Ethan A. Halm

Is Volume Related to Outcome in Health Care? A Systematic Review and Methodologic Critique of the Literature

Measuring and understanding the association between volume and outcome in the delivery of health services has been the focus of much research since the 1980s (1, 2). Recently, purchasers and consumer groups have taken an interest in the wider public dissemination of data on hospital volume for specific surgical procedures and medical conditions (3-5). Because high volume has been associated with better health outcomes for a variety of procedures and conditions, these groups recommend that consumers or health plans use data on volume to choose high-quality hospitals and physicians. Because reliable, valid, and timely information about health outcomes is lacking, data on volume are even more attractive. The wisdom of this policy, however, depends critically on the strength, magnitude, and meaning of the association between volume and outcome in health care. During the past 20 years, a large body of research has focused on measuring and explaining the association between patient outcomes and the volume of health services provided by hospitals and physicians (1, 2, 6-11). Many [but not all] studies have documented that higher volume is associated with better outcomes. Two principal hypotheses have been advanced to explain these relationships: 1) Physicians (and hospitals) develop more effective skills if they treat more patients [practice makes perfect] or 2) physicians (and hospitals) achieving better outcomes receive more referrals and thus accrue larger volumes (selective referral) (2, 6, 9, 10). Past reviews of this subject have focused only on specific procedures or conditions (12-14) or on effects of hospital volume (12, 15), have included nonpopulation-based studies (14-16), or were done before many recent primary studies (12, 16). In addition, to our knowledge, no comprehensive review has systematically analyzed and described the methodologic rigor of this literature. This project was undertaken to address some of these limitations as part of a 2000 joint workshop of the U.S. Institute of Medicine and the National Cancer Policy Board (17). We set out to conduct a systematic review of the research evidence linking volume and outcome in health care, to summarize and describe the methodologic rigor of the existing literature, and to highlight the research and policy implications of these findings. Methods Study Identification and Selection We searched MEDLINE for English-language articles published between 1 January 1980 and 31 December 2000 that assessed the relationship between volume and outcome in health care. Our search algorithms combined the Medical Subject Headings (MeSH terms) and text words outcome, outcome assessment, outcome and process assessment, volume, utilization, frequency, statistics, and regionalization with names of clinical conditions and procedures (Appendix). Bibliographies were reviewed to identify other articles of interest, and experts were contacted about missed or unpublished studies. We also searched the Cochrane Collaboration database. For our systematic review, we selected English-language articles in which hospital or physician volume was an independent variable, health outcomes (for example, death, stroke, or clinical complications) were the dependent variable, samples were community- or population-based, and patients had primarily been treated since 1980. When multiple articles used the same data, we included the most recent or complete article. We excluded studies published before 1980 because clinical and surgical care and outcomes have changed considerably since then for nearly all of the topics we reviewed. We excluded studies from single institutions, voluntary registries, or other convenience samples because of concerns about reporting bias and generalizability. Our initial search also identified articles about volume and outcome in trauma, newborn intensive care, and organ transplantation. We did not include these topics in our review because these services have already been extensively regionalized or are otherwise highly regulated by government or other administrative bodies. Review Methods Two of the authors reviewed each article independently, using a standardized abstraction form to record study characteristics, methodologic attributes, and research results. Reviewers were not blinded to journal, authors, or findings. The degree of initial agreement between reviewers was very high ( = 0.82 to 1.0). Any discrepancies were resolved by discussion. A third reviewer was used in rare instances when the original two reviewers did not reach full agreement. We critically read each study with an eye toward assessing its methodologic rigor as well as describing its results. Our methodologic review focused on key design attributes that influence the validity and generalizability of systematic reviews and the studies on which they are based (18, 19). Some preexisting patient factors, such as disease severity and burden of comorbid illness, are clear determinants of outcome independent of volume. Because it is necessary to account for differences in such factors to make valid comparisons between high- and low-volume providers, we assessed the quality of risk-adjustment techniques (12, 14, 20). We considered four levels of risk adjustment (none, models based on administrative data alone, models that included some clinical data, and clinical models with good calibration [HosmerLemeshow test]) and discrimination (c-statistic 0.75) (20). In addition, we noted whether the investigators controlled for any specific processes of care (medical therapies, surgical techniques, or adjunctive procedures) that are known to result in better outcomes. Increasing evidence shows that high-volume providers may more consistently use proven effective therapies, such as aspirin or -blockers in myocardial infarction (21) or adjuvant therapy in breast cancer (22). We also noted whether the investigators had explicitly measured the appropriateness of patient selection for procedural conditions. Although there has been little investigation of this issue, one study of carotid endarterectomy found that high-volume surgeons had a higher proportion of operations for inappropriate indications compared with low-volume surgeons (23). We ascertained four other analytic attributes: the type of outcomes assessed, the number of hospitals and physicians in each study (an indicator of the potential for variation at the two provider levels of interest), the number of volume strata examined, and the unit of analysis (whether effects of hospital and physician volume were assessed). Finally, samples that included all patients undergoing a specific procedure were considered more generalizable to the overall population than studies restricted to patients with one type of insurance. Statistical Analysis Studies that found a statistically significant mortality advantage for high-volume providers (P < 0.05) were considered positive. For each study, we recorded the definition of high and low volume (cases per year) and the overall mortality rate of the sample. All summary death rates reflect in-hospital mortality unless otherwise specified. We calculated the absolute difference in mortality rate between the highest and lowest volume strata reported and expressed this as the number of excess deaths per 100 cases attributable to low volume. We report medians and ranges for high- and low-volume thresholds, mean mortality rates, and absolute differences in mortality rates. A few studies assessed volume as a continuous variable, making it impossible to calculate a mortality difference between high- and low-volume providers. We included data on whether these studies demonstrated statistically significant associations in our summary. We used chi-square tests to assess associations between positive findings and methodologic attributes. All analyses were done by using SAS software, version 6.12 (SAS Institute, Inc., Cary, North Carolina). Results Methodologic Characteristics of Included Studies Our systematic review identified 254 articles. Eighteen articles reported on more than one procedure or condition. Because we summarized the literature by topic, we evaluated each article that studied more than one procedure as more than one study. We reviewed a total of 272 studies, of which 135 (53%) met all inclusion criteria. These 135 studies covered 27 clinical topics. Studies were most commonly excluded because volume was not an independent variable (n = 43), the sample was not population based (n = 40), or the study data were obtained before 1980 (n = 29). Studies were also excluded if no primary health outcomes were assessed, if mixed outcomes were assessed (for example, death plus long length of stay), or if data were duplicative. We found the literature to be extremely heterogeneous, even for a given procedure, making formal meta-analysis impossible. The methodologic characteristics of the 135 studies we reviewed are described in Table 1. Overall, 124 studies were from the United States, 6 were from Canada, 3 were from Europe, and 2 were from the United Kingdom. Half of all the studies we identified were published since 1998, underscoring the growing interest in this topic. The vast majority of reports were based on state or national hospital-discharge databases and had sample sizes that exceeded 1000 and included 20 or more hospitals and 50 or more physicians. For 79% of studies, the primary outcome was death, usually inpatient death. Many studies, however, reported 30-day mortality rates, and several articles on cancer reported long-term survival. Twenty-one percent of studies measured more than just death. For example, all 12 studies of coronary angioplasty also reported rates of emergency coronary artery bypass surgery, and half of the investigations of carotid endarterectomy reported stroke or other neurologic outcomes. Ninety percent of studies analyzed at least three categories of volume, usually tertiles or quartiles, and a

An automated model to identify heart failure patients at risk for 30-day readmission or death using electronic medical record data.

Background:A real-time electronic predictive model that identifies hospitalized heart failure (HF) patients at high risk for readmission or death may be valuable to clinicians and hospitals who care for these patients. Methods:An automated predictive model for 30-day readmission and death was derived and validated from clinical and nonclinical risk factors present on admission in 1372 HF hospitalizations to a major urban hospital between January 2007 and August 2008. Data were extracted from an electronic medical record. The performance of the electronic model was compared with mortality and readmission models developed by the Center for Medicaid and Medicare Services (CMS models) and a HF mortality model derived from the Acute Decompensated Heart Failure Registry (ADHERE model). Results:The 30-day mortality and readmission rates were 3.1% and 24.1% respectively. The electronic model demonstrated good discrimination for 30 day mortality (C statistic 0.86) and readmission (C statistic 0.72) and performed as well, or better than, the ADHERE model and CMS models for both outcomes (C statistic ranges: 0.72–0.73 and 0.56–0.66 for mortality and readmissions respectively; P < 0.05 in all comparisons). Markers of social instability and lower socioeconomic status improved readmission prediction in the electronic model (C statistic 0.72 vs. 0.61, P < 0.05). Conclusions:Clinical and social factors available within hours of hospital presentation and extractable from an EMR predicted mortality and readmission at 30 days. Incorporating complex social factors increased the models accuracy, suggesting that such factors could enhance risk adjustment models designed to compare hospital readmission rates.

Impact of Social Factors on Risk of Readmission or Mortality in Pneumonia and Heart Failure: Systematic Review

ABSTRACTBACKGROUNDReadmission and mortality after hospitalization for community-acquired pneumonia (CAP) and heart failure (HF) are publically reported. This systematic review assessed the impact of social factors on risk of readmission or mortality after hospitalization for CAP and HF—variables outside a hospital’s control.METHODSWe searched OVID, PubMed and PSYCHINFO for studies from 1980 to 2012. Eligible articles examined the association between social factors and readmission or mortality in patients hospitalized with CAP or HF. We abstracted data on study characteristics, domains of social factors examined, and presence and magnitude of associations.RESULTSSeventy-two articles met inclusion criteria (20 CAP, 52 HF). Most CAP studies evaluated age, gender, and race and found older age and non-White race were associated with worse outcomes. The results for gender were mixed. Few studies assessed higher level social factors, but those examined were often, but inconsistently, significantly associated with readmissions after CAP, including lower education, low income, and unemployment, and with mortality after CAP, including low income. For HF, older age was associated with worse outcomes and results for gender were mixed. Non-Whites had more readmissions after HF but decreased mortality. Again, higher level social factors were less frequently studied, but those examined were often, but inconsistently, significantly associated with readmissions, including low socioeconomic status (Medicaid insurance, low income), living situation (home stability rural address), lack of social support, being unmarried and risk behaviors (smoking, cocaine use and medical/visit non-adherence). Similar findings were observed for factors associated with mortality after HF, along with psychiatric comorbidities, lack of home resources and greater distance to hospital.CONCLUSIONSA broad range of social factors affect the risk of post-discharge readmission and mortality in CAP and HF. Future research on adverse events after discharge should study social determinants of health.

Echocardiography for assessing cardiac risk in patients having noncardiac surgery

Cardiac complications developing after noncardiac surgery are often serious, sometimes fatal, and almost always costly. An estimated 9 million of the 28 million patients in the United States who have noncardiac surgery each year are thought to have a high risk for postoperative cardiac complications because they are known to have or are suspected of having ischemic heart disease [1, 2]. As a result of this risk, approximately 1.5 million persons have adverse cardiac events each year, at a cost of more than

Persistent depression affects adherence to secondary prevention behaviors after acute coronary syndromes.

20 billion annually [1]. Cardiac assessment before elective surgery relies on two strategies: assessment of risk factors and diagnostic testing. Assessing risk factors involves ascertaining clinical characteristics that are associated with such cardiac complications as previous myocardial infarction, congestive heart failure, dysrhythmias, vascular disease, hypertension, diabetes mellitus, advanced age, and renal dysfunction [3-5]. However, many authorities advocate the use of noninvasive diagnostic tests to more precisely identify patients who are at high risk for perioperative illness and death [6]. The value of dipyridamidole-thallium scintigraphy has been widely studied but remains controversial [7-11]. Similarly, the use of radionuclide assessment of left ventricular function has been correlated with postoperative cardiac events in some studies [12, 13] but not in others [11, 14, 15]. Because of these controversies and the high costs of these tests, other, less-expensive approaches are being investigated. One commonly used test, transthoracic echocardiography, is increasingly used before surgery to assess cardiac risk because it provides information on global and regional ventricular function [16, 17]. Echocardiography is readily available; costs less than dipyridamidole-thallium scintigraphy and radionuclide angiography; and involves no intravenous injections, isotope handling, or exposure to radiation. However, its prognostic value in assessing cardiac risk before surgery is not known. We examined the usefulness of transthoracic echocardiography by posing two questions: 1) Can information from an echocardiogram routinely obtained before noncardiac surgery identify patients at risk for adverse cardiac outcomes after surgery? and 2) Do the echocardiographic data add any incremental prognostic information to the information already available from the history, physical examination, electrocardiogram, and laboratory studies? To answer these questions, we studied a cohort of patients who were known to have or were suspected of having ischemic heart disease, were scheduled for elective noncardiac surgery, and had preoperative echocardiography as part of the Study of Perioperative Ischemia. Methods Patients The study sample was drawn from a prospective cohort of 474 male veterans who were scheduled to have elective noncardiac surgery that required general anesthesia at the San Francisco Veterans Affairs Medical Center as part of the study of Perioperative Ischemia [4]. These men had definite coronary artery disease or a high risk for developing this disease. Consecutive patients who met entry criteria were enrolled from January 1987 to September 1989. The Committee on Human Research approved the study protocol, and all patients gave informed consent. Patients were considered to have definite coronary artery disease if they had previously had myocardial infarction, had typical angina, or had atypical angina with evidence of inducible ischemia shown by exercise testing [18] or evidence of myocardial perfusion defects shown by scintigraphy [19]. Patients were classified as having a high risk for coronary artery disease if they had previously had or were scheduled to have vascular surgery or if they had two or more of the following cardiac risk factors (in addition to male sex): diabetes mellitus, hypertension, age of 65 years or greater, current smoking, or a serum cholesterol level of at least 6.2 mmol/L (240 mg/dL). We excluded patients with paced rhythms or complete left bundle-branch block. Echocardiography was successfully done before surgery in 368 patients (78%). Echocardiograms were unavailable for the other patients because of scheduling problems, technical failures, or inadequate examinations. Our cohort comprised the 339 patients (92%) whose echocardiograms could be interpreted. Data Collection and Measurement A study physician did a routine clinical evaluation and reviewed the medical record of each patient before surgery. Clinical variables of interest were information from the history, physical examination, electrocardiography, and laboratory studies. All cardiovascular medications were recorded. The Canadian Cardiovascular Society classification of angina [20], the New York Heart Association classification of heart failure [21], the Goldman cardiac risk index [3], the Detsky risk index [5], and the American Society of Anesthesiologists classification of anesthetic risk [22] were also determined for each patient. Surgery was classified as major vascular (108 patients), intra-abdominal (76 patients), intrathoracic (21 patients), and other (134 patients; this category consisted of orthopedic, neurosurgical, general, plastic, and head and neck procedures). Preoperative testing included routine laboratory studies and 12-lead electrocardiography. The 12-lead electrocardiogram was analyzed for evidence of previous myocardial infarction using the Minnesota Code criteria [23] and was analyzed for left ventricular hypertrophy using the Sokolow-Lyon [24] and Romhilt-Estes [25] criteria. Standard two-dimensional and M-mode echocardiography were done in each patient before surgery. Standard parasternal long- and short-axis views, apical two- and four-chamber views, and subxiphoid views were obtained. A General Electric Pass II machine (Milwaukee, Wisconsin) equipped with 2.5- and 3.5-MHz transducer probes was used. Videotapes of the echocardiograms were read by one of two research cardiologists who were blinded to the clinical history, research data, and outcome events. The variability with which echocardiograms are interpreted in our laboratory has been reported previously; the interobserver, intraobserver, and interexamination agreement rates all exceed 90% [26]. Echocardiographic variables of interest were left ventricular systolic ejection fraction, regional wall motion abnormalities, and the presence of left ventricular hypertrophy. Ejection fraction was assessed visually, and numeric estimates were assigned when the endocardial resolution of both short-axis and four-chamber views or four- and two-chamber views was adequate. Left ventricular wall motion was assessed using standard techniques [26]. We used a standard system to assign wall motion scores for the anterobasal, anterolateral, apical, posterobasal, and diaphragmatic walls. Each segment was graded as 1 (normal wall motion), 2 (mild hypokinesis), 3 (severe hypokinesis), 4 (akinesis), or 5 (dyskinesis). The total wall motion score was calculated as the sum of the regional wall motion scores (range, 5 to 25). Left ventricular hypertrophy, determined by measuring wall thickness in the parasternal views, was deemed to be present if either the septal or the posterior wall was at least 11 mm thick. Clinical Care and Outcomes Research data were collected by independent study physicians in conjunction with routine clinical care. Patients were interviewed and examined by a study physician before surgery and then daily from the day of surgery until hospital discharge. Physicians directly involved in patient care were blinded to the research data, including the echocardiographic information. A 12-lead electrocardiogram was obtained before surgery, each day for the first 7 days after surgery, on days 10 and 14 after surgery, at hospital discharge, and when clinically indicated. Serum cardiac enzyme levels were measured before surgery, on days 1 and 5 after surgery, and when clinically indicated by symptoms or electrocardiographic changes [4]. Clinicians had full independence in medical decision making. Perioperative cardiac outcomes were documented by study physicians and were validated by two independent investigators who were blinded to the clinical and echocardiographic data obtained before surgery. The following adverse cardiac outcomes were considered hierarchically, in descending order of severity: cardiac-related death, nonfatal myocardial infarction, unstable angina, congestive heart failure, and ventricular tachycardia. If a patient had several outcomes, we considered only the most severe event. Cardiac-related death, nonfatal myocardial infarction, and unstable angina were classified as ischemic events. Cardiac-related death was defined as death caused by myocardial infarction, dysrhythmia, or congestive heart failure. Diagnosis of myocardial infarction required an elevation of the creatine-kinase MB isoenzyme level ( 0.83 mol/L per second, equivalent to 50 U/L) and at least one of the following: development of new Q waves (as defined by Minnesota Code I.1 or I.2 [23]); development of persistent ST-T wave changes (as defined by Minnesota Code IV or V [23]); or evidence of acute infarction on necropsy. Unstable angina was defined as severe precordial chest pain that was not related to the surgical incision, lasted 30 minutes or longer, did not respond to standard therapies (rest and nitroglycerin), and was associated with transient ST-segment and T-wave changes without the development of Q waves or elevated enzyme levels. Diagnosis of congestive heart failure required 1) symptoms or signs of pulmonary edema [shortness of breath and rales]; 2) signs of new left or right ventricular failure [cardiomegaly, a third heart sound, jugular venous distention, and peripheral edema]; 3) abnormal results on chest radiography [vascular redistribution and interstitial or alveolar edema]; and 4) a change in medication that involved at least treatment with diureti

Asthma in the elderly: Current understanding and future research needs—a report of a National Institute on Aging (NIA) workshop

AbstractBACKGROUND: The persistence of depressive symptoms after hospitalization is a strong risk factor for mortality after acute coronary syndromes (ACS). Poor adherence to secondary prevention behaviors may be a mediator of the relationship between depression and increased mortality. OBJECTIVE: To determine whether rates of adherence to risk reducing behaviors were affected by depressive status during hospitalization and 3 months later. DESIGN: Prospective observational cohort study. SETTING: Three university hospitals. PARTICIPANTS: Five hundred and sixty patients were enrolled within 7 days after ACS. Of these, 492 (88%) patients completed 3-month follow-up. MEASUREMENTS: We used the Beck Depression Inventory (BDI) to assess depressive symptoms in the hospital and 3 months after discharge. We assessed adherence to 5 risk-reducing behaviors by patient self-report at 3 months. We used χ2 analysis to compare differences in adherence among 3 groups: persistently nondepressed (BDI<10 at hospitalization and 3 months); remittent depressed (BDI ≥10 at hospitalization; <10 at 3 months); and persistently depressed patients (BDI ≥10 at hospitalization and 3 months). RESULTS: Compared with persistently nondepressed, persistently depressed patients reported lower rates of adherence to quitting smoking (adjusted odds ratio [OR] 0.23, 95% confidence interval [95% CI] 0.05 to 0.97), taking medications (adjusted OR 0.50, 95% CI 0.27 to 0.95), exercising (adjusted OR 0.57, 95% CI 0.34 to 0.95), and attending cardiac rehabilitation (adjusted OR 0.5, 95% CI 0.27 to 0.91). There were no significant differences between remittent depressed and persistently nondepressed patients. CONCLUSIONS: Persistently depressed patients were less likely to adhere to behaviors that reduce the risk of recurrent ACS. Differences in adherence to these behaviors may explain in part why depression predicts mortality after ACS.

The effect of perioperative anemia on clinical and functional outcomes in patients with hip fracture.

Asthma in the elderly is underdiagnosed and undertreated, and there is a paucity of knowledge on the subject. The National Institute on Aging convened this workshop to identify what is known and what gaps in knowledge remain and suggest research directions needed to improve the understanding and care of asthma in the elderly. Asthma presenting at an advanced age often has similar clinical and physiologic consequences as seen with younger patients, but comorbid illnesses and the psychosocial effects of aging might affect the diagnosis, clinical presentation, and care of asthma in this population. At least 2 phenotypes exist among elderly patients with asthma; those with longstanding asthma have more severe airflow limitation and less complete reversibility than those with late-onset asthma. Many challenges exist in the recognition and treatment of asthma in the elderly. Furthermore, the pathophysiologic mechanisms of asthma in the elderly are likely to be different from those seen in young asthmatic patients, and these differences might influence the clinical course and outcomes of asthma in this population.

Using the common sense model to design interventions for the prevention and management of chronic illness threats: From description to process

Objectives: To describe the epidemiology of perioperative anemia in patients with hip fracture and assess the relationship between the hemoglobin measurements and clinical outcomes. Design: Prospective observational cohort study. Setting: Four university and community teaching hospitals. Patients: A consecutive cohort of 550 patients who underwent surgery for hip fracture and survived to discharge from August 1997 and August 1998 were evaluated and followed prospectively. Main Outcome Measures: Deaths, readmissions and Functional Independence Motor mobility scores within 60 days of discharge. Results: Anemia (defined as hemoglobin <12.0 g/dL) was present in 40.4% of patients on admission, 45.6% at the presurgery nadir, 93.0% at the postsurgery nadir, and 84.6% near discharge. The mean drop in hemoglobin after surgery was 2.8 ± 1.6 g/dL. In multivariate analyses, higher hemoglobin levels on admission were associated with shorter lengths of hospital stay and lower odds of death and readmission even after controlling for a broad range of prefracture patient characteristics, clinical status on discharge, and use of blood transfusion. Admission and preoperative anemia was not associated with risk-adjusted Functional Independence Motor mobility scores. In multivariable analyses, higher postoperative hemoglobin was associated with shorter length of stay and lower readmission rates, but did not effect rates of death or Functional Independence Motor mobility scores. Conclusions: Substantial declines in hemoglobin were common in patients with hip fracture. Higher preoperative hemoglobin was associated with shorter length of stay and lower odds of death and readmission within 60 days of discharge. Postoperative hemoglobin was also related to length of stay and readmission rates.

Hospital Readmissions After Hospital Discharge for Hip Fracture: Surgical and Nonsurgical Causes and Effect on Outcomes

In this article, we discuss how one might use the common sense model of self-regulation (CSM) for developing interventions for improving chronic illness management. We argue that features of that CSM such as its dynamic, self-regulative (feedback) control feature and its system structure provide an important basis for patient-centered interventions. We describe two separate, ongoing interventions with patients with diabetes and asthma to demonstrate the adaptability of the CSM. Finally, we discuss three additional factors that need to be addressed before planning and implementing interventions: (1) the use of top-down versus bottom-up intervention strategies; (2) health care interventions involving multidisciplinary teams; and (3) fidelity of implementation for tailored interventions.

Risk Factors for Perioperative Death and Stroke After Carotid Endarterectomy Results of the New York Carotid Artery Surgery Study

OBJECTIVES:  To examine the causes of hospital readmission after hip fracture and the relationships between hospital readmission and 6‐month physical function and mortality.