Association Of Hospital Characteristics Research Articles

Abstract 11679: Post-resuscitation Care and Survival After In-hospital Cardiac Arrest

Background: More than 40% of in-hospital cardiac arrest (IHCA) deaths occur in patients during the post-resuscitation period following return of spontaneous circulation (ROSC). However, the degree to which post-resuscitation survival varies across hospitals and whether this variation is explained by hospital characteristics is unknown. Methods: We identified 80,201 patients within Get with the Guidelines-Resuscitation who achieved ROSC following IHCA. Using a multivariable hierarchical regression model, we calculated risk adjusted rates of post-resuscitation survival for each hospital and quantified hospital variation in post-resuscitation survival using median odds ratio (OR). We also assessed the association of hospital characteristics with post-resuscitation survival. Results: The mean age was 65.5 years, 57% were men, and 23% were black. Nearly 1 in 4 (23.0%) patients had an initial shockable rhythm. Overall, 33.5% of patients with ROSC survived to discharge, but the rate of post-resuscitation survival varied across hospitals (median hospital rate: 33.3%; interquartile range: 29.9%-36.7%; total range: 18.9%-55.1%). The median OR was 1.35 (95% CI: 1.30, 1.39, Figure), which suggests that post-resuscitation survival for 2 patients with similar covariates at 2 randomly selected hospitals varied by 35%. Except U.S. census region (P<0.001), no hospital characteristic was associated with hospital rates of post-resuscitation survival including, academic status, total bed number, hospital ownership, use of intensivists; number and proportion of intensive care unit [ICU] beds, neurological services, and coronary angiography capability. Conclusions: Rates of post-resuscitation survival vary among U.S. hospitals. However, this variation is not explained by hospital structural characteristics, thus highlighting a pressing need to identify post-resuscitation best practices at top-performing hospitals in post-cardiac arrest care.

Inpatient Laparoscopic Hysterectomy in the United States: Trends and Factors Associated With Approach Selection

To examine utilization patterns of different laparoscopic approaches in inpatient hysterectomy and identify patient and hospital characteristics associated with the selection of specific laparoscopic approaches. Using data from the 2007 to 2012 National (Nationwide) Inpatient Sample (NIS), we identified adult women undergoing inpatient laparoscopic hysterectomy for nonobstetric indications based on International Classification of Diseases, Ninth Revision, Clinical Modification codes. Benign cases were categorized based on laparoscopic approach, classified as total laparoscopic hysterectomy (TLH), laparoscopic-assisted vaginal hysterectomy (LAVH), or laparoscopic supracervical hysterectomy (LSH). We assessed changes in the use of these approaches during 2007 to 2012, and used multinomial logistic regression to examine the association of patient and hospital characteristics with the choice of laparoscopic approach in 2012. The NIS sample weights were applied to generate nationally representative estimates. Retrospective study (Canadian Task Force classification III). Hospital inpatient care nationwide. Female adult patients in the NIS database who underwent an inpatient laparoscopic hysterectomy between 2007 and2012. Inpatient laparoscopic hysterectomy. Of the inpatient laparoscopic hysterectomies performed in 2012, 83.2% were for benign indications. The TLH approach accounted for 48.3% of all laparoscopic hysterectomies, followed by LAVH at 37.3% and LSH at 14.4%. Robotic assistance was reported in 45.0% of all cases and 72.3% of malignant hysterectomies. An examination of temporal trends during 2007 to 2012 demonstrates a shift in the laparoscopic approach from LAVH toward TLH, with a slight decrease in LSH. Patient race/ethnicity, income, indication for hysterectomy, and comorbid conditions, as well as hospital teaching status, urban/rural location, bed size, type of ownership, and geographic region, were significantly associated with the choice of laparoscopic approach. Benign laparoscopic hysterectomy is increasingly performed as TLH rather than LAVH. In addition to clinical factors, the selection of laparoscopic approach is influenced by patient socioeconomic and hospital characteristics.

Associations of hospital characteristics with nosocomial pneumonia after cardiac surgery can impact on standardized infection rates.

To identify hospital-level factors associated with post-cardiac surgical pneumonia for assessing their impact on standardized infection rates (SIRs), we studied 43 691 patients in a cardiac surgery registry (2001-2011) in 16 hospitals. In a logistic regression model for pneumonia following cardiac surgery, associations with hospital characteristics were quantified with adjustment for patient characteristics while allowing for clustering of patients by hospital. Pneumonia rates varied from 0·7% to 12·4% across hospitals. Seventy percent of variability in the pneumonia rate was attributable to differences in hospitals in their long-term rates with the remainder attributable to within-hospital differences in rates over time. After adjusting for patient characteristics, the pneumonia rate was found to be higher in hospitals with more registered nurses (RNs)/100 intensive-care unit (ICU) admissions [adjusted odds ratio (aOR) 1·2, P = 0·006] and more RNs/available ICU beds (aOR 1·4, P < 0·001). Other hospital characteristics had no significant association with pneumonia. SIRs calculated on the basis of patient characteristics alone differed substantially from the same rates calculated on the basis of patient characteristics and the hospital characteristic of RNs/100 ICU admissions. Since SIRs using patient case-mix information are important for comparing rates between hospitals, the additional allowance for hospital characteristics can impact significantly on how hospitals compare.

Abstract A67: Do hospital characteristics explain racial/ethnic disparities in mortality after breast cancer diagnosis: The California Breast Cancer Survivorship Consortium

Abstract Introduction: Disparities in breast cancer mortality persist between racial/ethnic groups. Little is known about the role of the treatment environment, specifically the characteristics of the hospital reporting a patient's breast cancer diagnosis. Differential access to high quality care contributes to disparities in treatment and outcomes. The California Breast Cancer Survivorship Consortium (CBCSC) integrated data on patient demographics, behavioral and reproductive characteristics from patient interviews, and on tumor characteristics, treatment, and follow-up from the California Cancer Registry. This study leveraged the large size and racial/ethnic diversity to examine the extent to which hospital characteristics explain racial/ethnic disparities in mortality following breast cancer diagnosis. Methods: Using data from five of the six studies in the CBCSC, the study sample included 4,624 non-Latina whites, 1,849 Latinas, 1,832 African-Americans, and 1,333 Asian Americans diagnosed with Stage I-IV breast cancer between 1993 and 2007. We used study- and stage-stratified Cox regression models to assess the independent associations of hospital characteristics with mortality, and examined the change in racial/ethnic hazard ratios before and after adjustment for hospital characteristics. Hospital characteristics included composition measures based on the patients served by each hospital such as SES (percent of cancer patients from the highest quintile SES neighborhoods), race/ethnicity, and insurance type as well as NCI cancer center designation. Distance from patients' residences to hospitals was also examined. Patient sociodemographics include race/ethnicity, education, marital status, and neighborhood SES; behavioral and reproductive factors include smoking, alcohol consumption, obesity, exercise, family history of breast cancer, and parity; and clinical factors include tumor characteristics, treatment, and co-morbidities. Results: For all-cause mortality, patients seen in high SES hospitals had lower mortality rates than those seen in low SES hospitals (HR=0.87, 95% CI=0.75-0.99). The other hospital characteristics were not associated with all-cause mortality. Compared with non-Latina whites, we observed a higher mortality rate for African-Americans (HR=1.40, 95% CI=1.23-1.58), a lower mortality rate for Latinas (HR=0.89, 95% CI=0.78-1.01) and no statistically different rate for Asian Americans (HR=0.80, 95% CI=0.60-1.07). After adjusting for hospital characteristics, the higher mortality rate observed for African-Americans was slightly attenuated (HR=1.34, 95% CI= 1.18-1.51) whereas the lower mortality rate for Latinas became slightly stronger (HR=0.86, 95% CI=0.75-0.98). No statistically significant associations were observed for breast cancer-specific mortality. We also tested for interactions between race/ethnicity and hospital characteristics and found no statistically significant interactions. Conclusion: Hospital SES (as measured based on patient composition) is independently associated with all-cause mortality after a diagnosis of breast cancer, even after adjusting for a patient's educational level and neighborhood SES. However, adjusting for hospital characteristics accounted only slightly for the higher overall mortality rate among African-Americans and strengthened the lower mortality rate observed among Latinas. The fact that most breast cancer treatment occurs outside of hospitals may explain the lack of an observed association with disease-specific mortality; by contrast, hospital SES likely signifies a combination of factors (for example, the presence and severity of co-morbidities beyond what was measured, and access to effective care) that contribute to a gradient in all-cause mortality. Citation Format: Salma Shariff-Marco, Allison W. Kurian, Juan Yang, Jocelyn Koo, Esther M. John, Theresa H. M. Keegan, Iona Cheng, Kristine R. Monroe, Cheryl Vigen, Marilyn L. Kwan, Yani Lu, Brian E. Henderson, Leslie Bernstein, Richard Sposto, Anna H. Wu, Scarlett L. Gomez. Do hospital characteristics explain racial/ethnic disparities in mortality after breast cancer diagnosis: The California Breast Cancer Survivorship Consortium. [abstract]. In: Proceedings of the Seventh AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 9-12, 2014; San Antonio, TX. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2015;24(10 Suppl):Abstract nr A67.

Medicare Charges and Payments for Cervical Spine Surgery: Association With Hospital Characteristics.

Retrospective analysis. To determine the association of hospital and patient population characteristics with charges and payments for Medicare patients undergoing cervical spine surgery. Third-party payers such as Medicare pay negotiated rates for health care services that represent a substantial savings from hospitals' list prices. Previous research has shown geographical variation in hospital charges. However, the association with other hospital and patient population characteristics is poorly understood. We determined the association of hospital characteristics (hospital size, ownership, location, teaching status, procedure volume, and geographical region) and patient population characteristics (proportion female, nonwhite, or with ≥1 comorbid conditions) with excess charges (difference between hospital charges and payments) and cost-to-charge ratio (ratio of payments to hospital charges) for Medicare patients undergoing cervical spine fusion without complication (MS-DRG 473). Significance levels were set at a P value less than 0.05. The median excess charge was $59,799 (interquartile range, $41,668, $69,576) and cost-to-charge ratio was 25.8% (interquartile range, 20.4%, 32.7%). Higher excess charges were observed for urban hospitals (P = 0.003). There was an association between excess charges and procedure volume (P = 0.034) and proportion of patients with 1 or more comorbid conditions (P = 0.008). There were no differences based on hospital size, ownership, teaching status, geographical region, or proportion of female or nonwhite patients.Private hospitals had higher cost-to-charge ratios than government hospitals (P = 0.017). There was no association with hospital size, teaching status, geographical region, procedure volume, or proportion of patients who were female, nonwhite, or who had 1 or more comorbid conditions. The relationship between hospital charges and payments for cervical spine surgery without complication is associated with certain hospital and patient population characteristics. Further study is needed to determine whether these differences are associated with health outcomes. 3.

Abstract 269: Does Functional Recovery After Stroke Vary by Hospital Type?

Background: Functional recovery following an acute ischemic stroke is a highly important outcome from a patient’s perspective. Whether functional outcomes following stroke vary among treating hospitals is unknown. Methods: We examined 3 month functional recovery measured by the modified Rankin Scale (mRS) among 2,076 ischemic stroke patients treated at 82 U.S. hospitals in the Adherence eValuation After Ischemic stroke Longitudinal (AVAIL) study and Get With The Guidelines-Stroke registry. We used multivariable hierarchical models to examine the association of hospital characteristics (number of beds, region, academic/teaching center, annual ischemic stroke discharges, primary stroke center certification, hospitals’ composite score indicating stroke quality of care) and the outcome after adjusting for patient characteristics (socio-demographics and clinical factors including stroke severity as measured by the NIHSS). Rankin scores were classified as moderate-severe disability (mRS 3-5) vs. minor to no disability (mRS &lt;2) and evaluated as continuous scores. Results: Overall by 3 months after discharge, 35.9% of stroke patients had moderate-severe disability. Rates of moderate-severe disability varied by treating hospital (Figure) (mean 36%, IQR 26%-45%). Patients cared for in a teaching hospital (adjusted OR 0.71, 95% CI 0.52-0.96) or primary stroke center certified hospital (adjusted OR 0.69, 95% CI 0.51-0.93) were significantly less likely to have moderate-severe disability at 3 months. Relative to the Northeast, care in hospitals in the Midwest or South was associated with higher likelihood moderate-severe disability (OR 1.45, 95% CI 1.04-2.03 and OR 1.57, 95% CI 1.06-2.30, respectively). In contrast, functional outcomes did not vary by hospital stroke care quality, stroke volume, or hospital bed size. Findings were similar for mRS as a continuous outcome. Conclusions: A third of acute ischemic stroke patients had moderate-severe disability three months after hospital discharge and these rates varied considerably among U.S. hospitals. Receiving stroke care at a teaching or primary stroke center hospital was associated with significantly better post discharge functional status.

Association of Emergency Department and Hospital Characteristics with Elopements and Length of Stay

As the Centers for Medicare & Medicaid Services (CMS) core measures in 2013 compare Emergency Department (ED) treatment time intervals, it is important to identify ED and hospital characteristics associated with these metrics to facilitate accurate comparisons. The objective of this study is to assess differences in operational metrics by ED and hospital characteristics. ED-level characteristics included annual ED volume, percentage of patients admitted, percentage of patients presenting by ambulance, and percentage of pediatric patients. Hospital-level characteristics included teaching hospital status, trauma center status, hospital ownership (nonprofit or for-profit), inpatient bed capacity, critical access status, inpatient bed occupancy, and rural vs. urban location area. Data from the ED Benchmarking Alliance from 2004 to 2009 were merged with the American Hospital Association's Annual Survey Database to include hospital characteristics that may impact ED throughput. Overall median length of stay (LOS) and left before treatment is complete (LBTC) were the primary outcome variables, and a linear mixed model was used to assess the association between outcome variables and ED and hospital characteristics, while accounting for correlations among multiple observations within each hospital. All data were at the hospital level on a yearly basis. There were 445 EDs included in the analysis, from 2004 to 2009, with 850 observations over 6 years. Higher-volume EDs were associated with higher rates of LBTC and LOS. For-profit hospitals had lower LBTC and LOS. Higher inpatient bed occupancies were associated with a higher LOS. Increasing admission percentages were positively associated with overall LOS for EDs, but not with rates of LBTC. Higher-volume EDs are associated with higher LBTC and LOS, and for-profit hospitals appear more favorably in these metrics compared with their nonprofit counterparts. It is important to appreciate that hospitals have different baselines for performance that may be more tied to volume and capacity, and less to quality of care.

The Association of Hospital Characteristics and Quality Improvement Activities in Inpatient Medical Services

Quality of U.S. health care has been the focus of increasing attention, with deficiencies in patient care well recognized and documented. However, relatively little is known about the extent to which hospitals engage in quality improvement activities (QIAs) or factors influencing extent of QIAs. To identify 1) the extent of QIAs in Veterans Administration (VA) inpatient medical services; and 2) factors associated with widespread adoption of QIAs, in particular use of hospitalists, non-physician providers, and extent of goal alignment between the inpatient service and senior managers on commitment to quality. Cross-sectional, descriptive study of QIAs using a survey administered to Chiefs of Medicine (COM) at all 124 VA acute care hospitals. We conducted hierarchical regression, regressing QIA use on facility contextual variables, followed by use of hospitalists, non-physician providers, and goal alignment/quality commitment. Outcome measures pertained to use of a set of 27 QIAs and to three dimensions--infrastructure, prevention, and information gathering--that were identified by factor analysis among the 27 QIAs overall. Survey response rate was 90 % (111/124). Goal alignment/quality commitment was associated with more widespread use of all four QIA categories [infrastructure (b = 0.42; p < 0.001); prevention (b = 0.24; p < 0.001); information gathering (b = 0.28; p = <0.001); and overall QIA (b = 0.31; p < 0.001)], as was greater use of hospitalists [infrastructure (b = 0.55; p = 0.03); prevention (b = 0.61; p < 0.001); information gathering (b = 0.75; p = 0.01); and overall QIAs (b = 0.61; p < 0.001)]; higher occupancy rate was associated with greater infrastructure QIAs (b = 1.05, p = 0.02). Non-physician provider use, hospital size, university affiliation, and geographic region were not associated with QIAs. As hospitals respond to changes in healthcare (e.g., pay for performance, accountable care organizations), this study suggests that practices such as use of hospitalists and leadership focus on goal alignment/quality commitment may lead to greater implementation of QIAs.

Association between value-based purchasing score and hospital characteristics.

BackgroundMedicare hospital Value-based purchasing (VBP) program that links Medicare payments to quality of care will become effective from 2013. It is unclear whether specific hospital characteristics are associated with a hospital’s VBP score, and consequently incentive payments.The objective of the study was to assess the association of hospital characteristics with (i) the mean VBP score, and (ii) specific percentiles of the VBP score distribution. The secondary objective was to quantify the associations of hospital characteristics with the VBP score components: clinical process of care (CPC) score and patient satisfaction score.MethodsObservational analysis that used data from three sources: Medicare Hospital Compare Database, American Hospital Association 2010 Annual Survey and Medicare Impact File. The final study sample included 2,491 U.S. acute care hospitals eligible for the VBP program. The association of hospital characteristics with the mean VBP score and specific VBP score percentiles were assessed by ordinary least square (OLS) regression and quantile regression (QR), respectively.ResultsVBP score had substantial variations, with mean score of 30 and 60 in the first and fourth quartiles of the VBP score distribution. For-profit status (vs. non-profit), smaller bed size (vs. 100–199 beds), East South Central region (vs. New England region) and the report of specific CPC measures (discharge instructions, timely provision of antibiotics and beta blockers, and serum glucose controls in cardiac surgery patients) were positively associated with mean VBP scores (p<0.01 in all). Total number of CPC measures reported, bed size of 400–499 (vs. 100–199 beds), a few geographic regions (Mid-Atlantic, West North Central, Mountain and Pacific) compared to the New England region were negatively associated with mean VBP score (p<0.01 in all). Disproportionate share index, proportion of Medicare and Medicaid days to total inpatient days had significant (p<0.01) but small effects. QR results indicate evidence of differential effects of some of the hospital characteristics across low-, medium- and high-quality providers.ConclusionsAlthough hospitals serving the poor and the elderly are more likely to score lower under the VBP program, the correlation appears small. Profit status, geographic regions, number and type of CPC measures reported explain the most variation among scores.

Abstract 258: Incidence and Predictors of Cardiac Arrest in Cerebrovascular Diseases

Background and purpose: Large scale studies of cardiac arrest in hospitalized patients with cerebrovascular accident (CVA) are lacking. We sought to describe the incidence, demographics and hospital characteristics of cardiac arrest in CVA. Additionally, we aimed to indentify predictors of cardiac arrest in patients with CVA. Methods: We analyzed the data from the Nationwide Inpatient Sample (NIS) of Healthcare Cost and Utilization Project for years 2005-2009. NIS is a discharge level 20% stratified sample of all non-federal hospitals in the US. We used International Classification of Diseases-9 (ICD-9) codes to select cases of CVA. Comparisons were made by using χ2 and student-t tests. Multivariate logistic regression was used to identify independent predictors of cardiac arrest. Results: We included 672,161 cases of CVA [ischemic stroke: 58.2%, transient ischemic attack (TIA):28.2%, intracerebral hemorrhage (ICH): 9.7%, and subarachnoid hemorrhage (SAH): 3.9%] in our analysis. Of these, 3,154 (0.467%) also had cardiac arrest. Compared to ischemic stroke (0.413%), incidence of cardiac arrest was higher in ICH (1.221%) and SAH (2.523%) and was lower in TIA (0.038%). Patients with cardiac arrest were younger (mean age±SD: 67.8±16.4 vs. 70.5±15.7 years, p&lt;0.001) and were less likely of female gender (51.8% vs. 55.7%, p&lt;0.001). There was a significant difference in the incidence of cardiac arrest between various ethnic groups (Caucasian: 0.415% vs. African-American: 0.563% vs. Hispanic: 0.633% vs. Asian/Pacific Islander: 0.722%, p&lt;0.001). Compared to the rest, patients in lowest income quartile had higher incidence of cardiac arrest (0.526% vs. 0.437%, p&lt;0.001). Significant differences based on the hospital characteristics were as follows: 1. Bedsize: small (0.349%) vs. medium (0.443%) vs. large (0.498%), p&lt;0.001; 2. Location: rural (0.354%) vs. urban (0.485%), p&lt;0.001; 3. Academic status: teaching (0.553%) vs. non-teaching (0.403%), p&lt;0.001; and 4. Region: northeast (0.399%) vs. midwest (0.403%) vs. south (0.489%) vs. west (0.553%), p&lt;0.001. In multivariate analysis, factors associated with cardiac arrest are shown in the table. Conclusion: This is one of the largest studies to describe the predictors of cardiac arrest in CVA. The patients with ICH and SAH are at significantly higher risk of cardiac arrest. The association of hospital characteristics and the incidence of cardiac arrest warrants further exploration into the contributing factors. The patients with higher risk profile as per the predictor model should warrant closer monitoring.

Association of Hospital Characteristics and Diagnosis With the Repeat Use of CT and MRI: A Nationwide Population-Based Study in an Asian Country

The objective of our study was to assess the association of hospital characteristics and diagnosis with repeated utilization of CT and MRI using the nationwide population-based Taiwan National Health Insurance database. All CT and MR examinations for all health care services-including inpatient, outpatient, and emergency services-performed during 2004 and 2005 were identified. Logistic regression using generalized estimating equations was used for multivariate analysis to explore the relationships between hospital characteristics, diagnosis, and the use of CT and MRI repeated within 90 days. A total of 2,152,292 patients underwent CT and MR examinations during the study period, and 21.5% of those patients underwent repeat scanning within 90 days. The medical center had the highest rate of repeat scanning (24.9%) followed by the regional hospital (20.4%) and community hospital (13%). Repeat CT or MRI was most commonly performed of patients with a malignancy (31.8%), a neurologic disorder (24.0%), or a brain or spinal injury (25.3%). Our study shows that repeat use of CT and MRI within 90 days is high and is related to both diagnosis and hospital characteristics. Although the Taiwanese experience might not apply to all countries, this knowledge should aid in the review of health care policies so that guidelines for repeat scanning may be tailored to the different levels of hospitals (medical centers, 25%; regional hospital, 20%; community hospital, 13%) and to different diseases (malignant neoplasms, 32%; neurologic disorders and brain, neck, or spinal injury, 25%; other entities, 20%) to achieve maximum efficiency within a limited health care budget.

Delivery of Physical Therapy in the Acute Care Setting: A Population-Based Study

Population-based studies on physical therapy use in acute care are lacking. The purpose of this study was to examine population-based, hospital discharge data from North Carolina to describe the demographic and diagnostic characteristics of individuals who receive physical therapy and, for common diagnostic subgroups, to identify factors associated with the receipt of and intensity of physical therapy use. This was a cross-sectional, descriptive study. Hospital discharge data for 2006-2007 from the 128 acute care hospitals in the state were examined to identify the most common diagnoses that receive physical therapy and to describe the characteristics of physical therapy users. For 2 of the most common diagnoses, logistic and linear regression analyses were conducted to identify factors associated with the receipt and intensity of physical therapy. Of the more than 2 million people treated in acute care hospitals, 22.5% received physical therapy (mean age=66 years; 58% female). Individuals with osteoarthritis (admitted for joint replacement) and stroke were 2 of the most common patient types to receive physical therapy. Almost all individuals admitted for a joint replacement received physical therapy, with little between-hospital variation. Between-hospital variation in physical therapy use for stroke was greater. Demographic and hospital-related factors were associated with physical therapy use and physical therapy intensity for both diagnoses, after controlling for illness severity and comorbidities. Data from only one state were examined, and the studied variables were limited. The use and intensity of physical therapy for stroke and joint replacement in acute care hospitals in North Carolina vary by clinical and nonclinical factors. Reasons behind the association of hospital characteristics and physical therapy use need further investigation.

Patient and hospital characteristics associated with variation in guideline adherence in intrauterine insemination care

To assess the association of patient and hospital characteristics with adherence to guidelines for intrauterine insemination (IUI) care. Retrospective cohort study using multilevel regression analysis. Characteristics studied at the patient level were female age, type and duration of subfertility, diagnosis and number of started IUI cycles. At the hospital level, the characteristics studied were hospital size, teaching hospital, in vitro fertilization (IVF) licence and number of physicians involved in the IUI programme. Data were obtained from medical records and questionnaires for gynaecologists. Five hundred and fifty-eight subfertile couples who underwent IUI treatment at 10 Dutch hospitals. Adherence to systematically developed guideline-based performance indicators describing 20 processes of IUI care. A total of 558 couples who started 2,334 IUI cycles participated. Guideline adherence in IUI care was often substandard and varied considerably between hospitals. Variation in guideline adherence in IUI care was associated with the patient characteristics 'diagnosis' and 'female age'. Only adherence to the guideline recommendation regarding 'screening for tubal occlusion' was associated with hospital characteristics ('hospital size' and 'IVF licence'). Large explained variances up to 39% were found for the different models. A number of patient and hospital characteristics were associated with variation in guideline adherence in IUI care, particularly the patient characteristics 'diagnosis' and 'female age'. The identification of different subgroups in the patient population and different types of hospitals with regard to the extent of guideline adherence in IUI care is important for the tailoring of interventions to improve IUI care.

Hospitalisations for sport-related concussions in US children aged 5 to 18 years during 2000–2004

Objectives:To describe patient and hospital characteristics associated with hospitalisation for a diagnosis of non-fatal sport-related concussion, and to determine factors associated with these hospitalisations.Methods:Children aged 5–18 years with a primary...

The Relationship of Hospital Characteristics and the Results of Peer Review in Six Large States

To determine which characteristics of hospitals may be related to a higher quality of care, the association of hospital characteristics with the outcomes of medical record review by state Peer Review Organizations (PROs) was studied. The two data sources were: 1) the AHA 1986 Annual Survey of Hospitals and 2) reviews completed between July 1987 through June 1988 from six large PROs. For each hospital the percentage of cases that failed physician review (the confirmed problem rate) was computed. Hospital characteristics evaluated included financial status, ownership, medical training, technological sophistication, and size. The following characteristics were significantly associated with a lower confirmed problem rate: a higher occupancy rate, greater payroll expenses per bed, a higher proportion of physicians who were board-certified specialists, greater technological sophistication, a higher number of beds, a higher proportion of nurses who were registered, and membership in the Council of Teaching Hospitals. Public hospitals had higher problems rates than private not-for-profit hospitals. All characteristics significantly related to higher confirmed problem rates were also related to higher adjusted mortality rates in a previous study of 3,100 U.S. hospitals. The results suggest that hospital resources, including financial status, training of medical personnel, and availability of sophisticated equipment, are related to the quality of care provided by the hospital.