Directions: please follow explicitly *** primarily this assignment is filling in the tables- attached all articles to use **** Use the attached “Literature Evaluation Table to complete this assignme
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All Rights Reserved. Copyright © 2020 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. 1752 www.ccmjournal.org December 2020 • Volume 48 • Number 12 Objectives: Growing evidence supports the Awakening and Breathing Coordination, Delirium monitoring/management, and Early exercise/mobility (ABCDE) bundle processes as improving a number of short- and long-term clinical outcomes for patients requiring ICU care. To assess the cost-effectiveness of this inter- vention, we determined the impact of ABCDE bundle adherence on inpatient and 1-year mortality, quality-adjusted life-years, length of stay, and costs of care. Design: We conducted a 2-year, prospective, cost-effectiveness study in 12 adult ICUs in six hospitals belonging to a large, inte- grated healthcare delivery system. Setting: Hospitals included a large, urban tertiary referral center and five community hospitals. ICUs included medical/surgical, trauma, neurologic, and cardiac care units. Patients: The study included 2,953 patients, 18 years old or older, with an ICU stay greater than 24 hours, who were on a ventilator for more than 24 hours and less than 14 days. Intervention: ABCDE bundle. Measurements and Main Results: We used propensity score- adjusted regression models to determine the impact of high bundle adherence on inpatient mortality, discharge status, length of stay, and costs. A Markov model was used to estimate the potential effect of improved bundle adherence on health- care costs and quality-adjusted life-years in the year follow- ing ICU admission. We found that patients with high ABCDE bundle adherence (≥ 60%) had significantly decreased odds of inpatient mortality (odds ratio 0.28) and significantly higher costs ($3,920) of inpatient care. The incremental cost-effec- tiveness ratio of high bundle adherence was $15,077 (95% CI, $13,675–$16,479) per life saved and $1,057 per life-year saved. High bundle adherence was associated with a 0.12 in- crease in quality-adjusted life-years, a $4,949 increase in 1-year care costs, and an incremental cost-effectiveness ratio of $42,120 per quality-adjusted life-year. Conclusions: The ABCDE bundle appears to be a cost-effective means to reduce in-hospital and 1-year mortality for patients with an ICU stay. (Crit Care Med 2020; 48:1752–1759) Key Words: cost-effectiveness; critical care; delirium T he provision of critical care is associated with high rates of morbidity and mortality and is a major source of healthcare expenditures in the United States (1). Stud- ies have shown that 20–80% of patients in the ICU develop delirium as a complication of care (2). ICU-acquired delirium is independently associated with increased cognitive and phys- ical impairment, mortality, hospital length of stay (LOS), and healthcare costs (3–10). In a recent study, Vasilevskis et al (11) found that the additional costs of care attributable to ICU de- lirium ranged from $11,132 to $23,497 per patient, and a pre- vious study reported that delirium costs $152 billion dollars annually in the United States (12). Cost-effective, scalable interventions that ameliorate ICU- acquired delirium and facilitate ventilator liberation are important for improving delivery of care and outcomes in crit- ically ill patients. The Awakening and Breathing Coordination, Delirium monitoring/management, and Early exercise/mo- bility (ABCDE) bundle (Supplemental Table 1, Supplemental Digital Content 1, http://links.lww.com/CCM/F811) is an in- terdisciplinary, multicomponent patient safety intervention designed to reduce prevalence of delirium in ICUs by improv- ing collaboration among clinical team members, standardizing care processes, and breaking the cycle of oversedation and pro- longed ventilation (13–18). Studies examining the effectiveness of the ABCDE bundle have shown significant reductions in de- lirium prevalence, ventilator days, coma days, readmission, and in-hospital mortality, and a significant increase in the number of patients who were mobilized out of bed during their ICU stay and discharged home, but few have examined its cost ef- fectiveness (2, 19–23). The objective of this study was to deter – mine the impact of ABCDE processes on inpatient mortality, LOS, discharge status, and direct costs of care (from a payer perspective), with mortality and cost outcomes serving as a basis to evaluate the cost-effectiveness of bundle adherence. DOI: 10.1097/CCM.0000000000004609 *See also p. 1897. All authors: Center for Clinical Effectiveness, Baylor Scott & White Health, Dallas, TX. Copyright © 2020 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Evaluating the Cost-Effectiveness of the ABCDE Bundle: Impact of Bundle Adherence on Inpatient and 1-Year Mortality and Costs of Care* Ashley W. Collinsworth, ScD, MPH; Elisa L. Priest, DrPH; Andrew L. Masica, MD, MSCI Copyright © 2020 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Clinical Investigations Critical Care Medicine www.ccmjournal.org 1753 MATERIALS AND METHODS Overview This cost-effective analysis was a component of a larger ABCDE bundle implementation study that began in July 2012 in 12 ICUs of six Baylor Scott & White Health (BSWH) hospitals in- cluding a large, urban tertiary referral center and five com- munity hospitals. ICUs included medical/surgical, trauma, neurologic, and cardiac care units. The ABCDE bundle incor – porates several individual evidence-based critical care processes. Since the prospective phase of the study was performed, the bundle has been modified slightly to include additional com- ponents (pain assessment/management and family engage- ment), and the ICU liberation approach endorsed by the Society of Critical Care Medicine is now the “ABCDEF bundle” (24). The number of care processes a patient is eligible for on a given day depends on whether or not the patient is ventilated and passes the appropriate screening criteria. Different strategies were em- ployed to improve bundle adherence in study ICUs during the first year of the study including modification of the electronic health record (EHR) to facilitate uptake and documentation of bundle elements, staff training, clinical champions, and monthly perfor – mance reports (25). Given the EHR modifications went live in July 2013, altered the documentation of bundle adherence, and likely improved the reliability and validity of the adherence data, we lim- ited this cost-effectiveness analysis to the observations obtained in the 2 years following the EHR modifications. This study was reviewed and approved by the BSWH Institutional Review Board. Patients The 2,953 patients admitted to study ICUs from July 2013 to June 2015 who were greater than or equal to 18 years old, had an ICU admission greater than 24 hours, and were on a ven- tilator for greater than 24 hours and less than 14 days were included. Patients were excluded if they were on comfort care; were awaiting a transfer order to a non-ICU bed; had a primary diagnosis of brain tumor, mental disorder, stroke, intracranial injury, or poisoning; or had a hospital stay greater than 30 days. Study Design We used a prospective, quasi-experimental design to examine differences in bundle adherence on in-hospital mortality, LOS, and cost outcomes. We then conducted an exploratory cost-ef- fectiveness analysis using a Markov model to estimate differ – ences in 1-year costs and quality-adjusted life-years (QALYs) for patients with low and high levels of bundle adherence from a payer perspective. Outcome Measures We examined differences in in-hospital mortality, LOS, dis- charge status, and direct costs of hospital care among patients with varying levels of bundle adherence. Bundle adherence was calculated as the total number of care processes a patient re- ceived divided by the total number of care processes the patient was eligible for during the ICU stay. Given that the bundle con- sisted of multiple daily care processes, few patients had 100% adherence. Recognizing the potential of partial adherence to improve outcomes, we examined differences between patients with high and low bundle adherence, with high adherence de- fined as receiving greater than or equal to 60% of bundle ele- ments based on the mean level of adherence obtained in sites following ABCDE bundle implementation efforts, rather than using an all-or-none adherence measure (26). We also esti- mated differences in costs and QALYs for patients with low and high bundle adherence in the year following ICU admission. Data Sources Process measures, demographics, and outcomes data were col- lected from the EHR and administrative databases. The cost of inpatient care was calculated as the direct care cost for each patient and was obtained from the Trendstar clinical costing system. These costs included the costs of any additional patient services, with the exception of overhead or physician fees, asso- ciated with bundle application. The cost of bundle implemen- tation was approximately $165,000 and included salary support (1.65 full-time equivalents) for the project lead, project man- ager, clinical champions, information technology personnel for EHR modifications, and data analysts plus the cost of trainings and visual aids. These sunk costs were excluded from the cost calculation. Costs were adjusted to 2013 dollars using the med- ical component of the consumer price index (27). Postacute care costs were estimated from 2014 Medicare average payments for patients based on discharge status (28). One-year mortality rates and QALYs based on discharge status were obtained from a 1-year prospective economic evaluation of patients who received prolonged ventilation in an academic medical center ICU (29, 30). Statistical Analysis We conducted a univariate analysis to examine unadjusted differences in patient characteristics and outcomes. We com- pared differences in continuous variables and outcomes that did not violate normality assumptions with independent t tests and differences in categorical variables and outcomes with chi- square and Fisher exact tests. Because patients with greater severity of illness and risk of mortality were more likely to have low levels of bundle ad- herence, propensity score adjustment was used to reduce the impact of selection bias on the association between bundle ad- herence and the outcomes of interest. The propensity score, the conditional probability of a patient having high bundle adher – ence, was determined from a multivariable logistic regression model based on findings from the literature (Supplemental Table 2, Supplemental Digital Content 2, http://links.lww.com/ CCM/F812). Propensity score-adjusted effects of bundle ad- herence on inpatient mortality and discharge status were mod- eled using logistic regression. A generalized linear model with a log link function and a gamma distribution was used to model direct costs due the highly skewed nature of the data (31). All statistical analyses were conducted using SAS 9.4 (SAS Institute, Cary, NC). Statistical significance was indicated at the α less than 0.05 level. Copyright © 2020 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Copyright © 2020 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Collinsworth et al 175 4 www.ccmjournal.org December 2020 • Volume 48 • Number 12 Cost-Effectiveness Analysis Potential patient life-years saved were calculated by estimating the number of life-years lost for each patient who died. Life expectancy was projected based on the age and sex of the pa- tient using the Social Security Administration’s actuarial life tables for 2010 (32), discounted based on the 5-year survival for patients discharged from ICUs compared with the general population (33). We calculated life-years saved as the differ – ence in projected life expectancy and the age of the patient at the time of death. We used recycled predictions to estimate the effect of high versus low adherence on outcomes. Outcomes were predicted from the modeled equations based on every patient having high adherence and every patient having low adherence. The difference between these two predictions constituted the pre- dicted mean differences in outcomes between groups. We gen- erated 1,000 bootstraps of this process to estimate the mean differences in outcomes and ses of these statistics. Bootstrap estimates obtained were used as inputs in the Markov model (Fig. 1) created with TreeAge Pro (TreeAge Software, LLC, Williamstown, MA) along with the 1-year mor – tality risks, QALYs, and costs of care obtained from the litera- ture (Supplemental Table 3, Supplemental Digital Content 3, http://links.lww.com/CCM/F813). Life expectancy estimates for the patients who died in the year following discharge were based on LOS averages for each discharge location. We assumed a life expectancy of 30 days for patients who died after being discharged home or to home health. We calculated the 1-year incremental cost effectiveness of high bundle adherence as the ratio of incremental healthcare costs in the year following ICU admission to the incremental effects (QALYs). RESULTS A total of 2,953 eligible patients received care in the study ICUs from July 2013 to June 2015. After excluding patients with missing data, we found that 1,710 (57.9%) had high (≥ 60%) bundle adherence. Patients in the low adherence group had significantly higher all patient refined diagnosis re- lated groups Severity, Risk of Mortality, and Acute Physiology and Chronic Health Evaluation II scores indicating greater ill- ness severity (Table 1). Among the 684 patients who died in the low (< 60%) bundle adherence group, 431 (63.0%) were eligible for 10 or fewer bundle elements. Of the 318 patients who died in the high adherence group, only 57 (17.9%) were eligible for 10 or fewer bundle elements. After risk-adjustment using propensity scores, patients with bundle adherence greater than or equal to 60% had decreased odds of mortality (0.28) (Table 2). Patients with higher levels of bundle adherence had significantly increased odds of being discharged home, to home health, inpatient rehabilitation, and to a skilled nursing facility. Hospital LOS and direct costs were significantly higher in patients with bundle adherence greater than or equal to 60%, after risk adjustment. Rates of risk-adjusted compliance varied across the 12 study ICUs, but patients in cardiac ICUs were significantly less likely to have high bundle adherence compared with patients in medical/ surgical ICUs (Supplemental Table 1, Supplemental Digital Content 1, http://links.lww.com/CCM/F811). The mean effect of ABCDE bundle adherence greater than or equal to 60% on inpatient mortality and costs obtained from the bootstrap analysis was a reduction in mortality (48% vs 22%) and a $4,949 increase in direct inpatient costs (Supplemental Table 3, Supplemental Digital Content 3, http:// links.lww.com/CCM/F813). Potential life-years saved were estimated at 14.3 years per patient. Based on the inpatient mortality rates observed in the included ICUs, the incremental cost-effectiveness ratio (ICER) was calculated as $15,077 per life saved and $1,057 per life-year saved (Table 3). The 95% CI per life saved calculated by applying Fieller’s method from the bootstrap estimates was $13,675–$16,479. In the exploratory cost-effectiveness analysis using a Markov model and QALY and cost inputs from the literature to estimate potential differ - ences in outcomes and costs at 1 year for the study population based on discharge status, we found high bundle adherence (≥ 60%) was associated with a 0.12 increase in QALYs and a $4,949 increase in costs (Table 3). Based on these differences, the ICER was calculated as $42,120 per QALY. One-way sensi- tivity analysis indicated that the ICERs were most sensitive to the probability of being discharged home and the cost of hos- pitalization (Fig. 2). DISCUSSION The ABCDE bundle has been identified as a patient safety in- tervention for critically ill patients that mitigates ICU delirium and is associated with reductions in mortality as well as other deleterious outcomes (20, 34). We found that higher levels (> 60%) of bundle adherence were associated with consider – ably lower risk-adjusted odds of mortality (odds ratio = 0.28). The results of our survival and cost analysis indicate that use of the ABCDE bundle is a cost-effective strategy for reducing mortality in ICU patients. The mortality reduction we observed in patients with higher bundle compliance is similar to findings in studies by Barnes-Daly et al (20) (odds of hospital survival increased by 7% for every 10% increase in total bundle compliance) and Pun et al (34) (hazard ratio, 0.32; 0.17–0.62 for mortality within 7 d with complete bundle compliance). Patients in our study with high bundle adherence had an increased likelihood of being discharged home or to other care facilities. Direct in- patient costs were higher for patients with higher adherence. We did not directly examine the sources of incremental cost difference according to bundle adherence level, but a portion of that increased cost likely stems from bed charges related to the higher LOS in the greater than 60% adherence group. Furthermore, patients with higher bundle adherence had sig- nificantly better likelihood of surviving to discharge, and that may have changed their inpatient spend trajectory (additional testing, monitoring, or other therapeutic interventions which would not have been indicated in the low adherence group). Based on the differences in inpatient mortality and costs, the ICER for high adherence to the ABCDE bundle was $15,077 per life saved and $1,057 per life-year saved. The estimated ICER for Copyright © 2020 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Clinical Investigations Critical Care Medicine www.ccmjournal.org 1755 high bundle adherence in the year following hospital admission was $38,687 per QALY. These estimates are below the threshold of $50,000 per life-year or QALY frequently used as to assess the cost-effectiveness of health interventions in the United States (35). Not surprisingly, the ICERs were most sensitive to the probability of being discharged home and the cost of hospital- ization. The costs of being discharged home or to home health as opposed to a nursing facility are much lower from a health insurer’s perspective, and we observed a wide range in the per – centage of patients being discharged home across other ABCDE bundle studies. Although being discharged home may be linked to additional societal costs, we did not have the data needed to examine such costs. Hospital costs in patients with high adher – ence were approximately $4,000 greater than those with low ad- herence and served as the main source of differences in costs for patients discharged home. We used bootstrap estimates from our model to determine the range for hospital costs, as these costs were not available from previous ABCDE bundle studies. Few studies have examined the cost-effectiveness of the ABCDE bundle. Awissi et al (36) examined the cost-effectiveness Figure 1. Markov tree. Copyright © 2020 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Copyright © 2020 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Collinsworth et al 175 6 www.ccmjournal.org December 2020 • Volume 48 • Number 12 TABLE 1. Characteristics of Patients Admitted to Study ICUs Characteristic Bundle Adherence < 60%, n = 1,243 ≥ 60%, n = 1,710 p Age, mean ( sd) 61.1 (15.1)61.7 (15.6)0.3652 Gender (male), n (%) 696 (56.0) 971 (56.8)0.6691 Race, n (%) White 825 (66.4)1,168 (68.3) 0.2415 Black 364 (29.3)469 (27.4) Asian 41 (3.3)45 (2.6) Other 13 (1.1)19 (1.6) Ethnicity, n (%) Hispanic 169 (13.6)194 (11.4)0.0693 Insurance, n (%) Private 163 (13.1)252 (14.7)0.4679 Medicare 666 (53.6)909 (53.2) Medicaid 71 (5.7)73 (4.3) Other federal 114 (9.2)156 (9.1) Self-pay 127 (10.2)182 (10.6) Other 102 (8.2)138 (8.1) Risk factors Charlson Comorbidity Index, mean ( sd) 5.04 (2.76)4.87 (2.83)0.1108 APR-dRG severity, n (%) 1 0 (0.0)1 (0.1)< 0.0001 a 2 4 (0.3)20 (1.2) 3 93 (7.5)233 (13.6) 4 1,145 (92.2)1,454 (85.1) APR-DRG mortality risk, n (%) 1 4 (0.3)7 (0.4)< 0.0001 a 2 9 (0.7)47 (3.0) 3 158 (12.7)450 (26.4) 4 1,071 (86.2)1,204 (70.5) Acute Physiology and Chronic Health Evaluation II score, mean ( sd) 20.6 (7.0) 18.4 (6.5)< 0.001 a surgical, n (%) 162 (13.0) 280 (16.4)0.0108 a Dementia, n (%) 76 (6.1) 136 (8.0) 0.0514 Alcohol, n (%) 28 (2.3) 35 (2.1)0.7025 Current smoker, n (%) 244 (19.6) 342 (20.0)0.8035 Inpatient mortality, n (%) 684 (54.7) 318 (18.4)< 0.001 a Discharge status, n (%) Home 206 (16.5)637 (37.3)< 0.001 a Home health 40 (3.2)117 (6.8) Hospice 117 (9.4)133 (7.8) Long-term care facility 54 (4.3)124 (7.2) Inpatient rehabilitation facility 57 (4.6)149 (8.7) Skilled nursing facility 86 (6.9)232 (13.6) Length of stay (d), mean ( sd) 9.9 (7.0)12.3 (6.8)< 0.001 a Cost difference ($), n (%) 25,685 (26,370) 31,170 (33,109)< 0.001 a APR-DRG = all patient refined diagnosis related groups.a p < 0.05. Copyright © 2020 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Clinical Investigations Critical Care Medicine www.ccmjournal.org 1757 of a multifaceted care processes for management of seda- tion, analgesia, and delirium and found that mean hospital costs were $933 less in the group of ICU patients treated with a sedation, analgesia, and delirium management protocol (p = 0.022), primarily due to an average 1-day reduction in LOS. Although we found greater adherence to the ABCDE bundle to be associated with an increase rather than a decrease in LOS and inpatient costs, we have found evidence that use of bundle had a statistically significant impact on decreasing in-hospital mortality. This study has several limitations. Because this was a quasi-experimental study, differences in patient characteris- tics may have influenced bundle adherence rates, potentially overestimating the impact of improved bundle adherence on outcomes. This bias may have been due to improper appli- cation of bundle inclusion criteria, poor documentation, or differences in the provision of care for patients who were se- verely ill and had a high risk of mortality. We attempted to control for this selection bias and reduce potential endoge- neity by using a propensity score risk-adjustment approach to estimate the conditional probability of a patient having high bundle adherence. However, risk-adjustment can only account for observed confounders and does not ensure a bal- anced distribution of covariates between groups. In addition, all patients in this study were critically ill, and it is difficult to differentiate levels of illness severity within this population with existing measures. Overall bundle adherence observed during the study remained relatively low, as only 58% of patients received greater than 60% of bundle elements, and among patients who died, bundle process eligibility differed greatly in the low and high adherence groups (63.0% of patients in the low adher - ence group were eligible for 10 or fewer processes compared with 17.9% in the high adherence group). This may indicate that ABCDE bundle elements were not applied to patients who died early in their hospital stay and would not have accrued benefit from the care processes, as well as those perceived as being too acutely ill for the bundle to modify mortality risk. Removing the ICUs with the highest and lowest levels of compliance, controlling for cardiac ICUs, and controlling for bundle process eligibility at less than five and less than 10 pro- cesses, did not significantly impact the observed odds of inpa- tient mortality at the greater than 60% adherence threshold. Given that discernment of bundle process eligibility was re- liant on extractable structured documentation in the EHR, it is possible that there are unmeasured confounders pertaining to severity of illness in the low adherence group. Accordingly, the degree of mortality reduction attributable to bundle use in our analysis is likely overestimated. In spite of this limitation, our results directionally align with other recent studies showing a risk-adjusted mortality benefit associated with ABCDE bundle adherence. TABLE 2. The Unadjusted and Adjusted Effect of Bundle Adherence on Inpatient Outcomes Bundle Adherence Threshold 60% Unadjusted (95% CI) Adjusted (95% CI) Inpatient mortality (OR) 0.19 (0.16–0.22) a 0.28 (0.24–0.34) a Discharge status (OR) Home 2.99 (2.50–3.57) a 2.46 (2.02–2.89) a Home health 2.21 (1.53–3.19) a 1.76 (1.18–2.63) a Hospice 0.81 (0.63–1.05) 0.85 (0.64–1.14) Long-term care facility 1.72 (1.24–2.39) a 1.35 (0.94–1.94) Inpatient rehabilitation facility 1.99 (1.45–2.72) a 1.83 (1.30–2.57) a Skilled nursing facility 2.11 (1.63–2.74) a 1.61 (1.21–2.13) a Length of stay (d) 0.64 (0.51–0.76) a 0.57 (0.45–0.69) a Cost difference ($) 5,485 (2,689–8,283) a 4,067 (989–7,144) OR = odds ratio.a p < 0.05. TABLE 3. Cost-Effectiveness of High Versus Low Bundle Adherence in Terms of Inpatient Costs and Survival Inpatient Costs and Survival Cost Per Patient Incremental Cost Inpatient Survival Rate Incremental Effectiveness Cost/ Effectiveness Incremental Cost- Effectiveness Ratio Low bundle adherence (< 60%) $28,366 0.52 $54,550 High bundle adherence (≥ 60%) $32,256 $3,9200.78 0.26$41,353 $15,077 1-yr care costs and QALYS QALYs Low bundle adherence (< 60%) $34,181 0.2237 $152,799 High bundle adherence (≥ 60%) $39,130 $4,9490.3412 0.1175$115,088 $42,120 QALYS = quality-adjusted life-years. Copyright © 2020 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Copyright © 2020 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Collinsworth et al 175 8 www.ccmjournal.org December 2020 • Volume 48 • Number 12 As we did not have data for patients beyond their inpatient stay, we chose to model the impact of ABCDE bundle adher - ence on 1-year outcomes based on 1-year mortality and QALY estimates obtained from another study. The patient popula- tion of that study was similar to our patient population, but patients were 5 years older on average. While we excluded patients who were on the ventilator for greater than 14 days, the other study included 114 patients (14%) who were ventilated for greater than or equal to 21 days. Thus, the mortality esti- mates obtained from the study likely overestimated the 1-year mortality risk and underestimated QALYs. In addition, more rigorous research is needed to quantify health-related quality of life among ICU survivors (37). Our basic Markov model did not account for readmissions and transitions other than from hospital to home/discharge facility and from discharge facility to home or death. We recognize that there are inherent limita- tions in the Markov model, but have included it as an explor - atory analysis and as a starting point for future research given the current lack of cost-effectiveness studies pertaining to the ABCDE bundle. CONCLUSIONS Based on findings from our study and exploratory analysis, the ABCDE bundle appears to be a cost-effective means to improve outcomes for patients with ICU stays. There is building evi- dence that consistent use of the ABCDE bundle can favorably impact a range of clinical measures, including a reduction in the risk of mortality. Further research is needed to obtain bet- ter estimates of the effects of the ABCDE bundle on total costs of care over extended time periods, including an assessment of societal costs, for patients with an index admission to the ICU. Current address for Dr. Collin- sworth: 3M, Value Based Solutions Group, Medical Solutions Division, Dallas, TX; Dr. Priest: Baylor Scott & White Health Research Institute, Dallas, TX; and Dr. Masica: Texas Health Resources, Arlington, TX. Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s website (http://journals. lww.com/ccmjournal). Supported, in part, by the Agency for Healthcare Research and Quality (R18HS021459) and operational funds from the Baylor Scott & White Health Center for Clinical Effective- ness. Drs. Collinsworth’s, Masica’s, and Priest’s institution received fund- ing from the Agency for Healthcare Research and Quality for article re- search. Their institution received funding from Boehringer Ingelheim, Mallinckrodt Pharmaceuticals, and the Patient Centered Outcomes Re- search Institute/People Centered Research Foundation for work unrelated to this study. Dr. Priest’s institu- tion received funding from GlaxoSmithKline. For information regarding this article, E-mail: [email protected] REFERENCES 1. Chang B, Lorenzo J, Macario A: Examining health care costs: Oppor- tunities to provide value in the intensive care unit. Anesthesiol Clin 2015; 33:753–770 2. Kram SL, DiBartolo MC, Hinderer K, et al: Implementation of the ABCDE bundle to improve patient outcomes in the intensive care unit in a rural community hospital. Dimens Crit Care Nurs 2015; 34:250– 258 3. Inouye SK: Delirium in older persons. N Engl J Med 2006; 354:1157– 1165 4. Lundström M, Edlund A, Karlss

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Unit VII Scholarly Activity Textbook:Colbert, B. J., & Katrancha, E. D. (2016). Career success in health care: Professionalism in action (3rd ed.). Cengage Learning. https://online.vitalsource.com
2 Healthcare Professional Introduction Any healthcare professional needs specific crucial skills to be successful. These skills can range from particular areas such as communication, interrelating with others, and even dealing with cases involving stress. There are essential qualities needed to be a great professional in healthcare. Different healthcare workers bring additional attributes related to healthcare while performing their roles. These qualities they bring affect their career advancement. Therefore, healthcare professionals need to experience growth in certain areas at the early stages of their careers. Significant qualities Empathy; is a quality whereby the healthcare professional puts himself in the circumstance of the patient to comprehend the suffering better the patient and relatives go through. This quality makes healthcare professionals offer the best care to patients as they understand their suffering. Therefore it is a key quality needed to succeed in the healthcare profession. Excellence in communication; this quality involves speaking and listening. A healthcare professional should be able to engage the patients for better treatment. They should also be able to listen carefully to the patients to offer the right services. Success in healthcare can be attained through effective communication(Humphries et al., 2018). A healthcare worker can only meet the needs of patients if they understand them. The first step of getting this understanding is through effective communication. 3 Attentive to all details; being attentive to all details is another key to success in the healthcare profession. The work of healthcare involves a lot of pressure and stress, but all details should be considered. Life is delicate, and a small mistake can easily lead to death. Thus being attentive to all details is a key quality to getting success in the profession of healthcare. The ability to solve problems and issues is required when traditional methods fail to work. The ability to solve problems in cases where conventional methods fail to work brings the disparity between a good healthcare worker and a successful one. Therefore, solving problems is a key quality to being successful in the healthcare profession. Interpersonal skills: Any healthcare professional should work well with others. Success in healthcare needs teamwork. For example, doctors need nurses and other workers(Zechariah et al., 2019). Thus good relations should be maintained for success. Rapid response; quick acts are needed in cases of emergency. Emergency plans and first aid kits should be put in place to save lives in emergency cases. Looking for certain things may lead to death in cases of emergency. The ability to save lives is considered as one quality of successful professionals. Therefore, a quick response is needed to attain success in the healthcare profession. Qualities associated with professionalism Ability to solve problems; I will bring the quality of solving problems. The ability to solve problems will make sure I put into consideration other qualities such as effective communication and attention. It is hard to solve a problem without excellent communication and to consider even the minor details in healthcare. Therefore, the quality of solving problems will make me successful healthcare professional. This, in turn, will lead to promotions to higher levels. 4 Interpersonal skills; I will further bring the quality of interpersonal skills. This quality will make me work well with others and even be fruitful. It will also lead to the practice of effective communication. Working well with others involves excellent speaking and listening. Success in healthcare requires teamwork. Bringing the quality of interpersonal skills will make me succeed in my role and further open doors for promotion and other more challenging responsibilities. Getting more demanding responsibilities will give me more experience in healthcare. Areas to experience growth Rapid response areas; I need to experience growth in handling emergencies. Some situations, such as attending to accident victims, require maturity. The fact that I’m not used to attending to emergency cases means I need to get used to serving victims in different critical states to have great knowledge of responding to emergencies. Empathy areas; putting myself into patients’ situations may sometimes severely affect me. The conditions may affect me emotionally and even psychologically. This, in turn, may lead to stress. At first, I need to manage emotions and stress. This will aid in empathizing maturely as I serve patients. Conclusion Empathy, excellence in communication, attention to all details, ability to solve problems, interpersonal skills, and rapid response is required to succeed in healthcare. I will bring the quality of solving issues and interpersonal skills in my role. In addition, I will need to experience growth in areas involving rapid response and empathy. 5 References Humphries, Jaganathan, S., Panniyammakal, J., Singh, S., Goenka, S., Dorairaj, P., Gill, P., Greenfield, S., Lilford, R., & Manaseki-Holland, S. (2018). Investigating clinical handover and healthcare communication for outpatients with chronic disease in India: A mixed-methods study. PloS One, 13(12), e0207511–e0207511. 6 https://doi.org/10.1371/journal.pone.0207511 Zechariah, Ansa, B. E., Johnson, S. W., Gates, A. M., & Leo, G. D. (2019). Interprofessional Education and Collaboration in Healthcare: An Exploratory Study of the Perspectives of Medical Students in the United States. Healthcare (Basel), 7(4), 117–. https://doi.org/10.3390/healthcare7040117 Priem, R. L. (2018). Toward becoming a complete teacher of strategic management. Academy of Management Learning & Education , 17 (3), 374-388. https://journals.aom.org/doi/abs/10.5465/amle.2017.0237
Unit VII Scholarly Activity Textbook:Colbert, B. J., & Katrancha, E. D. (2016). Career success in health care: Professionalism in action (3rd ed.). Cengage Learning. https://online.vitalsource.com
2 Introduction Goals are the outcomes that are required to be achieved within a specific duration. For goals to be achieved, they have to be made realistic depending on what a person wants to achieve. Goals are composed of three primary purposes where; the first objective is that it acts as a conceptual framework which is essential for defining approaches to attaining the intended goal. The second primary purpose of a goal is to allow surveillance to allow an objective to be evaluated, thus allowing a person to track the progress of a project. The third objective is to equip a person with analytical tools to assess the services required to run the project’s effectiveness. This paper will focus on my short-term, mid-range, and long-term goals as a medical biller and a coder specialist. ( Yarygin et al. 2019 ) Short term goals For the first six months to two years, I have a goal of finding a medical billing mentor, learning multiple skills and growing my billing and coding network. Finding a mentor in medical billing is essential as he will equip me with skills based on the main activities carried out by a medical biller in a healthcare facility which will allow me to focus on the core topics while in college. To engage efficiently with the mentor, I will require effective communication, thus making me successful. To work as a medical biller and coder, he must have effective communication, attention to detail, and computer skills. I can achieve all these skills by focusing on the lectures from my professors. To enhance my skills, I will have to do all my assignments on time and read ahead of the professors, allowing me to understand better the information taught. ( Burns et al. 2018 ) 3 Various strategies are updated regularly in the medical field, leading to developing a medical and billing network. With a network in the medical and billing field, I will know about recent updates, thus focusing on the current trends, which will allow me to co-operate with other professionals. I can grow my medical billing and coding network by actively engaging in social media platforms to know about current trends in the medical field. Mid-range goals After developing short-term goals, I will focus on my midrange goals which will take three to five years. My mid-range goals will include; enhancing my skills, joining a team of medical coders and building my reputation. To enhance my skills, I will need to focus on what other medical billers are carrying out in the medical field, perfecting my skills. To achieve this, I will need cooperation with other team members to teach me new ideas. My second goal is to join a team of medical billers and coding specialists. Joining a team of medical billers and specialists will allow me to familiarize myself with more activities I did not know, thus market myself. Joining a team of medical billers will allow me to gain more skills making me more knowledgeable as I will come across ideas I had never learnt before. After joining medical billers, I have to use enthusiastic learning skills since it will allow me to learn, thus enhancing the skills required in my career. After working with medical billers and coding specialists, I will develop my reputation. Developing my reputation will be essential as many healthcare facilities will likely know about my services. They are likely to invite me for an interview, which will allow me to get a good-paying career. When I focus on developing my reputation, I have to use self-confidence and communication. 4 Long-term goals My long-term goals as a medical record coordinator are to create a positive work environment, act as a mentor, and lead a coding team. Creating a positive work environment will allow all the workers to enjoy working in the facility, thus making my department successful and efficient. To achieve this, I will have to use personal development skills. Employees will work with me with personal development skills, thus increasing their ability to work in the workstation and become productive. My second long-term goal is to become a mentor to young medical billers. To become a mentor, I have to use effective communication skills. Using effective communication skills, younger billers will be willing to focus on my training speech, and they will be able to refer other billers to me. By becoming a mentor, all medical institutions are likely to become knowledgeable about me, which will expand my career in all parts of the nation. (Bipp et al. 2020) As a medical record coordinator, I aim to lead the medical teams efficiently as I have the required skills in the medical environment. By leading other coding teams, I will be able to receive a considerable salary, which will allow me to meet my expectations. To lead other medical billers, I will have to use decision-making skills and effective communication to allow efficiency when communicating with one another, thus facilitating success in the medical facility. Meeting my objectives will have a lot of positive impacts on my life as they will provide me with a direction that will motivate me to achieve them. My goals will impact the health and medical field where they will allow me to enhance patient care, thus preventing prescription errors, minimizing inefficiencies in healthcare facilities and enhancing staff relationship facilitating cooperation. 5 References 6 Bipp, T., Kleingeld, A., & Schelp, L. (2020). Achievement goals and goal progress as drivers of work engagement. Psychological Reports. Burns, E. C., Martin, A. J., & Collie, R. J. (2018). Adaptability, personal best (PB) goals setting, and gains in students’ academic outcomes: A longitudinal examination from a social cognitive perspective. Contemporary Educational Psychology , 53 , 57-72. Yarygin, O. N., Korostelev, A. A., Akhmetov, L. G., & Maseleno, A. (2019). Modelling competence as a tool of goal setting for education in modern society. International Journal of Recent Technology and Engineering , 7 (6), 72-77.

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