Brief Reports

Pain management is an integral component of patient‐centered medical care and is a major concern for patients who are hospitalized.[1] Patient‐reported ratings of pain management are highly correlated with overall satisfaction with healthcare delivery.[2] Current research indicates that patient satisfaction with pain management may be improving[3]; however, there may be structural and county‐level disparities in these improvements in satisfaction. Although patient satisfaction with pain management increased from 2008 to 2012, a discrepancy in patient satisfaction with pain management has emerged between 3 different hospital systems (safety net, acute care, critical access hospitals)[3] Specifically, acute care hospitals provide less satisfactory pain management as compared to critical access hospitals.[3] Although patients' perception of pain management is an integral part of delivering patient‐centered care, prior research indicates that there may not be a simple inverse association between pain intensity score and patient satisfaction.[4] The management of pain in hospitals continues to be problematic, perhaps, for instance, due to discrepancies in understanding the relationship between patient satisfaction and pain management. Certainly for this reason and many others, satisfaction with pain management is now one of the dimensions assessed by the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey, which is a global measure of patient satisfaction.

The HCAHPS survey is utilized by 85% of all US‐based hospitals and gathers patient satisfaction information pertaining to 10 dimensions, including pain management. Patient satisfaction scores (via HCAHPS) now constitute 30% of Hospital Value‐Based Purchasing (HVBP), which makes up 2% of at‐risk reimbursements by the Centers for Medicare and Medicaid Services (CMS) as put forth by the Affordable Care Act (ACA) of 2010.[5] The ACA mandates that payments to hospitals must partly depend on metrics that assess patient satisfaction, as broadly measured by the HCAHPS, which are completed by patients upon hospital discharge.[5, 6] Therefore, patient satisfaction, as measured by patients, now directly affects CMS payments for over 3000 hospitals across the United States. This constitutes a large amount of money for most hospitals that operate on high revenue but have low profit margins. As such, the 2% at‐risk reimbursement may place many hospitals at financial risk that could be ameliorated with effective inpatient pain management.

In addition to its critical role in reimbursement to hospitals, patient satisfaction with pain management is also integrally related to providing patient‐centered care. As such, patient satisfaction with pain management is considered a critical element of various models of the patient‐centered approach to providing medical care. Although a medical inpatient team can assess objective signs of pain, patient‐centric pain measurements are paramount in understanding the pain experience of patients and providing adequate pain management care. Moreover, patients, doctors, payers of medical services, and now CMS increasingly regard a patient‐centered approach to medical care as crucial for the delivery of high‐quality care.

HCAHPS survey sampling represents an excellent opportunity to help assess current gaps in patient‐centered clinical care. However, ecological factors, such as county‐level demographics and hospital size (eg, bed number), are known to influence health outcomes but have not been adequately studied in pain management patient satisfaction.[7] Hospital and county‐level factors may influence the degree to which patients experience patient‐centered pain management care. For instance, most patient satisfaction scores are worse in urban areas.[8, 9] These disparities in patient satisfaction scores could be associated with population density, greater ethnic diversity or nonEnglish‐speaking individuals, or number of hospital beds.

The US Census demographics and hospital‐bed number provide a concurrent measure that can be used across the country to estimate hospital ecology. This study evaluated the influence of county‐level demographic and structural factors (ie, hospital beds) on patient satisfaction with hospital pain management in all HCAHPS‐participating hospitals across the United States. We hypothesized that demographic diversity, higher population density, and higher numbers of hospital beds would predict lower levels of patient satisfaction with inpatient pain management.

METHODS

RESULTS

Complete HCAHPS scores were obtained from 3907 hospitals out of a total of 4621 US hospitals (85%). The majority of hospitals (73.8%, n = 2884) collected over 300 surveys, fewer (n = 696) collected 100 to 299 surveys, and a small number of hospitals (n = 327) collected less than 100 surveys. Based on the most conservative estimate, results were available from at least 934,800 individual surveys. Missing HCAHPS hospital data averaged 13.4 (standard deviation [SD] = 12.2) hospitals per state. County‐level data were obtained from all 3144 county or county equivalents across the United States (100%).

DISCUSSION

By utilizing county‐level demographic data and the HCAHPS survey measures from across the United States, this study provides a representative sample of US hospitals that can be used to define ecological trends in patient satisfaction with pain management. This statistical model demonstrates the nonrandom variability of pain management satisfaction across the United States, even after CMS patient‐mix adjustment. Although the quality of pain management may be increasing by some reports, our present results indicate that pain management satisfaction is not equitable with the rest of the country among select groups of patients (eg, foreign born, female gender, areas of long travel times to work) or in certain care settings (eg, larger hospitals, population dense areas). These data suggest that areas of pain management may lack in quality compared to pain management across the entire US as a whole. This is consistent with the increasingly recognized contribution of multiple nonmedical determinates to health outcomes.[12] These results demonstrate the overall magnitude of healthcare disparity in the United States, and are particularly concerning because African Americans and Hispanics tend to rate overall satisfaction higher than Caucasians in other studies.[13, 14] The same minority reporting bias may be reflected in HCAHPS results. These patients may be reporting higher pain management satisfaction that is not consistent with the level of care they received, as studies have consistently indicated worse pain management delivery for racial and ethnic minorities.[15]

The present findings reveal structural (eg, hospital beds) and demographic (eg, population density, foreign born) gaps in satisfaction with pain management. An effort to improve pain management for all people in the heterogeneous makeup of the United States is an enormous challenge. However, change may be forthcoming, as Hospital Value‐Based Purchasing draws attention pain practice inequities in real time. Although several of the significant explanatory variables cannot be modified (eg, size of hospital, urban setting, patients served), pain management delivery should receive extra attention in hospitals with those characteristics. Pain management delivery in large, urban hospitals that serve foreign‐born patients may be improved with focused multilevel interventions. Future research should examine these inequities further and develop multilevel interventions that target hospitals in at‐risk areas with the aim of lessening disparities in hospital‐based pain management.

Pain management is an integral component of patient‐centered medical care and is a major concern for patients who are hospitalized.[1] Patient‐reported ratings of pain management are highly correlated with overall satisfaction with healthcare delivery.[2] Current research indicates that patient satisfaction with pain management may be improving[3]; however, there may be structural and county‐level disparities in these improvements in satisfaction. Although patient satisfaction with pain management increased from 2008 to 2012, a discrepancy in patient satisfaction with pain management has emerged between 3 different hospital systems (safety net, acute care, critical access hospitals)[3] Specifically, acute care hospitals provide less satisfactory pain management as compared to critical access hospitals.[3] Although patients' perception of pain management is an integral part of delivering patient‐centered care, prior research indicates that there may not be a simple inverse association between pain intensity score and patient satisfaction.[4] The management of pain in hospitals continues to be problematic, perhaps, for instance, due to discrepancies in understanding the relationship between patient satisfaction and pain management. Certainly for this reason and many others, satisfaction with pain management is now one of the dimensions assessed by the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey, which is a global measure of patient satisfaction.

The HCAHPS survey is utilized by 85% of all US‐based hospitals and gathers patient satisfaction information pertaining to 10 dimensions, including pain management. Patient satisfaction scores (via HCAHPS) now constitute 30% of Hospital Value‐Based Purchasing (HVBP), which makes up 2% of at‐risk reimbursements by the Centers for Medicare and Medicaid Services (CMS) as put forth by the Affordable Care Act (ACA) of 2010.[5] The ACA mandates that payments to hospitals must partly depend on metrics that assess patient satisfaction, as broadly measured by the HCAHPS, which are completed by patients upon hospital discharge.[5, 6] Therefore, patient satisfaction, as measured by patients, now directly affects CMS payments for over 3000 hospitals across the United States. This constitutes a large amount of money for most hospitals that operate on high revenue but have low profit margins. As such, the 2% at‐risk reimbursement may place many hospitals at financial risk that could be ameliorated with effective inpatient pain management.

In addition to its critical role in reimbursement to hospitals, patient satisfaction with pain management is also integrally related to providing patient‐centered care. As such, patient satisfaction with pain management is considered a critical element of various models of the patient‐centered approach to providing medical care. Although a medical inpatient team can assess objective signs of pain, patient‐centric pain measurements are paramount in understanding the pain experience of patients and providing adequate pain management care. Moreover, patients, doctors, payers of medical services, and now CMS increasingly regard a patient‐centered approach to medical care as crucial for the delivery of high‐quality care.

HCAHPS survey sampling represents an excellent opportunity to help assess current gaps in patient‐centered clinical care. However, ecological factors, such as county‐level demographics and hospital size (eg, bed number), are known to influence health outcomes but have not been adequately studied in pain management patient satisfaction.[7] Hospital and county‐level factors may influence the degree to which patients experience patient‐centered pain management care. For instance, most patient satisfaction scores are worse in urban areas.[8, 9] These disparities in patient satisfaction scores could be associated with population density, greater ethnic diversity or nonEnglish‐speaking individuals, or number of hospital beds.

The US Census demographics and hospital‐bed number provide a concurrent measure that can be used across the country to estimate hospital ecology. This study evaluated the influence of county‐level demographic and structural factors (ie, hospital beds) on patient satisfaction with hospital pain management in all HCAHPS‐participating hospitals across the United States. We hypothesized that demographic diversity, higher population density, and higher numbers of hospital beds would predict lower levels of patient satisfaction with inpatient pain management.

METHODS

RESULTS

Complete HCAHPS scores were obtained from 3907 hospitals out of a total of 4621 US hospitals (85%). The majority of hospitals (73.8%, n = 2884) collected over 300 surveys, fewer (n = 696) collected 100 to 299 surveys, and a small number of hospitals (n = 327) collected less than 100 surveys. Based on the most conservative estimate, results were available from at least 934,800 individual surveys. Missing HCAHPS hospital data averaged 13.4 (standard deviation [SD] = 12.2) hospitals per state. County‐level data were obtained from all 3144 county or county equivalents across the United States (100%).

DISCUSSION

By utilizing county‐level demographic data and the HCAHPS survey measures from across the United States, this study provides a representative sample of US hospitals that can be used to define ecological trends in patient satisfaction with pain management. This statistical model demonstrates the nonrandom variability of pain management satisfaction across the United States, even after CMS patient‐mix adjustment. Although the quality of pain management may be increasing by some reports, our present results indicate that pain management satisfaction is not equitable with the rest of the country among select groups of patients (eg, foreign born, female gender, areas of long travel times to work) or in certain care settings (eg, larger hospitals, population dense areas). These data suggest that areas of pain management may lack in quality compared to pain management across the entire US as a whole. This is consistent with the increasingly recognized contribution of multiple nonmedical determinates to health outcomes.[12] These results demonstrate the overall magnitude of healthcare disparity in the United States, and are particularly concerning because African Americans and Hispanics tend to rate overall satisfaction higher than Caucasians in other studies.[13, 14] The same minority reporting bias may be reflected in HCAHPS results. These patients may be reporting higher pain management satisfaction that is not consistent with the level of care they received, as studies have consistently indicated worse pain management delivery for racial and ethnic minorities.[15]

The present findings reveal structural (eg, hospital beds) and demographic (eg, population density, foreign born) gaps in satisfaction with pain management. An effort to improve pain management for all people in the heterogeneous makeup of the United States is an enormous challenge. However, change may be forthcoming, as Hospital Value‐Based Purchasing draws attention pain practice inequities in real time. Although several of the significant explanatory variables cannot be modified (eg, size of hospital, urban setting, patients served), pain management delivery should receive extra attention in hospitals with those characteristics. Pain management delivery in large, urban hospitals that serve foreign‐born patients may be improved with focused multilevel interventions. Future research should examine these inequities further and develop multilevel interventions that target hospitals in at‐risk areas with the aim of lessening disparities in hospital‐based pain management.

Pain management is an integral component of patient‐centered medical care and is a major concern for patients who are hospitalized.[1] Patient‐reported ratings of pain management are highly correlated with overall satisfaction with healthcare delivery.[2] Current research indicates that patient satisfaction with pain management may be improving[3]; however, there may be structural and county‐level disparities in these improvements in satisfaction. Although patient satisfaction with pain management increased from 2008 to 2012, a discrepancy in patient satisfaction with pain management has emerged between 3 different hospital systems (safety net, acute care, critical access hospitals)[3] Specifically, acute care hospitals provide less satisfactory pain management as compared to critical access hospitals.[3] Although patients' perception of pain management is an integral part of delivering patient‐centered care, prior research indicates that there may not be a simple inverse association between pain intensity score and patient satisfaction.[4] The management of pain in hospitals continues to be problematic, perhaps, for instance, due to discrepancies in understanding the relationship between patient satisfaction and pain management. Certainly for this reason and many others, satisfaction with pain management is now one of the dimensions assessed by the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey, which is a global measure of patient satisfaction.

The HCAHPS survey is utilized by 85% of all US‐based hospitals and gathers patient satisfaction information pertaining to 10 dimensions, including pain management. Patient satisfaction scores (via HCAHPS) now constitute 30% of Hospital Value‐Based Purchasing (HVBP), which makes up 2% of at‐risk reimbursements by the Centers for Medicare and Medicaid Services (CMS) as put forth by the Affordable Care Act (ACA) of 2010.[5] The ACA mandates that payments to hospitals must partly depend on metrics that assess patient satisfaction, as broadly measured by the HCAHPS, which are completed by patients upon hospital discharge.[5, 6] Therefore, patient satisfaction, as measured by patients, now directly affects CMS payments for over 3000 hospitals across the United States. This constitutes a large amount of money for most hospitals that operate on high revenue but have low profit margins. As such, the 2% at‐risk reimbursement may place many hospitals at financial risk that could be ameliorated with effective inpatient pain management.

In addition to its critical role in reimbursement to hospitals, patient satisfaction with pain management is also integrally related to providing patient‐centered care. As such, patient satisfaction with pain management is considered a critical element of various models of the patient‐centered approach to providing medical care. Although a medical inpatient team can assess objective signs of pain, patient‐centric pain measurements are paramount in understanding the pain experience of patients and providing adequate pain management care. Moreover, patients, doctors, payers of medical services, and now CMS increasingly regard a patient‐centered approach to medical care as crucial for the delivery of high‐quality care.

HCAHPS survey sampling represents an excellent opportunity to help assess current gaps in patient‐centered clinical care. However, ecological factors, such as county‐level demographics and hospital size (eg, bed number), are known to influence health outcomes but have not been adequately studied in pain management patient satisfaction.[7] Hospital and county‐level factors may influence the degree to which patients experience patient‐centered pain management care. For instance, most patient satisfaction scores are worse in urban areas.[8, 9] These disparities in patient satisfaction scores could be associated with population density, greater ethnic diversity or nonEnglish‐speaking individuals, or number of hospital beds.

The US Census demographics and hospital‐bed number provide a concurrent measure that can be used across the country to estimate hospital ecology. This study evaluated the influence of county‐level demographic and structural factors (ie, hospital beds) on patient satisfaction with hospital pain management in all HCAHPS‐participating hospitals across the United States. We hypothesized that demographic diversity, higher population density, and higher numbers of hospital beds would predict lower levels of patient satisfaction with inpatient pain management.

METHODS

RESULTS

Complete HCAHPS scores were obtained from 3907 hospitals out of a total of 4621 US hospitals (85%). The majority of hospitals (73.8%, n = 2884) collected over 300 surveys, fewer (n = 696) collected 100 to 299 surveys, and a small number of hospitals (n = 327) collected less than 100 surveys. Based on the most conservative estimate, results were available from at least 934,800 individual surveys. Missing HCAHPS hospital data averaged 13.4 (standard deviation [SD] = 12.2) hospitals per state. County‐level data were obtained from all 3144 county or county equivalents across the United States (100%).

DISCUSSION

By utilizing county‐level demographic data and the HCAHPS survey measures from across the United States, this study provides a representative sample of US hospitals that can be used to define ecological trends in patient satisfaction with pain management. This statistical model demonstrates the nonrandom variability of pain management satisfaction across the United States, even after CMS patient‐mix adjustment. Although the quality of pain management may be increasing by some reports, our present results indicate that pain management satisfaction is not equitable with the rest of the country among select groups of patients (eg, foreign born, female gender, areas of long travel times to work) or in certain care settings (eg, larger hospitals, population dense areas). These data suggest that areas of pain management may lack in quality compared to pain management across the entire US as a whole. This is consistent with the increasingly recognized contribution of multiple nonmedical determinates to health outcomes.[12] These results demonstrate the overall magnitude of healthcare disparity in the United States, and are particularly concerning because African Americans and Hispanics tend to rate overall satisfaction higher than Caucasians in other studies.[13, 14] The same minority reporting bias may be reflected in HCAHPS results. These patients may be reporting higher pain management satisfaction that is not consistent with the level of care they received, as studies have consistently indicated worse pain management delivery for racial and ethnic minorities.[15]

The present findings reveal structural (eg, hospital beds) and demographic (eg, population density, foreign born) gaps in satisfaction with pain management. An effort to improve pain management for all people in the heterogeneous makeup of the United States is an enormous challenge. However, change may be forthcoming, as Hospital Value‐Based Purchasing draws attention pain practice inequities in real time. Although several of the significant explanatory variables cannot be modified (eg, size of hospital, urban setting, patients served), pain management delivery should receive extra attention in hospitals with those characteristics. Pain management delivery in large, urban hospitals that serve foreign‐born patients may be improved with focused multilevel interventions. Future research should examine these inequities further and develop multilevel interventions that target hospitals in at‐risk areas with the aim of lessening disparities in hospital‐based pain management.

Delirium is a rapidly developing, fluctuating disturbance in consciousness, caused by a medical condition. The diagnosis of delirium is often missed, potentiating negative outcomes.[1, 2] Regular delirium screening by nurses results in increased recognition and treatment.[3] Although multiple screening tools exist, many are cumbersome to execute. Efforts have been made to shorten them, but although the screening tools may predict adverse outcomes, there are concerns about their specificity.[1, 2, 4, 5, 6] The Delirium Observation Screening Scale[7] (DOS) is a brief screening tool based on observation. It has been validated in several patient populations, but no published studies have taken place in the United States or have focused on an older, general medicine, inpatient population. Given the low numbers of patients in earlier validation studies, the effectiveness of the DOS for screening hospitalized, older patients is not yet fully established.

This study aimed to determine the ability of the DOS to screen hospitalized, older patients for delirium compared to a validated delirium diagnostic tool, the Delirium Rating Scale‐Revised‐98 (DRS‐R‐98).[8] In addition, DOS acceptability, ease of use, and benefit were explored by surveying nurses.

METHODS

RESULTS

Logistic Regression Models

All models confirmed that positive DOS screens significantly predicted delirium. The traditional logistic regression model produced an odds ratio (OR) estimate of 92 (95% CI: 10‐824, P < 0.0001) for a positive DOS screen predicting delirium. The marginal logistic regression model accounting for repeated measures produced a consistent estimate (OR: 93, 95% CI: 11‐800, P < 0.0001). Continuous DOS scores predicted delirium (OR: 2.1, 95% CI: 1.5‐2.9, P < 0.0001), and the ROC curve supported the cutoff of DOS 3, corresponding to a predicted probability of 0.12 (Figure 1).

Figure 1

DISCUSSION

This study demonstrated the effectiveness, efficiency, and ease of use of the DOS as a delirium screening tool. The DOS exhibited high sensitivity (90%) and specificity (91%). Similar to previous findings, the positive predictive value was only 53%, but the negative predictive value was 99%.[12] These results support that the DOS is consistently able to rule out delirium, with only 1 false negative in this study.

Nursing responses regarding user‐friendliness are consistent with other studies; however, there was a knowledge gap related to how positive delirium screens can inform and change care for patients.[7] Education is a known barrier to integrating delirium screening tools secondary to the need for regular and extensive education, frequent reminders to screen, and regular evaluations of assessment quality.[11, 13, 14, 15] Developing guidelines for responding to positive DOS screens and documenting its impact on care may incentivize use.

Study strengths include strong evaluator consistency, blinding of evaluator and nurses, and responses from a broad range of nurses (14 of 16 units represented). Additionally, this study demonstrated the efficacy and ease of use of an EMR‐prompted delirium screen. However, this study had several limitations, including a small sample size and a low incidence of delirium. The lower incidence is likely secondary to selection bias that resulted from difficulty consenting delirious subjects. The discordant time between DOS and DRS‐R‐98 assessments may have also influenced results; however, inclusion of data from the previous 8 to 24 hours in both tools makes the temporal separation of assessments less impactful.

The ability of the DOS to accurately identify patients at high risk of delirium is useful for healthcare staff. Future work will include nurse and physician education to emphasize delirium understanding, the importance of regular screening, and the use of nonpharmacological interventions. Additional studies will include examination of the interventions and outcomes of patients who screen positive for delirium to determine the long‐term impact of delirium screening.

Delirium is a rapidly developing, fluctuating disturbance in consciousness, caused by a medical condition. The diagnosis of delirium is often missed, potentiating negative outcomes.[1, 2] Regular delirium screening by nurses results in increased recognition and treatment.[3] Although multiple screening tools exist, many are cumbersome to execute. Efforts have been made to shorten them, but although the screening tools may predict adverse outcomes, there are concerns about their specificity.[1, 2, 4, 5, 6] The Delirium Observation Screening Scale[7] (DOS) is a brief screening tool based on observation. It has been validated in several patient populations, but no published studies have taken place in the United States or have focused on an older, general medicine, inpatient population. Given the low numbers of patients in earlier validation studies, the effectiveness of the DOS for screening hospitalized, older patients is not yet fully established.

This study aimed to determine the ability of the DOS to screen hospitalized, older patients for delirium compared to a validated delirium diagnostic tool, the Delirium Rating Scale‐Revised‐98 (DRS‐R‐98).[8] In addition, DOS acceptability, ease of use, and benefit were explored by surveying nurses.

METHODS

RESULTS

Logistic Regression Models

All models confirmed that positive DOS screens significantly predicted delirium. The traditional logistic regression model produced an odds ratio (OR) estimate of 92 (95% CI: 10‐824, P < 0.0001) for a positive DOS screen predicting delirium. The marginal logistic regression model accounting for repeated measures produced a consistent estimate (OR: 93, 95% CI: 11‐800, P < 0.0001). Continuous DOS scores predicted delirium (OR: 2.1, 95% CI: 1.5‐2.9, P < 0.0001), and the ROC curve supported the cutoff of DOS 3, corresponding to a predicted probability of 0.12 (Figure 1).

Figure 1

DISCUSSION

This study demonstrated the effectiveness, efficiency, and ease of use of the DOS as a delirium screening tool. The DOS exhibited high sensitivity (90%) and specificity (91%). Similar to previous findings, the positive predictive value was only 53%, but the negative predictive value was 99%.[12] These results support that the DOS is consistently able to rule out delirium, with only 1 false negative in this study.

Nursing responses regarding user‐friendliness are consistent with other studies; however, there was a knowledge gap related to how positive delirium screens can inform and change care for patients.[7] Education is a known barrier to integrating delirium screening tools secondary to the need for regular and extensive education, frequent reminders to screen, and regular evaluations of assessment quality.[11, 13, 14, 15] Developing guidelines for responding to positive DOS screens and documenting its impact on care may incentivize use.

Study strengths include strong evaluator consistency, blinding of evaluator and nurses, and responses from a broad range of nurses (14 of 16 units represented). Additionally, this study demonstrated the efficacy and ease of use of an EMR‐prompted delirium screen. However, this study had several limitations, including a small sample size and a low incidence of delirium. The lower incidence is likely secondary to selection bias that resulted from difficulty consenting delirious subjects. The discordant time between DOS and DRS‐R‐98 assessments may have also influenced results; however, inclusion of data from the previous 8 to 24 hours in both tools makes the temporal separation of assessments less impactful.

The ability of the DOS to accurately identify patients at high risk of delirium is useful for healthcare staff. Future work will include nurse and physician education to emphasize delirium understanding, the importance of regular screening, and the use of nonpharmacological interventions. Additional studies will include examination of the interventions and outcomes of patients who screen positive for delirium to determine the long‐term impact of delirium screening.

Delirium is a rapidly developing, fluctuating disturbance in consciousness, caused by a medical condition. The diagnosis of delirium is often missed, potentiating negative outcomes.[1, 2] Regular delirium screening by nurses results in increased recognition and treatment.[3] Although multiple screening tools exist, many are cumbersome to execute. Efforts have been made to shorten them, but although the screening tools may predict adverse outcomes, there are concerns about their specificity.[1, 2, 4, 5, 6] The Delirium Observation Screening Scale[7] (DOS) is a brief screening tool based on observation. It has been validated in several patient populations, but no published studies have taken place in the United States or have focused on an older, general medicine, inpatient population. Given the low numbers of patients in earlier validation studies, the effectiveness of the DOS for screening hospitalized, older patients is not yet fully established.

This study aimed to determine the ability of the DOS to screen hospitalized, older patients for delirium compared to a validated delirium diagnostic tool, the Delirium Rating Scale‐Revised‐98 (DRS‐R‐98).[8] In addition, DOS acceptability, ease of use, and benefit were explored by surveying nurses.

METHODS

RESULTS

Logistic Regression Models

All models confirmed that positive DOS screens significantly predicted delirium. The traditional logistic regression model produced an odds ratio (OR) estimate of 92 (95% CI: 10‐824, P < 0.0001) for a positive DOS screen predicting delirium. The marginal logistic regression model accounting for repeated measures produced a consistent estimate (OR: 93, 95% CI: 11‐800, P < 0.0001). Continuous DOS scores predicted delirium (OR: 2.1, 95% CI: 1.5‐2.9, P < 0.0001), and the ROC curve supported the cutoff of DOS 3, corresponding to a predicted probability of 0.12 (Figure 1).

Figure 1

DISCUSSION

This study demonstrated the effectiveness, efficiency, and ease of use of the DOS as a delirium screening tool. The DOS exhibited high sensitivity (90%) and specificity (91%). Similar to previous findings, the positive predictive value was only 53%, but the negative predictive value was 99%.[12] These results support that the DOS is consistently able to rule out delirium, with only 1 false negative in this study.

Nursing responses regarding user‐friendliness are consistent with other studies; however, there was a knowledge gap related to how positive delirium screens can inform and change care for patients.[7] Education is a known barrier to integrating delirium screening tools secondary to the need for regular and extensive education, frequent reminders to screen, and regular evaluations of assessment quality.[11, 13, 14, 15] Developing guidelines for responding to positive DOS screens and documenting its impact on care may incentivize use.

Study strengths include strong evaluator consistency, blinding of evaluator and nurses, and responses from a broad range of nurses (14 of 16 units represented). Additionally, this study demonstrated the efficacy and ease of use of an EMR‐prompted delirium screen. However, this study had several limitations, including a small sample size and a low incidence of delirium. The lower incidence is likely secondary to selection bias that resulted from difficulty consenting delirious subjects. The discordant time between DOS and DRS‐R‐98 assessments may have also influenced results; however, inclusion of data from the previous 8 to 24 hours in both tools makes the temporal separation of assessments less impactful.

The ability of the DOS to accurately identify patients at high risk of delirium is useful for healthcare staff. Future work will include nurse and physician education to emphasize delirium understanding, the importance of regular screening, and the use of nonpharmacological interventions. Additional studies will include examination of the interventions and outcomes of patients who screen positive for delirium to determine the long‐term impact of delirium screening.

Superficial thrombophlebitis (SVTE), inflammation of superficial veins associated with thrombosis, is a painful condition, and 3% to 11% of the population will develop SVTE during their lifetime. Although generally considered a benign, self‐limited disease, it can cause considerable discomfort, impact mobility, and lead to further complications. Recent and accumulating evidence suggests that it is often associated with more serious forms of venous thromboembolism (VTE), including deep vein thrombosis (DVT) and pulmonary embolism (PE),[1] and SVTE is a strong risk factor for subsequent DVT or PE.[2, 3]

There is no clear consensus on the optimal treatment of SVTE. Although antithrombotic medications such as fondaparinux may be more effective than placebo in reducing the risk of subsequent DVT,[4] the evidence is generally of low grade, and the costs and inconveniences of anticoagulant therapy are not inconsequential.[1, 5, 6] Surveys suggest that physician opinions on the appropriate management of SVTE vary significantly, and management includes nonsteroidal anti‐inflammatory drugs (NSAIDs), topical therapies, or watchful waiting.[7] The objective of our study was to describe the initial management of SVTE in a community‐based population and examine subsequent rates of diagnosed DVT or PE in the following year.

MATERIALS AND METHODS

This was a retrospective, observational study seeking to describe the initial treatment for patients diagnosed with isolated SVTE.

RESULTS

Out of 930 patients with a diagnosis code for venous thrombosis and who underwent chart review, we identified 329 individuals who were considered by reviewers to have isolated SVTE events. Most SVTEs were of the lower extremity (60.8%) and diagnosed in an outpatient or emergency department setting (91.8%). Risk factors for SVTE were common, including documented varicose veins, recent peripheral venous catheterization or injection, or antecedent hospitalization (Table 1).

Initial treatment strategies for the 329 patients are presented in Table 2. Few patients with SVTE received anticoagulants for initial treatment, although patients with lower extremity SVTE were more likely to receive antithrombotic therapy compared to patients with SVTE of other locations (P < 0.001). None of the identified risk factors for thrombosis were statistically significantly associated with a greater likelihood of receiving anticoagulants (P > 0.05 for all).

In the 12 months after SVTE, 19 (5.8%) patients had a diagnosis encounter for VTE associated with a prescription for either warfarin or parenteral anticoagulant. Of the 200 patients in our study with lower extremity SVTE, 15 (7.5%) had a subsequent VTE diagnosis associated with anticoagulation prescription in the following year.

DISCUSSION

Clinically significant VTE within a year after SVTE diagnosis was uncommon in our study despite infrequent use of antithrombotic therapy. Although recommendations for the initial treatment of SVTE have evolved in more recent years to support the use of fondaparinux in selected patients, there are significant costs and inconveniences associated with anticoagulation therapy and debate among physicians about the preferred treatment.[7] The low rate of anticoagulant use in our study may be related to the years studied (before guidelines supported fondaparinux), as well as being largely comprised of outpatients, and also because we included types of SVTE that are unlikely to progress to DVT, such as small vein phlebitis or upper extremity SVTE.[4, 10]

Limitations of our analysis include the heterogeneous types of SVTE included in our study and our reliance on available chart documentation to ascertain SVTE diagnosis, risk factors, and treatment. Because of the observational nature of our study, SVTE in the hospital setting may have been less well documented in medical records, leading to a sample of mostly outpatients. Hence, our observed subsequent VTE rate may not be generalizable to a more inclusive population. Finally, the low rate of anticoagulant treatment and VTE diagnoses limited our ability to conduct multivariable modeling.

In conclusion, clinically significant VTE within a year after SVTE was uncommon in our study despite infrequent use of antithrombotic therapy. Although our data are observational, they suggest that not all patients may require anticoagulation for the management of SVTE, and that further investigation into defining which populations would most benefit from treatment with fondaparinux or other agents is warranted.

Superficial thrombophlebitis (SVTE), inflammation of superficial veins associated with thrombosis, is a painful condition, and 3% to 11% of the population will develop SVTE during their lifetime. Although generally considered a benign, self‐limited disease, it can cause considerable discomfort, impact mobility, and lead to further complications. Recent and accumulating evidence suggests that it is often associated with more serious forms of venous thromboembolism (VTE), including deep vein thrombosis (DVT) and pulmonary embolism (PE),[1] and SVTE is a strong risk factor for subsequent DVT or PE.[2, 3]

There is no clear consensus on the optimal treatment of SVTE. Although antithrombotic medications such as fondaparinux may be more effective than placebo in reducing the risk of subsequent DVT,[4] the evidence is generally of low grade, and the costs and inconveniences of anticoagulant therapy are not inconsequential.[1, 5, 6] Surveys suggest that physician opinions on the appropriate management of SVTE vary significantly, and management includes nonsteroidal anti‐inflammatory drugs (NSAIDs), topical therapies, or watchful waiting.[7] The objective of our study was to describe the initial management of SVTE in a community‐based population and examine subsequent rates of diagnosed DVT or PE in the following year.

MATERIALS AND METHODS

This was a retrospective, observational study seeking to describe the initial treatment for patients diagnosed with isolated SVTE.

RESULTS

Out of 930 patients with a diagnosis code for venous thrombosis and who underwent chart review, we identified 329 individuals who were considered by reviewers to have isolated SVTE events. Most SVTEs were of the lower extremity (60.8%) and diagnosed in an outpatient or emergency department setting (91.8%). Risk factors for SVTE were common, including documented varicose veins, recent peripheral venous catheterization or injection, or antecedent hospitalization (Table 1).

Initial treatment strategies for the 329 patients are presented in Table 2. Few patients with SVTE received anticoagulants for initial treatment, although patients with lower extremity SVTE were more likely to receive antithrombotic therapy compared to patients with SVTE of other locations (P < 0.001). None of the identified risk factors for thrombosis were statistically significantly associated with a greater likelihood of receiving anticoagulants (P > 0.05 for all).

In the 12 months after SVTE, 19 (5.8%) patients had a diagnosis encounter for VTE associated with a prescription for either warfarin or parenteral anticoagulant. Of the 200 patients in our study with lower extremity SVTE, 15 (7.5%) had a subsequent VTE diagnosis associated with anticoagulation prescription in the following year.

DISCUSSION

Clinically significant VTE within a year after SVTE diagnosis was uncommon in our study despite infrequent use of antithrombotic therapy. Although recommendations for the initial treatment of SVTE have evolved in more recent years to support the use of fondaparinux in selected patients, there are significant costs and inconveniences associated with anticoagulation therapy and debate among physicians about the preferred treatment.[7] The low rate of anticoagulant use in our study may be related to the years studied (before guidelines supported fondaparinux), as well as being largely comprised of outpatients, and also because we included types of SVTE that are unlikely to progress to DVT, such as small vein phlebitis or upper extremity SVTE.[4, 10]

Limitations of our analysis include the heterogeneous types of SVTE included in our study and our reliance on available chart documentation to ascertain SVTE diagnosis, risk factors, and treatment. Because of the observational nature of our study, SVTE in the hospital setting may have been less well documented in medical records, leading to a sample of mostly outpatients. Hence, our observed subsequent VTE rate may not be generalizable to a more inclusive population. Finally, the low rate of anticoagulant treatment and VTE diagnoses limited our ability to conduct multivariable modeling.

In conclusion, clinically significant VTE within a year after SVTE was uncommon in our study despite infrequent use of antithrombotic therapy. Although our data are observational, they suggest that not all patients may require anticoagulation for the management of SVTE, and that further investigation into defining which populations would most benefit from treatment with fondaparinux or other agents is warranted.

Superficial thrombophlebitis (SVTE), inflammation of superficial veins associated with thrombosis, is a painful condition, and 3% to 11% of the population will develop SVTE during their lifetime. Although generally considered a benign, self‐limited disease, it can cause considerable discomfort, impact mobility, and lead to further complications. Recent and accumulating evidence suggests that it is often associated with more serious forms of venous thromboembolism (VTE), including deep vein thrombosis (DVT) and pulmonary embolism (PE),[1] and SVTE is a strong risk factor for subsequent DVT or PE.[2, 3]

There is no clear consensus on the optimal treatment of SVTE. Although antithrombotic medications such as fondaparinux may be more effective than placebo in reducing the risk of subsequent DVT,[4] the evidence is generally of low grade, and the costs and inconveniences of anticoagulant therapy are not inconsequential.[1, 5, 6] Surveys suggest that physician opinions on the appropriate management of SVTE vary significantly, and management includes nonsteroidal anti‐inflammatory drugs (NSAIDs), topical therapies, or watchful waiting.[7] The objective of our study was to describe the initial management of SVTE in a community‐based population and examine subsequent rates of diagnosed DVT or PE in the following year.

MATERIALS AND METHODS

This was a retrospective, observational study seeking to describe the initial treatment for patients diagnosed with isolated SVTE.

RESULTS

Out of 930 patients with a diagnosis code for venous thrombosis and who underwent chart review, we identified 329 individuals who were considered by reviewers to have isolated SVTE events. Most SVTEs were of the lower extremity (60.8%) and diagnosed in an outpatient or emergency department setting (91.8%). Risk factors for SVTE were common, including documented varicose veins, recent peripheral venous catheterization or injection, or antecedent hospitalization (Table 1).

Initial treatment strategies for the 329 patients are presented in Table 2. Few patients with SVTE received anticoagulants for initial treatment, although patients with lower extremity SVTE were more likely to receive antithrombotic therapy compared to patients with SVTE of other locations (P < 0.001). None of the identified risk factors for thrombosis were statistically significantly associated with a greater likelihood of receiving anticoagulants (P > 0.05 for all).

In the 12 months after SVTE, 19 (5.8%) patients had a diagnosis encounter for VTE associated with a prescription for either warfarin or parenteral anticoagulant. Of the 200 patients in our study with lower extremity SVTE, 15 (7.5%) had a subsequent VTE diagnosis associated with anticoagulation prescription in the following year.

DISCUSSION

Clinically significant VTE within a year after SVTE diagnosis was uncommon in our study despite infrequent use of antithrombotic therapy. Although recommendations for the initial treatment of SVTE have evolved in more recent years to support the use of fondaparinux in selected patients, there are significant costs and inconveniences associated with anticoagulation therapy and debate among physicians about the preferred treatment.[7] The low rate of anticoagulant use in our study may be related to the years studied (before guidelines supported fondaparinux), as well as being largely comprised of outpatients, and also because we included types of SVTE that are unlikely to progress to DVT, such as small vein phlebitis or upper extremity SVTE.[4, 10]

Limitations of our analysis include the heterogeneous types of SVTE included in our study and our reliance on available chart documentation to ascertain SVTE diagnosis, risk factors, and treatment. Because of the observational nature of our study, SVTE in the hospital setting may have been less well documented in medical records, leading to a sample of mostly outpatients. Hence, our observed subsequent VTE rate may not be generalizable to a more inclusive population. Finally, the low rate of anticoagulant treatment and VTE diagnoses limited our ability to conduct multivariable modeling.

In conclusion, clinically significant VTE within a year after SVTE was uncommon in our study despite infrequent use of antithrombotic therapy. Although our data are observational, they suggest that not all patients may require anticoagulation for the management of SVTE, and that further investigation into defining which populations would most benefit from treatment with fondaparinux or other agents is warranted.

There is uncertainty regarding older adults' attitudes toward participating in group exercise. Although some evidence suggests that in the community, older adults prefer to exercise alone with some instruction,[1, 2] others support the preference of group exercise with peers.[3] Little is known about the attitudes of hospitalized older adults toward group physiotherapy (GPT). Providing physiotherapy (also known as physical therapy) in a group setting has been shown to be effective in a variety of populations,[4, 5, 6, 7] and as a consequence of simultaneously treating multiple patients, therapist[8] and cost[9] efficiency are enhanced. Description of the patient experience is increasingly being recognized as a crucial element in the delivery of patient‐centered care and performance evaluation of health professionals and services.[10] Therefore, the purpose of this investigation was to explore older inpatients' experiences of GPT to assist with planning and designing future inpatient programs to maximize patient participation, satisfaction, and clinical outcomes.

METHODS

RESULTS

Eight females and 4 males aged 73 to 93 years (mean = 82.5 years, standard deviation = 7.1 years) participated in the interviews. After initially consenting to participate, 1 participant declined due to fatigue. Three participants were discharged prior to scheduling an interview. Analysis revealed 6 major themes and 10 subthemes (Table 2).

DISCUSSION

Participants were positive about GPT and reported experiencing physical benefits. Motivation was reported as an important factor in recovery, with improving mobility and competition as commonly described extrinsic motivators. Social comparisons made between participants were motivating and reassuring.

Group physiotherapy sessions are often a replacement for individual physiotherapy; therefore, it is important that participants feel they are receiving a suitable alternative. Individual physiotherapy has advantages over GPT including affording a more individualized assessment and treatment; a combination of both may be appropriate for many older inpatients. Although there is conflicting evidence of the exercise preferences of community‐dwelling older adults,[1] the results of this study are consistent with evidence supporting exercising with peers.[3, 17]

Self‐determination theory describes motivation existing along a continuum, from intrinsic motivation to extrinsic motivation then amotivation.[18] Participants described valuing the physical benefits of exercise (extrinsic motivation), similarly noted by survivors of stroke.[19, 20] For those who do not value exercise, group instructors may consider discussing its benefits during GPT. Competition may be stimulated through exercising with peers; therefore, group instructors should utilize this advantage of GPT over individual physiotherapy.

Participants feeling socially supported in GPT were similar to those reported by hospitalized older adults[21] as well as those undertaking exercise groups for cardiac rehabilitation,[22] terminal cancer,[23] and following lung transplantation.[24] Fostering a supportive environment may enhance the patient experience; therefore, physiotherapists should encourage GPT attendance and socialization (as appropriate) and actively acknowledge physical improvements.

The Social Comparison Theory suggests that people evaluate their abilities by comparing themselves to their peers.[25, 26] Participants who made upward comparisons, with those who they perceived were better than them[26] resulted in motivation to attain the level of their more mobile peers. Downward comparisons were also made with those who they felt were less mobile; these engendered feelings of gratitude and appreciation for their own health and promoted self‐esteem,[26] and have also been reported in other populations including those with spinal cord injury[27] and breast cancer.[28]

CONCLUSION

This study provides new evidence to support GPT for hospitalized older adults. Participants in this study enjoyed GPT and were motivated and supported by their peers. As GPT was valued by hospitalized older adults who participated in this study for its physical and social benefits, clinicians could consider replacing several individual treatment sessions with GPT as part of a weekly treatment schedule.

There is uncertainty regarding older adults' attitudes toward participating in group exercise. Although some evidence suggests that in the community, older adults prefer to exercise alone with some instruction,[1, 2] others support the preference of group exercise with peers.[3] Little is known about the attitudes of hospitalized older adults toward group physiotherapy (GPT). Providing physiotherapy (also known as physical therapy) in a group setting has been shown to be effective in a variety of populations,[4, 5, 6, 7] and as a consequence of simultaneously treating multiple patients, therapist[8] and cost[9] efficiency are enhanced. Description of the patient experience is increasingly being recognized as a crucial element in the delivery of patient‐centered care and performance evaluation of health professionals and services.[10] Therefore, the purpose of this investigation was to explore older inpatients' experiences of GPT to assist with planning and designing future inpatient programs to maximize patient participation, satisfaction, and clinical outcomes.

METHODS

RESULTS

Eight females and 4 males aged 73 to 93 years (mean = 82.5 years, standard deviation = 7.1 years) participated in the interviews. After initially consenting to participate, 1 participant declined due to fatigue. Three participants were discharged prior to scheduling an interview. Analysis revealed 6 major themes and 10 subthemes (Table 2).

DISCUSSION

Participants were positive about GPT and reported experiencing physical benefits. Motivation was reported as an important factor in recovery, with improving mobility and competition as commonly described extrinsic motivators. Social comparisons made between participants were motivating and reassuring.

Group physiotherapy sessions are often a replacement for individual physiotherapy; therefore, it is important that participants feel they are receiving a suitable alternative. Individual physiotherapy has advantages over GPT including affording a more individualized assessment and treatment; a combination of both may be appropriate for many older inpatients. Although there is conflicting evidence of the exercise preferences of community‐dwelling older adults,[1] the results of this study are consistent with evidence supporting exercising with peers.[3, 17]

Self‐determination theory describes motivation existing along a continuum, from intrinsic motivation to extrinsic motivation then amotivation.[18] Participants described valuing the physical benefits of exercise (extrinsic motivation), similarly noted by survivors of stroke.[19, 20] For those who do not value exercise, group instructors may consider discussing its benefits during GPT. Competition may be stimulated through exercising with peers; therefore, group instructors should utilize this advantage of GPT over individual physiotherapy.

Participants feeling socially supported in GPT were similar to those reported by hospitalized older adults[21] as well as those undertaking exercise groups for cardiac rehabilitation,[22] terminal cancer,[23] and following lung transplantation.[24] Fostering a supportive environment may enhance the patient experience; therefore, physiotherapists should encourage GPT attendance and socialization (as appropriate) and actively acknowledge physical improvements.

The Social Comparison Theory suggests that people evaluate their abilities by comparing themselves to their peers.[25, 26] Participants who made upward comparisons, with those who they perceived were better than them[26] resulted in motivation to attain the level of their more mobile peers. Downward comparisons were also made with those who they felt were less mobile; these engendered feelings of gratitude and appreciation for their own health and promoted self‐esteem,[26] and have also been reported in other populations including those with spinal cord injury[27] and breast cancer.[28]

CONCLUSION

This study provides new evidence to support GPT for hospitalized older adults. Participants in this study enjoyed GPT and were motivated and supported by their peers. As GPT was valued by hospitalized older adults who participated in this study for its physical and social benefits, clinicians could consider replacing several individual treatment sessions with GPT as part of a weekly treatment schedule.

There is uncertainty regarding older adults' attitudes toward participating in group exercise. Although some evidence suggests that in the community, older adults prefer to exercise alone with some instruction,[1, 2] others support the preference of group exercise with peers.[3] Little is known about the attitudes of hospitalized older adults toward group physiotherapy (GPT). Providing physiotherapy (also known as physical therapy) in a group setting has been shown to be effective in a variety of populations,[4, 5, 6, 7] and as a consequence of simultaneously treating multiple patients, therapist[8] and cost[9] efficiency are enhanced. Description of the patient experience is increasingly being recognized as a crucial element in the delivery of patient‐centered care and performance evaluation of health professionals and services.[10] Therefore, the purpose of this investigation was to explore older inpatients' experiences of GPT to assist with planning and designing future inpatient programs to maximize patient participation, satisfaction, and clinical outcomes.

METHODS

RESULTS

Eight females and 4 males aged 73 to 93 years (mean = 82.5 years, standard deviation = 7.1 years) participated in the interviews. After initially consenting to participate, 1 participant declined due to fatigue. Three participants were discharged prior to scheduling an interview. Analysis revealed 6 major themes and 10 subthemes (Table 2).

DISCUSSION

Participants were positive about GPT and reported experiencing physical benefits. Motivation was reported as an important factor in recovery, with improving mobility and competition as commonly described extrinsic motivators. Social comparisons made between participants were motivating and reassuring.

Group physiotherapy sessions are often a replacement for individual physiotherapy; therefore, it is important that participants feel they are receiving a suitable alternative. Individual physiotherapy has advantages over GPT including affording a more individualized assessment and treatment; a combination of both may be appropriate for many older inpatients. Although there is conflicting evidence of the exercise preferences of community‐dwelling older adults,[1] the results of this study are consistent with evidence supporting exercising with peers.[3, 17]

Self‐determination theory describes motivation existing along a continuum, from intrinsic motivation to extrinsic motivation then amotivation.[18] Participants described valuing the physical benefits of exercise (extrinsic motivation), similarly noted by survivors of stroke.[19, 20] For those who do not value exercise, group instructors may consider discussing its benefits during GPT. Competition may be stimulated through exercising with peers; therefore, group instructors should utilize this advantage of GPT over individual physiotherapy.

Participants feeling socially supported in GPT were similar to those reported by hospitalized older adults[21] as well as those undertaking exercise groups for cardiac rehabilitation,[22] terminal cancer,[23] and following lung transplantation.[24] Fostering a supportive environment may enhance the patient experience; therefore, physiotherapists should encourage GPT attendance and socialization (as appropriate) and actively acknowledge physical improvements.

The Social Comparison Theory suggests that people evaluate their abilities by comparing themselves to their peers.[25, 26] Participants who made upward comparisons, with those who they perceived were better than them[26] resulted in motivation to attain the level of their more mobile peers. Downward comparisons were also made with those who they felt were less mobile; these engendered feelings of gratitude and appreciation for their own health and promoted self‐esteem,[26] and have also been reported in other populations including those with spinal cord injury[27] and breast cancer.[28]

CONCLUSION

This study provides new evidence to support GPT for hospitalized older adults. Participants in this study enjoyed GPT and were motivated and supported by their peers. As GPT was valued by hospitalized older adults who participated in this study for its physical and social benefits, clinicians could consider replacing several individual treatment sessions with GPT as part of a weekly treatment schedule.

Epidemiological studies estimate that 40% to 50% of patients with pneumonia develop a parapneumonic effusion (PPE), and up to 35% of these have empyema. Approximately 15% of patients require surgical drainage, which has a high mortality rate.[1] Although early intervention is important in patients with suspected PPE, diagnosing a PPE is challenging, as cultures and Gram stain are frequently negative.[1] Clinicians have to rely on tests, such as pleural fluid pH, lactate dehydrogenase (LDH), and glucose, which have low sensitivity and specificity in diagnosing a PPE.

Procalcitonin (PCT) is a distinct biomarker and mediator of sepsis, emanating from parenchymal cells ubiquitously (eg, lung, liver, kidney) due to reduced conversion to mature calcitonin.[2] Besides sepsis, PCT has been used as a biomarker of pneumonia based on its ability to differentiate bacterial versus viral infections.[3, 4, 5] PCT has been shown to be a biomarker in extravascular fluids such as saliva, wound effusions, and pleural fluid.[6, 7, 8, 9] In this study we investigate the diagnostic accuracy of pleural fluid PCT in distinguishing infectious and noninfectious etiologies of pleural effusion in veterans with lung infiltrates.

METHOD

The study protocol was approved by the institution review board at the Veterans Affairs Medical Center, Washington, DC. Patients were identified using a computerized patient record system after searching the procedure code for thoracentesis. A retrospective chart review was conducted on veterans who underwent a thoracentesis from February 2011 through January 2012.

RESULTS

A total of 75 patients were included in the study. There were 73 (97.4%) males, with mean age of 70.8 years (range, 4293 years). There were 18 patients with IPE and 57 with NIPE.

Patient characteristics are detailed in Table 1. In the infectious group, 2 patients had empyema. There were no cases of tuberculosis. Of the 57 effusions in the noninfectious group there were 42 exudative effusions, 23 of which were malignant, 3 each were due to a trapped lung and pulmonary embolism. The remaining NIPEs were due to nonpulmonary processes such as chylothorax, liver disease, and renal disease.

The pleural fluid characteristics and biomarkers are detailed in Table 1. Median pleural fluid PCT in IPE was 1.088 ng/mL (0.3122.940 ng/mL) and 0.123 ng/mL (0.050.263 ng/mL) in NIPE, with a P value <0.0001. Pleural fluid PCT >0.25 ng/mL had a sensitivity of 77.78% and specificity of 74.14% for diagnosing an IPE (Figure 1).

Figure 1

A subgroup analysis comparing 13 exudative effusions in the infectious group with the 23 exudative malignant and paramalignant effusions in the noninfectious group was also performed. The median pleural PCT value in the infectious group was 0.9743 ng/mL (0.454.117 ng/mL) and 0.1222 ng/mL (0.054650.1972 ng/mL) in the noninfectious group, with a P value <0.0009

DISCUSSION

Clinicians frequently face the dilemma of differentiating IPE from NIPE. In this study, pleural fluid PCT was significantly elevated in IPE. A pleural fluid PCT >0.25 ng/mL had a sensitivity of 77.78% and specificity of 74.14% for diagnosing an IPE (Figure 1). Our subgroup analysis also showed a higher PCT in exudative effusions of the infectious group as compared to exudative effusions of malignant/paramalignant etiology in the noninfectious group. PCT may have a role as a biomarker in diagnosing an infected malignant/paramalignant effusion. Further studies are needed to confirm the same.

Our study is one of the few using the more sensitive technology (eg, Kryptor) to measure PCT levels in pleural fluid, utilizing the current method of choice for serum PCT based on assay performance.[2] PCT is produced during bacterial infections by several tissues sources, and its role in differentiating IPE and NIPE has been investigated by several authors. A prior study reported on 233 patients, 28 of whom had PPEs, 49 had tubercular effusion, and 166 had NIPE.[1] The cutoff point in this study of PCT was >0.145 ng/mL, with a sensitivity of 51.6% and specificity of 66.5%.[1] Another study evaluated 82 patients with pleural effusions, 45 of whom were infectious (bacterial, nontubercular) and used a PCT cutoff value of 0.18 ng/mL to discriminate between IPE and NIPE. They reported a sensitivity of 66.7% and specificity of 77.4%. There was no significant difference in the serum and pleural fluid PCT values within IPE and NIPE subgroups. In fact, there was a significant positive correlation between serum and pleural fluid PCT. However, on comparing evolution of pleural and serum PCT between day 1 and day 3, the authors noted that unlike pleural fluid PCT, serum PCT values were lower on day 3 as compared to day 1.[8] A study on 12 forensic autopsy cases, to establish the usefulness of pericardial and pleural fluids for the postmortem diagnosis of sepsis, also reported significantly higher and similar PCT levels in the sepsis group in both serum and pleural fluid (using an immunoassay by Roche Diagnostic, Mannheim, Germany). The authors suggested that pleural fluid PCT can be used in lieu of serum PCT values to determine the etiology of an effusion.[11]

PCT has a role in the decision to initiate or discontinue antibiotics in the management of community‐acquired pneumonia.[12] In this era of multidrug resistance, appropriate use of antibiotics is of paramount importance, and PCT could play an important role in this regard. The gold standard test to diagnose an infectious pleural effusion is present in a small percentage of patients.[13] Larger randomized studies designed to evaluate the role of serial serum and pleural fluid PCT, with appropriate cutoff values, are needed to define the role of PCT in guiding antibiotic therapy.[14]

The limitations of this study include its retrospective nature and lack of serum PCT data. The gold standard methods to diagnose pleural effusion were not available in this study.

CONCLUSION

PCT is a novel biomarker for diagnosing infectious pleural effusion, and it would be worthwhile to investigate the role of pleural PCT in assessing severity of illness, risk stratification, and antibiotic stewardship in hospitalized patients with pleural effusions.

Disclosure: Nothing to report.

Epidemiological studies estimate that 40% to 50% of patients with pneumonia develop a parapneumonic effusion (PPE), and up to 35% of these have empyema. Approximately 15% of patients require surgical drainage, which has a high mortality rate.[1] Although early intervention is important in patients with suspected PPE, diagnosing a PPE is challenging, as cultures and Gram stain are frequently negative.[1] Clinicians have to rely on tests, such as pleural fluid pH, lactate dehydrogenase (LDH), and glucose, which have low sensitivity and specificity in diagnosing a PPE.

Procalcitonin (PCT) is a distinct biomarker and mediator of sepsis, emanating from parenchymal cells ubiquitously (eg, lung, liver, kidney) due to reduced conversion to mature calcitonin.[2] Besides sepsis, PCT has been used as a biomarker of pneumonia based on its ability to differentiate bacterial versus viral infections.[3, 4, 5] PCT has been shown to be a biomarker in extravascular fluids such as saliva, wound effusions, and pleural fluid.[6, 7, 8, 9] In this study we investigate the diagnostic accuracy of pleural fluid PCT in distinguishing infectious and noninfectious etiologies of pleural effusion in veterans with lung infiltrates.

METHOD

The study protocol was approved by the institution review board at the Veterans Affairs Medical Center, Washington, DC. Patients were identified using a computerized patient record system after searching the procedure code for thoracentesis. A retrospective chart review was conducted on veterans who underwent a thoracentesis from February 2011 through January 2012.

RESULTS

A total of 75 patients were included in the study. There were 73 (97.4%) males, with mean age of 70.8 years (range, 4293 years). There were 18 patients with IPE and 57 with NIPE.

Patient characteristics are detailed in Table 1. In the infectious group, 2 patients had empyema. There were no cases of tuberculosis. Of the 57 effusions in the noninfectious group there were 42 exudative effusions, 23 of which were malignant, 3 each were due to a trapped lung and pulmonary embolism. The remaining NIPEs were due to nonpulmonary processes such as chylothorax, liver disease, and renal disease.

The pleural fluid characteristics and biomarkers are detailed in Table 1. Median pleural fluid PCT in IPE was 1.088 ng/mL (0.3122.940 ng/mL) and 0.123 ng/mL (0.050.263 ng/mL) in NIPE, with a P value <0.0001. Pleural fluid PCT >0.25 ng/mL had a sensitivity of 77.78% and specificity of 74.14% for diagnosing an IPE (Figure 1).

Figure 1

A subgroup analysis comparing 13 exudative effusions in the infectious group with the 23 exudative malignant and paramalignant effusions in the noninfectious group was also performed. The median pleural PCT value in the infectious group was 0.9743 ng/mL (0.454.117 ng/mL) and 0.1222 ng/mL (0.054650.1972 ng/mL) in the noninfectious group, with a P value <0.0009

DISCUSSION

Clinicians frequently face the dilemma of differentiating IPE from NIPE. In this study, pleural fluid PCT was significantly elevated in IPE. A pleural fluid PCT >0.25 ng/mL had a sensitivity of 77.78% and specificity of 74.14% for diagnosing an IPE (Figure 1). Our subgroup analysis also showed a higher PCT in exudative effusions of the infectious group as compared to exudative effusions of malignant/paramalignant etiology in the noninfectious group. PCT may have a role as a biomarker in diagnosing an infected malignant/paramalignant effusion. Further studies are needed to confirm the same.

Our study is one of the few using the more sensitive technology (eg, Kryptor) to measure PCT levels in pleural fluid, utilizing the current method of choice for serum PCT based on assay performance.[2] PCT is produced during bacterial infections by several tissues sources, and its role in differentiating IPE and NIPE has been investigated by several authors. A prior study reported on 233 patients, 28 of whom had PPEs, 49 had tubercular effusion, and 166 had NIPE.[1] The cutoff point in this study of PCT was >0.145 ng/mL, with a sensitivity of 51.6% and specificity of 66.5%.[1] Another study evaluated 82 patients with pleural effusions, 45 of whom were infectious (bacterial, nontubercular) and used a PCT cutoff value of 0.18 ng/mL to discriminate between IPE and NIPE. They reported a sensitivity of 66.7% and specificity of 77.4%. There was no significant difference in the serum and pleural fluid PCT values within IPE and NIPE subgroups. In fact, there was a significant positive correlation between serum and pleural fluid PCT. However, on comparing evolution of pleural and serum PCT between day 1 and day 3, the authors noted that unlike pleural fluid PCT, serum PCT values were lower on day 3 as compared to day 1.[8] A study on 12 forensic autopsy cases, to establish the usefulness of pericardial and pleural fluids for the postmortem diagnosis of sepsis, also reported significantly higher and similar PCT levels in the sepsis group in both serum and pleural fluid (using an immunoassay by Roche Diagnostic, Mannheim, Germany). The authors suggested that pleural fluid PCT can be used in lieu of serum PCT values to determine the etiology of an effusion.[11]

PCT has a role in the decision to initiate or discontinue antibiotics in the management of community‐acquired pneumonia.[12] In this era of multidrug resistance, appropriate use of antibiotics is of paramount importance, and PCT could play an important role in this regard. The gold standard test to diagnose an infectious pleural effusion is present in a small percentage of patients.[13] Larger randomized studies designed to evaluate the role of serial serum and pleural fluid PCT, with appropriate cutoff values, are needed to define the role of PCT in guiding antibiotic therapy.[14]

The limitations of this study include its retrospective nature and lack of serum PCT data. The gold standard methods to diagnose pleural effusion were not available in this study.

CONCLUSION

PCT is a novel biomarker for diagnosing infectious pleural effusion, and it would be worthwhile to investigate the role of pleural PCT in assessing severity of illness, risk stratification, and antibiotic stewardship in hospitalized patients with pleural effusions.

Disclosure: Nothing to report.

Epidemiological studies estimate that 40% to 50% of patients with pneumonia develop a parapneumonic effusion (PPE), and up to 35% of these have empyema. Approximately 15% of patients require surgical drainage, which has a high mortality rate.[1] Although early intervention is important in patients with suspected PPE, diagnosing a PPE is challenging, as cultures and Gram stain are frequently negative.[1] Clinicians have to rely on tests, such as pleural fluid pH, lactate dehydrogenase (LDH), and glucose, which have low sensitivity and specificity in diagnosing a PPE.

Procalcitonin (PCT) is a distinct biomarker and mediator of sepsis, emanating from parenchymal cells ubiquitously (eg, lung, liver, kidney) due to reduced conversion to mature calcitonin.[2] Besides sepsis, PCT has been used as a biomarker of pneumonia based on its ability to differentiate bacterial versus viral infections.[3, 4, 5] PCT has been shown to be a biomarker in extravascular fluids such as saliva, wound effusions, and pleural fluid.[6, 7, 8, 9] In this study we investigate the diagnostic accuracy of pleural fluid PCT in distinguishing infectious and noninfectious etiologies of pleural effusion in veterans with lung infiltrates.

METHOD

The study protocol was approved by the institution review board at the Veterans Affairs Medical Center, Washington, DC. Patients were identified using a computerized patient record system after searching the procedure code for thoracentesis. A retrospective chart review was conducted on veterans who underwent a thoracentesis from February 2011 through January 2012.

RESULTS

A total of 75 patients were included in the study. There were 73 (97.4%) males, with mean age of 70.8 years (range, 4293 years). There were 18 patients with IPE and 57 with NIPE.

Patient characteristics are detailed in Table 1. In the infectious group, 2 patients had empyema. There were no cases of tuberculosis. Of the 57 effusions in the noninfectious group there were 42 exudative effusions, 23 of which were malignant, 3 each were due to a trapped lung and pulmonary embolism. The remaining NIPEs were due to nonpulmonary processes such as chylothorax, liver disease, and renal disease.

The pleural fluid characteristics and biomarkers are detailed in Table 1. Median pleural fluid PCT in IPE was 1.088 ng/mL (0.3122.940 ng/mL) and 0.123 ng/mL (0.050.263 ng/mL) in NIPE, with a P value <0.0001. Pleural fluid PCT >0.25 ng/mL had a sensitivity of 77.78% and specificity of 74.14% for diagnosing an IPE (Figure 1).

Figure 1

A subgroup analysis comparing 13 exudative effusions in the infectious group with the 23 exudative malignant and paramalignant effusions in the noninfectious group was also performed. The median pleural PCT value in the infectious group was 0.9743 ng/mL (0.454.117 ng/mL) and 0.1222 ng/mL (0.054650.1972 ng/mL) in the noninfectious group, with a P value <0.0009

DISCUSSION

Clinicians frequently face the dilemma of differentiating IPE from NIPE. In this study, pleural fluid PCT was significantly elevated in IPE. A pleural fluid PCT >0.25 ng/mL had a sensitivity of 77.78% and specificity of 74.14% for diagnosing an IPE (Figure 1). Our subgroup analysis also showed a higher PCT in exudative effusions of the infectious group as compared to exudative effusions of malignant/paramalignant etiology in the noninfectious group. PCT may have a role as a biomarker in diagnosing an infected malignant/paramalignant effusion. Further studies are needed to confirm the same.

Our study is one of the few using the more sensitive technology (eg, Kryptor) to measure PCT levels in pleural fluid, utilizing the current method of choice for serum PCT based on assay performance.[2] PCT is produced during bacterial infections by several tissues sources, and its role in differentiating IPE and NIPE has been investigated by several authors. A prior study reported on 233 patients, 28 of whom had PPEs, 49 had tubercular effusion, and 166 had NIPE.[1] The cutoff point in this study of PCT was >0.145 ng/mL, with a sensitivity of 51.6% and specificity of 66.5%.[1] Another study evaluated 82 patients with pleural effusions, 45 of whom were infectious (bacterial, nontubercular) and used a PCT cutoff value of 0.18 ng/mL to discriminate between IPE and NIPE. They reported a sensitivity of 66.7% and specificity of 77.4%. There was no significant difference in the serum and pleural fluid PCT values within IPE and NIPE subgroups. In fact, there was a significant positive correlation between serum and pleural fluid PCT. However, on comparing evolution of pleural and serum PCT between day 1 and day 3, the authors noted that unlike pleural fluid PCT, serum PCT values were lower on day 3 as compared to day 1.[8] A study on 12 forensic autopsy cases, to establish the usefulness of pericardial and pleural fluids for the postmortem diagnosis of sepsis, also reported significantly higher and similar PCT levels in the sepsis group in both serum and pleural fluid (using an immunoassay by Roche Diagnostic, Mannheim, Germany). The authors suggested that pleural fluid PCT can be used in lieu of serum PCT values to determine the etiology of an effusion.[11]

PCT has a role in the decision to initiate or discontinue antibiotics in the management of community‐acquired pneumonia.[12] In this era of multidrug resistance, appropriate use of antibiotics is of paramount importance, and PCT could play an important role in this regard. The gold standard test to diagnose an infectious pleural effusion is present in a small percentage of patients.[13] Larger randomized studies designed to evaluate the role of serial serum and pleural fluid PCT, with appropriate cutoff values, are needed to define the role of PCT in guiding antibiotic therapy.[14]

The limitations of this study include its retrospective nature and lack of serum PCT data. The gold standard methods to diagnose pleural effusion were not available in this study.

CONCLUSION

PCT is a novel biomarker for diagnosing infectious pleural effusion, and it would be worthwhile to investigate the role of pleural PCT in assessing severity of illness, risk stratification, and antibiotic stewardship in hospitalized patients with pleural effusions.

Disclosure: Nothing to report.

Low mobility is common in hospitalized older patients, and an independent predictor of poor functional outcomes.[1, 2, 3, 4] Few studies have included younger patients, but care models that support early mobility may reduce functional decline, enhance recovery, and reduce length of stay in older and mixed‐age populations.[5, 6] Barriers to mobility are complex and include patient symptoms and tethers, health provider behavior, team communication, and leadership, device availability, and environmental factors.[7, 8, 9, 10, 11] These contextual factors may differ even within a hospital between patient groups and ward settings. Simple measures to quantify mobility patterns would help address these barriers by providing opportunities for audit and feedback. Although accelerometry is the gold standard method for research, it requires equipment, analysis skills, and patient consent, which limits application in clinical practice. Behavioral mapping is a systematic method of observation developed in stroke patients, which is simple, objective, and requires no direct patient or staff participation,[12] and physical activity levels estimated from behavioral mapping are similar to those identified by accelerometry.[3, 13, 14] In the context of a phased quality‐improvement project aiming to reduce functional decline,[15] we undertook a cross‐sectional audit of mobility on 3 different wards using behavioral mapping, and examined differences among wards and between older (aged 65 years or more) and younger patients.

METHODS

This prospective observational study used cross‐sectional sampling from a 26‐bed general medical ward, a 30‐bed oncology ward, and a 24‐bed vascular surgical ward in a 900‐bed tertiary teaching hospital in Brisbane, Australia. Sampling was undertaken during 4 observation periods (2 mornings [10001400] and 2 afternoons [1400‐1800]) within 10 days in May 2013. All patients on each ward for each period were observed unless they were receiving end‐of‐life care. Structured observations were undertaken using behavioral mapping protocols similar to those previously described in stroke and general medical patients,[12, 13] with each patient room visited in the same sequence. Participants in each room were observed for a 2‐minute period (up to 4 participants could be observed concurrently in shared rooms) before moving to the next room, and the sequence was repeated in the same order for the whole 4‐hour period, with a single 15‐minute break. Depending on ward size and layout, this provided 12 to 17 observations per participant for each 4‐hour period (each individual observed every 1218 minutes). Observations were undertaken by 4 trained physiotherapy student observers using a predetermined set of mutually exclusive levels (lying in bed, sitting in or on the bed, sitting on a chair, standing, actively wheeling, or walking). The study was approved by the Royal Brisbane and Women's Hospital Human Research Ethics Committee as part of a quality‐improvement activity, and individual consent was not required. No clinical data except age and gender were collected for participants. The nurse unit manager for each ward was introduced to the observers and aware that observations were being conducted.

Patients who were observed for less than one‐half of an observation period were excluded so that all participants contributed at least 2 hours of observational data, up to a maximum of 16 hours. The number of valid observations for each participant (excluding time off ward or behind curtains if the level was not apparent) was calculated and used to derive the proportion of valid observations spent at each level for each participant. The proportion of observations at each level was summarized across all participants using frequency distributions and summary statistics. For ease of presentation, mean percentage of observed time in each activity was presented. However, as data were not normally distributed, statistical comparisons were undertaken using the Kruskal‐Wallis test, comparing the distribution of time spent upright (standing, walking, or actively wheeling) between groups (age group and ward). Interaction between age and ward effects was sought using generalized linear modeling.

RESULTS

Valid observations (at least 2 hours in 1 or more observation period) were available for 132 patients (48 medical, 50 oncology, and 34 surgery). Of these, 67 (51 %) were aged 65 years (54% medical, 44% oncology, 56% surgery) and 62 (47%) were male. There were a total of 3891 observations of location (median, 30 per patient; range, 965). Participants were observed in the bedded area 85.1% of observations, with 3.1% in the bathroom, 3.2% in the hallway or patient lounge, and 8.6% off ward. Allowing for time off ward and behind curtains, when observers could not be sure of their activity level, 3272 valid observations were available for physical activity.

More than half of the observed time (mean 57.4%) was spent lying in bed, 33.6% sitting on the bed or chair, and 9.0% standing, walking, or wheeling. Across all observation periods, 39/132 (29.5%) participants were never observed to be standing, walking or wheeling, and 7.6% were in bed at all observations. Comparing older and younger patients (Table 1), there was no difference in the time spent in active upright postures (median, 6.1% in older vs 7.4% in younger; P = 0.30). Table 2 summarizes descriptive data for the different wards. In the medical and surgical wards, 84% of the time was spend in or on the bed, and only 16% of the time was spent sitting in a chair or in active upright postures. Surgical patients, in particular, spent two‐thirds of observation time lying flat in bed, whereas medical patients spent more time sitting up on the bed. On statistical testing, time spent standing/walking/wheeling was significantly lower on the surgical ward (median, 4%; interquartile range [IQR], 010 for surgery; median, 7%; IQR, 013 for medical; and median, 10%; IQR 317 for oncology; P = 0.015). This was also reflected in a higher proportion of surgical patients never seen in an active upright position (44.1% compared to 27.1% medical and 22.0% oncology). Multivariate modeling showed no significant interaction between age and ward.

DISCUSSION

This observational cross‐sectional study extends previous observations of hospital inpatients to include a wider variety of patient types and ages. Observing 132 patients on medical, surgical, and oncology wards for up to 16 hours of weekday time, we found that patients spent only 9% in active upright postures, with significantly lower mobility on the surgical ward but no significant differences between older and younger patients.

Previous studies in older general medical patients using behavioral mapping[13] or accelerometers[2, 3] have shown 71% to 83% of time spent in bed, and 4% spent standing or walking, similar to our findings, although methodological differences between studies (eg, patient selection and time windows) caution against direct comparison. We identified different levels of physical activity on the surgical, medical, and oncology wards. This may reflect differences in patient case‐mix, ward environment, and/or ward culture. The medical and oncology wards each have a patient lounge, providing a potential walking destination, although only a small amount of patients' time was observed in these areas, suggesting that they may not fulfil their purpose. The oncology ward has a well developed wellness focus. The oncology and medical wards were actively involved in a quality‐improvement intervention to improve early patient mobility at the time of the audit,[15] whereas the surgical ward was at the precommencement (information gathering) stage. The data collected within this audit have formed part of the feedback cycle for staff involved in the improvement intervention. Repeat measurement will be undertaken on the surgical ward to help evaluate the impact of the intervention, and serial measurement will be undertaken in future participating wards to investigate the responsiveness of this measurement method.

Although the literature has focused on poor mobility in hospitalized elders, we did not find any better mobility in younger patients, suggesting that barriers to mobility are not confined to the elderly. Whereas individualized mobility assessment and support may be more important in the elderly,[16] addressing cultural and environmental issues such as promoting accountability for early ambulation, providing patients and families with permission and encouragement to ambulate, and ensuring accessible walking destinations may benefit patients of all ages.

Behavioral mapping has strengths and weaknesses compared to other methods such as accelerometry or patient/nurse report. Observations are conducted by an independent observer not involved in care and include all ward inpatients, providing a generalizable sample, as the observation protocol does not pose a participation burden for patient or ward staff. However, the cross‐sectional nature may oversample longer‐stay patients, the intermittent observation protocol tends to overestimate time spent upright,[14] the labor‐intensive nature of observations means choosing a limited time window (in our case 10001800), and the minimum time and observation frequency to generate reliable data remain uncertain. Further studies examining reliability, validity, and responsiveness would support the utility of this method for quality improvement.

In summary, this study shows that mobility is limited in older and younger adult inpatients across a range of inpatient wards, and that physical activity practices vary among wards. Interventions to enhance hospital mobility should include patients of all ages, and need to be tailored to local mobility practices, barriers, and enablers.