The organizational context of ethical dilemmas: a role-playing simulation for the intensive care unit

The allocation of health care resources often requires decision makers to balance conflicting ethical principles. The resource-constrained intensive care unit (ICU) provides an ideal setting to study how decision makers go about their balancing act in a complex and dynamic environment. The author presents a role-playing simulation exercise which models ICU admission and discharge decision making. Designed for the class-room, the simulation engages a variety of ethical, managerial, and public policy issues including end-of-life decision making, triage, and rationing. The simulation is based on a sequence of scenarios or "decision rounds" delineating conditions in the ICU in terms of disposition of ICU patients, number of available ICU beds, prognoses of candidates for admission, and other physiological and organizational information. Students, playing the roles of attending physician, hospital administrator, nurse manager, triage officer, and ethics committee member, are challenged to reach consensus in the context of multiple power centers and conflicting goals. An organization theory perspective, incorporated into the simulation, provides insight on how decisions are actually made and stimulates discussion on how decision making might be improved.     

The costs of nonbeneficial treatment in the intensive care setting

Ethics consultations have been shown to reduce the use of "nonbeneficial treatments," defined as life-sustaining treatments delivered to patients who ultimately did not survive to hospital discharge, when treatment conflicts occurred in the adult intensive care unit (ICU). In this paper we estimated the costs of nonbeneficial treatment using the results from a randomized trial of ethics consultations. We found that ethics consultations were associated with reductions in hospital days and treatment costs among patients who did not survive to hospital discharge. We conclude that consultations resolved conflicts that would have inappropriately prolonged nonbeneficial or unwanted treatments in the ICU instead of focusing on more appropriate comfort care.     

The hospital-survival and prognostic factors of patients with solid tumors admitted to an ICU

The decision to admit a patient with cancer to the intensive care unit (ICU) is complex. There are limited data as to the outcome and prognostic factors of patients with solid tumors admitted to the ICU. A retrospective chart review was undertaken to evaluate this issue. Over an 18-month period, 147 patients with solid tumors were admitted to our ICU. Lung, colorectal, and breast were the commonest sites of the primary tumors, with 52% of patients having metastatic disease. A total of 79 (54%) patients survived to hospital discharge, with 50 (34%) patients being discharged to home. Metastatic disease and the requirement for vasopressor agents were independent predictors of poor outcome. The relatively high survival rate of this cohort of patients should prompt a reevaluation of the ICU admission criteria for patients with solid tumors who become critically ill.     

Value of performing active surveillance cultures on intensive care unit discharge for detection of methicillin-resistant Staphylococcus aureus.

OBJECTIVE: To quantify the value of performing active surveillance cultures for detection of methicillin-resistant Staphylococcus aureus (MRSA) on intensive care unit (ICU) discharge. DESIGN: Prospective cohort study. SETTING: Medical ICU (MICU) and surgical ICU (SICU) of a tertiary care hospital. PARTICIPANTS: We analyzed data on adult patients who were admitted to the MICU or SICU between January 17, 2001, and December 31, 2004. All participants had a length of ICU stay of at least 48 hours and had surveillance cultures of anterior nares specimens performed on ICU admission and discharge. Patients who had MRSA-positive clinical cultures in the ICU were excluded. RESULTS: Of 2,918 eligible patients, 178 (6%) were colonized with MRSA on ICU admission, and 65 (2%) acquired MRSA in the ICU and were identified by results of discharge surveillance cultures. Patients with MRSA colonization confirmed by results of discharge cultures spent 853 days in non-ICU wards after ICU discharge, which represented 27% of the total number of MRSA colonization-days during hospitalization in non-ICU wards for patients discharged from the ICU. CONCLUSIONS: Surveillance cultures of nares specimens collected at ICU discharge identified a large percentage of MRSA-colonized patients who would not have been identified on the basis of results of clinical cultures or admission surveillance cultures alone. Furthermore, these patients were responsible for a large percentage of the total number of MRSA colonization-days during hospitalization in non-ICU wards for patients discharged from the ICU.     

A Pragmatic Randomised,Controlled Trial of Intensive Care follow up programmes in improving Longer-term outcomes from critical illness. The PRACTICAL study

Background  

A number of intensive care (ICU) patients experience significant problems with physical, psychological, and social functioning for some time after discharge from ICU. These problems have implications not just for patients, but impose a continuing financial burden for the National Health Service. To support recovery, a number of hospitals across the UK have developed Intensive Care follow-up clinics. However, there is a lack of evidence base to support these, and this study aims to test the hypothesis that intensive care follow up programmes are effective and cost-effective at improving physical and psychological quality of life in the year after intensive care discharge.     

Predicting the length of stay of patients admitted for intensive care using a first step analysis

For patients admitted to intensive care units (ICU), the length of stay in different destinations after the first day of ICU admission, has not been systematically studied. We aimed to estimate the average length of stay (LOS) of such patients in Colombia, using a discrete time Markov process. We used the maximum likelihood method and Markov chain modeling to estimate the average LOS in the ICU and at each destination after discharge from intensive care. Six Markov models were estimated, describing the LOS in each one of the Cardiovascular, Neurological, Respiratory, Gastrointestinal, Trauma and Other diagnostic groups from the ultimate primary reason for admission to ICU. Possible destinations were: the intensive care unit, ward in the same hospital, the high dependency unit/intermediate care area in the same hospital, ward in other hospital, intensive care unit in other hospital, other hospital, other location same hospital, discharge from same hospital and death. The stationary property was tested and using a split-sample analysis, we provide indirect evidence about the appropriateness of the Markov property. It is not possible to use a unique Markov chain model for each diagnostic group. The length of stay varies across the ultimate primary reason for admission to intensive care. Although our Markov models shown to be predictive, the fact that current available statistical methods do not allow us to verify the Markov property test is a limitation. Clinicians may be able to provide information about the hospital LOS by diagnostic groups for different hospital destinations.     

A Clinical Database-Driven Approach to Decision Support: Predicting Mortality Among Patients with Acute Kidney Injury

In exploring an approach to decision support based on information extracted from a clinical database, we developed mortality prediction models of intensive care unit (ICU) patients who had acute kidney injury (AKI) and compared them against the Simplified Acute Physiology Score (SAPS). We used MIMIC, a public de-identified database of ICU patients admitted to Beth Israel Deaconess Medical Center, and identified 1400 patients with an ICD9 diagnosis of AKI and who had an ICU stay > 3 days. Multivariate regression models were built using the SAPS variables from the first 72 hours of ICU admission. All the models developed on the training set performed better than SAPS (AUC = 0.64, Hosmer-Lemeshow p < 0.001) on an unseen test set; the best model had an AUC = 0.74 and Hosmer-Lemeshow p = 0.53. These findings suggest that local customized modeling might provide more accurate predictions. This could be the first step towards an envisioned individualized point-of-care probabilistic modeling using one's clinical database.     

Managing admission and discharge processes in intensive care units

The intensive care unit (ICU) is one of the most crucial and expensive resources in a health care system. While high fixed costs usually lead to tight capacities, shortages have severe consequences. Thus, various challenging issues exist: When should an ICU admit or reject arriving patients in general? Should ICUs always be able to admit critical patients or rather focus on high utilization? On an operational level, both admission control of arriving patients and demand-driven early discharge of currently residing patients are decision variables and should be considered simultaneously. This paper discusses the trade-off between medical and monetary goals when managing intensive care units by modeling the problem as a Markov decision process. Intuitive, myopic rule mimicking decision-making in practice is applied as a benchmark. In a numerical study based on real-world data, we demonstrate that the medical results deteriorate dramatically when focusing on monetary goals only, and vice versa. Using our model, we illustrate the trade-off along an efficiency frontier that accounts for all combinations of medical and monetary goals. Coming from a solution that optimizes monetary costs, a significant reduction of expected mortality can be achieved at little additional monetary cost.

     

Economic evaluation of nurse-led intensive care follow-up programmes compared with standard care: the PRaCTICaL trial

Objective

Following intensive care discharge, many patients suffer severe physical and psychological morbidity and a continuing high use of health services. Follow-up programmes have been proposed to improve the outcomes for these patients. We tested the hypothesis that nurse-led intensive care follow-up programmes are cost-effective.

Methods

A pragmatic, multicentre, randomised controlled trial of nurse-led intensive care unit follow-up programmes versus standard care. A cost-utility analysis was conducted after 12 months' follow-up to compare the two interventions. Costs were assessed from the perspective of the UK NHS and outcomes were measured in quality-adjusted life years (QALYs) based upon responses to the EQ-5D administered at baseline, 6 and 12 months.

Results

A total of 286 patients were recruited to the trial. Total mean cost was £5,789 for standard care and £7,577 for the discharge clinic. The adjusted difference in means was £2,435 [95 % confidence interval (CI) ?297 to 5,566]. Mean QALYs were 0.58 for standard care and 0.60 for the discharge clinic. The adjusted mean difference was ?0.003 (95 % CI ?0.066 to 0.060). If society were willing to pay £20,000 per QALY then there would be a 93 % chance that standard care would be considered most efficient.

Conclusions

A nurse-led intensive care unit (ICU) follow-up programme showed no evidence of being cost-effective at 12 months. Further work should focus on evidence-based development of discharge clinic services and current ICU follow-up programmes should review their practice in light of these results.     

Operations research in intensive care unit management: a literature review

The intensive care unit (ICU) is a crucial and expensive resource largely affected by uncertainty and variability. Insufficient ICU capacity causes many negative effects not only in the ICU itself, but also in other connected departments along the patient care path. Operations research/management science (OR/MS) plays an important role in identifying ways to manage ICU capacities efficiently and in ensuring desired levels of service quality. As a consequence, numerous papers on the topic exist. The goal of this paper is to provide the first structured literature review on how OR/MS may support ICU management. We start our review by illustrating the important role the ICU plays in the hospital patient flow. Then we focus on the ICU management problem (single department management problem) and classify the literature from multiple angles, including decision horizons, problem settings, and modeling and solution techniques. Based on the classification logic, research gaps and opportunities are highlighted, e.g., combining bed capacity planning and personnel scheduling, modeling uncertainty with non-homogenous distribution functions, and exploring more efficient solution approaches.     

Inside the black box of shared decision making: distinguishing between the process of involvement and who makes the decision

BACKGROUND: Shared decision making has practical implications for everyday health care. However, it stems from largely theoretical frameworks and is not widely implemented in routine practice. AIMS: We undertook an empirical study to inform understanding of shared decision making and how it can be operationalized more widely. METHOD: The study involved patients visiting UK general practitioners already well experienced in shared decision making. After these consultations, semi-structured telephone interviews were conducted and analysed using the constant comparative method of content analysis. RESULTS: All patients described at least some components of shared decision making but half appeared to perceive the decision as shared and half as 'patient-led'. However, patients exhibited some uncertainty about who had made the decision, reflecting different meanings of decision making from those described in the literature. A distinction is indicated between the process of involvement (option portrayal, exchange of information and exploring preferences for who makes the decision) and the actual decisional responsibility (who makes the decision). The process of involvement appeared to deliver benefits for patients, not the action of making the decision. Preferences for decisional responsibility varied during some consultations, generating unsatisfactory interactions when actual decisional responsibility did not align with patient preferences at that stage of a consultation. However, when conducted well, shared decision making enhanced reported satisfaction, understanding and confidence in the decisions. CONCLUSIONS: Practitioners can focus more on the process of involving patients in decision making rather than attaching importance to who actually makes the decision. They also need to be aware of the potential for changing patient preferences for decisional responsibility during a consultation and address non-alignment of patient preferences with the actual model of decision making if this occurs.     

Model Parameter Estimation and Uncertainty: A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force-6

A model's purpose is to inform medical decisions and health care resource allocation. Modelers employ quantitative methods to structure the clinical, epidemiological, and economic evidence base and gain qualitative insight to assist decision makers in making better decisions. From a policy perspective, the value of a model-based analysis lies not simply in its ability to generate a precise point estimate for a specific outcome but also in the systematic examination and responsible reporting of uncertainty surrounding this outcome and the ultimate decision being addressed. Different concepts relating to uncertainty in decision modeling are explored. Stochastic (first-order) uncertainty is distinguished from both parameter (second-order) uncertainty and from heterogeneity, with structural uncertainty relating to the model itself forming another level of uncertainty to consider. The article argues that the estimation of point estimates and uncertainty in parameters is part of a single process and explores the link between parameter uncertainty through to decision uncertainty and the relationship to value of information analysis. The article also makes extensive recommendations around the reporting of uncertainty, in terms of both deterministic sensitivity analysis techniques and probabilistic methods. Expected value of perfect information is argued to be the most appropriate presentational technique, alongside cost-effectiveness acceptability curves, for representing decision uncertainty from probabilistic analysis.     

The Potential Cost-Effectiveness of a Machine Learning Tool That Can Prevent Untimely Intensive Care Unit Discharge

ObjectivesThe machine learning prediction model Pacmed Critical (PC), currently under development, may guide intensivists in their decision-making process on the most appropriate time to discharge a patient from the intensive care unit (ICU). Given the financial pressure on healthcare budgets, this study assessed whether PC has the potential to be cost-effective compared with standard care, without the use of PC, for Dutch patients in the ICU from a societal perspective.MethodsA 1-year, 7-state Markov model reflecting the ICU care pathway and incorporating the PC decision tool was developed. A hypothetical cohort of 1000 adult Dutch patients admitted in the ICU was entered in the model. We used the literature, expert opinion, and data from Amsterdam University Medical Center for model parameters. The uncertainty surrounding the incremental cost-effectiveness ratio was assessed using deterministic and probabilistic sensitivity analyses and scenario analyses.ResultsPC was a cost-effective strategy with an incremental cost-effectiveness ratio of €18 507 per quality-adjusted life-year. PC remained cost-effective over standard care in multiple scenarios and sensitivity analyses. The likelihood that PC will be cost-effective was 71% at a willingness-to-pay threshold of €30 000 per quality-adjusted life-year. The key driver of the results was the parameter “reduction in ICU length of stay.”ConclusionsWe showed that PC has the potential to be cost-effective for Dutch ICUs in a time horizon of 1 year. This study is one of the first cost-effectiveness analyses of a machine learning device. Further research is needed to validate the effectiveness of PC, thereby focusing on the key parameter “reduction in ICU length of stay” and potential spill-over effects.     

Using an intervention mapping approach to develop a discharge protocol for intensive care patients

Background

Admission into an intensive care unit (ICU) may result in long-term physical, cognitive, and emotional consequences for patients and their relatives. The care of the critically ill patient does not end upon ICU discharge; therefore, integrated and ongoing care during and after transition to the follow-up ward is pivotal. This study described the development of an intervention that responds to this need.

Methods

Intervention Mapping (IM), a six-step theory- and evidence-based approach, was used to guide intervention development. The first step, a problem analysis, comprised a literature review, six semi-structured telephone interviews with former ICU-patients and their relatives, and seven qualitative roundtable meetings for all eligible nurses (i.e., 135 specialized and 105 general ward nurses). Performance and change objectives were formulated in step two. In step three, theory-based methods and practical applications were selected and directed at the desired behaviors and the identified barriers. Step four designed a revised discharge protocol taking into account existing interventions. Adoption, implementation and evaluation of the new discharge protocol (IM steps five and six) are in progress and were not included in this study.

Results

Four former ICU patients and two relatives underlined the importance of the need for effective discharge information and supportive written material. They also reported a lack of knowledge regarding the consequences of ICU admission. 42 ICU and 19 general ward nurses identified benefits and barriers regarding discharge procedures using three vignettes framed by literature. Some discrepancies were found. For example, ICU nurses were skeptical about the impact of writing a lay summary despite extensive evidence of the known benefits for the patients. ICU nurses anticipated having insufficient skills, not knowing the patient well enough, and fearing legal consequences of their writings. The intervention was designed to target the knowledge, attitudes, self-efficacy, and perceived social influence. Building upon IM steps one to three, a concept discharge protocol was developed that is relevant and feasible within current daily practice.

Conclusion

Intervention mapping provided a comprehensive framework to improve ICU discharge by guiding the development process of a theory- and empirically-based discharge protocol that is robust and useful in practice.

     

Oxidative stress status: possible guideline for clinical management of critically ill patients

BACKGROUND: Critical care medicine has developed in the last few years into a separate scientific discipline and studies related to the outcome after intensive care usually suggest a long hospital stay that becomes cost prohibitive. The majority of problems (death) amongst critically ill patients requiring critical care involve sepsis, inflammation, tissue damage-oxidative stress, oxygen tension PO2, lipid peroxidation. The present investigation involves monitoring of serum levels of MDA, SOD as a possible guideline for severity of clinical situations in critically ill patients. METHODS: Fifty critically ill heterogeneous patients requiring intensive care in the ICU of IKDRC were selected as subjects with ages varying from 17 to 75 years. Serum levels of MDA (ng/ml), SOD (U/ml) were determined right from admission to discharge due to improvement / DAMA / death. MDA and SOD were estimated according to the methods of Buege and Aust et al. (1978), Nandi and Chatterji (1988). RESULTS: Critically ill patients irrespective of the disease process indicated significantly very high serum levels of MDA and low levels of SOD at the time of admission (13.28+/-4.26 ng/ml, 3.80+/-2.60 U/ml, respectively) according to the severity of the prevalent clinical situation. The pattern of serum levels of MDA and SOD according to subsequent clinical performance did indicate a decreasing trend of MDA (oxidant) and fluctuating trend of SOD (antioxidant enzyme except in those who inevitably succumbed to death in spite of adequate clinical management. CONCLUSIONS: The results of the present study have amply revealed the utility and relevance of monitoring oxidative stress in critically ill patients as biochemical markers, cost-effectiveness and role in decision making (withdrawal/continuation of different support modalities) as deemed fit.     

Intensive Care Unit Utilization and Interhospital Transfers As Potential Indicators of Rural Hospital Quality

CONTEXT: Obtaining meaningful information from statistically valid and reliable measures of the quality of care for disease-specific care provided in small rural hospitals is limited by small numbers of cases and different definitive care capacities. An alternative approach may be to aggregate and analyze patient services that reflect more generalized care processes. PURPOSE: To evaluate the applicability of intensive care unit (ICU) utilization and interhospital transfers as potential indicators of quality in rural hospitals. METHODS: Secondary data analysis of ICU utilization and interhospital transfer practices in Iowa's Critical Access (CAH), rural, rural referral, and urban hospitals. FINDINGS: Rural hospitals have fewer resources, provide a more limited range of definitive care services, and rely to a greater extent on transferring patients to other hospitals capable of providing the required definitive care. Examining ICU utilization and interhospital transfer patterns we found (1) that lower percentages of patients receive ICU care in smaller facilities; (2) higher transfer rates for both ICU and non-ICU patients in CAH hospitals; (3) shorter average lengths of stay for ICU patients from smaller hospitals who were transferred; and (4) lower mortality rates for CAH and rural hospital ICU patients. CONCLUSIONS: Examining ICU utilization and interhospital transfer patterns offers potential insights into rural hospital quality measurement and comparisons.     

Parental involvement in neonatal critical care decision‐making

The article analyses the decision‐making process between doctors and parents of babies in neonatal intensive care. In particular, it focuses on cases in which the decision concerns the redirection of care from full intensive care to palliative care at the end of life. Thirty one families were recruited from a neonatal intensive care unit in England and their formal interactions with the doctor recorded. The conversations were transcribed and analysed using conversation analysis. Analysis focused on sequences in which decisions about the redirection of care were initiated and progressed. Two distinct communicative approaches to decision‐making were used by doctors: ‘making recommendations’ and ‘providing options’. Different trajectories for parental involvement in decision‐making were afforded by each design, as well as differences in terms of the alignments, or conflicts, between doctors and parents. ‘Making recommendations’ led to misalignment and reduced opportunities for questions and collaboration; ‘providing options’ led to an aligned approach with opportunities for questions and fuller participation in the decision‐making process. The findings are discussed in the context of clinical uncertainty, moral responsibility and the implications for medical communication training and guidance. A Virtual Abstract of this paper can be accessed at: https://www.youtube.com/watch?v=MyuymxDNupk&feature=youtu.be     

Value of information of a clinical prediction rule: informing the efficient use of healthcare and health research resources

OBJECTIVES: The aim of this study was to estimate the potential cost-effectiveness and expected value of perfect information of a recently derived clinical prediction rule for patients presenting to emergency departments with chest discomfort. METHODS: A decision analytic model was constructed to compare the Early Disposition Prediction Rule (EDPR) with the current standard of care. Results were used to calculate the potential cost-effectiveness of the EDPR, as well as the Value of Information in conducting further research. Study subjects were adults presenting with chest discomfort to two urban emergency departments in Vancouver, British Columbia, Canada. The clinical prediction rule identifies patients who are eligible for early discharge within 3 hours of presentation to the emergency department. The outcome measure used was inappropriate emergency department discharge of patients with acute coronary syndrome (ACS). RESULTS: The incremental cost-effectiveness ratio of the EDPR in comparison to usual care was (negative) $2,999 per inappropriate ACS discharge prevented, indicating a potential cost-savings in introducing the intervention. The expected value of perfect information was $16.3 million in the first year of implementation, suggesting a high benefit from conducting further research to validate the decision rule. CONCLUSIONS: The EDPR is likely to be cost-effective; however, given the high degree of uncertainty in the estimates of costs and patient outcomes, further research is required to inform the decision to implement the intervention. The potential health and monetary benefits of this clinical prediction rule outweigh the costs of doing further research.     

The cultural meaning attributed to the intensive care unit by patients and their parents: a link between the edge of the abysm and freedom

The purpose of this ethnographic study was to identify the cultural meaning that patients in an intensive care unit and their relatives attribute to the hospitalization process. Data were collected by means of participant observation and interviews with 17 participants (clients and their family), during hospitalization. Data were classified in tree categories: 1) ICU, the abysm border: a strange and scary place; 2) ICU: the link between the abysm border and freedom; 3) discharge from ICU: freedom of life. The main theme was: "Intensive Care Unit--a link between abysm border and freedom". Authors considered relevant to unveil the cultural meanings involved in the situation in order to provide elements for a personalized care to the client and family.