Sandra F. Simmons, Emily K. Hollingsworth, Jason M. Slagle, Jennifer Kim, Lucy Wilson, Avantika Shah, Mariu C. Duggan, John F. Schnelle
{"title":"一种确定老年急症护理(ACE)医院护理人员配置的客观方法:离散事件模拟。","authors":"Sandra F. Simmons, Emily K. Hollingsworth, Jason M. Slagle, Jennifer Kim, Lucy Wilson, Avantika Shah, Mariu C. Duggan, John F. Schnelle","doi":"10.1111/jgs.19507","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Many hospitals have acute care for elders (ACE) units or engage in programs to enhance care for older inpatients. However, few studies have objectively evaluated nurse staffing models to support care for older inpatients.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>This study applied discrete event simulation (DES) to an ACE unit to objectively evaluate registered nurse (RN) and nursing assistant (NA) staffing allocations. Research staff collected standardized, objective data related to nursing tasks and time requirements to model the ACE unit clinical care environment and evaluate varying RN and NA staffing allocations on measures of nursing workload, care quality, and care efficiency.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>On a 22-bed ACE unit, 85% of patients were aged 65 or older, 37% had cognitive impairment, and 89% required toileting and/or mobility assistance. Nurse care routines were interrupted frequently by unscheduled patient care requests, with an average frequency of 6.1 (±1.6) requests per hour. DES was used to simulate four different RN and NA staffing allocations. Results showed the most common staffing (four RNs and one NA) resulted in the highest nursing workload rates (89% and 88% for RNs and NAs, respectively) and the highest rate of predicted care omissions (6.2%). Additionally, RNs were predicted to help with 83% of NA care tasks related to toileting and mobility assistance. Alternative allocations of four RNs and three NAs or five RNs and two NAs resulted in more feasible workload rates, lower rates of care omissions, and less reliance on RNs for NA care tasks.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>DES provides an objective method to identify nurse staffing needs for an ACE hospital unit. This approach can be used to safely evaluate the potential impact of varying nurse staffing allocations. The DES model for the ACE unit is adaptable to other types of hospital units that care for older patients.</p>\n </section>\n </div>","PeriodicalId":17240,"journal":{"name":"Journal of the American Geriatrics Society","volume":"73 7","pages":"2146-2154"},"PeriodicalIF":4.5000,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jgs.19507","citationCount":"0","resultStr":"{\"title\":\"An Objective Method to Determine Nurse Staffing for an Acute Care for Elders (ACE) Hospital Unit: Discrete Event Simulation\",\"authors\":\"Sandra F. Simmons, Emily K. Hollingsworth, Jason M. Slagle, Jennifer Kim, Lucy Wilson, Avantika Shah, Mariu C. Duggan, John F. Schnelle\",\"doi\":\"10.1111/jgs.19507\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>Many hospitals have acute care for elders (ACE) units or engage in programs to enhance care for older inpatients. However, few studies have objectively evaluated nurse staffing models to support care for older inpatients.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>This study applied discrete event simulation (DES) to an ACE unit to objectively evaluate registered nurse (RN) and nursing assistant (NA) staffing allocations. Research staff collected standardized, objective data related to nursing tasks and time requirements to model the ACE unit clinical care environment and evaluate varying RN and NA staffing allocations on measures of nursing workload, care quality, and care efficiency.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>On a 22-bed ACE unit, 85% of patients were aged 65 or older, 37% had cognitive impairment, and 89% required toileting and/or mobility assistance. Nurse care routines were interrupted frequently by unscheduled patient care requests, with an average frequency of 6.1 (±1.6) requests per hour. DES was used to simulate four different RN and NA staffing allocations. Results showed the most common staffing (four RNs and one NA) resulted in the highest nursing workload rates (89% and 88% for RNs and NAs, respectively) and the highest rate of predicted care omissions (6.2%). Additionally, RNs were predicted to help with 83% of NA care tasks related to toileting and mobility assistance. Alternative allocations of four RNs and three NAs or five RNs and two NAs resulted in more feasible workload rates, lower rates of care omissions, and less reliance on RNs for NA care tasks.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusions</h3>\\n \\n <p>DES provides an objective method to identify nurse staffing needs for an ACE hospital unit. This approach can be used to safely evaluate the potential impact of varying nurse staffing allocations. 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An Objective Method to Determine Nurse Staffing for an Acute Care for Elders (ACE) Hospital Unit: Discrete Event Simulation
Background
Many hospitals have acute care for elders (ACE) units or engage in programs to enhance care for older inpatients. However, few studies have objectively evaluated nurse staffing models to support care for older inpatients.
Methods
This study applied discrete event simulation (DES) to an ACE unit to objectively evaluate registered nurse (RN) and nursing assistant (NA) staffing allocations. Research staff collected standardized, objective data related to nursing tasks and time requirements to model the ACE unit clinical care environment and evaluate varying RN and NA staffing allocations on measures of nursing workload, care quality, and care efficiency.
Results
On a 22-bed ACE unit, 85% of patients were aged 65 or older, 37% had cognitive impairment, and 89% required toileting and/or mobility assistance. Nurse care routines were interrupted frequently by unscheduled patient care requests, with an average frequency of 6.1 (±1.6) requests per hour. DES was used to simulate four different RN and NA staffing allocations. Results showed the most common staffing (four RNs and one NA) resulted in the highest nursing workload rates (89% and 88% for RNs and NAs, respectively) and the highest rate of predicted care omissions (6.2%). Additionally, RNs were predicted to help with 83% of NA care tasks related to toileting and mobility assistance. Alternative allocations of four RNs and three NAs or five RNs and two NAs resulted in more feasible workload rates, lower rates of care omissions, and less reliance on RNs for NA care tasks.
Conclusions
DES provides an objective method to identify nurse staffing needs for an ACE hospital unit. This approach can be used to safely evaluate the potential impact of varying nurse staffing allocations. The DES model for the ACE unit is adaptable to other types of hospital units that care for older patients.
期刊介绍:
Journal of the American Geriatrics Society (JAGS) is the go-to journal for clinical aging research. We provide a diverse, interprofessional community of healthcare professionals with the latest insights on geriatrics education, clinical practice, and public policy—all supporting the high-quality, person-centered care essential to our well-being as we age. Since the publication of our first edition in 1953, JAGS has remained one of the oldest and most impactful journals dedicated exclusively to gerontology and geriatrics.