Hospitalization for mental illness: evaluation of admission trends from 1941 to 1971.

A study of the diagnostic composition of the inpatient population of Ontario and Canadian psychiatric facilities has shown an important change in hospital-treated illness over the period 1941-71. Patients with nonpsychotic disorders accounted for 54% of all admissions to Ontario public mental hospitals in 1971, compared with only 8% in 1941. The trend was similar for both first admissions and proportion of readmissions, and was similar for psychiatric units of general hospitals. In contrast, the overall rate of first admission for psychotic disorders to inpatient facilities remained remarkably constant over time, as did the proportion of readmissions among all admissions. The findings dispel the notion that the increasing proportion of readmissions is due largely to a rapid turnover of former long-stay psychotic patients (the "revolving-door phenomenon"). The findings could not be attributed to a changing prevalence of types of psychiatric illness, increased availability of psychiatric inpatient facilities or comprehensive medical insurance.     

Incidence of potentially avoidable urgent readmissions and their relation to all-cause urgent readmissions

Background:

Urgent, unplanned hospital readmissions are increasingly being used to gauge the quality of care. We reviewed urgent readmissions to determine which were potentially avoidable and compared rates of all-cause and avoidable readmissions.

Methods:

In a multicentre, prospective cohort study, we reviewed all urgent readmissions that occurred within six months among patients discharged to the community from 11 teaching and community hospitals between October 2002 and July 2006. Summaries of the readmissions were reviewed by at least four practising physicians using standardized methods to judge whether the readmission was an adverse event (poor clinical outcome due to medical care) and whether the adverse event could have been avoided. We used a latent class model to determine whether the probability that each readmission was truly avoidable exceeded 50%.

Results:

Of the 4812 patients included in the study, 649 (13.5%, 95% confidence interval [CI] 12.5%–14.5%) had an urgent readmission within six months after discharge. We considered 104 of them (16.0% of those readmitted, 95% CI 13.3%–19.1%; 2.2% of those discharged, 95% CI 1.8%–2.6%) to have had a potentially avoidable readmission. The proportion of patients who had an urgent readmission varied significantly by hospital (range 7.5%–22.5%; χ² = 92.9, p < 0.001); the proportion of readmissions deemed avoidable did not show significant variation by hospital (range 1.2%–3.7%; χ² = 12.5, p < 0.25). We found no association between the proportion of patients who had an urgent readmission and the proportion of patients who had an avoidable readmission (Pearson correlation 0.294; p = 0.38). In addition, we found no association between hospital rankings by proportion of patients readmitted and rankings by proportion of patients with an avoidable readmission (Spearman correlation coefficient 0.28, p = 0.41).

Interpretation:

Urgent readmissions deemed potentially avoidable were relatively uncommon, comprising less than 20% of all urgent readmissions following hospital discharge. Hospital-specific proportions of patients who were readmitted were not related to proportions with a potentially avoidable readmission.Urgent, unplanned hospital readmissions are increasingly being used to measure institutional or regional quality of care.^1–4 The public reporting of readmissions and their use in considerations for funding suggest a belief that readmissions indicate the quality of care provided by particular institutions. However, urgent readmissions are an informative metric only if we know what proportion of them are avoidable. If they are rarely avoidable, they would be a poor gauge of the quality of patient care.Current estimates of the proportion of urgent readmissions that are avoidable are unreliable. In a systematic review of 34 studies that reviewed how many readmissions were avoidable, 3 of the studies relied solely on combinations of administrative diagnostic codes, and most used undefined or subjective criteria.⁵ In addition, most of the studies were conducted at a single centre and used only one reviewer. The proportion of readmissions deemed avoidable varied widely, from 5.1%⁶ to 78.9%,⁷ which reflected in part the lack of standardized and reliable methods to identify avoidable readmissions.We conducted a multicentre prospective cohort study to elicit judgments from multiple practising physicians who used standard implicit review methods to determine whether urgent readmissions were potentially avoidable. We analyzed these judgments using a latent class analysis. We also measured the proportion of readmissions deemed avoidable and compared hospital-specific proportions of all-cause and avoidable readmissions.     

Are readmissions avoidable?

OBJECTIVE--To examine the possible use of readmission rates as an outcome indicator of hospital inpatient care by investigating avoidability of unplanned readmissions within 28 days of discharge. DESIGN--Retrospective analysis of a stratified random sample of case notes of patients with an unplanned readmission between July 1987 and June 1988 by nine clinical assessors (263 assessments) and categorisation of the readmission as avoidable, unavoidable, or unclassifiable. SETTING--District in North East Thames region. 481 General medical, geriatric, and general surgical inpatients with a readmission at 0-6 days or 21-27 days after the first (index) discharge between July 1987 and June 1988 from whom 100 case notes were selected randomly and of which 74 were available for study. MAIN OUTCOME MEASURES--Assessment of readmissions as avoidable, unavoidable, unclassifiable, variability of assessment within cases and variability among assessors according to specialty and duration to readmission. RESULTS--General medical and geriatric readmissions and surgical readmissions at 0-6 days after discharge were more likely to be assessed as avoidable than those at 21-27 days (medical readmissions 32 v 6%, surgical admissions 49 v 19%). General surgical readmissions were significantly more frequently assessed as avoidable than general medical and geriatric readmissions. The extent of agreement between doctors varied, with general medical and geriatric readmissions at 21-27 days after first discharge causing the greatest variability of judgment. CONCLUSIONS--Differences were apparent in the extent of avoidability of readmissions in different groups of admissions. However, assessors rated only 49.3% of the group with the highest proportion of avoidable admissions (surgical readmissions at 0-6 days) as avoidable. The remainder were thought to be unavoidable except for 2%, which could not be classified. The use of readmission rates as an outcome indicator of hospital inpatient care should be avoided.     

Readmissions after Hospitalization for Heart Failure,Acute Myocardial Infarction,or Pneumonia among Young and Middle-Aged Adults: A Retrospective Observational Cohort Study

Background

Patients aged ≥65 years are vulnerable to readmissions due to a transient period of generalized risk after hospitalization. However, whether young and middle-aged adults share a similar risk pattern is uncertain. We compared the rate, timing, and readmission diagnoses following hospitalization for heart failure (HF), acute myocardial infarction (AMI), and pneumonia among patients aged 18–64 years with patients aged ≥65 years.

Methods and Findings

We used an all-payer administrative dataset from California consisting of all hospitalizations for HF (n = 206,141), AMI (n = 107,256), and pneumonia (n = 199,620) from 2007–2009. The primary outcomes were unplanned 30-day readmission rate, timing of readmission, and readmission diagnoses. Our findings show that the readmission rate among patients aged 18–64 years exceeded the readmission rate in patients aged ≥65 years in the HF cohort (23.4% vs. 22.0%, p<0.001), but was lower in the AMI (11.2% vs. 17.5%, p<0.001) and pneumonia (14.4% vs. 17.3%, p<0.001) cohorts. When adjusted for sex, race, comorbidities, and payer status, the 30-day readmission risk in patients aged 18–64 years was similar to patients ≥65 years in the HF (HR 0.99; 95%CI 0.97–1.02) and pneumonia (HR 0.97; 95%CI 0.94–1.01) cohorts and was marginally lower in the AMI cohort (HR 0.92; 95%CI 0.87–0.96). For all cohorts, the timing of readmission was similar; readmission risks were highest between days 2 and 5 and declined thereafter across all age groups. Diagnoses other than the index admission diagnosis accounted for a substantial proportion of readmissions among age groups <65 years; a non-cardiac diagnosis represented 39–44% of readmissions in the HF cohort and 37–45% of readmissions in the AMI cohort, while a non-pulmonary diagnosis represented 61–64% of patients in the pneumonia cohort.

Conclusion

When adjusted for differences in patient characteristics, young and middle-aged adults have 30-day readmission rates that are similar to elderly patients for HF, AMI, and pneumonia. A generalized risk after hospitalization is present regardless of age. Please see later in the article for the Editors'' Summary     

Inequality in Diabetes-Related Hospital Admissions in England by Socioeconomic Deprivation and Ethnicity: Facility-Based Cross-Sectional Analysis

ObjectiveTo investigate the effect of social deprivation and ethnicity on inpatient admissions due to diabetes in England.DesignFacility-based cross-sectional analysis.SettingNational Health Service (NHS) trusts in England reporting inpatient admissions with better than 80% data reporting quality from 2010–2011 (355 facilities).ParticipantsNon-obstetric patients over 16 years old in all NHS facilities in England. The sample size after exclusions was 5,147,859 all-cause admissions.ResultsThere were 445,504 diabetes-related hospital admissions in England in 2010, giving a directly (age-sex) standardized rate of 1049.0 per 100,000 population (95% confidence interval (CI): 1046.0–1052.1). The relative risk of inpatient admission in the most deprived quintile was 2.08 times higher than that of the least deprived quintile (95% CI: 2.02–2.14), and the effect of deprivation varied across ethnicities. About 30.1% of patients admitted due to diabetes were readmitted at least once due to diabetes. South Asians showed 2.62 times (95% CI: 2.51 – 2.74) higher admission risk. Readmission risk increased with IMD among white British but not other ethnicities. South Asians showed slightly lower risk of readmission than white British (0.86, 95% CI: 0.80 – 0.94).ConclusionsMore deprived areas had higher rates of inpatient admissions and readmissions due to diabetes. South Asian British showed higher admission risk and lower readmission risk than white British. However, there was almost no difference by ethnicity in readmission due to diabetes. Higher rates of admission among deprived people may not necessarily reflect higher prevalence, but higher admission rates in south Asian British may be explained by their higher prevalence because their lower readmission risk suggests no inequality in primary care to prevent readmission. Better interventions in poorer areas, are needed to reduce these inequalities.     

Hospital Readmission Prevalence and Analysis of Those Potentially Avoidable in Southern Italy

Background

One quality indicator of hospital care, which can be used to judge the process of care, is the prevalence of hospital readmission because it reflects the impact of hospital care on the patient’s condition after discharge. The purposes of the study were to measure the prevalence of hospital readmissions, to identify possible factors that influence such readmission and to measure the prevalence of readmissions potentially avoidable in Italy.

Methods

A sample of 2289 medical records of patients aged 18 and over admitted for medical or surgical illness at one 502-bed community non-teaching hospital were randomly selected.

Results

A total of 2252 patients were included in the final analysis, equaling a response rate of 98.4%. The overall hospital readmission prevalence within 30 days of discharge was 10.2%. Multivariate logistic regression analysis revealed that the proportion of patients readmitted within 30 days of discharge significantly increased regardless of Charlson et al. comorbidity score, among unemployed or retired patients, and in patients in general surgery. A total of 43.7% hospital readmissions were judged to be potentially avoidable. Multivariate logistic regression analysis showed that potentially avoidable readmissions were significantly higher in general surgery, in patients referred to hospital by an emergency department physician, and in those with a shortened time between discharge and readmission.

Conclusion

Additional research on intervention or bundle of interventions applicable to acute inpatient populations that aim to reduce potentially avoidable readmissions is strongly needed, and health care providers are urged to implement evidence-based programs for more cost-effective delivery of health care.     

Use of medical record linkage to study readmission rates.

Readmission rates after inpatient care were studied by using routinely collected data from the Oxford record linkage study for 1968-85. Discharges from hospital and subsequent admissions were identified for people who were both resident and treated in the area covered by the linkage study. Rates were calculated for readmissions within 28 days after discharge from the first, index event. Readmission rates for elective readmissions after elective index admissions rose from 3.5% in 1968 to 7.1% in 1985. Those for elective readmissions after immediate (emergency or accident) index admissions rose from 2.4% to 3.5% during the same period. Emergency readmissions after an immediate index admission rose from 4.0% to 7.0%, and emergency readmissions after an elective index admission rose from 1.3% to 2.5%. All these increases were significant. The rise in elective readmissions may in part reflect a trend towards planned discharge with the expectation of readmission. The rise in emergency readmissions, which has been fairly gradual over many years, may, in some cases, be due to pressure on resources and inappropriately short lengths of stay. Further evidence is required to confirm or refute this. Readmission rates are one of the few potential measures available from routine statistics for assessing outcome, but due consideration must be given to issues of method and interpretation.     

The TAPS project. 17: Readmission to hospital for long term psychiatric patients after discharge to the community.

OBJECTIVE--To identify risk factors which increase the likelihood of readmission for long stay psychiatric patients after discharge from hospital. DESIGN--Follow up for five years of all long stay patients discharged from two large psychiatric hospitals to compare patients readmitted and not readmitted. SETTING--Friern and Claybury Hospitals in north London and their surrounding catchment areas. Most patients were discharged to staffed or unstaffed group homes. SUBJECTS--357 psychiatric patients who had been in hospital for over one year, of whom 118 were "new" long stay and 239 "old" long stay patients. MAIN OUTCOME MEASURES--Readmission to hospital and length of subsequent stay. RESULTS--Of all discharged patients 97 (27%) were readmitted at some time during the follow up period, 57 (16%) in the first year after discharge, and 31 (9%) then remained in hospital for over a year. The best explanatory factors for readmission were: male sex, younger age group, high number of previous admissions, higher levels of symptomatic and social behavioural disturbance, a diagnosis of manic-depressive psychosis, and living in a non-staffed group home. CONCLUSIONS--During the closure of psychiatric hospitals, facilities need to be preserved for acute relapses among long term, and especially younger, discharged patients. Staffed group homes may help prevent relapse and reduce the number of admission beds required.     

Proportion of hospital readmissions deemed avoidable: a systematic review

Background

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.

Methods

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.

Results

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.

Interpretation

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.In most instances, unplanned readmissions to hospital indicate bad health outcomes for patients. Sometimes they are due to a medical error or the provision of suboptimal patient care. Other times, they are unavoidable because they are due to the development of new conditions or the deterioration of refractory, severe chronic conditions.Hospital readmissions are frequently used to gauge patient care. Many organizations use them as a metric for institutional or regional quality of care.¹ The widespread public reporting of hospital readmissions and their use in considerations for funding implicitly suggest a belief that readmissions indicate the quality of care provided by particular physicians and institutions.The validity of hospital readmissions as an indicator of quality of care depends on the extent that readmissions are avoidable. As the proportion of readmissions deemed to be avoidable decreases, the effort and expense required to avoid one readmission will increase. This decrease in avoidable admissions will also dilute the relation between the overall readmission rate and quality of care. Therefore, it is important to know the proportion of hospital readmissions that are avoidable.We conducted a systematic review of studies that measured the proportion of readmissions that were avoidable. We examined how such readmissions were measured and estimated their prevalence.     

Readmission for Acute Exacerbation within 30 Days of Discharge Is Associated with a Subsequent Progressive Increase in Mortality Risk in COPD Patients: A Long-Term Observational Study

Background and Objective

Twenty per cent of chronic obstructive pulmonary disease (COPD) patients are readmitted for acute exacerbation (AECOPD) within 30 days of discharge. The prognostic significance of early readmission is not fully understood. The objective of our study was to estimate the mortality risk associated with readmission for acute exacerbation within 30 days of discharge in COPD patients.

Methods

The cohort (n = 378) was divided into patients readmitted (n = 68) and not readmitted (n = 310) within 30 days of discharge. Clinical, laboratory, microbiological, and severity data were evaluated at admission and during hospital stay, and mortality data were recorded at four time points during follow-up: 30 days, 6 months, 1 year and 3 years.

Results

Patients readmitted within 30 days had poorer lung function, worse dyspnea perception and higher clinical severity. Two or more prior AECOPD (HR, 2.47; 95% CI, 1.51–4.05) was the only variable independently associated with 30-day readmission. The mortality risk during the follow-up period showed a progressive increase in patients readmitted within 30 days in comparison to patients not readmitted; moreover, 30-day readmission was an independent risk factor for mortality at 1 year (HR, 2.48; 95% CI, 1.10–5.59). In patients readmitted within 30 days, the estimated absolute increase in the mortality risk was 4% at 30 days (number needed to harm NNH, 25), 17% at 6-months (NNH, 6), 19% at 1-year (NNH, 6) and 24% at 3 years (NNH, 5).

Conclusion

In conclusion a readmission for AECOPD within 30 days is associated with a progressive increased long-term risk of death.     

Readmission rates of patients discharged against medical advice: a matched cohort study

Objective

We compared the readmission rates and the pattern of readmission among patients discharged against medical advice (AMA) to control patients discharged with approval over a one-year follow-up period.

Methods

A retrospective matched-cohort study of 656 patients(328 were discharged AMA) who were followed for one year after their initial hospitalization at an urban university-affiliated teaching hospital in Vancouver, Canada that serves a population with high prevalence of addiction and psychiatric disorders. Multivariate conditional logistic regression was used to examine the independent association of discharge AMA on 14-day related diagnosis hospital readmission. We fit a multivariate conditional negative binomial regression model to examine the readmission frequency ratio between the AMA and non-AMA group.

Principal Findings

AMA patients were more likely to be homeless (32.3% vs. 11%) and have co-morbid conditions such as psychiatric illnesses, injection drug use, HIV, hepatitis C and previous gastrointestinal bleeding. Patients discharged AMA were more likely to be readmitted: 25.6% vs. 3.4%, p<0.001 by day 14. The AMA group were more likely to be readmitted within 14 days with a related diagnosis than the non-AMA group (Adjusted Odds Ratio 12.0; 95% Confidence Interval [CI]: 3.7–38.9). Patients who left AMA were more likely to be readmitted multiple times at one year compared to the non-AMA group (adjusted frequency ratio 1.6; 95% CI: 1.3–2.0). There was also higher all-cause in-hospital mortality during the 12-month follow-up in the AMA group compared to non-AMA group (6.7% vs. 2.4%, p = 0.01).

Conclusions

Patients discharged AMA were more likely to be homeless and have multiple co-morbid conditions. At one year follow-up, the AMA group had higher readmission rates, were predisposed to multiple readmissions and had a higher in-hospital mortality. Interventions to reduce discharges AMA in high-risk groups need to be developed and tested.     

Thirty-Day Readmission Rates in Orthopedics: A Systematic Review and Meta-Analysis

Background

Hospital readmission rates are being used to evaluate performance. A survey of the present rates is needed before policies can be developed to decrease incidence of readmission. We address three questions: What is the present rate of 30-day readmission in orthopedics? How do factors such as orthopedic specialty, data source, patient insurance, and time of data collection affect the 30-day readmission rate? What are the causes and risk factors for 30-day readmissions?

Methods/Findings

A review was first registered with Prospero (CRD42014010293, 6/17/2014) and a meta-analysis was performed to assess the current 30-day readmission rate in orthopedics. Studies published after 2006 were retrieved, and 24 studies met the inclusion criteria. The 30-day readmission rate was extrapolated from each study along with the orthopedic subspecialty, data source, patient insurance, time of collection, patient demographics, and cause of readmission. A sensitivity analysis was completed on the stratified groups. The overall 30-day readmission rate across all orthopedics was 5.4 percent (95% confidence interval: 4.8,6.0). There was no significant difference between subspecialties. Studies that retrieved data from a multicenter registry had a lower 30-day readmission rate than those reporting data from a single hospital or a large national database. Patient populations that only included Medicare patients had a higher 30-day readmission rate than populations of all insurance. The 30-day readmission rate has decreased in the past ten years. Age, length of stay, discharge to skilled nursing facility, increased BMI, ASA score greater than 3, and Medicare/Medicaid insurance showed statistically positive correlation with increased 30-day readmissions in greater than 75 percent of studies. Surgical site complications accounted for 46 percent of 30-day readmissions.

Conclusions

This meta-analysis shows the present rate of 30-day readmissions in orthopedics. Demonstrable heterogeneity between studies underlines the importance of uniform collection and reporting of readmission rates for hospital evaluation and reimbursement.     

Hospital Readmissions of Patients with Heart Failure: The Impact of Hospital and Primary Care Organizational Factors in Northern Italy

BackgroundPrimary health care is essential for an appropriate management of heart failure (HF), a disease which is a major clinical and public health issue and a leading cause of hospitalization. The aim of this study was to evaluate the impact of different organizational factors on readmissions of patients with HF.MethodsThe study population included elderly resident in the Local Health Authority of Bologna (Northern Italy) and discharged with a diagnosis of HF from January to December 2010. Unplanned hospital readmissions were measured in four timeframes: 30 (short-term), 90 (medium-term), 180 (mid-long-term), and 365 days (long-term). Using multivariable multilevel Poisson regression analyses, we investigated the association between readmissions and organizational factors (discharge from a cardiology department, general practitioners’ monodisciplinary organizational arrangement, and implementation of a specific HF care pathway).ResultsThe 1873 study patients had a median age of 83 years (interquartile range 77–87) and 55.5% were females; 52.0% were readmitted to the hospital for any reason after a year, while 20.1% were readmitted for HF. The presence of a HF care pathway was the only factor significantly associated with a lower risk of readmission for HF in the short-, medium-, mid-long- and long-term period (short-term: IRR [incidence rate ratio]=0.57, 95%CI [confidence interval]=0.35–0.92; medium-term: IRR=0.70, 95%CI=0.51–0.96; mid-long-term: IRR=0.79, 95%CI=0.64–0.98; long-term: IRR=0.82, 95%CI=0.67–0.99), and with a lower risk of all-cause readmission in the short-term period (IRR=0.73, 95%CI=0.57–0.94).ConclusionOur study shows that the HF care specific pathway implemented at the primary care level was associated with lower readmission rate for HF in each timeframe, and also with lower readmission rate for all causes in the short-term period. Our results suggest that the engagement of primary care professionals starting from the early post-discharge period may be relevant in the management of patients with HF.     

Recurrent psychiatric hospitalization.

Undue emphasis has been placed on rising rates of readmission to psychiatric facilities. After a decade of preoccupation with discharge rates, readmission statistics have been singled out in the last 15 years as the key factor for assessing hospital effectiveness. A study of a group of patients at high risk for recurrent hospitalization revealed that these patients were characterized more by features relating to environmental supports than by diagnosis. The operational definition for recurrent hospitalization (five or more admissions during the 2-year period preceding the latest admission) was effective in identifying this group; this is the first reported instance in which the definition has specified a certain number of admissions within a time-limited period. The findings of this study, as well as of an analysis of case histories and consumer opinion, led to the design of a pilot program for persons undergoing recurrent hospitalization. Readmission statistics are useless or misleading as measures of hospital effectiveness and efficiency; what matters is the way the former patients function in the community after discharge. Rather than simply trying to reduce the readmission rate psychiatric facilities should be examining the types of persons who are hospitalized recurrently to develop programs aimed at improving the functioning of these people in the community.     

Tobacco Stained Fingers and Its Association with Death and Hospital Admission: A Retrospective Cohort Study

Background

Among smokers, the presence of tobacco stains on fingers has recently been associated with a high prevalence of tobacco related conditions and alcohol abuse.

Objective

we aimed to explore tobacco stains as a marker of death and hospital readmission.

Method

Seventy-three smokers presenting tobacco-tar staining on their fingers and 70 control smokers were followed during a median of 5.5 years in a retrospective cohort study. We used the Kaplan-Meier survival analysis and the log-rank test to compare mortality and hospital readmission rates among smokers with and smokers without tobacco stains. Multivariable Cox models were used to adjust for confounding factors: age, gender, pack-year unit smoked, cancer, harmful alcohol use and diabetes. The number of hospital admissions was compared through a negative binomial regression and adjusted for the follow-up time, diabetes, and alcohol use.

Results

Forty-three patients with tobacco-stained fingers died compared to 26 control smokers (HR 1.6; 95%CI: 1.0 to 2.7; p 0.048). The association was not statistically significant after adjustment. Patients with tobacco-stained fingers needed a readmission earlier than smokers without stains (HR 2.1; 95%CI: 1.4 to 3.1; p<0.001), and more often (incidence rate ratio (IRR) 1.6; 95%CI: 1.1 to 2.1). Associations between stains and the first hospital readmission (HR 1.6; 95%CI: 1.0 to 2.5), and number of readmissions (IRR 1.5; 95%CI: 1.1 to 2.1) persisted after adjustment for confounding factors.

Conclusions

Compared to other smokers, those presenting tobacco-stained fingers have a high unadjusted mortality rate and need early and frequent hospital readmission even when controlling for confounders.     

Measuring readmission rates.

OBJECTIVE--To assess the feasibility of extracting data on readmissions and readmission rates from Körner data for use as health service indicators. DESIGN--Retrospective analysis of inpatient Körner data for January 1988 to April 1989. SETTING--Three districts in North East Thames region. MAIN OUTCOME MEASURES--Number of readmissions after index discharge for all acute specialties combined and by specialty (general medicine, general surgery, gynaecology, trauma and orthopaedics, and geriatrics); readmission rates at 28 days after index discharge; and rates standardised for age group and sex by specialty and by consultant. RESULTS--All specialties showed an early peak in number of admissions, which levelled off by 28 days. Readmission rates at 28 days were appreciably lower in surgical specialties than in medical specialties (for example, general surgery 4.1% v geriatric medicine 15.1%). They were related to age and sex of the patient. Rates standardised for these variables did not significantly differ by district. Likewise, significant differences in standardised rates were not obtained for consultants within a specialty in one district. CONCLUSIONS--Readmission rates may be measured with Körner data. The pattern of readmissions with time means that readmission rates should be measured at not more than 28 days after the index discharge; the rates require standardisation for age and sex. Annual comparisons of standardised rates may be made among districts for combinations of specialties; those among individual consultants or specialties are unlikely to be statistically valid.     

Emergency Department Non-Urgent Visits and Hospital Readmissions Are Associated with Different Socio-Economic Variables in Italy

Objective

The aim of this paper was to evaluate socio-economic factors associated to poor primary care utilization by studying two specific subjects: the hospital readmission rate, and the use of the Emergency Department (ED) for non-urgent visits.

Methods

The study was carried out by the analysis of administrative database for hospital readmission and with a specific survey for non-urgent ED use.

Results

Among the 416,698 sampled admissions, 6.39% (95% CI, 6.32–6.47) of re-admissions have been registered; the distribution shows a high frequency of events in the age 65–84 years group, and in the intermediate care hospitals (51.97%; 95%CI 51.37–52.57). The regression model has shown the significant role played by age, type of structure (geriatric acute care), and deprivation index of the area of residence on the readmission, however, after adjusting for the intensity of primary care, the role of deprivation was no more significant. Non-urgent ED visits accounted for the 12.10%, (95%CI 9.38–15.27) of the total number of respondents to the questionnaire (N = 504). The likelihood of performing a non-urgent ED visit was higher among patients aged <65 years (OR 3.2, 95%CI 1.3–7.8 p = 0.008), while it was lower among those perceiving as urgent their health problem (OR 0.50, 95%CI 0.30–0.90).

Conclusions

In the Italian context repeated readmissions and ED utilization are linked to different trajectories, besides the increasing age and comorbidity of patients are the factors that are related to repeated admissions, the self-perceived trust in diagnostic technologies is an important risk factor in determining ED visits. Better use of public national health care service is mandatory, since its correct utilization is associated to increasing equity and better health care utilization.     

Healthcare Resource Utilization for Recurrent Clostridium difficile Infection in a Large University Hospital in Houston,Texas

Background

There are limited data examining healthcare resource utilization in patients with recurrent Clostridium difficile infection (CDI).

Methods

Patients with CDI at a tertiary-care hospital in Houston, TX, were prospectively enrolled into an observational cohort study. Recurrence was assessed via follow-up phone calls. Patients with one or more recurrence were included in this study. The location at which healthcare was obtained by patients with recurrent CDI was identified along with hospital length of stay. CDI-attributable readmissions, defined as a positive toxin test within 48 hours of admission and a primary CDI diagnosis, were also assessed.

Results

372 primary cases of CDI were identified of whom 64 (17.2%) experienced at least one CDI recurrence. Twelve of 64 patients experienced 18 further episodes of CDI recurrence. Of these 64 patients, 33 (50.8%) patients with recurrent CDI were readmitted of which 6 (18.2%) required ICU care, 29 (45.3%) had outpatient care only, and 2 (3.1%) had an ED visit. Nineteen (55.9%) readmissions were defined as CDI-attributable. For patients with CDI-attributable readmission, the average length of stay was 6±6 days.

Conclusion

Recurrent CDI leads to significant healthcare resource utilization. Methods of reducing the burden of recurrent CDI should be further studied.     

Trends in the hospital care of acute childhood asthma 1970-8: a regional study.

In the South-west Thames Region over the period 1970-8 the number of admissions for asthma in children aged 5-14 years increased from 256 to 684, an increase of 167%. Factors associated with this trend were investigated by an analysis of routine hospital statistics and examination of case notes for 1970 and 1978 from every hospital in the region. The trend was caused partly by an increase in readmission rates. There was a more than fivefold increase in self-referrals; these patients had less severe asthma on admission and a higher readmission rate than patients referred by general practitioners. Drug management before and after admission changed considerably over the nine years, as did hospital investigations. Overall, there was little change in the level of severity on admission. The increase in admissions was not associated with a reduction in deaths from asthma in the region and occurred in spite of major advances in the drug control of asthma; this indicates an inadequacy of ambulatory care. The shift in the balance of care towards the hospital and the increasing adoption of a primary care function by the hospital indicate a need for hospitals and general practice to agree jointly on management policies for acute asthma.     

Factors affecting early unplanned readmission of elderly patients to hospital.

A random sample of 133 elderly patients who had an unplanned readmission to a district general hospital within 28 days of discharge from hospital was studied and compared with a matched control sample of patients who were not readmitted. The total group was drawn from all specialties in the hospital, and by interviewing the patients, their carers, the ward sisters, and the patients'' general practitioners the factors causing early unplanned readmission for each patient were identified. Seven possible principal reasons were found: relapse of original condition, development of a new problem, carer problems, complications of the initial illness, need for terminal care, problems with medication, and problems with services. There were also contributory reasons, and it was usual for several of these to be present in each case. The unplanned readmission rate was 6%; the planned readmission rate was 3%. It was thought that unplanned readmission was avoidable for 78 (59%) patients. Patients in the study group and in the control group showed significant differences in certain characteristics--such as low income, previous hospital admission, already having nursing care, and admission by general practitioners--and this might help to identify patients who are likely to be readmitted in an emergency.