Background Numerous studies have tried to determine the association between continuity and outcomes. Studies doing so must actually measure continuity. If continuity and outcomes are measured ...concurrently, their association can only be determined with time‐dependent methods.
Objective To identify and summarize all methodologically studies that measure the association between continuity of care and patient outcomes.
Methods We searched MEDLINE database (1950–2008) and hand‐searched to identify studies that tried to associate continuity and outcomes. English studies were included if they: actually measured continuity; determined the association of continuity with patient outcomes; and properly accounted for the relative timing of continuity and outcome measures.
Results A total of 139 English language studies tried to measure the association between continuity and outcomes but only 18 studies (12.9%) met methodological criteria. All but two studies measured provider continuity and used health utilization or patient satisfaction as the outcome. Eight of nine high‐quality studies found a significant association between increased continuity and decreased health utilization including hospitalization and emergency visits. Five of seven studies found improved patient satisfaction with increased continuity.
Conclusions These studies validate the belief that increased provider continuity is associated with improved patient outcomes and satisfaction. Further research is required to determine whether information or management continuity improves outcomes.
Readmissions to hospital are common, costly and often preventable. An easy-to-use index to quantify the risk of readmission or death after discharge from hospital would help clinicians identify ...patients who might benefit from more intensive post-discharge care. We sought to derive and validate an index to predict the risk of death or unplanned readmission within 30 days after discharge from hospital to the community.
In a prospective cohort study, 48 patient-level and admission-level variables were collected for 4812 medical and surgical patients who were discharged to the community from 11 hospitals in Ontario. We used a split-sample design to derive and validate an index to predict the risk of death or nonelective readmission within 30 days after discharge. This index was externally validated using administrative data in a random selection of 1,000,000 Ontarians discharged from hospital between 2004 and 2008.
Of the 4812 participating patients, 385 (8.0%) died or were readmitted on an unplanned basis within 30 days after discharge. Variables independently associated with this outcome (from which we derived the mnemonic "LACE") included length of stay ("L"); acuity of the admission ("A"); comorbidity of the patient (measured with the Charlson comorbidity index score) ("C"); and emergency department use (measured as the number of visits in the six months before admission) ("E"). Scores using the LACE index ranged from 0 (2.0% expected risk of death or urgent readmission within 30 days) to 19 (43.7% expected risk). The LACE index was discriminative (C statistic 0.684) and very accurate (Hosmer-Lemeshow goodness-of-fit statistic 14.1, p=0.59) at predicting outcome risk.
The LACE index can be used to quantify risk of death or unplanned readmission within 30 days after discharge from hospital. This index can be used with both primary and administrative data. Further research is required to determine whether such quantification changes patient care or outcomes.
Readmissions to hospital are increasingly being used as an indicator of quality of care. However, this approach is valid only when we know what proportion of readmissions are avoidable. We conducted ...a systematic review of studies that measured the proportion of readmissions deemed avoidable. We examined how such readmissions were measured and estimated their prevalence.
We searched the MEDLINE and EMBASE databases to identify all studies published from 1966 to July 2010 that reviewed hospital readmissions and that specified how many were classified as avoidable.
Our search strategy identified 34 studies. Three of the studies used combinations of administrative diagnostic codes to determine whether readmissions were avoidable. Criteria used in the remaining studies were subjective. Most of the studies were conducted at single teaching hospitals, did not consider information from the community or treating physicians, and used only one reviewer to decide whether readmissions were avoidable. The median proportion of readmissions deemed avoidable was 27.1% but varied from 5% to 79%. Three study-level factors (teaching status of hospital, whether all diagnoses or only some were considered, and length of follow-up) were significantly associated with the proportion of admissions deemed to be avoidable and explained some, but not all, of the heterogeneity between the studies.
All but three of the studies used subjective criteria to determine whether readmissions were avoidable. Study methods had notable deficits and varied extensively, as did the proportion of readmissions deemed avoidable. The true proportion of hospital readmissions that are potentially avoidable remains unclear.
Delay of surgery for hip fracture is associated with increased risk of morbidity and mortality, but the effects of surgical delays on mortality and resource use in the context of other emergency ...surgeries is poorly described. Our objective was to measure the independent association between delay of emergency surgery and in-hospital mortality, length of stay and costs.
We identified all adult patients who underwent emergency noncardiac surgery between January 2012 and October 2014 at a single tertiary care centre. Delay of surgery was defined as the time from surgical booking to operating room entry exceeding institutionally defined acceptable wait times, based on a standardized 5-level priority system that accounted for surgery type and indication. Patients with delayed surgery were matched to those without delay using propensity scores derived from variables that accounted for details of admission and the hospital stay, patient characteristics, physiologic instability, and surgical urgency and risk.
Of 15 160 patients, 2820 (18.6%) experienced a delay. The mortality rates were 4.9% (138/2820) for those with delay and 3.2% (391/12 340) for those without delay (odds ratio OR 1.59, 95% confidence interval CI 1.30-1.93). Within the propensity-matched cohort, delay was significantly associated with mortality (OR 1.56, 95% CI 1.18-2.06), increased length of stay (incident rate ratio 1.07, 95% CI 1.01-1.11) and higher total costs (incident rate ratio 1.06, 95% CI 1.01-1.11).
Delayed operating room access for emergency surgery was associated with increased risk of inhospital mortality, longer length of stay and higher costs. System issues appeared to underlie most delays and must be addressed to improve the outcomes of emergency surgery.
Background: Comorbidity measures are necessary to describe patient populations and adjust for confounding. In direct comparisons, studies have found the Elixhauser comorbidity system to be ...statistically slightly superior to the Charlson comorbidity system at adjusting for comorbidity. However, the Elixhauser classification system requires 30 binary variables, making its use for reporting and analysis of comorbidity cumbersome. Objective: Modify the Elixhauser classification system into a single numeric score for administrative data. Methods: For all hospitalizations at the Ottawa Hospital, Canada, between 1996 and 2008, we determined if International Classification of Disease codes for chronic diagnoses were in any of the 30 Elixhauser comorbidity groups. We then used backward stepwise multivariate logistic regression to determine the independent association of each comorbidity group with death in hospital. Regression coefficients were modified into a scoring system that reflected the strength of each comorbidity group's independent association with hospital death. Results: Hospitalizations that were included were 345,795 (derivation: 228,565; validation 117,230). Twenty-one of the 30 groups were independently associated with hospital mortality. The resulting comorbidity score had an equivalent discrimination in the derivation and validation groups (overall c-statistic 0.763, 95% CI: 0.759-0.766). This was similar to models having all Elixhauser groups (0.760, 95% CI: 0.756-0.764) or significant groups only (0.759, 95% CI: 0.754-0.762), but significantly exceeded discrimination when comorbidity was expressed using the Charlson score (0.745, 95% CI: 0.742-0.749). Conclusion: When analyzing administrative data, the Elixhauser comorbidity system can be condensed to a single numeric score that summarizes disease burden and is adequately discriminative for death in hospital.
Abstract Objective Administrative database research (ADR) frequently uses codes to identify diagnoses or procedures. The association of these codes with the condition it represents must be measured ...to gauge misclassification in the study. Measure the proportion of ADR studies using diagnostic or procedural codes that measured or referenced code accuracy. Study Design and Setting Random sample of 150 MEDLINE-cited ADR studies stratified by year of publication. The proportion of ADR studies using codes to define patient cohorts, exposures, or outcomes that measured or referenced code accuracy and Bayesian estimates for probability of disease given code operating characteristics were measured. Results One hundred fifteen ADR studies (76.7% 95% confidence interval (CI), 69.3–82.8) used codes. Of these studies, only 14 (12.1% 7.3–19.5) measured or referenced the association of the code with the entity it supposedly represented. This proportion did not vary by year of publication but was significantly higher in journals with greater impact factors. Of five studies reporting code sensitivity and specificity, the estimated probability of code-related condition in code-positive patients was less than 50% in two. Conclusion In ADR, diagnostic and procedural codes are commonly used but infrequently validated. People with a code frequently do not have the condition it represents.
To examine long-term mortality, resource utilization, and healthcare costs in sepsis patients compared to hospitalized nonsepsis controls.
Propensity-matched population-based cohort study using ...administrative data.
Ontario, Canada.
We identified a cohort of adults (≥ 18) admitted to hospitals in Ontario between April 1, 2012, and March 31, 2016, with follow-up to March 31, 2017. Sepsis patients were flagged using a validated International Classification of Diseases, 10th Revision-coded algorithm (Sepsis-2 definition), including cases with organ dysfunction (severe sepsis) and without (nonsevere). Remaining hospitalized patients were potential controls. Cases and controls were matched 1:1 on propensity score, age, sex, admission type, and admission date.
None.
Differences in mortality, rehospitalization, hospital length of stay, and healthcare costs were estimated, adjusting for remaining confounders using Cox regression and generalized estimating equations. Of 270,669 sepsis cases, 196,922 (73%) were successfully matched: 64,204 had severe and 132,718 nonsevere sepsis (infection without organ dysfunction). Over follow-up (median 2.0 yr), severe sepsis patients had higher mortality rates than controls (hazard ratio, 1.66; 95% CI, 1.63-1.68). Both severe and nonsevere sepsis patients had higher rehospitalization rates than controls (hazard ratio, 1.53; 95% CI, 1.50-1.55 and hazard ratio, 1.41; 95% CI, 1.40-1.43, respectively). Incremental costs (Canadian dollar 2018) in sepsis cases versus controls at 1-year were: $29,238 (95% CI, $28,568-$29,913) for severe and $9,475 (95% CI, $9,150-$9,727) for nonsevere sepsis.
Severe sepsis was associated with substantially higher long-term risk of death, rehospitalization, and healthcare costs, highlighting the need for effective postdischarge care for sepsis survivors.
To compare the accuracy of the modified Fried Index (mFI) and the Clinical Frailty Scale (CFS) to predict death or patient-reported new disability 90 days after major elective surgery.
The ...association of frailty with patient-reported outcomes, and comparisons between preoperative frailty instruments are poorly described.
This was a prospective multicenter cohort study. We determined frailty status in individuals ≥65 years having elective noncardiac surgery using the mFI and CFS. Outcomes included death or patient-reported new disability (primary); safety incidents, length of stay (LOS), and institutional discharge (secondary); ease of use, usefulness, benefit, clinical importance, and feasibility (tertiary). We measured the adjusted association of frailty with outcomes using regression analysis and compared true positive and false positive rates (TPR/FPR).
Of 702 participants, 645 had complete follow up. The CFS identified 297 (42.3%) with frailty, the mFI 257 (36.6%); 72 (11.1%) died or experienced a new disability. Frailty was significantly associated with the primary outcome (CFS adjusted odds ratio, OR, 2.51, 95% confidence interval, CI, 1.50-4.21; mFI adjusted-OR 2.60, 95% CI 1.57-4.31). TPR and FPR were not significantly different between instruments. Frailty was the only significant predictor of death or new disability in a multivariable analysis. Need for institutional discharge, costs and LOS were significantly increased in individuals with frailty. The CFS was easier to use, required less time and had less missing data.
Older people with frailty are significantly more likely to die or experience a new patient-reported disability after surgery. Clinicians performing frailty assessments before surgery should consider the CFS over the mFI as accuracy was similar, but ease of use and feasibility were higher.
Rationale and objectives Urgent readmission to hospital is commonly used to measure hospital quality of care. Hospitals that measure the proportion of urgent readmissions judged avoidable need to ...know previously published rates for comparison. In this study, we generated a literature‐based estimate for the proportion of 30‐day urgent readmissions deemed avoidable for hospitals to use to gauge their performance in avoidable readmissions.
Methods We searched the Medline and Embase databases to identify published studies that reported the proportion of 30‐day urgent readmissions deemed avoidable. We then modelled the overall proportion of 30‐day urgent readmissions deemed avoidable.
Results We included 16 studies that used a wide variety of patients and a diverse range of methods to classify readmissions as avoidable. Studies reported a broad range for the proportion of urgent 30‐day readmissions deemed avoidable. Overall, 848 of 3669 readmissions (23.1%, 95% confidence interval, 21.7–24.5) of 30‐day urgent readmissions were classified as avoidable. This proportion varied significantly based on hospital teaching status and number of reviewers for each case teaching hospitals: with one reviewer, 9.3% (4.2–19.3); with >1 reviewer, 21.6% (13.2–33.3); non‐teaching hospital: with one reviewer, 32.2% (11.4–63.9); with >1 reviewer, 39.9% (37.6–42.2). Significant heterogeneity remained between studies even after clustering studies by these covariates.
Conclusions Less than one in four readmissions were deemed avoidable. Health system planners need to use caution in interpreting all cause readmission statistics as they are only partially influenced by quality of care.
There has been limited study of patient-reported outcomes (PROs) in patients at risk of limb loss. Our primary objective was to estimate the prevalence of disability in this patient population using ...the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0). We recruited patients referred to a limb-preservation clinic. Patients self-reported their disability status using the 12-domain WHODAS 2.0. Severity of disability in each domain was scored from 1 = none to 5 = extreme and the total normalized to a 100-point scale (total score greater than or equal to25 = clinically significant disability). We also asked patients about wound-specific concerns and wound-related discomfort or distress. We included 162 patients. Reasons for clinic referral included arterial-insufficient (37.4%), postoperative (25.9%), and mixed etiology (10.8%) wounds. The mean WHODAS 2.0 disability score was 35.0 (standard deviation = 16.0). One-hundred-and-nineteen (73.5%) patients had clinically significant disability. Patients reported they had the greatest difficulty walking a long distance (mean score = 4.2), standing for long periods of time (mean score = 3.6), taking care of household responsibilities (mean score = 2.7), and dealing with the emotional impact of their health problems (mean score = 2.5). In the two-weeks prior to presentation, 87 (52.7%) patients expressed concern over their wound(s) and 90 (55.6%) suffered a moderate amount or great deal of wound-related discomfort or distress. In adjusted ordinary least squares regression models, although WHODAS 2.0 disability scores varied with changes in wound volume (p = 0.03) and total revised photographic wound assessment tool scores (p<0.001), the largest decrease in disability severity was seen in patients with less wound-specific concerns and wound-related discomfort and distress. The majority of people at risk of limb loss report suffering a substantial burden of disability, pain, and wound-specific concerns. Research is needed to further evaluate the WHODAS 2.0 in a multicenter fashion among these patients and determine whether care and interventions may improve their PROs.
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