Incorporating health care quality into health antitrust law

<p>Abstract</p> <p>Background</p> <p>Antitrust authorities treat price as a proxy for hospital quality since health care quality is difficult to observe. As the ability to measure quality improved, more research became necessary to investigate the relationship between hospital market power and patient outcomes. This paper examines the impact of hospital competition on the quality of care as measured by the risk-adjusted mortality rates with the hospital as the unit of analysis. The study separately examines the effect of competition on non-profit hospitals.</p> <p>Methods</p> <p>We use California Office of Statewide Health Planning and Development (OSHPD) data from 1997 through 2002. Empirical model is a cross-sectional study of 373 hospitals. Regression analysis is used to estimate the relationship between Coronary Artery Bypass Graft (CABG) risk-adjusted mortality rates and hospital competition.</p> <p>Results</p> <p>Regression results show lower risk-adjusted mortality rates in the presence of a more competitive environment. This result holds for all alternative hospital market definitions. Non-profit hospitals do not have better patient outcomes than investor-owned hospitals. However, they tend to provide better quality in less competitive environments. CABG volume did not have a significant effect on patient outcomes.</p> <p>Conclusion</p> <p>Quality should be incorporated into the antitrust analysis. When mergers lead to higher prices and lower quality, thus lower social welfare, the antitrust challenge of hospital mergers is warranted. The impact of lower hospital competition on quality of care delivered by non-profit hospitals is ambiguous.</p

Hospital competition, resource allocation and quality of care

BACKGROUND: A variety of approaches have been used to contain escalating hospital costs. One approach is intensifying price competition. The increase in price based competition, which changes the incentives hospitals face, coupled with the fact that consumers can more easily evaluate the quality of hotel services compared with the quality of clinical care, may lead hospitals to allocate more resources into hotel rather than clinical services. METHODS: To test this hypothesis we studied hospitals in California in 1982 and 1989, comparing resource allocations prior to and following selective contracting, a period during which the focus of competition changed from quality to price. We estimated the relationship between clinical outcomes, measured as risk-adjusted-mortality rates, and resources. RESULTS: In 1989, higher competition was associated with lower clinical expenditures levels compared with 1982. The trend was stronger for non-profit hospitals. Lower clinical resource use was associated with worse risk adjusted mortality outcomes. CONCLUSIONS: This study raises concerns that cost reductions may be associated with increased mortality

Patients' experiences of the quality of long-term care among the elderly: comparing scores over time

Contains fulltext : 108999.pdf (publisher's version ) (Open Access)BACKGROUND: Every two years, long-term care organizations for the elderly are obliged to evaluate and publish the experiences of residents, representatives of psychogeriatric patients, and/or assisted-living clients with regard to quality of care. Our hypotheses are that publication of this quality information leads to improved performance, and that organizations with substandard performance will improve more than those whose performance is relatively good. METHODS: The analyses included organizational units that measured experiences twice between 2007 (t(0)) and 2009 (t(1)). Experiences with quality of care were measured with Consumer Quality Index (CQI) questionnaires. Besides descriptive analyses (i.e. mean, 5(th) and 95(th) percentile, and 90% central range) of the 19 CQI indicators and change scores of these indicators were calculated. Differences across five performance groups (ranging from 'worst' to 'best') were tested using an ANOVA test and effect sizes were measured with omega squared (omega(2)). RESULTS: At t0 experiences of residents, representatives, and assisted-living clients were positive on all indicators. Nevertheless, most CQI indicators had improved scores (up to 0.37 change score) at t(1). Only three indicators showed a minor decline (up to -0.08 change score). Change scores varied between indicators and questionnaires, e.g. they were more profound for the face-to-face interview questionnaire for residents in nursing homes than for the other two mail questionnaires (0.15 vs. 0.05 and 0.04, respectively), possibly due to more variation between nursing homes on the first measurement, perhaps indicating more potential for improvement. A negative relationship was found between prior performance and change, particularly with respect to the experiences of residents (omega(2) = 0.16) and assisted-living clients (omega(2) = 0.15). However, the relation between prior performance and improvement could also be demonstrated with respect to the experiences reported by representatives of psychogeriatric patients and by assisted-living clients. For representatives of psychogeriatric patients, the performance groups 1 and 2 ([much] below average) improved significantly more than the other three groups (omega(2) = 0.05). CONCLUSIONS: Both hypotheses were confirmed: almost all indicator scores improved over time and long-term care organizations for the elderly with substandard performance improved more than those with a performance which was already relatively good

Nursing home characteristics associated with methicillin-resistant Staphylococcus aureus (MRSA) Burden and Transmission

Background: MRSA prevalence in nursing homes often exceeds that in hospitals, but reasons for this are not well understood. We sought to measure MRSA burden in a large number of nursing homes and identify facility characteristics associated with high MRSA burden.Methods: We performed nasal swabs of residents from 26 nursing homes to measure MRSA importation and point prevalence, and estimate transmission. Using nursing home administrative data, we identified facility characteristics associated with MRSA point prevalence and estimated transmission risk in multivariate models.Results: We obtained 1,649 admission and 2,111 point prevalence swabs. Mean MRSA point prevalence was 24%, significantly higher than mean MRSA admission prevalence, 16%, (paired t-test, p<0.001), with a mean estimated MRSA transmission risk of 16%.In multivariate models, higher MRSA point prevalence was associated with higher admission prevalence (p=0.005) and higher proportions of residents with indwelling devices (p=0.01). Higher estimated MRSA transmission risk was associated with higher proportions of residents with diabetes (p=0.01) and lower levels of social engagement (p=0.03).Conclusions: MRSA importation was a strong predictor of MRSA prevalence, but MRSA burden and transmission were also associated with nursing homes caring for more residents with chronic illnesses or indwelling devices. Frequent social interaction among residents appeared to be protective of MRSA transmission, suggesting that residents healthy enough to engage in group activities do not incur substantial risks of MRSA from social contact. Identifying characteristics of nursing homes at risk for high MRSA burden and transmission may allow facilities to tailor infection control policies and interventions to mitigate MRSA spread. © 2012 Murphy et al.; licensee BioMed Central Ltd

The use of quality information by general practitioners: does it alter choices? A randomized clustered study

Background: Following the introduction of elements of managed competition in the Netherlands in 2006, General Practitioners (GPs) and patients were given the role to select treatment hospital using public quality information. In this study we investigate to what extent hospital preferences of GP's are affected by performance indicators on medical effectiveness and patient experiences. We selected three conditions: breast cancer, cataract surgery, and hip and knee replacement. Methods. After an inquiry 26 out of 226 GPs in the region signed up to participate in our study. After a 2:1 randomization, we analyzed the referral patterns in the region using three groups of GPs: GPs (n=17) who used the report cards and received personal clarification, GPs that signed up for the study but were assigned to the control group (n=9), and the GPs outside the study (n=200).We conducted a difference in differences analysis where the choice for a particular hospital was the dependent variable and time (2009 or 2010), the sum score of the CQI, the sum score of the PI's and dummy variables for the individual hospitals were used as independent variables. Results: The analysis of the conditions together and cataract surgery and hip and knee replacement separately, showed no significant relationships between the scores on the report cards and the referral patterns of the GPs. For breast cancer our analysis revealed that GPs in the intervention group refer 1.0% (p=0.01) more to hospitals that score one percent point better on the indicators for medical effectiveness. Conclusion: Our study provides empirical evidence that GP referral patterns were unaffected by the available quality information, except for the outcome indicators for breast cancer care that were presented. This finding was surprising since our study was designed to identify changes in hospital preference (1) amongst the most motivated GP's, (2) that received personal clarification of the performance indicators, and (3) selected indicators/conditions from a large set of indicators that they believed were most important. This finding may differ when quality information is based on outcome indicators with a clinically relevant difference, as shown by our indicators for breast cancer treatment. We believe that the current set of (largely process) hospital quality indicators do not serve the GP's information needs and consequently quality plays little role in the selection of hospitals for treatment. © 2013 Ikkersheim and Koolman; licensee BioMed Central Ltd

A Comparison of Administrative and Physiologic Predictive Models in Determining Risk Adjusted Mortality Rates in Critically Ill Patients

Hospitals are increasingly compared based on clinical outcomes adjusted for severity of illness. Multiple methods exist to adjust for differences between patients. The challenge for consumers of this information, both the public and healthcare providers, is interpreting differences in risk adjustment models particularly when models differ in their use of administrative and physiologic data. We set to examine how administrative and physiologic models compare to each when applied to critically ill patients.We prospectively abstracted variables for a physiologic and administrative model of mortality from two intensive care units in the United States. Predicted mortality was compared through the Pearsons Product coefficient and Bland-Altman analysis. A subgroup of patients admitted directly from the emergency department was analyzed to remove potential confounding changes in condition prior to ICU admission.We included 556 patients from two academic medical centers in this analysis. The administrative model and physiologic models predicted mortalities for the combined cohort were 15.3% (95% CI 13.7%, 16.8%) and 24.6% (95% CI 22.7%, 26.5%) (t-test p-value<0.001). The r(2) for these models was 0.297. The Bland-Atlman plot suggests that at low predicted mortality there was good agreement; however, as mortality increased the models diverged. Similar results were found when analyzing a subgroup of patients admitted directly from the emergency department. When comparing the two hospitals, there was a statistical difference when using the administrative model but not the physiologic model. Unexplained mortality, defined as those patients who died who had a predicted mortality less than 10%, was a rare event by either model.In conclusion, while it has been shown that administrative models provide estimates of mortality that are similar to physiologic models in non-critically ill patients with pneumonia, our results suggest this finding can not be applied globally to patients admitted to intensive care units. As patients and providers increasingly use publicly reported information in making health care decisions and referrals, it is critical that the provided information be understood. Our results suggest that severity of illness may influence the mortality index in administrative models. We suggest that when interpreting "report cards" or metrics, health care providers determine how the risk adjustment was made and compares to other risk adjustment models

Profiling quality of care for patients with chronic headache in three different German hospitals – a case study

BACKGROUND: Legal requirements for quality assurance in German rehabilitation hospitals include comparisons of providers. Objective is to describe and to compare outcome quality of care offered by three hospitals providing in-patient rehabilitative treatment exemplified for patients with chronic headache. METHODS: We performed a prospective three center observational study on patients suffering from chronic headache. Patients underwent interventions commonly used according to internal guidelines of the hospitals. Measurements were taken at three points in time (at admission, at discharge and 6 months after discharge). Indicators of outcome quality included pain intensity and frequency of pain, functional ability, depression, quality of life and health related behavior. Analyses of differences amongst the hospitals were adjusted by covariates due to case-mix situation. RESULTS: 306 patients from 3 hospitals were included in statistical analysis. Amongst the hospitals, patients differed significantly in age, education, diagnostic subgroups, beliefs, and with respect to some pain-related baseline values (covariates). Patients in all three hospitals benefited from intervention to a clinically relevant degree. At discharge from hospital, outcome quality differed significantly after adjustment according to case-mix only in terms of patients' global assessment of treatment results. Six months after discharge, the only detectable significant differences were for secondary outcomes like improved coping with stress or increased use of self-help. The profiles for satisfaction with the hospital stay showed clear differences amongst patients. CONCLUSION: The results of this case study do not suggest a definite overall ranking of the three hospitals that were compared, but outcome profiles offer a multilayer platform of reliable information which might facilitate decision making

Measuring and explaining mortality in Dutch hospitals; The Hospital Standardized Mortality Rate between 2003 and 2005

Background. Indicators of hospital quality, such as hospital standardized mortality ratios (HSMR), have been used increasingly to assess and improve hospital quality. Our aim has been to describe and explain variation in new HSMRs for the Netherlands. Methods. HSMRs were estimated using data from the complete population of discharged patients during 2003 to 2005. We used binary logistic regression to indirectly standardize for differences in case-mix. Out of a total of 101 hospitals 89 hospitals remained in our explanatory analysis. In this analysis we explored the association between HSMRs and determinants that can and cannot be influenced by hospitals. For this analysis we used a two-level hierarchical linear regression model to explain variation in yearly HSMRs. Results. The average HSMR decreased yearly with more than eight

The relationship between safety net activities and hospital financial performance

<p>Abstract</p> <p>Background</p> <p>During the 1990's hospitals in the U.S were faced with cost containment charges, which may have disproportionately impacted hospitals that serve poor patients. The purposes of this paper are to study the impact of safety net activities on total profit margins and operating expenditures, and to trace these relationships over the 1990s for all U.S urban hospitals, controlling for hospital and market characteristics.</p> <p>Methods</p> <p>The primary data source used for this analysis is the Annual Survey of Hospitals from the American Hospital Association and Medicare Hospital Cost Reports for years 1990-1999. Ordinary least square, hospital fixed effects, and two-stage least square analyses were performed for years 1990-1999. Logged total profit margin and operating expenditure were the dependent variables. The safety net activities are the socioeconomic status of the population in the hospital serving area, and Medicaid intensity. In some specifications, we also included uncompensated care burden.</p> <p>Results</p> <p>We found little evidence of negative effects of safety net activities on total margin. However, hospitals serving a low socioeconomic population had lower expenditure raising concerns for the quality of the services provided.</p> <p>Conclusions</p> <p>Despite potentially negative policy and market changes during the 1990s, safety net activities do not appear to have imperiled the survival of hospitals. There may, however, be concerns about the long-term quality of the services for hospitals serving low socioeconomic population.</p