Acute Care Hospitals In Pennsylvania Research Articles

A comparison of critical access hospitals and other rural acute care hospitals in Pennsylvania.

As the Flex Program celebrates its 25th anniversary, we examined changes in critical access hospital (CAH) financial performance, investigated whether CAH status has reduced hospitals' financial vulnerability, and identified factors influencing financial performance. We collected data on acute care hospitals in Pennsylvania's rural counties for 2000-20. Our sample contained 1,444 hospital-year observations. We used trend analysis to compare the financial performance of CAHs and rural prospective payment system (PPS) hospitals (non-CAHs). We investigated the effect of CAH status on financial performance and identified the time-variant factors impacting financial performance using fixed-effects regression analysis. The median total margin of CAHs lagged behind that of non-CAHs. When compared to non-CAH costs over the same period, the median cost per patient day incurred by CAHs has increased, with the rate of increase being significantly higher in the most recent decade. Our findings show that while CAH status does not appear to have a direct impact on the total margin, it is significantly associated with a higher cost per patient day. CAHs in Pennsylvania appear to be facing a double whammy of declining margins and rising costs compared to non-CAHs. Our findings demonstrate how crucial the Flex program has been in sustaining CAHs in Pennsylvania ever since its inception. Our findings have implications for rural health care delivery as well. While providing financial support and operational flexibility to CAHs should be a continuing policy priority, a long-term policy goal should be to envision an economic development strategy that capitalizes on the unique strengths of each of the rural archetypes.

Emergency departments: The gatekeepers of admissions in Pennsylvania's rural hospitals

Study objectiveTo analyze trends in admission rates and the proportion of admissions via the ED at rural hospitals in Pennsylvania and to identify factors that may impact admission rates. MethodsWe use retrospective, longitudinal data on rural acute care hospitals in Pennsylvania for 2000–19 to investigate temporal patterns in admission rates and the proportion of admissions via the ED. Regression analysis is then used to identify factors that may impact admission rates. ResultsIn general admission rates, which averaged 14.5%, experienced a gradual decline (Change: −16.9%; from 15.7% to 13%) between 2000 and 2019. The proportion of hospital admissions via the ED, which averaged 64.9%, increased steadily (21%; from 57% to 69%). Critical access hospitals experienced a sharp decline in admissions via the ED (−49.1%) and admission rates (−55.3%). The fixed-effects regression model revealed several hospital- and ED-level characteristics were significantly associated with admission rate. ConclusionsEmergency departments are the gatekeepers of admissions at rural acute care hospitals in Pennsylvania. Many hospitals in rural Pennsylvania, including CAHs, are admitting most of their patients through the ED, concomitant with a significant decline in admissions and admission rates. This highlights the need to strengthen primary care practices serving rural Pennsylvania as well as the need to improve rural emergency and trauma systems. In the short to medium term, policy makers should explore innovative ways to fund smaller hospitals, especially CAHs, to develop level IV trauma center capabilities.

Do EHR and HIE deliver on their promise? Analysis of Pennsylvania acute care hospitals

BackgroundThe HITECH Act of 2009 promoted the use of health information technology (HIT). There is limited research on the effect of health information exchange (HIE) on healthcare outcomes and cost. Analyzing data from the recent past provides us an excellent opportunity to determine EHR and HIE's impact on hospital operations. PurposeTo investigate association between HIT (EHR and HIE) and quality of care, hospital efficiency, and patient flow. MethodologyMultivariable regression models using panel data with year fixed effects and hospital individual effects were used. Outcome variables were readmission index and mortality index (quality of care), cost per inpatient day and cost per inpatient admission (hospital efficiency), and average length of stay (patient flow). We use two variables to measure HIT usage – proportion of functionalities owned/utilized under electronic health records (EHR) and HIE. We use four years of data (2014-17) on 115 acute care hospitals in Pennsylvania from five different data sources. ResultsWe find evidence for efficiency (lower costs) improvement associated with HIE and for EHR associated with reduced mortality. Also, HIE is adversely associated with mortality. Other effects were not significant. ConclusionEHR and HIE usage in the hospitals may not be enough or optimal. The healthcare system may also suffer from integration issues. Diffusion of technology is a slow process and users may take time to understand and learn how to apply effectively. Managers and policy makers must be wary of the short- and long-term effect of technology investments on hospital efficiency and quality of care.

In-Hospital Substance Use and Possession: A Study of Events From 38 Acute Care Hospitals in Pennsylvania

Patients’ substance use and possession at acute care hospitals is an understudied topic. To learn more about this topic, we queried the Pennsylvania Patient Safety Reporting System (PA-PSRS) for events that occurred during calendar year 2018. We identified 106 reports from 38 acute care hospitals (excluding psychiatric, detox, and behavioral health units and facilities) where a patient possessed and/or misused a substance (e.g., heroin, oxycodone, liquor). We analyzed these reports to better understand how hospital personnel attempt to prevent in-hospital substance use and manage patients who are at risk for using a substance. We explored a range of variables, including antecedent conditions and hospital personnel’s actions post- detection of a patient’s substance use or possession. We found that a relatively low percentage of patients (26%) were identified as having a prior history of substance use, despite later using or being in possession of a substance in hospital. In our sample, patients frequently acquired the substances from visitors, more than half of the substances were consumed intravenously, and opioids were the most common substance. The most prevalent actions taken by hospital personnel were conducting searches for substances and paraphernalia, use of a patient sitter or video monitor, moving patients to a different room, and implementing visitor restrictions. Based on our findings and previous research, hospitals should consider increasing their use of substance use disorder (SUD) screening tools, pharmacotherapy, and referring patients to treatment. Overall, our results can help personnel better understand the nature of and strategies that may reduce the likelihood of in-hospital substance use. Keywords: substance use, paraphernalia, substance use disorder, in-hospital, addiction, opioid, risk mitigation, patient safety

Association of Race/Ethnicity With Hospital Discharge Disposition After Elective Total Knee Arthroplasty

Total knee arthroplasty (TKA) is one of the most common elective procedures performed in adults with end-stage arthritis. Racial disparities in TKA outcomes have been described in the literature. To assess the association of race/ethnicity with discharge disposition and hospital readmission after elective primary TKA and to assess the association of nonhome discharge disposition with hospital readmission risk. This retrospective cohort study used data from the Pennsylvania Health Care Cost Containment Council Database, a large regional database that included demographic data from all discharges of patients who underwent elective primary TKA in 170 nongovernmental acute care hospitals in Pennsylvania from April 1, 2012, to September 30, 2015. Data analyses were conducted from September 29, 2017, to November 29, 2017. Patient race/ethnicity and discharge disposition. Discharge disposition and 90-day hospital readmission. Among 107 768 patients, 7287 (6.8%) were African American, 68 372 (63.4%) were women, 46 420 (43.1%) were younger than 65 years, and 60 636 (56.3%) were insured by Medicare. In multivariable logistic regression, among patients younger than 65 years, African American patients were more likely than white patients to be discharged to inpatient rehabilitation facility (IRF) (adjusted relative risk ratio [aRRR], 2.49 [95% CI, 1.42-4.36]; P = .001) or a skilled nursing facility (SNF) (aRRR, 3.91 [95% CI, 2.17-7.06]; P < .001) and had higher odds of 90-day hospital readmission (adjusted odds ratio [aOR], 1.30 [95% CI, 1.02-1.67]; P = .04). Compared with white patients 65 years or older, African American patients 65 years or older were more likely to be discharged to SNF (aRRR, 3.30 [95% CI, 1.81-6.02]; P < .001). In both age groups, discharge to an IRF (age <65 years: aOR, 3.62 [95% CI, 2.33-5.64]; P < .001; age ≥65 years: aOR, 2.85 [95% CI, 2.25-3.61]; P < .001) or SNF (age <65 years: aOR, 1.91 [95% CI, 1.37-2.65]; P < .001; age ≥65 years: aOR, 1.55 [95% CI, 1.27-1.89]; P < .001) was associated with higher odds of 90-day readmission. This cohort study found that race/ethnicity was associated with higher odds of discharge to an IRF or SNF for postoperative care after primary TKA. Among patients younger than 65 years, African American patients were more likely than white patients to be readmitted to the hospital within 90 days. Discharge to an IRF or SNF for postoperative care and rehabilitation was also associated with a higher risk of readmission to an acute care hospital.

An administrative model for benchmarking hospitals on their 30-day sepsis mortality

BackgroundGiven the increased attention to sepsis at the population level there is a need to assess hospital performance in the care of sepsis patients using widely-available administrative data. The goal of this study was to develop an administrative risk-adjustment model suitable for profiling hospitals on their 30-day mortality rates for patients with sepsis.MethodsWe conducted a retrospective cohort study using hospital discharge data from general acute care hospitals in Pennsylvania in 2012 and 2013. We identified adult patients with sepsis as determined by validated diagnosis and procedure codes. We developed an administrative risk-adjustment model in 2012 data. We then validated this model in two ways: by examining the stability of performance assessments over time between 2012 and 2013, and by examining the stability of performance assessments in 2012 after the addition of laboratory variables measured on day one of hospital admission.ResultsIn 2012 there were 115,213 sepsis encounters in 152 hospitals. The overall unadjusted mortality rate was 18.5%. The final risk-adjustment model had good discrimination (C-statistic = 0.78) and calibration (slope and intercept of the calibration curve = 0.960 and 0.007, respectively). Based on this model, hospital-specific risk-standardized mortality rates ranged from 12.2 to 24.5%. Comparing performance assessments between years, correlation in risk-adjusted mortality rates was good (Pearson’s correlation = 0.53) and only 19.7% of hospitals changed by more than one quintile in performance rankings. Comparing performance assessments after the addition of laboratory variables, correlation in risk-adjusted mortality rates was excellent (Pearson’s correlation = 0.93) and only 2.6% of hospitals changed by more than one quintile in performance rankings.ConclusionsA novel claims-based risk-adjustment model demonstrated wide variation in risk-standardized 30-day sepsis mortality rates across hospitals. Individual hospitals’ performance rankings were stable across years and after the addition of laboratory data. This model provides a robust way to rank hospitals on sepsis mortality while adjusting for patient risk.

Physician-Level Variation in Outcomes of Mechanically Ventilated Patients.

Physicians are increasingly being held accountable for patient outcomes, yet their specific contribution to the outcomes remains uncertain. To determine variation in outcomes of mechanically ventilated patients among intensivists, as well as associations between intensivist experience and patient outcomes. We performed a retrospective cohort study of mechanically ventilated Medicare fee-for-service patients in acute care hospitals in Pennsylvania using administrative, clinical, and physician data from Centers for Medicare and Medicaid Services and the American Medical Association from 2008 and 2009. We identified intensivists by training background, board certification, and claims for services provided to patients admitted to an intensive care unit. We assigned patients to intensivists for outcome attribution based on submitted claims for critical care and in-patient services. We estimated the physician-specific adjusted odds ratios (ORs) for 30-day mortality using a hierarchical model with a random effect for physician, adjusted for patient and hospital characteristics. We tested for independent association of physician experience with patient outcomes using mixed-effects regression for the primary outcome of 30-day mortality. We defined physician experience in two ways: years since training completion ("duration") and annual number of mechanically ventilated patients ("volume"). We assigned 345 physicians to 11,268 patients. The 30-day mortality was 43% and median hospital length of stay was 11 days (interquartile range = 6-18). The physician adjusted OR varied from 0.72 to 1.64 (median = 0.99; interquartile range = 0.92-1.09). A total of 48% of physicians was outliers, with an adjusted OR significantly different from 1. However, among intensivists, physician experience was not associated with 30-day mortality (duration OR = 1.00 per additional year; 95% confidence interval = 1.00-1.01; volume OR = 1.00 per additional patient; 95% confidence interval = 1.00-1.00). Intensivists independently contribute to outcomes of Medicare patients who undergo mechanical ventilation, as evidenced by the variation in risk-adjusted mortality across intensivists. However, physician experience does not underlie this relationship between intensivists, suggesting the need to identify modifiable physician factors to improve outcomes.

Diffusion of Evidence-based Intensive Care Unit Organizational Practices. A State-Wide Analysis.

Several intensive care unit (ICU) organizational practices have been associated with improved patient outcomes. However, the uptake of these evidence-based practices is unknown. To assess diffusion of ICU organizational practices across the state of Pennsylvania. We conducted two web-based, cross-sectional surveys of ICU organizational practices in Pennsylvania acute care hospitals, in 2005 (chief nursing officer respondents) and 2014 (ICU nurse manager respondents). Of 223 eligible respondents, nurse managers from 136 (61%) medical, surgical, mixed medical-surgical, cardiac, and specialty ICUs in 98 hospitals completed the 2014 survey, compared with 124 of 164 (76%) chief nursing officers in the 2005 survey. In 2014, daytime physician staffing models varied widely, with 23 of 136 (17%) using closed models and 33 (24%) offering no intensivist staffing. Nighttime intensivist staffing was used in 37 (27%) ICUs, 38 (28%) used nonintensivist attending staffing, and 24 (18%) had no nighttime attending physicians. Daily multidisciplinary rounds occurred in 93 (68%) ICUs. Regular participants included clinical pharmacists in 68 of 93 (73%) ICUs, respiratory therapists in 62 (67%), and advanced practitioners in 37 (39%). Patients and family members participated in rounds in 36 (39%) ICUs. Clinical protocols or checklists for mechanically ventilated patients were available in 128 of 133 (96%) ICUs, low tidal volume ventilation for acute respiratory distress syndrome in 54 of 132 (41%) ICUs, prone positioning for severe acute respiratory distress syndrome in 37 of 134 (28%) ICUs, and family meetings in 19 of 134 (14%) ICUs. Among 61 ICUs that responded to both surveys, there was a significant increase in the proportion of ICUs using nighttime in-ICU attending physicians (23 [38%] in 2005 vs. 30 [49%] in 2014; P = 0.006). The diffusion of evidence-based ICU organizational practices has been variable across the state of Pennsylvania. Only half of Pennsylvania ICUs have intensivists dedicated to the ICU. Variable numbers use clinical protocols for life-saving therapies, and few use structured family engagement strategies. In contrast, the diffusion of non-evidence-based practices, including overnight ICU attending physician staffing, is increasing. Future research should focus on promoting implementation of organizational evidence to promote high-quality ICU care.

Development of a list of high-risk operations for patients 65 years and older.

No consensus exists regarding the definition of high-risk surgery in older adults. An inclusive and precise definition of high-risk surgery may be useful for surgeons, patients, researchers, and hospitals. To develop a list of high-risk operations. Retrospective cohort study and modified Delphi procedure. The setting included all Pennsylvania acute care hospitals (Pennsylvania Health Care Cost Containment Council [PHC4] April 1, 2001, to December 31, 2007) and a nationally representative sample of US acute care hospitals (Nationwide Inpatient Sample [NIS], Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality January 1, 2001, to December 31, 2006). Patients included were those 65 years and older admitted to PHC4 hospitals and those 18 years and older admitted to NIS hospitals. We identified International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) procedure codes associated with at least 1% inpatient mortality in the PHC4. We used a modified Delphi procedure with 5 board-certified surgeons to further refine this list by excluding nonoperative procedures and operations that were unlikely to be the proximate cause of mortality and were instead a marker of critical illness (eg, tracheostomy). We then cross-validated this list of ICD-9-CM codes in the NIS. Modified Delphi procedure consensus of at least 4 of 5 panelists and proportion agreement in the NIS. Among 4,739,522 admissions of patients 65 years and older in the PHC4, a total of 2,569,589 involved a procedure, encompassing 2853 unique procedures. Of 1130 procedures associated with a crude inpatient mortality of at least 1%, 264 achieved consensus as high-risk operations by the modified Delphi procedure. The observed inpatient mortality in the NIS was at least 1% for 227 of 264 procedures (86%) in patients 65 years and older. The pooled inpatient mortality for these identified high-risk procedures performed on patients 65 years and older was double the pooled inpatient mortality for correspondingly identified high-risk operations for patients younger than 65 years (6% vs 3%). We developed a list of procedure codes to identify high-risk surgical procedures in claims data. This list of high-risk operations can be used to standardize the definition of high-risk surgery in quality and outcomes-based studies and to design targeted clinical interventions.

Recommendations For Prevention Of Medical Errors Through An Empirical Investigation Of The Error Reporting Systems Within Acute Care Hospitals In Pennsylvania

The researcher investigated the procedures taken by healthcare administrators within twenty-two Pennsylvania acute care hospitals with respect to the prevention of medical errors. Structured interview questions provided relevant data in relation to how healthcare administrators could structure the workplace environment in hopes to prevent the number of medical errors that occur in acute care hospitals in Pennsylvania. Recommendations for prevention include conducting needs assessments the areas of cultural assessment, error reporting system assessment, workplace environment assessment, corrective action procedures assessment, and policies and procedures assessment. Recommendations and implications for conducting the needs assessments are provided in this paper in an effort to bring attention to actions that may be taken by hospital administrators in hopes of reducing the number of medical errors that occur within acute care hospitals in Pennsylvania.

Elevated Admission Glucose and Mortality in Patients With Acute Pulmonary Embolism

OBJECTIVEAlthough associated with adverse outcomes in other cardiopulmonary conditions, the prognostic value of elevated glucose in patients with acute pulmonary embolism (PE) is unknown. We sought to examine the association between glucose levels and mortality and hospital readmission rates for patients with PE.RESEARCH DESIGN AND METHODSWe evaluated 13,621 patient discharges with a primary diagnosis of PE from 185 acute care hospitals in Pennsylvania (from January 2000 to November 2002). Admission glucose levels were analyzed as a categorical variable (≤110, >110–140, >140–170, >170–240, and >240 mg/dL). The outcomes were 30-day all-cause mortality and hospital readmission. We used random-intercept logistic regression to assess the independent association between admission glucose levels and mortality and hospital readmission, adjusting for patient (age, sex, race, insurance, comorbid conditions, severity of illness, laboratory parameters, and thrombolysis) and hospital (region, size, and teaching status) factors.RESULTSElevated glucose (>110 mg/dL) was present in 8,666 (63.6%) patients. Patients with a glucose level ≤110, >110–140, >140–170, >170–240, and >240 mg/dL had a 30-day mortality of 5.6, 8.4, 12.0, 15.6, and 18.3%, respectively (P < 0.001). Compared with patients with a glucose level ≤110 mg/dL, the adjusted odds of dying were greater for patients with a glucose level >110–140 (odds ratio 1.19 [95% CI 1.00–1.42]), >140–170 (1.44 [1.17–1.77]), >170–240 (1.54 [1.26–1.90]), and >240 mg/dL (1.60 [1.26–2.03]), with no difference in the odds of hospital readmission.CONCLUSIONSIn patients with acute PE, elevated admission glucose is common and independently associated with short-term mortality.

An Empirical Investigation Into The Administrative Procedures Taken In Response To The Detection Of Medical Errors Within Acute Care Hospitals In Pennsylvania

This researcher investigates the procedures taken by healthcare administrators within Pennsylvania acute care hospitals with respect to the detection of medical errors in order to provide corrective measures. In response to structured interview questions, the overwhelming majority of research participants stated that the procedures for corrective actions focused upon various training interventions as deemed appropriate by management. However, scholarly literature states that the majority of medical errors do not occur due to the lack of competence, skills, or knowledge of healthcare professionals. Thus, using training interventions to solve non-training problems may not prove effective. The outcome of the study has lead to several important implications for the healthcare industry. Lastly, further research was suggested as it relates to patient safety and the reduction of medical errors.

Incorporating health outcomes in Pennsylvania hospital efficiency: an additive super-efficiency DEA approach

The health care sector is one of the fastest growing sectors in the United States. Researchers are interested in conducting studies in the area of health economics in order to propose solutions to curb the rapid increase in health care spending and to improve the efficiency of the health care system in the United States. Specifically, hospital efficiency is one important research area in health economics. In this paper, data envelopment analysis (DEA) is used to assess hospital efficiency. An additive super-efficiency model is presented and applied to a sample of general acute care hospitals in Pennsylvania. In addition to the conventional choice of input and output variables, we include the survival rate as a quality measure of health outcome in the set of output variables. Thus our model takes both the quantity and the quality of the output into account. With the results obtained from our proposed DEA model, inefficiencies can be identified for hospitals to address without sacrificing the quality of care.

Hospital Protocols for the Inpatient Care of Older Adults: Results from a Statewide Survey

To assess the prevalence of protocols or guidelines for selected domains of inpatient care for older adults; to explore associations between hospital characteristics and adoption of these guidelines or protocols. Telephone- and Web-based questionnaire. General acute care hospitals in Pennsylvania. Chief nursing officers, directors of nursing, other hospital executives. Questionnaire items assessed the presence of written protocols or guidelines for selected processes of inpatient care; written guidelines, protocols, or pathways for hip fracture care; and inpatient geriatric consultation. Responses were obtained from 103 of 147 hospitals (70%) between June 21, 2009, and October 12, 2009. The prevalence of written protocols for general hospital practices (e.g., dosing of preoperative antibiotics, deep venous thrombosis prophylaxis) ranged from 84 of 98 (86%) to 90 of 97 (93%) respondents. Twenty of 95 (21%) and 16 of 94 (17%) respondents reported guidelines for the assessment of risk factors for delirium and for routine screening for delirium. Sixty-six of 92 respondents (72%) reported the presence of a written protocol, guideline, or pathway for hip fracture, and 61 of 100 respondents (39%) confirmed availability of inpatient geriatric consultation. No systematic differences were found in survey responses between facilities on the basis of geriatric consultation availability, hospital size, or teaching status. Hospitals vary in their adoption of protocols and guidelines for the care of older adults. Broad opportunities may exist to improve the quality of inpatient care for older adults through better dissemination and implementation of guidelines and protocols for selected geriatric conditions.

Increased Mortality and Length of Stay Among Patients With Inflammatory Bowel Disease and Hospital-Acquired Infections

Hospitalized patients with inflammatory bowel disease (IBD) could be at increased risk for hospital-acquired infections (HAIs). By using HAI outcome data from Pennsylvania, we examined the influence of HAIs on in-patient mortality and length of stay (LOS) in the hospital among patients with IBD. Data were generated by linking the Clinical Research Databases from CareFusion (formerly MediQual), which includes all acute care hospitals in Pennsylvania, with publicly reported HAI data from Pennsylvania. The study population included all patients discharged in 2004 with International Classification of Diseases, 9th Clinical Modification codes of 555.x or 556.x (2324 IBD cases from 161 hospitals). Controls were selected using risk-score matching with a 5:1 ratio. Mortality and LOS end points were estimated and corroborated with regression methods. Among the IBD patients studied, there were 20 deaths and 22 reported cases of HAI. The mortality from HAI among patients with IBD was 13.6%, compared with 0.9% among controls (P = .0146, Fisher exact test). The odds ratio for mortality was 17.2 (95% confidence interval, 1.7-174.3). The median LOS for patients with IBD and HAI was 22 days, versus 6 days for controls (P < .001, Wilcoxon). Of the 22 cases with HAIs, 15 were urinary tract infections, 5 were blood stream infections, and 2 were from multiple sources. Results from a population-based data set indicate that mortality and LOS are increased among IBD patients who develop HAIs. A majority of the HAIs were from urinary sources. Although HAIs are low-frequency events, increased vigilance to avoid HAI among patients with IBD could improve outcomes.

Acute care practices relevant to quality end-of-life care: a survey of Pennsylvania hospitals

BackgroundImproving end-of-life care in the hospital is a national priority.PurposeTo explore the prevalence and reasons for implementation of hospital-wide and intensive care unit (ICU) practices relevant to quality care in...

The Effect of Multidisciplinary Care Teams on Intensive Care Unit Mortality

Critically ill patients are medically complex and may benefit from a multidisciplinary approach to care. We conducted a population-based retrospective cohort study of medical patients admitted to Pennsylvania acute care hospitals (N = 169) from July 1, 2004, to June 30, 2006, linking a statewide hospital organizational survey to hospital discharge data. Multivariate logistic regression was used to determine the independent relationship between daily multidisciplinary rounds and 30-day mortality. A total of 112 hospitals and 107 324 patients were included in the final analysis. Overall 30-day mortality was 18.3%. After adjusting for patient and hospital characteristics, multidisciplinary care was associated with significant reductions in the odds of death (odds ratio [OR], 0.84; 95% confidence interval [CI], 0.76-0.93 [P = .001]). When stratifying by intensivist physician staffing, the lowest odds of death were in intensive care units (ICUs) with high-intensity physician staffing and multidisciplinary care teams (OR, 0.78; 95% CI, 0.68-0.89 [P < .001]), followed by ICUs with low-intensity physician staffing and multidisciplinary care teams (OR, 0.88; 95% CI, 0.79-0.97 [P = .01]), compared with hospitals with low-intensity physician staffing but without multidisciplinary care teams. The effects of multidisciplinary care were consistent across key subgroups including patients with sepsis, patients requiring invasive mechanical ventilation, and patients in the highest quartile of severity of illness. Daily rounds by a multidisciplinary team are associated with lower mortality among medical ICU patients. The survival benefit of intensivist physician staffing is in part explained by the presence of multidisciplinary teams in high-intensity physician-staffed ICUs.

Development and Validation of Hospital “End-of-Life” Treatment Intensity Measures

Health care utilization among decedents is increasingly used as a measure of health care efficiency, but decedent-based measures may be biased estimates of care received by "dying" patients. To develop and validate new measures of hospital "end-of-life" treatment intensity. Retrospective cohort study using Pennsylvania Health Care Cost Containment Council (PHC4) discharge data (April 2001-March 2005) and Centers for Medicare and Medicaid Services (CMS) data (January 1999-December 2003). Patients 65 and older admitted to 174 Pennsylvania acute care hospitals. Hospital-specific standardized ratios of intensive care unit (ICU) and life-sustaining treatment (LST) use among terminal admissions (decedents) and admissions with a high probability of dying, and spending and use of hospitals, ICUs, and physicians among patients in their last 6 months of life. There was marked between-hospital variation in the use of the ICU and LSTs among decedents and admissions with high probability of dying. All hospital decedent and high probability of dying measures were highly correlated (P < 00001). In principal components factor analysis, all 4 of the last-6-months cohort-based measures, the decedent and high-risk admission-based ICU measures, and 8 of the 12 decedent and high probability of dying LST measures loaded onto a single factor, explaining 42% of the variation in the data. Hospitals' end-of-life intensity varies in the use of specific life-sustaining treatments that are somewhat emblematic of aggressive end-of-life care. End-of-life intensity is a relatively stable hospital attribute that is robust to multiple measurement approaches.

The Relationship between Hospital Volume and Mortality in Mechanical Ventilation: An Instrumental Variable Analysis

To examine the relationship between hospital volume and mortality for nonsurgical patients receiving mechanical ventilation. Pennsylvania state discharge records from July 1, 2004, to June 30, 2006, linked to the Pennsylvania Department of Health death records and the 2000 United States Census. We categorized all general acute care hospitals in Pennsylvania (n=169) by the annual number of nonsurgical, mechanically ventilated discharges according to previous criteria. To estimate the relationship between annual volume and 30-day mortality, we fit linear probability models using administrative risk adjustment, clinical risk adjustment, and an instrumental variable approach. Using a clinical measure of risk adjustment, we observed a significant reduction in the probability of 30-day mortality at higher volume hospitals (>or=300 admissions per year) compared with lower volume hospitals (<300 patients per year; absolute risk reduction: 3.4%, p=.04). No significant volume-outcome relationship was observed using only administrative risk adjustment. Using the distance from the patient's home to the nearest higher volume hospital as an instrument, the volume-outcome relationship was greater than observed using clinical risk adjustment (absolute risk reduction: 7.0%, p=.01). Care in higher volume hospitals is independently associated with a reduction in mortality for patients receiving mechanical ventilation. Adequate risk adjustment is essential in order to obtained unbiased estimates of the volume-outcome relationship.

Predictors of early hospital readmission after acute pulmonary embolism.

Risk factors for early mortality after pulmonary embolism (PE) are widely known. However, it is uncertain which factors are associated with early readmission after PE. We sought to identify predictors of readmission after an admission for PE. We studied 14 426 patient discharges with a primary diagnosis of PE from 186 acute care hospitals in Pennsylvania from January 1, 2000, to November 30, 2002. The outcome was readmission within 30 days of presentation for PE. We used a discrete proportional odds model to study the association between time to readmission and patient factors (age, sex, race, insurance, discharge status, and severity of illness), thrombolysis, and hospital characteristics (region, teaching status, and number of beds). Overall, 2064 patient discharges (14.3%) resulted in a readmission within 30 days of presentation for PE. The most common reasons for readmission were venous thromboembolism (21.9%), cancer (10.8%), pneumonia (5.2%), and bleeding (5.0%). In multivariable analysis, African American race (odds ratio [OR], 1.19; 95% confidence interval [CI], 1.02-1.38), Medicaid insurance (OR, 1.54; 95% CI, 1.31-1.81), discharge home with supplemental care (OR, 1.40; 95% CI, 1.27-1.54), leaving the hospital against medical advice (OR, 2.84; 95% CI, 1.80-4.48), and severity of illness were independently associated with readmission; readmission also varied by hospital region. Early readmission after PE is common. African American race, Medicaid insurance, severity of illness, discharge status, and hospital region are significantly associated with readmission. The high readmission rates for venous thromboembolism and bleeding suggest that readmission may be linked to suboptimal quality of care in the management of PE.