PREVENTION OF PRESSURE ULCERS IN HIGH RISK PATIENTS IN AN ACUTE CARE AND REHABILITATION SETTING

2007 ◽  
Vol 34 (Supplement) ◽  
pp. S22
Author(s):  
Laura G. Shafer ◽  
Kathy Boyle
Keyword(s):  
High Risk ◽  
Acute Care ◽  
Pressure Ulcers ◽  
High Risk Patients ◽  
Risk Patients

Reducing hospital aquired pneumonia (HAP) with Massey Screen.

2016 ◽  
Vol 34 (7_suppl) ◽  
pp. 232-232
Author(s):  
Kerri Slavin ◽  
Robyn Dunbar ◽  
Cheryl Clements ◽  
Margaret Bonawitz ◽  
Joanne McGovern
Keyword(s):  
High Risk ◽  
Early Detection ◽  
Acute Care ◽  
Patient Outcomes ◽  
Nursing Staff ◽  
Oral Care ◽  
Oncology Patients ◽  
High Risk Patients ◽  
Telemetry Unit ◽  
Risk Patients

232 Background: Hospital Acquired Pneumonia (HAP) is a leading cause of prolonged hospitalization in patients. The oncology population is especially susceptible to critical illness related to an immunocompromised state. The purpose of this study was to implement the Massey Bedside Swallowing Screen upon admission to the oncology telemetry unit to detect any deficits that could potentially lead to HAP, in conjunction with strict oral care for identified high risk patients. Methods: The importance of the Massey Bedside Swallowing Screen upon admission and the knowledge that early detection leads to better patient outcomes was educated to the nursing staff. Every patient admitted to the oncology telemetry unit was screened with the Massey Bedside Swallowing Screen. Patients identified as high-risk were placed on nothing-by-mouth (NPO) precaution. A Speech and Swallow Evaluation was ordered to further evaluate the patient. Acutely ill oncology patients unable to perform their own oral care were placed on a strict oral care regimen performed by the nursing staff. The charge nurse audited compliance with this protocol. Results: The pre-intervention phase of the study evaluated January – April 2015 included 1,605 patient days. The data revealed 4 HAPs acquired on the oncology telemetry unit, demonstrating 2.45 incidence/1000 patient days. Post-intervention [May – August 2015] indicated 2 HAPs acquired on the oncology telemetry unit, signifying 1.35 incidence/1000 patient days. With the implementation of the Massey Bedside Swallowing Screen for each patient upon admission, and strict oral care regimen for high-risk patients, the overall incidence of HAP on the unit decreased by 50%. Conclusions: Oncology patients assessed with the Massey Bedside Swallowing Screen upon admission to the oncology telemetry unit were noted to have improved outcomes and lower rates of HAP. Every oncology patient admitted to an acute care unit should have an admission screen in place to evaluate risk for aspiration. Early detection of patients at high-risk for HAP and implementation of interventions to improve oral care in high-risk patients lead to improved patient outcomes through lower incidence of HAP in the acute care setting.

Pilot program of remote monitoring for high-risk patients on antineoplastic treatment.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 2027-2027
Author(s):  
Robert Michael Daly ◽  
Gilad Kuperman ◽  
Alice Zervoudakis ◽  
Alice Ro ◽  
Ankita Roy ◽  
...  
Keyword(s):  
High Risk ◽  
Acute Care ◽  
Nurse Practitioners ◽  
Perceived Value ◽  
Patient Portal ◽  
Pilot Program ◽  
High Risk Patients ◽  
Risk Patients ◽  
Antineoplastic Treatment

2027 Background: Early detection and management of symptoms in patients with cancer improves outcomes, however, the optimal approach to symptom monitoring and management is unknown. This pilot program uses a mobile health intervention to capture and make accessible symptom data for high-risk patients to mitigate symptom escalation. Methods: Patients initiating antineoplastic treatment at a Memorial Sloan Kettering regional location were eligible. A dedicated staff of RNs and nurse practitioners managed the patients remotely. The technology supporting the program included: 1) a predictive model that identified patients at high risk for a potentially preventable acute care visit; 2) a patient portal enabling daily ecological momentary assessments (EMA); 3) alerts for concerning symptoms; 4) an application that allowed staff to review and trend symptom data; and 5) a secure messaging platform to support communications and televisits between staff and patients. Feasibility and acceptability were evaluated through enrollment (goal ≥25% of new treatment starts) and response rates (completion of > 50% of daily symptom assessments); symptom alerts; perceived value based on qualitative interviews with patients and providers; and acute care usage. Results: Between October 15, 2018 and July 10, 2019, the pilot enrolled 100 high-risk patients with solid tumors and lymphoma initiating antineoplastic treatment (median age: 66 years, 45% female). This represented 29% of patients starting antineoplastics. Over six months of follow-up, the response rate to the daily assessments was 56% and 93% of patients generated a severe symptom alert (Table). Both patients and providers perceived value in the program and 5,010 symptom-related secure messages were shared between staff and enrolled patients during the follow-up period. There was a preliminary signal in acute care usage with a 17% decrease in ED visits compared to a cohort of high-risk unenrolled patients. Conclusions: This pilot program of intensive monitoring of high-risk patients is feasible and holds significant potential to improve patient care and decrease hospital resources. Future work should focus on the optimal cadence of EMAs, the workforce to support remote symptom management, and how best to return symptom data to patients and clinical teams. [Table: see text]

Implementing a clinical risk prediction tool for patients undergoing active cancer treatment.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. TPS2086-TPS2086
Author(s):  
Nathan Handley ◽  
Adam Binder ◽  
Michael Li ◽  
Aliya Rogers ◽  
Valerie Pracilio Csik
Keyword(s):  
High Risk ◽  
Acute Care ◽  
Nursing Intervention ◽  
Emergency Department Visits ◽  
Low Risk ◽  
High Risk Patients ◽  
Nurse Navigator ◽  
Risk Patients ◽  
The Impact ◽  
Active Cancer

TPS2086 Background: Acute care utilization (ACU), encompassing both emergency department visits and hospitalizations, is common in patients with cancer, with nearly three quarters of patients with advanced disease hospitalized at least once in the year after their diagnosis. Efforts to prospectively identify these patients prior to ACU have led to the development of a variety of scoring systems for specific cancer patient populations, including the elderly and those initiating palliative infusional chemotherapy. Prospectively identifying patients may enable early interventions to reduce ACU. However, few studies have demonstrated effective implementation of such prediction tools in clinical practice. We developed an oncology risk score (ORS) for active oncology patients (defined as patients with an active cancer diagnosis in the last 12 months who had a Medical Oncology encounter in a 180-day period ) to prospectively determine risk of ACU. Patients are defined as high risk (18% of patients, accounting for 57% of historical ACU), intermediate risk (25% of patients, accounting for 25% of ACU), or low risk (56% of patients, accounting for 18% of ACU) by the ORS. We are currently deploying a pragmatic implementation initiative to evaluate the impact of targeted nurse navigator (NN) outreach to patients defined as high risk for ACU by the ORS. Methods: The ORS is embedded within the health system electronic medical record. The ORS will be queried on a weekly basis. NNs will contact identified patients, prioritizing patients not yet identified by the navigation team by other means. Following chart review, NNs will either meet patients in person (if a visit is already planned within 24 hours) or complete standard navigation outreach and documentation (consisting of phone call and barrier assessment, as well as appropriate nursing intervention) if no visit is planned. NNs will determine follow up cadence based on clinical judgement. Efficacy will be determined using a case-control method. Case patients will be OCM patients defined as high risk by the ORS (historical n = 289); control patients will be non-OCM high risk patients (historical n = 388). The total number of patients in the case and control groups, as well as the proportion of patients in the group utilizing acute care, will be monitored over time. Proportion of high risk patients known to navigation will be tracked. ACU in medium and low risk groups will also be monitored. Targeted outreach to high risk patients using the ORS began on 2/5/2019.

scholarly journals Use of Hydrocolloid Dressings in Preventing Pressure Ulcers in High-risk Patients: a Retrospective Cohort

2018 ◽  
Vol 36 (1) ◽  
pp. e11 ◽  
Author(s):  
Olga Lucía Cortés Cortés ◽  
◽  
Luz Dary Salazar-Beltrán ◽  
Yudi Andrea Rojas-Castañeda ◽  
Paula Andrea Alvarado-Muriel ◽  
...  
Keyword(s):  
High Risk ◽  
Retrospective Cohort ◽  
Pressure Ulcers ◽  
High Risk Patients ◽  
Risk Patients

scholarly journals Validation of the STRATIFY Falls Risk Assessment Tool in a Japanese Acute Care Hospital Setting

2016 ◽  
Vol 9 (2) ◽  
pp. 277 ◽  
Author(s):  
Shin-ichi Toyabe ◽  
Thoshihiro Kaneko ◽  
Akira Suzuki ◽  
Ayuko Yasuda
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Acute Care ◽  
Hospital Setting ◽  
Assessment System ◽  
Low Risk ◽  
Falls Risk ◽  
High Risk Patients ◽  
Risk Patients ◽  
Inpatient Falls

<p>Patient falls are the most frequent adverse events that occur in a hospital. Prevention of inpatient falls is performed by a strategy to target patients at high risk for falls determined by a falls risk assessment system such as the STRATIFY tool. However, the performance of the STRATIFY tool in a Japanese hospital setting has not been determined. We tried to verify the performance of the STRATIFY tool for predicting falls in acutely hospitalized patients in Japan by a multi-center study. A total of 113,413 patients admitted to four acute cares national university hospitals during the period from April 2010 to March 2012 were studied. Inpatient falls per 1,000 patient-days varied from 1.42 to 2.92 in the four hospitals. The STRATIFY score was calculated on the basis of data extracted electronically from the hospital information system. Although the distribution of STRATIFY scores differed significantly among the four hospitals, logistic regression analysis and survival analysis showed that the proportion of high-risk patients who fell was significantly larger than the proportion of low-risk patients in all of the four hospitals. The odds ratio and hazard ratio for high-risk patients versus low-risk patients were 2.5 to 4.3 (combined estimate, 3.9 (95% confidence interval (95% CI), 2.1 to 7.6) and 1.8 to 5.1 (combined estimate, 3.1 (95% CI, 2.1 to 4.6)), respectively. The results suggest that the STRATIFY tool can be used as a screening tool to detect patients at high risk for falls in a Japanese acute care setting as used commonly in other countries. </p>

scholarly journals Improving transitions from acute care to home among complex older adults using the LACE Index and care coordination

2020 ◽  
Vol 9 (2) ◽  
pp. e000814 ◽  
Author(s):  
Lesley Charles ◽  
Lisa Jensen ◽  
Jacqueline M I Torti ◽  
Jasneet Parmar ◽  
Bonnie Dobbs ◽  
...  
Keyword(s):  
High Risk ◽  
Acute Care ◽  
Care Coordination ◽  
Phase 1 ◽  
Hospital Readmissions ◽  
Acute Care Hospital ◽  
Care Hospital ◽  
High Risk Patients ◽  
Phone Calls ◽  
Risk Patients

BackgroundImproving transitions in care is a major focus of healthcare planning. The objective of this study was to determine the improvement in transitions from an intervention identifying complex older adult patients in acute care and supporting their discharge into the community.MethodsThis was a quality assurance study evaluating an intervention on high-risk patients admitted in an acute care hospital. In phase 1, the Length of Stay, Acuity of the Admission, Charlson Comorbidity Index Score, and Emergency Department Use (LACE Index) was selected to assess a patient’s risk for readmission and a standard discharge protocol was developed. In phase 2, the intervention was implemented: (1) all patients were screened for the risk of readmission using the LACE Index; and (2) the high-risk patients were provided care coordination including follow-up phone calls focused on medications, equipment and homecare services. Emergency department (ED) revisits and hospital readmissions were measured.ResultsThe LACE Index identified 433/1621 (27%) patients at high risk for readmission. Care coordination was achieved within 72 hours in 79% of patients. The 433 high-risk patients receiving the intervention, compared with a group without intervention (n=231), had lower lengths of stay (12.7 days vs 16.6 days); similar 7-day ED revisits (10.6% vs 10.8%) and 30-day ED revisits (30.5% vs 33.3%); lower 90-day readmissions (39.3% vs 44.6%); and lower 6-month readmissions (50.9% vs 58.4%). The 7-day and 30-day readmissions were similar in both groups.ConclusionsIdentifying complex patients at high risk for readmission and supporting them during transitions from acute care to home potentially decreases lengths of hospital stay and prevents short-term ED revisits and long-term readmissions.

scholarly journals InSight Care Pilot Program: Redefining Seeing a Patient

2020 ◽  
pp. OP.20.00214
Author(s):  
Bobby Daly ◽  
Gilad Kuperman ◽  
Alice Zervoudakis ◽  
Abigail Baldwin Medsker ◽  
Ankita Roy ◽  
...  
Keyword(s):  
High Risk ◽  
Acute Care ◽  
Perceived Value ◽  
Improve Patient Care ◽  
Symptom Assessment ◽  
Program Improvement ◽  
Patient Portal ◽  
Pilot Program ◽  
High Risk Patients ◽  
Risk Patients

PURPOSE: Early detection and management of symptoms in patients with cancer improves outcomes. However, the optimal approach to symptom monitoring and management is unknown. InSight Care is a mobile health intervention that captures symptom data and facilitates patient-provider communication to mitigate symptom escalation. PATIENTS AND METHODS: Patients initiating antineoplastic treatment at a Memorial Sloan Kettering regional location were eligible. Technology supporting the program included the following: a predictive model that identified patient risk for a potentially preventable acute care visit; a secure patient portal enabling communication, televisits, and daily delivery of patient symptom assessments; alerts for concerning symptoms; and a symptom-trending application. The main outcomes of the pilot were feasibility and acceptability evaluated through enrollment and response rates and symptom alerts, and perceived value evaluated on the basis of qualitative patient and provider interviews. RESULTS: The pilot program enrolled 100 high-risk patients with solid tumors and lymphoma (29% of new treatment starts v goal of 25%). Over 6 months of follow-up, the daily symptom assessment response rate was 56% (the goal was 50%), and 93% of patients generated a severe symptom alert. Patients and providers perceived value in the program, and archetypes were developed for program improvement. Enrolled patients were less likely to use acute care than were other high-risk patients. CONCLUSION: InSight Care was feasible and holds the potential to improve patient care and decrease facility-based care. Future work should focus on optimizing the cadence of patient assessments, the workforce supporting remote symptom management, and the return of symptom data to patients and clinical teams.

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