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Biomedical subjects

L I Iezzoni

Publications and source records attributed to L I Iezzoni.

At least 19 recordsLinked to original sources
PubMed2000

Identification of in-hospital complications from claims data. Is it valid?

OBJECTIVES: This study examined the validity of the Complications Screening Program (CSP) by testing whether (1) ICD-9-CM codes used to identify a complication are coded completely and accurately and (2) the CSP algorithm successfully separates conditions present on admission from those occurring in the hospital. METHODS: We compared diagnosis and procedure codes contained in the Medicare claim with codes abstracted from an independent re-review of more than 1,200 medical records from Connecticut and California. RESULTS: Eighty-nine percent of the surgical cases and 84% of the medical cases had their CSP trigger codes corroborated by re-review of the medical record. For 13% of the surgical cases and 58% of the medical cases, the condition represented by the code was judged to be present on admission rather than occurring in-hospital. The positive predictive value of the claim was greater than 80% for the surgical risk pool, suggesting the value of the CSP as a screening tool. CONCLUSIONS: The CSP has validity as a screen for most surgical complications but only for 1 medical complication. The CSP does not have validity as a "stand-alone" tool to identify more than a few in-hospital surgery-related events. The addition of an indicator to the Medicare claim to capture the timing of secondary diagnoses would improve the validity of the CSP for identifying both surgical and medical in-hospital events.

Aged↗
PubMed2000

Use of administrative data to find substandard care: validation of the complications screening program.

OBJECTIVE: The use of administrative data to identify inpatient complications is technically feasible and inexpensive but unproven as a quality measure. Our objective was to validate whether a screening method that uses data from standard hospital discharge abstracts identifies complications of care and potential quality problems. DESIGN: This was a case-control study with structured implicit physician reviews. SETTING: Acute-care hospitals in California and Connecticut in 1994. PATIENTS: The study included 1,025 Medicare beneficiaries greater than 265 years of age. METHODS: Using administrative data, we stratified acute-care hospitals by observed-to-expected complication rates and randomly selected hospitals within each state. We randomly selected cases flagged with 1 of 17 surgical complications and 6 medical complications. We randomly selected controls from unflagged cases. MAIN OUTCOME MEASURE: Peer-review organization physicians' judgments about the presence of the flagged complication and potential quality-of-care problems. RESULTS: Physicians confirmed flagged complications in 68.4% of surgical and 27.2% of medical cases. They identified potential quality problems in 29.5% of flagged surgical and 15.7% of medical cases but in only 2.1% of surgical and medical controls. The rate of physician-identified potential quality problems among flagged cases exceeded 25% in 9 surgical screens and 1 medical screen. Reviewers noted several potentially mitigating circumstances that affected their judgments about quality, including factors related to the patients' illness, the complexity of the case, and technical difficulties that clinicians encountered. CONCLUSIONS: For some types of complications, screening administrative data may offer an efficient approach for identifying potentially problematic cases for physician review. Understanding the basis for physicians' judgments about quality requires more investigation.

Aged↗
PubMed2000

Does clinical evidence support ICD-9-CM diagnosis coding of complications?

BACKGROUND: Hospital discharge diagnoses, coded by use of the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM), increasingly determine reimbursement and support quality monitoring. Prior studies of coding validity have investigated whether coding guidelines were met, not whether the clinical condition was actually present. OBJECTIVE: To determine whether clinical evidence in medical records confirms selected ICD-9-CM discharge diagnoses coded by hospitals. RESEARCH DESIGN AND SUBJECTS: Retrospective record review of 485 randomly sampled 1994 hospitalizations of elderly Medicare beneficiaries in Califomia and Connecticut. MAIN OUTCOME MEASURE: Proportion of patients with specified ICD-9-CM codes representing potential complications who had clinical evidence confirming the coded condition. RESULTS: Clinical evidence supported most postoperative acute myocardial infarction diagnoses, but fewer than 60% of other diagnoses had confirmatory clinical evidence by explicit clinical criteria; 30% of medical and 19% of surgical patients lacked objective confirmatory evidence in the medical record. Across 11 surgical and 2 medical complications, objective clinical criteria or physicians' notes supported the coded diagnosis in >90% of patients for 2 complications, 80% to 90% of patients for 4 complications, 70% to <80% of patients for 5 complications, and <70% for 2 complications. For some complications (postoperative pneumonia, aspiration pneumonia, and hemorrhage or hematoma), a large fraction of patients had only a physician's note reporting the complication. CONCLUSIONS: Our findings raise questions about whether the clinical conditions represented by ICD-9-CM codes used by the Complications Screening Program were in fact always present. These findings highlight concerns about the clinical validity of using ICD-9-CM codes for quality monitoring.

Aged↗
PubMed2000

Mobility impairments and use of screening and preventive services.

OBJECTIVES: Primary care for people with disabilities often concentrates on underlying debilitating disorders to the exclusion of preventive health concerns. This study examined use of screening and preventive services among adults with mobility problems (difficulty walking, climbing stairs, or standing for extended periods). METHODS: The responses of non-institutionalized adults to the 1994 National Health Interview Survey, including the disability and Healthy People 2000 supplements, were analyzed. Multivariable logistic regressions predicted service use on the basis of mobility level, demographic characteristics, and indicators of health care access. RESULTS: Ten percent of the sample reported some mobility impairment; 3% experienced major problems. People with mobility problems were as likely as others to receive pneumonia and influenza immunizations but were less likely to receive other services. Adjusted odds ratios for women with major mobility difficulties were 0.6 (95% confidence interval [CI] = 0.4, 0.9) for the Papanicolaou test and 0.7 (95% CI = 0.5, 0.9) for mammography. CONCLUSIONS: More attention should be paid to screening and preventive services for people with mobility difficulties. Shortened appointment times, physically inaccessible care sites, and inadequate equipment could further compromise preventive care for this population.

Adult↗
PubMed1999

Explaining differences in English hospital death rates using routinely collected data.

OBJECTIVES: To ascertain hospital inpatient mortality in England and to determine which factors best explain variation in standardised hospital death ratios. DESIGN: Weighted linear regression analysis of routinely collected data over four years, with hospital standardised mortality ratios as the dependent variable. SETTING: England. SUBJECTS: Eight million discharges from NHS hospitals when the primary diagnosis was one of the diagnoses accounting for 80% of inpatient deaths. MAIN OUTCOME MEASURES: Hospital standardised mortality ratios and predictors of variations in these ratios. RESULTS: The four year crude death rates varied across hospitals from 3.4% to 13.6% (average for England 8.5%), and standardised hospital mortality ratios ranged from 53 to 137 (average for England 100). The percentage of cases that were emergency admissions (60% of total hospital admissions) was the best predictor of this variation in mortality, with the ratio of hospital doctors to beds and general practitioners to head of population the next best predictors. When analyses were restricted to emergency admissions (which covered 93% of all patient deaths analysed) number of doctors per bed was the best predictor. CONCLUSION: Analysis of hospital episode statistics reveals wide variation in standardised hospital mortality ratios in England. The percentage of total admissions classified as emergencies is the most powerful predictor of variation in mortality. The ratios of doctors to head of population served, both in hospital and in general practice, seem to be critical determinants of standardised hospital death rates; the higher these ratios, the lower the death rates in both cases.

Data Collection↗
PubMed1999

Does the Complications Screening Program flag cases with process of care problems? Using explicit criteria to judge processes.

BACKGROUND: The Complications Screening Program (CSP) aims to identify 28 potentially preventable complications of hospital care using computerized discharge abstracts, including demographic information, diagnosis and procedure codes. OBJECTIVE: To validate the CSP as a quality indicator by using explicit process of care criteria to determine whether hospital discharges flagged by the CSP experienced more process problems than unflagged discharges. METHODS: The (CSP was applied to computerized hospital discharge abstracts from Mledicare beneficiaries > 65 years old admitted in 1994 to hospitals in California and Connecticut for major surgery or medical treatment. ()f 28 CSP complications, 17 occurred sufficient frequently to study. Discharges flagged (cases) and unflagged (controls) by the (CSP were sampled and photocopied medical records were obtained. Physicians specified detailed, objective, explicit criteria, itemizing 'key steps' in processes of care that could potentially have prevented or caused complications. Trained nurses abstracted medical records using these explicit criteria. Process problem rates between cases and controls were compared. RESULTS: The final sample included 740 surgical and 416 medical discharges. Rates of process problems were high, ranging from 24.4 to 82.5% across CSP screens for surgical cases. Problems were lower for medical cases, ranging from 2.0 to 69.1% across CSP screens. Problem rates were 45.7% for surgical and 5.0% for medical controls. Rates of problems did not differ significantly across flagged and unflagged discharges. CONCLUSIONS: The CSP did not flag discharges with significantly higher rates of explicit process problems than unflagged discharges. Various initiatives throughout the USA use techniques similar to the CSP to identify complications of care. Based on these CSP findings, such approaches should be evaluated cautiously.

Aged↗
PubMed1999

Screening inpatient quality using post-discharge events.

BACKGROUND: Decreasing hospital lengths of stay (LOS) hamper efforts to detect and to definitively treat complications of care. Patients leave before some complications are identified. OBJECTIVES: To develop a computerized method to screen for hospital complications using readily available administrative data from outpatient and nonacute care within 90 days of discharge. DESIGN: We developed the Complications Screening Program for Outpatient data (CSP-O) by using diagnosis and procedure codes from Medicare Part A and B claims to define 50 complication screens. Seventeen apply to specific procedural cases, and 33 apply to all adult, acute, medical, or surgical hospitalizations. The CSP-O algorithm examined outpatient, physician office, home health agency, and hospice claims within 90 days following discharge. SUBJECTS: Seven hundred thirty nine thousand, two hundred and forty eight discharges of Medicare beneficiaries (age range, > or = 65 years) were admitted to 515 hospitals nationwide in 1994. RESULTS: Complete 90-day, post-discharge windows were present for 62.8% of all and 68.5% of procedural cases. The 33 general screens flagged 13.6% of all cases; only 1.8% of procedural cases were flagged by the 17 procedural screens. When we allowed the CSP-O algorithm to scan information from acute hospital readmissions, flag rates rose to 32.8% for general and 8.7% for procedural complications. Controlling for patient and hospital characteristics, flag rates were considerably higher among the very old and at small and for-profit institutions. CONCLUSIONS: Whereas several CSP-O findings have construct validity, limitations of claims raise concerns. Regardless of the CSPO's ultimate utility, examining post-discharge experiences to identify inpatient complications remains important as LOSs fall.

Aftercare↗
PubMed1998

Validation of relative value scale for congenital heart operations.

BACKGROUND: To determine the validity of the newly assigned work relative value unit (RVU) scale for surgical procedures for congenital heart disease, we measured its relationship to length of hospital stay, total hospital charges, and mortality. METHODS: We identified cases by the presence of ICD-9-CM codes in nine statewide, administrative hospital discharge abstract databases for 1992. Computer algorithms were generated to assign RVUs to individual cases. Spearman correlation coefficients between work and practice expense RVUs and median length of hospital stay, total hospital charges, and in-hospital mortality were determined, as well as parameter estimates from linear and logistic regression. RESULTS: Using data from 5,192 cases involving 34 surgical procedures for congenital heart disease, higher work RVUs were associated with longer lengths of hospital stay (rs = 0.72, p < 0.0001), higher total hospital charges (rs = 0.81, p < 0.0001), and higher in-hospital mortality (rs = 0.45, p = 0.01). A 5-point increase in the relative value scale was associated with an increase in the length of stay by a multiplicative factor of 1.3 (p < 0.0001); total hospital charges by 1.5 (p < 0.0001); and the odds of in-hospital death by 1.9 (p < 0.0001). Findings were similar for practice expense RVUs, as work and practice expense RVUs were highly correlated (rs = 0.93, p < 0.0001). CONCLUSIONS: The group of work RVUs for surgical procedures for congenital heart defects are reasonable relative measures, on average, of physician work for these procedures, thus supporting the use of this scale to determine physician reimbursement. Practice expense RVUs may not be an independent measure for these procedures.

Cardiac Surgical Procedures↗
PubMed1998

Predicting in-hospital deaths from coronary artery bypass graft surgery. Do different severity measures give different predictions?

OBJECTIVES: Severity-adjusted death rates for coronary artery bypass graft (CABG) surgery by provider are published throughout the country. Whether five severity measures rated severity differently for identical patients was examined in this study. METHODS: Two severity measures rate patients using clinical data taken from the first two hospital days (MedisGroups, physiology scores); three use diagnoses and other information coded on standard, computerized hospital discharge abstracts (Disease Staging, Patient Management Categories, all patient refined diagnosis related groups). The database contained 7,764 coronary artery bypass graft patients from 38 hospitals with 3.2% in-hospital deaths. Logistic regression was performed to predict deaths from age, age squared, sex, and severity scores, and c statistics from these regressions were used to indicate model discrimination. Odds ratios of death predicted by different severity measures were compared. RESULTS: Code-based measures had better c statistics than clinical measures: all patient refined diagnosis related groups, c = 0.83 (95% C.I. 0.81, 0.86) versus MedisGroups, c = 0.73 (95% C.I. 0.70, 0.76). Code-based measures predicted very different odds of dying than clinical measures for more than 30% of patients. Diagnosis codes indicting postoperative, life-threatening conditions may contribute to the superior predictive power of code-based measures. CONCLUSIONS: Clinical and code-based severity measures predicted different odds of dying for many coronary artery bypass graft patients. Although code-based measures had better statistical performance, this may reflect their reliance on diagnosis codes for life-threatening conditions occurring late in the hospitalization, possibly as complications of care. This compromises their utility for drawing inferences about quality of care based on severity-adjusted coronary artery bypass graft death rates.

Coronary Artery Bypass↗
PubMed1997

The risks of risk adjustment.

CONTEXT: Risk adjustment is essential before comparing patient outcomes across hospitals. Hospital report cards around the country use different risk adjustment methods. OBJECTIVES: To examine the history and current practices of risk adjusting hospital death rates and consider the implications for using risk-adjusted mortality comparisons to assess quality. DATA SOURCES AND STUDY SELECTION: This article examines severity measures used in states and regions to produce comparisons of risk-adjusted hospital death rates. Detailed results are presented from a study comparing current commercial severity measures using a single database. It included adults admitted for acute myocardial infarction (n=11880), coronary artery bypass graft surgery (n=7765), pneumonia (n=18016), and stroke (n=9407). Logistic regressions within each condition predicted in-hospital death using severity scores. Odds ratios for in-hospital death were compared across pairs of severity measures. For each hospital, z scores compared actual and expected death rates. RESULTS: The severity measure called Disease Staging had the highest c statistic (which measures how well a severity measure discriminates between patients who lived and those who died) for acute myocardial infarction, 0.86; the measure called All Patient Refined Diagnosis Related Groups had the highest for coronary artery bypass graft surgery, 0.83; and the measure, MedisGroups, had the highest for pneumonia, 0.85 and stroke, 0.87. Different severity measures predicted different probabilities of death for many patients. Severity measures frequently disagreed about which hospitals had particularly low or high z scores. Agreement in identifying low- and high-mortality hospitals between severity-adjusted and unadjusted death rates was often better than agreement between severity measures. CONCLUSIONS: Severity does not explain differences in death rates across hospitals. Different severity measures frequently produce different impressions about relative hospital performance. Severity-adjusted mortality rates alone are unlikely to isolate quality differences across hospitals.

Benchmarking↗
PubMed1997

Assessing quality using administrative data.

Administrative data result from administering health care delivery, enrolling members into health insurance plans, and reimbursing for services. The primary producers of administrative data are the federal government, state governments, and private health care insurers. Although the clinical content of administrative data includes only the demographic characteristics and diagnoses of patients and codes for procedures, these data are often used to evaluate the quality of health care. Administrative data are readily available, are inexpensive to acquire, are computer readable, and typically encompass large populations. They have identified startling practice variations across small geographic areas and-supported research about outcomes of care. Many hospital report cards (which compare patient mortality rates) and physician profiles (which compare resource consumption) are derived from administrative data. However, gaps in clinical information and the billing context compromise the ability to derive valid quality appraisals from administrative data. With some exceptions, administrative data allow limited insight into the quality of processes of care, errors of omission or commission, and the appropriateness of care. In addition, questions about the accuracy and completeness of administrative data abound. Current administrative data are probably most useful as screening tools that highlight areas in which quality should be investigated in greater depth. The growing availability of electronic clinical information will change the nature of administrative data in the future, enhancing opportunities for quality measurement.

Abstracting and Indexing↗
PubMed1997

Patient-physician communication at hospital discharge and patients' understanding of the postdischarge treatment plan.

BACKGROUND: The quality of discharge planning is an important determinant of patient outcomes following hospital discharge. Patients often report inadequate discussion prior to discharge regarding major elements of the postdischarge treatment plan, including medication and daily activities. OBJECTIVE: To determine whether this apparent lack of communication might be the result of differing perceptions on the part of patients and physicians regarding the patients' understanding of the treatment plan. METHODS: We surveyed 99 patients and their attending physicians. All patients had been discharged recently from an academic medical center with the diagnosis of acute myocardial infarction or pneumonia. We asked both patients and physicians about time spent prior to discharge discussing the postdischarge treatment plan and the patients' understanding of this plan. McNemar test was used to determine whether responses of patients and physicians differed. RESULTS: Physicians reported spending more time discussing postdischarge care than did patients (P = .10). Physicians believed that 89% of patients understood the potential side effects of their medications, but only 57% of patients reported that they understood (P < .001). Similarly, physicians believed that 95% of patients understood when to resume normal activities, while only 58% of patients reported that they understood (P < .001). CONCLUSIONS: Physicians overestimate patients' understanding of the postdischarge treatment plan. Steps should be taken to improve communication about postdischarge treatment.

Adult↗