Siu L. Hui, PhD

Infections acquired in the hospital are termed healthcare‐associated infections (HAIs) and include central lineassociated blood stream infections (CLABSIs). Among HAIs, CLABSIs cause the highest number of preventable deaths.[1] Central venous catheters (CVCs) or central lines are commonly used in the hospital.[2] Each year their use is linked to 250,000 cases of CLABSIs in the United States.[3] Some CLABSIs may be prevented by the prompt removal of the line.[4] However, CVCs are often retained after their clinical indication has lapsed and are then referred to as idle lines.[5, 6] In this work, we propose and theoretically test a guideline to facilitate the safe removal of an idle line by observing the agreement and disagreement between actual practice and the proposed guideline.

METHODS

RESULTS

A total of 126 lines were observed in 126 patients. Eighty‐three (65.9%) of the lines were PICCs. The remaining 43 (34.1%) were CVLs. The indications for line placement were distributed between the need for central access, total parenteral nutrition, or antibiotics (Table 2).

Out of the 126 patients, 50 (39.7%) were discharged from the hospital, died, were transferred to a higher level of care, or transitioned to palliative or hospice care with the line in place. In the remaining 76 patients, the audit captured 635 days, out of which a line was in place for 522 (82.2%) days. Of these 522 days, the line's presence was justified by our criteria for 351 (67.2%) days. The most common reason for a line to be justified on any given day was the need for antibiotics followed by the presence of SIRS criteria (Table 3). The remaining 171 (32.7%) days were idle.

A comparison of the actual removal of the 76 central lines in practice relative to the proposed guideline of removing it the day following the first idle day is displayed in Figure 1. The central line was removed prior to our proposed guideline in 11 (14.5%) patients, and waiting for an idle day in these patients would have added 46 line days. In almost half the patients (n = 36, 47.4%), the line was removed in agreement with the proposed guideline. None of the patients in whom the line was removed prior to or in accordance with our proposed guideline required a line reinsertion. Line removal was delayed in 29 (38.2%) patients when compared to our proposed guideline. In these patients, following the guideline would have created 122 line‐free days. Most (n = 102, 83.6%) of these potential line‐free days were idle. Twenty (16.4%) were justified, of which half (n = 10) were justified by meeting SIRS criteria.

Figure 1

DISCUSSION

Approximately 1 in every 25 inpatients in the United States has at least 1 HAI on any given day.[11] The case fatality rate from a CLABSI may be as high as 12%, and up to 70% of these infections may be preventable.[1, 12] Interventions successful in decreasing CLABSIs have focused on patients in ICUs.[13] However, CVCs are increasingly prevalent outside the ICU, with over 4.5 million line days in non‐ICU beds reported to the National Healthcare Safety Network in 2012 compared to 2.5 million in 2010.[2, 14] However, adherence rates to infection control practices may be lower on the wards than in the ICUs.[6, 15] Consequently, although the number of CLABSIs has declined over the last decade, most are now occurring outside the ICU.[16] These trends underscore the need to develop strategies aimed at CLABSI prevention on the floors.

Analogous to the life cycle of a urinary catheter described by Meddings et al.,[17] strategies to prevent CLABSIs and other CVC‐related complications may be designed around the life cycle of a CVC. The life cycle starts with insertion and moves on to the maintenance, removal, and possible reinsertion of the line. The process thus starts with the decision to place the line. Over the last decade, this decision making has changed in part due to PICCs. This shift is reflected in PICC prevalence rates: in 2001, 11% of audited central lines were PICCs compared to 56% in 2007.[5, 6] In our audit, 66% of the CVCs were PICCs. This increase in the use of PICCs may be attributable to the ease and safety of their placement coupled with the increased availability of vascular access placement teams.[18] The risk of overuse that may result from such expediency may be countered by adhering to guidelines such as the Michigan Appropriateness Guide for Intravenous Catheters, which provides both clinically detailed guidance and an impetus for reflective decision making around intravenous access.[19]

The placement of CVCs for prolonged parenteral antibiotics may be a particular subset that bears further exploration. Similar to previous reports, we found that a large number of the CVCs were both inserted for and justified by the need for IV antibiotics.[5] Guidelines delineated by the Infectious Diseases Society of America regarding outpatient parenteral antibiotics weigh both the duration of therapy and the antimicrobial's potential for causing phlebitis when recommending the type of intravascular access.[20] Many courses may therefore be completed through peripheral or midline catheters. Developing strong partnerships between infectious disease specialists, hospitalists, and the facilities or home‐care services treating these patients may curtail the use of CVCs for antimicrobial administration.

The main focus of our work is on facilitating the safe removal of CVCs. The risk of CLABSIs increases each day a CVC is in place, and guidelines to prevent CLABSIs include recommendations to promptly remove nonessential catheters.[4, 21] There is also an emerging understanding that the risk of a PICC‐related CLABSI approaches that from a traditional central line in hospitalized patients, and PICCs confer an increased risk of venous thromboembolism.[18, 22] Although nearly half of surveyed hospitalists recently reported leaving PICCs in place until discharge day, our data suggest that this practice may be driven by the trajectory of a patient's recovery as much as by knowledge gaps related to the use of PICCs.[23] In nearly half the instances, clinical practice already mirrors our proposed guideline, with line removal coinciding with both the timing proposed by our guideline and discharge day. However, there is room for improvement, as line removal may have been expedited in the 29 patients in whom the line was retained after the first idle day. Maintaining an awareness of its presence and weighing its risks and benefits daily may facilitate the removal of a CVC. Based on the recent findings that up to a quarter of clinicians are unaware that their patients have a central line, the mere reminder of the presence of a line using such criteria may expedite its removal by triggering a purposeful reassessment of its ongoing need.[24] Premature CVC removal requiring line reinsertion is an unintended consequence that may emerge from the earlier removal of lines. In our sample, none of the patients who had lines removed either prior to or in accordance with our proposed guideline required a line reinsertion. In addition to line reinsertion, delays in laboratory testing and reporting due to the unavailability of access, increased patient discomfort, or increased workload on the bedside nurse or vascular access team must also be considered when implementing strategies aimed at decreasing line days.

We envisage using these criteria to both empower practitioners with knowledge and foster shared accountability between all team members by using a uniform tool. This can occur through partnerships between infection control, clinical nurse specialists, bedside nursing, and physicians. The electronic medical record could be leveraged to scan the record for the criteria and create a notification when the line becomes idle. In alignment with the Michigan Appropriateness Guide for Intravenous Catheters guidelines, we do not support the removal of lines by nursing staff without physician notification.[19] Such principles have been successfully harnessed in strategies to prevent both catheter‐associated urinary tract infections and CLABSIs in ICUs.[13, 25] In light of the complexity surrounding the decision making for CVCs, our criteria were focused on the wards and erred on the side of clinical caution. This clinical conservatism is apparent in the patients in whom lines were removed prior to what our guideline would propose, yet none of the patients required a line reinsertion. As concerns about recrudescent clinical instability may drive decision making around line removal, such conservatism may be warranted initially. However, the fidelity of these criteria in the clinical setting will need prospective validation. In particular, the inclusion of SIRS criteria may have led to an overestimation of justified days. Further studies may be needed to refine the criteria and find a clinical hierarchy that balances the risks and benefits of retaining a central line.

Our work has certain limitations. It is a single center's experience, and our findings may not therefore be generalizable. Except for when the indication for the line was for difficult access, we did not attempt to verify the presence of a peripheral IV. This, in combination with the inclusion of SIRS criteria, likely leads to an underestimation of idle days. In the interest of focusing on patients in whom the decision making around a line would be the least controversial, we did not continue to follow patients who were transferred to a higher level of care. It is possible, however, that these transfers were precipitated by line‐associated complications such as sepsis and would be important to track. We did not measure the agreement between data collectors, although definitions and methodologies were standardized and reviewed prior to data collection. As this was an observational assessment of a proposed guideline, we cannot predict how the recommendations generated by it will be received by clinicians. Although this may prove to be a barrier in adoption, we hope that the conversation it initiates leads to change.

Hospitalists are positioned to potentially influence the entire life cycle of a central line on the floor. Strategies can be enacted at each stage to help decrease the potential of harm from these devices to our patients. Creating and testing criteria and guidelines such as we propose represents just 1 such strategy in a multidisciplinary effort to provide the best possible care we can.

Infections acquired in the hospital are termed healthcare‐associated infections (HAIs) and include central lineassociated blood stream infections (CLABSIs). Among HAIs, CLABSIs cause the highest number of preventable deaths.[1] Central venous catheters (CVCs) or central lines are commonly used in the hospital.[2] Each year their use is linked to 250,000 cases of CLABSIs in the United States.[3] Some CLABSIs may be prevented by the prompt removal of the line.[4] However, CVCs are often retained after their clinical indication has lapsed and are then referred to as idle lines.[5, 6] In this work, we propose and theoretically test a guideline to facilitate the safe removal of an idle line by observing the agreement and disagreement between actual practice and the proposed guideline.

METHODS

RESULTS

A total of 126 lines were observed in 126 patients. Eighty‐three (65.9%) of the lines were PICCs. The remaining 43 (34.1%) were CVLs. The indications for line placement were distributed between the need for central access, total parenteral nutrition, or antibiotics (Table 2).

Out of the 126 patients, 50 (39.7%) were discharged from the hospital, died, were transferred to a higher level of care, or transitioned to palliative or hospice care with the line in place. In the remaining 76 patients, the audit captured 635 days, out of which a line was in place for 522 (82.2%) days. Of these 522 days, the line's presence was justified by our criteria for 351 (67.2%) days. The most common reason for a line to be justified on any given day was the need for antibiotics followed by the presence of SIRS criteria (Table 3). The remaining 171 (32.7%) days were idle.

A comparison of the actual removal of the 76 central lines in practice relative to the proposed guideline of removing it the day following the first idle day is displayed in Figure 1. The central line was removed prior to our proposed guideline in 11 (14.5%) patients, and waiting for an idle day in these patients would have added 46 line days. In almost half the patients (n = 36, 47.4%), the line was removed in agreement with the proposed guideline. None of the patients in whom the line was removed prior to or in accordance with our proposed guideline required a line reinsertion. Line removal was delayed in 29 (38.2%) patients when compared to our proposed guideline. In these patients, following the guideline would have created 122 line‐free days. Most (n = 102, 83.6%) of these potential line‐free days were idle. Twenty (16.4%) were justified, of which half (n = 10) were justified by meeting SIRS criteria.

Figure 1

DISCUSSION

Approximately 1 in every 25 inpatients in the United States has at least 1 HAI on any given day.[11] The case fatality rate from a CLABSI may be as high as 12%, and up to 70% of these infections may be preventable.[1, 12] Interventions successful in decreasing CLABSIs have focused on patients in ICUs.[13] However, CVCs are increasingly prevalent outside the ICU, with over 4.5 million line days in non‐ICU beds reported to the National Healthcare Safety Network in 2012 compared to 2.5 million in 2010.[2, 14] However, adherence rates to infection control practices may be lower on the wards than in the ICUs.[6, 15] Consequently, although the number of CLABSIs has declined over the last decade, most are now occurring outside the ICU.[16] These trends underscore the need to develop strategies aimed at CLABSI prevention on the floors.

Analogous to the life cycle of a urinary catheter described by Meddings et al.,[17] strategies to prevent CLABSIs and other CVC‐related complications may be designed around the life cycle of a CVC. The life cycle starts with insertion and moves on to the maintenance, removal, and possible reinsertion of the line. The process thus starts with the decision to place the line. Over the last decade, this decision making has changed in part due to PICCs. This shift is reflected in PICC prevalence rates: in 2001, 11% of audited central lines were PICCs compared to 56% in 2007.[5, 6] In our audit, 66% of the CVCs were PICCs. This increase in the use of PICCs may be attributable to the ease and safety of their placement coupled with the increased availability of vascular access placement teams.[18] The risk of overuse that may result from such expediency may be countered by adhering to guidelines such as the Michigan Appropriateness Guide for Intravenous Catheters, which provides both clinically detailed guidance and an impetus for reflective decision making around intravenous access.[19]

The placement of CVCs for prolonged parenteral antibiotics may be a particular subset that bears further exploration. Similar to previous reports, we found that a large number of the CVCs were both inserted for and justified by the need for IV antibiotics.[5] Guidelines delineated by the Infectious Diseases Society of America regarding outpatient parenteral antibiotics weigh both the duration of therapy and the antimicrobial's potential for causing phlebitis when recommending the type of intravascular access.[20] Many courses may therefore be completed through peripheral or midline catheters. Developing strong partnerships between infectious disease specialists, hospitalists, and the facilities or home‐care services treating these patients may curtail the use of CVCs for antimicrobial administration.

The main focus of our work is on facilitating the safe removal of CVCs. The risk of CLABSIs increases each day a CVC is in place, and guidelines to prevent CLABSIs include recommendations to promptly remove nonessential catheters.[4, 21] There is also an emerging understanding that the risk of a PICC‐related CLABSI approaches that from a traditional central line in hospitalized patients, and PICCs confer an increased risk of venous thromboembolism.[18, 22] Although nearly half of surveyed hospitalists recently reported leaving PICCs in place until discharge day, our data suggest that this practice may be driven by the trajectory of a patient's recovery as much as by knowledge gaps related to the use of PICCs.[23] In nearly half the instances, clinical practice already mirrors our proposed guideline, with line removal coinciding with both the timing proposed by our guideline and discharge day. However, there is room for improvement, as line removal may have been expedited in the 29 patients in whom the line was retained after the first idle day. Maintaining an awareness of its presence and weighing its risks and benefits daily may facilitate the removal of a CVC. Based on the recent findings that up to a quarter of clinicians are unaware that their patients have a central line, the mere reminder of the presence of a line using such criteria may expedite its removal by triggering a purposeful reassessment of its ongoing need.[24] Premature CVC removal requiring line reinsertion is an unintended consequence that may emerge from the earlier removal of lines. In our sample, none of the patients who had lines removed either prior to or in accordance with our proposed guideline required a line reinsertion. In addition to line reinsertion, delays in laboratory testing and reporting due to the unavailability of access, increased patient discomfort, or increased workload on the bedside nurse or vascular access team must also be considered when implementing strategies aimed at decreasing line days.

We envisage using these criteria to both empower practitioners with knowledge and foster shared accountability between all team members by using a uniform tool. This can occur through partnerships between infection control, clinical nurse specialists, bedside nursing, and physicians. The electronic medical record could be leveraged to scan the record for the criteria and create a notification when the line becomes idle. In alignment with the Michigan Appropriateness Guide for Intravenous Catheters guidelines, we do not support the removal of lines by nursing staff without physician notification.[19] Such principles have been successfully harnessed in strategies to prevent both catheter‐associated urinary tract infections and CLABSIs in ICUs.[13, 25] In light of the complexity surrounding the decision making for CVCs, our criteria were focused on the wards and erred on the side of clinical caution. This clinical conservatism is apparent in the patients in whom lines were removed prior to what our guideline would propose, yet none of the patients required a line reinsertion. As concerns about recrudescent clinical instability may drive decision making around line removal, such conservatism may be warranted initially. However, the fidelity of these criteria in the clinical setting will need prospective validation. In particular, the inclusion of SIRS criteria may have led to an overestimation of justified days. Further studies may be needed to refine the criteria and find a clinical hierarchy that balances the risks and benefits of retaining a central line.

Our work has certain limitations. It is a single center's experience, and our findings may not therefore be generalizable. Except for when the indication for the line was for difficult access, we did not attempt to verify the presence of a peripheral IV. This, in combination with the inclusion of SIRS criteria, likely leads to an underestimation of idle days. In the interest of focusing on patients in whom the decision making around a line would be the least controversial, we did not continue to follow patients who were transferred to a higher level of care. It is possible, however, that these transfers were precipitated by line‐associated complications such as sepsis and would be important to track. We did not measure the agreement between data collectors, although definitions and methodologies were standardized and reviewed prior to data collection. As this was an observational assessment of a proposed guideline, we cannot predict how the recommendations generated by it will be received by clinicians. Although this may prove to be a barrier in adoption, we hope that the conversation it initiates leads to change.

Hospitalists are positioned to potentially influence the entire life cycle of a central line on the floor. Strategies can be enacted at each stage to help decrease the potential of harm from these devices to our patients. Creating and testing criteria and guidelines such as we propose represents just 1 such strategy in a multidisciplinary effort to provide the best possible care we can.

Infections acquired in the hospital are termed healthcare‐associated infections (HAIs) and include central lineassociated blood stream infections (CLABSIs). Among HAIs, CLABSIs cause the highest number of preventable deaths.[1] Central venous catheters (CVCs) or central lines are commonly used in the hospital.[2] Each year their use is linked to 250,000 cases of CLABSIs in the United States.[3] Some CLABSIs may be prevented by the prompt removal of the line.[4] However, CVCs are often retained after their clinical indication has lapsed and are then referred to as idle lines.[5, 6] In this work, we propose and theoretically test a guideline to facilitate the safe removal of an idle line by observing the agreement and disagreement between actual practice and the proposed guideline.

METHODS

RESULTS

A total of 126 lines were observed in 126 patients. Eighty‐three (65.9%) of the lines were PICCs. The remaining 43 (34.1%) were CVLs. The indications for line placement were distributed between the need for central access, total parenteral nutrition, or antibiotics (Table 2).

Out of the 126 patients, 50 (39.7%) were discharged from the hospital, died, were transferred to a higher level of care, or transitioned to palliative or hospice care with the line in place. In the remaining 76 patients, the audit captured 635 days, out of which a line was in place for 522 (82.2%) days. Of these 522 days, the line's presence was justified by our criteria for 351 (67.2%) days. The most common reason for a line to be justified on any given day was the need for antibiotics followed by the presence of SIRS criteria (Table 3). The remaining 171 (32.7%) days were idle.

A comparison of the actual removal of the 76 central lines in practice relative to the proposed guideline of removing it the day following the first idle day is displayed in Figure 1. The central line was removed prior to our proposed guideline in 11 (14.5%) patients, and waiting for an idle day in these patients would have added 46 line days. In almost half the patients (n = 36, 47.4%), the line was removed in agreement with the proposed guideline. None of the patients in whom the line was removed prior to or in accordance with our proposed guideline required a line reinsertion. Line removal was delayed in 29 (38.2%) patients when compared to our proposed guideline. In these patients, following the guideline would have created 122 line‐free days. Most (n = 102, 83.6%) of these potential line‐free days were idle. Twenty (16.4%) were justified, of which half (n = 10) were justified by meeting SIRS criteria.

Figure 1

DISCUSSION

Approximately 1 in every 25 inpatients in the United States has at least 1 HAI on any given day.[11] The case fatality rate from a CLABSI may be as high as 12%, and up to 70% of these infections may be preventable.[1, 12] Interventions successful in decreasing CLABSIs have focused on patients in ICUs.[13] However, CVCs are increasingly prevalent outside the ICU, with over 4.5 million line days in non‐ICU beds reported to the National Healthcare Safety Network in 2012 compared to 2.5 million in 2010.[2, 14] However, adherence rates to infection control practices may be lower on the wards than in the ICUs.[6, 15] Consequently, although the number of CLABSIs has declined over the last decade, most are now occurring outside the ICU.[16] These trends underscore the need to develop strategies aimed at CLABSI prevention on the floors.

Analogous to the life cycle of a urinary catheter described by Meddings et al.,[17] strategies to prevent CLABSIs and other CVC‐related complications may be designed around the life cycle of a CVC. The life cycle starts with insertion and moves on to the maintenance, removal, and possible reinsertion of the line. The process thus starts with the decision to place the line. Over the last decade, this decision making has changed in part due to PICCs. This shift is reflected in PICC prevalence rates: in 2001, 11% of audited central lines were PICCs compared to 56% in 2007.[5, 6] In our audit, 66% of the CVCs were PICCs. This increase in the use of PICCs may be attributable to the ease and safety of their placement coupled with the increased availability of vascular access placement teams.[18] The risk of overuse that may result from such expediency may be countered by adhering to guidelines such as the Michigan Appropriateness Guide for Intravenous Catheters, which provides both clinically detailed guidance and an impetus for reflective decision making around intravenous access.[19]

The placement of CVCs for prolonged parenteral antibiotics may be a particular subset that bears further exploration. Similar to previous reports, we found that a large number of the CVCs were both inserted for and justified by the need for IV antibiotics.[5] Guidelines delineated by the Infectious Diseases Society of America regarding outpatient parenteral antibiotics weigh both the duration of therapy and the antimicrobial's potential for causing phlebitis when recommending the type of intravascular access.[20] Many courses may therefore be completed through peripheral or midline catheters. Developing strong partnerships between infectious disease specialists, hospitalists, and the facilities or home‐care services treating these patients may curtail the use of CVCs for antimicrobial administration.

The main focus of our work is on facilitating the safe removal of CVCs. The risk of CLABSIs increases each day a CVC is in place, and guidelines to prevent CLABSIs include recommendations to promptly remove nonessential catheters.[4, 21] There is also an emerging understanding that the risk of a PICC‐related CLABSI approaches that from a traditional central line in hospitalized patients, and PICCs confer an increased risk of venous thromboembolism.[18, 22] Although nearly half of surveyed hospitalists recently reported leaving PICCs in place until discharge day, our data suggest that this practice may be driven by the trajectory of a patient's recovery as much as by knowledge gaps related to the use of PICCs.[23] In nearly half the instances, clinical practice already mirrors our proposed guideline, with line removal coinciding with both the timing proposed by our guideline and discharge day. However, there is room for improvement, as line removal may have been expedited in the 29 patients in whom the line was retained after the first idle day. Maintaining an awareness of its presence and weighing its risks and benefits daily may facilitate the removal of a CVC. Based on the recent findings that up to a quarter of clinicians are unaware that their patients have a central line, the mere reminder of the presence of a line using such criteria may expedite its removal by triggering a purposeful reassessment of its ongoing need.[24] Premature CVC removal requiring line reinsertion is an unintended consequence that may emerge from the earlier removal of lines. In our sample, none of the patients who had lines removed either prior to or in accordance with our proposed guideline required a line reinsertion. In addition to line reinsertion, delays in laboratory testing and reporting due to the unavailability of access, increased patient discomfort, or increased workload on the bedside nurse or vascular access team must also be considered when implementing strategies aimed at decreasing line days.

We envisage using these criteria to both empower practitioners with knowledge and foster shared accountability between all team members by using a uniform tool. This can occur through partnerships between infection control, clinical nurse specialists, bedside nursing, and physicians. The electronic medical record could be leveraged to scan the record for the criteria and create a notification when the line becomes idle. In alignment with the Michigan Appropriateness Guide for Intravenous Catheters guidelines, we do not support the removal of lines by nursing staff without physician notification.[19] Such principles have been successfully harnessed in strategies to prevent both catheter‐associated urinary tract infections and CLABSIs in ICUs.[13, 25] In light of the complexity surrounding the decision making for CVCs, our criteria were focused on the wards and erred on the side of clinical caution. This clinical conservatism is apparent in the patients in whom lines were removed prior to what our guideline would propose, yet none of the patients required a line reinsertion. As concerns about recrudescent clinical instability may drive decision making around line removal, such conservatism may be warranted initially. However, the fidelity of these criteria in the clinical setting will need prospective validation. In particular, the inclusion of SIRS criteria may have led to an overestimation of justified days. Further studies may be needed to refine the criteria and find a clinical hierarchy that balances the risks and benefits of retaining a central line.

Our work has certain limitations. It is a single center's experience, and our findings may not therefore be generalizable. Except for when the indication for the line was for difficult access, we did not attempt to verify the presence of a peripheral IV. This, in combination with the inclusion of SIRS criteria, likely leads to an underestimation of idle days. In the interest of focusing on patients in whom the decision making around a line would be the least controversial, we did not continue to follow patients who were transferred to a higher level of care. It is possible, however, that these transfers were precipitated by line‐associated complications such as sepsis and would be important to track. We did not measure the agreement between data collectors, although definitions and methodologies were standardized and reviewed prior to data collection. As this was an observational assessment of a proposed guideline, we cannot predict how the recommendations generated by it will be received by clinicians. Although this may prove to be a barrier in adoption, we hope that the conversation it initiates leads to change.

Hospitalists are positioned to potentially influence the entire life cycle of a central line on the floor. Strategies can be enacted at each stage to help decrease the potential of harm from these devices to our patients. Creating and testing criteria and guidelines such as we propose represents just 1 such strategy in a multidisciplinary effort to provide the best possible care we can.

Despite an estimated annual $2.6 trillion expenditure on healthcare, the United States performs poorly on indicators of health and harm during care.[1, 2, 3] Hospitals around the nation are working to improve the care they deliver. We describe a model developed at our institution and report the evaluation of the outcomes associated with its implementation on the general medical and surgical units. The Indiana University Institutional Review Board approved this work.

SETTING AND DEFINITIONS

Indiana University Health Methodist Hospital (MH) is an academic center in Indianapolis, Indiana, serving over 30,000 patients annually.[4] In 2012, responding to the coexisting needs to improve quality and contain costs, the MH leadership team redesigned care in the hospital. The new model centers around accountable care teams (ACTs). Each ACT is a geographically defined set of providers accepting ownership for the clinical, service, and financial outcomes of their respective inpatient unit. The units studied are described in Table 1.

THE ACT MODEL

The model comprises 8 interventions rooted in 3 foundational domains: (1) enhancing interprofessional collaboration (IPC), (2) enabling data‐driven decisions, and (3) providing leadership. Each intervention is briefly described under its main focus (see Supporting Information, Appendix A, in the online version of this article for further details).

Implementation Timelines and ACT Scores

The development of the ACTs started in the spring of 2012. Physician, nursing, and pharmacy support was sought, and a pilot unit was formed in August 2012. The model was cascaded hospital wide by December 2013, with support from the ACT program director (A.N.). The program director observed and scored the uptake of each intervention by each unit monthly. A score of 1 denoted no implementation, whereas 5 denoted complete implementation. The criteria for scoring are presented in Table 2. The monthly scores for all 8 interventions in each of the 11 units were averaged as an overall ACT score, which reflects the implementation dose of the ACT model. Monthly domain scores for enhancing IPC and enabling data‐driven decisions were also calculated as the average score within each domain. This yielded 3 domain scores. Figure 1A plots by month the overall ACT score for the medical and surgical units, and Figure 1B plots the implementation score for the 3 domains between August 2012 and December 2013 for all units. The uptake of the interventions varied between units. This allowed our analysis to explore the dose relationships between the model and outcomes independent of underlying time trends that may be affected by concomitant initiatives.

Table 2.Scoring Grid

	1	2	3	4	5
NOTE: Abbreviations: ACT, accountable care team. *The ACT disciplines used for this scoring include the hospitalists, clinical nurse specialists, pharmacists, case managers, and social workers. Members of the ACT team not included in the scoring scheme include unit nurse managers, nursing, charge nurse, physical therapists, nutrition support, and occupational therapists. The maximum number of specialists on any unit is 3 (eg, cardiothoracic surgery, cardiology, and vascular surgery on the cardiovascular surgery unit). For general medical units, a score of 3 would be the next score possible after 1.
Geographical cohorting of patients and the ACT*	None	At least 1 discipline comprising the ACT is unit based	All disciplines comprising the ACT except the hospitalist unit based	All disciplines including the hospitalist unit based	4 + 80% of hospitalist provider's patients on the unit
Bedside collaborative rounding	None	Occurring 1 day a week on at least 25% of the patients on the unit	Occurring 2 to 3 days a week on at least 50% of the patients on the unit	Occurring 3 to 4 days a week on at least 75% of the patients on the unit	Occurring MondayFriday on all patients on the unit
Daily huddle	None	Occurring daily, 1 out of 4 ACT disciplines represented, at least 25% of patients on the unit discussed	Occurring daily, 2 out of 4 ACT disciplines represented, at least 50% of patients on the unit discussed	Occurring daily, 3 out of 4 ACT disciplines represented, at least 75% of patients on the unit discussed	Occurring daily, all disciplines of the ACT represented, all patients on the unit discussed
Hospitalist and specialty comanagement agreements	None	One out of 3 specialists represented on the unit collaborating with the hospitalists on at least 25% of relevant patients	One out of 3 specialists represented on the unit collaborating with the hospitalists on at least 50% of relevant patients	Two out of 3 specialists on the unit collaborating with the hospitalists on at least 75% of relevant patients	All specialists on the unit collaborating with the hospitalists on all relevant patients on the unit
Unit white board	None	Present but only used by nursing	Present and used by all ACT disciplines except physician providers	Present and used by entire ACT; use inconsistent	Present and used MondayFriday by all disciplines of ACT
Monthly review of unit level data	None	Nurse manager reviewing data with ACT program director	Nurse manager and unit leader reviewing data with ACT program director	Meeting either not consistently occurring monthly or not consistently attended by entire ACT	Monthly meeting with entire ACT
Weekly patient satisfaction rounding	None	Nurse manager performing up to 1 week a month	Nurse manager performing weekly	Nurse and physician leader performing up to 3 times a month	Nurse and physician leader performing weekly
Leadership	None	For units with specialties, either hospitalist or specialist leader identified	Both hospitalist and specialist leader Identified	Both hospitalist and specialist leaders (where applicable) identified and partially engaged in leadership role	Both hospitalist and specialist leaders (where applicable) identified and engaged in leadership role

Figure 1

Outcomes

Monthly data between August 2012 and December 2013 were analyzed.

Measures of Value

MH is a member of the University Health Consortium, which measures outcomes of participants relative to their peers. MH measures LOS index as a ratio of observed LOS to expected LOS that is adjusted for severity of illness.[5]

Variable direct costs (VDCs) are costs that a hospital can save if a service is not provided.[6] A hospital's case‐mix index (CMI) represents the average diagnosis‐related group relative weight for that hospital. We track VDCs adjusted for CMI (CMI‐adjusted VDC).[7]

Thirty‐day readmission rate is the percentage of cases that are readmitted to MH within 30 days of discharge from the index admission.[8]

Measures of Patient Satisfaction

The Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey covers topics relevant to a patient's experience in the hospital.[9] Patient satisfaction scores are tracked by responses to the HCAHPS survey.

Measures of Provider Satisfaction

Hospitalist and specialty providers, leadership, and case management teams were surveyed via email through SurveyMonkey in July 2014. The survey included Likert responses that elicited opinions and comments about the ACT model.

RESULTS

The overall ACT score was associated with LOS index and CMI‐adjusted VDC (both P < 0.001). For every 1‐unit increase in the overall ACT score, LOS index decreased by 0.078 and CMI‐adjusted VDC decreased by $273.99 (Table 3).

Looking at domains, enhancing IPC resulted in statistically significant decreases in both LOS index and CMI‐adjusted VDC, but providing leadership and enabling data‐driven decisions decreased only the LOS index. Most of the 8 individual interventions were associated with at least 1 of these 2 outcomes. (Even where the associations were not significant, they were all in the direction of decreasing LOS and cost). In these models, the covariate of type of units (medical vs surgical) was not associated with LOS or cost. There was no significant time trend in LOS or cost, except in models where an intervention had no association with either outcome. Inclusion of all individual effective interventions in the same statistical model to assess their relative contributions was not possible because they were highly correlated (correlations 0.450.89).

Thirty‐day readmissions and patient satisfaction were not significantly associated with the overall ACT score, but exploratory analyses showed that patient satisfaction increased with the implementation of geographical cohorting (P = 0.007).

DISCUSSION

The serious problems in US healthcare constitute an urgent imperative to innovate and reform.[10] Inpatient care reflects 31% of the expenditure on healthcare, and in 2010, 35.1 million patients were discharged from the hospital after spending an average of 4.8 days as an inpatient.[11] These figures represent an immense opportunity to intervene. Measuring the impact of quality improvement efforts is often complicated by concomitant changes that affect outcomes over the interval studied. Our approach allowed us to detect statistically significant changes in LOS index and CMI‐adjusted VDC associated with the ACT implementation dose that could be separated from the underlying time trends.

The ACT model we describe is rooted in improving 3 foundational domains; quantifying each intervention's compartmentalized contribution, however, proved difficult. Each intervention intertwines with the others to create changes in attitudes, knowledge, and culture that are difficult to measure yet may synergistically affect outcomes. For example, although geographical cohorting appears to have the strongest statistical association with outcomes, this may be mediated by how it enables other processes to take place more effectively. Based on this analysis, therefore, the ACT model may best be considered a bundled intervention.

The team caring for a patient during hospitalization is so complex that fewer than a quarter of patients know their physician's or nurse's name.[12] This complexity impairs communication between patients and providers and between the providers themselves. Communication failures are consistently identified as root causes in sentinel events reported to the Joint Commission.[13] IPC is the process by which different professional groups work together to positively impact health care. IPC overlaps with communication, coordination, and teamwork, and improvements in IPC may improve care.[14] Some elements of the model we describe have been tested previously.[15, 16, 17] Localization of teams may increase productivity and the frequency with which physicians and nurses communicate. Localization also decreases the number of pages received and steps walked by providers during a workday.[15, 16, 17] However, these studies reported a trend toward an increase in the LOS and neutral effects on cost and readmission rates. We found statistically significant decreases in both LOS and cost associated with the geographic cohorting of patients and providers. Notably, our model localized not only the physician providers but also the interdisciplinary team of pharmacists, clinical nurse specialists, case managers, and social workers. This proximity may facilitate IPC between all members that culminates in improved efficiency. The possibility of delays in discharges to avoid new admissions in a geographically structured team has previously been raised to explain the associated increases in LOS.[16, 17] The accountability of each unit for its metrics, the communication between nursing and physicians, and the timely availability of the unit's performance data aligns everyone toward a shared goal and provides some protection from an unintended consequence.

Structured interdisciplinary rounds decrease adverse events and improve teamwork ratings.[18, 19] The huddle in our model is a forum to collaborate between disciplines that proved to be effective in decreasing LOS and costs. Our huddle aims to discuss all the patients on the unit. This allows the team to assist each other in problem solving for the entire unit and not just the patients on the geographically cohorted team. This approach, in addition to the improved IPC fostered by the ACT model, may help explain how benefits in LOS and costs permeated across all 11 diverse units despite the presence of patients who are not directly served by the geographically cohorted team.

High‐performing clinical systems maintain an awareness of their overarching mission and unit‐based leaders can influence the frontline by reiterating the organizational mission and aligning efforts with outcomes.[20] Our leadership model is similar to those described by other institutions in the strong partnerships between physicians and nursing.[21] As outlined by Kim et al., investing in the professional development of the unit leaders may help them fulfill their roles and serve the organization better.[21]

The fragmentation and lack of ownership over the continuum of patient care causes duplication and waste. The proposal in the Accountable Care Act to create accountable care organizations is rooted in the understanding that providers and organizations will seek out new ways of improving quality when held accountable for their outcomes.[22] To foster ownership and accountability, reporting of metrics at the unit level is needed. Furthermore, an informational infrastructure is critical, as improvements cannot occur without the availability of data to both monitor performance and measure the effect of interventions.[10, 23] Even without any other interventions, providing feedback alone is an effective way of changing practices.[24] According to Berwick et al., this phenomenon reflects practitioners' intrinsic motivation to simply want to be better.[25] Our monthly review of each unit's data is an effective way to provide timely feedback to the frontline that sparks pride, ownership, and innovative thinking.

Based on our mean ACT score and CMI‐adjusted VDC reductions alone, we estimate savings of $649.36 per hospitalization (mean increase in ACT implementation of 2.37 times reduction in cost index of $273.99 per unit increase in overall ACT score). This figure does not include savings realized through reductions in LOS. This is a small decrease relative to the mean cost of hospitalization, yet when compounded over the annual MH census, it would result in substantial savings. The model relied on the restructuring of the existing workforce and the only direct additional cost was the early salary support for the ACT program director.

FURTHER DIRECTIONS

Although there is a need to improve our healthcare system, interventions should be deliberate and evidence based wherever possible.[26] Geographic cohorting may decrease the frequency of paging interruptions for physicians and practitioners while increasing face‐to‐face interruptions.[27] The net effect on safety with this trade‐off should be investigated.

The presence of an intervention does not guarantee its success. Despite geographic cohorting and interdisciplinary meetings, communication that influences physician decision making may not improve.[28] Although instruments to measure ratings of team work and collaboration are available, focusing on clinically relevant outcomes of teamwork, such as prevention of harm, may be more empowering feedback for the frontline. Formal cost‐benefit analyses and outcomes related to physician and nursing retention will be equally important for assessing the sustainability of the model. Involving patients and their caregivers and inviting their perspectives as care is redesigned will also be critical in maintaining patient centeredness. Research addressing interventions to mediate preventable readmission risk and understanding the drivers of patient satisfaction is also needed.

The true value of the model may be in its potential to monitor and drive change within itself. Continuously aligning aims, incentives, performance measures, and feedback will help support this innovation and drive. This affects not only patient care but creates microcosms within which research and education can thrive. We hope that our experience will help guide other institutions as we all strive in our journey to improve the care we deliver.

Despite an estimated annual $2.6 trillion expenditure on healthcare, the United States performs poorly on indicators of health and harm during care.[1, 2, 3] Hospitals around the nation are working to improve the care they deliver. We describe a model developed at our institution and report the evaluation of the outcomes associated with its implementation on the general medical and surgical units. The Indiana University Institutional Review Board approved this work.

SETTING AND DEFINITIONS

Indiana University Health Methodist Hospital (MH) is an academic center in Indianapolis, Indiana, serving over 30,000 patients annually.[4] In 2012, responding to the coexisting needs to improve quality and contain costs, the MH leadership team redesigned care in the hospital. The new model centers around accountable care teams (ACTs). Each ACT is a geographically defined set of providers accepting ownership for the clinical, service, and financial outcomes of their respective inpatient unit. The units studied are described in Table 1.

THE ACT MODEL

The model comprises 8 interventions rooted in 3 foundational domains: (1) enhancing interprofessional collaboration (IPC), (2) enabling data‐driven decisions, and (3) providing leadership. Each intervention is briefly described under its main focus (see Supporting Information, Appendix A, in the online version of this article for further details).

Implementation Timelines and ACT Scores

The development of the ACTs started in the spring of 2012. Physician, nursing, and pharmacy support was sought, and a pilot unit was formed in August 2012. The model was cascaded hospital wide by December 2013, with support from the ACT program director (A.N.). The program director observed and scored the uptake of each intervention by each unit monthly. A score of 1 denoted no implementation, whereas 5 denoted complete implementation. The criteria for scoring are presented in Table 2. The monthly scores for all 8 interventions in each of the 11 units were averaged as an overall ACT score, which reflects the implementation dose of the ACT model. Monthly domain scores for enhancing IPC and enabling data‐driven decisions were also calculated as the average score within each domain. This yielded 3 domain scores. Figure 1A plots by month the overall ACT score for the medical and surgical units, and Figure 1B plots the implementation score for the 3 domains between August 2012 and December 2013 for all units. The uptake of the interventions varied between units. This allowed our analysis to explore the dose relationships between the model and outcomes independent of underlying time trends that may be affected by concomitant initiatives.

Table 2.Scoring Grid

	1	2	3	4	5
NOTE: Abbreviations: ACT, accountable care team. *The ACT disciplines used for this scoring include the hospitalists, clinical nurse specialists, pharmacists, case managers, and social workers. Members of the ACT team not included in the scoring scheme include unit nurse managers, nursing, charge nurse, physical therapists, nutrition support, and occupational therapists. The maximum number of specialists on any unit is 3 (eg, cardiothoracic surgery, cardiology, and vascular surgery on the cardiovascular surgery unit). For general medical units, a score of 3 would be the next score possible after 1.
Geographical cohorting of patients and the ACT*	None	At least 1 discipline comprising the ACT is unit based	All disciplines comprising the ACT except the hospitalist unit based	All disciplines including the hospitalist unit based	4 + 80% of hospitalist provider's patients on the unit
Bedside collaborative rounding	None	Occurring 1 day a week on at least 25% of the patients on the unit	Occurring 2 to 3 days a week on at least 50% of the patients on the unit	Occurring 3 to 4 days a week on at least 75% of the patients on the unit	Occurring MondayFriday on all patients on the unit
Daily huddle	None	Occurring daily, 1 out of 4 ACT disciplines represented, at least 25% of patients on the unit discussed	Occurring daily, 2 out of 4 ACT disciplines represented, at least 50% of patients on the unit discussed	Occurring daily, 3 out of 4 ACT disciplines represented, at least 75% of patients on the unit discussed	Occurring daily, all disciplines of the ACT represented, all patients on the unit discussed
Hospitalist and specialty comanagement agreements	None	One out of 3 specialists represented on the unit collaborating with the hospitalists on at least 25% of relevant patients	One out of 3 specialists represented on the unit collaborating with the hospitalists on at least 50% of relevant patients	Two out of 3 specialists on the unit collaborating with the hospitalists on at least 75% of relevant patients	All specialists on the unit collaborating with the hospitalists on all relevant patients on the unit
Unit white board	None	Present but only used by nursing	Present and used by all ACT disciplines except physician providers	Present and used by entire ACT; use inconsistent	Present and used MondayFriday by all disciplines of ACT
Monthly review of unit level data	None	Nurse manager reviewing data with ACT program director	Nurse manager and unit leader reviewing data with ACT program director	Meeting either not consistently occurring monthly or not consistently attended by entire ACT	Monthly meeting with entire ACT
Weekly patient satisfaction rounding	None	Nurse manager performing up to 1 week a month	Nurse manager performing weekly	Nurse and physician leader performing up to 3 times a month	Nurse and physician leader performing weekly
Leadership	None	For units with specialties, either hospitalist or specialist leader identified	Both hospitalist and specialist leader Identified	Both hospitalist and specialist leaders (where applicable) identified and partially engaged in leadership role	Both hospitalist and specialist leaders (where applicable) identified and engaged in leadership role

Figure 1

Outcomes

Monthly data between August 2012 and December 2013 were analyzed.

Measures of Value

MH is a member of the University Health Consortium, which measures outcomes of participants relative to their peers. MH measures LOS index as a ratio of observed LOS to expected LOS that is adjusted for severity of illness.[5]

Variable direct costs (VDCs) are costs that a hospital can save if a service is not provided.[6] A hospital's case‐mix index (CMI) represents the average diagnosis‐related group relative weight for that hospital. We track VDCs adjusted for CMI (CMI‐adjusted VDC).[7]

Thirty‐day readmission rate is the percentage of cases that are readmitted to MH within 30 days of discharge from the index admission.[8]

Measures of Patient Satisfaction

The Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey covers topics relevant to a patient's experience in the hospital.[9] Patient satisfaction scores are tracked by responses to the HCAHPS survey.

Measures of Provider Satisfaction

Hospitalist and specialty providers, leadership, and case management teams were surveyed via email through SurveyMonkey in July 2014. The survey included Likert responses that elicited opinions and comments about the ACT model.

RESULTS

The overall ACT score was associated with LOS index and CMI‐adjusted VDC (both P < 0.001). For every 1‐unit increase in the overall ACT score, LOS index decreased by 0.078 and CMI‐adjusted VDC decreased by $273.99 (Table 3).

Looking at domains, enhancing IPC resulted in statistically significant decreases in both LOS index and CMI‐adjusted VDC, but providing leadership and enabling data‐driven decisions decreased only the LOS index. Most of the 8 individual interventions were associated with at least 1 of these 2 outcomes. (Even where the associations were not significant, they were all in the direction of decreasing LOS and cost). In these models, the covariate of type of units (medical vs surgical) was not associated with LOS or cost. There was no significant time trend in LOS or cost, except in models where an intervention had no association with either outcome. Inclusion of all individual effective interventions in the same statistical model to assess their relative contributions was not possible because they were highly correlated (correlations 0.450.89).

Thirty‐day readmissions and patient satisfaction were not significantly associated with the overall ACT score, but exploratory analyses showed that patient satisfaction increased with the implementation of geographical cohorting (P = 0.007).

DISCUSSION

The serious problems in US healthcare constitute an urgent imperative to innovate and reform.[10] Inpatient care reflects 31% of the expenditure on healthcare, and in 2010, 35.1 million patients were discharged from the hospital after spending an average of 4.8 days as an inpatient.[11] These figures represent an immense opportunity to intervene. Measuring the impact of quality improvement efforts is often complicated by concomitant changes that affect outcomes over the interval studied. Our approach allowed us to detect statistically significant changes in LOS index and CMI‐adjusted VDC associated with the ACT implementation dose that could be separated from the underlying time trends.

The ACT model we describe is rooted in improving 3 foundational domains; quantifying each intervention's compartmentalized contribution, however, proved difficult. Each intervention intertwines with the others to create changes in attitudes, knowledge, and culture that are difficult to measure yet may synergistically affect outcomes. For example, although geographical cohorting appears to have the strongest statistical association with outcomes, this may be mediated by how it enables other processes to take place more effectively. Based on this analysis, therefore, the ACT model may best be considered a bundled intervention.

The team caring for a patient during hospitalization is so complex that fewer than a quarter of patients know their physician's or nurse's name.[12] This complexity impairs communication between patients and providers and between the providers themselves. Communication failures are consistently identified as root causes in sentinel events reported to the Joint Commission.[13] IPC is the process by which different professional groups work together to positively impact health care. IPC overlaps with communication, coordination, and teamwork, and improvements in IPC may improve care.[14] Some elements of the model we describe have been tested previously.[15, 16, 17] Localization of teams may increase productivity and the frequency with which physicians and nurses communicate. Localization also decreases the number of pages received and steps walked by providers during a workday.[15, 16, 17] However, these studies reported a trend toward an increase in the LOS and neutral effects on cost and readmission rates. We found statistically significant decreases in both LOS and cost associated with the geographic cohorting of patients and providers. Notably, our model localized not only the physician providers but also the interdisciplinary team of pharmacists, clinical nurse specialists, case managers, and social workers. This proximity may facilitate IPC between all members that culminates in improved efficiency. The possibility of delays in discharges to avoid new admissions in a geographically structured team has previously been raised to explain the associated increases in LOS.[16, 17] The accountability of each unit for its metrics, the communication between nursing and physicians, and the timely availability of the unit's performance data aligns everyone toward a shared goal and provides some protection from an unintended consequence.

Structured interdisciplinary rounds decrease adverse events and improve teamwork ratings.[18, 19] The huddle in our model is a forum to collaborate between disciplines that proved to be effective in decreasing LOS and costs. Our huddle aims to discuss all the patients on the unit. This allows the team to assist each other in problem solving for the entire unit and not just the patients on the geographically cohorted team. This approach, in addition to the improved IPC fostered by the ACT model, may help explain how benefits in LOS and costs permeated across all 11 diverse units despite the presence of patients who are not directly served by the geographically cohorted team.

High‐performing clinical systems maintain an awareness of their overarching mission and unit‐based leaders can influence the frontline by reiterating the organizational mission and aligning efforts with outcomes.[20] Our leadership model is similar to those described by other institutions in the strong partnerships between physicians and nursing.[21] As outlined by Kim et al., investing in the professional development of the unit leaders may help them fulfill their roles and serve the organization better.[21]

The fragmentation and lack of ownership over the continuum of patient care causes duplication and waste. The proposal in the Accountable Care Act to create accountable care organizations is rooted in the understanding that providers and organizations will seek out new ways of improving quality when held accountable for their outcomes.[22] To foster ownership and accountability, reporting of metrics at the unit level is needed. Furthermore, an informational infrastructure is critical, as improvements cannot occur without the availability of data to both monitor performance and measure the effect of interventions.[10, 23] Even without any other interventions, providing feedback alone is an effective way of changing practices.[24] According to Berwick et al., this phenomenon reflects practitioners' intrinsic motivation to simply want to be better.[25] Our monthly review of each unit's data is an effective way to provide timely feedback to the frontline that sparks pride, ownership, and innovative thinking.

Based on our mean ACT score and CMI‐adjusted VDC reductions alone, we estimate savings of $649.36 per hospitalization (mean increase in ACT implementation of 2.37 times reduction in cost index of $273.99 per unit increase in overall ACT score). This figure does not include savings realized through reductions in LOS. This is a small decrease relative to the mean cost of hospitalization, yet when compounded over the annual MH census, it would result in substantial savings. The model relied on the restructuring of the existing workforce and the only direct additional cost was the early salary support for the ACT program director.

FURTHER DIRECTIONS

Although there is a need to improve our healthcare system, interventions should be deliberate and evidence based wherever possible.[26] Geographic cohorting may decrease the frequency of paging interruptions for physicians and practitioners while increasing face‐to‐face interruptions.[27] The net effect on safety with this trade‐off should be investigated.

The presence of an intervention does not guarantee its success. Despite geographic cohorting and interdisciplinary meetings, communication that influences physician decision making may not improve.[28] Although instruments to measure ratings of team work and collaboration are available, focusing on clinically relevant outcomes of teamwork, such as prevention of harm, may be more empowering feedback for the frontline. Formal cost‐benefit analyses and outcomes related to physician and nursing retention will be equally important for assessing the sustainability of the model. Involving patients and their caregivers and inviting their perspectives as care is redesigned will also be critical in maintaining patient centeredness. Research addressing interventions to mediate preventable readmission risk and understanding the drivers of patient satisfaction is also needed.

The true value of the model may be in its potential to monitor and drive change within itself. Continuously aligning aims, incentives, performance measures, and feedback will help support this innovation and drive. This affects not only patient care but creates microcosms within which research and education can thrive. We hope that our experience will help guide other institutions as we all strive in our journey to improve the care we deliver.

Despite an estimated annual $2.6 trillion expenditure on healthcare, the United States performs poorly on indicators of health and harm during care.[1, 2, 3] Hospitals around the nation are working to improve the care they deliver. We describe a model developed at our institution and report the evaluation of the outcomes associated with its implementation on the general medical and surgical units. The Indiana University Institutional Review Board approved this work.

SETTING AND DEFINITIONS

Indiana University Health Methodist Hospital (MH) is an academic center in Indianapolis, Indiana, serving over 30,000 patients annually.[4] In 2012, responding to the coexisting needs to improve quality and contain costs, the MH leadership team redesigned care in the hospital. The new model centers around accountable care teams (ACTs). Each ACT is a geographically defined set of providers accepting ownership for the clinical, service, and financial outcomes of their respective inpatient unit. The units studied are described in Table 1.

THE ACT MODEL

The model comprises 8 interventions rooted in 3 foundational domains: (1) enhancing interprofessional collaboration (IPC), (2) enabling data‐driven decisions, and (3) providing leadership. Each intervention is briefly described under its main focus (see Supporting Information, Appendix A, in the online version of this article for further details).

Implementation Timelines and ACT Scores

The development of the ACTs started in the spring of 2012. Physician, nursing, and pharmacy support was sought, and a pilot unit was formed in August 2012. The model was cascaded hospital wide by December 2013, with support from the ACT program director (A.N.). The program director observed and scored the uptake of each intervention by each unit monthly. A score of 1 denoted no implementation, whereas 5 denoted complete implementation. The criteria for scoring are presented in Table 2. The monthly scores for all 8 interventions in each of the 11 units were averaged as an overall ACT score, which reflects the implementation dose of the ACT model. Monthly domain scores for enhancing IPC and enabling data‐driven decisions were also calculated as the average score within each domain. This yielded 3 domain scores. Figure 1A plots by month the overall ACT score for the medical and surgical units, and Figure 1B plots the implementation score for the 3 domains between August 2012 and December 2013 for all units. The uptake of the interventions varied between units. This allowed our analysis to explore the dose relationships between the model and outcomes independent of underlying time trends that may be affected by concomitant initiatives.

Table 2.Scoring Grid

	1	2	3	4	5
NOTE: Abbreviations: ACT, accountable care team. *The ACT disciplines used for this scoring include the hospitalists, clinical nurse specialists, pharmacists, case managers, and social workers. Members of the ACT team not included in the scoring scheme include unit nurse managers, nursing, charge nurse, physical therapists, nutrition support, and occupational therapists. The maximum number of specialists on any unit is 3 (eg, cardiothoracic surgery, cardiology, and vascular surgery on the cardiovascular surgery unit). For general medical units, a score of 3 would be the next score possible after 1.
Geographical cohorting of patients and the ACT*	None	At least 1 discipline comprising the ACT is unit based	All disciplines comprising the ACT except the hospitalist unit based	All disciplines including the hospitalist unit based	4 + 80% of hospitalist provider's patients on the unit
Bedside collaborative rounding	None	Occurring 1 day a week on at least 25% of the patients on the unit	Occurring 2 to 3 days a week on at least 50% of the patients on the unit	Occurring 3 to 4 days a week on at least 75% of the patients on the unit	Occurring MondayFriday on all patients on the unit
Daily huddle	None	Occurring daily, 1 out of 4 ACT disciplines represented, at least 25% of patients on the unit discussed	Occurring daily, 2 out of 4 ACT disciplines represented, at least 50% of patients on the unit discussed	Occurring daily, 3 out of 4 ACT disciplines represented, at least 75% of patients on the unit discussed	Occurring daily, all disciplines of the ACT represented, all patients on the unit discussed
Hospitalist and specialty comanagement agreements	None	One out of 3 specialists represented on the unit collaborating with the hospitalists on at least 25% of relevant patients	One out of 3 specialists represented on the unit collaborating with the hospitalists on at least 50% of relevant patients	Two out of 3 specialists on the unit collaborating with the hospitalists on at least 75% of relevant patients	All specialists on the unit collaborating with the hospitalists on all relevant patients on the unit
Unit white board	None	Present but only used by nursing	Present and used by all ACT disciplines except physician providers	Present and used by entire ACT; use inconsistent	Present and used MondayFriday by all disciplines of ACT
Monthly review of unit level data	None	Nurse manager reviewing data with ACT program director	Nurse manager and unit leader reviewing data with ACT program director	Meeting either not consistently occurring monthly or not consistently attended by entire ACT	Monthly meeting with entire ACT
Weekly patient satisfaction rounding	None	Nurse manager performing up to 1 week a month	Nurse manager performing weekly	Nurse and physician leader performing up to 3 times a month	Nurse and physician leader performing weekly
Leadership	None	For units with specialties, either hospitalist or specialist leader identified	Both hospitalist and specialist leader Identified	Both hospitalist and specialist leaders (where applicable) identified and partially engaged in leadership role	Both hospitalist and specialist leaders (where applicable) identified and engaged in leadership role

Figure 1

Outcomes

Monthly data between August 2012 and December 2013 were analyzed.

Measures of Value

MH is a member of the University Health Consortium, which measures outcomes of participants relative to their peers. MH measures LOS index as a ratio of observed LOS to expected LOS that is adjusted for severity of illness.[5]

Variable direct costs (VDCs) are costs that a hospital can save if a service is not provided.[6] A hospital's case‐mix index (CMI) represents the average diagnosis‐related group relative weight for that hospital. We track VDCs adjusted for CMI (CMI‐adjusted VDC).[7]

Thirty‐day readmission rate is the percentage of cases that are readmitted to MH within 30 days of discharge from the index admission.[8]

Measures of Patient Satisfaction

The Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey covers topics relevant to a patient's experience in the hospital.[9] Patient satisfaction scores are tracked by responses to the HCAHPS survey.

Measures of Provider Satisfaction

Hospitalist and specialty providers, leadership, and case management teams were surveyed via email through SurveyMonkey in July 2014. The survey included Likert responses that elicited opinions and comments about the ACT model.

RESULTS

The overall ACT score was associated with LOS index and CMI‐adjusted VDC (both P < 0.001). For every 1‐unit increase in the overall ACT score, LOS index decreased by 0.078 and CMI‐adjusted VDC decreased by $273.99 (Table 3).

Looking at domains, enhancing IPC resulted in statistically significant decreases in both LOS index and CMI‐adjusted VDC, but providing leadership and enabling data‐driven decisions decreased only the LOS index. Most of the 8 individual interventions were associated with at least 1 of these 2 outcomes. (Even where the associations were not significant, they were all in the direction of decreasing LOS and cost). In these models, the covariate of type of units (medical vs surgical) was not associated with LOS or cost. There was no significant time trend in LOS or cost, except in models where an intervention had no association with either outcome. Inclusion of all individual effective interventions in the same statistical model to assess their relative contributions was not possible because they were highly correlated (correlations 0.450.89).

Thirty‐day readmissions and patient satisfaction were not significantly associated with the overall ACT score, but exploratory analyses showed that patient satisfaction increased with the implementation of geographical cohorting (P = 0.007).

DISCUSSION

The serious problems in US healthcare constitute an urgent imperative to innovate and reform.[10] Inpatient care reflects 31% of the expenditure on healthcare, and in 2010, 35.1 million patients were discharged from the hospital after spending an average of 4.8 days as an inpatient.[11] These figures represent an immense opportunity to intervene. Measuring the impact of quality improvement efforts is often complicated by concomitant changes that affect outcomes over the interval studied. Our approach allowed us to detect statistically significant changes in LOS index and CMI‐adjusted VDC associated with the ACT implementation dose that could be separated from the underlying time trends.

The ACT model we describe is rooted in improving 3 foundational domains; quantifying each intervention's compartmentalized contribution, however, proved difficult. Each intervention intertwines with the others to create changes in attitudes, knowledge, and culture that are difficult to measure yet may synergistically affect outcomes. For example, although geographical cohorting appears to have the strongest statistical association with outcomes, this may be mediated by how it enables other processes to take place more effectively. Based on this analysis, therefore, the ACT model may best be considered a bundled intervention.

The team caring for a patient during hospitalization is so complex that fewer than a quarter of patients know their physician's or nurse's name.[12] This complexity impairs communication between patients and providers and between the providers themselves. Communication failures are consistently identified as root causes in sentinel events reported to the Joint Commission.[13] IPC is the process by which different professional groups work together to positively impact health care. IPC overlaps with communication, coordination, and teamwork, and improvements in IPC may improve care.[14] Some elements of the model we describe have been tested previously.[15, 16, 17] Localization of teams may increase productivity and the frequency with which physicians and nurses communicate. Localization also decreases the number of pages received and steps walked by providers during a workday.[15, 16, 17] However, these studies reported a trend toward an increase in the LOS and neutral effects on cost and readmission rates. We found statistically significant decreases in both LOS and cost associated with the geographic cohorting of patients and providers. Notably, our model localized not only the physician providers but also the interdisciplinary team of pharmacists, clinical nurse specialists, case managers, and social workers. This proximity may facilitate IPC between all members that culminates in improved efficiency. The possibility of delays in discharges to avoid new admissions in a geographically structured team has previously been raised to explain the associated increases in LOS.[16, 17] The accountability of each unit for its metrics, the communication between nursing and physicians, and the timely availability of the unit's performance data aligns everyone toward a shared goal and provides some protection from an unintended consequence.

Structured interdisciplinary rounds decrease adverse events and improve teamwork ratings.[18, 19] The huddle in our model is a forum to collaborate between disciplines that proved to be effective in decreasing LOS and costs. Our huddle aims to discuss all the patients on the unit. This allows the team to assist each other in problem solving for the entire unit and not just the patients on the geographically cohorted team. This approach, in addition to the improved IPC fostered by the ACT model, may help explain how benefits in LOS and costs permeated across all 11 diverse units despite the presence of patients who are not directly served by the geographically cohorted team.

High‐performing clinical systems maintain an awareness of their overarching mission and unit‐based leaders can influence the frontline by reiterating the organizational mission and aligning efforts with outcomes.[20] Our leadership model is similar to those described by other institutions in the strong partnerships between physicians and nursing.[21] As outlined by Kim et al., investing in the professional development of the unit leaders may help them fulfill their roles and serve the organization better.[21]

The fragmentation and lack of ownership over the continuum of patient care causes duplication and waste. The proposal in the Accountable Care Act to create accountable care organizations is rooted in the understanding that providers and organizations will seek out new ways of improving quality when held accountable for their outcomes.[22] To foster ownership and accountability, reporting of metrics at the unit level is needed. Furthermore, an informational infrastructure is critical, as improvements cannot occur without the availability of data to both monitor performance and measure the effect of interventions.[10, 23] Even without any other interventions, providing feedback alone is an effective way of changing practices.[24] According to Berwick et al., this phenomenon reflects practitioners' intrinsic motivation to simply want to be better.[25] Our monthly review of each unit's data is an effective way to provide timely feedback to the frontline that sparks pride, ownership, and innovative thinking.

Based on our mean ACT score and CMI‐adjusted VDC reductions alone, we estimate savings of $649.36 per hospitalization (mean increase in ACT implementation of 2.37 times reduction in cost index of $273.99 per unit increase in overall ACT score). This figure does not include savings realized through reductions in LOS. This is a small decrease relative to the mean cost of hospitalization, yet when compounded over the annual MH census, it would result in substantial savings. The model relied on the restructuring of the existing workforce and the only direct additional cost was the early salary support for the ACT program director.

FURTHER DIRECTIONS

Although there is a need to improve our healthcare system, interventions should be deliberate and evidence based wherever possible.[26] Geographic cohorting may decrease the frequency of paging interruptions for physicians and practitioners while increasing face‐to‐face interruptions.[27] The net effect on safety with this trade‐off should be investigated.

The presence of an intervention does not guarantee its success. Despite geographic cohorting and interdisciplinary meetings, communication that influences physician decision making may not improve.[28] Although instruments to measure ratings of team work and collaboration are available, focusing on clinically relevant outcomes of teamwork, such as prevention of harm, may be more empowering feedback for the frontline. Formal cost‐benefit analyses and outcomes related to physician and nursing retention will be equally important for assessing the sustainability of the model. Involving patients and their caregivers and inviting their perspectives as care is redesigned will also be critical in maintaining patient centeredness. Research addressing interventions to mediate preventable readmission risk and understanding the drivers of patient satisfaction is also needed.

The true value of the model may be in its potential to monitor and drive change within itself. Continuously aligning aims, incentives, performance measures, and feedback will help support this innovation and drive. This affects not only patient care but creates microcosms within which research and education can thrive. We hope that our experience will help guide other institutions as we all strive in our journey to improve the care we deliver.

In 2001, approximately 12.6 million individuals age 65 and older were discharged from American hospitals with an average length of stay of 5.8 days1 and up to 66% of them suffered from cognitive impairment (CI).220 CI in hospitalized older adults includes a variety of disorders ranging from mild cognitive deficit, delirium, to full‐blown dementia. Dementia is a syndrome of decline in memory plus at least 1 other cognitive domain, such as language, visuospatial, or executive function sufficient to interfere with social or occupational functioning in an alert person.21 Delirium is a disturbance of consciousness with reduced ability to focus, sustain, or shift attention that occurs over a short period of time and tends to fluctuate over the course of the day.22 Mild CI without dementia is defined as the presence of a cognitive deficit in the absence of delirium that does not affect functional performance.23

Hospitalized older adults with CI are vulnerable to hospital complications, including delirium, physical restraints, urinary catheters, and tethers.2, 3, 2435 The management of their medical or surgical illnesses requires avoiding certain medications with anticholinergic activities that might worsen cognition.36 Furthermore, CI may delay diagnostic and therapeutic procedures, demand more time for informed consentrelated issues, and result in difficulty in adherence to medical recommendations.37, 38 The special needs of hospitalized older adults with delirium and dementia has been shown to increase demands on nursing staff, risk of postdischarge institutionalization, length of stay, and health care costs.310, 27, 3948 We wanted to look specifically at CI because it often goes undetected4951 and can have a great impact on the hospital course of elders.

Screening for CI among hospitalized older adults has been considered to have potential benefit in hospital care of older adults.52 Screening may lead to early detection by uncovering subtle symptoms not yet apparent to families or other caregivers who know the patient well but do not notice small declines or changes in day‐to‐day functioning. Early recognition of CI may lead to early treatment and subsequently may delay progression of cognitive decline and improve health outcomes. Screening may enhance physician prescribing practices and reduce exposure to harmful medications among these vulnerable patients. Finally, delirium is an important prognostic indicator, and screening patients could provide invaluable information toward the overall clinical picture. Despite all of this, the current literature does not provide sufficient information to support the use of routine screening on admission.220, 41, 5254 Most of the published studies were conducted among elders who stayed in the hospital for more than 48 hours, missing data on the crucial first 48 hours of the hospital course.220, 41, 5254 These studies did not evaluate the impact of unrecognized CI on the hospital course and the majority of these studies were not conducted in the urban and lower socioeconomic status populations of elders that are the most vulnerable to bad health outcomes.220, 41, 5254 Finally, few studies evaluated the impact of delirium superimposed on CI on the hospital course and mortality of elders.220, 41, 5254

With these details in mind, we wanted to explore the impact of CI recognition among patients age 65 years and older admitted to the medical services of an urban, public hospital in Indianapolis to determine the prevalence and the impact of recognized and unrecognized CI on the hospital course of these elders. Furthermore, we examined the role of delirium superimposed on these hospitalized elders with CI.

Patients and Methods

The study was approved by the Indiana University Purdue University at Indianapolis Institutional Review Board (IRB).

Results

Discussion

Our study found that in an urban, public hospital, acute or preexisting CI affects more than one‐third of hospitalized elders admitted to general medical services. Unfortunately, our hospital system does not currently recognize the majority of these vulnerable patients. Our study also found that delirium affects more than one‐third of hospitalized elders with CI during their hospital course. Delirium complicates hospital care by prolonging length of stay and decreasing the probability of surviving and getting discharged home. It leads to high use of Foley catheterization, physical restraints, and tethers.

The high prevalence of CI with and without delirium in our cohort is within the rates reported previously in the literature. It is estimated that the prevalence of CI in hospitalized older adults ranges from 14% to 66%, depending on the method used to measure cognition, the definition of CI, and the type of hospital ward (surgical, medical, and geriatric units).220 One particular study that used a similar cognitive assessment method reported higher prevalence rates for both CI and delirium.11 The study randomly evaluated a sample of 201 patients age 65 and over who were hospitalized for a medical illness and found that 56% of the cohort suffered from CI and among those with CI, 47% had delirium.11 The difference between this finding and our study is most likely due to our sampling technique; more than 70% of our cognitive screening occurred in the first 48 hours of hospital admission whereas the Australian study, in similar enrollment criteria to all of the published studies in this area, excluded patients who were discharged within 48 hours of admission. We believe, however, that by including the first 48 hours of admission in our design, our study provides a more generalizable reflection of the actual acute care experience.

The impact of delirium on the course of hospital care found in our study supports some of the findings from previous studies conducted in the past 2 decades.5, 6, 11 Despite 2 decades of clinical research, delirium continues to increase mortality, hospital stays, and posthospital institutionalization.

We were surprised to find that patients suffering from delirium continue to receive at least 1 definite anticholinergic medication. Such medications are considered inappropriate among patients with any form of cognitive impairment.36, 62 Although the impact of anticholinergic medications on hospitalized outcomes is less well‐described, their use has been suspected to negatively impact long‐term outcomes of cognitive impairment.61, 63 Our study found no difference in the use of anticholinergic medications between those with CI who experienced delirium and those who did not; however, the total burden of anticholinergic medication was not assessed in a quantitative manner. It is still unknown if certain anticholinergic medications or a cumulative effect of anticholinergic medications may impact cognitive or health‐related outcomes in a vulnerable older population with CI.

Although our study reported for the first time in a systematic way the rate of undocumented CI among hospitalized elders found to have CI on admission, we found no impact of such underrecognition on the length of hospital stay, mortality, discharge location, and delirium occurrence. Although the use of anticholinergic medications is not recommended for patients with any form of CI, our results indicate that a significant number of patients with cognitive impairment continue to receive inappropriate medications. CI recognition in the elderly was not shown to have a statistically significant affect on length of stay, cost, or mortality.

Our study has some limitations. First of all, we did not determine the underlying types of CI such as Alzheimer disease, vascular dementia, mild cognitive impairment, or reversible etiology other than delirium. Such a categorization requires posthospital assessment, which was not included in our study design. Second, our delirium incidence rate and delirium impact on hospital outcomes might be very conservative and may underestimate its true prevalence and correlation due to our data collection methods. Despite the fluctuating nature of delirium, our study was not designed to assess the presence of delirium every shift and tried to assess cognitive function on a daily basis throughout the patient's hospitalization. Therefore, the severity and duration of delirium could not be accurately assessed. Our reported rates of use of Foley catheterization, physical restraints, and tethers are also very conservative and we could not determine the appropriateness of these procedures. Our study was conducted in 1 public hospital in an urban city with a higher percentage of African Americans. Thus, our sample is not a true representative sample. However, studies with significant representation of minority groups are not common in the research literature, especially in CI research; we hope to fulfill some of the gaps in the literature regarding the most vulnerable older American population. Finally, we were limited in our use of ICD‐9 coding to determine if patients had previously been recognized by other providers as having CI. ICD‐9 coding, while useful, is not perfect in identifying all if a patient's medical problems. Use of coding to determine whether a patient had been recognized as impaired also does not allow us to determine when the diagnosis was made.

In conclusion, our study evaluated cognitive impairment in hospitalized elders and found that in our cohort of 997 patients, 43% were cognitively impaired on admission. Of those with CI, 61% were not documented or recognized as impaired. We found no statistically significant difference between those with documented CI and those with undocumented CI in terms of length of stay, mortality, home discharge, readmission rates, incidence of delirium, or potential to receive anticholinergics or restraints. Among those with CI, 38% had delirium. Those with delirium experienced increased length of stay, decreased discharge to home, and increased use of Foley catheters and restraints.

In 2001, approximately 12.6 million individuals age 65 and older were discharged from American hospitals with an average length of stay of 5.8 days1 and up to 66% of them suffered from cognitive impairment (CI).220 CI in hospitalized older adults includes a variety of disorders ranging from mild cognitive deficit, delirium, to full‐blown dementia. Dementia is a syndrome of decline in memory plus at least 1 other cognitive domain, such as language, visuospatial, or executive function sufficient to interfere with social or occupational functioning in an alert person.21 Delirium is a disturbance of consciousness with reduced ability to focus, sustain, or shift attention that occurs over a short period of time and tends to fluctuate over the course of the day.22 Mild CI without dementia is defined as the presence of a cognitive deficit in the absence of delirium that does not affect functional performance.23

Hospitalized older adults with CI are vulnerable to hospital complications, including delirium, physical restraints, urinary catheters, and tethers.2, 3, 2435 The management of their medical or surgical illnesses requires avoiding certain medications with anticholinergic activities that might worsen cognition.36 Furthermore, CI may delay diagnostic and therapeutic procedures, demand more time for informed consentrelated issues, and result in difficulty in adherence to medical recommendations.37, 38 The special needs of hospitalized older adults with delirium and dementia has been shown to increase demands on nursing staff, risk of postdischarge institutionalization, length of stay, and health care costs.310, 27, 3948 We wanted to look specifically at CI because it often goes undetected4951 and can have a great impact on the hospital course of elders.

Screening for CI among hospitalized older adults has been considered to have potential benefit in hospital care of older adults.52 Screening may lead to early detection by uncovering subtle symptoms not yet apparent to families or other caregivers who know the patient well but do not notice small declines or changes in day‐to‐day functioning. Early recognition of CI may lead to early treatment and subsequently may delay progression of cognitive decline and improve health outcomes. Screening may enhance physician prescribing practices and reduce exposure to harmful medications among these vulnerable patients. Finally, delirium is an important prognostic indicator, and screening patients could provide invaluable information toward the overall clinical picture. Despite all of this, the current literature does not provide sufficient information to support the use of routine screening on admission.220, 41, 5254 Most of the published studies were conducted among elders who stayed in the hospital for more than 48 hours, missing data on the crucial first 48 hours of the hospital course.220, 41, 5254 These studies did not evaluate the impact of unrecognized CI on the hospital course and the majority of these studies were not conducted in the urban and lower socioeconomic status populations of elders that are the most vulnerable to bad health outcomes.220, 41, 5254 Finally, few studies evaluated the impact of delirium superimposed on CI on the hospital course and mortality of elders.220, 41, 5254

With these details in mind, we wanted to explore the impact of CI recognition among patients age 65 years and older admitted to the medical services of an urban, public hospital in Indianapolis to determine the prevalence and the impact of recognized and unrecognized CI on the hospital course of these elders. Furthermore, we examined the role of delirium superimposed on these hospitalized elders with CI.

Patients and Methods

The study was approved by the Indiana University Purdue University at Indianapolis Institutional Review Board (IRB).

Results

Discussion

Our study found that in an urban, public hospital, acute or preexisting CI affects more than one‐third of hospitalized elders admitted to general medical services. Unfortunately, our hospital system does not currently recognize the majority of these vulnerable patients. Our study also found that delirium affects more than one‐third of hospitalized elders with CI during their hospital course. Delirium complicates hospital care by prolonging length of stay and decreasing the probability of surviving and getting discharged home. It leads to high use of Foley catheterization, physical restraints, and tethers.

The high prevalence of CI with and without delirium in our cohort is within the rates reported previously in the literature. It is estimated that the prevalence of CI in hospitalized older adults ranges from 14% to 66%, depending on the method used to measure cognition, the definition of CI, and the type of hospital ward (surgical, medical, and geriatric units).220 One particular study that used a similar cognitive assessment method reported higher prevalence rates for both CI and delirium.11 The study randomly evaluated a sample of 201 patients age 65 and over who were hospitalized for a medical illness and found that 56% of the cohort suffered from CI and among those with CI, 47% had delirium.11 The difference between this finding and our study is most likely due to our sampling technique; more than 70% of our cognitive screening occurred in the first 48 hours of hospital admission whereas the Australian study, in similar enrollment criteria to all of the published studies in this area, excluded patients who were discharged within 48 hours of admission. We believe, however, that by including the first 48 hours of admission in our design, our study provides a more generalizable reflection of the actual acute care experience.

The impact of delirium on the course of hospital care found in our study supports some of the findings from previous studies conducted in the past 2 decades.5, 6, 11 Despite 2 decades of clinical research, delirium continues to increase mortality, hospital stays, and posthospital institutionalization.

We were surprised to find that patients suffering from delirium continue to receive at least 1 definite anticholinergic medication. Such medications are considered inappropriate among patients with any form of cognitive impairment.36, 62 Although the impact of anticholinergic medications on hospitalized outcomes is less well‐described, their use has been suspected to negatively impact long‐term outcomes of cognitive impairment.61, 63 Our study found no difference in the use of anticholinergic medications between those with CI who experienced delirium and those who did not; however, the total burden of anticholinergic medication was not assessed in a quantitative manner. It is still unknown if certain anticholinergic medications or a cumulative effect of anticholinergic medications may impact cognitive or health‐related outcomes in a vulnerable older population with CI.

Although our study reported for the first time in a systematic way the rate of undocumented CI among hospitalized elders found to have CI on admission, we found no impact of such underrecognition on the length of hospital stay, mortality, discharge location, and delirium occurrence. Although the use of anticholinergic medications is not recommended for patients with any form of CI, our results indicate that a significant number of patients with cognitive impairment continue to receive inappropriate medications. CI recognition in the elderly was not shown to have a statistically significant affect on length of stay, cost, or mortality.

Our study has some limitations. First of all, we did not determine the underlying types of CI such as Alzheimer disease, vascular dementia, mild cognitive impairment, or reversible etiology other than delirium. Such a categorization requires posthospital assessment, which was not included in our study design. Second, our delirium incidence rate and delirium impact on hospital outcomes might be very conservative and may underestimate its true prevalence and correlation due to our data collection methods. Despite the fluctuating nature of delirium, our study was not designed to assess the presence of delirium every shift and tried to assess cognitive function on a daily basis throughout the patient's hospitalization. Therefore, the severity and duration of delirium could not be accurately assessed. Our reported rates of use of Foley catheterization, physical restraints, and tethers are also very conservative and we could not determine the appropriateness of these procedures. Our study was conducted in 1 public hospital in an urban city with a higher percentage of African Americans. Thus, our sample is not a true representative sample. However, studies with significant representation of minority groups are not common in the research literature, especially in CI research; we hope to fulfill some of the gaps in the literature regarding the most vulnerable older American population. Finally, we were limited in our use of ICD‐9 coding to determine if patients had previously been recognized by other providers as having CI. ICD‐9 coding, while useful, is not perfect in identifying all if a patient's medical problems. Use of coding to determine whether a patient had been recognized as impaired also does not allow us to determine when the diagnosis was made.

In conclusion, our study evaluated cognitive impairment in hospitalized elders and found that in our cohort of 997 patients, 43% were cognitively impaired on admission. Of those with CI, 61% were not documented or recognized as impaired. We found no statistically significant difference between those with documented CI and those with undocumented CI in terms of length of stay, mortality, home discharge, readmission rates, incidence of delirium, or potential to receive anticholinergics or restraints. Among those with CI, 38% had delirium. Those with delirium experienced increased length of stay, decreased discharge to home, and increased use of Foley catheters and restraints.

In 2001, approximately 12.6 million individuals age 65 and older were discharged from American hospitals with an average length of stay of 5.8 days1 and up to 66% of them suffered from cognitive impairment (CI).220 CI in hospitalized older adults includes a variety of disorders ranging from mild cognitive deficit, delirium, to full‐blown dementia. Dementia is a syndrome of decline in memory plus at least 1 other cognitive domain, such as language, visuospatial, or executive function sufficient to interfere with social or occupational functioning in an alert person.21 Delirium is a disturbance of consciousness with reduced ability to focus, sustain, or shift attention that occurs over a short period of time and tends to fluctuate over the course of the day.22 Mild CI without dementia is defined as the presence of a cognitive deficit in the absence of delirium that does not affect functional performance.23

Hospitalized older adults with CI are vulnerable to hospital complications, including delirium, physical restraints, urinary catheters, and tethers.2, 3, 2435 The management of their medical or surgical illnesses requires avoiding certain medications with anticholinergic activities that might worsen cognition.36 Furthermore, CI may delay diagnostic and therapeutic procedures, demand more time for informed consentrelated issues, and result in difficulty in adherence to medical recommendations.37, 38 The special needs of hospitalized older adults with delirium and dementia has been shown to increase demands on nursing staff, risk of postdischarge institutionalization, length of stay, and health care costs.310, 27, 3948 We wanted to look specifically at CI because it often goes undetected4951 and can have a great impact on the hospital course of elders.

Screening for CI among hospitalized older adults has been considered to have potential benefit in hospital care of older adults.52 Screening may lead to early detection by uncovering subtle symptoms not yet apparent to families or other caregivers who know the patient well but do not notice small declines or changes in day‐to‐day functioning. Early recognition of CI may lead to early treatment and subsequently may delay progression of cognitive decline and improve health outcomes. Screening may enhance physician prescribing practices and reduce exposure to harmful medications among these vulnerable patients. Finally, delirium is an important prognostic indicator, and screening patients could provide invaluable information toward the overall clinical picture. Despite all of this, the current literature does not provide sufficient information to support the use of routine screening on admission.220, 41, 5254 Most of the published studies were conducted among elders who stayed in the hospital for more than 48 hours, missing data on the crucial first 48 hours of the hospital course.220, 41, 5254 These studies did not evaluate the impact of unrecognized CI on the hospital course and the majority of these studies were not conducted in the urban and lower socioeconomic status populations of elders that are the most vulnerable to bad health outcomes.220, 41, 5254 Finally, few studies evaluated the impact of delirium superimposed on CI on the hospital course and mortality of elders.220, 41, 5254

With these details in mind, we wanted to explore the impact of CI recognition among patients age 65 years and older admitted to the medical services of an urban, public hospital in Indianapolis to determine the prevalence and the impact of recognized and unrecognized CI on the hospital course of these elders. Furthermore, we examined the role of delirium superimposed on these hospitalized elders with CI.

Patients and Methods

The study was approved by the Indiana University Purdue University at Indianapolis Institutional Review Board (IRB).

Results

Discussion

Our study found that in an urban, public hospital, acute or preexisting CI affects more than one‐third of hospitalized elders admitted to general medical services. Unfortunately, our hospital system does not currently recognize the majority of these vulnerable patients. Our study also found that delirium affects more than one‐third of hospitalized elders with CI during their hospital course. Delirium complicates hospital care by prolonging length of stay and decreasing the probability of surviving and getting discharged home. It leads to high use of Foley catheterization, physical restraints, and tethers.

The high prevalence of CI with and without delirium in our cohort is within the rates reported previously in the literature. It is estimated that the prevalence of CI in hospitalized older adults ranges from 14% to 66%, depending on the method used to measure cognition, the definition of CI, and the type of hospital ward (surgical, medical, and geriatric units).220 One particular study that used a similar cognitive assessment method reported higher prevalence rates for both CI and delirium.11 The study randomly evaluated a sample of 201 patients age 65 and over who were hospitalized for a medical illness and found that 56% of the cohort suffered from CI and among those with CI, 47% had delirium.11 The difference between this finding and our study is most likely due to our sampling technique; more than 70% of our cognitive screening occurred in the first 48 hours of hospital admission whereas the Australian study, in similar enrollment criteria to all of the published studies in this area, excluded patients who were discharged within 48 hours of admission. We believe, however, that by including the first 48 hours of admission in our design, our study provides a more generalizable reflection of the actual acute care experience.

The impact of delirium on the course of hospital care found in our study supports some of the findings from previous studies conducted in the past 2 decades.5, 6, 11 Despite 2 decades of clinical research, delirium continues to increase mortality, hospital stays, and posthospital institutionalization.

We were surprised to find that patients suffering from delirium continue to receive at least 1 definite anticholinergic medication. Such medications are considered inappropriate among patients with any form of cognitive impairment.36, 62 Although the impact of anticholinergic medications on hospitalized outcomes is less well‐described, their use has been suspected to negatively impact long‐term outcomes of cognitive impairment.61, 63 Our study found no difference in the use of anticholinergic medications between those with CI who experienced delirium and those who did not; however, the total burden of anticholinergic medication was not assessed in a quantitative manner. It is still unknown if certain anticholinergic medications or a cumulative effect of anticholinergic medications may impact cognitive or health‐related outcomes in a vulnerable older population with CI.

Although our study reported for the first time in a systematic way the rate of undocumented CI among hospitalized elders found to have CI on admission, we found no impact of such underrecognition on the length of hospital stay, mortality, discharge location, and delirium occurrence. Although the use of anticholinergic medications is not recommended for patients with any form of CI, our results indicate that a significant number of patients with cognitive impairment continue to receive inappropriate medications. CI recognition in the elderly was not shown to have a statistically significant affect on length of stay, cost, or mortality.

Our study has some limitations. First of all, we did not determine the underlying types of CI such as Alzheimer disease, vascular dementia, mild cognitive impairment, or reversible etiology other than delirium. Such a categorization requires posthospital assessment, which was not included in our study design. Second, our delirium incidence rate and delirium impact on hospital outcomes might be very conservative and may underestimate its true prevalence and correlation due to our data collection methods. Despite the fluctuating nature of delirium, our study was not designed to assess the presence of delirium every shift and tried to assess cognitive function on a daily basis throughout the patient's hospitalization. Therefore, the severity and duration of delirium could not be accurately assessed. Our reported rates of use of Foley catheterization, physical restraints, and tethers are also very conservative and we could not determine the appropriateness of these procedures. Our study was conducted in 1 public hospital in an urban city with a higher percentage of African Americans. Thus, our sample is not a true representative sample. However, studies with significant representation of minority groups are not common in the research literature, especially in CI research; we hope to fulfill some of the gaps in the literature regarding the most vulnerable older American population. Finally, we were limited in our use of ICD‐9 coding to determine if patients had previously been recognized by other providers as having CI. ICD‐9 coding, while useful, is not perfect in identifying all if a patient's medical problems. Use of coding to determine whether a patient had been recognized as impaired also does not allow us to determine when the diagnosis was made.

In conclusion, our study evaluated cognitive impairment in hospitalized elders and found that in our cohort of 997 patients, 43% were cognitively impaired on admission. Of those with CI, 61% were not documented or recognized as impaired. We found no statistically significant difference between those with documented CI and those with undocumented CI in terms of length of stay, mortality, home discharge, readmission rates, incidence of delirium, or potential to receive anticholinergics or restraints. Among those with CI, 38% had delirium. Those with delirium experienced increased length of stay, decreased discharge to home, and increased use of Foley catheters and restraints.