a machine learning early warning risk score, electronic Cardiac Arrest Risk Triage (eCART), on mortality for elevated-risk adult inpatients. DESIGN: A pragmatic pre- and post-intervention study conducted over the same 10-month period in 2 consecutive years. SETTING: Four-hospital community-academic health system. PATIENTS: All adult patients admitted to a medical-surgical ward. INTERVENTIONS: During the baseline period, clinicians were blinded to eCART scores. During the intervention period, scores were presented to providers. Scores greater than or equal to 95th percentile were designated high risk prompting a physician assessment for ICU admission. Scores between the 89th and 95th percentiles were designated intermediate risk, triggering a nurse-directed workflow that included measuring vital signs every 2 hours and contacting a physician to review the treatment plan. MEASUREMENTS AND MAIN RESULTS: The primary outcome was all-cause inhospital mortality. Secondary measures included vital sign assessment within 2 hours, ICU transfer rate, and time to ICU transfer. A total of 60,261 patients were admitted during the study period, of which 6,681 (11.1%) met inclusion criteria (baseline period n = 3,191, intervention period n = 3,490). The intervention period was associated with a significant decrease in hospital mortality for the main cohort (8.8% vs 13.9%; p < 0.0001; adjusted odds ratio [OR], 0.60 [95% CI, 0.52-0.71]). A significant decrease in mortality was also seen for the average-risk cohort not subject to the intervention (0.49% vs 0.26%; p < 0.05; adjusted OR, 0.53 [95% CI, 0.41-0.74]). In subgroup analysis, the benefit was seen in both high- (17.9% vs 23.9%; p = 0.001) and intermediate-risk (2.0% vs 4.0 %; p = 0.005) patients. The intervention period was also associated with a significant increase in ICU transfers, decrease in time to ICU transfer, and increase in vital sign reassessment within 2 hours. CONCLUSIONS: Implementation of a machine learning early warning score-driven protocol was associated with reduced inhospital mortality, likely driven by earlier and more frequent ICU transfer.

Who Signs Up for and Engages in a Peer Support Heart Failure Self-management Intervention.

BACKGROUND: Many programs for patients with heart failure (HF) fail to improve clinical outcomes in part because of low rates of patient enrollment and engagement. A better understanding of patient characteristics associated with willingness to enroll and then engage in HF self-management programs will improve the design and targeting of programs. METHODS AND RESULTS: Analyses of screening, baseline, and engagement data from a randomized controlled effectiveness trial of an HF peer self-management support program were conducted. The median age of the 266 recently hospitalized HF patients who enrolled in the study was 69 years, 51% were female, and 26% were minorities (primarily African American). Of 135 randomized to the peer support intervention, only 39% engaged in either the group sessions or telephone peer support calls. Older white women who reported higher baseline health status, functioning, social support, and confidence in their ability to manage and less difficulty with the physical and emotional aspects of living with HF were the most likely to engage in program activities. Minority status and reporting a need for social support were both correlated with higher enrollment but lower engagement in the intervention. CONCLUSIONS: Although minority patients with poorer reported health status and social support were most likely to consent to participate in the study, participants who engaged in program activities were more likely to have higher baseline health status, functioning, and social support. Developing HF interventions that successfully engage participants most in need of HF self-management support remains a difficult challenge.

Project BOOST implementation: lessons learned.

OBJECTIVES: Enhancing care coordination and reducing hospital readmissions have been a focus of multiple quality improvement (QI) initiatives. Project BOOST (Better Outcomes by Optimizing Safe Transitions) aims to enhance the discharge transition from hospital to home. Previous research indicates that QI initiatives originating externally often face difficulties gaining momentum or effecting lasting change in a hospital. We performed a qualitative evaluation of Project BOOST implementation by examining the successes and failures experienced by six pilot sites. We also evaluated the unique physician mentoring component of this program. Finally, we examined the impact of intensification of the physician mentoring model on adoption of BOOST interventions in two later Illinois cohorts (27 hospitals). METHODS: Qualitative analysis of six pilot hospitals used a process of methodological triangulation and analysis of the BOOST enrollment applications, the listserv, and content from telephone interviews. Evaluation of BOOST implementation at Illinois hospitals occurred via mid-year and year-end surveys. RESULTS: The identified common barriers included inadequate understanding of the current discharge process, insufficient administrative support, lack of protected time or dedicated resources, and lack of frontline staff buy-in. Facilitators of implementation included the mentor, a small beginning, teamwork, and proactive engagement of the patient. Notably, hospitals viewed their mentors as essential facilitators of change. Sites consistently commented that the individualized mentoring was extremely helpful and provided significant accountability and stimulated creativity. In the Illinois cohorts, the improved mentoring model showed more complete implementation of BOOST interventions. CONCLUSIONS: The implementation of Project BOOST was well received by hospitals, although sites faced substantial barriers consistent with other QI research reports. The unique mentorship element of Project BOOST proved extremely valuable in helping sites overcome their distinctive challenges and identify facilitators for success. The findings from this qualitative study should contribute to future BOOST implementation success and others' efforts to optimize hospital discharge transitions.

Magnetic resonance imaging screening to identify spinal and paraspinal infections associated with injections of contaminated methylprednisolone acetate.

IMPORTANCE: Injection of contaminated methylprednisolone has resulted in an unprecedented nationwide outbreak of Exserohilum rostratum fungal infections, manifested initially as meningitis and/or basilar stroke. Insidious onset of spinal or paraspinal infection at the injection site has been increasingly reported and is occurring months after receipt of injection with the contaminated drug. The clinical findings are often subtle and similar to those that led the patient to undergo the methylprednisolone injection. OBJECTIVE: To determine if patients who had not presented for medical care but who had received contaminated methylprednisolone developed spinal or paraspinal infection at the injection site using contrast-enhanced magnetic resonance imaging (MRI) screening. DESIGN, SETTING, AND PARTICIPANTS: There were 172 patients who had received an injection of contaminated methylprednisolone from a highly contaminated lot (No. 06292012@26) at a pain facility but had not presented for medical care related to adverse effects after the injection. Screening MRI was performed between November 9, 2012, and April 30, 2013. MAIN OUTCOMES AND MEASURES: Number of persons identified with previously undiagnosed spinal or paraspinal infection. RESULTS: Of the 172 patients screened, MRI was abnormal in 36 (21%), showing epidural or paraspinal abscess or phlegmon, arachnoiditis, spinal osteomyelitis or diskitis, or moderate to severe epidural, paraspinal, or intradural enhancement. Of the 115 patients asked about new or worsening back or neck pain, lower extremity weakness, or radiculopathy symptoms, 35 (30%) had at least 1 symptom. Thirty-five of the 36 patients with abnormal MRIs met the Centers for Disease Control and Prevention (CDC) case definition for probable (17 patients) or confirmed (18 patients) fungal spinal or paraspinal infection. All 35 patients were treated with antifungal agents (voriconazole, with or without liposomal amphotericin B), and 24 required surgical debridement. At the time of surgery, 17 of 24 patients (71%), including 5 patients who denied having symptoms, had laboratory evidence of fungal infection. CONCLUSIONS AND RELEVANCE: Among patients who underwent screening MRI to look for infection at the site of injection of contaminated methylprednisolone, 21% had an abnormal MRI, and all but one met CDC criteria for probable or confirmed fungal spinal or paraspinal infection. Screening MRI led to identification of patients who had minimal or no symptoms of spinal or paraspinal infection and allowed early initiation of medical and surgical treatment.

Continuous Remote Patient Monitoring in Patients With Heart Failure (Cascade Study): Protocol for a Mixed Methods Feasibility Study.

BACKGROUND: Heart failure (HF) is a prevalent chronic disease and is associated with increases in mortality and morbidity. HF is a leading cause of hospitalizations and readmissions in the United States. A potentially promising area for preventing HF readmissions is continuous remote patient monitoring (CRPM). OBJECTIVE: The primary aim of this study is to determine the feasibility and preliminary efficacy of a CRPM solution in patients with HF at NorthShore University HealthSystem. METHODS: This study is a feasibility study and uses a wearable biosensor to continuously remotely monitor patients with HF for 30 days after discharge. Eligible patients admitted with an HF exacerbation at NorthShore University HealthSystem are being recruited, and the wearable biosensor is placed before discharge. The biosensor collects physiological ambulatory data, which are analyzed for signs of patient deterioration. Participants are also completing a daily survey through a dedicated study smartphone. If prespecified criteria from the physiological data and survey results are met, a notification is triggered, and a predetermined electronic health record-based pathway of telephonic management is completed. In phase 1, which has already been completed, 5 patients were enrolled and monitored for 30 days after discharge. The results of phase 1 were analyzed, and modifications to the program were made to optimize it. After analysis of the phase 1 results, 15 patients are being enrolled for phase 2, which is a calibration and testing period to enable further adjustments to be made. After phase 2, we will enroll 45 patients for phase 3. The combined results of phases 1, 2, and 3 will be analyzed to determine the feasibility of a CRPM program in patients with HF. Semistructured interviews are being conducted with key stakeholders, including patients, and these results will be analyzed using the affective adaptation of the technology acceptance model. RESULTS: During phase 1, of the 5 patients, 2 (40%) were readmitted during the study period. The study completion rate for phase 1 was 80% (4/5), and the study attrition rate was 20% (1/5). There were 57 protocol deviations out of 150 patient days in phase 1 of the study. The results of phase 1 were analyzed, and the study protocol was adjusted to optimize it for phases 2 and 3. Phase 2 and phase 3 results will be available by the end of 2022. CONCLUSIONS: A CRPM program may offer a low-risk solution to improve care of patients with HF after hospital discharge and may help to decrease readmission of patients with HF to the hospital. This protocol may also lay the groundwork for the use of CRPM solutions in other groups of patients considered to be at high risk. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/36741.

An operationally implementable model for predicting the effects of an infectious disease on a comprehensive regional healthcare system.

An operationally implementable predictive model has been developed to forecast the number of COVID-19 infections in the patient population, hospital floor and ICU censuses, ventilator and related supply chain demand. The model is intended for clinical, operational, financial and supply chain leaders and executives of a comprehensive healthcare system responsible for making decisions that depend on epidemiological contingencies. This paper describes the model that was implemented at NorthShore University HealthSystem and is applicable to any communicable disease whose risk of reinfection for the duration of the pandemic is negligible.

Safe Transitions and Congregate Living in the Age of COVID-19: A Retrospective Cohort Study.

BACKGROUND: COVID-19 represents a grave risk to residents in skilled nursing facilities (SNFs). OBJECTIVE: To determine whether establishment of an appropriate-use committee was associated with a reduction in SNF utilization. DESIGNS, SETTING, AND PARTICIPANTS: Retrospective cohort study at NorthShore University HealthSystem, a multihospital integrated health system in northern Illinois. Participants were patients hospitalized from March 19, 2019, to July 16, 2020. INTERVENTION: Creation of a multidisciplinary committee to assess appropriateness of discharge to SNF following hospitalization. MAIN OUTCOME AND MEASURES: Primary outcome was total discharges to SNFs. Secondary outcomes were new discharges to SNFs, readmissions, length of stay (LOS), and COVID-19 incidence following discharge. RESULTS: Matched populations pre and post intervention were each 4424 patients. Post intervention, there was a relative reduction in total SNF discharges of 49.7% (odds ratio [OR], 0.42; 95% CI, 0.38-0.47) and in new SNF discharges of 66.9% (OR, 0.29; 95% CI, 0.25-0.34). Differences in readmissions and LOS were not statistically significant. For patients discharged to a SNF, 2.99% (95% CI, 1.59%-4.39%) developed COVID-19 within 30 days, compared with 0.26% (95% CI, 0.29%-0.93%) of patients discharged to other settings (P < .001). CONCLUSION: Implementing a review committee to assess for appropriateness of SNF use after a hospitalization during the COVID-19 pandemic is highly effective. There was no negative impact on safety or efficiency of hospital care, and reduced SNF use likely prevented several cases of COVID-19. This model could serve as a template for other hospitals to reduce the risks of COVID-19 in SNFs and as part of a value-based care strategy.

Continuous Remote Patient Monitoring: Evaluation of the Heart Failure Cascade Soft Launch.

OBJECTIVE: We report on our experience of deploying a continuous remote patient monitoring (CRPM) study soft launch with structured cascading and escalation pathways on heart failure (HF) patients post-discharge. The lessons learned from the soft launch are used to modify and fine-tune the workflow process and study protocol. METHODS: This soft launch was conducted at NorthShore University HealthSystem's Evanston Hospital from December 2020 to March 2021. Patients were provided with non-invasive wearable biosensors that continuously collect ambulatory physiological data, and a study phone that collects patient-reported outcomes. The physiological data are analyzed by machine learning algorithms, potentially identifying physiological perturbation in HF patients. Alerts from this algorithm may be cascaded with other patient status data to inform home health nurses' (HHNs') management via a structured protocol. HHNs review the monitoring platform daily. If the patient's status meets specific criteria, HHNs perform assessments and escalate patient cases to the HF team for further guidance on early intervention. RESULTS: We enrolled five patients into the soft launch. Four participants adhered to study activities. Two out of five patients were readmitted, one due to HF, one due to infection. Observed miscommunication and protocol gaps were noted for protocol amendment. The study team adopted an organizational development method from change management theory to reconfigure the study protocol. CONCLUSION: We sought to automate the monitoring aspects of post-discharge care by aligning a new technology that generates streaming data from a wearable device with a complex, multi-provider workflow into a novel protocol using iterative design, implementation, and evaluation methods to monitor post-discharge HF patients. CRPM with structured escalation and telemonitoring protocol shows potential to maintain patients in their home environment and reduce HF-related readmissions. Our results suggest that further education to engage and empower frontline workers using advanced technology is essential to scale up the approach.

Making inpatient medication reconciliation patient centered, clinically relevant, and implementable: a consensus statement on key principles and necessary first steps.

This white paper identifies potential solutions to help ensure the utility and sustainability of this critical patient safety issue.

Clinical Analytics Prediction Engine (CAPE): Development, electronic health record integration and prospective validation of hospital mortality, 180-day mortality and 30-day readmission risk prediction models.

BACKGROUND: Numerous predictive models in the literature stratify patients by risk of mortality and readmission. Few prediction models have been developed to optimize impact while sustaining sufficient performance. OBJECTIVE: We aimed to derive models for hospital mortality, 180-day mortality and 30-day readmission, implement these models within our electronic health record and prospectively validate these models for use across an entire health system. MATERIALS & METHODS: We developed, integrated into our electronic health record and prospectively validated three predictive models using logistic regression from data collected from patients 18 to 99 years old who had an inpatient or observation admission at NorthShore University HealthSystem, a four-hospital integrated system in the United States, from January 2012 to September 2018. We analyzed the area under the receiver operating characteristic curve (AUC) for model performance. RESULTS: Models were derived and validated at three time points: retrospective, prospective at discharge, and prospective at 4 hours after presentation. AUCs of hospital mortality were 0.91, 0.89 and 0.77, respectively. AUCs for 30-day readmission were 0.71, 0.71 and 0.69, respectively. 180-day mortality models were only retrospectively validated with an AUC of 0.85. DISCUSSION: We were able to retain good model performance while optimizing potential model impact by also valuing model derivation efficiency, usability, sensitivity, generalizability and ability to prescribe timely interventions to reduce underlying risk. Measuring model impact by tying prediction models to interventions that are then rapidly tested will establish a path for meaningful clinical improvement and implementation.

Evidence-based interventions to improve the palliative care of pain, dyspnea, and depression at the end of life: a clinical practice guideline from the American College of Physicians.

RECOMMENDATION 1: In patients with serious illness at the end of life, clinicians should regularly assess patients for pain, dyspnea, and depression. (Grade: strong recommendation, moderate quality of evidence.) RECOMMENDATION 2: In patients with serious illness at the end of life, clinicians should use therapies of proven effectiveness to manage pain. For patients with cancer, this includes nonsteroidal anti-inflammatory drugs, opioids, and bisphosphonates. (Grade: strong recommendation, moderate quality of evidence.) RECOMMENDATION 3: In patients with serious illness at the end of life, clinicians should use therapies of proven effectiveness to manage dyspnea, which include opioids in patients with unrelieved dyspnea and oxygen for short-term relief of hypoxemia. (Grade: strong recommendation, moderate quality of evidence.) RECOMMENDATION 4: In patients with serious illness at the end of life, clinicians should use therapies of proven effectiveness to manage depression. For patients with cancer, this includes tricyclic antidepressants, selective serotonin reuptake inhibitors, or psychosocial intervention. (Grade: strong recommendation, moderate quality of evidence.) RECOMMENDATION 5: Clinicians should ensure that advance care planning, including completion of advance directives, occurs for all patients with serious illness. (Grade: strong recommendation, low quality of evidence.).

COVID-19 Vaccination and Parent-Reported Symptomatic Child Asthma Prevalence.

This cross-sectional study evaluates the association between COVID-19 vaccination and symptomatic child asthma.

How do hospitalized patients feel about resident work hours, fatigue, and discontinuity of care?

BACKGROUND: Patient-centered care requires that physicians understand patients' perspectives. Since the resident work hour rules were instituted, little information is available about how patients perceive these issues. Our objectives were to explore patients' knowledge, concerns, and attitudes about resident work hours, fatigue, and continuity of inpatient care and to evaluate the association between patients' trust and satisfaction with these concerns and attitudes. METHODS: We conducted a cross-sectional survey of 134 internal medicine inpatients at 3 institutions including a tertiary care academic health center, a Veterans Affairs medical center, and a private community teaching hospital. RESULTS: Mean age was 59 (range, 24-90), with 60% men and 70% white. Most patients agreed (50%) or felt neutral (38%) toward resident work hours being limited. Patients estimated that residents worked 60 h per week but thought that they should work no more than 51 h per week (p < .01 for the difference). Twenty-seven percent of patients had some concern about fatigue in the residents, and 28% reported concern about how often hand-offs of care occurred. Factor analysis yielded 3 factors: "worried about discontinuity/fatigue," "attitude toward resident/nurse work hours," and "perceived resident/nurse fatigue." In multivariable analyses, the "worried about fatigue/discontinuity" factor significantly predicted trust and satisfaction, and the "perceived resident/nurse fatigue" factor also predicted satisfaction. CONCLUSIONS: Some inpatients are concerned about both fatigue in resident physicians and discontinuity of care. This may play a role in trust and satisfaction for patients. Taking steps to design systems to minimize fatigue and discontinuity would be ideal.

Increases in Medicare prescription drug plan costs attributable to psychotropic medications.

OBJECTIVE: Older patients may regard some medications, particularly psychotropic medications, as discretionary compared with what they perceive as more "essential " nonpsychiatric medications. Patients' concerns about psychotropic medication costs under Medicare Part D may reinforce these impressions. DESIGN: The authors examined which Medicare prescription drug plans (PDPs) would be least expensive for beneficiaries considering the costs of 1) all medications; and 2) only nonpsychiatric medications. SETTING: The authors collected data from the PDP online comparison tool provided by the Centers for Medicare and Medicaid Services (CMS). PARTICIPANTS: Hypothetical Medicare beneficiaries. MEASUREMENTS: The authors examined four clinical scenarios from older outpatients with both chronic medical and psychiatric conditions (including psychosis, bipolar disorder, depression, and dementia with behavioral disturbances). RESULTS: The authors examined data from all 160 plans available in CMS PDP regions in May 2007. There were frequent discrepancies in the least expensive PDPs within region, depending on considering the costs of all medications, or just nonpsychiatric medications. In the clinical scenarios, patients selecting a PDP based on nonpsychiatric medications alone would pick an unnecessarily more expensive plan 74%-100% of the time (when they took any brand name medication), suggesting that excluding psychiatric medications from PDP choices may be excessively costly. However, brand name psychotropic medications significantly increased the costs of the least expensive plans. The latter finding might persuade patients to avoid taking needed psychiatric medication due to cost. CONCLUSION: This research highlights the complexity that patients with psychiatric and cognitive disorders face when choosing a Medicare PDP. Policymakers and clinicians should be aware of the tradeoffs that beneficiaries with psychiatric disorders face when making PDP plan choices.

Organizational structure for addressing the attributes of the ideal healthcare delivery system.

The Institute of Medicine's (IOM) report Crossing the Quality Chasm described the aims, characteristics, and components of the ideal healthcare system but did not provide the templates of organizational structures needed to achieve this vision. In this article, we review three principles of effective organizations to inform the design of a facilitative clinical care structure: a focus on the patient and caregiving team, the use of information, and connectivity with executive and operational leadership. These concepts can be realized in an organizational chart that is inverted to place patients and their care providers on top, flat with few degrees of separation between patients and executive leadership, and webbed to reflect connections to the professional and ancillary departments. An example of a recently implemented clinical care infrastructure follows this discussion. This model divides the patient population into nonexclusive subgroups, each with an interdisciplinary collaborative practice team that oversees and advocates the subgroup's clinical care activities. The organization's interdisciplinary practice council, in conjunction with its physician and nursing practice councils, backs these teams, providing a second layer of support. The council layer is connected to the health system board through the clinical oversight group, whose core membership consists of council chairs, the chief executive officer, and the chief medical and nursing officers. Clinical information for planning and evaluation is available at all levels. This model provides a framework for identifying the individuals and processes necessary to achieve IOM's vision.

Variation in estimated Medicare prescription drug plan costs and affordability for beneficiaries living in different states.

BACKGROUND: Medicare Part D prescription drug plans (PDPs) implemented in January 2006 are designed to improve beneficiaries' access to pharmaceuticals and use market competition to yield affordable drug costs. Variations in estimated PDP costs for beneficiaries living in different states have not previously been characterized. OBJECTIVE: To describe variations in the estimated costs of PDPs (plan premium, copays, and coinsurance) within and across states. DESIGN: To estimate PDP costs based on 4 actual patient cases that exemplify common conditions and prescription drug combinations for Medicare beneficiaries, we used the online tool provided by the Centers for Medicare and Medicaid Services. MEASUREMENTS: Principal study outcomes included (a) variation across states in the estimated annual cost of the lowest-cost PDP for each case and (b) variation in the estimated affordability of the lowest-cost PDPs across states, based on cost-of-living-adjusted median income for zero-earner households. RESULTS: For all 4 patient cases, we found substantive within-state and between-state differences in the estimated costs of Medicare PDPs incurred by beneficiaries. The estimated annual costs to beneficiaries of the lowest-cost PDPs varied across states by as much as $320 for medications in the least expensive scenario, and by as much as $13,000 for the most expensive scenario. On average across states, a beneficiary with cost-of-living-adjusted median income would expect to spend 3%-28% of annual income to pay for medications in the lowest-cost PDPs in the 4 patient cases. The affordability of the lowest-cost plans varied across states, and for 2 of the 4 cases the lowest-cost PDP estimates were negatively correlated with cost-of-living-adjusted median income. CONCLUSIONS: Substantive differences in estimated PDP costs are evident across states for patients with common Medicare conditions. Importantly, the lowest-cost plans were not proportionally affordable with respect to state-specific cost-of-living-adjusted median income. Refinement of the Medicare drug program may be needed to improve national balance in PDP affordability for beneficiaries living in different states.

"I am not alone": the feasibility and acceptability of interactive voice response-facilitated telephone peer support among older adults with heart failure.

Patient self-management is a critical determinant of heart failure (HF) outcomes, yet patients with HF are often frail and socially isolated, factors that may limit their ability to manage self-care and access clinic-based services. Mobilizing peer support among HF patients is a promising strategy to improve self-management support. In this pilot, the authors evaluated the feasibility and acceptability of an interactive voice response (IVR)-based platform to facilitate telephone peer support among older adults with HF. Participants completed a baseline survey, were offered a 3-hour training session in peer communication skills, and were paired with another patient who had HF. Participants were asked to contact their partner weekly using a toll-free IVR phone system that protected their anonymity and provided automated reminders if contacts were not made. Times and duration of participants' telephone contacts were monitored and recorded. After the 7-week intervention, participants completed surveys and brief face-to-face interviews. The authors found high levels of use and satisfaction and improvements in depressive symptoms among the 20 pilot study participants. An IVR peer-support intervention is feasible, is acceptable to patients, and may have positive effects on patients' HF social support and health outcomes, in conjunction with structured health system support, that warrant more rigorous evaluation in a randomized trial.

A comparison of two hospitalist models with traditional care in a community teaching hospital.

PURPOSE: Many studies have documented significant length of stay reduction and cost savings when hospitalist care is compared with traditional care. However, less is known about the concurrent performance of more than one hospitalist model in a single site. SUBJECTS AND METHODS: This retrospective cohort study of 10595 patients was conducted between July 2001 and June 2002 in a tertiary care community-based teaching hospital. Risk-adjusted length of stay, variable costs, 30-day readmission rates, and in-hospital and 30-day mortality were measured for patients treated by Community Physicians, Private Hospitalists and Academic Hospitalists. RESULTS: There was a 20% reduction in length of stay on the Academic Hospitalist service (p <.0001) and 8% on the Private Hospitalist service (P = .049) compared with Community Physicians. Similarly, total costs were 10% less on the Academic (P <.0001) and 6% less on the Private Hospitalist (P = .02) services compared with Community Physicians. The length of stay of Academic Hospitalists was 13% shorter than that of Private Hospitalists (P = .002); differences in costs between hospitalist groups were not statistically significant. Differences in in-hospital and 30-day mortality and 30-day readmission rates among the 3 physician groups were also not statistically significant. CONCLUSIONS: The impact on patient outcomes and resource utilization may vary with the hospitalist model used. Future studies should examine the specific organizational characteristics of hospitalists that contribute to improved patient care and resource utilization.

Provider response to different formats of the adult immunization schedule.

BACKGROUND: Providers' failure to administer vaccines in accordance with established recommendations is a well-recognized barrier to national immunization efforts. This study evaluated the ease of use of two different formats of the Centers for Disease Control and Prevention's (CDC) adult immunization schedule by physicians in private practice, where the majority of adult immunizations are administered. METHODS: A series of focus groups was conducted with 94 physicians and other clinical staff in 11 private practices (family medicine and internal medicine) in six U.S. cities. Each session was based on a structured set of questions that explored barriers to adult immunizations, followed by three mock clinical scenarios to examine how each of two graphical depictions of the 2003-2004 adult immunization schedule (one from the CDC's Advisory Committee on Immunization Practices, and the other from the Immunization Action Coalition) might facilitate assessments of recommended immunizations. Group dialogue and individual participants' written responses to the scenarios and the alternate schedule formats were analyzed. RESULTS: Providers perceived multiple barriers to adult immunization independent of immunization schedule formats, chiefly patients' low interest in immunization and refusal of vaccines. Most participants were not familiar with either format of CDC's adult immunization schedule before the study, but quickly developed strong preferences for one versus the other (usually the second format that they encountered). About half of the providers changed their vaccine recommendations for clinical scenarios when they consulted either schedule format, although some of the changes were not clinically appropriate. Participants suggested several ways to enhance the availability of the information contained in the schedule formats, especially through electronic means. CONCLUSIONS: This qualitative study suggests ways in which graphic depictions of an adult immunization schedule may address adult immunization barriers. Greater provider familiarity with schedule formats will be critical to their appropriate application in clinical encounters.