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BACKGROUND: To address concerns that the Hospital Readmissions Reduction Program (HRRP) unfairly penalized safety net hospitals treating patients with high social and functional risks, Medicare recently modified HRRP to compare hospitals with similar proportions of high-risk, dual-eligible patients (“peer group hospitals”). Whether the change fully accounts for patients’ social and functional risks is unknown. OBJECTIVE: Examine risk-standardized readmission rates (RSRRs) and hospital penalties after adding patient-level social and functional and community-level risk factors. DESIGN: Using 2000-2014 Medicare hospital discharge, Health and Retirement Study, and community-level data, latent factors for patient social and functional factors and community factors were identified. We estimated RSRRs for peer groups and by safety net status using four hierarchical logistic regression models: “base” (HRRP model); “patient” (base plus patient factors); “community” (base plus community factors); and “full” (all factors). The proportion of hospitals penalized was calculated by safety net status. PATIENTS: 20,255 fee-for-service Medicare beneficiaries (65+) with eligible index hospitalizations MAIN MEASURES: RSRRs KEY RESULTS: Half of safety net hospitals are in peer group 5. Compared with other hospitals, peer group 5 hospitals (most dual-eligibles) treated sicker, more functionally limited patients from socially disadvantaged groups. RSRRs decreased by 0.7% for peer groups 2 and 4 and 1.3% for peer group 5 under the patient and full (versus base) models. Measured performance improved after adjusting for patient risk factors for hospitals in peer group 4 and 5 hospitals, but worsened for those in peer groups 1, 2, and 3. Under the patient (versus base) model, fewer safety net hospitals (48.7% versus 51.3%) but more non-safety net hospitals (50.0% versus 49.1%) were penalized. CONCLUSIONS: Patient-level risk adjustment decreased RSRRs for hospitals serving more at-risk patients and proportion of safety net hospitals penalized, while modestly increasing RSRRs and proportion of non-safety net hospitals penalized. Results suggest HRRP modifications may not fully account for hospital variation in patient-level risk. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11606-020-06222-1) contains supplementary material, which is available to authorized users.

BACKGROUND: Potentially preventable admissions are a target for healthcare cost containment. OBJECTIVE: To identify rates of, characterize associations with, and explore physician decision-making around potentially preventable admissions. DESIGN: A comparative cohort study was used to determine rates of potentially preventable admissions and to identify associated factors and patient outcomes. A qualitative case study was used to explore physicians’ clinical decision-making. PARTICIPANTS: Patients admitted from the emergency department (ED) to the general medicine (GM) service over a total of 4 weeks were included as cases (N = 401). Physicians from both emergency medicine (EM) and GM that were involved in the cases were included (N = 82). APPROACH: Physicians categorized admissions as potentially preventable. We examined differences in patient characteristics, admission characteristics, and patient outcomes between potentially preventable and control admissions. Interviews with participating physicians were conducted and transcribed. Transcriptions were systematically analyzed for key concepts regarding potentially preventable admissions. KEY RESULTS: EM and GM physicians categorized 22.2% (90/401) of admissions as potentially preventable. There were no significant differences between potentially preventable and control admissions in patient or admission characteristics. Potentially preventable admissions had shorter length of stay (2.1 vs. 3.6 days, p

Diagnostic and treatment delay in depression are due to physician and patient factors. Patients vary in awareness of their depressive symptoms and ability to bring depression-related concerns to medical attention.To inform interventions to improve recognition and management of depression in primary care by understanding patients' inner experiences prior to and during the process of seeking treatment.Focus groups, analyzed qualitatively.One hundred and sixteen adults (79% response) with personal or vicarious history of depression in Rochester NY, Austin TX and Sacramento CA. Neighborhood recruitment strategies achieved sociodemographic diversity.Open-ended questions developed by a multidisciplinary team and refined in three pilot focus groups explored participants' "lived experiences" of depression, depression-related beliefs, influences of significant others, and facilitators and barriers to care-seeking. Then, 12 focus groups stratified by gender and income were conducted, audio-recorded, and analyzed qualitatively using coding/editing methods.Participants described three stages leading to engaging in care for depression - "knowing" (recognizing that something was wrong), "naming" (finding words to describe their distress) and "explaining" (seeking meaningful attributions). "Knowing" is influenced by patient personality and social attitudes. "Naming" is affected by incongruity between the personal experience of depression and its narrow clinical conceptualizations, colloquial use of the word depression, and stigma. "Explaining" is influenced by the media, socialization processes and social relations. Physical/medical explanations can appear to facilitate care-seeking, but may also have detrimental consequences. Other explanations (characterological, situational) are common, and can serve to either enhance or reduce blame of oneself or others.To improve recognition of depression, primary care physicians should be alert to patients' ill-defined distress and heterogeneous symptoms, help patients name their distress, and promote explanations that comport with patients' lived experience, reduce blame and stigma, and facilitate care-seeking.

OBJECTIVE: Efforts to evaluate variations in cardiac procedures have focused on patient factors and differences in health care delivery systems. We wanted to assess how physicians’ inclination to test patients with coronary artery disease influences utilization patterns. SETTING AND SUBJECTS: Physicians and the populations of Maine, New Hampshire, and Vermont. DESIGN: We conducted a survey of 263 family practitioners, internists, and cardiologists residing in 57 hospital service areas in Maine, New Hampshire, and Vermont. Using patient scenarios, we assessed the clinicians’ inclinations to test during the evaluation of patients with coronary artery disease. Self-reported testing intensities were used to create three indices: a Catheterization Index, an Imaging Exercise Tolerance Test (ETT) Index, and a Nonimaging ETT Index. Using administrative data, age- and gender-adjusted population-based coronary angiography rates were calculated. Physicians were assigned to low (2.9/1,000), average (4.2/1,000), and high (5.8/1,000) coronary angiography rate areas, based on where they practice. Analysis of variance techniques were used to assess the relation of the index scores to the population-based coronary angiography rates and to physician specialties. RESULTS: There was a positive relationship between the population-based coronary angiography rates and the self-reported scores of the Catheterization Index (p < .005) and the Imaging ETT Index (p = .01), but none was found for the Nonimaging ETT Index (p = .10). These relationships were evident in subanalyses of cardiologists and internists, but not of family practitioners. CONCLUSIONS: Self-reported testing intensity by physicians is related to the population-based rates of coronary angiography. This relationship cuts across specialties, suggesting that there is a “medical signature” for the evaluation of patients with coronary artery disease.

To better clarify patient factors that predict survival from in-hospital cardiopulmonary resuscitation (CPR), using two methods: 1) meta-analysis and 2) validation of a prediction model, the pre-arrest morbidity (PAM) index.Meta-analysis of previously published studies by standard techniques. Retrospective chart review of validation sample.University-affiliated teaching hospital.Meta-analytic sample of 21 previous studies from 1965-1989. The validation sample consisted of all patients surviving resuscitation from the authors' hospital during the period September 1986 to January 1991. A matched sample of patients who did not survive from the same time period was used as the comparison group.None.The strongest negative predictors of survival, by meta-analysis, were renal failure (r = 0.088, p0.0002), cancer (r = 0.08, p0.0002), and age more than 60 years (r = 0.063, p0.006). Sepsis (r = 0.046, p0.02), recent cerebrovascular accident (CVA) (r = 0.038, p0.04), and congestive heart failure (CHF) class III/IV (r = 0.036, p0.05) were weaker negative predictors. Presence of acute myocardial infarction (AMI) was a significant positive predictor of survival (r = 0.15, p0.0001). The PAM score was highly predictive of survival in a logistic regression model (p0.0003, R2 = 9.6%). No patient who survived to discharge had a PAM score higher than 8.Meta-analysis reveals that the most significant negative predictors of survival from CPR are renal failure, cancer, and age more than 60 years, while AMI is a significant positive predictor. The PAM index is a useful method of stratifying probability of survival from CPR, especially for those patients with high PAM scores, who have essentially no chance of survival.

BACKGROUND Osteoporosis screening rates are low, and it is unclear which patient factors are associated with screening and physician recommendations for screening. OBJECTIVE To identify patient characteristics associated with osteoporosis screening recommendations and receipt of screening in older adults. DESIGN Cross-sectional mailed survey. PARTICIPANTS Women and men ≥60 years old living in or near western Pennsylvania. MEASUREMENTS Sociodemographic characteristics and osteoporosis-related data, including risk factors, physician recommendations for screening, and receipt of screening. Multivariable logistic regression analyses were performed to determine odds ratios for receipt of screening and screening recommendations for individuals with particular osteoporosis risk factors, adjusting for sociodemographic and other risk factors. RESULTS Surveys were completed by 1,268 of the 1,830 adults to whom surveys were mailed (69.3%). Most respondents were white (92.9%), female (58.7%), and believed they were in good to excellent health (88.2%). Only 47.6% said their physician recommended osteoporosis screening, and 62.6% of all respondents reported being screened. Screening recommendations were less likely for older respondents than younger ones (OR, 0.87 per 5-year increase in age; 95% CI, 0.77–0.97). Individuals with osteoporosis risk factors of a history of oral steroid use for >1 month, height loss >2.54 cm, or history of low-trauma fracture were no more likely to report screening recommendations than individuals without these characteristics. Receipt of screening was no more likely for more elderly respondents or respondents with a history of oral steroid use for >1 month than for respondents without these characteristics. CONCLUSIONS Individuals with several known osteoporosis risk factors are not being sufficiently targeted for screening.