Development and Initial Validation of the PROMIS®-Plus-HF Profile Measure.

Background Bringing together generic and heart failure (HF)-specific items in a publicly available, patient-reported outcome measure may facilitate routine health status assessment for improving clinical care and shared decision-making, assessing quality of care, evaluating new interventions, and comparing groups with different conditions. Methods and Results We performed a mixed-methods study to develop and validate the PROMIS®-Plus-HF (Patient-Reported Outcomes Measurement Information System®-Plus-Heart Failure) profile measure-a HF-specific instrument based on the generic PROMIS. We conducted 8 focus groups with 61 patients with HF and phone interviews with 10 HF clinicians. The measure was developed via an iterative process of reviewing existing PROMIS items and developing and testing new HF items. In a 600-patient sample, we estimated reliability (internal consistency; test-retest, with n=100 participants). We conducted validity analyses using Pearson r and Spearman ρ correlations with Kansas City Cardiomyopathy Questionnaire subscores. In a longitudinal sample, we performed responsiveness testing (paired t tests) with 75 patients with HF receiving interventions with expected health status improvement. The PROMIS-Plus-HF measure comprises 86 items (64 existing; 22 new) across 18 domains. Internal consistency reliability (Cronbach α) coefficients ranged from 0.52 to 0.96, with α≥0.70 in 12 of 17 domains. Test-retest intraclass correlation coefficients were ≥0.90. Correlations with Kansas City Cardiomyopathy Questionnaire subscores supported expected convergent ( r/ρ>0.60) and divergent validity ( r/ρ<0.30). In the longitudinal sample, 10 of 18 domains had improved ( P<0.05) scores from baseline to follow-up. Conclusions The PROMIS-Plus-HF profile measure-a complete assessment of physical, mental, and social health-exhibited good psychometric characteristics and may facilitate patient-centered care and research. Subsets of domains and items can be used depending on the clinical or research purpose.

Market variations in intensity of Medicare service use and beneficiary experiences with care.

OBJECTIVE: Examine associations between patient experiences with care and service use across markets. DATA SOURCES/STUDY SETTING: Medicare fee-for-service (FFS) and managed care (Medicare Advantage [MA]) beneficiaries in 306 markets from the 2003 Consumer Assessments of Healthcare Providers and Systems (CAHPS) surveys. Resource use intensity is measured by the 2003 end-of-life expenditure index. STUDY DESIGN: We estimated correlations and linear regressions of eight measures of case-mix-adjusted beneficiary experiences with intensity of service use across markets. DATA COLLECTION/EXTRACTION: We merged CAHPS data with service use data, excluding beneficiaries under 65 years of age or receiving Medicaid. PRINCIPAL FINDINGS: Overall, higher intensity use was associated (p<.05) with worse (seven measures) or no better care experiences (two measures). In higher-intensity markets, Medicare FFS and MA beneficiaries reported more problems getting care quickly and less helpful office staff. However, Medicare FFS beneficiaries in higher-intensity markets reported higher overall ratings of their personal physician and main specialist. Medicare MA beneficiaries in higher-intensity markets also reported worse quality of communication with physicians, ability to get needed care, and overall ratings of care. CONCLUSIONS: Medicare beneficiaries in markets characterized by high service use did not report better experiences with care. This trend was strongest for those in managed care.

Comorbidity risk-adjustment strategies are comparable among persons with hip fracture.

OBJECTIVE: To determine the magnitude and importance of declines in model performance associated with altering the data source and time frame from which comorbid conditions were identified in claims-based risk adjustment among persons with hip fracture. STUDY DESIGN AND SETTING: Medicare claims data were used to identify incident hip fracture cases in 1999. Three risk-adjustment instruments were evaluated: one by Iezzoni, the Charlson Index (Romano adaptation), and the Clinical Classification Software (CCS). Several implementation strategies, defined by altering data source (MedPar and/or Part B claims) and time frame (index hospitalization and/or 1-year preperiod), were assessed for each instrument. Logistic regression was used to predict 1-year mortality, and model performance was compared. RESULTS: Each instrument had modest ability to predict 1-year mortality after hip fracture. The CCS performed best overall (c=0.76), followed by the Iezzoni (c=0.73) and Charlson models (c=0.72). Although each instrument performed most favorably when applied to both inpatient and outpatient claims and when comorbidities were considered during the preperiod, varying data source and time frame had trivial effects on model performance. CONCLUSION: The similar predictive ability of the three risk-adjustment instruments suggests that ease of implementation be a key consideration in choosing an approach for hip fracture populations.

Abstracts in high profile journals often fail to report harm.

BACKGROUND: To describe how frequently harm is reported in the abstract of high impact factor medical journals. DESIGN AND POPULATION: We carried out a blinded structured review of a random sample of 363 Randomised Controlled Trials (RCTs) carried out on human beings, and published in high impact factor medical journals in 2003. Main endpoint: 1) Proportion of articles reporting harm in the abstract; and 2) Proportion of articles that reported harm in the abstract when harm was reported in the main body of the article. ANALYSIS: Corrected Prevalence Ratio (cPR) and its exact confidence interval were calculated. Non-conditional logistic regression was used. RESULTS: 363 articles and 407 possible comparisons were studied. Overall, harm was reported in 135 abstracts [37.2% (CI95%:32.2 to 42.4)]. Harm was reported in the main text of 243 articles [66.9% (CI95%: 61.8 to 71.8)] and was statistically significant in 54 articles [14.9% (CI95%: 11.4 to 19.0)]. Among the 243 articles that mentioned harm in the text, 130 articles [53.5% (CI95% 47.0 to 59.9)] reported harm in the abstract; a figure that rose to 75.9% (CI95%: 62.4 to 86.5) when the harm reported in the text was statistically significant. Harm in the abstract was more likely to be reported when statistically significant harm was reported in the main body of the article [cPR = 1.70 (CI95% 1.47 to 1.92)] and when drug companies (not public institutions) funded the RCTs [cPR = 1.29 (CI95% 1.03 to 1.67)]. CONCLUSION: Abstracts published in high impact factor medical journals underreport harm, even when harm is reported in the main body of the article.