scholarly journals Rothman Index as a Predictor of 30-Day Hospital Readmission

2021 ◽  
Keyword(s):  
High Risk ◽  
Health Systems ◽  
Hospital Readmission ◽  
Medical Center ◽  
Academic Medical Center ◽  
Day Hospital ◽  
Readmission Rates ◽  
Predictive Tool ◽  
Point Increase ◽  
Index Value

Introduction: The Centers for Medicare and Medicaid services financially penalize hospitals for elevated 30-day readmission rates. Identifying patients at high risk for short-term readmission would allow health systems to strategically allocate resources to this vulnerable population. The objective of this study was to determine whether there was a difference in mean Rothman Index value for patients readmitted to the hospital within 30 days of index stay versus patients not readmitted in order to evaluate the Rothman Index’s utility as a predictive tool. Materials and Methods: Data from 100 subjects from a single academic medical center, with a balanced number of readmit (n=50, mean age 68.9 years, 54% female) and non-readmits (n=50, 46% female, mean age 70.9 years), was collected. Results: Non-readmits demonstrated significantly higher mean Rothman Index values (70.94 ± 1.3) compared to patients readmitted within 30 days (mean Rothman Index of 61.68 ± 1.6) at (P< .001; 95% CI, 5.10 to 13.41). Age (95% CI, -0.052 to 0.006; P= .12), gender (95% CI, -0.949 to 0.948; P= .99) and primary discharge diagnosis from index stay (P= 0.31) were not predictive of readmission; only the Rothman Index was (95% CI, -0.136 to -0.039; P<.001).The coefficient of the Rothman Index was -0.088, indicating that for each 1 point increase in Rothman Index, a patient’s odds of readmission within 30 days declined by 8.8% (95% CI, -0.136 to -0.039; P< .001). Conclusions: The Rothman Index can be utilized as a predictive tool to identify patients at high risk of unplanned 30-day hospital readmission, thereby allowing health systems to strategically allocate outside hospital resources.

scholarly journals Reducing Preventable Readmissions in a Neurosurgical Patient Population at an Academic Medical Center

Neurosurgery ◽  
2019 ◽  
Vol 66 (Supplement_1) ◽  
Author(s):  
Shayan Moosa ◽  
Lindsay Bowerman ◽  
Ellen Smith ◽  
Mindy Bryant ◽  
Natalie Krovetz ◽  
...  
Keyword(s):  
High Risk ◽  
Patient Population ◽  
Medical Center ◽  
Academic Medical Center ◽  
Readmission Rates ◽  
Academic Medical ◽  
Neurosurgical Patient ◽  
Neurosurgical Patients ◽  
Significant Difference

Abstract INTRODUCTION Hospital readmissions are extremely costly in terms of time and resources and negatively impact patient safety and satisfaction. In this study, we performed a Pareto analysis of 30-day readmissions in a neurosurgical patient population in order to identify patients at high-risk for readmission. Using this information, we implemented a new practice parameter with the goal of reducing preventable readmissions. METHODS Patient characteristics and causes for readmission were prospectively collected for all neurosurgical patients readmitted to an academic medical center within 30 d of discharge between July and October 2018. A program was then initiated where postoperative neurosurgical spine patients were contacted by phone at standardized intervals before their 2-wk follow-up appointment, with the purpose of more quickly addressing surgical concerns and/or coordinating care for general medical issues. Finally, 30-d readmission rates were compared between the initial 4-mo period and January 2019 through April 2019. RESULTS Prior to intervention, the largest group of readmitted patients included those who had undergone recent spinal surgery (16/47, 34%). Among spine readmissions during this time, 47% were readmitted before their two-week follow-up appointment, 67% lived over 50 miles from the medical center, and 40% were Medicare-insured. There was a statistically significant difference in the mean rate of spine readmissions per month in the periods before (7.0%) and after (3.0%) the program onset (P = .029, 57% decline). The total number of surgically and medically related spine readmissions decreased between the pre- and postintervention periods from 10 to 3 (70%) and 3 to 1 (67%), respectively. CONCLUSION Our data suggests that a large number of neurosurgical readmissions may be prevented by the simple process of early follow-up and consistent communication via telephone. Readmission rates may be further reduced by standardizing the coordination of postoperative general medical follow-up and providing thorough wound care teaching for high-risk patients.

Impacting Readmission Rates and Patient Satisfaction: Results of a Discharge Pharmacist Pilot Program

2011 ◽  
Vol 46 (11) ◽  
pp. 876-883 ◽  
Author(s):  
Samaneh Tavalali Wilkinson ◽  
Pal Aroop ◽  
J. Couldry Richard
Keyword(s):  
Patient Satisfaction ◽  
High Risk ◽  
Readmission Rate ◽  
Medical Center ◽  
Academic Medical Center ◽  
Control Group ◽  
Unplanned Readmission ◽  
Discharge Process ◽  
Readmission Rates ◽  
The Impact

Background Readmission to a hospital within 30 days of discharge has become a key quality outcome measure. With an observed 30-day readmission rate as high as 20% and attributed costs of almost $17.4 billion a year for Medicare patients, the potential implications for patients and the entire health care system are significant. Medication-related complications have been shown to increase the risk for unplanned readmission. Pharmacists have an opportunity to impact quality and cost by risk stratifying and identify patients at high risk for hospital readmission. Objective To study the impact of a pharmacist-driven discharge counseling program for high-risk patients identified by BOOST (Better Outcomes for Older adults through Safe Transitions) criteria on 30-day readmission rates. Method This was a prospective, cohort, nonrandomized trial at a single medical-surgical unit with telemetry capability at a single academic medical center including 669 patients who were older than 18 years. Primary outcome was 30-day readmission rate. Secondary outcomes were the number and type of pharmacist interventions, cost avoidance, and patient satisfaction results. Results The readmission rate for patients counseled by a pharmacist during the discharge process was 15.7% compared to 21.6% for patients not counseled by a pharmacist on discharge (relative risk [RR] 0.728; 95% confidence interval [CI], 0.514–1.032; P = .04). The readmission rate for adult medicine patients not counseled at discharge by a pharmacist in the study was comparable to the readmission rates of a similar patient control group at 3 months and 1 year prior to the initiation of the study (18.7% and 19.1% vs 19.6%). Conclusions Pharmacists' support in the discharge process facilitated increased communication on the multidisciplinary team and resulted in a lower unplanned readmission rate for patients.

scholarly journals Advancing Pharmacy Practice through an Innovative Ambulatory Care Transitions Program at an Academic Medical Center

Pharmacy ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 40
Author(s):  
Jamie Cavanaugh ◽  
Nicole Pinelli ◽  
Stephen Eckel ◽  
Mark Gwynne ◽  
Rowell Daniels ◽  
...  
Keyword(s):  
Usual Care ◽  
Hospital Readmission ◽  
Medical Center ◽  
Academic Medical Center ◽  
Hospital Readmissions ◽  
Care Transition ◽  
Day Hospital ◽  
Transition Intervention ◽  
Academic Medical

Hospital readmissions are common and often preventable, leading to unnecessary burden on patients, families, and the health care system. The purpose of this descriptive communication is to share the impact of an interdisciplinary, outpatient clinic-based care transition intervention on clinical, organizational, and financial outcomes. Compared to usual care, the care transition intervention decreased the median time to Internal Medicine Clinic (IMC) or any clinic follow-up visit by 5 and 4 days, respectively. By including a pharmacist in the hospital follow-up visit, the program significantly reduced all-cause 30-day hospital readmission rates (9% versus 26% in usual care) and the composite endpoint of 30-day health care utilization, which is defined as readmission and emergency department (ED) rates (19% versus 44% usual care). Over the course of one year, this program can prevent 102 30-day hospital readmissions with an estimated cost reduction of $1,113,000 per year. The pharmacist at the IMC collaborated with the Family Medicine Clinic (FMC) pharmacist to standardize practices. In the FMC, the hospital readmission rate was 6.5% for patients seen by a clinic-based pharmacist within 30 days of discharge compared to 20% for those not seen by a pharmacist. This transitions intervention demonstrated a consistent and recognizable contribution from pharmacists providing direct patient care and practicing in the ambulatory care primary care settings that has been replicated across clinics at our academic medical center.

scholarly journals Impact of Critical Care Consultation Requests for Avoidable Central Venous Catheters on Medical-Surgical Units

2020 ◽  
Vol 41 (S1) ◽  
pp. s258-s258
Author(s):  
Madhuri Tirumandas ◽  
Theresa Madaline ◽  
Gregory David Weston ◽  
Ruchika Jain ◽  
Jamie Figueredo
Keyword(s):  
Critical Care ◽  
High Risk ◽  
Medical Center ◽  
Academic Medical Center ◽  
Retrospective Chart Review ◽  
Bloodstream Infections ◽  
Central Line ◽  
Central Venous Catheters ◽  
High Risk Population ◽  
Central Venous

Background: Although central-line–associated bloodstream infections (CLABSI) in US hospitals have improved in the last decade, ~30,100 CLABSIs occur annually.1,2 Central venous catheters (CVC) carry a high risk of infections and should be limited to appropriate clinical indications.6,7 Montefiore Medical Center, a large, urban, academic medical center in the Bronx, serves a high-risk population with multiple comobidities.8–11 Despite this, the critical care medicine (CCM) team is often consulted to place a CVC when a peripheral intravenous line (PIV) cannot be obtained by nurses or primary providers. We evaluated the volume of CCM consultation requests for avoidable CVCs and related CLABSIs. Methods: Retrospective chart review was performed for patients with CCM consultation requests for CVC placement between July and October 2019. The indication for CVC, type of catheter inserted or recommended, and NHSN data were used to identify CLABSIs. CVCs were considered avoidable if a PIV was used for the stated indication and duration of therapy, with no anatomical contraindications to PIV in nonemergencies, according to the Michigan Appropriateness Guide for Intravenous Catheters (MAGIC).6Results: Of 229 total CCM consults, 4 (18%) requests were for CVC placement; 21 consultations (9%) were requested for avoidable CVCs. Of 40 CVC requests, 18 (45%) resulted in CVC placement by the CCM team, 4 (10%) were deferred for nonurgent PICC by interventional radiology, and 18 (45%) were deferred in favor of PIV or no IV. Indications for CVC insertion included emergent chemotherapy (n = 8, 44%) and dialysis (n = 3, 16%), vasopressors (n = 3, 16%), antibiotics (n = 2, 11%) and blood transfusion (n = 2, 11%). Of 18 CVCs, 9 (50%) were potentially avoidable: 2 short-term antibiotics and rest for nonemergent indications; 2 blood transfusions, 1 dialysis, 2 chemotherapy and 2 vasopressors. Between July and October 2019, 6 CLABSIs occurred in CVCs placed by the CCM team; in 3 of 6 CLABSI events (50%), the CVC was avoidable. Conclusions: More than half of consultation requests to the CCM team for CVCs are avoidable, and they disproportionately contribute to CLABSI events. Alternatives for intravenous access could potentially avoid 9% of CCM consultations and 50% of CLABSIs in CCM-inserted CVCs on medical-surgical wards.Funding: NoneDisclosures: None

Development and validation of the Tool for Pharmacists to Predict 30-day hospital readmission in patients with Heart Failure (ToPP-HF)

2021 ◽  
Author(s):  
Melissa R Riester ◽  
Laura McAuliffe ◽  
Christine Collins ◽  
Andrew R Zullo
Keyword(s):  
Heart Failure ◽  
High Risk ◽  
Hospital Readmission ◽  
Left Ventricular Ejection ◽  
Day Hospital ◽  
High Risk Patients ◽  
C Statistic ◽  
Patients With Heart Failure ◽  
Risk Patients ◽  
Development And Validation

Abstract Purpose Pharmacists are well positioned to provide transitions of care (TOC) services to patients with heart failure (HF); however, hospitalizations for patients with HF likely exceed the capacity of a TOC pharmacist. We developed and validated a tool to help pharmacists efficiently identify high-risk patients with HF and maximize their potential impact by intervening on patients at the highest risk for 30-day all-cause readmission. Methods We conducted a retrospective cohort study including adults with HF admitted to a health system between October 1, 2016, and October 31, 2019. We randomly divided the cohort into development (n = 2,114) and validation (n = 1,089) subcohorts. Nine models were applied to select the most important predictors of 30-day readmission. The final tool, called the Tool for Pharmacists to Predict 30-day hospital readmission in patients with Heart Failure (ToPP-HF) relied upon multivariable logistic regression. We assessed discriminative ability using the C statistic and calibration using the Hosmer-Lemeshow goodness-of-fit test. Results The risk of 30-day all-cause readmission was 15.7% (n = 331) and 18.8% (n = 205) in the development and validation subcohorts, respectively. The ToPP-HF tool included 13 variables: number of hospital admissions in previous 6 months; admission diagnosis of HF; number of scheduled medications; chronic obstructive pulmonary disease diagnosis; number of comorbidities; estimated glomerular filtration rate; hospital length of stay; left ventricular ejection fraction; critical care requirement; renin-angiotensin-aldosterone system inhibitor use; antiarrhythmic use; hypokalemia; and serum sodium. Discriminatory performance (C statistic of 0.69; 95% confidence interval [CI], 0.65-0.73) and calibration (Hosmer-Lemeshow P = 0.28) were good. Conclusions The ToPP-HF performs well and can help pharmacists identify high-risk patients with HF most likely to benefit from TOC services.

Abstract 169: Targeting Patients with Multiple Readmissions in the Year after Non-ST-Elevation Myocardial Infarction Could Lower Hospital Readmission Rates

2013 ◽  
Vol 6 (suppl_1) ◽  
Author(s):  
Gwen Bernacki ◽  
Karen Alexander ◽  
Matthew Roe ◽  
Shuang Li ◽  
Laine Thomas ◽  
...  
Keyword(s):  
High Risk ◽  
Hospital Readmission ◽  
Transitional Care ◽  
Multivariable Analysis ◽  
Patient Characteristics ◽  
High Risk Group ◽  
Billing Data ◽  
Readmission Rates ◽  
Bundled Payment ◽  
Hospital Readmission Rates

Background: Bundled payment policies have focused on 30-day readmission rates after AMI, yet these are likely to lengthen over time. Identifying patients with multiple readmissions in the year after AMI could help focus transitional care efforts on these high risk patients. Methods: Data from the CRUSADE registry linked to Medicare billing data was used to examine longitudinal outcomes of 32,776 NSTEMI patients ≥ 65 years between 2003 and 2006 with 12-month follow-up. Defining frequent readmissions as ≥3 hospitalizations in 12 months, we compared characteristics of patients frequently readmitted vs. not. The association between frequent readmissions and patient characteristics was examined using multivariable logistic regression. Results: Readmission within 12 months after NSTEMI occurred: once (N=8,830, 26.9%); twice (N=4334, 13.2%); 3 times (N=2,319, 7.1%); ≥4 times (N=2470, 7.5%). Those with multiple (≥3) readmissions (14.6%) were older with recent prior hospitalization and greater prevalence of comorbidities. In multivariable analysis, these factors increased discrimination of patients with frequent readmissions, (c-statistic=0.714). Conclusions: Comorbidities and recent prior hospitalization can predict patients with frequent readmissions. Better understanding of the influence of these clinical factors in this high-risk group presents an opportunity to lower hospital readmission rates.

scholarly journals Integration of an Academic Medical Center and a Large Health System: Implications for Pharmacy

2019 ◽  
Vol 54 (3) ◽  
pp. 170-174
Author(s):  
Brian L. Erstad ◽  
Tina Aramaki ◽  
Kurt Weibel
Keyword(s):  
Health System ◽  
Health Systems ◽  
Integration Method ◽  
Medical Center ◽  
Academic Medical Center ◽  
Lessons Learned ◽  
Faculty Members ◽  
Pharmacy Services ◽  
Academic Medical ◽  
High Level

Objective: To provide lessons learned for colleges of pharmacy and large health systems that are contemplating or in the process of undergoing integration. Method: This report describes the merger of an academic medical center and large health system with a focus on the implications of the merger for pharmacy from the perspectives of both a college of pharmacy and a health system’s pharmacy services. Results: Overarching pharmacy issues to consider include having an administrator from the college of pharmacy directly involved in the merger negotiation discussions, having at least one high-level administrator from the college of pharmacy and one high-level pharmacy administrator from the health system involved in ongoing discussions about implications of the merger and changes that are likely to affect teaching, research, and clinical service activities, having focused discussions between college and health system pharmacy administrators on the implications of the merger on experiential and research-related activities, and anticipating concerns by clinical faculty members affected by the merger. Conclusion: The integration of a college of pharmacy and a large health system during the acquisition of an academic medical center can be challenging for both organizations, but appropriate pre- and post-merger discussions between college and health system pharmacy administrators that include a strategic planning component can assuage concerns and problems that are likely to arise, increasing the likelihood of a mutually beneficial collaboration.

Thirty-day and 90-day hospital readmission rates in women with endometrial cancer

2020 ◽  
Vol 159 ◽  
pp. 205
Author(s):  
R. Shibata ◽  
A. Nizam ◽  
J.S. Whyte ◽  
B. Bustamante ◽  
W. Shan ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Hospital Readmission ◽  
Day Hospital ◽  
Readmission Rates ◽  
Hospital Readmission Rates
Sign in / Sign up

Export Citation Format

Share Document