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Background Improving the process of hospital discharge is a critical priority. Interventions to improve care transitions have been shown to reduce the rate of early unplanned readmissions, and consequently, there is growing interest in improving transitions of care between hospital and home through appropriate interventions. Project Re-Engineered Discharge (RED) has shown promise in strengthening the discharge process. Although studies have analyzed the implementation of RED among private-sector hospitals, little is known about how hospitals in the Veterans Health Administration (VHA) have implemented RED. The RED implementation process was evaluated in five VHA hospitals, and contextual factors that may impede or facilitate the undertaking of RED were identified. Methods A qualitative evaluation of VHA hospitals' implementation of RED was conducted through semistructured telephone interviews with personnel involved in RED implementation. Qualitative data from these interviews were coded and used to compare implementation activities across the five sites. In addition guided by the Practical, Robust Implementation and Sustainability Model (PRISM), cross-site analyses of the contextual factors were conducted using a consensus process. Results Progress and adherence to the RED toolkit implementation steps and intervention components varied across study sites. A majority of contextual factors identified were positive influences on sites' implementation. Conclusion Although the study sites were able to tailor and implement RED because of its adaptability, redesigning discharge processes is a significant undertaking, requiring additional support/resources to incorporate into an organization's existing practices. Lessons learned from the study should be useful to both VHA and private-sector hospitals interested in implementing RED and undertaking a care transition intervention.

Background US healthcare organizations increasingly use physician satisfaction and attitudes as a key performance indicator. Further, many health care organizations also have an academically oriented mission. Physician involvement in research and teaching may lead to more positive workplace attitudes, with subsequent decreases in turnover and beneficial impact on patient care. This article aimed to understand the influence of time spent on academic activities and perceived quality of care in relation to job attitudes among internal medicine physicians in the Veterans Health Administration (VHA). Methods A cross-sectional survey was conducted with inpatient attending physicians from 36 Veterans Affairs Medical Centers. Participants were surveyed regarding demographics, practice settings, workplace staffing, perceived quality of care, and job attitudes. Job attitudes consisted of three measures: overall job satisfaction, intent to leave the organization, and burnout. Analysis used a two-level hierarchical model to account for the nesting of physicians within medical centers. The regression models included organizational-level characteristics: inpatient bed size, urban or rural location, hospital teaching affiliation, and performance-based compensation. Results A total of 373 physicians provided useable survey responses. The majority (72%) of respondents reported some level of teaching involvement. Almost half (46%) of the sample reported some level of research involvement. Degree of research involvement was a significant predictor of favorable ratings on physician job satisfaction and intent to leave. Teaching involvement did not have a significant impact on outcomes. Perceived quality of care was the strongest predictor of physician job satisfaction and intent to leave. Perceived levels of adequate physician staffing was a significant contributor to all three job attitude measures. Conclusions Expanding opportunities for physician involvement with research may lead to more positive work experiences, which could potentially reduce turnover and improve system performance. Electronic supplementary material The online version of this article (10.1186/s12913-018-3015-z) contains supplementary material, which is available to authorized users.

Italian and American hospitals, in two different periods, have been urged by external circumstances to extensively redesign their quality improvement strategies. This paper, through the use of a survey administered to chief quality officers in both countries, aims to identify commonalities and differences between the two systems and to understand which approaches are effective in improving quality of care. In both countries chief quality officers report quality improvement has become a strategic priority, clinical governance approaches, and tools—such as disease-specific quality improvement projects and clinical pathways—are commonly used, and there is widespread awareness that clinical decision making must be supported by protocols and guidelines. Furthermore, the study clearly outlines the critical importance of adopting a system-wide approach to quality improvement. To this extent Italy seems lagging behind compared to US in fact: (i) responsibilities for different dimensions of quality are spread across different organizational units; (ii) quality improvement strategies do not typically involve administrative staff; and (iii) quality performance measures are not disseminated widely within the organization but are reported primarily to top management. On the other hand, in Italy chief quality officers perceive that the typical hospital organizational structure, which is based on clinical directories, allows better coordination between clinical specialties than in the United States. In both countries, the results of the study show that it is not the single methodology/model that makes the difference but how the different quality improvement strategies and tools interact to each other and how they are coherently embedded with the overall organizational strategy.

Background In the USA, administrative data-based readmission rates such as the Centers for Medicare and Medicaid Services’ all-cause readmission measures are used for public reporting and hospital payment penalties. To improve this measure and identify better quality improvement targets, 3M developed the Potentially Preventable Readmissions (PPRs) measure. It matches clinically related index admission and readmission diagnoses that may indicate readmissions resulting from admission- or post-discharge-related quality problems. Objective To examine whether PPR software-flagged pneumonia readmissions are associated with poorer quality of care. Methods Using a retrospective observational study design and Veterans Health Administration (VA) data, we identified pneumonia discharges associated with 30-day readmissions, and then flagged cases as PPR–yes or PPR–no using the PPR software. To assess quality of care, we abstracted electronic medical records of 100 random readmissions using a tool containing explicit care processes organised into admission work-up, in-hospital evaluation/treatment, discharge readiness and post-discharge period. We derived quality scores, scaled to a maximum of 25 per section (maximum total score=100) and compared cases by total and section-specific mean scores using t tests and effect size (ES) to characterise the clinical significance of findings. Results Our abstraction sample was selected from 11 278 pneumonia readmissions (readmission rate=16.5%) during 1 October 2005–30 September 2010; 77% were flagged as PPR–yes. Contrary to expectations, total and section mean quality scores were slightly higher, although non-significantly, among PPR–yes (N=77) versus PPR–no (N=23) cases (respective total scores, 71.2±8.7 vs 65.8±11.5, p=0.14); differences demonstrated ES >0.30 overall and for admission work-up and post-discharge period sections. Conclusions Among VA pneumonia readmissions, PPR categorisation did not produce the expected quality of care findings. Either PPR–yes cases are not more preventable, or preventability assessment requires other data collection methods to capture poorly documented processes (eg, direct observation).

Survey response rate is regarded as a key data-quality indicator, yet response rate is not necessarily predictive of nonresponse bias. Our study objective was to use a high-response-rate survey to assess nonresponse bias across successive waves. This survey of healthcare leaders utilized a web-based, self-report format with an initial invitation and four nonrespondent follow-ups. Across five waves, comparisons were made for demographic and facility characteristics, proportion of items completed, and distribution of three question types: factual reports of customized categorical responses; single-item evaluations using five-point Likert scales; and multi-item scales, across four- or five-point Likert scales. The overall response rate was 95 percent (118/124); waves did not differ by demographic and facility characteristics or missing data. Across waves, there were no significant differences between responses to two factual report questions or the single- or multi-item scale measures of attitudes. According to a “what-if” analysis of cumulative results by wave, the same conclusions would have been reached if data collection had been halted at earlier points in time. Precision and statistical power increased as number of respondents accumulated by wave. The high response rate facilitated studying the impact of nonresponse bias by wave. Although high response rates are desirable because of precision and power, as survey fatigue increases, absolute thresholds representing “adequate” response rates may be less realistic. Results from “low” response-rate surveys should be considered on their merits, as they may accurately represent attitudes of the population. Therefore, low response rates should not be cited as reasons to dismiss results as uninformative.

Background Advanced practice providers (APPs), including nurse practitioners (NPs) and physician assistants (PAs) are cost-effective substitutes for physicians, with similar outcomes in primary care and surgery. However, little is understood about APP roles in inpatient medicine. Objective Describe APPs role in inpatient medicine. Design Observational cross-sectional cohort study. Setting One hundred twenty-four Veterans Health Administration (VHA) hospitals. Participants Chiefs of medicine (COMs) and nurse managers. Measurements Surveys included inpatient medicine scope of practice for APPs and perceived healthcare quality. We conducted bivariate unadjusted and multivariable adjusted analyses. Results One hundred eighteen COMs (95.2%) and 198 nurse managers (75.0%) completed surveys. Of 118 medicine services, 56 (47.5%) employed APPs; 27 (48.2%) used NPs only, 15 (26.8%) PAs only, and 14 (25.0%) used both. Full-time equivalents for NPs was 0.5 to 7 (mean = 2.22) and PAs was 1 to 9 (mean = 2.23). Daily caseload was similar at 4 to 10 patients (mean = 6.5 patients). There were few significant differences between tasks. The presence of APPs was not associated with patient or nurse manager satisfaction. Presence of NPs was associated with greater overall inpatient and discharge coordination ratings by COMs and nurse managers, respectively; the presence of PAs was associated with lower overall inpatient coordination ratings by nurse managers. Conclusions NPs and PAs work on half of VHA inpatient medicine services with broad, yet similar, scopes of practice. There were few differences between their roles and perceptions of care. Given their very different background, regulation, and reimbursement, this has implications for inpatient medicine services that plan to hire NPs or PAs.

Professional language interpreters are skilled in the nuances of interpretation and are less likely to make errors of clinical significance but clinicians infrequently use them. We examine system-level factors that may shape clinicians' perceptions and use of professional interpreters. Exploratory qualitative study in 12 California public hospitals. We conducted in-person key informant interviews with hospital leadership, clinical staff, and administrative staff. Five emergent themes highlight system-level factors that may influence clinicians' perceptions and use of professional interpreters in hospitals: (1) organization-wide commitment to improving language access for LEP patients; (2) organizational investment in remote interpreter technologies to increase language access; (3)training clinicians on how to access and work with interpreters; (4) hospital supports the training and certification of bilingual staff to serve as interpreters to expand in-person, on-site, interpreter capacity; and (5)organizational investment in readily accessible telephonic interpretation. Multiple system-level factors underlie clinicians' use of professional interpreters. Interventions that target these factors could improve language services for patients with limited English proficiency.

Objective: To assign responsibility for variations in small area hospitalization rates to specific hospitals and to evaluate the Roemer’s Law in a way that does not artificially induce correlation between bed supply and utilization. Data Sources/Study Setting: We used data on hospitalizations and outpatient treatment for 15 medical conditions of nonmanaged care Part B eligible Medicare enrollees of 65 years and older in Massachusetts in 2000. Study Design: We used a Bayesian model to estimate each hospital’s pool of potential patients and the fraction of the pool hospitalized (its propensity to hospitalize, PTH). To evaluate the Roemer’s Law, we calculated the correlation between hospitals’ PTH and beds per potential patient. Patient severity was measured using All Patient Refined Diagnosis Related Groups. Results: We show that our approach does not artificially induce a correlation between beds and utilization whereas the traditional approach does. Nevertheless, our approach indicates a strong relationship between PTH and beds (r=0.56). Eighteen (of 66) hospitals had a high PTH that differed significantly from 16 hospitals with a low PTH. Average patient severity in the high PTH hospitals was lower than in the low PTH hospitals. Although the difference was not statistically significant (P=0.12), there was a medium effect size (0.58). Discussion: Variation across hospitals in the PTH index, the strong relationship between beds and the PTH, and the lack of relationship between severity and the PTH suggest the importance of policies that limit bed growth of high PTH hospitals and create incentives for high PTH hospitals to reduce hospitalizations.

Background: A single composite measure calculated from individual quality indicators (QIs) is a useful measure of hospital performance and can be justified conceptually even when the indicators are not highly correlated with one another. Objective: To compare 2 basic approaches for calculating a composite measure: an extension of the most widely-used approach, which weights individual indicators based on the number of people eligible for the indicator (referred to as denominator-based weights, DBWs), and a Bayesian hierarchical latent variable model (BLVM). Methods: Using data for 15 QIs from 3275 hospitals in the Hospital Compare database, we calculated hospital ranks using several versions of DBWs and 2 BLVMs. Estimates in 1 BLVM were driven by differences in variances of the QIs (BLVM1) and estimates in the other by differences in the signal-to-noise ratios of the QIs (BLVM2). Results: There was a high correlation in ranks among all of the DBW approaches and between those approaches and BLVM1. However, a high correlation does not necessarily mean that the same hospitals were ranked in the top or bottom quality deciles. In general, large hospitals were ranked in higher quality deciles by all of the approaches, though the effect was most apparent using BLVM2. Conclusions: Both conceptually and practically, hospital-specific DBWs are a reasonable approach for calculating a composite measure. However, this approach fails to take into account differences in the reliability of estimates from hospitals of different sizes, a big advantage of the Bayesian models.

Five years after the Institute of Medicine (IOM) called for a redesigned U.S. health care system, relatively little was known about the extent to which hospitals had undertaken quality improvement (QI) efforts to address deficiencies in patient care. To examine the state of hospital QI activities in 2006, the authors designed and conducted a survey of short-term, general hospitals with 25 or more beds. In a sample of 470 hospitals, they found that many were actively engaged in improvement efforts but that these activities varied in method and impact. Hospitals with high levels of perceived quality, as reflected in assessments by their quality managers, were more likely to have embraced QI as a strategic priority, employed quality practices and processes consistent with IOM aims, fostered staff training and involvement in QI methods, engaged in an array of QI activities and clinical QI strategies, and maintained staffing levels favoring fewer patients per nurse.

Background The Institute of Medicine's 2001 report Crossing the Quality Chasm argued for fundamental redesign of the U.S. health care system. Six years later, many health care organizations have embraced the report's goals, but few have succeeded in making the substantial transformations needed to achieve those aims. Purposes This article offers a model for moving organizations from short-term, isolated performance improvements to sustained, reliable, organization-wide, and evidence-based improvements in patient care. Methodology Longitudinal comparative case studies were conducted in 12 health care systems using a mixed-methods evaluation design based on semistructured interviews and document review. Participating health care systems included seven systems funded through the Robert Wood Johnson Foundation's Pursuing Perfection Program and five systems with long-standing commitments to improvement and high-quality care. Findings Five interactive elements appear critical to successful transformation of patient care: (1) Impetus to transform; (2) Leadership commitment to quality; (3) Improvement initiatives that actively engage staff in meaningful problem solving; (4) Alignment to achieve consistency of organization goals with resource allocation and actions at all levels of the organization; and (5) Integration to bridge traditional intra-organizational boundaries among individual components. These elements drive change by affecting the components of the complex health care organization in which they operate: (1) Mission, vision, and strategies that set its direction and priorities; (2) Culture that reflects its informal values and norms; (3) Operational functions and processes that embody the work done in patient care; and (4) Infrastructure such as information technology and human resources that support the delivery of patient care. Transformation occurs over time with iterative changes being sustained and spread across the organization. Practice implications The conceptual model holds promise for guiding health care organizations in their efforts to pursue the Institute of Medicine aims of fundamental system redesign to achieve dramatically improved patient care.

Many studies have reported large variations in age- and sex-adjusted rates of hospitalizations across small geographic areas. These variations have often been attributed to differences in medical practice style which are not reflected in differences in health care outcomes. There is, however, another potentially important source of variation that has not been examined much in the literature: geographic differences in the age–sex adjusted size of the pool of patients who present with the disease and are candidates for hospitalization. Previous studies of small area variations in hospitalization rates have only used data on hospitalizations. Thus, it has not been possible to distinguish the extent to which differences in hospitalization rates are due to (i) differences in the chance that patients diagnosed with a disease are admitted to a hospital, which we refer to as the ‘practice style effect,’ versus (ii) geographic differences in the total amount of diagnosed disease, which we refer to as the ‘disease effect.’ Elementary methods for estimating the relative strength of the two effects directly from the data can be misleading, since equal amounts of variability in each effect result in unequal impacts on hospitalization rates. In this paper we describe a model-based approach for estimating the relative importance of the practice style effect and the disease effect in explaining variations in hospitalization rates. The key to our approach is the use of data on both inpatient and outpatient visits. We use 1997 Medicare data for two respiratory medical conditions across 71 small areas in Massachusetts: chronic bronchitis and emphysema, and bacterial pneumonia. Based on a Poisson model for the process generating hospitalizations and outpatient visits, we use a Bayesian framework and Gibbs sampling to compute and compare the correlation between the number of people hospitalized and each of these two sources of variation. Our results show that for the two conditions, disease rate variation explains at least as much of the variation in hospitalization rates as does practice style variation. Copyright © 2003 John Wiley & Sons, Ltd.

We acknowledge here and in our paper1 that the Potentially Preventable Readmissions (PPRs) and the Centers for Medicare and Medicaid Services (CMS) readmission measures are intended to be used for hospital-level comparisons of risk-adjusted rates. The premise behind both measures is that hospitals or providers with higher than expected rates have more readmissions associated with quality of care problems during the index admission and postdischarge periods.2 ,3 However, the PPRs purport to improve upon the CMS all-cause readmission measure by including readmissions that are more likely to be preventable. For both measures, in order to improve rates, a hospital or provider would have to drill down to the individual discharge or patient level to examine further if there were any quality-of-care issues. Since we wanted to know if the PPRs provided any additional benefit for this purpose beyond …

Background Despite numerous calls for hospitals to employ quality improvement (QI) interventions to improve emergency department (ED) performance, their impact has not been explored in multi-site investigations. Objective We investigated the association between use of QI interventions (patient flow strategies, ED electronic dashboards, and five-level triage systems) and hospital performance on receipt of percutaneous intervention (PCI) within 90 min for acute myocardial infarction patients, a publicly available quality measure. Methods This was an exploratory, cross-sectional analysis of secondary data from 292 hospitals. Data were drawn from the Quality Improvement Activities Survey, the American Hospital Association's Annual Survey, and Hospital Compare. Linear regression models were used to detect differences in PCI performance scores based on whether hospitals employed one or more QI interventions. Results Fifty-three percent of hospitals reported widespread use of patient flow strategies, 62% reported using a dashboard, and 74% reported using a five-level triage system. Time to PCI performance scores were 3.5 percentage points higher (i.e., better) for hospitals that used patient flow strategies and 6.2 percentage points higher for hospitals that used a five-level triage system. Scores were 10.4 percentage points higher at hospitals that employed two quality improvement interventions and 12.8 percentage points higher at hospitals that employed three. Conclusion Employing QI interventions was associated with better PCI scores. More research is needed to explore the direction of this relationship, but results suggest that hospitals should consider adopting patient flow strategies, electronic dashboards, and five-level triage systems to improve PCI scores.

The objective of this study was to assess the role of provider coordination on nurse manager and physician perceptions of care quality, while controlling for organizational factors. Findings indicated that nurse-nurse coordination was positively associated with nurse manager perceptions of care quality; neither physician-physician nor physician-nurse coordination was associated with physician perceptions. Organizational factors associated with positive perceptions of care quality included facility support of education for nurses and physicians, and the use of multidisciplinary rounding.

BACKGROUND As the care of hospitalized patients becomes more complex, intraprofessional coordination among nurses and among physicians, and interprofessional coordination between these groups are likely to play an increasingly important role in the provision of hospital care. PURPOSE The purpose of this study was to identify the independent effects of organizational factors on provider ratings of overall coordination in inpatient medicine (OCIM). METHODOLOGY/APPROACH This was an exploratory cross-sectional, descriptive study. Primary data were collected between June 2010 and September 2011 through surveys of inpatient medicine nurse managers, physicians, and chiefs of medicine at 36 Veterans Health Administration medical centers. Secondary data from the 2011 Veterans Health Administration national survey of nurses were also used. Individual-level data were aggregated and analyzed at the facility level. Multivariate linear regression models were used to assess the relationship between 55 organizational factors and provider ratings of OCIM. FINDINGS Organizational factors that were common across models and associated with better provider ratings of OCIM included provider perceptions that the goals of senior leadership are aligned with those of the inpatient service and that the facility is committed to the highest quality of patient care, having resources and staff that enable clinicians to do their jobs, and use of strategies that enhance interactions and communication among and between nurses and physicians. PRACTICE IMPLICATIONS To improve intraprofessional and interprofessional coordination and, consequently, patient care, facilities should consider making patient care quality a more important strategic organizational priority; ensuring that providers have the staffing, training, supplies, and other resources they need to do their jobs; and implementing strategies that improve interprofessional communication and working relationships, such as multidisciplinary rounding.

Objective: Illustrate Ward's clustering algorithm, an approach that creates small geographic areas based on similarity in the pattern of hospital use. Compare areas resulting from Ward's algorithm using all hospital discharges to 1) areas resulting from the plurality rule, the more widely used approach, and 2) areas resulting from Ward's algorithm using subsets of discharges.

To determine the extent of inappropriate hospital use, to investigate factors related to variations in appropriateness, and to identify reasons for inappropriateness, the Appropriateness Evaluation Protocol (AEP) was applied to 2067 patient days in two hospitals between March 1997 and 1998 in Ankara, Turkey. A substantial amount of inappropriate utilization was found in both hospitals (34.2%, 24.6%). Factors affecting the appropriateness of hospital utilization and reasons for inappropriateness were varied and presented by internal medicine, general surgery, and gynecology services. In general, results of the logistic regression analysis indicated that inappropriateness was significantly associated with admission number (first admission/readmission), admission route (emergent/non-emergent), and day of the week. The most common reason for inappropriateness was diagnostic procedures and/or treatments that could have been carried out on an ambulatory basis. This study demonstrates that the AEP can be used as a tool to improve the efficiency of the Turkish hospitals.

OBJECTIVE To assess the inter-rater reliability between nurses and the convergent validity of the Appropriateness Evaluation Protocol (AEP) in the Turkish context. METHODS Two nurses applied the original AEP concurrently to a random subsample of 335 patient-days in internal medicine, general surgery, and gynaecology departments at a university hospital and a government teaching hospital, as a part of a larger study. Inter-rater reliability was tested by calculating overall agreement and specific agreements between nurse reviewers' AEP assessments. Validity was tested by comparing the assessments of the nurses based on the AEP with the implicit judgements of five expert physicians on a random subsample of 818 patient-days. Sensitivity, specificity, positive and negative predictive values of the AEP were calculated. Reliability and validity were also evaluated by the K statistic. RESULTS In the reliability test, there was a high level of agreement between the two independent raters applying the AEP in the three departments studied: overall agreement = 90.7-97.6%; specific inappropriate agreement = 69.1-92.3%; specific appropriate agreement = 88.3-96.6%. In validity testing, the AEP had a sensitivity of 0.83-0.97, specificity of 0.62-0.80, and positive and negative predictive values of 0.84-0.88 and 0.73-0.95 respectively. Kappa coefficients in internal medicine and gynaecology indicated almost perfect agreement in reliability testing and moderate agreement in validity testing. In general surgery, the K coefficients showed substantial agreement in both tests. CONCLUSION These results indicate that the AEP is a reliable and valid instrument to assess appropriateness of patient-days in Turkey.

This paper examines the popular idea that competition among managed care plans will lead not only to lower prices, but also to improved quality. We explore the likelihood that competition based on quality will occur and that better quality care will result. First, we discuss key elements of competitive theory and then we attempt to apply them to markets for health care coverage and care. We identify the conditions necessary for competition to have the desired effects and assess the extent to which those conditions do or can exist. We conclude that in the USA, many consumers have no choice among plans and, therefore, cannot select one based on quality. Moreover, the evidence suggests that as long as price varies among health plans, consumers who do have a choice will tend to emphasize price, not quality, in making their selections. We conclude with suggestions to increase the likelihood that quality can improve as a result of competition.

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

Data on outcomes of medical care are becoming much more available in health care organizations and systems of care. This will create new opportunities for operations researchers to make contributions to health care policy and management. To provide some background to those new to the health care area, in this article we do the following: (1) provide a brief exposure to major administrative databases that are available and useful for analyzing outcomes data; (2) discuss the strengths and limitations of the diagnostic information contained in these databases; (3) describe several systems that use this information, or in some cases information from the medical record, to determine patient severity, thus providing a basis for severity-adjustment before considering outcomes; and (4) finally, provide an overview of some recent advances in obtaining improved parameter estimates from large databases.

This study tests whether the rate of inappropriate hospital admissions is high in areas with high medical admission rates. Seventy small geographic areas were formed by grouping Massachusetts ZIP codes by similarity of hospital use. Appropriateness of hospital admission was measured both by applying the Appropriateness Evaluation Protocol and by applying physicians' judgment to the medical records of patients age sixty-five and older who were admitted for treatment of a medical condition in 1990-1992. No relationship between hospital admission rate and inappropriate admission rate was found, which calls into question the common assumption that areas with higher hospital use have more inappropriate use of hospital care.

The purpose of this paper is to provide a description of utilization review (UR) methods that have been used in the United States and the direction UR is likely to take in the future. In contrast to the European studies reported in this issue, which consist primarily of empirical studies quantifying the magnitude of inappropriate hospital utilization, the focus of this paper is on the methods used to perform UR operationally. Particular attention will be paid to the predominant form of UR employed in the United States, concurrent review of the need for a hospital level of care, and on the criteria used to assess appropriateness of hospital admissions and days.

Electrical stimulation of upper limb nerves evokes a train of high-frequency wavelets (high-frequency oscillations, HFOs) on the human scalp. These HFOs are related to the influence of arousal-promoting structures on somatosensory input processing, and are generated in the primary somatosensory cortex (post-synaptic HFOs) and the terminal tracts of thalamocortical radiations (pre-synaptic HFOs). We previously reported that HFOs do not undergo habituation to repeated stimulations; here, we verified whether HFOs could be modulated by external sensitising stimuli. We recorded somatosensory evoked potentials (SSEPs) in 15 healthy volunteers before and after sensitisation training with an auditory stimulus. Pre-synaptic HFO amplitudes, reflecting somatosensory thalamic/thalamocortical activity, significantly increased after the sensitising acoustic stimulation, whereas both the low-frequency N20 SSEP component and post-synaptic HFOs were unaffected. Cross-talk between subcortical arousal-related structures is a probable mechanism for the pre-synaptic HFO effect observed in this study. We propose that part of the ascending somatosensory input encoded in HFOs is specifically able to convey sensitised inputs. This preferential involvement in sensitisation mechanisms suggests that HFOs play a critical role in the detection of potentially relevant stimuli, and act at very early stages of somatosensory input processing.

Background Recently, there has been considerable effort to promote the use of health information technology (HIT) in order to improve health care quality. However, relatively little is known about the extent to which HIT implementation is associated with hospital patient care quality. We undertook this study to determine the association of various HITs with: hospital quality improvement (QI) practices and strategies; adherence to process of care measures; risk-adjusted inpatient mortality; patient satisfaction; and assessment of patient care quality by hospital quality managers and front-line clinicians. Methods We conducted surveys of quality managers and front-line clinicians (physicians and nurses) in 470 short-term, general hospitals to obtain data on hospitals’ extent of HIT implementation, QI practices and strategies, assessments of quality performance, commitment to quality, and sufficiency of resources for QI. Of the 470 hospitals, 401 submitted complete data necessary for analysis. We also developed measures of hospital performance from several publicly data available sources: Hospital Compare adherence to process of care measures; Medicare Provider Analysis and Review (MEDPAR) file; and Hospital Consumer Assessment of Healthcare Providers and Systems HCAHPS® survey. We used Poisson regression analysis to examine the association between HIT implementation and QI practices and strategies, and general linear models to examine the relationship between HIT implementation and hospital performance measures. Results Controlling for potential confounders, we found that hospitals with high levels of HIT implementation engaged in a statistically significant greater number of QI practices and strategies, and had significantly better performance on mortality rates, patient satisfaction measures, and assessments of patient care quality by hospital quality managers; there was weaker evidence of higher assessments of patient care quality by front-line clinicians. Conclusions Hospital implementation of HIT was positively associated with activities intended to improve patient care quality and with higher performance on four of six performance measures.

Recently, there has been considerable effort to promote the use of health information technology (HIT) in order to improve health care quality. However, relatively little is known about the extent to which HIT implementation is associated with hospital patient care quality. We undertook this study to determine the association of various HITs with: hospital quality improvement (QI) practices and strategies; adherence to process of care measures; risk-adjusted inpatient mortality; patient satisfaction; and assessment of patient care quality by hospital quality managers and front-line clinicians.

This research investigates the degree that estimates of the magnitude of small area variations in hospitalization rates depend on both the estimation method and the number of years of data used. Hospital discharge abstracts for patients 65 and older from acute care hospitals in Massachusetts from 1982 to 1987 were analyzed. The SCV statistic, the approach used in many current small area variation studies, and empirical Bayes (EB), an approach that adjusts more fully for the effect of random variation, were compared. EB estimates based on 3 years of data were best able to predict future area-specific hospitalization rates. Compared to EB estimates using 3 years of data, the SCV statistic with 1 year of data overestimated the median amount of systematic variation by over 70% for the 68 conditions studied; with 3 years of data, the SCV overestimated the median by 55%. Regardless of method, the same conditions were identified as relatively more variable and the same geographic areas were found to have higher than expected hospitalization rates. The magnitude of differences in hospitalization rates depends on how the data are analyzed and how many years of data are used. Hospitalization rates across small geographic areas may vary substantially less than reported previously.

Sharing lessons from high-performing hospitals facilitates quality improvement. High-performing hospitals have usually been identified using a small number of performance measures. The objective was to analyze how well 1,006 hospitals performed across a broader range of measures. Five measures were developed from publicly available data: adherence to processes of care, 30-day readmission rates, in-hospital mortality, efficiency, and patient satisfaction. For a subset of hospitals, the authors included two survey-based assessments of patient care quality, one by chief quality officers and one by frontline clinicians. In general, there was little correlation among the publicly available measures ( r ≤ .10), though there was notable correlation between objective measures and survey-based measures ( r = .23). Hospitals that performed well on a composite measure calculated from the publicly available measures were often not in the top quintile on most individual measures. This highlights the challenge in identifying high-performing hospitals to learn organizational-level best practices.

Medical record review is increasing in importance as the need to identify and monitor utilization and quality of care problems grow. To conserve resources, reviews are usually performed on a subset of cases. If judgment is used to identify subgroups for review, this raises the following questions: How should subgroups be determined, particularly since the locus of problems can change over time? What standard of comparison should be used in interpreting rates of problems found in subgroups? How can population problem rates be estimated from observed subgroup rates? How can the bias be avoided that arises because reviewers know that selected cases are suspected of having problems? How can changes in problem rates over time be interpreted when evaluating intervention programs? Simple random sampling, an alternative to subgroup review, overcomes the problems implied by these questions but is inefficient. The Self-Adapting Focused Review System (SAFRS), introduced and described here, provides an adaptive approach to record selection that is based upon model-weighted probability sampling. It retains the desirable inferential properties of random sampling while allowing reviews to be concentrated on cases currently thought most likely to be problematic. Model development and evaluation are illustrated using hospital data to predict inappropriate admissions.

In our study, preparation of voluntary movement was used to physiologically activate the motor cortex areas and the effect of this activation on CO(2) laser-evoked potentials (LEPs) was explored. LEPs were recorded from 31 scalp electrodes in 10 healthy subjects after painful stimulation of the right C6-C7 skin dermatomes. LEP stimuli were delivered in the time interval between a visual warning stimulus followed after 1 s. by an imperative stimulus. The imperative stimulus triggered: (i) no task in the baseline condition (Pain); (ii) flexion-extension movements of the second finger of the right hand in the movement condition (Pain + Movement); (iii) cognitive task (mathematic computation) in the distraction condition (Pain + Cognition). The experimental conditions were also repeated during application of laser stimuli on the left C6-C7 skin dermatomes. Compared with the baseline condition (no task required), during preparation of right-hand voluntary movement there was a significant reduction in LEP amplitude and subjective pain rating after right- but not after left-hand stimulation, which suggests that the observed effect cannot be attributed to a nonspecific reduction in attention toward painful stimulus. During preparation of a cognitive task, LEP amplitude was reduced compared to baseline. Our results represent the first neurophysiological suggestion that physiological activation of the motor cortex, occurring during movement preparation, inhibits cortical pain processing by a centrifugal mechanism.

BACKGROUND, There have been few studies of the extent to which differences in the pool of patients being managed might account for geographic variations in treatment rates. OBJECTIVE. For two cardiac procedures, cardiac catheterization and revascularization, we evaluate the hypothesis that differences in "the percentage of patients for whom the procedure is appropriate" is a factor explaining variations in use rates among those hospitalized with coronary heart disease (CHD). RESEARCH DESIGN. Based on hospital utilization patterns in Massachusetts in 1990, we created 70 small geographic areas. Using 1992 Massachusetts Peer Review Organization data, areas were ranked from highest to lowest based on (empirical-Bayes-adjusted) hospitalization rates for each procedure. One thousand seven hundred four cases from 43 hospitals were sampled, roughly half each from high and low use areas. Half had a procedure and half were candidates for the same procedure but did not have it. For each procedure, medical records were reviewed to determine whether the procedure was (or, for those not having it, would have been) appropriate, based on criteria developed using a modified Delphi approach. RESULTS. Among those having either procedure, appropriateness rates were similar in high and low rate areas (P = 0.59 for catheterization and P = 0.30 for revascularization). However, among candidates for either procedure who did not have it, appropriateness for performing the procedure was greater in high-rate areas (41.4% vs. 32.1%, P = 0.05 for catheterization; 71.2% vs. 57.2%, P = 0.003, for revascularization). CONCLUSION. Among those hospitalized with CHD, appropriateness rates for two cardiac procedures are higher in areas with higher use rates.

To determine the extent of inappropriate hospital use, to investigate factors related to variations in appropriateness, and to identify reasons for inappropriateness, the Appropriateness Evaluation Protocol (AEP) was applied to 2,067 patient days in two hospitals between March 1997 and 1998 in Ankara, Turkey. A substantial amount of inappropriate utilization was found in both hospitals (34.2%, 24.6%). Factors affecting the appropriateness of hospital utilization and reasons for inappropriateness were varied and presented by internal medicine, general surgery, and gynecology services. In general, results of the logistic regression analysis indicated that inappropriateness was significantly associated with admission number (first admission/readmission), admission route (emergent/non-emergent), and day of the week. The most common reason for inappropriateness was diagnostic procedures and/or treatments that could have been carried out on an ambulatory basis. This study demonstrates that the AEP can be used as a tool to improve the efficiency of the Turkish hospitals.

Conflicting results have been reported about abnormalities of the N30 somatosensory evoked potential (SEP) in movement disorders. In these studies, the N30 amplitude was measured in the frontal scalp region. Our aim was to identify the scalp electrodes recording the genuine activity of the N30 generator. In 18 subjects, we recorded the scalp SEPs from 19 electrodes and found a negative potential around 30 ms reaching its maximal amplitude in the frontal region. However, neither simple visual inspection of the frontal traces nor topographic analysis could distinguish the N24 from the N30 component of the frontal negativity. Brain electrical source analysis of SEPs showed that a four dipolar source model could well explain the scalp SEP distribution. We calculated the scalp field distributions of the source activities as modeled from the scalp recordings and observed that the maximal field distribution reflecting the activity of the N30 source was in the central region, whereas that reflecting the N24 source activity was frontal. We conclude that the negative response recorded around 30 ms in the central traces represents "genuine" N30 source activity, whereas the frontal negativity, which is higher in amplitude, is a mixture of the activities of both the N30 and N24 sources.

To assess the perceived quality of care in a group of pregnant women attended in a public Hospital.All pregnant women seen at the Hospital Clinic of Barcelona in 1996. Two study groups were defined: group A, women seen at the outpatient clinic as a regular follow-up visit for pregnancy, and group B, women seen at the outpatient clinic for follow-up after delivery. A satisfaction questionnaire survey was used in a random sample of both groups of women.Total number of interviews performed was 174. Both groups, A and B were comparable. Scores recorded in both groups were significantly different (P0.01) for the clinical follow-up and privacy variables (regarded as better than expected). The difference in scores for the information supplied was also statistically significant (P0.01), but regarded as worst than expected.The analysis of satisfaction does not seem to follow a linear, straightforward explanation. The differences seen strongly suggest the need of patient's satisfaction surveys to be specific by dimension and tailored to patients' expectations.

This paper examines the popular idea that competition among managed care plans will lead not only to lower prices, but also to improved quality. We explore the likelihood that competition based on quality will occur and that better quality care will result. First, we discuss key elements of competitive theory and then we attempt to apply them to markets for health care coverage and care. We identify the conditions necessary for competition to have the desired effects and assess the extent to which those conditions do or can exist. We conclude that in the USA, many consumers have no choice among plans and, therefore, cannot select one based on quality. Moreover, the evidence suggests that as long as price varies among health plans, consumers who do have a choice will tend to emphasize price, not quality, in making their selections. We conclude with suggestions to increase the likelihood that quality can improve as a result of competition.