Patient flow variability and unplanned readmissions to an intensive care unit*

Baker, David; Pronovost, Peter J.; Morlock, Laura L.; Geocadin, Romergryko G.; Holzmueller, Christine G.

doi:10.1097/ccm.0b013e3181b01caf

Cited by 73 publications

(55 citation statements)

References 16 publications

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“…[17][18][19] Additionally, the performance of ICUs on ICU readmissions is not correlated with performance on other measures of ICU quality, such as mortality or process measures. 3,18,[20][21][22][23][24] Th ese latter observations suggest that ICU readmissions may result from practice variations residing outside the causal pathway to other poor outcomes.…”

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confidence: 99%

Assessing the Utility of ICU Readmissions as a Quality Metric

Brown

Ratcliffe

Halpern

2015

Chest

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BACKGROUND: ICU readmissions are associated with increased mortality and costs; however, it is unclear whether these outcomes are caused by readmissions or by residual confounding by illness severity. An assessment of temporal changes in ICU readmission in response to a specific policy change could help disentangle these possibilities. We sought to determine whether ICU readmission rates changed aft er 2003 Accreditation Council for Graduate Medical Education Resident Duty Hours reform ("reform") and whether there were temporally corresponding changes in other ICU outcomes.

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confidence: 99%

Assessing the Utility of ICU Readmissions as a Quality Metric

Brown

Ratcliffe

Halpern

2015

Chest

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“…We have defined "ICU capacity strain" as a set of temporally varying influences on the ability of an ICU to provide high-quality care for everyone who is or could become a patient in that ICU on that day (7). Several time-varying ICU factors are associated with patient outcomes, including ICU census, the proportion of new admissions, the mean acuity of other ICU patients, and bed occupancy (8)(9)(10)(11)(12)(13)(14). However, not all studies have documented such associations (15), and the impact of these and other variables on other potential consequences of capacity strain is unclear.…”

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confidence: 99%

Objective Factors Associated with Physicians’ and Nurses’ Perceptions of Intensive Care Unit Capacity Strain

et al. 2014

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Rationale: Time-varying demand for critical care may strain the capacities of intensive care units (ICUs) to provide optimal care. Intensivists and ICU nurses may be the best judges of the strain on their ICU. Yet, it is not clear what ICU and hospital factors contribute to this perceived sense of strain among ICU providers.Objectives: To identify measureable ICU and hospital factors associated with perceived strain by intensivists and ICU nurses.Methods: During a 6-month prospective cohort study, we surveyed nurses and physicians responsible for bed management regarding the ability of a 24-bed medical ICU (MICU) to provide optimal critical care. We simultaneously assessed time-varying ICU-level factors, including patient census, number of admissions, average patient acuity, number of interhospital transfer requests, and censuses of other hospital units. To identify factors associated with strain, we used an algorithm for covariate selection in regression models that selects variables that contribute sufficiently to model prediction to justify their inclusion. Measurements and Main Results:Of 254 surveys, 226 (89%) were completed by 18 charge nurses and 17 physicians. On a scale of 1 to 10 (where a higher score indicated more strain), the median perceived strain score among nurses was 6 (interquartile range, 3-7) and among physicians was 5 (interquartile range, 3-7), with moderate correlation within days (interclass correlation coefficient, 0.45; 95% confidence interval: 0.30, 0.60). Average patient acuity, MICU census, number of MICU admissions, and general ward census were included in the most efficient model of strain perceived by nurses. Only MICU census was strongly associated with strain perceived by physicians. Conclusions:A model containing commonly available metrics of ICU census, average patient acuity, and the proportion of new admissions has validity as a model of ICU nurses' perceived ICU capacity strain. However, only ICU census was associated with increased perceived capacity strain by physicians, highlighting the need for involvement of multiple stakeholder groups to improve our understanding of ICU capacity strain.

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“…Healthcare institutions utilize patient flow analyses to evaluate and improve aspects of the patient experience including safety, effectiveness, efficiency, timeliness, patient centeredness, and equity. [1][2][3][4][5][6][7][8] Hospitals can evaluate patient flow using specific metrics, such as time in emergency department (ED) or percent of discharges completed by a certain time of day. However, no single metric can represent the full spectrum of processes inherent to patient flow.…”

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confidence: 99%

Measuring patient flow in a children's hospital using a scorecard with composite measurement

Fieldston

Zaoutis

Agosto

et al. 2014

Journal of Hospital Medicine

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BACKGROUND Although patient flow is a focus for improvement in hospitals, commonly used single or unaggregated measures fail to capture its complexity. Composite measures can account for multiple dimensions of performance but have not been reported for the assessment of patient flow. OBJECTIVES To present and discuss the implementation of a composite measure system as a way to measure and monitor patient flow and improvement activities at an urban children's hospital. METHODS A 5‐domain patient flow scorecard with composite measurement was designed by an interdisciplinary workgroup using measures involved in multiple aspects of patient flow. RESULTS The composite score measurement system provided improvement teams and administrators with a comprehensive overview of patient flow. It captured overall performance trends and identified operational domains and specific components of patient flow that required improvement. DISCUSSION A patient flow scorecard with composite measurement holds advantages over a single or unaggregated measurement system, because it provides a holistic assessment of performance while also identifying specific areas in need of improvement. Journal of Hospital Medicine 2014;9:463–468. © 2014 Society of Hospital Medicine

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Patient flow variability and unplanned readmissions to an intensive care unit*

Cited by 73 publications

References 16 publications

Assessing the Utility of ICU Readmissions as a Quality Metric

Assessing the Utility of ICU Readmissions as a Quality Metric

Objective Factors Associated with Physicians’ and Nurses’ Perceptions of Intensive Care Unit Capacity Strain

Measuring patient flow in a children's hospital using a scorecard with composite measurement

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