Cleft palate surgery: an evaluation of length of stay, complications, and costs by hospital type.

OBJECTIVE: The purpose of this study was to assess length of stay (LOS), complication rates, costs, and charges of cleft palate repair by various hospital types. We hypothesized that pediatric hospitals would have shorter LOS, fewer complications, and lower costs and charges. METHODS: Patients were identified by ICD-9-CM code for cleft palate repair (27.62) using databases from the Agency for Health Research and Quality Healthcare Cost and Utilization Project Kids' Inpatient Database from 1997, 2000, 2003, and 2006. Patient characteristics (age, race, gender, insurer, comorbidities) and facility resources (hospital beds, cleft palate surgery volume, nurse-to-bed ratio, pediatric intensive care unit [PICU], PICU intensivist, burn unit) were examined. Hospitals types included pediatric hospitals, general hospitals, and nonaccredited children's hospital. For each hospital type, mean LOS, extended LOS (LOS > 2), and complications were assessed. RESULTS: A total of 14,153 patients had cleft repair with a mean LOS of 2 days (SD, 0.04), mortality 0.01%, transfusion 0.3%, and complication <3%. Pediatric hospitals had fewer patients with extended hospital stays. Patients with an LOS >2 days were associated with fourfold higher complications. Comorbidities increased the relative rate of LOS >2 days by 90%. Pediatric hospitals had the highest comorbidities, yet 35% decreased the relative rate of LOS >2 days. Median total charges of $10,835 increased to $15,104 with LOS >2 days; median total costs of $4367 increased to $6148 with a LOS >2 days. CONCLUSION: Pediatric hospitals had higher comorbidities yet shorter LOS. Pediatric resources significantly decreased the relative rate of LOS >2 days. Median costs and charges increased by 41% with LOS >2 days. Further research is needed to understand additional aspects of pediatric hospitals associated with lower LOS.

A systematic review of the care coordination measurement landscape.

BACKGROUND: Care 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. METHODS: We 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). RESULTS: Among 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%). CONCLUSIONS: New 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.

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.

Incorporating harms into the weighting of the revised Agency for Healthcare Research and Quality Patient Safety for Selected Indicators Composite (Patient Safety Indicator 90).

OBJECTIVE: To reweight the Agency for Healthcare Research and Quality Patient Safety for Selected Indicators Composite (Patient Safety Indicator [PSI] 90) from weights based solely on the frequency of component PSIs to those that incorporate excess harm reflecting patients' preferences for outcome-related health states. DATA SOURCES: National administrative and claims data involving hospitalizations in nonfederal, nonrehabilitation, acute care hospitals. STUDY DESIGN: We estimated the average excess aggregate harm associated with the occurrence of each component PSI using a cohort sample for each indicator based on denominator-eligible records. We used propensity scores to account for potential confounding in the risk models for each PSI and weighted observations to estimate the "average treatment effect in the treated" for those with the PSI event. We fit separate regression models for each harm outcome. Final PSI weights reflected both the disutilities and the frequencies of the harms. DATA COLLECTION/EXTRACTION METHODS: We estimated PSI frequencies from the 2012 Healthcare Cost and Utilization Project State Inpatient Databases with present on admission data and excess harms using 2012-2013 Centers for Medicare & Medicaid Services Medicare Fee-for-Service data. PRINCIPAL FINDINGS: Including harms in the weighting scheme changed individual component weights from the original frequency-based weighting. In the reweighted composite, PSIs 11 ("Postoperative Respiratory Failure"), 13 ("Postoperative Sepsis"), and 12 ("Perioperative Pulmonary Embolism or Deep Vein Thrombosis") contributed the greatest harm, with weights of 29.7%, 21.1%, and 20.4%, respectively. Regarding reliability, the overall average hospital signal-to-noise ratio for the reweighted PSI 90 was 0.7015. Regarding discrimination, among hospitals with greater than median volume, 34% had significantly better PSI 90 performance, and 41% had significantly worse performance than benchmark rates (based on percentiles). CONCLUSIONS: Reformulation of PSI 90 with harm-based weights is feasible and results in satisfactory reliability and discrimination, with a more clinically meaningful distribution of component weights.

Expanding the uses of AHRQ's prevention quality indicators: validity from the clinician perspective.

BACKGROUND: The Agency for Healthcare Research and Quality's prevention quality indicators (PQIs) are used as a metric of area-level access to quality care. Recently, interest has expanded to using the measures at the level of payer or large physician groups, including public reporting or pay-for-performance programs. However, the validity of these expanded applications is unknown. RESEARCH DESIGN: We conducted a novel panel process to establish face validity of the 12 PQIs at 3 denominator levels: geographic area, payer, and large physician groups; and 3 uses: quality improvement, comparative reporting, and pay for performance. Sixty-four clinician panelists were split into Delphi and Nominal Groups. We aimed to capitalize on the reliability of the Delphi method and information sharing in the Nominal group method by applying these techniques simultaneously. We examined panelists' perceived usefulness of the indicators for specific uses using median scores and agreement within and between groups. RESULTS: Panelists showed stronger support of the usefulness of chronic disease indicators at the payer and large physician group levels than for acute disease indicators. Panelists fully supported the usefulness of 2 indicators for comparative reporting (asthma, congestive heart failure) and no indicators for pay-for-performance applications. Panelists expressed serious concerns about the usefulness of all new applications of 3 indicators (angina, perforated appendix, dehydration). Panelists rated age, current comorbidities, earlier hospitalization, and socioeconomic status as the most important risk-adjustment factors. CONCLUSIONS: Clinicians supported some expanded uses of the PQIs, but generally expressed reservations. Attention to denominator definitions and risk adjustment are essential for expanded use.

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.

Development and Validation of the Agency for Healthcare Research and Quality Measures of Potentially Preventable Emergency Department (ED) Visits: The ED Prevention Quality Indicators for General Health Conditions.

OBJECTIVE: To develop and validate rates of potentially preventable emergency department (ED) visits as indicators of community health. DATA SOURCES: Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project 2008-2010 State Inpatient Databases and State Emergency Department Databases. STUDY DESIGN: Empirical analyses and structured panel reviews. METHODS: Panels of 14-17 clinicians and end users evaluated a set of ED Prevention Quality Indicators (PQIs) using a Modified Delphi process. Empirical analyses included assessing variation in ED PQI rates across counties and sensitivity of those rates to county-level poverty, uninsurance, and density of primary care physicians (PCPs). PRINCIPAL FINDINGS: ED PQI rates varied widely across U.S. communities. Indicator rates were significantly associated with county-level poverty, median income, Medicaid insurance, and levels of uninsurance. A few indicators were significantly associated with PCP density, with higher rates in areas with greater density. A clinical and an end-user panel separately rated the indicators as having strong face validity for most uses evaluated. CONCLUSIONS: The ED PQIs have undergone initial validation as indicators of community health with potential for use in public reporting, population health improvement, and research.

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.

Medicaid dental coverage alone may not lower rates of dental emergency department visits.

Medicaid was expanded to millions of individuals under the Affordable Care Act, but many states do not provide dental coverage for adults under their Medicaid programs. In the absence of dental coverage, patients may resort to costly emergency department (ED) visits for dental conditions. Medicaid coverage of dental benefits could help ease the burden on the ED, but ED use for dental conditions might remain a problem in areas with a scarcity of dentists. We examined county-level rates of ED visits for nontraumatic dental conditions in twenty-nine states in 2010 in relation to dental provider density and Medicaid coverage of nonemergency dental services. Higher density of dental providers was associated with lower rates of dental ED visits by patients with Medicaid in rural counties but not in urban counties, where most dental ED visits occurred. County-level Medicaid-funded dental ED visit rates were lower in states where Medicaid covered nonemergency dental services than in other states, although this difference was not significant after other factors were adjusted for. Providing dental coverage alone might not reduce Medicaid-funded dental ED visits if patients do not have access to dental providers.

A national profile of patient safety in U.S. hospitals.

Measures based on routinely collected data would be useful to examine the epidemiology of patient safety. Extending previous work, we established the face and consensual validity of twenty Patient Safety Indicators (PSIs). We generated a national profile of patient safety by applying these PSIs to the HCUP Nationwide Inpatient Sample. The incidence of most nonobstetric PSIs increased with age and was higher among African Americans than among whites. The adjusted incidence of most PSIs was highest at urban teaching hospitals. The PSIs may be used in AHRQ's National Quality Report, while providers may use them to screen for preventable complications, target opportunities for improvement, and benchmark performance.

Implications of metric choice for common applications of readmission metrics.

OBJECTIVE: To quantify the differential impact on hospital performance of three readmission metrics: all-cause readmission (ACR), 3M Potential Preventable Readmission (PPR), and Centers for Medicare and Medicaid 30-day readmission (CMS). DATA SOURCES: 2000-2009 California Office of Statewide Health Planning and Development Patient Discharge Data Nonpublic file. STUDY DESIGN: We calculated 30-day readmission rates using three metrics, for three disease groups: heart failure (HF), acute myocardial infarction (AMI), and pneumonia. Using each metric, we calculated the absolute change and correlation between performance; the percent of hospitals remaining in extreme deciles and level of agreement; and differences in longitudinal performance. PRINCIPAL FINDINGS: Average hospital rates for HF patients and the CMS metric were generally higher than for other conditions and metrics. Correlations between the ACR and CMS metrics were highest (r = 0.67-0.84). Rates calculated using the PPR and either ACR or CMS metrics were moderately correlated (r = 0.50-0.67). Between 47 and 75 percent of hospitals in an extreme decile according to one metric remained when using a different metric. Correlations among metrics were modest when measuring hospital longitudinal change. CONCLUSIONS: Different approaches to computing readmissions can produce different hospital rankings and impact pay-for-performance. Careful consideration should be placed on readmission metric choice for these applications.

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.

Preliminary assessment of pediatric health care quality and patient safety in the United States using readily available administrative data.

OBJECTIVES: With >6 million hospital stays, costing almost $50 billion annually, hospitalized children represent an important population for which most inpatient quality indicators are not applicable. Our aim was to develop indicators using inpatient administrative data to assess aspects of the quality of inpatient pediatric care and access to quality outpatient care. METHODS: We adapted the Agency for Healthcare Research and Quality quality indicators, a publicly available set of measurement tools refined previously by our team, for a pediatric population. We systematically reviewed the literature for evidence regarding coding and construct validity specific to children. We then convened 4 expert panels to review and discuss the evidence and asked them to rate each indicator through a 2-stage modified Delphi process. From the 2000 and 2003 Agency for Healthcare Research and Quality Healthcare Cost and Utilization Project Kids' Inpatient Database, we generated national estimates for provider level indicators and for area level indicators. RESULTS: Panelists recommended 18 indicators for inclusion in the pediatric quality indicator set based on overall usefulness for quality improvement efforts. The indicators included 13 hospital-level indicators, including 11 based on complications, 1 based on mortality, and 1 based on volume, as well as 5 area-level potentially preventable hospitalization indicators. National rates for all 18 of the indicators varied minimally between years. Rates in high-risk strata are notably higher than in the overall groups: in 2003 the decubitus ulcer pediatric quality indicator rate was 3.12 per 1000, whereas patients with limited mobility experienced a rate of 22.83. Trends in rates by age varied across pediatric quality indicators: short-term complications of diabetes increased with age, whereas admissions for gastroenteritis decreased with age. CONCLUSIONS: Tracking potentially preventable complications and hospitalizations has the potential to help prioritize quality improvement efforts at both local and national levels, although additional validation research is needed to confirm the accuracy of coding.