Shifting the Demand for Vaccines: A Review of Strategies.

Vaccines prevent millions of deaths, and yet millions of people die each year from vaccine-preventable diseases. The primary reason for these deaths is that a significant fraction of the population chooses not to vaccinate. Why don't people vaccinate, and what can be done to increase vaccination rates besides providing free and easy access to vaccines? This review presents a conceptual framework, motivated by economic theory, of which factors shift the demand for vaccines. Next, it critically examines the literature on these demand shifters and interventions that target these demand shifters. The review concludes with offering directions for future research and lessons for public health decision making.

Trends in the Use of Skilled Nursing Facility and Home Health Care Under the Hospital Readmissions Reduction Program: An Interrupted Time-series Analysis.

BACKGROUND: Medicare's Hospital Readmission Reduction Program (HRRP) penalizes hospitals with elevated 30-day readmission rates for acute myocardial infarction (AMI), heart failure (HF), or pneumonia. To reduce readmissions, hospitals may have increased referrals to skilled nursing facilities (SNFs) and home health care. RESEARCH DESIGN: Outcomes included 30-day postdischarge utilization of SNF and home health care, including any use as well as days of use. Subjects included Medicare fee-for-service beneficiaries aged 65 years and older who were admitted with AMI, HF, or pneumonia to hospitals subject to the HRRP. Using an interrupted time-series analysis, we compared utilization rates observed after the announcement of the HRRP (April 2010 through September 2012) and after the imposition of penalties (October 2012 through September 2014) with projected utilization rates that accounted for pre-HRRP trends (January 2008 through March 2010). Models included patient characteristics and hospital fixed effects. RESULTS: For AMI and HF, utilization of SNF and home health care remained stable overall. For pneumonia, observed utilization of any SNF care increased modestly (1.0%, P<0.001 during anticipation; 2.4%, P<0.001 after penalties) and observed utilization of any home health care services declined modestly (-0.5%, P=0.008 after announcement; -0.7%, P=0.045 after penalties) relative to projections. Beneficiaries with AMI and pneumonia treated at penalized hospitals had higher rates of being in the community 30 days postdischarge. CONCLUSIONS: Hospitals might be shifting to more intensive postacute care to avoid readmissions among seniors with pneumonia. At the same time, penalized hospitals' efforts to prevent readmissions may be keeping higher proportions of their patients in the community.

Staffing Shortages, Staffing Hours, and Resident Deaths in US Nursing Homes During the COVID-19 Pandemic.

OBJECTIVES: Staffing shortages at nursing homes during the COVID-19 pandemic may have impacted care providers' staffing hours and affected residents' care and outcomes. This study examines the association of staffing shortages with staffing hours and resident deaths in nursing homes during the COVID-19 pandemic. DESIGN: This study measured staffing hours per resident using payroll data and measured weekly resident deaths and staffing shortages using the Centers for Disease Control and Prevention's National Healthcare Safety Network data. Multivariate linear regressions with facility and county-week fixed effects were used to investigate the association of staffing shortages with staffing hours and resident deaths. SETTING AND PARTICIPANTS: 15,212 nursing homes. MEASURES: The primary outcomes included staffing hours per resident of registered nurses (RNs), licensed practical nurses (LPNs), and certified nursing assistants (CNAs) and weekly total deaths per 100 residents. RESULTS: Between May 31, 2020, and May 15, 2022, 18.4% to 33.3% of nursing homes reported staffing shortages during any week. Staffing shortages were associated with lower staffing hours per resident with a 0.009 decrease in RN hours per resident (95% CI 0.005-0.014), a 0.014 decrease in LPN hours per resident (95% CI 0.010-0.018), and a 0.050 decrease in CNA hours per resident (95% CI 0.043-0.057). These are equivalent to a 1.8%, 1.7%, and 2.4% decline, respectively. There was a positive association between staffing shortages and resident deaths with 0.068 (95% CI 0.048-0.088) total deaths per 100 residents. This was equivalent to an increase of 10.5%. CONCLUSION AND IMPLICATIONS: Our results showed that self-reported staffing shortages were associated with a statistically significant decrease in staffing hours and with a statistically significant increase in resident deaths. These results suggest that addressing staffing shortages in nursing homes can save lives.

Socioeconomic risk factors of hypertension and blood pressure among persons aged 15-49 in Nepal: a cross-sectional study.

OBJECTIVES: This study estimated the prevalence of hypertension, in accordance with the American College of Cardiology and American Heart Association's 2017 guidelines, and examined the association between various socioeconomic factors and systolic blood pressure (SBP), diastolic blood pressure (DBP) and hypertension. SETTING AND DESIGN: We used nationally representative data from the 2016 Nepal Demographic and Health Survey. Multivariate analysis was used to study the association of hypertension with socioeconomic factors: logistic regression was used for hypertension and linear regression was used for DBP and SBP. PARTICIPANTS: Our sample consisted of 9827 adults between the ages of 15 and 49 years. RESULTS: The prevalence of hypertension was 36%. The mean DBP and SBP were 76.4 and 111.5, respectively. Janjatis (adjusted OR (AOR): 1.34, CI: 1.12 to 1.59), Other Terai castes (AOR: 1.38, CI: 1.03 to 1.84), Muslim and other ethnicities (AOR: 1.64, CI: 1.15 to 2.33) and Dalits (AOR: 1.26, CI: 1.00 to 1.58) had higher odds of hypertension. Individuals employed in professional, technical and managerial professions collectively (AOR: 1.62; CI: 1.18 to 2.21) also had higher odds of hypertension. Moderately food insecure household had lower odds of hypertension (AOR: 0.84; CI: 0.72 to 0.99) compared with households with no issue of food insecurity. Results were similar for SBP and DBP. When stratified by sex, there were differences mainly in terms of occupation and ethnicity. CONCLUSION: There are substantial disparities in hypertension prevalence in Nepal. These disparities extend across ethnic groups, occupational status and food security status. Differences also persist across different provinces. As hypertension continues to be increasingly more significant, more research is needed to better understand the disparities and gradients that exist across various socioeconomic factors.

Psychotic symptoms in a patient with Systemic Lupus Erythematosus: A diagnostic dilemma between lupus psychosis and steroid induced psychosis.

Introduction: Systemic Lupus Erythematosus (SLE) is a chronic auto-immune disorder with the involvement of multiple organ systems. It is more common in females. Case presentation: Here, we present a case of 12-year-old female, known case of SLE with lupus nephritis, presenting with neuropsychiatric symptoms. She was under steroids as well for a few weeks due to flare-up of symptoms prior to that. Due to this, there was a diagnostic dilemma between lupus psychosis and steroid induced psychosis. Clinical discussion: Approximately one third to half of the patients may have neurological involvement in Systemic Lupus Erythematosus. However, neuropsychiatric symptoms in them could be due to corticosteroids, which are frequently used in treatment. There are no definitive and easily available laboratory markers to distinguish these two aetiologies. Conclusions: Systemic Lupus Erythematosus patients, who are on steroids, with neuropsychiatric features should be assessed adequately. As there are no specific guideline and biomarkers to distinguish between these two, meticulous evaluation is necessary for appropriate management.

Luck of the draw: Role of chance in the assignment of medicare readmissions penalties.

Pay-for-performance programs are one strategy used by health plans to improve the efficiency and quality of care delivered to beneficiaries. Under such programs, providers are often compared against their peers in order to win bonuses or face penalties in payment. Yet luck has the potential to affect performance assessment through randomness in the sorting of patients among providers or through random events during the evaluation period. To investigate the impact luck can have on the assessment of performance, we investigated its role in assigning penalties under Medicare's Hospital Readmissions Reduction Policy (HRRP), a program that penalizes hospitals with excess readmissions. We performed simulations that estimated program hospitals' 2015 readmission penalties in 1,000 different hypothetical fiscal years. These hypothetical fiscal years were created by: (a) randomly varying which patients were admitted to each hospital and (b) randomly varying the readmission status of discharged patients. We found significant differences in penalty sizes and probability of penalty across hypothetical fiscal years, signifying the importance of luck in readmission performance under the HRRP. Nearly all of the impact from luck arose from events occurring after hospital discharge. Luck played a smaller role in determining penalties for hospitals with more beds, teaching hospitals, and safety-net hospitals.

Regression to the Mean in the Medicare Hospital Readmissions Reduction Program.

IMPORTANCE: Excess 30-day readmissions have declined substantially in hospitals initially penalized for high readmission rates under the Medicare Hospital Readmissions Reduction Program (HRRP). Although a possible explanation is that the policy incentivized penalized hospitals to improve care processes, another is regression to the mean (RTM), a statistical phenomenon that predicts entities farther from the mean in one period are likely to fall closer to the mean in subsequent (or preceding) periods owing to random chance. OBJECTIVE: To quantify the contribution of RTM to declining readmission rates at hospitals initially penalized under the HRRP. DESIGN, SETTING, AND PARTICIPANTS: This study analyzed data from Medicare Provider and Analysis Review files to assess changes in readmissions going forward and backward in time at hospitals with high and low readmission rates during the measurement window for the first year of the HRRP (fiscal year [FY] 2013) and for a measurement window that predated the FY 2013 measurement window for the HRRP among hospitals participating in the HRRP. Hospital characteristics are based on the 2012 survey by the American Hospital Association. The analysis included fee-for-service Medicare beneficiaries 65 years or older with an index hospitalization for 1 of the 3 target conditions of heart failure, acute myocardial infarction, or pneumonia or chronic obstructive pulmonary disease and who were discharged alive from February 1, 2006, through June 30, 2014, with follow-up completed by July 30, 2014. Data were analyzed from January 23, 2018, through March 29, 2019. EXPOSURES: Hospital Readmission Reduction Program penalties. MAIN OUTCOME AND MEASURES: The excess readmission ratio (ERR), calculated as the ratio of a hospital's readmissions to the readmissions that would be expected based on an average hospital with similar patients. Hospitals with ERRs of greater than 1.0 were penalized. RESULTS: A total of 3258 hospitals were included in the study. For the 3 target conditions, hospitals with ERRs of greater than 1.0 during the FY 2013 measurement window exhibited decreases in ERRs in the subsequent 3 years, whereas hospitals with ERRs of no greater than 1.0 exhibited increases. For example, for patients with heart failure, mean ERRs declined from 1.086 to 1.038 (-0.048; 95% CI, -0.053 to -0.043; P < .001) at hospitals with ERRs of greater than 1.0 and increased from 0.917 to 0.957 (0.040; 95% CI, 0.036-0.044; P < .001) at hospitals with ERRs of no greater than 1.0. The same results, with ERR changes of similar magnitude, were found when the analyses were repeated using an alternate measurement window that predated the HRRP and followed up hospitals for 3 years (for patients with heart failure, mean ERRs declined from 1.089 to 1.044 [-0.045; 95% CI, -0.050 to -0.040; P < .001] at hospitals with below-mean performance and increased from 0.915 to 0.948 [0.033; 95% CI, 0.029 to 0.037; P < .001] at hospitals with above-mean performance). By comparing actual changes in ERRs with expected changes due to RTM, 74.3% to 86.5% of the improvement in ERRs for penalized hospitals was explained by RTM. CONCLUSIONS AND RELEVANCE: Most of the decline in readmission rates in hospitals with high rates during the measurement window for the first year of the HRRP appeared to be due to RTM. These findings seem to call into question the notion of an HRRP policy effect on readmissions.