Scott A. Flanders, MD

Peripherally inserted central catheters (PICCs) are integral to the care of hospitalized patients in the United States.¹ Consequently, utilization of these devices in acutely ill patients has steadily increased in the past decade.² Although originally designed to support the delivery of total parenteral nutrition, PICCs have found broader applications in the hospital setting given the ease and safety of placement, the advances in technology that facilitate insertion, and the growing availability of specially trained vascular nurses that place these devices at the bedside.³ Furthermore, because they are placed in deeper veins of the arm, PICCs are more durable than peripheral catheters and can support venous access for extended durations.^4-6

However, the growing use of PICCs has led to the realization that these devices are not without attendant risks. For example, PICCs are associated with venous thromboembolism (VTE) and central-line associated blood stream infection (CLABSI).^7,8 Additionally, complications such as catheter occlusion and tip migration commonly occur and may interrupt care or necessitate device removal.^9-11 Hence, thoughtful weighing of the risks against the benefits of PICC use prior to placement is necessary. To facilitate such decision-making, we developed the Michigan Appropriateness Guide for Intravenous (IV) Catheters (MAGIC) criteria,¹² which is an evidence-based tool that defines when the use of a PICC is appropriate in hospitalized adults.

The use of PICCs for infusion of peripherally compatible therapies for 5 or fewer days is rated as inappropriate by MAGIC.¹² This strategy is also endorsed by the Centers for Disease Control and Prevention’s (CDC) guidelines for the prevention of catheter-related infections.¹³ Despite these recommendations, short-term PICC use remains common. For example, a study conducted at a tertiary pediatric care center reported a trend toward shorter PICC dwell times and increasing rates of early removal.² However, factors that prompt such short-term PICC use are poorly understood. Without understanding drivers and outcomes of short-term PICC use, interventions to prevent such practice are unlikely to succeed.

Therefore, by using data from a multicenter cohort study, we examined patterns of short-term PICC use and sought to identify which patient, provider, and device factors were associated with such use. We hypothesized that short-term placement would be associated with difficult venous access and would also be associated with the risk of major and minor complications.

Study Setting and Design

We used data from the Michigan Hospital Medicine Safety (HMS) Consortium to examine patterns and predictors of short-term PICC use.¹⁴ As a multi-institutional clinical quality initiative sponsored by Blue Cross Blue Shield of Michigan and Blue Care Network, HMS aims to improve the quality of care by preventing adverse events in hospitalized medical patients.^4,15-17 In January of 2014, dedicated, trained abstractors started collecting data on PICC placements at participating HMS hospitals by using a standard protocol and template for data collection. Patients who received PICCs while admitted to either a general medicine unit or an intensive care unit (ICU) during clinical care were eligible for inclusion. Patients were excluded if they were (a) under the age of 18 years, (b) pregnant, (c) admitted to a nonmedical service (eg, surgery), or (d) admitted under observation status.

Every 14 days, each hospital collected data on the first 17 eligible patients that received a PICC, with at least 7 of these placements occurring in an ICU setting. All patients were prospectively followed until the PICC was removed, death, or until 70 days after insertion, whichever occurred first. For patients who had their PICC removed prior to hospital discharge, follow-up occurred via a review of medical records. For those discharged with a PICC in place, both medical record review and telephone follow-up were performed. To ensure data quality, annual random audits at each participating hospital were performed by the coordinating center at the University of Michigan.

For this analysis, we included all available data as of June 30, 2016. However, HMS hospitals continue to collect data on PICC use and outcomes as part of an ongoing clinical quality initiative to reduce the incidence of PICC-related complications.

Patient, Provider, and Device Data

Patient characteristics, including demographics, detailed medical history, comorbidities, physical findings, laboratory results, and medications were abstracted directly from medical records. To estimate the comorbidity burden, the Charlson-Deyo comorbidity score was calculated for each patient by using data available in the medical record at the time of PICC placement.¹⁸ Data, such as the documented indication for PICC insertion and the reason for removal, were obtained directly from medical records. Provider characteristics, including the specialty of the attending physician at the time of insertion and the type of operator who inserted the PICC, were also collected. Institutional characteristics, such as total number of beds, teaching versus nonteaching, and urban versus rural, were obtained from hospital publicly reported data and semiannual surveys of HMS sites.^19,20 Data on device characteristics, such as catheter gauge, coating, insertion attempts, tip location, and number of lumens, were abstracted from PICC insertion notes.

Outcomes of Interest

The outcome of interest was short-term PICC use, defined as PICCs removed within 5 days of insertion. Patients who expired with a PICC in situ were excluded. Secondary outcomes of interest included PICC-related complications, categorized as major (eg, symptomatic VTE and CLABSI) or minor (eg, catheter occlusion, superficial thrombosis, mechanical complications [kinking, coiling], exit site infection, and tip migration). Symptomatic VTE was defined as clinically diagnosed deep venous thrombosis (DVT) and/or pulmonary embolism (PE) not present at the time of PICC placement and confirmed via imaging (ultrasound or venogram for DVT; computed tomography scan, ventilation perfusion scan, or pulmonary angiogram for PE). CLABSI was defined in accordance with the CDC’s National Healthcare Safety Network criteria or according to Infectious Diseases Society of America recommendations.^21,22 All minor PICC complications were defined in accordance with prior published definitions.⁴

Statistical Analysis

Cases of short-term PICC use were identified and compared with patients with a PICC dwell time of 6 or more days by patient, provider, and device characteristics. The initial analyses for the associations of putative factors with short-term PICC use were performed using χ2 or Wilcoxon tests for categorical and continuous variables, respectively. Univariable mixed effect logistic regression models (with a random hospital-specific intercept) were then used to control for hospital-level clustering. Next, a mixed effects multivariable logistic regression model was used to identify factors associated with short-term PICC use. Variables with P ≤ .25 were considered as candidate predictors for the final multivariable model, which was chosen through a stepwise variable selection algorithm performed on 1000 bootstrapped data sets.²³ Variables in the final model were retained based on their frequency of selection in the bootstrapped samples, significance level, and contribution to the overall model likelihood. Results were expressed as odds ratios (OR) with corresponding 95% confidence intervals (CI). SAS for Windows (version 9.3, SAS Institute Inc., Cary, NC) was used for analyses.

Ethical and Regulatory Oversight

The study was classified as “not regulated” by the Institutional Review Board at the University of Michigan (HUM00078730).

Overall Characteristics of the Study Cohort

Characteristics of Short-Term Peripherally Inserted Central Catheter Use

Of the 15,397 PICCs included, we identified 3902 PICCs (25.3%) with a dwell time of ≤5 days (median = 3 days; IQR, 2-4 days). When compared to PICCs that were in place for longer durations, no significant differences in age or comorbidity scores were observed. Importantly, despite recommendations to avoid PICCs in patients with moderate to severe chronic kidney disease (glomerular filtration rate [GFR] ≤ 59 ml/min), 1292 (33.1%) short-term PICCs occurred in patients that met such criteria.

Among short-term PICCs, 3618 (92.7%) were power-capable devices, 2785 (71.4%) were 5-French, and 2813 (72.1%) were multilumen. Indications for the use of short-term PICCs differed from longer term devices in important ways (P <  .001). For example, the most common documented indication for short-term PICC use was difficult venous access (28.2%), while for long-term PICCs, it was antibiotic administration (39.8%). General internists and hospitalists were the most common attending physicians for patients with short-term and long-term PICCs (65.1% and 65.5%, respectively [P = .73]). Also, the proportion of critical care physicians responsible for patients with short versus long-term PICC use was similar (14.0% vs 15.0%, respectively [P = .123]). Of the short-term PICCs, 2583 (66.2%) were inserted by vascular access nurses, 795 (20.4%) by interventional radiologists, and 439 (11.3%) by advance practice professionals. Almost all of the PICCs placed ≤5 days (95.5%) were removed during hospitalization.

Complications Associated with Short-Term Peripherally Inserted Central Catheter Use

This large, multisite prospective cohort study is the first to examine patterns and predictors of short-term PICC use in hospitalized adults. By examining clinically granular data derived from the medical records of patients across 52 hospitals, we found that short-term use was common, representing 25% of all PICCs placed. Almost all such PICCs were removed prior to discharge, suggesting that they were placed primarily to meet acute needs during hospitalization. Multivariable models indicated that patients with difficult venous access, multilumen devices, and teaching hospital settings were associated with short-term use. Given that (a) short term PICC use is not recommended by published evidence-based guidelines,^12,13 (b) both major and minor complications were not uncommon despite brief exposure, and (c) specific factors might be targeted to avoid such use, strategies to improve PICC decision-making in the hospital appear increasingly necessary.

In our study, difficult venous access was the most common documented indication for short-term PICC placement. For patients in whom an anticipated catheter dwell time of 5 days or less is expected, MAGIC recommends the consideration of midline or peripheral IV catheters placed under ultrasound guidance.¹² A midline is a type of peripheral IV catheter that is about 7.5 cm to 25 cm in length and is typically inserted in the larger diameter veins of the upper extremity, such as the cephalic or basilic veins, with the tip terminating distal to the subclavian vein.^7,12 While there is a paucity of information that directly compares PICCs to midlines, some data suggest a lower risk of bloodstream infection and thrombosis associated with the latter.^24-26 For example, at one quaternary teaching hospital, house staff who are trained to insert midline catheters under ultrasound guidance in critically ill patients with difficult venous access reported no CLABSI and DVT events.²⁶

Interestingly, multilumen catheters were used twice as often as single lumen catheters in patients with short-term PICCs. In these instances, the use of additional lumens is questionable, as infusion of multiple incompatible fluids was not commonly listed as an indication prompting PICC use. Because multilumen PICCs are associated with higher risks of both VTE and CLABSI compared to single lumen devices, such use represents an important safety concern.^27-29 Institutional efforts that not only limit the use of multilumen PICCs but also fundamentally define when use of a PICC is appropriate may substantially improve outcomes related to vascular access.^28,30,31We observed that short-term PICCs were more common in teaching compared to nonteaching hospitals. While the design of the present study precludes understanding the reasons for such a difference, some plausible theories include the presence of physician trainees who may not appreciate the risks of PICC use, diminishing peripheral IV access securement skills, and the lack of alternatives to PICC use. Educating trainees who most often order PICCs in teaching settings as to when they should or should not consider this device may represent an important quality improvement opportunity.³² Similarly, auditing and assessing the clinical skills of those entrusted to place peripheral IVs might prove helpful.^33,34 Finally, the introduction of a midline program, or similar programs that expand the scope of vascular access teams to place alternative devices, should be explored as a means to improve PICC use and patient safety.

Our study also found that a third of patients who received PICCs for 5 or fewer days had moderate to severe chronic kidney disease. In these patients who may require renal replacement therapy, prior PICC placement is among the strongest predictors of arteriovenous fistula failure.^35,36 Therefore, even though national guidelines discourage the use of PICCs in these patients and recommend alternative routes of venous access,^12,37,38 such practice is clearly not happening. System-based interventions that begin by identifying patients who require vein preservation (eg, those with a GFR < 45 ml/min) and are therefore not appropriate for a PICC would be a welcomed first step in improving care for such patients.^37,38Our study has limitations. First, the observational nature of the study limits the ability to assess for causality or to account for the effects of unmeasured confounders. Second, while the use of medical records to collect granular data is valuable, differences in documentation patterns within and across hospitals, including patterns of missing data, may produce a misclassification of covariates or outcomes. Third, while we found that higher rates of short-term PICC use were associated with teaching hospitals and patients with difficult venous access, we were unable to determine the precise reasons for this practice trend. Qualitative or mixed-methods approaches to understand provider decision-making in these settings would be welcomed.

Our study also has several strengths. First, to our knowledge, this is the first study to systematically describe and evaluate patterns and predictors of short-term PICC use. The finding that PICCs placed for difficult venous access is a dominant category of short-term placement confirms clinical suspicions regarding inappropriate use and strengthens the need for pathways or protocols to manage such patients. Second, the inclusion of medical patients in diverse institutions offers not only real-world insights related to PICC use, but also offers findings that should be generalizable to other hospitals and health systems. Third, the use of a robust data collection strategy that emphasized standardized data collection, dedicated trained abstractors, and random audits to ensure data quality strengthen the findings of this work. Finally, our findings highlight an urgent need to develop policies related to PICC use, including limiting the use of multiple lumens and avoidance in patients with moderate to severe kidney disease.

In conclusion, short-term use of PICCs is prevalent and associated with key patient, provider, and device factors. Such use is also associated with complications, such as catheter occlusion, tip migration, VTE, and CLABSI. Limiting the use of multiple-lumen PICCs, enhancing education for when a PICC should be used, and defining strategies for patients with difficult access may help reduce inappropriate PICC use and improve patient safety. Future studies to examine implementation of such interventions would be welcomed.

Disclosure: Drs. Paje, Conlon, Swaminathan, and Boldenow disclose no conflicts of interest. Dr. Chopra has received honoraria for talks at hospitals as a visiting professor. Dr. Flanders discloses consultancies for the Institute for Healthcare Improvement and the Society of Hospital Medicine, royalties from Wiley Publishing, honoraria for various talks at hospitals as a visiting professor, grants from the CDC Foundation, Agency for Healthcare Research and Quality, Blue Cross Blue Shield of Michigan (BCBSM), and Michigan Hospital Association, and expert witness testimony. Dr. Bernstein discloses consultancies for Blue Care Network and grants from BCBSM, Department of Veterans Affairs, and National Institutes of Health. Dr. Kaatz discloses no relevant conflicts of interest. BCBSM and Blue Care Network provided support for the Michigan HMS Consortium as part of the BCBSM Value Partnerships program. Although BCBSM and HMS work collaboratively, the opinions, beliefs, and viewpoints expressed by the author do not necessarily reflect the opinions, beliefs, and viewpoints of BCBSM or any of its employees. Dr. Chopra is supported by a career development award from the Agency for Healthcare Research and Quality (1-K08-HS022835-01). BCBSM and Blue Care Network supported data collection at each participating site and funded the data coordinating center but had no role in study concept, interpretation of findings, or in the preparation, final approval, or decision to submit the manuscript.

Peripherally inserted central catheters (PICCs) are integral to the care of hospitalized patients in the United States.¹ Consequently, utilization of these devices in acutely ill patients has steadily increased in the past decade.² Although originally designed to support the delivery of total parenteral nutrition, PICCs have found broader applications in the hospital setting given the ease and safety of placement, the advances in technology that facilitate insertion, and the growing availability of specially trained vascular nurses that place these devices at the bedside.³ Furthermore, because they are placed in deeper veins of the arm, PICCs are more durable than peripheral catheters and can support venous access for extended durations.^4-6

However, the growing use of PICCs has led to the realization that these devices are not without attendant risks. For example, PICCs are associated with venous thromboembolism (VTE) and central-line associated blood stream infection (CLABSI).^7,8 Additionally, complications such as catheter occlusion and tip migration commonly occur and may interrupt care or necessitate device removal.^9-11 Hence, thoughtful weighing of the risks against the benefits of PICC use prior to placement is necessary. To facilitate such decision-making, we developed the Michigan Appropriateness Guide for Intravenous (IV) Catheters (MAGIC) criteria,¹² which is an evidence-based tool that defines when the use of a PICC is appropriate in hospitalized adults.

The use of PICCs for infusion of peripherally compatible therapies for 5 or fewer days is rated as inappropriate by MAGIC.¹² This strategy is also endorsed by the Centers for Disease Control and Prevention’s (CDC) guidelines for the prevention of catheter-related infections.¹³ Despite these recommendations, short-term PICC use remains common. For example, a study conducted at a tertiary pediatric care center reported a trend toward shorter PICC dwell times and increasing rates of early removal.² However, factors that prompt such short-term PICC use are poorly understood. Without understanding drivers and outcomes of short-term PICC use, interventions to prevent such practice are unlikely to succeed.

Therefore, by using data from a multicenter cohort study, we examined patterns of short-term PICC use and sought to identify which patient, provider, and device factors were associated with such use. We hypothesized that short-term placement would be associated with difficult venous access and would also be associated with the risk of major and minor complications.

Study Setting and Design

We used data from the Michigan Hospital Medicine Safety (HMS) Consortium to examine patterns and predictors of short-term PICC use.¹⁴ As a multi-institutional clinical quality initiative sponsored by Blue Cross Blue Shield of Michigan and Blue Care Network, HMS aims to improve the quality of care by preventing adverse events in hospitalized medical patients.^4,15-17 In January of 2014, dedicated, trained abstractors started collecting data on PICC placements at participating HMS hospitals by using a standard protocol and template for data collection. Patients who received PICCs while admitted to either a general medicine unit or an intensive care unit (ICU) during clinical care were eligible for inclusion. Patients were excluded if they were (a) under the age of 18 years, (b) pregnant, (c) admitted to a nonmedical service (eg, surgery), or (d) admitted under observation status.

Every 14 days, each hospital collected data on the first 17 eligible patients that received a PICC, with at least 7 of these placements occurring in an ICU setting. All patients were prospectively followed until the PICC was removed, death, or until 70 days after insertion, whichever occurred first. For patients who had their PICC removed prior to hospital discharge, follow-up occurred via a review of medical records. For those discharged with a PICC in place, both medical record review and telephone follow-up were performed. To ensure data quality, annual random audits at each participating hospital were performed by the coordinating center at the University of Michigan.

For this analysis, we included all available data as of June 30, 2016. However, HMS hospitals continue to collect data on PICC use and outcomes as part of an ongoing clinical quality initiative to reduce the incidence of PICC-related complications.

Patient, Provider, and Device Data

Patient characteristics, including demographics, detailed medical history, comorbidities, physical findings, laboratory results, and medications were abstracted directly from medical records. To estimate the comorbidity burden, the Charlson-Deyo comorbidity score was calculated for each patient by using data available in the medical record at the time of PICC placement.¹⁸ Data, such as the documented indication for PICC insertion and the reason for removal, were obtained directly from medical records. Provider characteristics, including the specialty of the attending physician at the time of insertion and the type of operator who inserted the PICC, were also collected. Institutional characteristics, such as total number of beds, teaching versus nonteaching, and urban versus rural, were obtained from hospital publicly reported data and semiannual surveys of HMS sites.^19,20 Data on device characteristics, such as catheter gauge, coating, insertion attempts, tip location, and number of lumens, were abstracted from PICC insertion notes.

Outcomes of Interest

The outcome of interest was short-term PICC use, defined as PICCs removed within 5 days of insertion. Patients who expired with a PICC in situ were excluded. Secondary outcomes of interest included PICC-related complications, categorized as major (eg, symptomatic VTE and CLABSI) or minor (eg, catheter occlusion, superficial thrombosis, mechanical complications [kinking, coiling], exit site infection, and tip migration). Symptomatic VTE was defined as clinically diagnosed deep venous thrombosis (DVT) and/or pulmonary embolism (PE) not present at the time of PICC placement and confirmed via imaging (ultrasound or venogram for DVT; computed tomography scan, ventilation perfusion scan, or pulmonary angiogram for PE). CLABSI was defined in accordance with the CDC’s National Healthcare Safety Network criteria or according to Infectious Diseases Society of America recommendations.^21,22 All minor PICC complications were defined in accordance with prior published definitions.⁴

Statistical Analysis

Cases of short-term PICC use were identified and compared with patients with a PICC dwell time of 6 or more days by patient, provider, and device characteristics. The initial analyses for the associations of putative factors with short-term PICC use were performed using χ2 or Wilcoxon tests for categorical and continuous variables, respectively. Univariable mixed effect logistic regression models (with a random hospital-specific intercept) were then used to control for hospital-level clustering. Next, a mixed effects multivariable logistic regression model was used to identify factors associated with short-term PICC use. Variables with P ≤ .25 were considered as candidate predictors for the final multivariable model, which was chosen through a stepwise variable selection algorithm performed on 1000 bootstrapped data sets.²³ Variables in the final model were retained based on their frequency of selection in the bootstrapped samples, significance level, and contribution to the overall model likelihood. Results were expressed as odds ratios (OR) with corresponding 95% confidence intervals (CI). SAS for Windows (version 9.3, SAS Institute Inc., Cary, NC) was used for analyses.

Ethical and Regulatory Oversight

The study was classified as “not regulated” by the Institutional Review Board at the University of Michigan (HUM00078730).

Overall Characteristics of the Study Cohort

Characteristics of Short-Term Peripherally Inserted Central Catheter Use

Of the 15,397 PICCs included, we identified 3902 PICCs (25.3%) with a dwell time of ≤5 days (median = 3 days; IQR, 2-4 days). When compared to PICCs that were in place for longer durations, no significant differences in age or comorbidity scores were observed. Importantly, despite recommendations to avoid PICCs in patients with moderate to severe chronic kidney disease (glomerular filtration rate [GFR] ≤ 59 ml/min), 1292 (33.1%) short-term PICCs occurred in patients that met such criteria.

Among short-term PICCs, 3618 (92.7%) were power-capable devices, 2785 (71.4%) were 5-French, and 2813 (72.1%) were multilumen. Indications for the use of short-term PICCs differed from longer term devices in important ways (P <  .001). For example, the most common documented indication for short-term PICC use was difficult venous access (28.2%), while for long-term PICCs, it was antibiotic administration (39.8%). General internists and hospitalists were the most common attending physicians for patients with short-term and long-term PICCs (65.1% and 65.5%, respectively [P = .73]). Also, the proportion of critical care physicians responsible for patients with short versus long-term PICC use was similar (14.0% vs 15.0%, respectively [P = .123]). Of the short-term PICCs, 2583 (66.2%) were inserted by vascular access nurses, 795 (20.4%) by interventional radiologists, and 439 (11.3%) by advance practice professionals. Almost all of the PICCs placed ≤5 days (95.5%) were removed during hospitalization.

Complications Associated with Short-Term Peripherally Inserted Central Catheter Use

This large, multisite prospective cohort study is the first to examine patterns and predictors of short-term PICC use in hospitalized adults. By examining clinically granular data derived from the medical records of patients across 52 hospitals, we found that short-term use was common, representing 25% of all PICCs placed. Almost all such PICCs were removed prior to discharge, suggesting that they were placed primarily to meet acute needs during hospitalization. Multivariable models indicated that patients with difficult venous access, multilumen devices, and teaching hospital settings were associated with short-term use. Given that (a) short term PICC use is not recommended by published evidence-based guidelines,^12,13 (b) both major and minor complications were not uncommon despite brief exposure, and (c) specific factors might be targeted to avoid such use, strategies to improve PICC decision-making in the hospital appear increasingly necessary.

In our study, difficult venous access was the most common documented indication for short-term PICC placement. For patients in whom an anticipated catheter dwell time of 5 days or less is expected, MAGIC recommends the consideration of midline or peripheral IV catheters placed under ultrasound guidance.¹² A midline is a type of peripheral IV catheter that is about 7.5 cm to 25 cm in length and is typically inserted in the larger diameter veins of the upper extremity, such as the cephalic or basilic veins, with the tip terminating distal to the subclavian vein.^7,12 While there is a paucity of information that directly compares PICCs to midlines, some data suggest a lower risk of bloodstream infection and thrombosis associated with the latter.^24-26 For example, at one quaternary teaching hospital, house staff who are trained to insert midline catheters under ultrasound guidance in critically ill patients with difficult venous access reported no CLABSI and DVT events.²⁶

Interestingly, multilumen catheters were used twice as often as single lumen catheters in patients with short-term PICCs. In these instances, the use of additional lumens is questionable, as infusion of multiple incompatible fluids was not commonly listed as an indication prompting PICC use. Because multilumen PICCs are associated with higher risks of both VTE and CLABSI compared to single lumen devices, such use represents an important safety concern.^27-29 Institutional efforts that not only limit the use of multilumen PICCs but also fundamentally define when use of a PICC is appropriate may substantially improve outcomes related to vascular access.^28,30,31We observed that short-term PICCs were more common in teaching compared to nonteaching hospitals. While the design of the present study precludes understanding the reasons for such a difference, some plausible theories include the presence of physician trainees who may not appreciate the risks of PICC use, diminishing peripheral IV access securement skills, and the lack of alternatives to PICC use. Educating trainees who most often order PICCs in teaching settings as to when they should or should not consider this device may represent an important quality improvement opportunity.³² Similarly, auditing and assessing the clinical skills of those entrusted to place peripheral IVs might prove helpful.^33,34 Finally, the introduction of a midline program, or similar programs that expand the scope of vascular access teams to place alternative devices, should be explored as a means to improve PICC use and patient safety.

Our study also found that a third of patients who received PICCs for 5 or fewer days had moderate to severe chronic kidney disease. In these patients who may require renal replacement therapy, prior PICC placement is among the strongest predictors of arteriovenous fistula failure.^35,36 Therefore, even though national guidelines discourage the use of PICCs in these patients and recommend alternative routes of venous access,^12,37,38 such practice is clearly not happening. System-based interventions that begin by identifying patients who require vein preservation (eg, those with a GFR < 45 ml/min) and are therefore not appropriate for a PICC would be a welcomed first step in improving care for such patients.^37,38Our study has limitations. First, the observational nature of the study limits the ability to assess for causality or to account for the effects of unmeasured confounders. Second, while the use of medical records to collect granular data is valuable, differences in documentation patterns within and across hospitals, including patterns of missing data, may produce a misclassification of covariates or outcomes. Third, while we found that higher rates of short-term PICC use were associated with teaching hospitals and patients with difficult venous access, we were unable to determine the precise reasons for this practice trend. Qualitative or mixed-methods approaches to understand provider decision-making in these settings would be welcomed.

Our study also has several strengths. First, to our knowledge, this is the first study to systematically describe and evaluate patterns and predictors of short-term PICC use. The finding that PICCs placed for difficult venous access is a dominant category of short-term placement confirms clinical suspicions regarding inappropriate use and strengthens the need for pathways or protocols to manage such patients. Second, the inclusion of medical patients in diverse institutions offers not only real-world insights related to PICC use, but also offers findings that should be generalizable to other hospitals and health systems. Third, the use of a robust data collection strategy that emphasized standardized data collection, dedicated trained abstractors, and random audits to ensure data quality strengthen the findings of this work. Finally, our findings highlight an urgent need to develop policies related to PICC use, including limiting the use of multiple lumens and avoidance in patients with moderate to severe kidney disease.

In conclusion, short-term use of PICCs is prevalent and associated with key patient, provider, and device factors. Such use is also associated with complications, such as catheter occlusion, tip migration, VTE, and CLABSI. Limiting the use of multiple-lumen PICCs, enhancing education for when a PICC should be used, and defining strategies for patients with difficult access may help reduce inappropriate PICC use and improve patient safety. Future studies to examine implementation of such interventions would be welcomed.

Disclosure: Drs. Paje, Conlon, Swaminathan, and Boldenow disclose no conflicts of interest. Dr. Chopra has received honoraria for talks at hospitals as a visiting professor. Dr. Flanders discloses consultancies for the Institute for Healthcare Improvement and the Society of Hospital Medicine, royalties from Wiley Publishing, honoraria for various talks at hospitals as a visiting professor, grants from the CDC Foundation, Agency for Healthcare Research and Quality, Blue Cross Blue Shield of Michigan (BCBSM), and Michigan Hospital Association, and expert witness testimony. Dr. Bernstein discloses consultancies for Blue Care Network and grants from BCBSM, Department of Veterans Affairs, and National Institutes of Health. Dr. Kaatz discloses no relevant conflicts of interest. BCBSM and Blue Care Network provided support for the Michigan HMS Consortium as part of the BCBSM Value Partnerships program. Although BCBSM and HMS work collaboratively, the opinions, beliefs, and viewpoints expressed by the author do not necessarily reflect the opinions, beliefs, and viewpoints of BCBSM or any of its employees. Dr. Chopra is supported by a career development award from the Agency for Healthcare Research and Quality (1-K08-HS022835-01). BCBSM and Blue Care Network supported data collection at each participating site and funded the data coordinating center but had no role in study concept, interpretation of findings, or in the preparation, final approval, or decision to submit the manuscript.

Peripherally inserted central catheters (PICCs) are integral to the care of hospitalized patients in the United States.¹ Consequently, utilization of these devices in acutely ill patients has steadily increased in the past decade.² Although originally designed to support the delivery of total parenteral nutrition, PICCs have found broader applications in the hospital setting given the ease and safety of placement, the advances in technology that facilitate insertion, and the growing availability of specially trained vascular nurses that place these devices at the bedside.³ Furthermore, because they are placed in deeper veins of the arm, PICCs are more durable than peripheral catheters and can support venous access for extended durations.^4-6

However, the growing use of PICCs has led to the realization that these devices are not without attendant risks. For example, PICCs are associated with venous thromboembolism (VTE) and central-line associated blood stream infection (CLABSI).^7,8 Additionally, complications such as catheter occlusion and tip migration commonly occur and may interrupt care or necessitate device removal.^9-11 Hence, thoughtful weighing of the risks against the benefits of PICC use prior to placement is necessary. To facilitate such decision-making, we developed the Michigan Appropriateness Guide for Intravenous (IV) Catheters (MAGIC) criteria,¹² which is an evidence-based tool that defines when the use of a PICC is appropriate in hospitalized adults.

The use of PICCs for infusion of peripherally compatible therapies for 5 or fewer days is rated as inappropriate by MAGIC.¹² This strategy is also endorsed by the Centers for Disease Control and Prevention’s (CDC) guidelines for the prevention of catheter-related infections.¹³ Despite these recommendations, short-term PICC use remains common. For example, a study conducted at a tertiary pediatric care center reported a trend toward shorter PICC dwell times and increasing rates of early removal.² However, factors that prompt such short-term PICC use are poorly understood. Without understanding drivers and outcomes of short-term PICC use, interventions to prevent such practice are unlikely to succeed.

Therefore, by using data from a multicenter cohort study, we examined patterns of short-term PICC use and sought to identify which patient, provider, and device factors were associated with such use. We hypothesized that short-term placement would be associated with difficult venous access and would also be associated with the risk of major and minor complications.

Study Setting and Design

We used data from the Michigan Hospital Medicine Safety (HMS) Consortium to examine patterns and predictors of short-term PICC use.¹⁴ As a multi-institutional clinical quality initiative sponsored by Blue Cross Blue Shield of Michigan and Blue Care Network, HMS aims to improve the quality of care by preventing adverse events in hospitalized medical patients.^4,15-17 In January of 2014, dedicated, trained abstractors started collecting data on PICC placements at participating HMS hospitals by using a standard protocol and template for data collection. Patients who received PICCs while admitted to either a general medicine unit or an intensive care unit (ICU) during clinical care were eligible for inclusion. Patients were excluded if they were (a) under the age of 18 years, (b) pregnant, (c) admitted to a nonmedical service (eg, surgery), or (d) admitted under observation status.

Every 14 days, each hospital collected data on the first 17 eligible patients that received a PICC, with at least 7 of these placements occurring in an ICU setting. All patients were prospectively followed until the PICC was removed, death, or until 70 days after insertion, whichever occurred first. For patients who had their PICC removed prior to hospital discharge, follow-up occurred via a review of medical records. For those discharged with a PICC in place, both medical record review and telephone follow-up were performed. To ensure data quality, annual random audits at each participating hospital were performed by the coordinating center at the University of Michigan.

For this analysis, we included all available data as of June 30, 2016. However, HMS hospitals continue to collect data on PICC use and outcomes as part of an ongoing clinical quality initiative to reduce the incidence of PICC-related complications.

Patient, Provider, and Device Data

Patient characteristics, including demographics, detailed medical history, comorbidities, physical findings, laboratory results, and medications were abstracted directly from medical records. To estimate the comorbidity burden, the Charlson-Deyo comorbidity score was calculated for each patient by using data available in the medical record at the time of PICC placement.¹⁸ Data, such as the documented indication for PICC insertion and the reason for removal, were obtained directly from medical records. Provider characteristics, including the specialty of the attending physician at the time of insertion and the type of operator who inserted the PICC, were also collected. Institutional characteristics, such as total number of beds, teaching versus nonteaching, and urban versus rural, were obtained from hospital publicly reported data and semiannual surveys of HMS sites.^19,20 Data on device characteristics, such as catheter gauge, coating, insertion attempts, tip location, and number of lumens, were abstracted from PICC insertion notes.

Outcomes of Interest

The outcome of interest was short-term PICC use, defined as PICCs removed within 5 days of insertion. Patients who expired with a PICC in situ were excluded. Secondary outcomes of interest included PICC-related complications, categorized as major (eg, symptomatic VTE and CLABSI) or minor (eg, catheter occlusion, superficial thrombosis, mechanical complications [kinking, coiling], exit site infection, and tip migration). Symptomatic VTE was defined as clinically diagnosed deep venous thrombosis (DVT) and/or pulmonary embolism (PE) not present at the time of PICC placement and confirmed via imaging (ultrasound or venogram for DVT; computed tomography scan, ventilation perfusion scan, or pulmonary angiogram for PE). CLABSI was defined in accordance with the CDC’s National Healthcare Safety Network criteria or according to Infectious Diseases Society of America recommendations.^21,22 All minor PICC complications were defined in accordance with prior published definitions.⁴

Statistical Analysis

Cases of short-term PICC use were identified and compared with patients with a PICC dwell time of 6 or more days by patient, provider, and device characteristics. The initial analyses for the associations of putative factors with short-term PICC use were performed using χ2 or Wilcoxon tests for categorical and continuous variables, respectively. Univariable mixed effect logistic regression models (with a random hospital-specific intercept) were then used to control for hospital-level clustering. Next, a mixed effects multivariable logistic regression model was used to identify factors associated with short-term PICC use. Variables with P ≤ .25 were considered as candidate predictors for the final multivariable model, which was chosen through a stepwise variable selection algorithm performed on 1000 bootstrapped data sets.²³ Variables in the final model were retained based on their frequency of selection in the bootstrapped samples, significance level, and contribution to the overall model likelihood. Results were expressed as odds ratios (OR) with corresponding 95% confidence intervals (CI). SAS for Windows (version 9.3, SAS Institute Inc., Cary, NC) was used for analyses.

Ethical and Regulatory Oversight

The study was classified as “not regulated” by the Institutional Review Board at the University of Michigan (HUM00078730).

Overall Characteristics of the Study Cohort

Characteristics of Short-Term Peripherally Inserted Central Catheter Use

Of the 15,397 PICCs included, we identified 3902 PICCs (25.3%) with a dwell time of ≤5 days (median = 3 days; IQR, 2-4 days). When compared to PICCs that were in place for longer durations, no significant differences in age or comorbidity scores were observed. Importantly, despite recommendations to avoid PICCs in patients with moderate to severe chronic kidney disease (glomerular filtration rate [GFR] ≤ 59 ml/min), 1292 (33.1%) short-term PICCs occurred in patients that met such criteria.

Among short-term PICCs, 3618 (92.7%) were power-capable devices, 2785 (71.4%) were 5-French, and 2813 (72.1%) were multilumen. Indications for the use of short-term PICCs differed from longer term devices in important ways (P <  .001). For example, the most common documented indication for short-term PICC use was difficult venous access (28.2%), while for long-term PICCs, it was antibiotic administration (39.8%). General internists and hospitalists were the most common attending physicians for patients with short-term and long-term PICCs (65.1% and 65.5%, respectively [P = .73]). Also, the proportion of critical care physicians responsible for patients with short versus long-term PICC use was similar (14.0% vs 15.0%, respectively [P = .123]). Of the short-term PICCs, 2583 (66.2%) were inserted by vascular access nurses, 795 (20.4%) by interventional radiologists, and 439 (11.3%) by advance practice professionals. Almost all of the PICCs placed ≤5 days (95.5%) were removed during hospitalization.

Complications Associated with Short-Term Peripherally Inserted Central Catheter Use

This large, multisite prospective cohort study is the first to examine patterns and predictors of short-term PICC use in hospitalized adults. By examining clinically granular data derived from the medical records of patients across 52 hospitals, we found that short-term use was common, representing 25% of all PICCs placed. Almost all such PICCs were removed prior to discharge, suggesting that they were placed primarily to meet acute needs during hospitalization. Multivariable models indicated that patients with difficult venous access, multilumen devices, and teaching hospital settings were associated with short-term use. Given that (a) short term PICC use is not recommended by published evidence-based guidelines,^12,13 (b) both major and minor complications were not uncommon despite brief exposure, and (c) specific factors might be targeted to avoid such use, strategies to improve PICC decision-making in the hospital appear increasingly necessary.

In our study, difficult venous access was the most common documented indication for short-term PICC placement. For patients in whom an anticipated catheter dwell time of 5 days or less is expected, MAGIC recommends the consideration of midline or peripheral IV catheters placed under ultrasound guidance.¹² A midline is a type of peripheral IV catheter that is about 7.5 cm to 25 cm in length and is typically inserted in the larger diameter veins of the upper extremity, such as the cephalic or basilic veins, with the tip terminating distal to the subclavian vein.^7,12 While there is a paucity of information that directly compares PICCs to midlines, some data suggest a lower risk of bloodstream infection and thrombosis associated with the latter.^24-26 For example, at one quaternary teaching hospital, house staff who are trained to insert midline catheters under ultrasound guidance in critically ill patients with difficult venous access reported no CLABSI and DVT events.²⁶

Interestingly, multilumen catheters were used twice as often as single lumen catheters in patients with short-term PICCs. In these instances, the use of additional lumens is questionable, as infusion of multiple incompatible fluids was not commonly listed as an indication prompting PICC use. Because multilumen PICCs are associated with higher risks of both VTE and CLABSI compared to single lumen devices, such use represents an important safety concern.^27-29 Institutional efforts that not only limit the use of multilumen PICCs but also fundamentally define when use of a PICC is appropriate may substantially improve outcomes related to vascular access.^28,30,31We observed that short-term PICCs were more common in teaching compared to nonteaching hospitals. While the design of the present study precludes understanding the reasons for such a difference, some plausible theories include the presence of physician trainees who may not appreciate the risks of PICC use, diminishing peripheral IV access securement skills, and the lack of alternatives to PICC use. Educating trainees who most often order PICCs in teaching settings as to when they should or should not consider this device may represent an important quality improvement opportunity.³² Similarly, auditing and assessing the clinical skills of those entrusted to place peripheral IVs might prove helpful.^33,34 Finally, the introduction of a midline program, or similar programs that expand the scope of vascular access teams to place alternative devices, should be explored as a means to improve PICC use and patient safety.

Our study also found that a third of patients who received PICCs for 5 or fewer days had moderate to severe chronic kidney disease. In these patients who may require renal replacement therapy, prior PICC placement is among the strongest predictors of arteriovenous fistula failure.^35,36 Therefore, even though national guidelines discourage the use of PICCs in these patients and recommend alternative routes of venous access,^12,37,38 such practice is clearly not happening. System-based interventions that begin by identifying patients who require vein preservation (eg, those with a GFR < 45 ml/min) and are therefore not appropriate for a PICC would be a welcomed first step in improving care for such patients.^37,38Our study has limitations. First, the observational nature of the study limits the ability to assess for causality or to account for the effects of unmeasured confounders. Second, while the use of medical records to collect granular data is valuable, differences in documentation patterns within and across hospitals, including patterns of missing data, may produce a misclassification of covariates or outcomes. Third, while we found that higher rates of short-term PICC use were associated with teaching hospitals and patients with difficult venous access, we were unable to determine the precise reasons for this practice trend. Qualitative or mixed-methods approaches to understand provider decision-making in these settings would be welcomed.

Our study also has several strengths. First, to our knowledge, this is the first study to systematically describe and evaluate patterns and predictors of short-term PICC use. The finding that PICCs placed for difficult venous access is a dominant category of short-term placement confirms clinical suspicions regarding inappropriate use and strengthens the need for pathways or protocols to manage such patients. Second, the inclusion of medical patients in diverse institutions offers not only real-world insights related to PICC use, but also offers findings that should be generalizable to other hospitals and health systems. Third, the use of a robust data collection strategy that emphasized standardized data collection, dedicated trained abstractors, and random audits to ensure data quality strengthen the findings of this work. Finally, our findings highlight an urgent need to develop policies related to PICC use, including limiting the use of multiple lumens and avoidance in patients with moderate to severe kidney disease.

In conclusion, short-term use of PICCs is prevalent and associated with key patient, provider, and device factors. Such use is also associated with complications, such as catheter occlusion, tip migration, VTE, and CLABSI. Limiting the use of multiple-lumen PICCs, enhancing education for when a PICC should be used, and defining strategies for patients with difficult access may help reduce inappropriate PICC use and improve patient safety. Future studies to examine implementation of such interventions would be welcomed.

Disclosure: Drs. Paje, Conlon, Swaminathan, and Boldenow disclose no conflicts of interest. Dr. Chopra has received honoraria for talks at hospitals as a visiting professor. Dr. Flanders discloses consultancies for the Institute for Healthcare Improvement and the Society of Hospital Medicine, royalties from Wiley Publishing, honoraria for various talks at hospitals as a visiting professor, grants from the CDC Foundation, Agency for Healthcare Research and Quality, Blue Cross Blue Shield of Michigan (BCBSM), and Michigan Hospital Association, and expert witness testimony. Dr. Bernstein discloses consultancies for Blue Care Network and grants from BCBSM, Department of Veterans Affairs, and National Institutes of Health. Dr. Kaatz discloses no relevant conflicts of interest. BCBSM and Blue Care Network provided support for the Michigan HMS Consortium as part of the BCBSM Value Partnerships program. Although BCBSM and HMS work collaboratively, the opinions, beliefs, and viewpoints expressed by the author do not necessarily reflect the opinions, beliefs, and viewpoints of BCBSM or any of its employees. Dr. Chopra is supported by a career development award from the Agency for Healthcare Research and Quality (1-K08-HS022835-01). BCBSM and Blue Care Network supported data collection at each participating site and funded the data coordinating center but had no role in study concept, interpretation of findings, or in the preparation, final approval, or decision to submit the manuscript.

In the United States, up to 6 million patients are admitted to intensive care units (ICUs) annually at a cost estimated to exceed $80 billion or about 13% of total hospital costs.^1,2 It also appears that as our population ages and illness severity increases, demand for ICU care is increasing.³ Given its importance, the organization and delivery of critical care has been extensively studied. High-intensity physician staffing by an intensivist (all patients managed or comanaged by an intensivist), while inconsistently shown to be associated with improved outcomes, has been endorsed as a high-quality care model by professional societies and the Leapfrog group. Despite its adoption by many hospitals, widespread implementation has been hampered by a national shortage of intensivists that continues to worsen over time. Hospitals, by necessity, look to alternative models to care for critically ill patients, and one such model is the use of hospitalists.

The Society of Hospital Medicine estimates that there are nearly 50,000 hospitalists practicing in the United States, and several studies show they routinely provide care in the nation’s ICUs.⁴ While in some ICUs hospitalists work alongside intensivists, in many, they work without intensivist support, and regardless of the model, they often serve as the primary attending physician. There is good reason to think this model of care would be effective. Most hospitalists are internists, graduating from training programs that tend to emphasize care of acutely ill hospitalized patients. Hospitalists are often present in the hospital 24/7, are comfortable working in multidisciplinary teams, and routinely engage in quality improvement, which are all characteristics common in highly functioning ICUs. Yet, a study in this issue of the Journal of Hospital Medicine raises some concern.

Sweigart and colleagues⁵ surveyed 425 hospitalists to understand the structure and perception of their ICU practices. Consistent with prior studies, 77% provided ICU care with 66% serving as the primary attending. A novel finding is the high level of angst and lack of support hospitalists perceived in caring for these critically ill patients. Among rural hospitalists, 43% reported they were expected to practice beyond their perceived scope of practice, and almost a third reported they never had sufficient intensivist support. Even more concerning is that among hospitalists serving as the primary attending, over two-thirds reported difficulty transferring patients to a higher level of care (Sweigart et al.⁵). While we have concerns over how representative this sample is of hospitalist practice (the survey response rate was only about 10%), it does appear that many hospitalists feel very uncomfortable with the ICU care they are providing and perceive barriers to moving their patients to a potentially safer care setting.

While one might argue more intensivists would solve this problem, calls for more intensivists are shortsighted, as there are compelling reasons to believe that such efforts will do little to address the mismatch between patient need and provider supply. Graduate medical education slots for intensivists cannot be easily and affordably increased, and even if more intensivists could be trained, there are few incentives to encourage them to work where they are needed most. Prioritization of intensivist training also diverts resources from training demands in equally important undersupplied specialties such as primary care.⁶ Finally, simply increasing intensivist supply fails to attend to important issues surrounding the multidisciplinary nature of care in an ICU, which relies heavily on multiple providers communicating and collaborating to provide optimal care. As noted in the study by Sweigart and colleagues,⁵ even in settings where intensivists were available 24 hours per day or made all major decisions, nearly one-third of hospitalists felt they practiced beyond their scope of expertise, suggesting that more intensivists may do little to improve hospitalists’ comfort in caring for patients in the ICU.

In lieu of increasing intensivist numbers, policymakers should consider several strategies that have the potential to improve the quality of care delivered to patients in the ICU without increasing intensivists. Recent data suggest that some ICU patients can be safely managed by physician assistants and nurse practitioners.^7,8 Care models involving such providers may free up overworked intensivists and hospitalists, allowing them to focus their efforts on the sickest patients. ICU telemedicine has also emerged as a promising tool that can bring the expertise of intensivists to hospitals where they are needed. Beyond the additional oversight of routine care practices it provides, telemedicine could allow rapid and real time consultation with intensivists for clinicians at the bedside facing difficult management decisions, potentially saving lives.⁹ The rapid growth of clinically integrated networks, which often include large well-staffed medical centers surrounded by many smaller regional hospitals, might facilitate faster implementation of innovative telemedicine models. Regionalization of care is a third strategy that may improve the quality of care for the critically ill without increasing intensivist supply. Regionalization seeks to selectively transfer the most ill patients to high-volume centers with the greatest expertise in critical care, a practice associated with reduced mortality.¹⁰ Of course, for regionalization to be successful, front-line providers like hospitalists need to be able to orchestrate the transfer to the referral center, a process that, as noted by Sweigart and others, is neither easy nor universally successful.¹¹

A final strategy would be to reduce the demand for intensivists through limiting the number of individuals in an ICU. While policies that explicitly ration ICU beds for individuals who have the greatest ability to benefit are ethically problematic, reductions in ICU beds would force providers to implicitly allocate beds more efficiently. There are a multitude of studies showing that our nation’s ICUs are often filled with patients who derive little benefit from intensive care.^12,13 Further research on ethically sound strategies to avoid ICU admission for patients unlikely to benefit is desperately needed. With fewer patients in an ICU, the busy intensivist could focus on the sickest patients and spend more time communicating with hospitalists about patients they are managing together.

Regardless of the care models that develop, hospitalists will increasingly be called upon to staff ICUs. Hospitalists are necessary, but as the study by Sweigart et al.⁵ suggests, just throwing them into our current ICU models with little support from their critical care colleagues is not sufficient. In the absence of a major influx of new intensivists, hospital medicine and critical care professional societies need to actively collaborate to develop creative training and educational models that provide hospitalists with the necessary skills to care for the critically ill and to lead the multidisciplinary care teams they will work within. More importantly, these professional societies must advocate together for more substantial reform to our current ICU care models. Novel solutions that prioritize the efficient use of existing ICU beds for those individuals with the greatest ability to benefit, but also capitalize on emerging technologies and regional centers of excellence, have great potential to address the mismatch between supply and demand. Given the increasing demand and substantial cost for ICU care, we can’t afford to continue with business as usual.

Disclosure

The authors declared no conflicts of interest.

In the United States, up to 6 million patients are admitted to intensive care units (ICUs) annually at a cost estimated to exceed $80 billion or about 13% of total hospital costs.^1,2 It also appears that as our population ages and illness severity increases, demand for ICU care is increasing.³ Given its importance, the organization and delivery of critical care has been extensively studied. High-intensity physician staffing by an intensivist (all patients managed or comanaged by an intensivist), while inconsistently shown to be associated with improved outcomes, has been endorsed as a high-quality care model by professional societies and the Leapfrog group. Despite its adoption by many hospitals, widespread implementation has been hampered by a national shortage of intensivists that continues to worsen over time. Hospitals, by necessity, look to alternative models to care for critically ill patients, and one such model is the use of hospitalists.

The Society of Hospital Medicine estimates that there are nearly 50,000 hospitalists practicing in the United States, and several studies show they routinely provide care in the nation’s ICUs.⁴ While in some ICUs hospitalists work alongside intensivists, in many, they work without intensivist support, and regardless of the model, they often serve as the primary attending physician. There is good reason to think this model of care would be effective. Most hospitalists are internists, graduating from training programs that tend to emphasize care of acutely ill hospitalized patients. Hospitalists are often present in the hospital 24/7, are comfortable working in multidisciplinary teams, and routinely engage in quality improvement, which are all characteristics common in highly functioning ICUs. Yet, a study in this issue of the Journal of Hospital Medicine raises some concern.

Sweigart and colleagues⁵ surveyed 425 hospitalists to understand the structure and perception of their ICU practices. Consistent with prior studies, 77% provided ICU care with 66% serving as the primary attending. A novel finding is the high level of angst and lack of support hospitalists perceived in caring for these critically ill patients. Among rural hospitalists, 43% reported they were expected to practice beyond their perceived scope of practice, and almost a third reported they never had sufficient intensivist support. Even more concerning is that among hospitalists serving as the primary attending, over two-thirds reported difficulty transferring patients to a higher level of care (Sweigart et al.⁵). While we have concerns over how representative this sample is of hospitalist practice (the survey response rate was only about 10%), it does appear that many hospitalists feel very uncomfortable with the ICU care they are providing and perceive barriers to moving their patients to a potentially safer care setting.

While one might argue more intensivists would solve this problem, calls for more intensivists are shortsighted, as there are compelling reasons to believe that such efforts will do little to address the mismatch between patient need and provider supply. Graduate medical education slots for intensivists cannot be easily and affordably increased, and even if more intensivists could be trained, there are few incentives to encourage them to work where they are needed most. Prioritization of intensivist training also diverts resources from training demands in equally important undersupplied specialties such as primary care.⁶ Finally, simply increasing intensivist supply fails to attend to important issues surrounding the multidisciplinary nature of care in an ICU, which relies heavily on multiple providers communicating and collaborating to provide optimal care. As noted in the study by Sweigart and colleagues,⁵ even in settings where intensivists were available 24 hours per day or made all major decisions, nearly one-third of hospitalists felt they practiced beyond their scope of expertise, suggesting that more intensivists may do little to improve hospitalists’ comfort in caring for patients in the ICU.

In lieu of increasing intensivist numbers, policymakers should consider several strategies that have the potential to improve the quality of care delivered to patients in the ICU without increasing intensivists. Recent data suggest that some ICU patients can be safely managed by physician assistants and nurse practitioners.^7,8 Care models involving such providers may free up overworked intensivists and hospitalists, allowing them to focus their efforts on the sickest patients. ICU telemedicine has also emerged as a promising tool that can bring the expertise of intensivists to hospitals where they are needed. Beyond the additional oversight of routine care practices it provides, telemedicine could allow rapid and real time consultation with intensivists for clinicians at the bedside facing difficult management decisions, potentially saving lives.⁹ The rapid growth of clinically integrated networks, which often include large well-staffed medical centers surrounded by many smaller regional hospitals, might facilitate faster implementation of innovative telemedicine models. Regionalization of care is a third strategy that may improve the quality of care for the critically ill without increasing intensivist supply. Regionalization seeks to selectively transfer the most ill patients to high-volume centers with the greatest expertise in critical care, a practice associated with reduced mortality.¹⁰ Of course, for regionalization to be successful, front-line providers like hospitalists need to be able to orchestrate the transfer to the referral center, a process that, as noted by Sweigart and others, is neither easy nor universally successful.¹¹

A final strategy would be to reduce the demand for intensivists through limiting the number of individuals in an ICU. While policies that explicitly ration ICU beds for individuals who have the greatest ability to benefit are ethically problematic, reductions in ICU beds would force providers to implicitly allocate beds more efficiently. There are a multitude of studies showing that our nation’s ICUs are often filled with patients who derive little benefit from intensive care.^12,13 Further research on ethically sound strategies to avoid ICU admission for patients unlikely to benefit is desperately needed. With fewer patients in an ICU, the busy intensivist could focus on the sickest patients and spend more time communicating with hospitalists about patients they are managing together.

Regardless of the care models that develop, hospitalists will increasingly be called upon to staff ICUs. Hospitalists are necessary, but as the study by Sweigart et al.⁵ suggests, just throwing them into our current ICU models with little support from their critical care colleagues is not sufficient. In the absence of a major influx of new intensivists, hospital medicine and critical care professional societies need to actively collaborate to develop creative training and educational models that provide hospitalists with the necessary skills to care for the critically ill and to lead the multidisciplinary care teams they will work within. More importantly, these professional societies must advocate together for more substantial reform to our current ICU care models. Novel solutions that prioritize the efficient use of existing ICU beds for those individuals with the greatest ability to benefit, but also capitalize on emerging technologies and regional centers of excellence, have great potential to address the mismatch between supply and demand. Given the increasing demand and substantial cost for ICU care, we can’t afford to continue with business as usual.

Disclosure

The authors declared no conflicts of interest.

In the United States, up to 6 million patients are admitted to intensive care units (ICUs) annually at a cost estimated to exceed $80 billion or about 13% of total hospital costs.^1,2 It also appears that as our population ages and illness severity increases, demand for ICU care is increasing.³ Given its importance, the organization and delivery of critical care has been extensively studied. High-intensity physician staffing by an intensivist (all patients managed or comanaged by an intensivist), while inconsistently shown to be associated with improved outcomes, has been endorsed as a high-quality care model by professional societies and the Leapfrog group. Despite its adoption by many hospitals, widespread implementation has been hampered by a national shortage of intensivists that continues to worsen over time. Hospitals, by necessity, look to alternative models to care for critically ill patients, and one such model is the use of hospitalists.

The Society of Hospital Medicine estimates that there are nearly 50,000 hospitalists practicing in the United States, and several studies show they routinely provide care in the nation’s ICUs.⁴ While in some ICUs hospitalists work alongside intensivists, in many, they work without intensivist support, and regardless of the model, they often serve as the primary attending physician. There is good reason to think this model of care would be effective. Most hospitalists are internists, graduating from training programs that tend to emphasize care of acutely ill hospitalized patients. Hospitalists are often present in the hospital 24/7, are comfortable working in multidisciplinary teams, and routinely engage in quality improvement, which are all characteristics common in highly functioning ICUs. Yet, a study in this issue of the Journal of Hospital Medicine raises some concern.

Sweigart and colleagues⁵ surveyed 425 hospitalists to understand the structure and perception of their ICU practices. Consistent with prior studies, 77% provided ICU care with 66% serving as the primary attending. A novel finding is the high level of angst and lack of support hospitalists perceived in caring for these critically ill patients. Among rural hospitalists, 43% reported they were expected to practice beyond their perceived scope of practice, and almost a third reported they never had sufficient intensivist support. Even more concerning is that among hospitalists serving as the primary attending, over two-thirds reported difficulty transferring patients to a higher level of care (Sweigart et al.⁵). While we have concerns over how representative this sample is of hospitalist practice (the survey response rate was only about 10%), it does appear that many hospitalists feel very uncomfortable with the ICU care they are providing and perceive barriers to moving their patients to a potentially safer care setting.

While one might argue more intensivists would solve this problem, calls for more intensivists are shortsighted, as there are compelling reasons to believe that such efforts will do little to address the mismatch between patient need and provider supply. Graduate medical education slots for intensivists cannot be easily and affordably increased, and even if more intensivists could be trained, there are few incentives to encourage them to work where they are needed most. Prioritization of intensivist training also diverts resources from training demands in equally important undersupplied specialties such as primary care.⁶ Finally, simply increasing intensivist supply fails to attend to important issues surrounding the multidisciplinary nature of care in an ICU, which relies heavily on multiple providers communicating and collaborating to provide optimal care. As noted in the study by Sweigart and colleagues,⁵ even in settings where intensivists were available 24 hours per day or made all major decisions, nearly one-third of hospitalists felt they practiced beyond their scope of expertise, suggesting that more intensivists may do little to improve hospitalists’ comfort in caring for patients in the ICU.

In lieu of increasing intensivist numbers, policymakers should consider several strategies that have the potential to improve the quality of care delivered to patients in the ICU without increasing intensivists. Recent data suggest that some ICU patients can be safely managed by physician assistants and nurse practitioners.^7,8 Care models involving such providers may free up overworked intensivists and hospitalists, allowing them to focus their efforts on the sickest patients. ICU telemedicine has also emerged as a promising tool that can bring the expertise of intensivists to hospitals where they are needed. Beyond the additional oversight of routine care practices it provides, telemedicine could allow rapid and real time consultation with intensivists for clinicians at the bedside facing difficult management decisions, potentially saving lives.⁹ The rapid growth of clinically integrated networks, which often include large well-staffed medical centers surrounded by many smaller regional hospitals, might facilitate faster implementation of innovative telemedicine models. Regionalization of care is a third strategy that may improve the quality of care for the critically ill without increasing intensivist supply. Regionalization seeks to selectively transfer the most ill patients to high-volume centers with the greatest expertise in critical care, a practice associated with reduced mortality.¹⁰ Of course, for regionalization to be successful, front-line providers like hospitalists need to be able to orchestrate the transfer to the referral center, a process that, as noted by Sweigart and others, is neither easy nor universally successful.¹¹

A final strategy would be to reduce the demand for intensivists through limiting the number of individuals in an ICU. While policies that explicitly ration ICU beds for individuals who have the greatest ability to benefit are ethically problematic, reductions in ICU beds would force providers to implicitly allocate beds more efficiently. There are a multitude of studies showing that our nation’s ICUs are often filled with patients who derive little benefit from intensive care.^12,13 Further research on ethically sound strategies to avoid ICU admission for patients unlikely to benefit is desperately needed. With fewer patients in an ICU, the busy intensivist could focus on the sickest patients and spend more time communicating with hospitalists about patients they are managing together.

Regardless of the care models that develop, hospitalists will increasingly be called upon to staff ICUs. Hospitalists are necessary, but as the study by Sweigart et al.⁵ suggests, just throwing them into our current ICU models with little support from their critical care colleagues is not sufficient. In the absence of a major influx of new intensivists, hospital medicine and critical care professional societies need to actively collaborate to develop creative training and educational models that provide hospitalists with the necessary skills to care for the critically ill and to lead the multidisciplinary care teams they will work within. More importantly, these professional societies must advocate together for more substantial reform to our current ICU care models. Novel solutions that prioritize the efficient use of existing ICU beds for those individuals with the greatest ability to benefit, but also capitalize on emerging technologies and regional centers of excellence, have great potential to address the mismatch between supply and demand. Given the increasing demand and substantial cost for ICU care, we can’t afford to continue with business as usual.

Disclosure

The authors declared no conflicts of interest.

Patient satisfaction with medical care during hospitalization is a common quality metric.^1,2 Studies showing higher patient satisfaction have reported lower 30-day hospital readmissions³ and improved overall health.^4,5 Conversely, communication failures are associated with dissatisfaction among hospitalized patients and adverse outcomes.^6,7 A lack of familiarity with hospital providers weakens collaborative decision making and prevents high-quality patient care.^8,9

Bedside visual tools, such as whiteboards and pictures of medical staff, have been widely used to enhance communication between patients, families, and providers.^10,11 Results of studies evaluating these tools are varied. For example, 1 study found that 98% of patients were better able to identify physicians when their names were written on whiteboards.¹² Yet in another, only 21.1% of patients were more likely to correctly identify ≥1 physicians using pictures.¹³ Thus, despite widespread use,¹¹ whether visual tools improve patient satisfaction and patient care more broadly remains unclear.^14,15

We performed a systematic review to answer the following 3 questions: first, what is the effect of visual tools on outcomes (ie, provider identification, understanding of providers’ roles, patient–provider communication, and satisfaction); second, does impact vary by type of visual tool (eg, whiteboards vs pictures of providers); and third, what factors (eg, study design, patient population) are associated with provider identification, communication, and patient satisfaction?

Search Strategy

We used the Preferred Reporting Items for Systematic Reviews and Meta-Analysis when performing this review.¹⁶ A research librarian (WT) conducted serial searches for studies reporting the use of bedside visual tools for hospitalized patients in Medline (via OVID), Embase, SCOPUS, Web of Science, CINAHL, and Cochrane DSR and CENTRAL. Controlled vocabularies (ie, Medical Subject Headings terms) were used to identify synonyms for visual tools of interest. Additional studies were identified manually through bibliographies and meeting abstracts. No study design, publication date, or language restrictions were placed on the search, which was conducted between April 2016 and February 2017 (see supplementary Appendix A).

Study Selection

Two reviewers (AG and KT) independently assessed study eligibility; discrepancies were resolved by a third reviewer (VC). We included all adult or pediatric English language studies in which the effect of visual tool(s) on patient outcomes was reported. Visual tools were defined as the bedside display of information or an instrument given to patients to convey information regarding providers or medical care. Patient-reported outcomes included the following: (a) physician identification, (b) understanding of provider roles, (c) patient–provider communication, and (d) patient satisfaction with care. Providers were defined as physicians, residents, interns, medical students, nurse practitioners, or nurses. We excluded studies that were not original research (eg, conference abstracts, not peer reviewed), reported qualitative data without quantitative outcomes, or did not include a bedside visual tool. Given our interest in hospitalized general medicine patients, studies conducted in emergency departments, surgical units, obstetrics and gynecology wards, and intensive care units were excluded.

Data Extraction and Analysis

Data were extracted independently and in duplicate from all studies by using a template adapted from the Cochrane Collaboration.¹⁷ For all studies, we abstracted study design, type of visual tool (eg, whiteboards), unit setting (eg, medical), population studied (eg, adult vs pediatric), and outcomes reported (ie, physician identification, understanding of provider roles, communication, and satisfaction with care). Reviewers independently assessed and categorized the impact of tools on reported outcomes.

To standardize and compare outcomes across studies, the following were used to denote a positive association between visual tools and relevant outcomes: a greater number of physicians correctly identified by name/picture or title/role; the use of terms such as “high,” “agreed,” or “significant” on surveys; or ≥4 Likert scores for domains of identification, understanding of roles, communication, and satisfaction with care. Conversely, the inability to identify providers compared to the control/baseline; poor recall of titles/roles; lower Likert-scale scores (ie, ≤2); or survey terms such as “poor,” “disagreed,” or “insignificant” were considered to connote negative impact. Studies in which Likert scores were rated neither high nor low (ie, 3), or in which patients neither agreed nor disagreed on value were considered neutral.

Owing to clinical heterogeneity within studies, meta-analyses were not performed. Descriptive statistics were used to describe study outcomes. A priori¹⁸ studies were evaluated according to the following categories: design (eg, randomized vs observational), outcomes (eg, patient satisfaction), intervention (type of visual tool), and patient population (adult or pediatric). Because pediatric patients have underdeveloped communication skills and include parents and/or guardians, data from pediatric studies were tabulated and reported separately to those from adult studies.

Quality Assessment

As recommended by the Cochrane Collaboration, 2 reviewers (AG, KT) assessed the risk of study bias by using the Downs and Black Scale.^17,19 Discrepancies in assessment were resolved by a third reviewer (VC). This instrument uses a point-based system to estimate the quality of a study by rating domains such as internal and external validity, bias, and confounding. In keeping with prior systematic reviews,^18,20,21 studies with a score of ≥18 were considered high quality. Interrater agreement for the adjudication of study quality was calculated using the Cohen κ statistic.

Eleven studies were conducted on adult hospitalized pa­tients ^{12-14,22-24,26,27,29,30,33} and included 3 randomized controlled studies.^14,27,33

Results by Outcomes Provider Identification Nine studies measured patients’ ability to identify providers with the use of visual aids, and all 9 reported improvements in this outcome. Visual tools used to measure provider identification included pictures (n = 5),^{13,14,23,27,33} whiteboards (n = 3),^12,22,30 and patient portals (n = 1).²⁶ Within studies that used pictures, individual pictures (n = 2)^13,23 and handouts with pictures of multiple providers (n = 3) were used.^14,27,33 In 2 studies, care team members such as a dietitian, physiotherapist or pharmacist, were included when measuring identification.^14,33

Understanding Providers’ RolesSix studies assessed the effect of visual tools on patients’ understanding of provider roles.^{13,14,22,26,27,33} Four studies reported a positive effect with the use of pictures,^27,33 whiteboards,²² and patient portals.²⁶ However, 2 studies reported either no difference or negative impressions. Appel et al.¹⁴ reported no difference in the understanding of physician roles using a handout of providers’ pictures and titles. Arora et al.¹³ used individual pictures of physicians with descriptions of roles and found a negative association, as demonstrated by fewer patients rating their understanding of physicians’ roles as excellent or very good in the intervention period (45.6%) compared with the baseline (55.3%).

 

Patient–Provider Communication

Three studies evaluated the influence of visual tools on communication.^14,24,29 Using pictures, Appel et al.¹⁴ found no difference in the perceived quality of communication. Singh et al.²⁹ used whiteboards and reported improved communication scores for physicians and nurses. With notepads, patients surveyed by Farberg et al.²⁴ stated that the tool improved provider communication.

Patient Satisfaction

Five studies assessed patient satisfaction related to the use of visual tools. ^{22,23,27,30,33} One study reported satisfaction as positive with the use of individual pictures.²³ Two studies that used handouts with pictures of all team members reported either a positive³³ or neutral²⁷ impact on satisfaction. Studies that used whiteboards reported a positive association with satisfaction^22,30 despite differences in content, such as the inclusion of prewritten prompts for writing goals of care and scheduled tests³⁰ versus the name of the nurse and their education level.²²

Results by Type of Visual Tool Pictures

Five studies that used pictures reported a positive effect on provider identification.^{13,14,23,27,33} Two^27,33 of 4 studies^13,14,27,33 that assessed patients’ understanding of team member roles reported a positive influence, while 1 reported no difference.¹⁴ A fourth study demonstrated a negative association, perhaps due to differences in the description of providers’ roles listed on the tool.¹³ Only 1 study examined the influence of pictures on patient–provider communication, and this study found no difference.¹⁴ Satisfaction with care via the use of pictures varied between positive (2 studies)^23,33 and neutral (1 study).²⁷

Whiteboards

Four studies tested the use of whiteboards; of these, 3 reported a positive influence on provider identification.^12,22,30 One study reported a positive impact on patient–provider communication.²⁹ Two studies noted a positive effect on patient satisfaction.^22,30 Notably, the responsibility for updating whiteboards differed between the studies (ie, nurses only²² vs residents, medical students, and nurses).³⁰

Patient Portal

In 1 study, an electronic portal that included names with pictures of providers, descriptions of their roles, lists of medications, and scheduled tests and/or procedures was used as a visual tool. The portal improved patients’ identification of physicians and patients’ understanding of roles. However, improvements in the knowledge of medication changes and planned tests and/or procedures during hospitalization were not observed.²⁶ This finding would suggest limitations in the hospitalized patient’s knowledge of the plan of care, which could potentially weaken patient–provider communication.

Notepads

Only 1 study assessed the use of formatted notepads on patient–provider communication and noted a positive association. Notepads used prompts for different categories (eg, diagnosis/treatment, medications, etc) to encourage patient questions for providers.²⁴

Five studies were conducted on hospitalized pediatric units.^{15,25,28,31,32} All studies surveyed the parents, guardians, or caregivers of pediatric patients. One study excluded patients ≥12 years of age because of legal differences in access to adolescent health information,³² while another interviewed parents and/or guardians of teenagers.¹⁵

Results by Outcomes Provider Identification and Understanding of Physicians’ Roles

Four studies that assessed the influence of visual tools on provider identification and understanding of roles reported a positive association.^15,25,28,31 Visual tools varied between pictures (n = 2),^15,31 patient portal (n = 1),²⁸ and whiteboards and pictures combined (n = 1).²⁵ The measurement of outcomes varied between surveys with free text responses,²⁸ multiple choice questions,²⁵ and 1-5 Likert scales.^15,31

Patient–Provider Communication

Two studies assessed the impact of patient portal use on communication and reported a positive association.^28,32 The 2 portals autopopulated names, pictures, and roles of providers from electronic medical records. Singh et al.²⁸ used a portal that was also available in Spanish and accommodated for non-English speakers. Kelly et al.³² reported that 90% of parents perceived that portal use was associated with reduced errors in care, with 8% finding errors in their child’s medication list.

Patient Satisfaction

Three studies assessed patient satisfaction via the use of visual tools.^15,28,31 Singh et al.²⁸ noted a positive influence on satisfaction via a patient portal. Dudas et al.¹⁵ used a single-page handout with names and pictures of each provider, along with information regarding the training and roles of each provider. Distribution of these handouts to patients by investigators led to a positive influence on satisfaction. While Unaka et al.³¹ used a similar handout, they asked residents to distribute them and found no significant difference in satisfaction scores between the intervention (66%) and control group (62%).

Results by Type of Visual Tool Pictures

Two studies reported a positive impact on provider identification and understanding of roles with the use of pictures.^15,31 Dudas et al.¹⁵ demonstrated a 4.8-fold increase in the odds of parents identifying a medical student, as compared with the control. Similarly, after adjusting for length of stay and prior hospitalization, Unaka et al.³¹ reported that a higher percentage of patients correctly identified providers using this approach.

Whiteboard and Picture

One study evaluated the simultaneous use of whiteboards and pictures to improve the identification of providers. The study noted improved identification of supervising doctors and increased recognition of roles for supervising doctors, residents, and medical students.²⁵

Patient Portal

Two studies used patient portals as visual tools. Singh et al.²⁸ assessed the use of a patient portal with names, roles, and pictures of treatment team members. Use of this tool was positively associated with provider identification, understanding of roles, communication, and satisfaction. Kelly et al.³² noted that 60% of parents felt that portal use improved healthcare team communication.

The risk of bias was assessed for both adult and pediatric studies in aggregate. The average risk of bias using the Downs and Black Scale was 17.81 (range 14-22, standard deviation [SD] 2.20). Of the 16 included studies, 9 were rated at a low risk of bias (score

• >

18).^13-15,26-31 Risk of bias was greatest for measures of external validity (mean 2.88, range 2-3, SD 0.34), internal validity (mean 4.06, range 3-6, SD 1.00), and confounding (mean 2.69, range 1-6, SD 1.35). Two of 3 randomized controlled trials had a low risk of bias.^14,27 Interrater reliability for study quality adjudication was 0.90, suggesting excellent agreement (see supplementary Appendix B).

In this systematic review, the effects of visual tools on outcomes, such as provider identification, understanding of roles, patient–provider communication, and satisfaction with care, were variable. The majority of included studies were conducted on adult patients (n = 11).^{12-14,22-24,26,27,29,30,33} Pictures were the most frequently used tool (n = 7)^{13-15,23,27,31,33} and consequently had the greatest sample size across the review (n = 1297). While pictures had a positive influence on provider identification in all studies, comprehension of provider roles and satisfaction were variable. Although the content of whiteboards varied between studies, they showed favorable effects on provider identification (3 of 4 studies)^12,22,30 and satisfaction (2 of 2 studies).^22,30 While electronic medical record-based tools had a positive influence on outcomes,^26,28 only 1 accounted for language preferences.²⁸ Formatted notepads positively influenced patient–provider communication, but their use was limited by literacy.²⁴ Collectively, these data suggest that visual tools have varying effects on patient-reported outcomes, likely owing to differences in study design, interventions, and evaluation methods.

Theoretically, visual tools should facilitate easier identification of providers and engender collaborative relationships. However, such tools do not replace face-to-face patient–provider and family discussions. Rather, these enhancements best serve as a medium to asynchronously display information to patients and family members. Indeed, within the included studies, we found that the use of visual tools was effective in improving satisfaction (6/8 studies), identification (13/13 studies), and understanding of provider roles (8/10 studies). Thus, it is reasonable to say that, in conjunction with excellent clinical care, these tools have an important role in improving care delivery in the hospital.

Despite this promise, we noted that the effectiveness of individual tools varied, a fact that may relate to differences across studies. First, inconsistencies in the format and/or content of the tools were noted. For example, within studies using pictures, tools varied from individual photographs of each team member^13,23 to 1-page handouts with pictures of all team members.^14,15,31 Such differences in presentation could affect spatial recognition in identifying providers, as single photos are known to be easier to process than multiple images at the same time.³⁴ Second, no study evaluated patient preference of a visual tool. Thus, personal preferences for pictures versus whiteboards versus electronic modalities or a combination of tools might affect outcomes. Additionally, the utility of visual tools in visually impaired, confused, or non-English-speaking patients may limit effectiveness. Future studies that address these aspects and account for patient preferences may better elucidate the role of visual tools in hospitals.

Our results should be considered in the context of several limitations. First, only 3 studies used randomized trial designs; thus, confounding from unmeasured variables inherent to observational designs is possible. Second, none of the interventions tested were blinded to providers, raising the possibility of a Hawthorne effect (ie, alteration of provider behavior in response to awareness of being observed).³⁵ Third, all studies were conducted at single centers, and only 9 of 16 studies were rated at a low risk of bias; thus, caution in broad extrapolations of this literature is necessary.

However, our study has several strengths, including a thorough search of heterogeneous literature, inclusion of both adult and pediatric populations, and a focus on myriad patient-reported outcomes. Second, by contrasting outcomes and measurement strategies across studies, our review helps explicate differences in results related to variation in outcome measurement or presentation of visual data. Third, because we frame results by outcome and type of visual tool used, we are able to identify strengths and weaknesses of individual tools in novel ways. Finally, our data suggest that the use of picture-based techniques and whiteboards are among the most promising visual interventions. Future studies that pair graphic designers with patients to improve the layout of these tools might prove valuable. Additionally, because the measurement of outcomes is confounded by aspects such as lack of controls, severity of illness, and language barriers, a randomized design would help provide greater clarity regarding effectiveness.

In conclusion, we found that visual tools appear to foster recognition of providers and understanding of their roles. However, variability of format, content, and measurement of outcomes hinders the identification of a single optimal approach. Future work using randomized controlled trial designs and standardized tools and measurements would be welcomed.

Acknowledgments

The authors thank Laura Appel, Kevin O’Leary, and Siddharth Singh for providing unpublished data and clarifications to help these analyses.

Disclosure

 Anupama Goyal is the guarantor. Anupama Goyal and Komalpreet Tur performed primary data abstraction and analysis. Anupama Goyal, Scott Flanders, Jason Mann, and Vineet Chopra drafted the manuscript. All authors contributed to the development of the selection criteria, the risk of bias assessment strategy, and the data extraction criteria. Anupama Goyal, Jason Mann, Whitney Townsend, and Vineet Chopra developed the search strategy. Vineet Chopra provided systematic review expertise. All authors read, provided feedback, and approved the final manuscript. The authors declare that they have no conflicts of interest.

Patient satisfaction with medical care during hospitalization is a common quality metric.^1,2 Studies showing higher patient satisfaction have reported lower 30-day hospital readmissions³ and improved overall health.^4,5 Conversely, communication failures are associated with dissatisfaction among hospitalized patients and adverse outcomes.^6,7 A lack of familiarity with hospital providers weakens collaborative decision making and prevents high-quality patient care.^8,9

Bedside visual tools, such as whiteboards and pictures of medical staff, have been widely used to enhance communication between patients, families, and providers.^10,11 Results of studies evaluating these tools are varied. For example, 1 study found that 98% of patients were better able to identify physicians when their names were written on whiteboards.¹² Yet in another, only 21.1% of patients were more likely to correctly identify ≥1 physicians using pictures.¹³ Thus, despite widespread use,¹¹ whether visual tools improve patient satisfaction and patient care more broadly remains unclear.^14,15

We performed a systematic review to answer the following 3 questions: first, what is the effect of visual tools on outcomes (ie, provider identification, understanding of providers’ roles, patient–provider communication, and satisfaction); second, does impact vary by type of visual tool (eg, whiteboards vs pictures of providers); and third, what factors (eg, study design, patient population) are associated with provider identification, communication, and patient satisfaction?

Search Strategy

We used the Preferred Reporting Items for Systematic Reviews and Meta-Analysis when performing this review.¹⁶ A research librarian (WT) conducted serial searches for studies reporting the use of bedside visual tools for hospitalized patients in Medline (via OVID), Embase, SCOPUS, Web of Science, CINAHL, and Cochrane DSR and CENTRAL. Controlled vocabularies (ie, Medical Subject Headings terms) were used to identify synonyms for visual tools of interest. Additional studies were identified manually through bibliographies and meeting abstracts. No study design, publication date, or language restrictions were placed on the search, which was conducted between April 2016 and February 2017 (see supplementary Appendix A).

Study Selection

Two reviewers (AG and KT) independently assessed study eligibility; discrepancies were resolved by a third reviewer (VC). We included all adult or pediatric English language studies in which the effect of visual tool(s) on patient outcomes was reported. Visual tools were defined as the bedside display of information or an instrument given to patients to convey information regarding providers or medical care. Patient-reported outcomes included the following: (a) physician identification, (b) understanding of provider roles, (c) patient–provider communication, and (d) patient satisfaction with care. Providers were defined as physicians, residents, interns, medical students, nurse practitioners, or nurses. We excluded studies that were not original research (eg, conference abstracts, not peer reviewed), reported qualitative data without quantitative outcomes, or did not include a bedside visual tool. Given our interest in hospitalized general medicine patients, studies conducted in emergency departments, surgical units, obstetrics and gynecology wards, and intensive care units were excluded.

Data Extraction and Analysis

Data were extracted independently and in duplicate from all studies by using a template adapted from the Cochrane Collaboration.¹⁷ For all studies, we abstracted study design, type of visual tool (eg, whiteboards), unit setting (eg, medical), population studied (eg, adult vs pediatric), and outcomes reported (ie, physician identification, understanding of provider roles, communication, and satisfaction with care). Reviewers independently assessed and categorized the impact of tools on reported outcomes.

To standardize and compare outcomes across studies, the following were used to denote a positive association between visual tools and relevant outcomes: a greater number of physicians correctly identified by name/picture or title/role; the use of terms such as “high,” “agreed,” or “significant” on surveys; or ≥4 Likert scores for domains of identification, understanding of roles, communication, and satisfaction with care. Conversely, the inability to identify providers compared to the control/baseline; poor recall of titles/roles; lower Likert-scale scores (ie, ≤2); or survey terms such as “poor,” “disagreed,” or “insignificant” were considered to connote negative impact. Studies in which Likert scores were rated neither high nor low (ie, 3), or in which patients neither agreed nor disagreed on value were considered neutral.

Owing to clinical heterogeneity within studies, meta-analyses were not performed. Descriptive statistics were used to describe study outcomes. A priori¹⁸ studies were evaluated according to the following categories: design (eg, randomized vs observational), outcomes (eg, patient satisfaction), intervention (type of visual tool), and patient population (adult or pediatric). Because pediatric patients have underdeveloped communication skills and include parents and/or guardians, data from pediatric studies were tabulated and reported separately to those from adult studies.

Quality Assessment

As recommended by the Cochrane Collaboration, 2 reviewers (AG, KT) assessed the risk of study bias by using the Downs and Black Scale.^17,19 Discrepancies in assessment were resolved by a third reviewer (VC). This instrument uses a point-based system to estimate the quality of a study by rating domains such as internal and external validity, bias, and confounding. In keeping with prior systematic reviews,^18,20,21 studies with a score of ≥18 were considered high quality. Interrater agreement for the adjudication of study quality was calculated using the Cohen κ statistic.

Eleven studies were conducted on adult hospitalized pa­tients ^{12-14,22-24,26,27,29,30,33} and included 3 randomized controlled studies.^14,27,33

Results by Outcomes Provider Identification Nine studies measured patients’ ability to identify providers with the use of visual aids, and all 9 reported improvements in this outcome. Visual tools used to measure provider identification included pictures (n = 5),^{13,14,23,27,33} whiteboards (n = 3),^12,22,30 and patient portals (n = 1).²⁶ Within studies that used pictures, individual pictures (n = 2)^13,23 and handouts with pictures of multiple providers (n = 3) were used.^14,27,33 In 2 studies, care team members such as a dietitian, physiotherapist or pharmacist, were included when measuring identification.^14,33

Understanding Providers’ RolesSix studies assessed the effect of visual tools on patients’ understanding of provider roles.^{13,14,22,26,27,33} Four studies reported a positive effect with the use of pictures,^27,33 whiteboards,²² and patient portals.²⁶ However, 2 studies reported either no difference or negative impressions. Appel et al.¹⁴ reported no difference in the understanding of physician roles using a handout of providers’ pictures and titles. Arora et al.¹³ used individual pictures of physicians with descriptions of roles and found a negative association, as demonstrated by fewer patients rating their understanding of physicians’ roles as excellent or very good in the intervention period (45.6%) compared with the baseline (55.3%).

 

Patient–Provider Communication

Three studies evaluated the influence of visual tools on communication.^14,24,29 Using pictures, Appel et al.¹⁴ found no difference in the perceived quality of communication. Singh et al.²⁹ used whiteboards and reported improved communication scores for physicians and nurses. With notepads, patients surveyed by Farberg et al.²⁴ stated that the tool improved provider communication.

Patient Satisfaction

Five studies assessed patient satisfaction related to the use of visual tools. ^{22,23,27,30,33} One study reported satisfaction as positive with the use of individual pictures.²³ Two studies that used handouts with pictures of all team members reported either a positive³³ or neutral²⁷ impact on satisfaction. Studies that used whiteboards reported a positive association with satisfaction^22,30 despite differences in content, such as the inclusion of prewritten prompts for writing goals of care and scheduled tests³⁰ versus the name of the nurse and their education level.²²

Results by Type of Visual Tool Pictures

Five studies that used pictures reported a positive effect on provider identification.^{13,14,23,27,33} Two^27,33 of 4 studies^13,14,27,33 that assessed patients’ understanding of team member roles reported a positive influence, while 1 reported no difference.¹⁴ A fourth study demonstrated a negative association, perhaps due to differences in the description of providers’ roles listed on the tool.¹³ Only 1 study examined the influence of pictures on patient–provider communication, and this study found no difference.¹⁴ Satisfaction with care via the use of pictures varied between positive (2 studies)^23,33 and neutral (1 study).²⁷

Whiteboards

Four studies tested the use of whiteboards; of these, 3 reported a positive influence on provider identification.^12,22,30 One study reported a positive impact on patient–provider communication.²⁹ Two studies noted a positive effect on patient satisfaction.^22,30 Notably, the responsibility for updating whiteboards differed between the studies (ie, nurses only²² vs residents, medical students, and nurses).³⁰

Patient Portal

In 1 study, an electronic portal that included names with pictures of providers, descriptions of their roles, lists of medications, and scheduled tests and/or procedures was used as a visual tool. The portal improved patients’ identification of physicians and patients’ understanding of roles. However, improvements in the knowledge of medication changes and planned tests and/or procedures during hospitalization were not observed.²⁶ This finding would suggest limitations in the hospitalized patient’s knowledge of the plan of care, which could potentially weaken patient–provider communication.

Notepads

Only 1 study assessed the use of formatted notepads on patient–provider communication and noted a positive association. Notepads used prompts for different categories (eg, diagnosis/treatment, medications, etc) to encourage patient questions for providers.²⁴

Five studies were conducted on hospitalized pediatric units.^{15,25,28,31,32} All studies surveyed the parents, guardians, or caregivers of pediatric patients. One study excluded patients ≥12 years of age because of legal differences in access to adolescent health information,³² while another interviewed parents and/or guardians of teenagers.¹⁵

Results by Outcomes Provider Identification and Understanding of Physicians’ Roles

Four studies that assessed the influence of visual tools on provider identification and understanding of roles reported a positive association.^15,25,28,31 Visual tools varied between pictures (n = 2),^15,31 patient portal (n = 1),²⁸ and whiteboards and pictures combined (n = 1).²⁵ The measurement of outcomes varied between surveys with free text responses,²⁸ multiple choice questions,²⁵ and 1-5 Likert scales.^15,31

Patient–Provider Communication

Two studies assessed the impact of patient portal use on communication and reported a positive association.^28,32 The 2 portals autopopulated names, pictures, and roles of providers from electronic medical records. Singh et al.²⁸ used a portal that was also available in Spanish and accommodated for non-English speakers. Kelly et al.³² reported that 90% of parents perceived that portal use was associated with reduced errors in care, with 8% finding errors in their child’s medication list.

Patient Satisfaction

Three studies assessed patient satisfaction via the use of visual tools.^15,28,31 Singh et al.²⁸ noted a positive influence on satisfaction via a patient portal. Dudas et al.¹⁵ used a single-page handout with names and pictures of each provider, along with information regarding the training and roles of each provider. Distribution of these handouts to patients by investigators led to a positive influence on satisfaction. While Unaka et al.³¹ used a similar handout, they asked residents to distribute them and found no significant difference in satisfaction scores between the intervention (66%) and control group (62%).

Results by Type of Visual Tool Pictures

Two studies reported a positive impact on provider identification and understanding of roles with the use of pictures.^15,31 Dudas et al.¹⁵ demonstrated a 4.8-fold increase in the odds of parents identifying a medical student, as compared with the control. Similarly, after adjusting for length of stay and prior hospitalization, Unaka et al.³¹ reported that a higher percentage of patients correctly identified providers using this approach.

Whiteboard and Picture

One study evaluated the simultaneous use of whiteboards and pictures to improve the identification of providers. The study noted improved identification of supervising doctors and increased recognition of roles for supervising doctors, residents, and medical students.²⁵

Patient Portal

Two studies used patient portals as visual tools. Singh et al.²⁸ assessed the use of a patient portal with names, roles, and pictures of treatment team members. Use of this tool was positively associated with provider identification, understanding of roles, communication, and satisfaction. Kelly et al.³² noted that 60% of parents felt that portal use improved healthcare team communication.

The risk of bias was assessed for both adult and pediatric studies in aggregate. The average risk of bias using the Downs and Black Scale was 17.81 (range 14-22, standard deviation [SD] 2.20). Of the 16 included studies, 9 were rated at a low risk of bias (score

• >

18).^13-15,26-31 Risk of bias was greatest for measures of external validity (mean 2.88, range 2-3, SD 0.34), internal validity (mean 4.06, range 3-6, SD 1.00), and confounding (mean 2.69, range 1-6, SD 1.35). Two of 3 randomized controlled trials had a low risk of bias.^14,27 Interrater reliability for study quality adjudication was 0.90, suggesting excellent agreement (see supplementary Appendix B).

In this systematic review, the effects of visual tools on outcomes, such as provider identification, understanding of roles, patient–provider communication, and satisfaction with care, were variable. The majority of included studies were conducted on adult patients (n = 11).^{12-14,22-24,26,27,29,30,33} Pictures were the most frequently used tool (n = 7)^{13-15,23,27,31,33} and consequently had the greatest sample size across the review (n = 1297). While pictures had a positive influence on provider identification in all studies, comprehension of provider roles and satisfaction were variable. Although the content of whiteboards varied between studies, they showed favorable effects on provider identification (3 of 4 studies)^12,22,30 and satisfaction (2 of 2 studies).^22,30 While electronic medical record-based tools had a positive influence on outcomes,^26,28 only 1 accounted for language preferences.²⁸ Formatted notepads positively influenced patient–provider communication, but their use was limited by literacy.²⁴ Collectively, these data suggest that visual tools have varying effects on patient-reported outcomes, likely owing to differences in study design, interventions, and evaluation methods.

Theoretically, visual tools should facilitate easier identification of providers and engender collaborative relationships. However, such tools do not replace face-to-face patient–provider and family discussions. Rather, these enhancements best serve as a medium to asynchronously display information to patients and family members. Indeed, within the included studies, we found that the use of visual tools was effective in improving satisfaction (6/8 studies), identification (13/13 studies), and understanding of provider roles (8/10 studies). Thus, it is reasonable to say that, in conjunction with excellent clinical care, these tools have an important role in improving care delivery in the hospital.

Despite this promise, we noted that the effectiveness of individual tools varied, a fact that may relate to differences across studies. First, inconsistencies in the format and/or content of the tools were noted. For example, within studies using pictures, tools varied from individual photographs of each team member^13,23 to 1-page handouts with pictures of all team members.^14,15,31 Such differences in presentation could affect spatial recognition in identifying providers, as single photos are known to be easier to process than multiple images at the same time.³⁴ Second, no study evaluated patient preference of a visual tool. Thus, personal preferences for pictures versus whiteboards versus electronic modalities or a combination of tools might affect outcomes. Additionally, the utility of visual tools in visually impaired, confused, or non-English-speaking patients may limit effectiveness. Future studies that address these aspects and account for patient preferences may better elucidate the role of visual tools in hospitals.

Our results should be considered in the context of several limitations. First, only 3 studies used randomized trial designs; thus, confounding from unmeasured variables inherent to observational designs is possible. Second, none of the interventions tested were blinded to providers, raising the possibility of a Hawthorne effect (ie, alteration of provider behavior in response to awareness of being observed).³⁵ Third, all studies were conducted at single centers, and only 9 of 16 studies were rated at a low risk of bias; thus, caution in broad extrapolations of this literature is necessary.

However, our study has several strengths, including a thorough search of heterogeneous literature, inclusion of both adult and pediatric populations, and a focus on myriad patient-reported outcomes. Second, by contrasting outcomes and measurement strategies across studies, our review helps explicate differences in results related to variation in outcome measurement or presentation of visual data. Third, because we frame results by outcome and type of visual tool used, we are able to identify strengths and weaknesses of individual tools in novel ways. Finally, our data suggest that the use of picture-based techniques and whiteboards are among the most promising visual interventions. Future studies that pair graphic designers with patients to improve the layout of these tools might prove valuable. Additionally, because the measurement of outcomes is confounded by aspects such as lack of controls, severity of illness, and language barriers, a randomized design would help provide greater clarity regarding effectiveness.

In conclusion, we found that visual tools appear to foster recognition of providers and understanding of their roles. However, variability of format, content, and measurement of outcomes hinders the identification of a single optimal approach. Future work using randomized controlled trial designs and standardized tools and measurements would be welcomed.

Acknowledgments

The authors thank Laura Appel, Kevin O’Leary, and Siddharth Singh for providing unpublished data and clarifications to help these analyses.

Disclosure

 Anupama Goyal is the guarantor. Anupama Goyal and Komalpreet Tur performed primary data abstraction and analysis. Anupama Goyal, Scott Flanders, Jason Mann, and Vineet Chopra drafted the manuscript. All authors contributed to the development of the selection criteria, the risk of bias assessment strategy, and the data extraction criteria. Anupama Goyal, Jason Mann, Whitney Townsend, and Vineet Chopra developed the search strategy. Vineet Chopra provided systematic review expertise. All authors read, provided feedback, and approved the final manuscript. The authors declare that they have no conflicts of interest.

Patient satisfaction with medical care during hospitalization is a common quality metric.^1,2 Studies showing higher patient satisfaction have reported lower 30-day hospital readmissions³ and improved overall health.^4,5 Conversely, communication failures are associated with dissatisfaction among hospitalized patients and adverse outcomes.^6,7 A lack of familiarity with hospital providers weakens collaborative decision making and prevents high-quality patient care.^8,9

Bedside visual tools, such as whiteboards and pictures of medical staff, have been widely used to enhance communication between patients, families, and providers.^10,11 Results of studies evaluating these tools are varied. For example, 1 study found that 98% of patients were better able to identify physicians when their names were written on whiteboards.¹² Yet in another, only 21.1% of patients were more likely to correctly identify ≥1 physicians using pictures.¹³ Thus, despite widespread use,¹¹ whether visual tools improve patient satisfaction and patient care more broadly remains unclear.^14,15

We performed a systematic review to answer the following 3 questions: first, what is the effect of visual tools on outcomes (ie, provider identification, understanding of providers’ roles, patient–provider communication, and satisfaction); second, does impact vary by type of visual tool (eg, whiteboards vs pictures of providers); and third, what factors (eg, study design, patient population) are associated with provider identification, communication, and patient satisfaction?

Search Strategy

We used the Preferred Reporting Items for Systematic Reviews and Meta-Analysis when performing this review.¹⁶ A research librarian (WT) conducted serial searches for studies reporting the use of bedside visual tools for hospitalized patients in Medline (via OVID), Embase, SCOPUS, Web of Science, CINAHL, and Cochrane DSR and CENTRAL. Controlled vocabularies (ie, Medical Subject Headings terms) were used to identify synonyms for visual tools of interest. Additional studies were identified manually through bibliographies and meeting abstracts. No study design, publication date, or language restrictions were placed on the search, which was conducted between April 2016 and February 2017 (see supplementary Appendix A).

Study Selection

Two reviewers (AG and KT) independently assessed study eligibility; discrepancies were resolved by a third reviewer (VC). We included all adult or pediatric English language studies in which the effect of visual tool(s) on patient outcomes was reported. Visual tools were defined as the bedside display of information or an instrument given to patients to convey information regarding providers or medical care. Patient-reported outcomes included the following: (a) physician identification, (b) understanding of provider roles, (c) patient–provider communication, and (d) patient satisfaction with care. Providers were defined as physicians, residents, interns, medical students, nurse practitioners, or nurses. We excluded studies that were not original research (eg, conference abstracts, not peer reviewed), reported qualitative data without quantitative outcomes, or did not include a bedside visual tool. Given our interest in hospitalized general medicine patients, studies conducted in emergency departments, surgical units, obstetrics and gynecology wards, and intensive care units were excluded.

Data Extraction and Analysis

Data were extracted independently and in duplicate from all studies by using a template adapted from the Cochrane Collaboration.¹⁷ For all studies, we abstracted study design, type of visual tool (eg, whiteboards), unit setting (eg, medical), population studied (eg, adult vs pediatric), and outcomes reported (ie, physician identification, understanding of provider roles, communication, and satisfaction with care). Reviewers independently assessed and categorized the impact of tools on reported outcomes.

To standardize and compare outcomes across studies, the following were used to denote a positive association between visual tools and relevant outcomes: a greater number of physicians correctly identified by name/picture or title/role; the use of terms such as “high,” “agreed,” or “significant” on surveys; or ≥4 Likert scores for domains of identification, understanding of roles, communication, and satisfaction with care. Conversely, the inability to identify providers compared to the control/baseline; poor recall of titles/roles; lower Likert-scale scores (ie, ≤2); or survey terms such as “poor,” “disagreed,” or “insignificant” were considered to connote negative impact. Studies in which Likert scores were rated neither high nor low (ie, 3), or in which patients neither agreed nor disagreed on value were considered neutral.

Owing to clinical heterogeneity within studies, meta-analyses were not performed. Descriptive statistics were used to describe study outcomes. A priori¹⁸ studies were evaluated according to the following categories: design (eg, randomized vs observational), outcomes (eg, patient satisfaction), intervention (type of visual tool), and patient population (adult or pediatric). Because pediatric patients have underdeveloped communication skills and include parents and/or guardians, data from pediatric studies were tabulated and reported separately to those from adult studies.

Quality Assessment

As recommended by the Cochrane Collaboration, 2 reviewers (AG, KT) assessed the risk of study bias by using the Downs and Black Scale.^17,19 Discrepancies in assessment were resolved by a third reviewer (VC). This instrument uses a point-based system to estimate the quality of a study by rating domains such as internal and external validity, bias, and confounding. In keeping with prior systematic reviews,^18,20,21 studies with a score of ≥18 were considered high quality. Interrater agreement for the adjudication of study quality was calculated using the Cohen κ statistic.

Eleven studies were conducted on adult hospitalized pa­tients ^{12-14,22-24,26,27,29,30,33} and included 3 randomized controlled studies.^14,27,33

Results by Outcomes Provider Identification Nine studies measured patients’ ability to identify providers with the use of visual aids, and all 9 reported improvements in this outcome. Visual tools used to measure provider identification included pictures (n = 5),^{13,14,23,27,33} whiteboards (n = 3),^12,22,30 and patient portals (n = 1).²⁶ Within studies that used pictures, individual pictures (n = 2)^13,23 and handouts with pictures of multiple providers (n = 3) were used.^14,27,33 In 2 studies, care team members such as a dietitian, physiotherapist or pharmacist, were included when measuring identification.^14,33

Understanding Providers’ RolesSix studies assessed the effect of visual tools on patients’ understanding of provider roles.^{13,14,22,26,27,33} Four studies reported a positive effect with the use of pictures,^27,33 whiteboards,²² and patient portals.²⁶ However, 2 studies reported either no difference or negative impressions. Appel et al.¹⁴ reported no difference in the understanding of physician roles using a handout of providers’ pictures and titles. Arora et al.¹³ used individual pictures of physicians with descriptions of roles and found a negative association, as demonstrated by fewer patients rating their understanding of physicians’ roles as excellent or very good in the intervention period (45.6%) compared with the baseline (55.3%).

 

Patient–Provider Communication

Three studies evaluated the influence of visual tools on communication.^14,24,29 Using pictures, Appel et al.¹⁴ found no difference in the perceived quality of communication. Singh et al.²⁹ used whiteboards and reported improved communication scores for physicians and nurses. With notepads, patients surveyed by Farberg et al.²⁴ stated that the tool improved provider communication.

Patient Satisfaction

Five studies assessed patient satisfaction related to the use of visual tools. ^{22,23,27,30,33} One study reported satisfaction as positive with the use of individual pictures.²³ Two studies that used handouts with pictures of all team members reported either a positive³³ or neutral²⁷ impact on satisfaction. Studies that used whiteboards reported a positive association with satisfaction^22,30 despite differences in content, such as the inclusion of prewritten prompts for writing goals of care and scheduled tests³⁰ versus the name of the nurse and their education level.²²

Results by Type of Visual Tool Pictures

Five studies that used pictures reported a positive effect on provider identification.^{13,14,23,27,33} Two^27,33 of 4 studies^13,14,27,33 that assessed patients’ understanding of team member roles reported a positive influence, while 1 reported no difference.¹⁴ A fourth study demonstrated a negative association, perhaps due to differences in the description of providers’ roles listed on the tool.¹³ Only 1 study examined the influence of pictures on patient–provider communication, and this study found no difference.¹⁴ Satisfaction with care via the use of pictures varied between positive (2 studies)^23,33 and neutral (1 study).²⁷

Whiteboards

Four studies tested the use of whiteboards; of these, 3 reported a positive influence on provider identification.^12,22,30 One study reported a positive impact on patient–provider communication.²⁹ Two studies noted a positive effect on patient satisfaction.^22,30 Notably, the responsibility for updating whiteboards differed between the studies (ie, nurses only²² vs residents, medical students, and nurses).³⁰

Patient Portal

In 1 study, an electronic portal that included names with pictures of providers, descriptions of their roles, lists of medications, and scheduled tests and/or procedures was used as a visual tool. The portal improved patients’ identification of physicians and patients’ understanding of roles. However, improvements in the knowledge of medication changes and planned tests and/or procedures during hospitalization were not observed.²⁶ This finding would suggest limitations in the hospitalized patient’s knowledge of the plan of care, which could potentially weaken patient–provider communication.

Notepads

Only 1 study assessed the use of formatted notepads on patient–provider communication and noted a positive association. Notepads used prompts for different categories (eg, diagnosis/treatment, medications, etc) to encourage patient questions for providers.²⁴

Five studies were conducted on hospitalized pediatric units.^{15,25,28,31,32} All studies surveyed the parents, guardians, or caregivers of pediatric patients. One study excluded patients ≥12 years of age because of legal differences in access to adolescent health information,³² while another interviewed parents and/or guardians of teenagers.¹⁵

Results by Outcomes Provider Identification and Understanding of Physicians’ Roles

Four studies that assessed the influence of visual tools on provider identification and understanding of roles reported a positive association.^15,25,28,31 Visual tools varied between pictures (n = 2),^15,31 patient portal (n = 1),²⁸ and whiteboards and pictures combined (n = 1).²⁵ The measurement of outcomes varied between surveys with free text responses,²⁸ multiple choice questions,²⁵ and 1-5 Likert scales.^15,31

Patient–Provider Communication

Two studies assessed the impact of patient portal use on communication and reported a positive association.^28,32 The 2 portals autopopulated names, pictures, and roles of providers from electronic medical records. Singh et al.²⁸ used a portal that was also available in Spanish and accommodated for non-English speakers. Kelly et al.³² reported that 90% of parents perceived that portal use was associated with reduced errors in care, with 8% finding errors in their child’s medication list.

Patient Satisfaction

Three studies assessed patient satisfaction via the use of visual tools.^15,28,31 Singh et al.²⁸ noted a positive influence on satisfaction via a patient portal. Dudas et al.¹⁵ used a single-page handout with names and pictures of each provider, along with information regarding the training and roles of each provider. Distribution of these handouts to patients by investigators led to a positive influence on satisfaction. While Unaka et al.³¹ used a similar handout, they asked residents to distribute them and found no significant difference in satisfaction scores between the intervention (66%) and control group (62%).

Results by Type of Visual Tool Pictures

Two studies reported a positive impact on provider identification and understanding of roles with the use of pictures.^15,31 Dudas et al.¹⁵ demonstrated a 4.8-fold increase in the odds of parents identifying a medical student, as compared with the control. Similarly, after adjusting for length of stay and prior hospitalization, Unaka et al.³¹ reported that a higher percentage of patients correctly identified providers using this approach.

Whiteboard and Picture

One study evaluated the simultaneous use of whiteboards and pictures to improve the identification of providers. The study noted improved identification of supervising doctors and increased recognition of roles for supervising doctors, residents, and medical students.²⁵

Patient Portal

Two studies used patient portals as visual tools. Singh et al.²⁸ assessed the use of a patient portal with names, roles, and pictures of treatment team members. Use of this tool was positively associated with provider identification, understanding of roles, communication, and satisfaction. Kelly et al.³² noted that 60% of parents felt that portal use improved healthcare team communication.

The risk of bias was assessed for both adult and pediatric studies in aggregate. The average risk of bias using the Downs and Black Scale was 17.81 (range 14-22, standard deviation [SD] 2.20). Of the 16 included studies, 9 were rated at a low risk of bias (score

• >

18).^13-15,26-31 Risk of bias was greatest for measures of external validity (mean 2.88, range 2-3, SD 0.34), internal validity (mean 4.06, range 3-6, SD 1.00), and confounding (mean 2.69, range 1-6, SD 1.35). Two of 3 randomized controlled trials had a low risk of bias.^14,27 Interrater reliability for study quality adjudication was 0.90, suggesting excellent agreement (see supplementary Appendix B).

In this systematic review, the effects of visual tools on outcomes, such as provider identification, understanding of roles, patient–provider communication, and satisfaction with care, were variable. The majority of included studies were conducted on adult patients (n = 11).^{12-14,22-24,26,27,29,30,33} Pictures were the most frequently used tool (n = 7)^{13-15,23,27,31,33} and consequently had the greatest sample size across the review (n = 1297). While pictures had a positive influence on provider identification in all studies, comprehension of provider roles and satisfaction were variable. Although the content of whiteboards varied between studies, they showed favorable effects on provider identification (3 of 4 studies)^12,22,30 and satisfaction (2 of 2 studies).^22,30 While electronic medical record-based tools had a positive influence on outcomes,^26,28 only 1 accounted for language preferences.²⁸ Formatted notepads positively influenced patient–provider communication, but their use was limited by literacy.²⁴ Collectively, these data suggest that visual tools have varying effects on patient-reported outcomes, likely owing to differences in study design, interventions, and evaluation methods.

Theoretically, visual tools should facilitate easier identification of providers and engender collaborative relationships. However, such tools do not replace face-to-face patient–provider and family discussions. Rather, these enhancements best serve as a medium to asynchronously display information to patients and family members. Indeed, within the included studies, we found that the use of visual tools was effective in improving satisfaction (6/8 studies), identification (13/13 studies), and understanding of provider roles (8/10 studies). Thus, it is reasonable to say that, in conjunction with excellent clinical care, these tools have an important role in improving care delivery in the hospital.

Despite this promise, we noted that the effectiveness of individual tools varied, a fact that may relate to differences across studies. First, inconsistencies in the format and/or content of the tools were noted. For example, within studies using pictures, tools varied from individual photographs of each team member^13,23 to 1-page handouts with pictures of all team members.^14,15,31 Such differences in presentation could affect spatial recognition in identifying providers, as single photos are known to be easier to process than multiple images at the same time.³⁴ Second, no study evaluated patient preference of a visual tool. Thus, personal preferences for pictures versus whiteboards versus electronic modalities or a combination of tools might affect outcomes. Additionally, the utility of visual tools in visually impaired, confused, or non-English-speaking patients may limit effectiveness. Future studies that address these aspects and account for patient preferences may better elucidate the role of visual tools in hospitals.

Our results should be considered in the context of several limitations. First, only 3 studies used randomized trial designs; thus, confounding from unmeasured variables inherent to observational designs is possible. Second, none of the interventions tested were blinded to providers, raising the possibility of a Hawthorne effect (ie, alteration of provider behavior in response to awareness of being observed).³⁵ Third, all studies were conducted at single centers, and only 9 of 16 studies were rated at a low risk of bias; thus, caution in broad extrapolations of this literature is necessary.

However, our study has several strengths, including a thorough search of heterogeneous literature, inclusion of both adult and pediatric populations, and a focus on myriad patient-reported outcomes. Second, by contrasting outcomes and measurement strategies across studies, our review helps explicate differences in results related to variation in outcome measurement or presentation of visual data. Third, because we frame results by outcome and type of visual tool used, we are able to identify strengths and weaknesses of individual tools in novel ways. Finally, our data suggest that the use of picture-based techniques and whiteboards are among the most promising visual interventions. Future studies that pair graphic designers with patients to improve the layout of these tools might prove valuable. Additionally, because the measurement of outcomes is confounded by aspects such as lack of controls, severity of illness, and language barriers, a randomized design would help provide greater clarity regarding effectiveness.

In conclusion, we found that visual tools appear to foster recognition of providers and understanding of their roles. However, variability of format, content, and measurement of outcomes hinders the identification of a single optimal approach. Future work using randomized controlled trial designs and standardized tools and measurements would be welcomed.

Acknowledgments

The authors thank Laura Appel, Kevin O’Leary, and Siddharth Singh for providing unpublished data and clarifications to help these analyses.

Disclosure

 Anupama Goyal is the guarantor. Anupama Goyal and Komalpreet Tur performed primary data abstraction and analysis. Anupama Goyal, Scott Flanders, Jason Mann, and Vineet Chopra drafted the manuscript. All authors contributed to the development of the selection criteria, the risk of bias assessment strategy, and the data extraction criteria. Anupama Goyal, Jason Mann, Whitney Townsend, and Vineet Chopra developed the search strategy. Vineet Chopra provided systematic review expertise. All authors read, provided feedback, and approved the final manuscript. The authors declare that they have no conflicts of interest.