Previous studies of hospital readmission have focused on specific conditions or populations and generated complex prediction models. To identify predictors of early hospital readmission in a diverse patient population and derive and validate a simple model for identifying patients at high readmission risk. Prospective observational cohort study. Participants encompassed 10,946 patients discharged home from general medicine services at six academic medical centers and were randomly divided into derivation (n = 7,287) and validation (n = 3,659) cohorts. We identified readmissions from administrative data and 30-day post-discharge telephone follow-up. Patient-level factors were grouped into four categories: sociodemographic factors, social support, health condition, and healthcare utilization. We performed logistic regression analysis to identify significant predictors of unplanned readmission within 30 days of discharge and developed a scoring system for estimating readmission risk. Approximately 17.5% of patients were readmitted in each cohort. Among patients in the derivation cohort, seven factors emerged as significant predictors of early readmission: insurance status, marital status, having a regular physician, Charlson comorbidity index, SF12 physical component score, ≥1 admission(s) within the last year, and current length of stay >2 days. A cumulative risk score of ≥25 points identified 5% of patients with a readmission risk of approximately 30% in each cohort. Model discrimination was fair with a c-statistic of 0.65 and 0.61 for the derivation and validation cohorts, respectively. Select patient characteristics easily available shortly after admission can be used to identify a subset of patients at elevated risk of early readmission. This information may guide the efficient use of interventions to prevent readmission.

Background

Patients admitted to general medicine inpatient services are increasingly cared for by hospital-based physicians rather than their primary care providers (PCPs). This separation of hospital and ambulatory care may result in important care discontinuities after discharge. We sought to determine whether communication between hospital-based physicians and PCPs influences patient outcomes.

Methods

We approached consecutive patients admitted to general medicine services at six US academic centers from July 2001 to June 2003. A random sample of the PCPs for consented patients was contacted 2 weeks after patient discharge and surveyed about communication with the hospital medical team. Responses were linked with the 30-day composite patient outcomes of mortality, hospital readmission, and emergency department (ED) visits obtained through follow-up telephone survey and National Death Index search. We used hierarchical multi-variable logistic regression to model whether communication with the patient's PCP was associated with the 30-day composite outcome.

Results

A total of 1,772 PCPs for 2,336 patients were surveyed with 908 PCPs responses and complete patient follow-up available for 1,078 patients. The PCPs for 834 patients (77%) were aware that their patient had been admitted to the hospital. Of these, direct communication between PCPs and inpatient physicians took place for 194 patients (23%), and a discharge summary was available within 2 weeks of discharge for 347 patients (42%). Within 30 days of discharge, 233 (22%) patients died, were readmitted to the hospital, or visited an ED. In adjusted analyses, no relationship was seen between the composite outcome and direct physician communication (adjusted odds ratio 0.87, 95% confidence interval 0.56 - 1.34), the presence of a discharge summary (0.84, 95% CI 0.57-1.22), or PCP awareness of the index hospitalization (1.08, 95% CI 0.73-1.59).

Conclusion

Analysis of communication between PCPs and inpatient medical teams revealed much room for improvement. Although communication during handoffs of care is important, we were not able to find a relationship between several aspects of communication and associated adverse clinical outcomes in this multi-center patient sample.

Background

In patients hospitalized with community-acquired pneumonia (CAP), indicators of clinical instability at discharge (fever, tachycardia, tachypnea, hypotension, hypoxia, decreased oral intake and altered mental status) are associated with poor outcomes. It is not known whether the order of indicator stabilization is associated with outcomes.

Objectives

To describe variation in the sequences, including whether and in what order, indicators of clinical instability resolve among patients hospitalized with CAP, and to assess associations between patterns of stabilization and patient-level outcomes. DESIGN/PARTICIPANTS / MAIN MEASURES: Chart review ascertained whether and when indicators stabilized and other data for 1,326 adult CAP patients in six U.S. academic medical centers. The sequences of indicator stabilization were characterized using sequence analysis and grouped using cluster analysis. Associations between sequence patterns and 30-day mortality, length of stay (LOS), and total costs were modeled using regression analysis.

Key results

We found 986 unique sequences of indicator stabilization. Sequence analysis identified eight clusters of sequences (patterns) derived by the order or speed in which instabilities resolved or remained at discharge and inpatient mortality. Two of the clusters (56% of patients) were characterized by almost complete stabilization prior to discharge alive, but differing in the rank orders of four indicators and time to maximum stabilization. Five other clusters (42% of patients) were characterized by one to three instabilities at discharge with variable orderings of indicator stabilization. In models with fast and almost complete stabilization as the referent, 30-day mortality was lowest in clusters with slow and almost complete stabilization or tachycardia or fever at discharge [OR = 0.73, 95% CI = (0.28-1.92)], and highest in those with hypoxia with instabilities in mental status or oral intake at discharge [OR = 3.99, 95% CI = (1.68-9.50)].

Conclusions

Sequences of clinical instability resolution exhibit great heterogeneity, yet certain sequence patterns may be associated with differences in days to maximum stabilization, mortality, LOS, and hospital costs.

Although generic oral contraceptives (OCPs) can improve adherence and reduce health care expenditures, use of generic OCPs remains low, and the factors that affect generic prescribing are not well understood. We aimed to understand the barriers and facilitators of generic OCP prescribing and potential solutions to increase generic OCP prescribing, as well as pilot an educational module to address clinician misconceptions about generic OCPs. We developed focus group scripts using the 4D model of appreciative inquiry. A total of four focus groups occurred, two at the American Association of Nurse Practitioners (AANP) national conference and two at the American College of Physicians (ACP) Internal Medicine meeting. Focus group transcripts were analyzed using a constant comparative method with no a priori hypothesis to generate emerging and reoccurring themes. Findings from these focus groups were used to develop an educational module promoting generic OCP prescribing. Participants were recruited from the AANP Network for Research and the ACP Research Panel. This study demonstrates that health system factors, workflow factors, clinician factors, and patient factors were the main barriers to and facilitators of generic OCP prescribing. Nurse practitioners were responsive to an educational module and reported increased willingness to discuss and prescribe generic OCPs after completing the module. Interventions to increase generic OCP prescribing must address clinician and patient factors within the context of workflow and larger health system factors.

Importance

As prescription drug costs rise, it is important to understand attitudes among primary care physicians and nurse practitioners (NPs) towards generic drugs.

Objective

We aimed to examine the generic skepticism index (GSI) among primary care clinicians, and their willingness to discuss and prescribe generic antidepressants (ADs) and generic oral contraceptives (OCPs).

Design

We used a factorial vignette design survey to test 4 factors: message source, message, brand preference, and drug class. Participants were randomized to different combinations of factors.

Setting

This was a cross-sectional study.

Participants

Physicians registered with the American College of Physicians (ACP) and NPs registered with the American Association of Nurse Practitioners (AANP) participated in the study.

Main measures

The primary outcomes were generic skepticism as measured using the generic skepticism index (GSI), and clinician willingness to discuss and prescribe generics.

Results

Surveys were completed by 56% of physicians (n = 369/661) and 60% of NPs (n = 493/819). Compared with physicians, NPs were younger (p < 0.001), predominantly female (p < 0.001), and differed in the race (p < 0.001). According to the GSI, 16% (n = 138/862) were identified as generic skeptics (18.5% of NPs and 12.7% of physicians, p = 0.023). Generic skeptics had lower odds of willingness to discuss switching (OR 0.22, 95% CI (0.14-0.35), p < 0.001) or prescribe (OR 0.18, 95% CI (0.11-0.28), p < 0.001) generic OCPs. Participants had lower odds of willingness to prescribe generic drugs to patients with brand preference compared with brand-neutral patients (OR 0.64, 95% CI 0.50-0.82, p < 0.001).

Conclusions and relevance

Generic skepticism was associated with lower willingness to discuss or prescribe generic drugs. Clinicians reported lower willingness to discuss switching or prescribe generics for OCPs than for ADs. Patient brand preference hindered generic prescribing. Message source and message type were not significantly associated with outcomes.

While great interest in health effects of natural product (NP) including dietary supplements and foods persists, promising preclinical NP research is not consistently translating into actionable clinical trial (CT) outcomes. Generally considered the gold standard for assessing safety and efficacy, CTs, especially phase III CTs, are costly and require rigorous planning to optimize the value of the information obtained. More effective bridging from NP research to CT was the goal of a September, 2018 transdisciplinary workshop. Participants emphasized that replicability and likelihood of successful translation depend on rigor in experimental design, interpretation, and reporting across the continuum of NP research. Discussions spanned good practices for NP characterization and quality control; use and interpretation of models (computational through in vivo) with strong clinical predictive validity; controls for experimental artefacts, especially for in vitro interrogation of bioactivity and mechanisms of action; rigorous assessment and interpretation of prior research; transparency in all reporting; and prioritization of research questions. Natural product clinical trials prioritized based on rigorous, convergent supporting data and current public health needs are most likely to be informative and ultimately affect public health. Thoughtful, coordinated implementation of these practices should enhance the knowledge gained from future NP research.

While great interest in health effects of natural product (NP) including dietary supplements and foods persists, promising preclinical NP research is not consistently translating into actionable clinical trial (CT) outcomes. Generally considered the gold standard for assessing safety and efficacy, CTs, especially phase III CTs, are costly and require rigorous planning to optimize the value of the information obtained. More effective bridging from NP research to CT was the goal of a September, 2018 transdisciplinary workshop. Participants emphasized that replicability and likelihood of successful translation depend on rigor in experimental design, interpretation, and reporting across the continuum of NP research. Discussions spanned good practices for NP characterization and quality control; use and interpretation of models (computational through in vivo) with strong clinical predictive validity; controls for experimental artefacts, especially for in vitro interrogation of bioactivity and mechanisms of action; rigorous assessment and interpretation of prior research; transparency in all reporting; and prioritization of research questions. Natural product clinical trials prioritized based on rigorous, convergent supporting data and current public health needs are most likely to be informative and ultimately affect public health. Thoughtful, coordinated implementation of these practices should enhance the knowledge gained from future NP research.