Joseph D. Restuccia

The appropriateness evaluation protocol: a technique for assessing unnecessary days of hospital care.

A major national health policy objective is to improve the efficiency of hospital utilization. To evaluate programmatic interventions with this objective, such as the Professional Standards Review Organization program, measures of appropriate use are a fundamental need. This report represents the results of two developmental trials of a new technique, labeled the Appropriateness Evaluation Protocol (AEP), for assessing potentially unnecessary hospital days of care. Twenty-seven objective criteria items related to medical services, nursing/life support services and patient condition factors were incorporated in the protocol. If any one of the criteria was met, the day was deemed “appropriate,” and if none was met, the day was deemed “inappropriate” at an acute hospital level of care. A reviewer could override the objective criteria in either direction in reaching a final judgment. Three reviewers, two nurses and one physician each reviewed 200 charts at a teaching hospital. After correcting for a small number of abstracting errors, overall agreement rates between pairs of reviewers ranged from 92 to 94 per cent, levels significant p < 0.0001. Of all cases judged inappropriate by at least one of the reviewers, specific agreement rates for the reviewer pairs on which days were inappropriate ranged from 73 to 79 per cent. These overall agreement rates and specific agreement rates on days of care judged as inappropriate are higher than those of any previously reported assessment methods. A parallel study of the appropriateness of admissions in these same cases, using purely subjective reviewer judgments, found overall agreement rates averaging 90 per cent, but rates of specific agreement on in appropriate admissions were less than 40 per cent between pairs of reviewers. Along with comparisons to other, more subjective, assessment techniques, this finding suggests that objective criteria are a vital element in developing methodologically sound techniques for assessing appropriate hospital use.

Transformational change in health care systems: an organizational model.

Background: The Institute of Medicines 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 reports 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 Foundations 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.

The Effect of Concurrent Feedback in Reducing Inappropriate Hospital Utilization

This study, conducted in four general hospitals, evaluates the effectiveness of feedback from utilization review coordinators in reducing the number of inappropriate hospital days. Experimental control was exerted over the type of feedback provided in the utilization review process to produce four treatment groups (including a control group) that vary according to 1) the channel used to inform an attending physician of a probable inappropriately located patient and 2) the amount of discretion permitted the nurse coordinator in deciding whether, when and to whom this information is provided. The results of the study indicate that physician and hospital performance in utilization review, measured both by inappropriate patient days and length of stay, are affected by the feedback strategy employed. For patients inappropriately located for a portion of their hospital stay, provision of concurrent feedback resulted in reduction of approximately two thirds of an inappropriate day and two and one half total days, compared with patients for whom no feedback was provided or for whom physician advisor involvement was required. In addition, the effect of reasons causing patients to be inappropriately located (barriers) was assessed. Barriers outside the realm of influence of the hospital or the physician were found to impede the effectiveness of the utilization review systems.

A Survey of Hospital Quality Improvement Activities

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.

SMALL AREA VARIATIONS IN HOSPITALIZATION RATES : HOW MUCH YOU SEE DEPENDS ON HOW YOU LOOK

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.

Assessing the appropriateness of hospital utilization to improve efficiency and competitive position.

A hospital, induced by a certificate of need process and a newly competitive health care environment, made the transition from passive response to outside pressures to active utilization control.

Hospital Implementation of Health Information Technology and Quality of Care: Are They Related?

BackgroundRecently, 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.MethodsWe 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.ResultsControlling 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.ConclusionsHospital implementation of HIT was positively associated with activities intended to improve patient care quality and with higher performance on four of six performance measures.

Estimating a Composite Measure of Hospital Quality From the Hospital Compare Database Differences When Using a Bayesian Hierarchical Latent Variable Model Versus Denominator-Based Weights

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.

The utility of severity of illness information in assessing the quality of hospital care. The role of the clinical trajectory.

This research explored whether differentiating patients whose severity of illness worsened, improved, or remained the same over the hospital stay is a good screen for quality of care. The hypothesis was that substandard care is more likely to occur among patients who have worsened. Severity was measured using the Computerized Severity Index (CSI) and MedisGroups in 233 patients who had experienced acute myocardial infarction and 279 who had undergone coronary artery bypass graft who were admitted to four New England hospitals in 1987. Deaths and patients with discharge diagnoses indicating iatrogenic events and complications were oversampled. Potential quality problems were identified through explicit screening criteria applied by nurse researchers and implicit physician reviews. Acute myocardial infarction patients who worsened had higher rates of potential quality problems than other patients (CSI, P = 0.06; MedisGroups, P = 0.01). For the CSI, the 49.4% of patients who worsened captured 70.6% of the potentially substandard care; for MedisGroups, the 35.6% of patients who worsened also encompassed 70.6% of the problematic cases. For coronary artery bypass graft, results varied depending on how severity and quality were defined. The CSI performed better using implicit physician review to identify problematic care (P = 0.00), capturing 76.5% of substandard cases among the 41.6% of patients who worsened. In contrast, MedisGroups did better using explicit quality screens (P = 0.04), grouping 60.5% of the problematic cases among the 47.0% of patients who worsened. After removing in-hospital deaths from consideration, a worsening trajectory was generally associated with a higher fraction of potential quality problems among live discharges. This preliminary study suggests that examining changes in illness severity may be a useful screen for substandard hospital care, but its utility could vary by condition and by how quality problems are defined.

Total quality management in health care: a view of current and potential research.

Compared to its near-decade of influence in manufacturing and in several service sector industries, total quality management (TQM) has only recently been applied to health care. Since the early calls for action by Berwick and others beginning in 1988, and adoption of the quality management paradigm by the Joint Commission for Accreditation of Health Care Organizations (JCAHO), 58.5 percent of acute care hospitals &dquo;have a TQM/CQI program in place&dquo; (Grayson 1992, 25; Berwick 1988; Carroll 1991; Milakovich 1991; McLaughlin and Kaluzny 1990; Kaluzny, McLaughlin, and Kibbe 1992). Of those hospital chief executive officers who do not have a TQM program in their institution, 78.2 percent plan to start one within the next year (Grayson 1992). Only