David H. Kuykendall

The Association between the Quality of Inpatient Care and Early Readmission

Early readmission has great appeal as an indicator of hospital quality; it is common and costly. Depending on the diagnosis, 5% to 29% of adults are readmitted within a month of a medical-surgical stay [1] and 25% of Medicare expenditures for inpatient care are for readmissions within 60 days [2]. Hospital utilization databases make early readmission easy to tabulate. Some early readmissions are probably preventable. These features explain why early readmission has been used to screen for quality of care by payers (such as Medicare) and by multihospital systems (such as the Department of Veterans Affairs), since the early 1980s. However, a process-outcome link between early readmission and the quality of care during the previous hospitalization has not been well established. Only 10 primary data studies [3-12] have examined the process of inpatient care directly and compared early readmission rates of patients whose hospital care was substandard with patients whose care was normative; results from these studies differ. For example, we [3, 4] previously found, as did Reed and colleagues [5], that patients who had changes in their medication regimen just before discharge were more likely to be readmitted within a month or less. However, in a casecontrol study of 292 patients from 50 Veterans Affairs hospitals, Ludke and colleagues [6] detected no differences in the adequacy of discharge planning or in medical stability at discharge between patients who were and were not readmitted within 14 days. A single-hospital retrospective cohort study by Hayward and colleagues [7] showed that quality-of-care ratings of the index stay did not differ between patients who were and those who were not readmitted within 28 days. Early readmission is widely used as a quality-of-care indicator, although associations between it and the antecedent care process are not well established. We sought to determine whether the quality of inpatient care was associated with unplanned readmission within 14 days. Methods Participants Patients enrolled in our casecontrol study were men discharged from a hospital stay for treatment of diabetes, chronic obstructive lung disease, or heart failure at a convenience sample of 12 participating Veterans Affairs hospitals in the southern United States between 1 October 1987 and 30 September 1989. Three hospitals were large, urban, referral centers affiliated with medical schools. Five hospitals were medium sized; all but 1 of these had a medical school affiliation. The remaining 4 hospitals were small and had no or limited affiliations. Cases were men with an unplanned readmission to any Veterans Affairs hospital within 14 days of discharge from an index stay. Controls were men who did not have an unplanned readmission to a Veterans Affairs hospital within 14 days. The index stay was defined as the first hospitalization occurring during the 24-month period. The sampling frame was created using the computerized hospital discharge database of the Veterans Affairs medical system, the Patient Treatment File, which contains records of all hospital stays throughout the 159-hospital Veterans Affairs medical system. Three diagnosis-specific samples were created, with no patient appearing twice. Table 1 shows how samples were derived and lists reasons for ineligibility. Men discharged from an index stay with diabetes, chronic obstructive lung disease, or heart failure listed as the primary diagnosis were considered potentially eligible (International Classification of Disease codes available on request from the authors). All patients readmitted for any reason to any Veterans Affairs hospital within 14 days of the index discharge were placed on the list of potential eligible participants. Three patients who were not readmitted were randomly selected for each readmitted patient, and this 3:1 match provided a balance between the costs of chart review and statistical efficiency and power. The result of this sampling strategy was that patients who were not readmitted were group-matched to readmitted patients using hospital, diagnosis, and fixed 6-month period of discharge. Table 1. Selection of Participants The lists of potentially eligible patients were sent to each hospital. Personnel in records departments retrieved the charts, and study personnel traveled to each hospital to review them. We were interested only in those patients whose reason for admission was an exacerbation of one of the three conditions [diabetes, heart failure, and chronic obstructive lung disease] that we were studying, not those in whom one of the conditions was a comorbid illness. This distinction cannot be made accurately from computerized hospital-discharge abstracts. Therefore, before a patient was enrolled, his chart was examined to see if he met the final two eligibility criteria: 1) an admission presentation with evidence of an exacerbation of the conditions in question and 2) a discharge summary indicating that the condition was the primary reason for admission. Review of the Process of Care The process of care during the index stay was reviewed using a set of explicit, unit-weighted (0 or 1) process-of-care criteria specific for each diagnosis. (Criteria sets and instructions for use are available from the authors.) The criteria development and scoring processes have been described previously [13]. The sets were developed by panels composed of expert physicians and covered all elements of essential technical care of the hospitalized patient. Items were divided into three categories: criteria for the admission workup (history, physical examination, and initial tests), criteria for evaluation and treatment during the stay, and criteria for readiness for discharge. Many of the criteria were formulated as if, then statements, and a given criterion could be applicable or not applicable. The number of applicable criteria is a proxy for need for care. An adherence score, expressed as the percentage of applicable criteria that were met, was computed for each of the three categories of criteria. Each segment of the hospital stay was scored individually because different segments might influence the probability of readmission in a different manner. The same physician and physician assistant served as chart reviewers for the entire study. Inter-rater reliability was assessed for each criterion using the statistic [14]. To account for the problem of a low score despite a high percentage of agreement, we categorized the criteria based on whether there was high or low percentage of agreement, and we eliminated criteria for which the reviewers had an observed percentage of agreement lower than that expected by chance and a score of less than 0.20 that persisted after training. The final diabetes criteria set included 47 admission-workup criteria, 42 evaluation and treatment criteria, and 11 readiness-for-discharge criteria. Respective numbers of criteria were 44, 19, and 10 for heart failure and 54, 21, and 9 for obstructive lung disease. The reviewers traveled as a team to each site. One served as the administrative reviewer, and the other served as the quality reviewer. After ascertaining that the patient met the enrollment criteria, the administrative reviewer extracted data on severity of illness at admission using the Acute Physiology, Age, and Chronic Health Evaluation II (APACHE II) scoring method [15]; on comorbidity count (a list of 11 conditions with standardized definitions); and, in readmitted patients, on whether the readmission was planned or unplanned. The chart was then given to the quality reviewer, who applied the process-of-care criteria. The quality reviewer was kept blinded to the readmission status of the patient. Blinding is important because if reviewers know that an adverse outcome has occurred, they may rate the antecedent process of care as substandard [16]. Data on race, marital status, and number of admissions in the previous 2 years were obtained from the Patient Treatment File. Readmission The occurrence of readmission was tabulated from the Patient Treatment File and was therefore 100% complete for readmissions to any of the 159 Veterans Affairs hospitals. Readmissions to non-Veterans Affairs hospitals were not present in the Patient Treatment File and therefore could not be tabulated. Statistical Analysis Analyses were done separately for each disease. Bivariate comparisons were made using the Student t-test for continuous variables and the chi-square test for categorical variables. Student t-tests were two-tailed, and statistical significance was determined by a P value of less than 0.05. Multiple logistic regression [17] was used to estimate the unique effect of adherence scores on the probability of readmission, after controlling for patient demographic, illness-severity, and need-for-care variables as indicated by the number of applicable criteria. Because the number of criteria in each category differed for each of the three diseases, the numbers of applicable items were converted to standard normal variables to make the scales comparable. Conditional logistic regression was done to account for the matching of hospital and time period inherent in the design. The results were the same as those achieved with unconditional logistic regression, which indicated that hospital and time period were not confounding variables and that it was desirable to dissolve the matching. Unconditional logistic regression has advantages in the assessment of model fit because some regression diagnostic statistics (for example, Hosmer-Lemeshow deciles of risk) are not available for conditional logistic analysis. We examined all models and confirmed that the continuous variables conformed to a linear gradient. We assessed model fit by the Hosmer-Lemeshow deciles of risk statistic, by the log-likelihood chi-square analysis, and by the c-index (which corresponds to the area under the receiver-operating characteristic curve). The data d

Arthroscopic Treatment of Osteoarthritis of the Knee: A Prospective, Randomized, Placebo-Controlled Trial Results of a Pilot Study

The reasons why many patients seemingly benefit from arthroscopic treatment of osteoarthritis of the knee remain obscure. The purpose of this pilot study was to determine if a placebo effect might play a role in arthroscopic treatment of this condition. After giving full informed consent, including full knowledge of the pos sibility and nature of a placebo surgery, five subjects were randomized to a placebo arthroscopy group, three subjects were randomized to an arthroscopic lavage group, and two subjects were randomized to a standard arthroscopic debridement group. The physi cians performing the postoperative assessment and the patients remained blinded as to treatment. Patients who received the placebo surgery reported decreased frequency, intensity, and duration of knee pain. They also thought that the procedure was worthwhile and would recommend it to family and friends. Thus, there may be a significant placebo effect for arthroscopic treatment of osteoarthritis of the knee. The small num bers in this preliminary study preclude a valid statistical analysis, and no conclusions can be drawn regarding the superiority of one treatment over another. A larger study is needed to evaluate fully the efficacy of an arthroscopic procedure for this condition and to decide if it is reasonable to expend health care resources for

International Classification of Diseases, 9th Revision, Clinical Modification codes in discharge abstracts are poor measures of complication occurrence in medical inpatients.

OBJECTIVES The authors tested the ability of International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes in discharge abstracts to identify medical inpatients who experienced an in-hospital complication, using complications identified through chart review as the gold standard. METHODS Two sets of ICD-9-CM codes were used: an inclusive set including many medical diagnoses that may also be coexistent complicating conditions on admission rather than complications and an exclusive set consisting primarily of ICD-9-CM-specified complication and adverse drug event codes. RESULTS Neither set performed well as a diagnostic test for complication occurrence according to receiver operating characteristic analysis (ROC areas were 0.61 for the inclusive set and 0.55 for the exclusive set). Sensitivities of the ICD-9-CM codes for complications were 0.34 for the inclusive set and 0.14 for the exclusive set. Corresponding positive predictive values were 0.32 and 0.37, respectively. Sensitivities of code definitions for individual complications were generally poor, less than 0.5 in most cases. CONCLUSIONS The authors conclude that ICD-9-CM codes in discharge abstracts are poor measures of complication occurrence.

Using administrative databases to evaluate the quality of medical care: A conceptual framework

Health care is consuming an ever larger share of national resources in the United States. Measures to contain costs and evidence of unexplained variation in patient outcomes have led to concern about inadequacy in the quality of health care. As a measure of quality, the evaluation of hospitals through analysis of their discharge databases has been suggested because of the scope and economy offered by this methodology. However, the value of the information obtained through these analyses has been questioned because of the inadequacy of the clinical data contained in administrative databases and the resultant inability to control accurately for patient variation. We suggest, however, that the major shortcoming of prior attempts to use large databases to perform across-facility evaluation has resulted from the lack of a conceptual framework to guide the analysis. We propose a framework which identifies component areas and clarifies the underlying assumptions of the analytic process. For each area, criteria are identified which will maximize the validity of the results. Hospitals identified as having unexpectedly high unfavorable outcomes when our framework is applied will be those where poor quality will most likely be found by primary review of the process of care.(ABSTRACT TRUNCATED AT 250 WORDS)

Dyspepsia: How Should We Measure It?

This study developed and validated a multidimensional measure of dyspepsia. A questionnaire was administered to 126 patients with dyspepsia who presented for care at a VA outpatient clinic and a family physicians private office. Dyspepsia-specific health was measured by self-report using: (1) an existing dyspepsia scale that produces an aggregate score by summing ratings across pain and non-pain symptoms; (2) adaptations of two scales originally designed to measure back pain; and (3) a new scale measuring satisfaction with dyspepsia-related health. Generic health was measured using the SF-36. Results from factor analysis revealed four dimensions of dyspepsia-related health: pain intensity, pain disability, non-pain symptoms, and satisfaction with dyspepsia-related health. After refinements, scales representing the four dimensions conformed to psychometric standards for reliability, and convergent and discriminant validity. The importance of measuring dyspepsia using a multidimensional approach was confirmed by demonstrating that classification of dyspepsia severity depended on the dimension that was assessed. We conclude that dyspepsia is best measured using a multidimensional approach.

EXPECTED SOURCE OF PAYMENT AND USE OF HOSPITAL SERVICES FOR CORONARY ATHEROSCLEROSIS

To study associations between payer and provision of services for patients hospitalized for coronary atherosclerosis, the authors analyzed abstracts of 24,424 discharges from California acute care hospitals during 1989. Services examined included receipt of coronary artery bypass surgery, percutaneous transluminal coronary angioplasty (PTCA), long length of stay (LOS) without revascularization, and overall LOS. Regression techniques controlled demographic factors and comorbidities. The privately insured were 96% more likely to undergo revascularization (either bypass or PTCA) than Medicaid discharges and 117% more likely than the uninsured. Odds of revascularization for Medicare and health maintenance organization discharges resembled those for the privately insured. Analyzed separately, PTCA was far more likely among the privately insured than Medicaid beneficiaries and the uninsured. In addition, the adjusted odds for PTCA were 52% greater for the privately insured than for health maintenance organization discharges. The greatest likelihood of long LOS without revascularization and the greatest overall LOS was observed for Medicaid discharges. Strong associations, consistent with financial incentives to provide care, exist between payer and provision of services. Future studies need to address whether variations in process result from differences in thresholds for procedure performance, differences in admission practices, or both.

SELECTING DISEASE-OUTCOME PAIRS FOR MONITORING THE QUALITY OF HOSPITAL CARE

Health care payors and providers are increasingly monitoring hospital discharge data bases for adverse events as markers for quality of care. The principal criticisms of these analyses have focused on the impediments to risk adjustment posed by the incompleteness and inaccuracy of the data bases. However, efforts to address the inadequacies of the data bases will not correct deficiencies of the analytic process. These deficiencies arise from the application of one adverse outcome to all disease states. Instead, analysis should be restricted to comparisons of subgroups of patients in which a close fit exists between the quality of care for the disease state and the expected outcome. Furthermore, these disease-outcome pairs should be minimally subject to measurement error. The authors present a conceptual framework for developing such meaningful disease-outcome pairs, and using the hospital discharge data base of the Department of Veterans Affairs, show how the framework can be used to devise a monitoring strategy for re-admission.

In-hospital complications among survivors of admission for congestive heart failure, chronic obstructive pulmonary disease, or diabetes mellitus

OBJECTIVE: To determine the frequency of hospital complications among survivors of inpatient treatment for congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD), or diabetes mellitus (DM).DESIGN: Retrospective cohort study.SETTING: Nine Veterans Affairs hospitals in the southern United States.PATIENTS: 1,837 men veterans discharged alive following hospitalization for CHF, COPD, or DM between January 1987 and December 1989. This patient population represents a subset of cases gathered to study the process of care in the hospital and subsequent early readmission; thus, veterans who died in the hospital were not included.MEASUREMENTS: Medical record review to record the occurrence of any of 30 in-hospital complications such as cardiac arrest, nosocomial infections, or delirium (overall agreement between two reviewers=84%, kappa=0.37).RESISTS: Complications occurred in 15.7% of the CHF cases, 13.1% of the COPD cases, and 14.8% of the DM cases. Hypoglycemic reactions were the most frequent individual adverse events in the CHF and DM cases (3.6% and 11.4% of the cases, respectively), and theophylline toxicity was most frequent among the COPD cases (4.9%). Patient age, the presence of comorbid diseases, and the Acute Physiology Score (APS) of APACHE II were associated with complication occurrence. For each disease, the patients who had a complication had significantly longer mean hospital stays than did the patients who did not have complications (14.6 to 14.9 days vs 7.2 to 8.2 days, p<0.01).CONCLUSIONS: Complications are frequent among patients discharged alive with CHF, COPD, or DM. The patients who experienced complications were more ill on admission and had longer hospital stays.

The association of quality of care and occurrence of in-hospital, treatment-related complications.

BACKGROUND Little data exist supporting the association of quality of care and nonfatal adverse outcomes in hospitalized patients, yet those outcomes are routinely scrutinized in quality assessment efforts. OBJECTIVE To determine whether measurable differences in quality of care are associated with the occurrence of non-fatal, in-hospital, and treatment-related complications. DESIGN Retrospective cohort study. SUBJECTS A total of 2,268 patients who were discharged alive from 9 Southwestern Veterans Affairs Medical Centers with congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) or diabetes mellitus. MEASURES Retrospective chart review was performed to collect information on patient severity of illness, in-hospital complication occurrence, and process quality of care. Process quality was assessed as the adherence scores for admission work-up and for treatment during the hospital stay. Process quality represents the proportion of applicable admission or treatment criteria that were met by that patients care providers. Once severity of illness was taken into account Cox proportional hazards regression was used to assess the independent contribution of process quality of care to complication occurrence. RESULTS Higher admission work-up adherence scores for COPD patients and higher treatment adherence scores for COPD and diabetes patients were associated with a lower risk of complication occurrence. The adjusted risk ratios of complications for higher versus lower adherence scores (with 95% CI) were 0.64 (0.43, 0.97) and 0.52 (0.33, 0.80) for admission and treatment, respectively, in COPD patients, and 0.51 (0.31, 0.83) for treatment in diabetics. No significant association was found in CHF patients. CONCLUSION Better admission work-up and treatment quality in COPD patients, as well as treatment quality in diabetic patients, are associated with lower risk of nonfatal treatment-related complications in the study population.

The Impact of Status Asthmaticus Practice Guidelines on Patient Outcome and Physician Behavior

This study assesses the effects of a status asthmaticus guideline on patient outcome and pediatrician behavior in a staff model health maintenance organization (HMO). The guidelines were drafted by an asthma specialist in the HMO and then discussed with key clinical personnel. A preprinted protocol order form was developed to help implement the guideline into clinical practice. The medical records of pediatric patients admitted to the hospital with status asthmaticus before (N = 67) and after (N = 59) guideline development and implementation were reviewed. This study demonstrates that locally developed, treatment-specific guidelines based on scientific evidence and combined with a staff consensus process and a user-friendly protocol form can influence physician behavior and patient outcome positively.