Sheryl M Davies

A systematic review of the care coordination measurement landscape

BackgroundCare coordination has increasingly been recognized as an important aspect of high-quality health care delivery. Robust measures of coordination processes will be essential tools to evaluate, guide and support efforts to understand and improve coordination, yet little agreement exists among stakeholders about how to best measure care coordination. We aimed to review and characterize existing measures of care coordination processes and identify areas of high and low density to guide future measure development.MethodsWe conducted a systematic review of measures published in MEDLINE through April 2012 and identified from additional key sources and informants. We characterized included measures with respect to the aspects of coordination measured (domain), measurement perspective (patient/family, health care professional, system representative), applicable settings and patient populations (by age and condition), and data used (survey, chart review, administrative claims).ResultsAmong the 96 included measure instruments, most relied on survey methods (88%) and measured aspects of communication (93%), in particular the transfer of information (81%). Few measured changing coordination needs (11%). Nearly half (49%) of instruments mapped to the patient/family perspective; 29% to the system representative and 27% to the health care professionals perspective. Few instruments were applicable to settings other than primary care (58%), inpatient facilities (25%), and outpatient specialty care (22%).ConclusionsNew measures are needed that evaluate changing coordination needs, coordination as perceived by health care professionals, coordination in the home health setting, and for patients at the end of life.

Assessment of a Novel Hybrid Delphi and Nominal Groups Technique to Evaluate Quality Indicators

OBJECTIVE To test the implementation of a novel structured panel process in the evaluation of quality indicators. DATA SOURCE National panel of 64 clinicians rating usefulness of indicator applications in 2008-2009. STUDY DESIGN Hybrid panel combined Delphi Group and Nominal Group (NG) techniques to evaluate 81 indicator applications. PRINCIPAL FINDINGS The Delphi Group and NG rated 56 percent of indicator applications similarly. Group assignment (Delphi versus Nominal) was not significantly associated with mean ratings, but specialty and research interests of panelists, and indicator factors such as denominator level and proposed use were. Rating distributions narrowed significantly in 20.8 percent of applications between review rounds. CONCLUSIONS The hybrid panel process facilitated information exchange and tightened rating distributions. Future assessments of this method might include a control panel.

Limitations of using same-hospital readmission metrics

OBJECTIVE To quantify the limitations associated with restricting readmission metrics to same-hospital only readmission. DESIGN Using 2000-2009 California Office of Statewide Health Planning and Development Patient Discharge Data Nonpublic file, we identified the proportion of 7-, 15- and 30-day readmissions occurring to the same hospital as the initial admission using All-cause Readmission (ACR) and 3M Corporation Potentially Preventable Readmissions (PPR) Metric. We examined the correlation between performance using same and different hospital readmission, the percent of hospitals remaining in the extreme deciles when utilizing different metrics, agreement in identifying outliers and differences in longitudinal performance. Using logistic regression, we examined the factors associated with admission to the same hospital. RESULTS 68% of 30-day ACR and 70% of 30-day PPR occurred to the same hospital. Abdominopelvic procedures had higher proportions of same-hospital readmissions (87.4-88.9%), cardiac surgery had lower (72.5-74.9%) and medical DRGs were lower than surgical DRGs (67.1 vs. 71.1%). Correlation and agreement in identifying high- and low-performing hospitals was weak to moderate, except for 7-day metrics where agreement was stronger (r = 0.23-0.80, Kappa = 0.38-0.76). Agreement for within-hospital significant (P < 0.05) longitudinal change was weak (Kappa = 0.05-0.11). Beyond all patient refined-diagnostic related groups, payer was the most predictive factor with Medicare and MediCal patients having a higher likelihood of same-hospital readmission (OR 1.62, 1.73). CONCLUSIONS Same-hospital readmission metrics are limited for all tested applications. Caution should be used when conducting research, quality improvement or comparative applications that do not account for readmissions to other hospitals.

Why rescue the administrative data version of the "failure to rescue" quality indicator.

I ust as continuous quality improvement is needed for the highly complex world of health I care delivery, measurement of quality itself merits continual examination. With the price tag for health care rising and increased public awareness of medical error, pressures continue to mount for ways to efficiently measure the outcomes of health care. An alphabet soup of organizations are developing, evaluating, and implementing such measures for a variety of purposes. However, without sound validation studies and careful interpretation of their implications, the science of measurement and the appropriate usage of measures are stymied. Therefore, the validation study by Horwitz et al, conducted with members of the University HealthSystem Consortium (UHC), is a welcome addition to the scientific literature. This editorial offers a careful examination of the study and its implications, so that the sound bites inevitably culled from its analysis and conclusions do not obscure the essential truths. Drawing from a familiar metaphor the baby and the bathwater the voices that quickly seize any reason to dismiss an indicator, must be averted to preserve that which is particularly valuable in the tub: (1) the concept of failure to rescue (FTR), (2) use of administrative data, (3) chart review validation, and (4) prudent interpretation of the validation study.

Interhospital Facility Transfers in the United States: A Nationwide Outcomes Study.

Objectives Patient transfers between hospitals are becoming more common in the United States. Disease-specific studies have reported varying outcomes associated with transfer status. However, even as national quality improvement efforts and regulations are being actively adopted, forcing hospitals to become financially accountable for the quality of care provided, surprisingly little is known about transfer patients or their outcomes at a population level. This population-wide study provides timely analyses of the characteristics of this particularly vulnerable and sizable inpatient population. We identified and compared characteristics and outcomes of transfer and nontransfer patients. Methods With the use of the 2009 Nationwide Inpatient Sample, a nationally representative sample of U.S. hospitalizations, we examined patient characteristics, in-hospital adverse events, and discharge disposition for transfer versus nontransfer patients in this observational study. Results We identified 1,397,712 transfer patients and 31,692,211 nontransfer patients. Age, sex, race, and payer were significantly associated with odds of transfer (P < 0.05). Transfer patients had higher risk-adjusted inpatient mortality (4.6 versus 2.1, P < 0.01), longer length of stay (13.3 versus 4.5, P < 0.01), and fewer routine disposition discharges (53.6 versus 68.7, P < 0.01). In-hospital adverse events were significantly higher in transfer patients compared with nontransfer patients (P < 0.05). Conclusions Our results suggest that transfer patients have inferior outcomes compared with nontransfer patients. Although they are clinically complex patients and assessing accountability as between the transferring and receiving hospitals is methodologically difficult, transfer patients must nonetheless be included in quality benchmark data to assess the potential impact this population has on hospital outcome profiles. With hospital accountability and value-based payments constituting an integral part of health care reform, documenting the quality of care delivered to transfer patients is essential before accurate quality assessment improvement efforts can begin in this patient population.

Impact of Including Readmissions for Qualifying Events in the Patient Safety Indicators

The Agency for Healthcare Research and Quality Patient Safety Indicators (PSIs) do not capture complications arising after discharge. This study sought to quantify the bias related to omission of readmissions for PSI-qualifying conditions. Using 2000-2009 California Office of Statewide Health Planning and Development Patient Discharge Data, the study team examined the change in PSI rates when including readmissions in the numerator, hospitals performing in the extreme deciles, and longitudinal performance. Including 7-day readmissions resulted in a 0.3% to 8.9% increase in average hospital PSI rates. Hospital PSI rates with and without PSI-qualifying 30-day readmissions were highly correlated for point estimates and within-hospital longitudinal change. Most hospitals remained in the same relative performance decile. Longer length of stay, public payer, and discharge to skilled nursing facilities were associated with a higher risk of readmission for a PSI-qualifying event. Failure to include readmissions in calculating PSIs is unlikely to lead to erroneous conclusions.