Impact of Workload on Service Time and Patient Safety: An Econometric Analysis of Hospital Operations

Kc, Diwas Singh; Terwiesch, Christian

doi:10.1287/mnsc.1090.1037

Cited by 425 publications

(302 citation statements)

References 25 publications

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“…From an empirical perspective, using data from two distinct healthcare services, patient transport and cardiothoracic surgery, Kc and Terwiesch (2009) validate that workers adapt to increasing levels of load in the system by increasing their service rate. The authors also show that such temporary service rate increases are not sustainable (i.e., workers become fatigued) and can have potentially serious quality implications.…”

Section: Literature Reviewmentioning

confidence: 92%

An Econometric Analysis of Patient Flows in the Cardiac Intensive Care Unit

Terwiesch

2012

M&SOM

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208

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This paper explores the rationing of bed capacity in a cardiac intensive care unit (ICU). We find that the length of stay for patients admitted to the ICU is influenced by the occupancy level of the ICU. In particular, a patient is likely to be discharged early when the occupancy in the ICU is high. This in turn leads to an increased likelihood of the patient having to be readmitted to the ICU at a later time. Such "bounce-backs" have implications for the overall ICU effective capacity-an early discharge immediately frees up capacity, but at the risk of a (potentially much higher) capacity requirement when the patient needs to be readmitted. We analyze these capacity implications, shedding light on the question of whether an ICU should apply an aggressive discharge strategy or if it should follow the old quality slogan and "do it right the first time. " By comparing the total capacity usage for patients who were discharged early versus those who were not, we show that an aggressive discharge policy applied to patients with lower clinical severity levels frees up capacity in the ICU. However, we find that an increased number of readmissions of patients with high clinical severity levels occur when the ICU is capacity constrained, thereby effectively reducing peak bed capacity. Christian TerwieschThe Wharton School, University of Pennsylvania terwiesch@wharton.upenn.eduThis paper explores the rationing of bed capacity in a cardiac intensive care unit (ICU). We …nd that the length of stay for patients admitted to the ICU is in ‡uenced by the occupancy level of the ICU. In particular, a patient is likely to be discharged early when the occupancy in the ICU is high. This in turn leads to an increased likelihood of the patient having to be readmitted to the ICU at a later time. Such "bounce-backs" have implications for the overall ICU e¤ective capacity -an early discharge immediately frees up capacity, but at the risk of a (potentially much higher) capacity requirement when the patient needs to be readmitted. We analyze these capacity implications, shedding light on the question if an ICU should apply an aggressive discharge strategy or if it should follow the old quality slogan and "do it right the …rst time." By comparing the total capacity usage for patients who were discharged early versus those who were not, we show that an aggressive discharge policy applied to patients with lower clinical severity levels frees up capacity in the ICU. However, we …nd that an increased number of readmissions of patients with high clinical severity levels occur when the ICU is capacity constrained, thereby e¤ectively reducing peak bed capacity.

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Section: Literature Reviewmentioning

confidence: 92%

An Econometric Analysis of Patient Flows in the Cardiac Intensive Care Unit

Terwiesch

2012

M&SOM

Self Cite

208

135

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“…We evaluate worker productivity by using the measure of completion time. In the operations management literature, the length of time it takes to complete a task is a commonly used metric to assess individual productivity (e.g., Reagans, Argote and Brooks 2005;KC and Terwiesch 2009). To calculate completion time, we take the natural log of the number of minutes a worker spent to complete the focal task.…”

Section: Dependent Variablementioning

confidence: 99%

“…Research finds that workers may increase their service rate in response to an increased load (Schultz et al 1998;KC and Terwiesch 2009 …”

Section: Loadmentioning

confidence: 99%

“…Consequently, organizations employ a variety of strategies to boost worker productivity. These strategies include workflow designs to avoid system bottlenecks as well as incentives and varying task assignments to increase workers' motivation and capitalize on their abilities (e.g., KC and Terwiesch, 2009;Schultz, Schoenherr, and Nembhard, 2010;Staats and Gino, 2012). However, these strategies often fail to account for powerful exogenous factors, such as weather conditions on a given day, that may influence worker productivity.…”

Section: Introductionmentioning

confidence: 99%

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Rainmakers: Why bad weather means good productivity.

Lee¹,

Gino²,

Staats³

2014

Journal of Applied Psychology

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People believe that weather conditions influence their everyday work life, but to date, little is known about how weather affects individual productivity. Most people believe that bad weather conditions reduce productivity. In this research, we predict and find just the opposite. Drawing on cognitive psychology research, we propose that bad weather increases individual productivity by eliminating potential cognitive distractions resulting from good weather. When the weather is bad, individuals may focus more on their work rather than thinking about activities they could engage in outside of work. We tested our hypotheses using both field and lab data. First, we use field data on employees' productivity from a mid-size bank in Japan, which we then match with daily weather data to investigate the effect of bad weather conditions (in terms of precipitation, visibility, and temperature) on productivity. Second, we use a laboratory experiment to examine the psychological mechanism explaining the relationship between bad weather and increased productivity. Our findings support our proposed model and suggest that worker productivity is higher on bad rather than good weather days. We discuss the implications of our findings for workers and managers.

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“…The increase in workload not only affects the speed and the quality of the primary service (see KC and Terwiesch (2009)), but also compromises the ancillary activities that are secondary to the quality of outcomes while essential to generating income. Moreover, this has implications for the optimal design of prospective reimbursement systems in healthcare and elsewhere as it shows that the ability to accurately observe the system, a critical factor in the successful implementation of prospective reimbursements, may depend on the workload level the system is subjected to.…”

Section: Introductionmentioning

confidence: 99%

Physician Workload and Hospital Reimbursement: Overworked Physicians Generate Less Revenue per Patient

Powell

Savin

Savva

2012

M&SOM

116

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We study the impact of physician workload on hospital reimbursement utilizing a detailed data set from the trauma department of a major urban hospital. We find that the proportion of patients assigned a "highseverity" status for reimbursement purposes, which maps, on average, to a 47.8% higher payment for the hospital, is substantially reduced as the workload of the discharging physician increases. This effect persists after we control for a number of systematic differences in patient characteristics, condition and time of discharge. Furthermore, we show that it is unlikely to be caused by selection bias or endogeneity in either discharge timing or allocation of discharges to physicians. We attribute this phenomenon to a workloadinduced reduction in diligence of paperwork execution. We estimate the associated monetary loss to be approximately 1.1% (95% Confidence Interval 0.4% − 1.9%) of the department's annual revenue.

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Impact of Workload on Service Time and Patient Safety: An Econometric Analysis of Hospital Operations

Cited by 425 publications

References 25 publications

An Econometric Analysis of Patient Flows in the Cardiac Intensive Care Unit

An Econometric Analysis of Patient Flows in the Cardiac Intensive Care Unit

Rainmakers: Why bad weather means good productivity.

Physician Workload and Hospital Reimbursement: Overworked Physicians Generate Less Revenue per Patient

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