Richard A. Culbertson

A comparison of hospital adverse events identified by three widely used detection methods

OBJECTIVE Determine the degree of congruence between several measures of adverse events. DESIGN Cross-sectional study to assess frequency and type of adverse events identified using a variety of methods. SETTING Mayo Clinic Rochester hospitals. PARTICIPANTS All inpatients discharged in 2005 (n = 60 599). INTERVENTIONS Adverse events were identified through multiple methods: (i) Agency for Healthcare Research and Quality-defined patient safety indicators (PSIs) using ICD-9 diagnosis codes from administrative discharge abstracts, (ii) provider-reported events, and (iii) Institute for Healthcare Improvement Global Trigger Tool with physician confirmation. PSIs were adjusted to exclude patient conditions present at admission. MAIN OUTCOME MEASURE Agreement of identification between methods. RESULTS About 4% (2401) of hospital discharges had an adverse event identified by at least one method. Around 38% (922) of identified events were provider-reported events. Nearly 43% of provider-reported adverse events were skin integrity events, 23% medication events, 21% falls, 1.8% equipment events and 37% miscellaneous events. Patients with adverse events identified by one method were not usually identified using another method. Only 97 (6.2%) of hospitalizations with a PSI also had a provider-reported event and only 10.5% of provider-reported events had a PSI. CONCLUSIONS Different detection methods identified different adverse events. Findings are consistent with studies that recommend combining approaches to measure patient safety for internal quality improvement. Potential reported adverse event inconsistencies, low association with documented harm and reporting differences across organizations, however, raise concerns about using these patient safety measures for public reporting and organizational performance comparison.

Organizational models for medical school-clinical enterprise relationships.

Changes in the organization, financing, and delivery of health care services have prompted medical school leaders to search for new organizational models for linking medical schools, faculty practice groups, affiliated hospitals, and insurers—models that better meet the contemporary challenges of governance and decision making in academic medicine. However, medical school leaders have relatively little information about the range of organizational models that could be adopted, the extent to which particular organizational models are actually used, the conditions under which different organizational models are appropriate, and the ramifications of different organizational models for the academic mission. In this article, the authors offer a typology of eight organizational models that medical school leaders might use to understand and manage their relationships with physicians, hospitals, and other components of clinical delivery systems needed to support and fulfill the academic mission. In addition to illustrating the models with specific examples from the field, the authors speculate about their prevalence, the conditions that favor one over another, and the benefits and drawbacks of each for medical schools. To conclude, they discuss how medical school and clinical enterprise leaders could use the organizational typology to help them develop strategy and manage relationships with each other and their other partners.

Impact of diagnosis-timing indicators on measures of safety, comorbidity, and case mix groupings from administrative data sources

Context:Many attempts to identify hospital complications rely on secondary diagnoses from billing data. To be meaningful, diagnosis codes must distinguish between diagnoses after admission and those existing before admission. Objective:To assess the influence of diagnoses at admission on patient safety, comorbidity, severity measures, and case mix groupings for Medicare reimbursement. Design:Cross-sectional association of various diagnosis-based clinical and performance measures with and without diagnosis present on admission. Setting:Hospital discharges from Mayo Clinic Rochester hospitals in 2005 (N = 60,599). Patients:All hospital inpatients including surgical, medical, pediatric, maternity, psychiatric, and rehabilitation patients. About 33% of patients traveled more than 120 miles for care. Main Outcome Measures:Hospital patient safety indicators, comorbidity, severity, and case mix measures with and without diagnoses present at admission. Results:Over 90% of all diagnoses were present at admission whereas 27.1% of all inpatients had a secondary diagnosis coded in-hospital. About one-third of discharges with a safety indicator were flagged because of a diagnosis already present at admission, more likely among referral patients. In contrast, 87% of postoperative hemorrhage, 22% of postoperative hip fractures, and 54% of foreign bodies left in wounds were coded as in-hospital conditions. Severity changes during hospitalization were observed in less than 8% of discharges. Slightly over 3% of discharges were assigned to higher weight diagnosis-related groups based on an in-hospital complication. Conclusions:In general, many patient safety indicators do not reliably identify adverse hospital events, especially when applied to academic referral centers. Except as noted, conditions recorded after admission have minimal impact on comorbidity and severity measures or on Medicare reimbursement.

Effect of illness severity and comorbidity on patient safety and adverse events.

The objective was to investigate the effect of admission health status on hospital adverse events and added costs. Secondary data were from merged administrative and clinical sources for Mayo Clinic Rochester, Minnesota hospital discharges in 2005 (N = 60 599). This was a retrospective cross-sectional study of the effect of demographics, diagnosis group, comorbidity, and admission illness severity on adverse events, incremental costs, and length of stay (LOS) using the Agency for Healthcare Research and Quality Patient Safety Indicators and provider-reported events with harm. Estimates are derived from generalized linear models. Admission severity increased the likelihood of all types of adverse events (7.2% per unit acute physiology score for any event); 7 specific comorbidities were associated with increased events and 2 with decreased events. High admission severity increased incremental costs and LOS. Selected comorbidities increased incremental LOS but had no significant effect on incremental costs. Adverse event reporting should incorporate comorbidity and admission severity. Reimbursement incentives to improve patient safety should consider adjustment for admission health status.

Health-related quality of life after total hip replacement: a Taiwan study.

This study applied the generalised estimating equations (GEE) in a large-scale prospective cohort study of predictors of health-related quality of life (HRQoL) in a Taiwan population. The study population included all patients who had undergone primary total hip replacement (THR) performed between March 1998 and December 2002 by either of two orthopaedic surgeons in two hospitals. The SF-36 was used in pre- and postoperative assessments of 335 patients. Young age, male gender, minimal comorbidity, use of epidural anaesthesia, lack of readmission within the previous 30 days, and higher preoperative functional status were positively associated with HRQoL (P < 0.05). Patients should be advised that their postoperative HRQoL may depend not only on their postoperative health care but also on their preoperative functional status. These analytical results should be applicable to other Taiwan hospitals and to other countries with similar social and cultural practices.RésuméCette étude a pour but d’estimer la qualité de vie (HRQoL) de la population Taiwanaise après PTH. Méthode: la population étudiée a inclus tous les patients ayant bénéficié d’une prothèse totale de hanche primaire (THR) réalisée entre mars 1998 et décembre 2002 par deux chirurgiens orthopédistes dans deux établissements hospitaliers différents. Le questionnaire SF-36 a été utilisé en pré et postopératoire sur 335 patients. Résultats: jeune âge, sexe masculin, comorbidités minimes, utilisation de l’anesthésie épidurale et absence de réhospitalisation dans les 30 jours sont corrélés de façon positive avec le score HRQoL (P < 0.05). Conclusion: les patients sont avertis que le score HRQoL postopératoire dépend non seulement de leur état de santé postopératoire mais également de leur statut fonctionnel préopératoire. Cette analyse peut être généralisée à d’autres établissements hospitaliers Taïwanais et à d’autres pays présentant des similitudes sur le plan social et culturel.

Androgen-deprivation therapy versus radical prostatectomy as monotherapy among clinically localized prostate cancer patients

Background The most recent randomized controlled trial in a predominantly prostate-specific antigen-detected prostate cancer (PC) population found a nonsignificant reduction in mortality from radical prostatectomy (RP) compared to conservative management. The optimal treatment for clinically localized prostate cancer is anything but clear. The PC-specific mortality and all-cause mortality were compared between primary androgen-deprivation treatment (PADT) and RP, both as monotherapy, among clinically localized PC patients. Methods A retrospective cohort study among PC patients in Surveillance, Epidemiology and End Results-Medicare data with a median follow up of 2.87 years in the PADT cohort and 2.95 years in the RP cohort. Propensity score-matching was employed to adjust for the observed selection bias. PC-specific mortality and all-cause mortality were modeled using the Fine and Gray competing risk model and Cox proportional hazards model, respectively. The independent variables in these models included age, race, Gleason score risk groups, T-score, prostate-specific antigen, Charlson comorbidity, and index year of treatment initiation. Results After propensity score-matching, there were 1624 in the PADT cohort and 1624 in the RP cohort. All baseline values were comparable (all P-values >0.35). There were a total of 266 deaths (16.38%) and 60 (3.69%) PC-specific deaths among PADT recipients, while there were 56 (3.45%) deaths and four (0.25%) PC-specific deaths among RP recipients. According to the Kaplan–Meier estimation, the 8-year survival rate was 43.39% in the PADT cohort and 79.62% in the RP cohort. PADT was associated with increased risk of overall mortality (hazard ratio = 2.98, 95% confidence interval 2.35–3.79; P < 0.001) and increased risk of PC-specific mortality (hazard ratio = 12.47, 95% confidence interval 4.48–34.70; P < 0.001). Conclusion With adjustment for the observed selection bias, PADT was associated with increased all-cause mortality and PC-specific mortality when compared to RP.

Board Quality Scorecards: Measuring Improvement

Board accountability for quality and patient safety is widely accepted but the science for how to measure it is immature, and differences between measuring performance, identifying hazards, and monitoring progress are often misunderstood. Hospital leaders often provide scorecards to assist boards with their oversight role yet, in the absence of national standards, little evidence exists regarding which measures are valid and useful to boards to assess quality improvement. The authors describe results of a cross-sectional board study, identifying the measures used to monitor quality. The measures varied widely and many were of uncertain validity, generally identifying hazards rather than measuring rates. This article identifies some important policy implications regarding boards’ oversight of quality and acknowledges existing limits to how we can measure quality and safety progress on the national or hospital level. If boards and their hospitals are to monitor progress in improving quality, they need more valid outcome measures.

Factors influencing inappropriate use of ED visits among type 2 diabetics in an evidence‐based management programme

OBJECT This study analyses inappropriate use of emergency department (ED) services among type 2 diabetics under an evidence-based management programme. METHODS Using 1999-2006 databases of Louisiana Health Care Services Division (HCSD) eight public hospitals ED visits among the uninsured and other patients in Louisiana, we termed urgent ED visits appropriate and less-urgent visits inappropriate. Eliminating weekend ED visits, 17,458 urgent and 22,395 less-urgent visits by 8596 patients were analysed, using generalized estimating equation methods. RESULTS Caucasians were 0.82 times (95% CI: 0.751-0.889) less likely to use the ED inappropriately compared with African Americans. Patients with commercial insurance, Medicaid and Medicare used the ED more inappropriately than uninsured, with odds ratios of 1.28, 1.32 and 1.28, respectively. Patients hospitalized the prior year were 0.84 times (95% CI: 1.08-1.31) less likely for inappropriate. Patients in larger hospitals used the ED more inappropriately, with an odds ratio of 1.44 (95% CI: 1.32-1.56). CONCLUSIONS The study suggests that inappropriate use of the ED among diabetic patients in an evidence-based management programme is more likely to occur among African American, patients with insurance coverage and those seeking care in larger hospitals. Reinforcing the regular use of clinic services for diabetes management, providing clinic access in off-hours, and engaging the health plans in providing incentives for more appropriate use of the ED might reduce inappropriate ED visits. Notably, uninsured patients with diabetes from HCSD were more efficient users of the ED.

Use of the emergency department for less-urgent care among type 2 diabetics under a disease management program.

BackgroundThis study analyzed the likelihood of less-urgent emergency department (ED) visits among type 2 diabetic patients receiving care under a diabetes disease management (DM) program offered by the Louisiana State University Health Care Services Division (LSU HCSD).MethodsAll ED and outpatient clinic visits made by 6,412 type 2 diabetic patients from 1999 to 2006 were extracted from the LSU HCSD Disease Management (DM) Evaluation Database. Patient ED visits were classified as either urgent or less-urgent, and the likelihood of a less-urgent ED visit was compared with outpatient clinic visits using the Generalized Estimating Equation methodology for binary response to time-dependent variables.ResultsPatients who adhered to regular clinic visit schedules dictated by the DM program were less likely to use the ED for less urgent care with odds ratio of 0.1585. Insured patients had 1.13 to 1.70 greater odds of a less-urgent ED visit than those who were uninsured. Patients with better-managed glycated hemoglobin (A1c or HbA1c) levels were 82 times less likely to use less-urgent ED visits. Furthermore, being older, Caucasian, or a longer participant in the DM program had a modestly lower likelihood of less-urgent ED visits. The patients Charlson Comorbidity Index (CCI), gender, prior hospitalization, and the admitting facility showed no effect.ConclusionPatients adhering to the DM visit guidelines were less likely to use the ED for less-urgent problems. Maintaining normal A1c levels for their diabetes also has the positive impact to reduce less-urgent ED usages. It suggests that successful DM programs may reduce inappropriate ED use. In contrast to expectations, uninsured patients were less likely to use the ED for less-urgent care. Patients in the DM program with Medicaid coverage were 1.3 times more likely to seek care in the ED for non-emergencies while commercially insured patients were nearly 1.7 times more likely to do so. Further research to understand inappropriate ED use among insured patients is needed. We suggest providing visit reminders, a call centre, or case managers to reduce the likelihood of less-urgent ED visit use among DM patients. By reducing the likelihood of unnecessary ED visits, successful DM programs can improve patient care.

Financial Implications of Increasing Medical School Class Size: Does Tuition Cover Cost?

INTRODUCTION In 2006, the Association of American Medical Colleges (AAMC) issued a recommendation that medical schools increase the supply of physicians by 30% to meet the patient needs of the new millennium. OBJECTIVE To provide financial analysis of the cost of increasing class size. METHODS To determine the financial consequences of increasing medical student enrollment and in the absence of nationally published cost data for medical schools, adjusted secondary revenue data was analyzed using AAMC and Liaison Committee on Medical Education (LCME) financial data from 2009. Linear regression analysis was used to determine average fixed costs and variable cost per student in USD. RESULTS In USD,