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BACKGROUND: Hospital-based palliative care consultation is consistently associated with reduced hospitalization costs and more importantly with improved patient quality of life. As healthcare systems move toward value-based purchasing rather than fee-for-service models, understanding how palliative care consultation is associated with value-based purchasing metrics can provide evidence for expanded health system support for a greater palliative care presence. AIM: To understand how a palliative care consultation impacts rates of patient readmission and hospital-acquired infections associated with value-based purchasing metrics. DESIGN: Retrospective propensity-matched case-control study evaluating the impact of palliative care consultation on hospital charges, hospital and intensive care unit length of stay, readmission rates, and rates of hospital-acquired conditions. SETTING/PARTICIPANTS: All adult patients admitted to a two hospital healthcare system over a 2-year period from 1 April 2015 to 31 March 2017. The palliative care team involved three physicians, five advanced practice providers, a social worker, and a chaplain during the study period. RESULTS: A total of 3415 patients receiving a palliative consult were propensity matched to 25,028 controls. Compared to controls, cases had decreased charges per day and decreased rates of 7-, 30-, and 90-day readmissions. CONCLUSION: Through value-based purchasing, hospitals have 3% of their Medicare reimbursements at risk based on readmission rates. By clarifying prognosis and patient goals, palliative care consultation reduces readmission rates. Hospital systems may want to invest in larger palliative care programs as part of their efforts to reduce hospital readmissions.

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BACKGROUND: Increasing adoption of electronic health records (EHRs) with integrated alerting systems is a key initiative for improving patient safety. Considering the variety of dynamically changing clinical information, it remains a challenge to design EHR-driven alerting systems that notify the right providers for the right patient at the right time while managing alert burden. The objective of this study is to proactively develop and evaluate a systematic alert-generating approach as part of the implementation of an Early Warning Score (EWS) at the study hospitals. METHODS: We quantified the impact of an EWS-based clinical alert system on quantity and frequency of alerts using three different alert algorithms consisting of a set of criteria for triggering and muting alerts when certain criteria are satisfied. We used retrospectively collected EHRs data from December 2015 to July 2016 in three units at the study hospitals including general medical, acute care for the elderly and patients with heart failure. RESULTS: We compared the alert-generating algorithms by opportunity of early recognition of clinical deterioration while proactively estimating alert burden at a unit and patient level. Results highlighted the dependency of the number and frequency of alerts generated on the care location severity and patient characteristics. CONCLUSION: EWS-based alert algorithms have the potential to facilitate appropriate alert management prior to integration into clinical practice. By comparing different algorithms with regard to the alert frequency and potential early detection of physiological deterioration as key patient safety opportunities, findings from this study highlight the need for alert systems tailored to patient and care location needs, and inform alternative EWS-based alert deployment strategies to enhance patient safety.

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BACKGROUND: To determine the extent to which 30- and 90-day hospital readmission and mortality rates differ as a function of whether a chest pain patient is placed in observation status or admitted to the hospital for a short-stay (<48 h). METHODS: Using 114,043 observation stays and short-stay admissions for chest pain at Veterans Health Administration hospitals between 2005 and 2013, we estimated event-level logistic regression models using a generalized estimating equation framework to predict 30 and 90-day readmissions and mortality as a function of whether the patient had an observation stay or a short-stay admission. We also adjusted for a variety of patient characteristics and unobserved time-invariant hospital factors. RESULTS: Relative to the short-stay inpatient group, veterans with chest pain who were placed in observation status were significantly more likely to be female (7.0 % vs. 6.4 %, White (76.6 % vs. 71.0 %, and from a rural area (28.3 % vs. 20.2 %). There were no other meaningful differences between the groups. Veterans with chest pain who were placed in observation status had 25 % lower odds of dying within 30 days (95 % confidence interval [CI]: 3 % - 43 %) and 12 % lower odds of a 30-day readmission (95 % CI: 6 % - 17 %) compared to those admitted as short-stay inpatients. Neither 90-day outcome was significantly associated with placement in observation status. Patient demographics were also important predictors of mortality and readmissions. CONCLUSIONS: There are clinically observable differences in outcomes between patients admitted to observation and those admitted as short-stay inpatients. We find no evidence that the increase in observation stays reflects a lack of proper care for patients placed in observation status.

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Observation stays are an outpatient service used to diagnose and treat patients for extended periods of time while a decision is made regarding inpatient admission or discharge. Although the use of observation stays is increasing, little is known about which patients are observed and which are admitted for similar periods of time as inpatients. The aim was to identify patient characteristics associated with being observed rather than admitted for a short stay (<48 hours) within the Veterans Health Administration (VHA). In our longitudinal analysis, we used logistic regression within a generalized estimating equation framework to model observation stays as a function of patient characteristics, time trends, and hospital fixed effects. To minimize heterogeneity between groups, we limit our sample to patients with a presenting diagnosis of chest pain. Our analysis includes a total of 121 584 hospital events, which consist of all observation and short-stay admissions for chest pain patients at VHA hospitals between 2005 and 2013. Both the absolute and relative use of observation stays increased markedly over time. The odds of an observation stay were higher among women, but lower among older patients and rural residents. Despite strong evidence that chest pain patients are increasingly more likely to be observed than admitted, suggesting a substitution effect, we find little evidence of within-hospital disparities in VHA observation stay use.

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Recent studies have documented that a significant increase in the use of observation stays along with extensive variation in patterns of use across hospitals.The objective of this longitudinal observational study was to examine the extent to which patient, hospital, and local health system characteristics explain variation in observation stay rates across Veterans Health Administration (VHA) hospitals.Our data came from years 2005 to 2012 of the nationwide VHA Medical SAS inpatient and enrollment files, American Hospital Association Survey, and Area Health Resource File. We used these data to estimate linear regression models of hospitals' observation stay rates as a function of hospital, patient, and local health system characteristics, while controlling for time trends and Veterans Integrated Service Network level fixed effects.We found that observation stay rates are inversely related to hospital bed size and that hospitals with a greater proportion of younger or rural patients have higher observation stay rates. Observation stay rates were nearly 15 percentage points higher in 2012 than 2005.Although we identify several characteristics associated with variation in VHA hospital observation stay rates, many factors remain unmeasured.

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Variation in how hospitals perform on similar quality improvement (QI) efforts argues for a need to understand how different organizational characteristics affect QI performance. The objective of this study was to use data-mining methods to evaluate relationships between measures of organizational characteristics and hospital QI performance. Organizational characteristics were extracted from 2 surveys and analyzed in 3 separate decision-tree models. The decision trees did not find any predictive associations in this sample of 100 hospitals participating in a national QI collaborative. Further model review identified that measures of QI Experience were associated with an ability to make improvements, whereas measures of Staffing and Culture were associated with an ability to sustain improvements. A key area for future research is to understand the challenges faced as QI teams transition from improving care to sustaining quality and to ascertain what organizational characteristics can best overcome those challenges.

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BACKGROUND: Reducing length of stay (LOS) has been a priority for hospitals and health care systems. However, there is concern that this reduction may result in increased hospital readmissions. OBJECTIVE: To determine trends in hospital LOS and 30-day readmission rates for all medical diagnoses combined and 5 specific common diagnoses in the Veterans Health Administration. DESIGN: Observational study from 1997 to 2010. SETTING: All 129 acute care Veterans Affairs hospitals in the United States. PATIENTS: 4,124,907 medical admissions with subsamples of 2 chronic diagnoses (heart failure and chronic obstructive pulmonary disease) and 3 acute diagnoses (acute myocardial infarction, community-acquired pneumonia, and gastrointestinal hemorrhage). MEASUREMENTS: Unadjusted LOS and 30-day readmission rates with multivariable regression analyses to adjust for patient demographic characteristics, comorbid conditions, and admitting hospitals. RESULTS: For all medical diagnoses combined, risk-adjusted mean hospital LOS decreased by 1.46 days from 5.44 to 3.98 days, or 2% annually (P < 0.001). Reductions in LOS were also observed for the 5 specific common diagnoses, with greatest reductions for acute myocardial infarction (2.85 days) and community-acquired pneumonia (2.22 days). Over the 14 years, risk-adjusted 30-day readmission rates for all medical diagnoses combined decreased from 16.5% to 13.8% (P < 0.001). Reductions in readmissions were also observed for the 5 specific common diagnoses, with greatest reductions for acute myocardial infarction (22.6% to 19.8%) and chronic obstructive pulmonary disease (17.9% to 14.6%). All-cause mortality 90 days after admission was reduced by 3% annually. Of note, hospitals with mean risk-adjusted LOS that was lower than expected had a higher readmission rate, suggesting a modest tradeoff between hospital LOS and readmission (6% increase for each day lower than expected). LIMITATIONS: This study is limited to the Veterans Health Administration system; non-Veterans Affairs admissions were not available. No measure of readmission preventability was used. CONCLUSION: Veterans Affairs hospitals demonstrated simultaneous improvements in hospital LOS and readmissions over 14 years, suggesting that as LOS improved, hospital readmission did not increase. This is important because hospital readmission is being used as a quality indicator and may result in payment incentives. Future work should explore these relationships to see whether a tipping point exists for LOS reduction and hospital readmission. PRIMARY FUNDING SOURCE: Office of Rural Health and the Health Services Research & Development Service, Veterans Health Administration, U.S. Department of Veterans Affairs.

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BACKGROUND: Despite considerable efforts to improve healthcare quality and patient safety, broad measures of patient outcomes show little improvement. Many factors, including limited programme evaluations and understanding of whether quality improvement (QI) efforts are sustained, potentially contribute to the lack of widespread improvements in quality. This study examines whether hospitals participating in a Veterans Health Affairs QI collaborative have made and then sustained improvements. METHODS: Separate patient-level risk-adjusted time-series models for two primary outcomes (hospital length of stay (LOS) and rate of discharges before noon) as well as three secondary outcomes (30-day all-cause hospital readmission, in-hospital mortality and 30-day mortality). The models considered 2 years of pre-intervention data, 1 year of data to measure improvements and then 2 years of post-intervention data to see whether improvements were sustained. RESULTS: Among 130 Veterans Affairs hospitals, 35% and 46% exhibited improvements beyond baseline trends on LOS and discharges before noon, respectively. 60% of improving LOS hospitals exhibited sustained improvements, but only 32% for discharges by noon. Additional subgroup analyses by hospital size and region found a similar performance across most groups. CONCLUSIONS: This quasi-experimental evaluation found lower rates of improvements than normally reported in studies of QI collaboratives. The most striking observation was that a majority of hospitals increased their rates of discharges before noon, but after completing the collaborative their performance declined. Future work needs to qualitatively and quantitatively assess what organisational features distinguish those hospitals that can improve and sustain quality.

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STUDY OBJECTIVE: To analyze and compare four different methods of detecting medication misadventures in order to determine the optimal system for reporting clinically observed medication misadventures. DESIGN: Prospective cohort study. SETTING: Forty-eight-bed general internal medicine inpatient ward at a large academic teaching hospital with a decentralized pharmacy system. PATIENTS: One hundred twenty-six patients (54% male, mean age 54 yrs) with 133 consecutive admissions to the ward (mean length of stay 7.8 days) over an 8-week period from December 2001-February 2002. INTERVENTION: Medication misadventures were detected by four methods: house staff (resident physicians) report during their morning conference, nursing report during shift change, patient report at the discharge interview, and standardized medical record review. All methods of reporting medication misadventures were compared with the hospital's existing electronic medication misadventure reporting system. MEASUREMENTS AND MAIN RESULTS: Overall, 63 patients (47% of 133 admissions) experienced at least one medication misadventure. Thirty-seven adverse drug events (ADEs) and 69 medication errors were observed over 1035 patient bed-days. Little overlap was noted among the four intervention methods, with nearly 80% of all 106 events detected by only a single method (medical record review 51% [54 events], patient interview 11% [12], house-staff report 9% [10], nurse report 8% [9]). Of the 37 ADEs, 6 (16%) were due to medication errors and 10 (27%) were preventable. Of five life-threatening ADEs, all were preventable, and all were reported in the medical record and the electronic reporting system; however, only two were reported by a nurse, two by a resident physician, and one by a patient. CONCLUSION: Little overlap was noted among the individual medication misadventure reporting methods, suggesting the need to use multiple complementary methods to identify medication misadventures in hospitalized patients. These findings have important implications for development of surveillance systems, design of prevention initiatives, and future medication safety research.

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BACKGROUND: With 1-2% of patients leaving the hospital against medical advice (AMA), the potential for these patients to suffer adverse health outcomes is of major concern. OBJECTIVE: To examine 30-day hospital readmission and mortality rates for medical patients who left the hospital AMA and identify independent risk factors associated with these outcomes. DESIGN: A 5-year retrospective cohort of all patients discharged from a Veterans Administration (VA) hospital. SUBJECTS: The final study sample included 1,930,947 medical admissions to 129 VA hospitals from 2004 to 2008; 32,819 patients (1.70%) were discharged AMA. MEASUREMENTS: Primary outcomes of interest were 30-day mortality and 30-day all-cause hospital readmission. RESULTS: Compared to discharges home, AMA patients were more likely to be black, have low income, and have co-morbid alcohol abuse (for all, Chi(2) df = 1, p < 0.001). AMA patients had a higher 30-day readmission rate (17.7% vs. 11.0%, p < 0.001) and higher 30-day mortality rate (0.75% vs. 0.61%, p = 0.001). In Cox proportional hazard modeling controlling for demographics and co-morbidity, the largest hazard for patients having a 30-day readmission is leaving AMA (HR = 1.35, 95% CI 1.32-1.39). Similar modeling for 30-day mortality reveals a nearly significant increased hazard rate for patients discharged AMA (HR = 1.10, 95% CI 0.98-1.24). CONCLUSIONS: Due to the higher risk of adverse outcomes, hospitals should target AMA patients for post-discharge interventions, such as phone follow-up, home visits, or mental health counseling to improve outcomes.

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BACKGROUND: Two popular quality improvement (QI) approaches in health care are Lean and Six Sigma. Hospitals continue to adopt these QI approaches-or the hybrid Lean Sigma approach-with little knowledge on how well they produce sustainable improvements. A systematic literature review was conducted to determine whether Lean, Six Sigma, or Lean Sigma have been effectively used to create and sustain improvements in the acute care setting. METHODS: Databases were searched for articles published in the health care, business, and engineering literatures. Study inclusion criteria required identification of a Six Sigma, Lean, or Lean Sigma project; QI efforts focused on hospitalized patients; descriptions of project improvements; and reported results. Depending on the quality of data reported, articles were classified as summary reports, pre-post observational studies, or time-series reports. RESULTS: Database searches identified 539 potential articles. After review of titles, abstracts, and full text, 47 articles met inclusion criteria--10 articles summarized multiple projects, 12 reported Lean projects, 20 reported Six Sigma projects, and 5 reported Lean Sigma projects. Generally, the studies provided limited data, with only 15 articles providing any sort of follow-up data; of the 15, only 3 report a follow-up period greater than two years. CONCLUSION: Lean, Six Sigma, and Lean Sigma as QI approaches can aid institutions in tackling a wide variety of problems encountered in acute care. However, the true impact of these approaches is difficult to judge, given that the lack of rigorous evaluation or clearly sustained improvements provides little evidence supporting broad adoption. There is still a need for future work that will improve the evidence base for understanding more about QI approaches and how to achieve sustainable improvement.

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We demonstrate, for the first time, a robust novel polydimethylsiloxane (PDMS) chip that can provide controlled pulsatile release of DNA based molecules, proteins and oligonucleotides without external stimuli or triggers. The PDMS chip with arrays of wells was constructed by replica molding. Poly(lactic acid-co-glycolic acid) (PLGA) polymer films of varying composition and thickness were used as seals to the wells. The composition, molecular weight and thickness of the PLGA films were all parameters used to control the degradation rate of the seals and therefore the release profiles. Degradation of the films followed the PLGA composition order of 50:50 PLGA>75:25 PLGA>85:15 PLGA at all time-points beyond week 1. Scanning electron microscopy images showed that films were initially smooth, became porous and ruptured as the osmotic pressure pushed the degrading PLGA film outwards. Pulsatile release of DNA was controlled by the composition and thickness of the PLGA used to seal the well. Transfection experiments in a model Human Embryonic Kidney 293 (HEK293) cell line showed that plasmid DNA loaded in the wells was functional after pulsatile release in comparison to control plasmid DNA at all time-points. Thicker films degraded faster than thinner films and could be used to fine-tune the release of DNA over day length periods. Finally the PDMS chip was shown to provide repeated sequential release of CpG oligonucleotides and a model antigen, Ovalbumin (OVA), indicating significant potential for this device for vaccinations or applications that require defined complex release patterns of a variety of chemicals, drugs and biomolecules.

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