What are the costs of queuing for hip fracture surgery in Canada?

This paper investigates the effect of wait time for hip fracture surgery in Canada on post-surgery length of stay in hospital and inpatient mortality. After controlling for observed and unobserved patient and hospital characteristics, pre-surgery delay has little effect on either of the two outcome variables. Patients from higher income postal-codes experience only slightly shorter delays, and income has no substantial effect on post-surgery outcomes. For hip fracture patients surgery delay may lead to greater pre-surgery inpatient costs and more patient discomfort, but we find no evidence of a detrimental impact on post-surgery outcomes.     

Complications, comorbidities, and mortality: improving classification and prediction.

OBJECTIVE: First, to compare the distribution of complications and comorbidities associated with 17 common surgical procedures. We then describe the effect of augmenting an ICD-9-CM version of the Charlson comorbidity index, given the possible confounding of comorbidities and complications, for three common inpatient surgical procedures: coronary artery bypass surgery, pacemaker surgery, and hip fracture repair. DATA SOURCES AND STUDY SETTING: Individuals having one of the above procedures between April 1, 1990 and March 31, 1994, identified from Manitoba Health hospital discharge data, and their extracted records. STUDY DESIGN: Design was cross-sectional and longitudinal using Manitoba data on hospital utilization and mortality. DATA COLLECTION/EXTRACTION: Manitoba hospital discharge abstracts permit identifying whether or not the diagnosis represents an in-hospital complication of care. Two data sets were created for each procedure, one including complication diagnoses and another with complications removed. PRINCIPAL FINDINGS: The degree to which complications contaminated estimation of comorbidity depended both on the procedures studied and on the covariates selected. The unique structure of the algorithm for the Charlson comorbidity index led to complication diagnoses having only a minor effect on the comorbidity score generated. Unless a data set affords the opportunity to remove complication diagnoses, the improvement in comorbidity detection afforded by augmenting the Charlson index, combined with the potential for overestimation of comorbidity, seem sufficiently modest to contraindicate such augmentation.     

Do severity measures explain differences in length of hospital stay? The case of hip fracture.

OBJECTIVE: To examine whether judgments about hospital length of stay (LOS) vary depending on the measure used to adjust for severity differences. DATA SOURCES/STUDY SETTING: Data on admissions to 80 hospitals nationwide in the 1992 MedisGroups Comparative Database. STUDY DESIGN: For each of 14 severity measures, LOS was regressed on patient age/sex, DRG, and severity score. Regressions were performed on trimmed and untrimmed data. R-squared was used to evaluate model performance. For each severity measure for each hospital, we calculated the expected LOS and the z-score, a measure of the deviation of observed from expected LOS. We ranked hospitals by z-scores. DATA EXTRACTION: All patients admitted for initial surgical repair of a hip fracture, defined by DRG, diagnosis, and procedure codes. PRINCIPAL FINDINGS: The 5,664 patients had a mean (s.d.) LOS of 11.9 (8.9) days. Cross-validated R-squared values from the multivariable regressions (trimmed data) ranged from 0.041 (Comorbidity Index) to 0.165 (APR-DRGs). Using untrimmed data, observed average LOS for hospitals ranged from 7.6 to 23.9 days. The 14 severity measures showed excellent agreement in ranking hospitals based on z-scores. No severity measure explained the differences between hospitals with the shortest and longest LOS. CONCLUSIONS: Hospitals differed widely in their mean LOS for hip fracture patients, and severity adjustment did little to explain these differences.     

Rehabilitation costs: implications for prospective payment.

OBJECTIVE: To obtain information relevant to development of prospective payment for Medicare rehabilitation facilities (RFs) and skilled nursing facilities (SNFs): compares service utilization, length of stay (LOS), case mix, and resource consumption for Medicare patients receiving postacute institutional rehabilitation care. DATA SOURCES/STUDY SETTING: Longitudinal patient-level and related facility-level data on Medicare hip fracture (n = 513) and stroke (n = 483) patients admitted in 1991-1994 to a sample of 27 RFs and 65 SNFs in urban areas in 17 states. STUDY DESIGN: For each condition, two-group RF-SNF comparisons were made. Regression analysis was used to adjust RF-SNF differences in resource consumption per stay for patient condition (case mix) and other factors, since random assignment was not possible. DATA COLLECTION/EXTRACTION METHODS: Providers at each facility were trained to collect patient case-mix and service utilization information. Secondary data also were obtained. PRINCIPAL FINDINGS: RF patients had shorter LOS, fewer total nursing hours (but more skilled nursing hours), and more ancillary hours than SNF patients. After adjustment, ancillary resource consumption per stay remained substantially higher for RF than SNF patients, particularly for stroke. The adjusted nursing resource consumption differences were smaller than the ancillary differences and not statistically significant for hip fracture. Supplemental outcome findings suggested minimal differences for hip fracture patients but better outcomes for RF than SNF stroke patients. CONCLUSIONS: Much can be gained from an integrated approach to developing prospective payment for RFs and SNFs. In that context, consideration of condition-specific per-stay payment methods applicable to both settings appears warranted.     

Comorbidity risk-adjustment strategies are comparable among persons with hip fracture

OBJECTIVE: To determine the magnitude and importance of declines in model performance associated with altering the data source and time frame from which comorbid conditions were identified in claims-based risk adjustment among persons with hip fracture. STUDY DESIGN AND SETTING: Medicare claims data were used to identify incident hip fracture cases in 1999. Three risk-adjustment instruments were evaluated: one by Iezzoni, the Charlson Index (Romano adaptation), and the Clinical Classification Software (CCS). Several implementation strategies, defined by altering data source (MedPar and/or Part B claims) and time frame (index hospitalization and/or 1-year preperiod), were assessed for each instrument. Logistic regression was used to predict 1-year mortality, and model performance was compared. RESULTS: Each instrument had modest ability to predict 1-year mortality after hip fracture. The CCS performed best overall (c=0.76), followed by the Iezzoni (c=0.73) and Charlson models (c=0.72). Although each instrument performed most favorably when applied to both inpatient and outpatient claims and when comorbidities were considered during the preperiod, varying data source and time frame had trivial effects on model performance. CONCLUSION: The similar predictive ability of the three risk-adjustment instruments suggests that ease of implementation be a key consideration in choosing an approach for hip fracture populations.     

Association of hospital resource use with comorbidity status and patient age among hip fracture patients in Japan

OBJECTIVES: This study examined the association of resource use with comorbidity status and patient age among hip fracture patients who underwent surgical treatment. DESIGN: We used a database from the Voluntary Hospitals of Japan Quality Indicator Project that involved 10 privately owned leading teaching hospitals in Japan. SETTING: Four of these hospitals in Japan. PARTICIPANTS: We selected 778 operable hip fracture patients aged 65 or older who were admitted to these hospitals between January 1996 and August 2000 (mean age: 80.3 +/- 7.3 years). MEASUREMENTS: A linear mixed model was performed to identify factors associated with the resource use, such as total length of stay (LOS), LOS before surgery, LOS after surgery, total hospital charges, charges for diagnostic examinations, charges for surgery, and length of theater time, among operable hip fracture patients. RESULTS: The mean LOS was 45.9 days, and the mean total hospital charges were US dollars 14,495.0. Results from linear mixed models revealed that higher age was significantly associated with shorter length of theater time (P < 0.01), and that the presence of comorbidity among hip fracture patients was significantly associated with longer total LOS (P < 0.01), longer LOS after surgery (P < 0.001), higher charges for diagnostic examinations (P < 0.001), and shorter length of theater time (P < 0.01). CONCLUSION: These results suggest that the presence of comorbidity among operable hip fracture patients requires greater resource use during their hospital stay, but higher age is not significantly associated with greater resource use at all.     

Assessment of HCFA''s 1992 Medicare hospital information report of mortality following admission for hip arthroplasty.

OBJECTIVE. The Health Care Financing Administration (HCFA) produced annually from 1987 through 1994 mortality data information as part of the Medicare Hospital Information Project (MHIP) report. We assessed the validity of these data for hip arthroplasty for one state Medicare population and we analyzed the accuracy of the predictions derived from the Bailey-Makeham mortality model for this procedure. DATA SOURCES AND STUDY SETTING. The study sample consisted of claims and model data from 1,421 Medicare patients who underwent hip arthroplasty at acute care Arkansas hospitals from October 1990 through September 1991. STUDY DESIGN. Patients were stratified into two groups based on reason for surgery (fracture status): reconstruction or fracture management. Patient survival experience was compared between the two groups. The effect of fracture status on the HCFA model's predictive ability was examined empirically and via a simulation study. RESULTS. Our results indicate that hip arthroplasty patients are not uniform with regard to outcome, depending on the reason for the surgery. Patients with fracture had a much higher 30-day mortality rate than those who underwent reconstruction (p < .001). The empirical data and the simulation study suggest that the Bailey-Makeham model underestimates mortality for reconstructive surgery in fracture patients, providing a false benchmark for those institutions that perform hip arthroplasty on predominantly one category of patients. CONCLUSION. Published HCFA data concerning mortality for hip arthroplasty combines two different patient populations into one statistic. Casual examination of these data could result in a false benchmark for analysis of institutional performance. An important implication from this study for policymakers who base decisions on "report cards" or performance measurement reports is that, although they are necessary,generic case-mix, comorbidity, and severity of illness adjustments may not be sufficient to achieve accurate representations of outcomes, and that more disease/procedure--specific adjustments may be needed to avoid inappropriate conclusions.     

Concurrent prediction of hospital mortality and length of stay from risk factors on admission

OBJECTIVE: To develop a method for predicting concurrently both hospital survival and length of stay (LOS) for seriously ill or injured patients, with particular attention to the competing risks of death or discharge alive as determinants of LOS. DATA SOURCES: Previously collected 1995-1996 registry data on 2,646 cases of injured patients from three trauma centers in Maine. STUDY DESIGN: Time intervals were determined for which the rates of discharge or death were relatively constant. Poisson regression was used to develop a model for each type of terminal event, with risk factors on admission contributing proportionately to the subsequent rates for each outcome in each interval. Mean LOS and cumulative survival were calculated from a combination of the resulting piecewise exponential models. PRINCIPAL FINDINGS: Age, Glasgow Coma Scale, Abbreviated Injury Scores, and specific mechanisms of injury were significant predictors of the rates of death and discharge, with effects that were variable in different time intervals. Predicted probability of survival and mean LOS from the model were similar to actual values for categorized patient groups. CONCLUSIONS: Piecewise exponential models may be useful in predicting LOS, especially if determinants of mortality are separated from determinants of discharge alive.     

The effects of price competition and reduced subsidies for uncompensated care on hospital mortality

OBJECTIVE: To determine whether hospital mortality rates changed in New Jersey after implementation of a law that changed hospital payment from a regulated system based on hospital cost to price competition with reduced subsidies for uncompensated care and whether changes in mortality rates were affected by hospital market conditions. DATA SOURCES/STUDY SETTING: State discharge data for New Jersey and New York from 1990 to 1996. Study Design. We used an interrupted time series design to compare risk-adjusted in-hospital mortality rates between states over time. We compared the effect sizes in markets with different levels of health maintenance organization penetration and hospital market concentration and tested the sensitivity of our results to different approaches to defining hospital markets. DATA COLLECTION/EXTRACTION METHODS: The study sample included all patients under age 65 admitted to New Jersey or New York hospitals with stroke, hip fracture, pneumonia, pulmonary embolism, congestive heart failure, hip fracture, or acute myocardial infarction (AMI). PRINCIPAL FINDINGS: Mortality among patients in New Jersey improved less than in New York by 0.4 percentage points among the insured (p=.07) and 0.5 percentage points among the uninsured (p=.37). There was a relative increase in mortality for patients with AMI, congestive heart failure, and stroke, especially for uninsured patients with these conditions, but not for patients with the other four conditions we studied. Less competitive hospital markets were significantly associated with a relative decrease in mortality among insured patients. CONCLUSIONS: Market-based reforms may adversely affect mortality for some conditions but it appears the effects are not universal. Insured patients in less competitive markets fared better in the transition to price competition.     

Model selection in competing risks regression

In the analysis of time‐to‐event data, the problem of competing risks occurs when an individual may experience one, and only one, of m different types of events. The presence of competing risks complicates the analysis of time‐to‐event data, and standard survival analysis techniques such as Kaplan–Meier estimation, log‐rank test and Cox modeling are not always appropriate and should be applied with caution. Fine and Gray developed a method for regression analysis that models the hazard that corresponds to the cumulative incidence function. This model is becoming widely used by clinical researchers and is now available in all the major software environments. Although model selection methods for Cox proportional hazards models have been developed, few methods exist for competing risks data. We have developed stepwise regression procedures, both forward and backward, based on AIC, BIC, and BICcr (a newly proposed criteria that is a modified BIC for competing risks data subject to right censoring) as selection criteria for the Fine and Gray model. We evaluated the performance of these model selection procedures in a large simulation study and found them to perform well. We also applied our procedures to assess the importance of bone mineral density in predicting the absolute risk of hip fracture in the Women's Health Initiative–Observational Study, where mortality was the competing risk. We have implemented our method as a freely available R package called crrstep. Copyright © 2013 John Wiley & Sons, Ltd.     

Case-mix adjustment using objective measures of severity: the case for laboratory data.

OBJECTIVE. We evaluate the use of routinely gathered laboratory data to subclassify surgical and nonsurgical major diagnostic categories into groups homogeneous with respect to length of stay (LOS). DATA SOURCES AND STUDY SETTING. The source of data is the Combined Patient Experience database (COPE), created by merging data from computerized sources at the University of California San Francisco (UCSF) Medical Center and Stanford University Medical Center for a total sample size of 73,117 patient admissions. STUDY DESIGN. The study is cross-sectional and retrospective. All data were extracted from COPE consecutive admissions; the unit of analysis is an admission. The outcome variable LOS proxies hospital resource utilization for an inpatient stay. Nine (candidate) predictor variables were derived from seven lab tests (WBC, Na, K, C02, BUN, ALB, HCT) by recording the whole-stay minimum or maximum test result. DATA COLLECTION/EXTRACTION METHODS. Patient groups were formed by first assigning to major diagnostic categories (MDCs) all 73,117 admissions. Each MDC was then partitioned into medical and surgical subgroups (sub-MDCs). The 13 sub-MDCs selected for study define a study population of 32,599 patients that represents approximately 45 percent of inpatients. Within each of the 13 sub-MDCs, patients were randomly assigned to one of two data sets in a ratio of 2:1. The first set was used to create, the second to validate, three different LOS predictors. Predictive accuracies of individual DRG classes were compared with those of two alternative classification schemes, one formed by recursive partitioning (the sub-MDC) using only lab test results, the other by partitioning with both lab test results and individual DRGs. PRINCIPAL FINDINGS. For the eight largest sub-MDCs (81 percent of study population), individual DRGs explained 23 percent of the within sub-MDC variance in LOS, laboratory data classes explained 31 percent, and classes derived by considering individual DRGs and laboratory data explained 37 percent. (Each result is a weighted average R2. The average number of LOS classes into which the eight largest sub-MDCs were partitioned were 20, 10, and 10, respectively. Within six of the eight, partitioning on the basis of laboratory data alone explained more within sub-MDC variance than did partitioning into individual DRGs. CONCLUSIONS. Routine lab test data improve the accuracy of LOS prediction over that possible using DRG classes. We note that the improvements do not result from overfitting the data, since the numbers of LOS classes we use to predict LOS are considerably fewer than the numbers of individual DRGs.     

Modeling recurrence in colorectal cancer

OBJECTIVE: To assess the role of recurrence in prognosis of colon cancer, we investigated several methodologic issues, including application of classic survival analysis and Markov model. STUDY DESIGN AND SETTING: The data were recorded by the Registry of Digestive Tumors of C?te d'Or, France, for 874 patients who had been treated by surgery between 1976 and 1984 and followed for up to 11 years. Survival analyses included the Cox proportional hazards model and its two generalizations that allow recurrence to be taken into account as a time-dependent covariate or as a competing outcome. The Markov model was used to analyze simultaneously recurrence and death. RESULTS: The competing risks approach is not appropriate because censoring is indisputably informative. The Markov model and the Cox model, with recurrence as a time-dependent covariate, provided similar results, demonstrating the impact of age and gender on recurrence and revealing a reduction in the effect of site and stage on mortality. CONCLUSION: A Markov multistate model seems to give new insights about the course of digestive cancer progression and into the role of recurrence in this process.     

Does delay in surgery after hip fracture lead to worse outcomes? A multicenter survey.

OBJECTIVE: To estimate the impact of delays in surgery for hip fracture on short- and long-term outcomes. DESIGN: ANALYSIS: of inpatient hospital data integrated with national health plan data and Central Bureau Statistics. SETTING: Seven major tertiary hospitals. Patients All consecutive elderly patients admitted with hip fracture during the years 2001-2005. MAIN OUTCOME MEASURES: Time from the hospitalization to operation; one-year mortality. MAIN RESULT: Study population comprise 4633 patients, older than 65 years. The conservative approach was chosen in 818 patients (17.7%), while 1350 patients (29.1%) waited >2 days from admission to the surgery. There was a substantial variation in median pre-operative stay among the hospitals (range 0-4 days). Patients who had surgery within 2 days had lower mortality (in-hospital, 1-month and 1-year) compared to those who waited for surgery >4 days (2.9%, 4.0%, 17.4% vs. 4.6%, 6.1%, 26.2%, respectively). A Cox proportional regression model of 1-year mortality in operated patients adjusted for background morbidity (Charlson index) showed that the length of operation delay has a gradual effect on increasing mortality (<2 days-reference group, 2-4 days-OR = 1.20, 5 days or longer, OR=1.50). The 818 (17.7%) non-operated patients suffered the highest 1-year mortality, 36.2%. CONCLUSIONS: Delays in surgery for hip fracture are associated with significant increase in short-term and 1-year mortality. Variation among the hospitals was substantial and calls for prompt quality improvement actions.     

Extracapsular hip fracture management: cost-consequences analysis of two alternative operative methods

OBJECTIVES: The aim of this prospective study was to perform a cost and outcome comparison between two alternative operative techniques (osteosynthesis and hemiarthroplasty) used in the treatment of elderly patients with unstable trochanteric hip fracture. MATERIALS AND METHODS: One hundred seventy-three trochanteric hip fracture patients were followed-up for 1 year after surgery. For each operative technique, hospital treatment's cost per patient was computed. Mortality and complication rate in-hospital and at specific time points after surgery were used as outcome measures. Patients' functional level before and after hip fracture was estimated according to their mobility and ability to perform basic and instrumental activities of daily living. RESULTS: The cost for patients undergoing osteosynthesis reached euro 1,931 per case, whereas for those treated with hemiarthroplasty reached euro 3,719 per case (2001 rates). There was no statistically significant difference regarding in-hospital mortality and complication rate, as well as mortality and complication rate 1 year after surgery, between the two patient groups. CONCLUSIONS: The quite similar performance of the two operative techniques suggests that cost could be the key factor for choosing between them. However, it is critical that many more randomized studies, with larger sample sizes and wider follow-up time periods should be conducted.     

Does waiting for total hip replacement matter? Prospective cohort study

OBJECTIVES: To assess the impact on the outcome of total hip replacement of the length of timing spent waiting for surgery. METHODS: One hundred and forty-three orthopaedic and general hospitals provided information about aspects of surgical practice for each total hip replacement conducted between September 1996 and October 1997 for publicly and privately funded operations in five English health regions. These data were linked to patient information about hip-related pain and disability status (measured using the Oxford Hip Score) before operation and at 3 and 12 months after. Data were analysed using multiple regression analysis. RESULTS: Questionnaires were completed by surgeons for 10,410 (78%) patients treated during the recruitment period and by 7151 (54%) patients. Twelve months after total hip replacement, the majority of patients experienced substantial improvements in hip-related pain and disability (as measured by the Oxford Hip Score). Those patients who started with a worse Oxford Hip Score before the operation tended to remain worse after the operation. Worse pre-operative score was associated with an increased length of either outpatient or inpatient wait, and this trend remained after the operation. The relationship between waiting time and outcome remained after adjustment for possible confounding variables. A consistently worse score was observed in public compared with private patients at all three time-points. In addition, in both sectors, those patients who were socially disadvantaged had a worse score than more socially advantaged patients both before and after the operation. CONCLUSIONS: Waiting for surgery is associated with worse outcomes 12 months later. Longer-term outcome needs to be considered to see if this association persists.     

Relationship between regulatory status,quality of care,and three-year mortality in Canadian residential care facilities: a longitudinal study

OBJECTIVES: To compare the mortality rate in regulated and unregulated facilities, controlling for confounding variables, and investigate the effect of care quality on residents' length of survival. DATA SOURCES/STUDY SETTING: At baseline, subjects were assessed in their living environment with respect to their functional autonomy, cognitive abilities, and quality of care. Vital status, disease-related information, and hospitalization data were retrieved three years later from the subjects' medical files. STUDY DESIGN: A three-year follow-up study of 299 residents from 88 long-term care facilities located in the province of Quebec, Canada. The effect of regulatory status and quality of care on length of survival was investigated by means of multivariable Cox proportional hazards regression models, from both traditional and competing risks perspectives. PRINCIPAL FINDINGS: Controlling for age, comorbidity, and baseline functional abilities, a resident's length of survival is not significantly influenced by the regulatory status of the facility in which he or she lived at baseline. However, residents with poor quality ratings at baseline had shorter survival times than those provided with good care. Median survival was 28 months among residents classified as receiving inadequate care compared to 41 months for those adequately cared for (p = 0.0217). CONCLUSIONS: The study suggests that quality of care has a much stronger influence on resident outcomes than regulation per se. This finding underscores the relevance of testing innovative interventions aimed at improving the quality of care provided in long-term care facilities, regardless of their regulatory status.     

Mental illness and length of inpatient stay for medicaid recipients with AIDS

OBJECTIVE: To examine the associations between comorbid mental illness and length of hospital stays (LOS) among Medicaid beneficiaries with AIDS. DATA SOURCE AND COLLECTION/STUDY SETTING: Merged 1992-1998 Medicaid claims and AIDS surveillance data obtained from the State of New Jersey for adults with >or=1 inpatient stay after an AIDS diagnosis from 1992 to 1996. STUDY DESIGN: Observational study of 6,247 AIDS patients with 24,975 inpatient visits. Severe mental illness (SMI) and other less severe mental illness (OMI) diagnoses at visits were ascertained from ICD-9 Codes. About 4 percent of visits had an SMI diagnosis; 5 percent had an OMI diagnosis; 43 percent did not have a mental illness diagnosis, but were patients who had been identified as having an SMI or OMI history; and 48 percent were from patients with no identified history of mental illness. PRINCIPAL FINDINGS: The overall mean hospital LOS was 12.7 days. After adjusting for measures of HIV disease severity and health care access in multivariate models, patients presenting with primary and secondary severe mental illness (SMI) diagnoses had approximately 32 percent and approximately 11 percent longer LOS, respectively, than did similar patients without a mental illness history (p<0.001 for each). But in these adjusted models of length of stay: (1) diagnosis of OMI was not related to LOS, and (2) in the absence of a mental illness diagnosed at the visit, an identified history of either SMI or OMI was also not related to LOS. In adjusted models of time to readmission for a new visit, current diagnosis of SMI or OMI and in the absences of a current diagnosis, history of SMI or OMI all tended to be associated with quicker readmission. CONCLUSIONS: This study finds greater (adjusted) LOS for AIDS patients diagnosed with severe mental illness (but not for those diagnosed with less severe mental comorbidity) at a visit. The effect of acute severe mental illness on hospitalization time may be comparable to that of an acute AIDS opportunistic illness. While previous research raises concerns that mental illness increases LOS by interfering with treatment of HIV conditions, the associations here may simply indicate that extra time is needed to treat severe mental illnesses or arrange for discharge of afflicted patients.     

Hospital competition, managed care, and mortality after hospitalization for medical conditions in California

OBJECTIVE: To assess the effect of hospital competition and health maintenance organization (HMO) penetration on mortality after hospitalization for six medical conditions in California. DATA SOURCE: Linked hospital discharge and vital statistics data for short-term general hospitals in California in the period 1994-1999. The study sample included adult patients hospitalized for one of the following conditions: acute myocardial infarction (N=227,446), hip fracture (N=129,944), stroke (N=237,248), gastrointestinal hemorrhage (GIH, N=216,443), congestive heart failure (CHF, N=355,613), and diabetes (N=154,837). STUDY DESIGN: The outcome variable was 30-day mortality. We estimated multivariate logistic regression models for each study condition with hospital competition, HMO penetration, hospital characteristics, and patient severity measures as explanatory variables. PRINCIPAL FINDINGS: Higher hospital competition was associated with lower 30-day mortality for three to five of the six study conditions, depending on the choice of competition measure, and this finding was robust to a variety of sensitivity analyses. Higher HMO penetration was associated with lower mortality for GIH and CHF. CONCLUSIONS: Hospitals that faced more competition and hospitals in market areas with higher HMO penetration provided higher quality of care for adult patients with medical conditions in California. Studies using linked hospital discharge and vital statistics data from other states should be conducted to determine whether these findings are generalizable.     

Postoperative Dehydration Is Associated with Frailty and Decreased Survival in Older Patients with Hip Fracture

Background: Hyperosmolar dehydration (HD) is a risk factor for severe complications in hip fracture in older patients. However, evidence for recommending screening of dehydration is insufficient and its relation with frailty and mortality is unclear. We tested the hypothesis that postoperative HD is associated with frailty and increased mortality. Methods: We recruited 625 older (>65 years) patients surgically treated for hip fracture and co-managed by an orthogeriatric team over one year in 2017. Pre- and postoperative HD (serum osmolarity > 300 mmol/L) was diagnosed. Frailty and associated mortality risk were assessed by the Multidimensional Prognostic Index (MPI). Results: The prevalence of preoperative HD was 20.4%. Compared with no-HD, MPI was similar in HD patients despite higher (p < 0.05) prevalence of polypharmacy, arterial hypertension, diabetes, chronic kidney disease and heart failure. After surgery the incidence of HD decreased to 16.5%, but increased (p = 0.003) in the MPI high-risk subgroup. Postoperative HD was associated with more complications and was an independent determinant of adjusted hospital length of stay (LOS) and of 60- to 365-days mortality. Conclusions: Older frail patients with hip fracture are prone to developing postoperative HD, which independently predicts prolonged hospital LOS and mortality. Systematically screening older patients for frailty and dehydration is advisable to customize hydration management in high-risk individuals.     

Two-stage residual inclusion for survival data and competing risks—An instrumental variable approach with application to SEER-Medicare linked data

Instrumental variable is an essential tool for addressing unmeasured confounding in observational studies. Two-stage predictor substitution (2SPS) estimator and two-stage residual inclusion (2SRI) are two commonly used approaches in applying instrumental variables. Recently, 2SPS was studied under the additive hazards model in the presence of competing risks of time-to-events data, where linearity was assumed for the relationship between the treatment and the instrument variable. This assumption may not be the most appropriate when we have binary treatments. In this paper, we consider the 2SRI estimator under the additive hazards model for general survival data and in the presence of competing risks, which allows generalized linear models for the relation between the treatment and the instrumental variable. We derive the asymptotic properties including a closed-form asymptotic variance estimate for the 2SRI estimator. We carry out numerical studies in finite samples and apply our methodology to the linked Surveillance, Epidemiology and End Results (SEER)–Medicare database comparing radical prostatectomy versus conservative treatment in early-stage prostate cancer patients.