Potentially Inappropriate Medication Dispensing in Outpatients: Comparison of Different Measurement Approaches.

Purpose of the Research: This paper aims at comparing different approaches to measure potentially inappropriate medication (PIM) with routinely collected data on prescriptions, patient age institutionalization status (ie in nursing home or in the community). A secondary objective is to measure the rate and prevalence of PIM dispensing and to identify problematic practices in Switzerland. Material and Methods: The studied population includes about 90,000 insured over 17 years old from a Swiss health maintenance organization in 2019 and 2020. We computed and compared the number of PIM per patient for Beers criteria, Priscus list, Laroche, NORGEP and Prescrire approaches. We also created a composite indicator that accounts for the specificities of the Swiss context (adaptation to the Swiss drugs' market, recommendations in force related to sleeping pills, anxiolytics and NSAIDs). We also stratified the analysis per physician, including initiation and cessation of PIM prescription. Results: Our comparison revealed similarities between the approaches, but also that each of them had specific gaps that provides further motivation for the development of a composite approach. PIM rate was particularly high for sleeping pills, anxiolytics, NSAIDs, even when analyses were limited to chronic use. Drugs with anticholinergic effect were also frequently prescribed. Based on our composite indicator, 27% of insured over 64 years old received at least one PIM in 2020, and 8% received more than one. Our analyses also reveal that for sleeping pills and anxiolytics, half of the volume (or prevalence?) occurs in the <65 population. We observed strong variations between physicians and a significant proportion of new users among patients with PIM. Conclusion: Our results show that PIMs prescribing is very frequent in Switzerland and is driven mostly by a few drug categories. There is important physician variation in PIM prescribing that warrants the development of intervention targeted at high PIM-prescribers.

Determinants of drug expenditure in the Swiss healthcare market in 2006.

BACKGROUND: Several measures are in force in Switzerland to control the cost of drugs, but are not effective enough. There are many determinants influencing these expenditures, related to treatments, markets, physicians, patients and regions, but their impact on costs is not clear. METHODS: We applied a Bayesian multilevel model with five levels to adjust for patients, drugs' market, and physicians 'characteristics, treatment type, and district (i.e. Swiss canton). We used data of the Swiss drugs' market in 2006, offering real choices for doctors and patients (multiple products for similar active substances), with a neutral position of pharmacists (no financial incentives). RESULTS: Variance partitioning of yearly drugs' cost per insured showed that market level (delivered substance) contributed to 76% of the variance, treatment level (delivered product) to 20%, whereas patients' and physicians' levels accounted for only 2% each, without significant differences between Swiss cantons. After adjusting for covariables at each level, the model explained about 51% of the variation at the market and 20% at the treatment levels. We found that older but substitutable drugs, generics, larger size of the market and physician's specialty were associated with lower expenditure, whereas drugs requiring a physician's prescription, the number of prescribers per patient, patient' age, male gender, and comorbidities increased expenditure. Our results show that for a specific medication the yearly cost of recently released drugs was 36 CHF higher than for similar and substitutable drugs introduced 15 years earlier, corresponding to one third of the average annual treatment cost observed in our dataset. Competition did not seem to be effective to reduce expenditure on the drug market. CONCLUSION: The main finding of this study is that recentness of drugs was associated with an increase in drug expenditure in 2006, even after adjustment for all non-controllable determinants. Further research is recommended to confirm those results with updated data.

Measuring medically unjustified hospitalizations in Switzerland.

BACKGROUND: Inappropriate use of acute hospital beds is a major topic in health politics. We present here a new approach to measure unnecessary hospitalizations in Medicine and Pediatrics. METHODS: The necessity of a hospital admission was determined using explicit criteria related to the recorded diagnoses. Two indicators (i.e. "unjustified" and "sometimes justified" stays) were applied to more than 800,000 hospital stays and a random sample of 200 of them was analyzed by two clinicians, using routine data available in medical statistics. The validation of the indicators focused on their precision, validity and adjustment, as well as their usefulness (i.e. interest and risk of abuse). RESULTS: Rates, adjusted for case mix (i.e. age of patient, admission planned or not), showed statistically significant differences among hospitals. Only 6.5% of false positives were observed for "unjustified stays" and 17% for "sometimes justified stays". Respectively 7 and 12% of stays had an unknown status, due to a lack of sufficiently precise data. Considering true positives only, almost one third of medical and pediatric stays were classified as not strictly justified from a medical point of view in Switzerland. Among these stays, about one fifth could have probably been avoided without risk. To enable a larger ambulatory shift, recommendations were made to strengthen the ambulatory care, notably regarding post-emergency follow-up, cardiac and pulmonary functions' monitoring, pain management, falls prevention, and specialized at-home services that should be offered. CONCLUSION: We recommend using "unjustified stays" and "sometimes justified stays" indicators to monitor inappropriate hospitalizations. The latter could help the planning of reinforced ambulatory care measures to pursue the ambulatory shift. Nonetheless, we clearly advise against the use of these two indicators for hospitals financing purposes.

Lessons from a pandemic.

Several interventions have been used around the world trying to contain the SARS-CoV-2 pandemic, such as quarantine, prohibition of mass demonstrations, isolation of sick people, tracing of virus carriers, semi-containment, promotion of barrier gestures, development of rapid self-tests and vaccines among others. We propose a simple model to evaluate the potential impact of such interventions. A model for the reproduction number of an infectious disease including three main contexts of infection (indoor mass events, public indoor activities and household) and seven parameters is considered. We illustrate how these parameters could be obtained from the literature or from expert assumptions, and we apply the model to describe 20 scenarios that can typically occur during the different phases of a pandemic. This model provides a useful framework for better understanding and communicating the effects of different (combinations of) possible interventions, while encouraging constant updating of expert assumptions to better match reality. This simple approach will bring more transparency and public support to help governments to think, decide, evaluate and adjust what to do during a pandemic.

A comparison of statistical methods for allocating disease costs in the presence of interactions.

We consider the non-trivial problem of estimating a health cost repartition among diseases from patients' hospital stays' global costs in the presence of multimorbidity, that is, when the patients may suffer from more than one disease. The problem is even harder in the presence of interactions among the disease costs, that is, when the costs of having, for example, two diseases simultaneously do not match the sum of the basic costs of having each disease alone, generating an extra cost which might be either positive or negative. In such a situation, there might be no "true solution" and the choice of the method to be used to solve the problem will depend on how one wishes to allocate the extra costs among the diseases. In this article, we study mathematically how different methods proceed in this regard, namely ordinary least squares (OLS), generalized linear models (GLM), and an iterative proportional repartition (IPR) algorithm, in a simple case with only two diseases. It turned out that only IPR allowed to retrieve the total costs and the unambiguous solution that one would have in a setting without interaction, that is, when no extra cost has to be allocated, while OLS and GLM may produce some negative health costs. Also, contrary to OLS, IPR is taking into account the basic costs of the diseases for the allocation of the extra cost. We conclude that IPR seems to be the most natural method to solve the problem, at least among those considered.

Patterns of benzodiazepine prescription among older adults in Switzerland: a cross-sectional analysis of claims data.

OBJECTIVE: This study aimed to examine the prevalence and determinants of benzodiazepine prescription among older adults in Switzerland, and analyse association with hospitalisation and costs. DESIGN: Retrospective analysis of claims data. SETTING: The study was conducted in nine cantons in Switzerland. PARTICIPANTS: Older adults aged 65 years and older enrolled with a large Swiss health insurance company participated in the study. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was prevalence of benzodiazepine prescription. The secondary outcomes were (1) determinants of any benzodiazepine prescription; (2) the association between any prescription and the probability of hospitalisation for trauma and (3) the association between any prescription and total healthcare expenditures. RESULTS: Overall, 69 005 individuals were included in the study. Approximately 20% of participants had at least one benzodiazepine prescription in 2017. Prescription prevalence increased with age (65-69: 15.9%; 70-74: 18.4%; 75-80: 22.5%; >80: 25.8%) and was higher in women (25.1%) compared with men (14.6%). Enrollees with the highest deductible of Swiss Francs (CHF) 2500 were 70% less likely to receive a prescription than enrollees with the lowest deductible of CHF 300 (adjusted OR=0.29, 95% CI 0.24 to 0.35).Individuals with at least one prescription had a higher probability of hospitalisation for trauma (OR=1.31, 95% CI 1. 20 to 1.1.44), and 70% higher health care expenditures (ß=0.72, 95% CI 0. 67 to 0.77). Enrollees in canton Valais were three times more likely to receive a prescription compared to enrollees from canton Aargau (OR=2.84, 95% 2.51 to 3.21). CONCLUSIONS: The proportion of older adults with at least one benzodiazepine prescription is high, as found in the data of one large Swiss health insurance company. These enrollees are more likely to be hospitalised for trauma and have higher healthcare expenditures. Important differences in prescription prevalence across cantons were observed, suggesting potential overuse. Further research is needed to understand the drivers of variation, prescription patterns across providers, and trends over time.

Estimating Health Cost Repartition Among Diseases in the Presence of Multimorbidity.

We consider the nontrivial problem of estimating the health cost repartition among different diseases in the common case where the patients may have multiple diseases. To tackle this problem, we propose to use an iterative proportional repartition (IPR) algorithm, a nonparametric method which is simple to understand and to implement, allowing (among other) to avoid negative cost estimates and to retrieve the total health cost by summing up the estimated costs of the different diseases. This method is illustrated with health costs data from Switzerland and is compared in a simulation study with other methods such as linear regression and general linear models. In the case of an additive model without interactions between disease costs, a situation where the truth is clearly defined such that the methods can be compared on an objective basis, the IPR algorithm clearly outperformed the other methods with respect to efficiency of estimation in all the settings considered. In the presence of interactions, the situation is more complex and will deserve further investigation.

Heterogeneity in The drivers of health expenditures financed by health insurance in a fragmented health system: The case of Switzerland.

Switzerland is the world's second largest spender on health care, both per capita and as a share of the Gross Domestic Product (GDP). The Swiss health care system is a federation of 26 cantonal systems with highly fragmented provision and financing of care, leading to important geographical disparities in expenditures. We propose a simple conceptual framework to guide the decomposition of health care expenditures into five core components (i.e. demography, propensity to use health services, substitution between domains of care, quantity of services delivered, and unit price of these services), with the objective of better understanding the drivers of geographic variation. We illustrate this framework using aggregated insurance data from 85 % of the 2006 insured population and measure cross-cantonal variation disaggregated into these five components. Results obtained indicated a West-East gradient of controllable costs after adjusting for demography and propensity to use health services. Moreover, we found specific explanations for cost overruns: visits to physicians in private practice in some cantons, and, e.g., outpatient hospital care or variations in drug related expenses in others. This shows that the simple proposed approach provides interesting insights into the drivers of cost differences between regions, specifically in terms of substitution among health services, quantity of delivered services, and their prices.

Assessment of Avoidable Readmissions in a Visceral Surgery Department with an Algorithm: Methodology, Analysis and Measures for Improvement.

BACKGROUND: Standardized quality indicators assessing avoidable readmission become increasingly important in health care. They can identify improvements area and contribute to enhance the care delivered. However, the way of using them in practice was rarely described. METHODS: Retrospective study uses prospective inpatients' information. Thirty-day readmissions were deemed potentially avoidable or non-avoidable by a computerized algorithm, and annual rate was reported between 2010 and 2014. Observed rate was compared to expected rate, and medical record review of potentially avoidable readmissions was conducted on data between January and June 2014. RESULTS: During a period of ten semesters, 11,011 stays were screened by the algorithm and a potentially avoidable readmission rate (PAR) of 7% was measured. Despite stable expected rate of 5 ± 0.5%, an increase was noted concerning the observed rate since 2012, with a highest value of 9.4% during the first semester 2014. Medical chart review assessed the 109 patients screened positive for PAR during this period and measured a real rate of 7.8%. The delta was in part due to an underestimated case mix owing to sub-coded comorbidities and not to health care issue. CONCLUSIONS: The present study suggests a methodology for practical use of data, allowing a validated quality of care indicator. The trend of the observed PAR rate showed a clear increase, while the expected PAR rate was stable. The analysis emphasized the importance of adequate "coding chain" when such an algorithm is applied. Moreover, additional medical chart review is needed when results deviate from the norm.

Determinants of new drugs prescription in the Swiss healthcare market.

BACKGROUND: Drug markets are very complex and, while many new drugs are registered each year, little is known about what drives the prescription of these new drugs. This study attempts to lift the veil from this important subject by analyzing simultaneously the impact of several variables on the prescription of novelty. METHODS: Data provided by four Swiss sickness funds were analyzed. These data included information about more than 470,000 insured, notably their drug intake. Outcome variable that captured novelty was the age of the drug prescribed. The overall variance in novelty was partitioned across five levels (substitutable drug market, patient, physician, region, and prescription) and the influence of several variables measured at each of these levels was assessed using a non-hierarchical multilevel model estimated by Bayesian Markov Chain Monte Carlo methods. RESULTS: More than 92% of the variation in novelty was explained at the substitutable drug market-level and at the prescription-level. Newer drugs were prescribed in markets that were costlier, less concentrated, included more insured, provided more drugs and included more active substances. Over-the-counter drugs were on average 12.5 years older while generic drugs were more than 15 years older than non-generics. Regional disparities in terms of age of prescribed drugs could reach 2.8 years. CONCLUSIONS: Regulation of the demand has low impact, with little variation explained at the patient-level and physician-level. In contrary, the market structure (e.g. end of patent with generic apparition, concurrence among producers) had a strong contribution to the variation of drugs ages.

Control limits to identify outlying hospitals based on risk-stratification.

Outcome indicators are routinely used to compare hospitals with respect to quality of care. Indicators might be based on observed proportions of adverse events (binary outcomes) or observed averages of e.g. lengths or costs of hospital stays (continuous outcomes). These observed values are compared with expected ones in an average hospital, which might be estimated from a reference sample and should be appropriately adjusted for the case mix of patients. One possibility to achieve a reliable adjustment is to stratify the patients according to their risks, where each patient belongs to one and only one stratum. Control limits calculated under the null hypothesis of an average hospital, allowing to decide whether a discrepancy between an observed and an expected value might be explained by chance or not, are then plotted around the indicator, such that hospitals falling above those control limits are detected as being statistically worse than an average hospital. Calculation of valid control limits is however not always obvious. In this article, we propose a simple and unified framework to calculate such control limits when adjustment is based on stratification, where we allow to distinguish and disentangle the variability explained by stratification and the variability due to chance, where we take into account the uncertainty about the estimation of the expected values, and where it is possible not only to detect those hospitals which are statistically worse, but also those which are statistically much worse than an average hospital. The method applies both to binary and continuous outcomes and is illustrated on Swiss hospital discharge data.

[Geriatric institutions, between ambulatory and hospital care: patients' description and performance assessment]. / Évaluation d'une structure gériatrique entre l'ambulatoire et l'hospitalier.

INTRODUCTION: To describe patients admitted to a geriatric institution, providing short-term hospitalizations in the context of ambulatory care in the canton of Geneva. To measure the performances of thisstructure in terms of quality ofcare and costs. METHOD: Data related to the clinical,functioning and participation profiles of the first 100 patients were collected. Data related to effects (readmission, deaths, satisfaction, complications), services and resources were also documented over an 8-month period to measure various quality and costindicators. Observed values were systematically compared to expected values, adjustedfor case mix. RESULTS: Explicit criteria were proposed to focus on the suitable patients, excluding situations in which other structures were considered to be more appropriate. The specificity of this intermediate structure was to immediately organize, upon discharge, outpatient services at home. The low rate of potentially avoidable readmissions, the high patient satisfaction scores, the absence of premature death and the low number of iatrogenic complications suggest that medical and nursing care delivered reflect a good quality of services. The cost was significantly lower than expected, after adjusting for case mix. CONCLUSION: The pilot experience showed that a short-stay hospitalization unit was feasible with acceptable security conditions. The attending physician's knowledge of the patients allowed this system tofocus on essential issues without proposing inappropriate services.

The effect of patient, provider and financing regulations on the intensity of ambulatory physical therapy episodes: a multilevel analysis based on routinely available data.

BACKGROUND: Many studies have found considerable variations in the resource intensity of physical therapy episodes. Although they have identified several patient- and provider-related factors, few studies have examined their relative explanatory power. We sought to quantify the contribution of patients and providers to these differences and examine how effective Swiss regulations are (nine-session ceiling per prescription and bonus for first treatments). METHODS: Our sample consisted of 87,866 first physical therapy episodes performed by 3,365 physiotherapists based on referrals by 6,131 physicians. We modeled the number of visits per episode using a multilevel log linear regression with crossed random effects for physiotherapists and physicians and with fixed effects for cantons. The three-level explanatory variables were patient, physiotherapist and physician characteristics. RESULTS: The median number of sessions was nine (interquartile range 6-13). Physical therapy use increased with age, women, higher health care costs, lower deductibles, surgery and specific conditions. Use rose with the share of nine-session episodes among physiotherapists or physicians, but fell with the share of new treatments. Geographical area had no influence. Most of the variance was explained at the patient level, but the available factors explained only 4% thereof. Physiotherapists and physicians explained only 6% and 5% respectively of the variance, although the available factors explained most of this variance. Regulations were the most powerful factors. CONCLUSION: Against the backdrop of abundant physical therapy supply, Swiss financial regulations did not restrict utilization. Given that patient-related factors explained most of the variance, this group should be subject to closer scrutiny. Moreover, further research is needed on the determinants of patient demand.

Comparing potentially avoidable hospitalization rates related to ambulatory care sensitive conditions in Switzerland: the need to refine the definition of health conditions and to adjust for population health status.

BACKGROUND: Regional rates of hospitalization for ambulatory care sensitive conditions (ACSC) are used to compare the availability and quality of ambulatory care but the risk adjustment for population health status is often minimal. The objectives of the study was to examine the impact of more extensive risk adjustment on regional comparisons and to investigate the relationship between various area-level factors and the properly adjusted rates. METHODS: Our study is an observational study based on routine data of 2 million anonymous insured in 26 Swiss cantons followed over one or two years. A binomial negative regression was modeled with increasingly detailed information on health status (age and gender only, inpatient diagnoses, outpatient conditions inferred from dispensed drugs and frequency of physician visits). Hospitalizations for ACSC were identified from principal diagnoses detecting 19 conditions, with an updated list of ICD-10 diagnostic codes. Co-morbidities and surgical procedures were used as exclusion criteria to improve the specificity of the detection of potentially avoidable hospitalizations. The impact of the adjustment approaches was measured by changes in the standardized ratios calculated with and without other data besides age and gender. RESULTS: 25% of cases identified by inpatient main diagnoses were removed by applying exclusion criteria. Cantonal ACSC hospitalizations rates varied from to 1.4 to 8.9 per 1,000 insured, per year. Morbidity inferred from diagnoses and drugs dramatically increased the predictive performance, the greatest effect found for conditions linked to an ACSC. More visits were associated with fewer PAH although very high users were at greater risk and subjects who had not consulted at negligible risk. By maximizing health status adjustment, two thirds of the cantons changed their adjusted ratio by more than 10 percent. Cantonal variations remained substantial but unexplained by supply or demand. CONCLUSION: Additional adjustment for health status is required when using ACSC to monitor ambulatory care. Drug-inferred morbidities are a promising approach.

Disease identification based on ambulatory drugs dispensation and in-hospital ICD-10 diagnoses: a comparison.

BACKGROUND: Pharmacy-based case mix measures are an alternative source of information to the relatively scarce outpatient diagnoses data. But most published tools use national drug nomenclatures and offer no head-to-head comparisons between drugs-related and diagnoses-based categories. The objective of the study was to test the accuracy of drugs-based morbidity groups derived from the World Health Organization Anatomical Therapeutic Chemical Classification of drugs by checking them against diagnoses-based groups. METHODS: We compared drugs-based categories with their diagnoses-based analogues using anonymous data on 108,915 individuals insured with one of four companies. They were followed throughout 2005 and 2006 and hospitalized at least once during this period. The agreement between the two approaches was measured by weighted kappa coefficients. The reproducibility of the drugs-based morbidity measure over the 2 years was assessed for all enrollees. RESULTS: Eighty percent used a drug associated with at least one of the 60 morbidity categories derived from drugs dispensation. After accounting for inpatient under-coding, fifteen conditions agreed sufficiently with their diagnoses-based counterparts to be considered alternative strategies to diagnoses. In addition, they exhibited good reproducibility and allowed prevalence estimates in accordance with national estimates. For 22 conditions, drugs-based information identified accurately a subset of the population defined by diagnoses. CONCLUSIONS: Most categories provide insurers with health status information that could be exploited for healthcare expenditure prediction or ambulatory cost control, especially when ambulatory diagnoses are not available. However, due to insufficient concordance with their diagnoses-based analogues, their use for morbidity indicators is limited.

Determinants of generic drug substitution in Switzerland.

BACKGROUND: Since generic drugs have the same therapeutic effect as the original formulation but at generally lower costs, their use should be more heavily promoted. However, a considerable number of barriers to their wider use have been observed in many countries. The present study examines the influence of patients, physicians and certain characteristics of the generics' market on generic substitution in Switzerland. METHODS: We used reimbursement claims' data submitted to a large health insurer by insured individuals living in one of Switzerland's three linguistic regions during 2003. All dispensed drugs studied here were substitutable. The outcome (use of a generic or not) was modelled by logistic regression, adjusted for patients' characteristics (gender, age, treatment complexity, substitution groups) and with several variables describing reimbursement incentives (deductible, co-payments) and the generics' market (prices, packaging, co-branded original, number of available generics, etc.). RESULTS: The overall generics' substitution rate for 173,212 dispensed prescriptions was 31%, though this varied considerably across cantons. Poor health status (older patients, complex treatments) was associated with lower generic use. Higher rates were associated with higher out-of-pocket costs, greater price differences between the original and the generic, and with the number of generics on the market, while reformulation and repackaging were associated with lower rates. The substitution rate was 13% lower among hospital physicians. The adoption of the prescribing practices of the canton with the highest substitution rate would increase substitution in other cantons to as much as 26%. CONCLUSIONS: Patient health status explained a part of the reluctance to substitute an original formulation by a generic. Economic incentives were efficient, but with a moderate global effect. The huge interregional differences indicated that prescribing behaviours and beliefs are probably the main determinant of generic substitution.

Surgical safety and hospital volume across a wide range of interventions.

OBJECTIVES: For certain major operations, inpatient mortality risk is lower in high-volume hospitals than those in low-volume hospitals. Extending the analysis to a broader range of interventions and outcomes is necessary before adopting policies based on minimum volume thresholds. METHODS: Using the United States 2004 Nationwide Inpatient Sample, we assessed the effect of intervention-specific and overall hospital volume on surgical complications, potentially avoidable reoperations, and deaths across 1.4 million interventions in 353 hospitals. Outcome variations across hospitals were analyzed through a 3-level hierarchical logistic regression model (patients, surgical interventions, and hospitals), which took into account interventions on multiple organs, 144 intervention categories, and structural hospital characteristics. Discriminative performance and calibration were good. RESULTS: Hospitals with more experience in a given intervention had similar reoperation rates but lower mortality and complication rates: odds ratio per volume deciles 0.93 and 0.97. However, the benefit was limited to heart surgery and a small number of other operations. Risks were higher for hospitals that performed more interventions overall: odds ratio per 1000 for each event was approximately 1.02. Even after adjustment for specific volume, mortality varied substantially across both high- and low-volume hospitals. CONCLUSION: Although the link between specific volume and certain inpatient outcomes suggests that specialization might help improve surgical safety, the variable magnitude of this link and the heterogeneity of hospital effect do not support the systematic use of volume-based referrals. It may be more efficient to monitor risk-adjusted postoperative outcomes and to investigate facilities with worse than expected outcomes.

Risk-adjusted rates for potentially avoidable reoperations were computed from routine hospital data.

OBJECTIVES: Reoperations may reflect a suboptimal initial surgical treatment. The study aimed to develop a screening algorithm for those potentially avoidable, using only routinely collected hospital data and a prediction model to adjust rates for case-mix. STUDY DESIGN AND SETTING: Data of a 3-year random sample of 7,370 therapeutic operations on inpatients, among which 833 were followed-up by a reoperation during the same stay. A review of medical records identified clearly avoidable and other potentially avoidable reoperations to develop and test the screening algorithm. A logistic prediction model of potentially avoidable reoperations was developed on one randomly chosen half of the data (about 9,000 interventions) and tested on the other half (cross-validation). RESULTS: Two hundred thirty-seven interventions (3%) were followed by a potentially avoidable reoperation, among which 144 were clearly avoidable. The screening algorithm had a sensitivity of 75% and a specificity of 72%. Predictors of potentially avoidable reoperations were surgery categories, diagnosis related conditions, and experiencing prior surgery. The risk score, based on these variables, showed at once a satisfactory discriminative performance (C-statistic=0.76) and goodness-of-fit measure on the validation set. CONCLUSION: The adjusted rate of potentially avoidable reoperations should be included in internal reporting of hospital quality indicators, but further validated in various settings.

Validation of the potentially avoidable hospital readmission rate as a routine indicator of the quality of hospital care.

BACKGROUND: The hospital readmission rate has been proposed as an important outcome indicator computable from routine statistics. However, most commonly used measures raise conceptual issues. OBJECTIVES: We sought to evaluate the usefulness of the computerized algorithm for identifying avoidable readmissions on the basis of minimum bias, criterion validity, and measurement precision. RESEARCH DESIGN AND SUBJECTS: A total of 131,809 hospitalizations of patients discharged alive from 49 hospitals were used to compare the predictive performance of risk adjustment methods. A subset of a random sample of 570 medical records of discharge/readmission pairs in 12 hospitals were reviewed to estimate the predictive value of the screening of potentially avoidable readmissions. MEASURES: Potentially avoidable readmissions, defined as readmissions related to a condition of the previous hospitalization and not expected as part of a program of care and occurring within 30 days after the previous discharge, were identified by a computerized algorithm. Unavoidable readmissions were considered as censored events. RESULTS: A total of 5.2% of hospitalizations were followed by a potentially avoidable readmission, 17% of them in a different hospital. The predictive value of the screen was 78%; 27% of screened readmissions were judged clearly avoidable. The correlation between the hospital rate of clearly avoidable readmission and all readmissions rate, potentially avoidable readmissions rate or the ratio of observed to expected readmissions were respectively 0.42, 0.56 and 0.66. Adjustment models using clinical information performed better. CONCLUSION: Adjusted rates of potentially avoidable readmissions are scientifically sound enough to warrant their inclusion in hospital quality surveillance.