State-sponsored public reporting of hospital quality: results are hard to find and lack uniformity

Applicability of Publicly Reported Hospital Readmission Measures to Unreported Conditions and Other Patient Populations: A Cross-sectional All-Payer Study

BACKGROUND

Readmission rates after hospitalizations for heart failure (HF), acute myocardial infarction (AMI), and pneumonia among Medicare beneficiaries are used to assess quality and determine reimbursement. Whether these measures reflect readmission rates for other conditions or insurance groups is unknown.

OBJECTIVE

To investigate whether hospital-level 30-day readmission measures for publicly reported conditions (HF, AMI, and pneumonia) among Medicare patients reflect those for Medicare patients hospitalized for unreported conditions or non-Medicare patients hospitalized with HF, AMI, or pneumonia.

DESIGN

Cross-sectional.

SETTING

Population-based.

PARTICIPANTS

Hospitals in the all-payer Nationwide Readmissions Database in 2013 and 2014.

MEASUREMENTS

Hospital-level 30-day all-cause risk-standardized excess readmission ratios (ERRs) were compared for 3 groups of patients: Medicare beneficiaries admitted for HF, AMI, or pneumonia (Medicare reported group); Medicare beneficiaries admitted for other conditions (Medicare unreported group); and non-Medicare beneficiaries admitted for HF, AMI, or pneumonia (non-Medicare group).

RESULTS

Within-hospital differences in ERRs varied widely among groups. Medicare reported ratios differed from Medicare unreported ratios by more than 0.1 for 29% of hospitals and from non-Medicare ratios by more than 0.1 for 46% of hospitals. Among hospitals with higher readmission ratios, ERRs for the Medicare reported group tended to overestimate ERRs for the non-Medicare group but underestimate those for the Medicare unreported group.

LIMITATION

Medicare groups and risk adjustment differed slightly from those used by the Centers for Medicare & Medicaid Services.

CONCLUSION

Hospital ERRs, as estimated by Medicare to determine financial penalties, have poor agreement with corresponding measures for populations and conditions not tied to financial penalties. Current publicly reported measures may not be good surrogates for overall hospital quality related to 30-day readmissions.

PRIMARY FUNDING SOURCE

Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology.

A Review of Discharge-Prediction Processes in Acute Care Hospitals

AIMS AND OBJECTIVES

Discharge prediction is designed to streamline inpatient flow and reduce hospital overcrowding without adding capacity. This study's objective was to describe the literature on discharge prediction and assess its usefulness in evaluating the implementation and outcomes of discharge prediction projects.

METHODS

The authors reviewed the current peer-reviewed and grey literature on discharge prediction projects in acute care hospitals. Project descriptions were analyzed using Donabedian's structure-process-outcome model for evaluating complex healthcare innovations.

RESULTS

The review revealed a paucity of literature on the use and effectiveness of discharge prediction. There is high variation in its use and generally poor reporting of both implementation and outcomes.

CONCLUSIONS

The literature on discharge prediction generally lacks the descriptive detail that would be useful to parties considering or planning a discharge prediction initiative. Further study is required to determine how best to integrate these prediction tools into acute care hospitals.

Rankings versus reality in pancreatic cancer surgery: a real-world comparison

BACKGROUND

Patients are increasingly confronted with systems for rating hospitals. However, the correlations between publicized ratings and actual outcomes after pancreatectomy are unknown.

METHODS

The Massachusetts Division of Health Care Finance and Policy Hospital Inpatient Discharge Database was queried to identify pancreatic cancer resections carried out during 2005-2009. Hospitals performing fewer than 10 pancreatic resections in the 5-year period were excluded. Primary outcomes included mortality, complications, median length of stay (LoS) and a composite outcomes score (COS) combining primary outcomes. Ranks were determined and compared for: (i) volume, and (ii) ratings identified from consumer-directed hospital ratings including the US News & World Report (USN), Consumer Reports, Healthgrades and Hospital Compare. An inter-rater reliability analysis was performed and correlation coefficients (r) between outcomes and ratings, and between rating systems were calculated.

RESULTS

Eleven hospitals in which a total of 804 pancreatectomies were conducted were identified. Surgical volume correlated with overall outcome, but was not the strongest indicator. The highest correlation referred to that between USN rank and overall outcome. Mortality was most strongly correlated with Healthgrades ratings (r = 0.50); however, Healthgrades ratings demonstrated poorer correlations with all other outcomes. Consumer Reports ratings showed inverse correlations.

CONCLUSIONS

The plethora of publicly available hospital ratings systems demonstrates heterogeneity. Volume remains a good but imperfect indicator of surgical outcomes. Further systematic investigation into which measures predict quality outcomes in pancreatic cancer surgery will benefit both patients and providers.

What consumers want to know about quality when choosing a hospice provider

Despite the availability of endorsed quality measures and widespread usage of hospice, hospice quality data are rarely available to consumers. Moreover, little is known about how consumers prioritize extant measures. This study drew on focus group and survey data collected in 5 metropolitan areas. The study found that consumers reported the hospice quality indicators we tested were easy to understand. Participants placed top priority on measures related to pain and symptom management. Relative to consumers with hospice experience, consumers without previous experience tended to place less value on spiritual support for patients and caregivers, emotional support for caregivers, and after-hours availability. The National Quality Forum-approved measures resonate well with consumers. Consumers also appear to be ready for access to data on the quality of hospice providers.

The public disclosure of accreditation information in Australia: stakeholder perceptions of opportunities and challenges

Public disclosure is increasingly a requirement of accrediting agencies and governments. There are few published empirical evaluations of disclosure interventions that inform evidence-based implementation or policy. This study investigated the practices associated with the public disclosure of healthcare accreditation information, in addition to multi-stakeholder perceptions of key challenges and opportunities for improvement. We conducted a mixed methods study comprising analysis of disclosure practices by accreditation agencies, and 47 semi-structured individual or group interviews involving 258 people. Participants were diverse stakeholders associated with Australian primary, acute and residential aged care accreditation programmes. Four interrelated issues were identified. First, there was broad agreement that accreditation information should be publicly disclosed, although the three accreditation agencies differed in the information they made public. Second, two implementation issues emerged: the need to educate the community about accreditation information, and the practical question of the detail to be provided. Third, the impact, both positive and negative, of disclosing accreditation information was raised. Fourth, the lack of knowledge about the impact on consumers was discussed. Public disclosure of accreditation information is an idea that has widespread support. However, translating the idea into practice, so as to produce appropriate, meaningful information, is a challenge.

The use and misuse of biomedical data: is bigger really better?

Very large biomedical research databases, containing electronic health records (EHR) and genomic data from millions of patients, have been heralded recently for their potential to accelerate scientific discovery and produce dramatic improvements in medical treatments. Research enabled by these databases may also lead to profound changes in law, regulation, social policy, and even litigation strategies. Yet, is "big data" necessarily better data? This paper makes an original contribution to the legal literature by focusing on what can go wrong in the process of biomedical database research and what precautions are necessary to avoid critical mistakes. We address three main reasons for approaching such research with care and being cautious in relying on its outcomes for purposes of public policy or litigation. First, the data contained in biomedical databases is surprisingly likely to be incorrect or incomplete. Second, systematic biases, arising from both the nature of the data and the preconceptions of investigators, are serious threats to the validity of research results, especially in answering causal questions. Third, data mining of biomedical databases makes it easier for individuals with political, social, or economic agendas to generate ostensibly scientific but misleading research findings for the purpose of manipulating public opinion and swaying policymakers. In short, this paper sheds much-needed light on the problems of credulous and uninformed acceptance of research results derived from biomedical databases. An understanding of the pitfalls of big data analysis is of critical importance to anyone who will rely on or dispute its outcomes, including lawyers, policymakers, and the public at large. The Article also recommends technical, methodological, and educational interventions to combat the dangers of database errors and abuses.

California hospitals response to state and federal policies related to health care-associated infections

In October 2008, the Centers for Medicare and Medicaid Services (CMS) denied payment for ten selected health care-associated infections (HAI). In January 2009, California enacted mandatory reporting of infection prevention processes and HAI rates. This longitudinal mixed-methods study examined the impact of federal and state policy changes on California hospitals. Data on structures, processes, and outcomes of care were collected pre- and post-policy changes. In-depth interviews with hospital personnel were performed after policy implementation. More than 200 hospitals participated with 25 personnel interviewed. We found significant increases in adoption of and adherence to evidence-based practices and decreased HAI rates (p < .05). Infection preventionists (IP) spent more time on surveillance and in their offices and less time on education and in other locations (p < .05). Qualitative data confirmed mandatory reporting had intended and unintended consequences and highlighted the importance of technology and organizational climate in preventing infections and the changing IPs' role. This is especially relevant because the California Department of Public Health has since mandated hospitals to report data on 29 different for surgical site infections and a lawsuit has been filed to delay the implementation of these requirements.

Public Reporting on Risk-Adjusted Mortality After Percutaneous Coronary Interventions in New York State

Background—

Since the advent of public reporting on risk-adjusted mortality for coronary artery bypass graft surgery, public reporting on outcomes has expanded to include a variety of dissimilar conditions and procedures. We have little evidence to support such broad-based efforts.

Methods and Results—

We examined the quality performance of 351 cardiologists at 48 hospitals in New York State, using publicly reported risk-adjusted mortality rates (RAMRs) for nonemergent percutaneous coronary interventions between 1998 and 2007. In the year after report release, we examined the following: (1) average RAMR for hospitals, (2) change in market share for hospitals and cardiologists, and (3) proportion of physicians leaving practice. We found that patients who picked a hospital that performed significantly better than expected in prior years had lower RAMRs (0.47, 0.61, and 0.72 for patients choosing hospitals whose prior reports were better than, as, and worse than expected; P =0.02). However, choosing a hospital in the top quartile (or decile) of performance in prior years did not decrease a patient's chance of dying ( P =0.29, or P =0.27). Performance ranking was not associated with a change in market share for hospitals or for physicians, or with leaving practice (all P >0.05).

Conclusions—

Public reporting on nonemergent percutaneous coronary interventions in New York State identifies very high and low performers but provides insufficient information to differentiate between most hospitals. It appears to have had no effect on market share or physicians' decisions to leave practice. The utility of public reporting on RAMRs may differ for different conditions and procedures.