Trends in breast and prostate cancer screening and diagnostic procedures during the COVID-19 pandemic in central Massachusetts.

PURPOSE: We calculated rates of breast and prostate cancer screening and diagnostic procedures performed during the COVID-19 pandemic through December 2021 compared to the same months in 2019 in a large healthcare provider group in central Massachusetts. METHODS: We included active patients of the provider group between January 2019 and December 2021 aged 30-85 years. Monthly rates of screening mammography and digital breast tomosynthesis, breast MRI, total prostate specific antigen (PSA), and breast or prostate biopsy per 1,000 people were compared by year overall, by age, and race/ethnicity. Completed procedures were identified by relevant codes in electronic health record data. RESULTS: Rates of screening mammography, tomosynthesis, and PSA testing reached the lowest levels in April-May 2020. Breast cancer screening rates decreased 43% in March and 99% in April and May 2020, compared to 2019. Breast cancer screening rates increased gradually beginning in June 2020 through 2021, although more slowly in Black and Hispanic women and in women aged 75-85. PSA testing rates decreased 34% in March, 78% in April, and 53% in May 2020, but rebounded to pre-pandemic levels by June 2020; trends were similar across groups defined by age and race/ethnicity. CONCLUSION: The observed decline in two common screening procedures during the COVID-19 pandemic reflects the impact of the pandemic on cancer early detection and signals potential downstream effects on the prognosis of delayed cancer diagnoses. The slower rate of return for breast cancer screening procedures in certain subgroups should be investigated to ensure all women return for routine screenings.

Attitudes Toward a Potential SARS-CoV-2 Vaccine : A Survey of U.S. Adults.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has rapidly instigated a global pandemic. Vaccine development is proceeding at an unprecedented pace. Once available, it will be important to maximize vaccine uptake and coverage. OBJECTIVE: To assess intent to be vaccinated against COVID-19 among a representative sample of adults in the United States and identify predictors of and reasons for vaccine hesitancy. DESIGN: Cross-sectional survey, fielded from 16 through 20 April 2020. SETTING: Representative sample of adults residing in the United States. PARTICIPANTS: Approximately 1000 adults drawn from the AmeriSpeak probability-based research panel, covering approximately 97% of the U.S. household population. MEASUREMENTS: Intent to be vaccinated against COVID-19 was measured with the question, "When a vaccine for the coronavirus becomes available, will you get vaccinated?" Response options were "yes," "no," and "not sure." Participants who responded "no" or "not sure" were asked to provide a reason. RESULTS: A total of 991 AmeriSpeak panel members responded. Overall, 57.6% of participants (n = 571) intended to be vaccinated, 31.6% (n = 313) were not sure, and 10.8% (n = 107) did not intend to be vaccinated. Factors independently associated with vaccine hesitancy (a response of "no" or "not sure") included younger age, Black race, lower educational attainment, and not having received the influenza vaccine in the prior year. Reasons for vaccine hesitancy included vaccine-specific concerns, a need for more information, antivaccine attitudes or beliefs, and a lack of trust. LIMITATIONS: Participants' intent to be vaccinated was explored before a vaccine was available and when the pandemic was affecting a narrower swath of the United States. Questions about specific information or factors that might increase vaccination acceptance were not included. The survey response rate was 16.1%. CONCLUSION: This national survey, conducted during the coronavirus pandemic, revealed that approximately 3 in 10 adults were not sure they would accept vaccination and 1 in 10 did not intend to be vaccinated against COVID-19. Targeted and multipronged efforts will be needed to increase acceptance of a COVID-19 vaccine when one becomes available. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality.

Prostate-specific antigen testing after the US Preventive Services Task Force recommendation: a population-based analysis of electronic health data.

PURPOSE: This study describes longitudinal trends in the use of prostate-specific antigen (PSA)-based testing in two geographically distinct healthcare systems following the 2011 US Preventive Services Task Force (USPSTF) recommendations against routine PSA screening. METHODS: We analyzed population-based health claims data from 253,139 men aged 40-80 who were enrolled at two US healthcare systems. We assessed trends in the percentage of eligible men receiving ≥ 1 PSA test per year by time period (2000-2008, 2009-2011, 2012-2014), age (40-54, 55-69, 70-80), and race (white, black, other, unknown), and conducted a joinpoint regression analysis. RESULTS: Men aged 55-69 and 70-80 years of all races had similar use of PSA testing between 2000 and 2011, ranging between 47 and 56% of eligible men by year, while only 22-26% of men aged 40-54 had a PSA test per year during this period. Overall, the percentage of men receiving at least one PSA test per year decreased by 26% between 2009-2011 and 2012-2014, with similar trends across race and age groups. PSA testing declined significantly after 2011 (annual percent change = - 11.28). CONCLUSIONS: Following the 2011 USPSTF recommendations against routine PSA screening, declines in PSA testing were observed among men of all races and across all age groups in two large US healthcare systems.

Primary Care Providers' Opening of Time-Sensitive Alerts Sent to Commercial Electronic Health Record InBaskets.

BACKGROUND: Time-sensitive alerts are among the many types of clinical notifications delivered to physicians' secure InBaskets within commercial electronic health records (EHRs). A delayed alert review can impact patient safety and compromise care. OBJECTIVE: To characterize factors associated with opening of non-interruptive time-sensitive alerts delivered into primary care provider (PCP) InBaskets. DESIGN AND PARTICIPANTS: We analyzed data for 799 automated alerts. Alerts highlighted actionable medication concerns for older patients post-hospital discharge (2010-2011). These were study-generated alerts sent 3 days post-discharge to InBaskets for 75 PCPs across a multisite healthcare system, and represent a subset of all urgent InBasket notifications. MAIN MEASURES: Using EHR access and audit logs to track alert opening, we performed bivariate and multivariate analyses calculating associations between patient characteristics, provider characteristics, contextual factors at the time of alert delivery (number of InBasket notifications, weekday), and alert opening within 24 h. KEY RESULTS: At the time of alert delivery, the PCPs had a median of 69 InBasket notifications and had received a median of 379.8 notifications (IQR 295.0, 492.0) over the prior 7 days. Of the 799 alerts, 47.1% were opened within 24 h. Patients with longer hospital stays (>4 days) were marginally more likely to have alerts opened (OR 1.48 [95% CI 1.00-2.19]). Alerts delivered to PCPs whose InBaskets had a higher number of notifications at the time of alert delivery were significantly less likely to be opened within 24 h (top quartile >157 notifications: OR 0.34 [95% CI 0.18-0.61]; reference bottom quartile ≤42). Alerts delivered on Saturdays were also less likely to be opened within 24 h (OR 0.18 [CI 0.08-0.39]). CONCLUSIONS: The number of total InBasket notifications and weekend delivery may impact the opening of time-sensitive EHR alerts. Further study is needed to support safe and effective approaches to care team management of InBasket notifications.

Did Medicare Part D Affect National Trends in Health Outcomes or Hospitalizations? A Time-Series Analysis.

BACKGROUND: Medicare Part D increased economic access to medications, but its effect on population-level health outcomes and use of other medical services remains unclear. OBJECTIVE: To examine changes in health outcomes and medical services in the Medicare population after implementation of Part D. DESIGN: Population-level longitudinal time-series analysis with generalized linear models. SETTING: Community. PATIENTS: Nationally representative sample of Medicare beneficiaries (n = 56,293 [unweighted and unique]) from 2000 to 2010. MEASUREMENTS: Changes in self-reported health status, limitations in activities of daily living (ADLs) (ADLs and instrumental ADLs), emergency department visits and hospital admissions (prevalence, counts, and spending), and mortality. Medicare claims data were used for confirmatory analyses. RESULTS: Five years after Part D implementation, no clinically or statistically significant reductions in the prevalence of fair or poor health status or limitations in ADLs or instrumental ADLs, relative to historical trends, were detected. Compared with trends before Part D, no changes in emergency department visits, hospital admissions or days, inpatient costs, or mortality after Part D were seen. Confirmatory analyses were consistent. LIMITATIONS: Only total population-level outcomes were studied. Self-reported measures may lack sensitivity. CONCLUSION: Five years after implementation, and contrary to previous reports, no evidence was found of Part D's effect on a range of population-level health indicators among Medicare enrollees. Further, there was no clear evidence of gains in medical care efficiencies.

Impact of a physician recommendation on COVID-19 vaccination intent among vaccine hesitant individuals.

OBJECTIVE: To test the impact of varied physician recommendations on COVID-19 vaccine hesitancy. METHODS: We conducted a vignette-based experimental survey on Prolific, an online research platform. COVID-19 vaccine hesitant, adult panel members were assigned to one of five messages that varied by recommendation style (participatory vs explicit) and strategy (acknowledgement of concerns; comparison to the flu shot; statement that millions of people have already received it; emphasis on protecting others). Vaccine hesitancy was re-assessed with the question, "Would you get vaccinated at this visit?". RESULTS: Of the 752 participants, 60.1% were female, 43.4% Black, 23.6% Latino, and 33.0% White; mean age was 35.6 years. Overall, 33.1% of the initially "not sure" and 13.1% of the initially "no" participants became less hesitant following any recommendation. Among the "not sure" participants, 20.3% of those who received a participatory recommendation became less hesitant compared with 34.3%- 39.5% for the explicit recommendations. The "protect others" message was most effective among initially "no" participants; 19.8% become less hesitant, compared to 8.7% for the participatory recommendation. CONCLUSION: A physician recommendation may reduce COVID-19 vaccine hesitancy. PRACTICE IMPLICATIONS: An explicit recommendation and "protect others" message appear to be important elements of a physician recommendation for COVID-19 vaccination.

From COVID-19 Vaccine Hesitancy to Vaccine Acceptance: Results of a Longitudinal Survey.

OBJECTIVES: COVID-19 vaccines are widely available, but uptake is suboptimal. To develop strategies to increase vaccination rates, we sought to (1) characterize adults initially hesitant to be vaccinated for COVID-19 who later received the vaccine and (2) identify factors associated with their vaccination decision. METHODS: In January 2021, we conducted an online survey of US adults via Prolific that assessed vaccination intent, COVID-19-related knowledge and attitudes, and demographic characteristics. In May 2021, we recontacted respondents to assess vaccination status and factors influencing their vaccination decision. We used χ2 statistics and t tests to examine associations between respondents' vaccination status and their characteristics, knowledge, and attitudes. We analyzed reasons for vaccination using thematic analysis. RESULTS: Of 756 initially vaccine-hesitant respondents, 529 (70.0%) completed the follow-up survey. Nearly half of those initially not sure about vaccination (47.3%, 112 of 237) were vaccinated at follow-up, while 21.2% (62 of 292) of those initially planning not to be vaccinated were vaccinated at follow-up. Of those initially not sure, higher educational attainment, greater knowledge of COVID-19, and a doctor's recommendation were associated with vaccination. Of those initially intending not to be vaccinated, male sex, Democratic political affiliation, receipt of an influenza shot within 5 years, being more worried about COVID-19, and having greater COVID-19 knowledge were associated with increased likelihood of being vaccinated. Of 167 respondents who gave reasons for vaccination, protecting oneself and others (59.9%), practical issues (29.9%), social influences (17.4%), and vaccine safety (13.8%) were the main reasons. CONCLUSION: Providing information on the protective value of vaccination, implementing rules that make remaining unvaccinated burdensome, making vaccination easy, and providing social support may influence vaccine-hesitant adults to accept vaccination.

High-frequency hospital users: The tail that wags the readmissions dog.

OBJECTIVE: To describe the characteristics of high-frequency hospital users (four or more hospitalizations in a year) and the consequences of including or excluding their data from a readmission-based measure. DATA SOURCES: 2015 and 2016 Massachusetts Medicaid data. STUDY DESIGN: We compare demographics, morbidity burden, and social risk factors for high- and low-frequency hospital users, and membership in 17 accountable care organizations. We evaluate how excluding hospitalizations of high-frequency users from a 30-day readmission measure (with or without risk adjustment) changes its rate and variability and affects performance rankings of accountable care organizations. The outcome is readmission within 30 days; each live discharge from a hospital contributes one observation. DATA COLLECTION/EXTRACTION METHODS: We studied 74 706 hospitalizations of 42 794 MassHealth members, 18-64 years old, managed-care-eligible, and ever hospitalized in 2016. PRINCIPAL FINDINGS: Among adult managed-care-eligible MassHealth members with at least one acute hospitalization, 8.7% were high-frequency hospital users; they contributed 30.2% of hospitalizations and 69.4% of readmissions. High-frequency users were more often male (77.1% vs. 50.0%; P < 0.001) and sicker (mean medical morbidity score was 3.3 vs. 1.9; P < 0.001) than others. They also had significant social risks: 33.1% with housing problems, 44.1% disabled, 83.2% with serious mental illness, and 77.1% with substance abuse disorder (vs. 22.0%, 27.3%, 60.2%, and 50.0%, respectively, for other hospital users [all P values <0.001]). Fully 50.7% of hospitalizations for high-frequency users led to 30-day readmissions (vs. 9.7%), contributing 72.0% of the variance in 30-day readmission, and substantially affecting judgments about the relative performance of accountable care organizations. CONCLUSIONS: A small group of high-frequency hospital users have a disproportionate effect on 30-day readmission rates. This negatively affects some Medicaid ACOs, and more broadly is likely to adversely affect safety net hospitals. How these metrics are used should be reconsidered in this context.

Adherence with tobramycin inhaled solution and health care utilization.

BACKGROUND: Adherence with tobramycin inhalation solution (TIS) during routine cystic fibrosis (CF) care may differ from recommended guidelines and affect health care utilization. METHODS: We analyzed 2001-2006 healthcare claims data from 45 large employers. Study subjects had diagnoses of CF and at least 1 prescription for TIS. We measured adherence as the number of TIS therapy cycles completed during the year and categorized overall adherence as: low ≤ 2 cycles, medium >2 to <4 cycles, and high ≥ 4 cycles per year. Interquartile ranges (IQR) were created for health care utilization and logistic regression analysis of hospitalization risk was conducted by TIS adherence categories. RESULTS: Among 804 individuals identified with CF and a prescription for TIS, only 7% (n = 54) received ≥ 4 cycles of TIS per year. High adherence with TIS was associated with a decreased risk of hospitalization when compared to individuals receiving ≤ 2 cycles (adjusted odds ratio 0.40; 95% confidence interval 0.19-0.84). High adherence with TIS was also associated with lower outpatient service costs (IQR: $2,159-$8444 vs. $2,410-$14,423) and higher outpatient prescription drug costs (IQR: $35,125-$60,969 vs. $10,353-$46,768). CONCLUSIONS: Use of TIS did not reflect recommended guidelines and may impact other health care utilization.

Preferences for COVID-19 vaccination information and location: Associations with vaccine hesitancy, race and ethnicity.

This study examined the association between preferences for being informed about the COVID-19 vaccine and where to receive it with vaccination intent and race/ethnicity. We conducted an online survey, oversampling Black and Latino panel members. The 1668 participants were 53.2% female, 34.8% White, 33.3% Black, and 31.8% Latino. Participants who were vaccine hesitant (answered "not sure" or "no" to vaccination intent) were more likely to prefer a conversation with their doctor compared to those who answered "yes" (25.0% and 23.4% vs 7.8%, P < .001, respectively). Among participants who responded "not sure", 61.8% prefer to be vaccinated at a doctor's office, compared with 35.2% of those who responded "yes" (P < .001). Preferred location differed by race/ethnicity (P < .001) with 67.6% of Black "not sure" participants preferring a doctor's office compared to 60.2% of Latino and 54.9% of White "not sure" participants. These findings underscore the need to integrate healthcare providers into COVID-19 vaccination programs.

The Association of Nursing Home Characteristics and Quality with Adverse Events After a Hospitalization.

BACKGROUND/OBJECTIVES: We previously found high rates of adverse events (AEs) for long-stay nursing home residents who return to the facility after a hospitalization. Further evidence about the association of AEs with aspects of the facilities and their quality may support quality improvement efforts directed at reducing risk. DESIGN: Prospective cohort analysis. SETTING AND PARTICIPANTS: 32 nursing homes in the New England states. A total of 555 long-stay residents contributed 762 returns from hospitalizations. METHODS: We measured the association between AEs developing in the 45 days following discharge back to long-term care and characteristics of the nursing homes including bed size, ownership, 5-star quality ratings, registered nurse and nursing assistant hours, and the individual Centers for Medicare & Medicaid Services (CMS) quality indicators. We constructed Cox proportional hazards models controlling for individual resident characteristics that were previously found associated with AEs. RESULTS: We found no association of AEs with most nursing home characteristics, including 5-star quality ratings and the composite quality score. Associations with individual quality indicators were inconsistent and frequently not monotonic. Several individual quality indicators were associated with AEs; the highest tertile of percentage of residents with depression (4%-25%) had a hazard ratio (HR) of 1.65 [95% confidence interval (CI) 1.16, 2.35] and the highest tertile of the percentage taking antipsychotic medications (18%-35%) had an HR of 1.58 (CI 1.13, 2.21). The percentage of residents needing increased assistance with activities of daily living was statistically significant but not monotonic; the middle tertile (13% to <20%) had an HR of 1.69 (CI 1.16, 2.47). CONCLUSIONS AND IMPLICATIONS: AEs occurring during transitions between nursing homes and hospitals are not explained by the characteristics of the facilities or summary quality scores. Development of risk reduction approaches requires assessment of processes and quality beyond the current quality measures.

Out-of-pocket burden of health care spending and the adequacy of the Medicare Part D low-income subsidy.

BACKGROUND: Evaluating the adequacy of Medicare prescription drug program (Part D) and its low-income subsidy (LIS) requires a comprehensive understanding of drug spending in relation to household resources. OBJECTIVE: : To estimate out-of-pocket health care costs in the year before Part D, in context of total household spending, health status, and LIS eligibility. RESEARCH DESIGN: Nationally representative cross-sectional study. SUBJECTS: Two thousand two hundred thirty-one Medicare families in the 2005/2006 Health and Retirement Study. METHODS: We assessed health care costs as a share of household resources remaining after spending on essential housing, food, personal care, and transportation. Burdensome health care costs were defined as exceeding 40% of nonessential resources. We used logistic regressions to assess the probability of incurring burdensome health expenditures, controlling for LIS eligibility. RESULTS: In the year before Part D, more than half of Medicare families [56.0%; 95% confidence interval (CI): 55.3-59.9] experienced burdensome health care costs. Families in poor health allocated a median of 68.1% [interquartile range (IQR): 35.1-82.9] of nonessential resources to health care (compared with 34.0% median; IQR 11.9-52.2 among families in excellent health, P < 0.011). Most (64%) out-of-pocket health care spending was allocated to health insurance premiums and medications. As many as 26% of Medicare families had burdensome health care costs but were not eligible for LIS assistance. CONCLUSIONS: Before Part D, burdensome health care expenditures were common in Medicare families. Our estimates of Part D and LIS benefits indicate a limited scope of relief.

Adherence and occurrence of fractures after switching to once-monthly oral bisphophonates.

PURPOSE: Reducing dosing demands of medications generally increases adherence, although this relationship has not been demonstrated with the once-monthly oral bisphosphonates (BP). The study aim is to test whether switching from once-weekly BPs to once-monthly BPs improves adherence and fracture risk. METHODS: This is an interrupted times-series analysis of new users of once-weekly BPs in a nationwide administrative health database from 2003 to 2007. Participants include 1835 individuals who switched to once-monthly BPs and two propensity-matched comparator groups: 1835 individuals who switched to a different once-weekly BP, and 1835 who did not switch. We measured changes in adequate adherence pre- and post-switch as monthly medication possession ratio >0.80, and calculated incidence rate ratios (IRR) of osteoporotic fractures. RESULTS: All study groups experienced major adherence failure in the first year of therapy: the proportion of adequate adherers was 42% among once-monthly switchers, 47% among once-weekly switchers, and 37% among nonswitchers. However, the once-monthly switch was associated with less adherence failure (4% fewer adherers per month pre-switch vs. 1% fewer adherers per month post-switch, p<0.000). There was no statistically significant change in adherence rates for the other groups. We did not detect significantly reduced fracture risk with once-monthly switch: 1 year post-switch, the fracture incidence risk ratios for once-monthly switchers relative to once-weekly switchers were IRR 0.83, 95% CI: 0.50-1.36, and IRR 0.90, 95% CI: 0.54-1.49, relative to nonswitchers). CONCLUSIONS: Reducing the dosing demands of oral bisphosphonates from once-weekly to once-monthly decreased adherence failure but had an uncertain impact on fracture risk.

A cardiovascular disease risk prediction algorithm for use with the Medicare current beneficiary survey.

OBJECTIVE: To develop a cardiovascular disease (CVD) risk score that can be used to quantify CVD risk in the Medicare Current Beneficiary Survey (MCBS). DATA SOURCES: We used 1999-2013 MCBS data. STUDY DESIGN: We used a backward stepwise approach and cox proportional hazards regressions to build and validate a new CVD risk score, similar to the Framingham Risk Score (FRS), using only information available in MCBS. To assess its performance, we calculated C statistics and examined calibration plots. DATA COLLECTION/EXTRACTION METHODS: We studied 21 968 community-dwelling Medicare beneficiaries aged 65 years or older without pre-existing CVD. We obtained risk factors from both survey and claims data. We used claims data to derive "CVD event within 3 years" following the FRS definition of CVD. PRINCIPAL FINDINGS: About five percent of MCBS participants developed a CVD event over a mean follow-up period of 348 days. Our final MCBS-based model added morbidity burden, reported general health status, and functional limitation to the traditional FRS predictors of CVD. This model had relatively fair discrimination (C statistic = 0.69; 95% confidence interval [CI], 0.67-0.71) and performed well on validation (C = 0.68; CI, 0.66-0.70). More importantly, the plot of observed CVD outcomes versus predicted ones showed that this model had a good calibration. CONCLUSIONS: Our new CVD risk score can be calculated using MCBS data, thereby extending the survey's ability to quantify CVD risk in the Medicare population and better inform both health policy and health services research.

Characteristics of Long-Term Care Residents That Predict Adverse Events after Hospitalization.

BACKGROUND/OBJECTIVES: Adverse events (AEs) occur frequently in long-term care (LTC) residents transitioning from the hospital back to an LTC facility. Measuring the association between resident characteristics and AEs can inform AE risk reduction strategies. DESIGN: Prospective cohort analysis. SETTING: A total of 32 nursing homes from six New England states. PARTICIPANTS: A total of 555 LTC residents contributing 762 transitions from the hospital back to LTC. MEASUREMENTS: We measured the association between all AEs and preventable AEs developing in the 45 days following discharge back to LTC and demographic variables, hospital length of stay (LOS), Charlson Comorbidity Index (CCI) (0-1, 2-3, 4-5 and ≥6), dependency in activities of daily living (ADLs) using the Minimum Data Set Long Form Scale (in quintiles 0-12, 13-15, 16, 17-18, and ≥19), and number of regularly scheduled medications (0-9, 10-13, 14-17, and ≥18). To understand the independent association of each resident characteristic with AEs and preventable AEs, we constructed multiple Cox proportional hazards models. RESULTS: There were 283 discharges with one or more AEs and 212 with preventable AEs. Characteristics independently associated with higher risk of an AE included hospital LOS 9 or more days (hazard ratio [HR] = 1.49; 95% confidence interval [CI] = 1.02-2.17); CCI of 4 to 5 (HR = 1.74; 95% CI = 1.13-2.67) or 6 or higher (HR = 1.58; 95% CI = 1.01-2.46); 18 or more regularly scheduled medications (HR = 1.53; 95% CI = 1.07-2.18); and 19 and above on ADL dependency (HR = 1.78; 95% CI = 1.21-2.62). Results from models with preventable AEs were similar to those with all AEs. CONCLUSION: Increased LOS, higher comorbidity burden, greater dependency in ADLs, and polypharmacy were the resident characteristics most strongly associated with risk of AEs and preventable AEs. We recommend heightened vigilance in the care of LTC residents with these characteristics transitioning back to LTC. We also recommend research to assess strategies to reduce the risk of AEs.

Noncardiac-Related Morbidity, Mobility Limitation, and Outcomes in Older Adults With Heart Failure.

BACKGROUND: To examine the individual and combined associations of noncardiac-related conditions and mobility limitation with morbidity and mortality in adults with heart failure (HF). METHODS: We conducted a retrospective cohort study in a large, diverse group of adults with HF from five U.S. integrated healthcare delivery systems. We characterized patients with respect to the presence of noncardiac conditions (<3 vs ≥3) and/or mobility impairment (defined by the use/nonuse of a wheelchair, cane, or walker), categorizing them into four subgroups. Outcomes included all-cause death and hospitalizations for HF or any cause. RESULTS: Among 114,553 adults diagnosed with HF (mean age: 73 years old, 46% women), compared with <3 noncardiac conditions/no mobility limitation, adjusted hazard ratios (HR) for all-cause death among those with <3 noncardiac conditions/mobility limitation, ≥3 noncardiac conditions/no mobility limitation, ≥3 noncardiac conditions/mobility limitation (vs) were 1.40 (95% CI, 1.31-1.51), 1.72 (95% CI, 1.69-1.75), and 1.93 (95% CI, 1.85-2.01), respectively. We did not observe an increased risk of any-cause or HF-related hospitalization related to the presence of mobility limitation among those with a greater burden of noncardiac multimorbidity. Consistent findings regarding mortality were observed within groups defined according to age, gender, and HF type (preserved, reduced, mid-range ejection fraction), with the most prominent impact of mobility limitation in those <65 years of age. CONCLUSIONS: There is an additive association of mobility limitation, beyond the burden of noncardiac multimorbidity, on mortality for patients with HF, and especially prominent in younger patients.

Adverse Events in Long-term Care Residents Transitioning From Hospital Back to Nursing Home.

IMPORTANCE: Transition from hospital to nursing home is a high-risk period for adverse events in long-term care (LTC) residents. Adverse events include harms from medical care, including failure to provide appropriate care. OBJECTIVE: To report the incidence, type, severity, and preventability of adverse events in LTC residents transitioning from hospital back to the same LTC facility. DESIGN, SETTING, AND PARTICIPANTS: Prospective cohort study of LTC residents discharged from hospital back to LTC from March 1, 2016, to December 31, 2017, and followed up for 45 days. In a random sample of 32 nursing homes located in 6 New England states, 555 LTC residents were selected, contributing 762 transitions from hospital back to the same LTC facility. MAIN OUTCOMES AND MEASURES: The main outcome was an adverse event within the 45-day period after transition from hospital back to nursing home. Trained nurse abstractors reviewed nursing home records for the period, and then 2 physicians independently reviewed each potential adverse event to determine whether harm occurred and to characterize the type, severity, and preventability of each event. When reviewers disagreed, they met to reach consensus. RESULTS: Of the 555 individual residents, 365 (65.6%) were female, and the mean (SD) age at the time of discharge was 82.2 (11.5) years. Five hundred twenty (93.7%) were non-Hispanic white, 21 (3.8%) were non-Hispanic black, 9 (1.6%) were Hispanic, and 5 (0.9%) were of other non-Hispanic race/ethnicity. In the cohort, there were 379 adverse events among 762 discharges. One hundred ninety-seven events (52.0%) related to resident care, with pressure ulcers, skin tears, and falls with injury representing the most common types of events in this category. Health care-acquired infections (108 [28.5%]) and adverse drug events (64 [16.9%]) were the next most common. One hundred ninety-eight (52.2%) adverse events were characterized as less serious. However, 145 (38.3%) events were deemed serious, 28 (7.4%) life-threatening, and 8 (2.1%) fatal. In terms of preventability, 267 (70.4%) adverse events were found to be preventable or ameliorable, with less serious events more often considered preventable or ameliorable (146 [73.7%]) compared with more severe events (121 [66.9%]). In addition, resident care-related adverse events such as fall with injury, skin tear, and pressure ulcer were more commonly deemed preventable (173 of 197 [87.8%]) compared with adverse drug events (39 of 64 [60.9%]) or health care-acquired infections (49 of 108 [45.4%]). CONCLUSIONS AND RELEVANCE: Adverse events developed in nearly 4 of 10 of discharges from hospital back to LTC. Most were preventable or ameliorable. Standardized reporting of events and better coordination and information transfer across settings are potential ways to prevent adverse events in LTC residents.

Use of Electronic Health Record Access and Audit Logs to Identify Physician Actions Following Noninterruptive Alert Opening: Descriptive Study.

BACKGROUND: Electronic health record (EHR) access and audit logs record behaviors of providers as they navigate the EHR. These data can be used to better understand provider responses to EHR-based clinical decision support (CDS), shedding light on whether and why CDS is effective. OBJECTIVE: This study aimed to determine the feasibility of using EHR access and audit logs to track primary care physicians' (PCPs') opening of and response to noninterruptive alerts delivered to EHR InBaskets. METHODS: We conducted a descriptive study to assess the use of EHR log data to track provider behavior. We analyzed data recorded following opening of 799 noninterruptive alerts sent to 75 PCPs' InBaskets through a prior randomized controlled trial. Three types of alerts highlighted new medication concerns for older patients' posthospital discharge: information only (n=593), medication recommendations (n=37), and test recommendations (n=169). We sought log data to identify the person opening the alert and the timing and type of PCPs' follow-up EHR actions (immediate vs by the end of the following day). We performed multivariate analyses examining associations between alert type, patient characteristics, provider characteristics, and contextual factors and likelihood of immediate or subsequent PCP action (general, medication-specific, or laboratory-specific actions). We describe challenges and strategies for log data use. RESULTS: We successfully identified the required data in EHR access and audit logs. More than three-quarters of alerts (78.5%, 627/799) were opened by the PCP to whom they were directed, allowing us to assess immediate PCP action; of these, 208 alerts were followed by immediate action. Expanding on our analyses to include alerts opened by staff or covering physicians, we found that an additional 330 of the 799 alerts demonstrated PCP action by the end of the following day. The remaining 261 alerts showed no PCP action. Compared to information-only alerts, the odds ratio (OR) of immediate action was 4.03 (95% CI 1.67-9.72) for medication-recommendation and 2.14 (95% CI 1.38-3.32) for test-recommendation alerts. Compared to information-only alerts, ORs of medication-specific action by end of the following day were significantly greater for medication recommendations (5.59; 95% CI 2.42-12.94) and test recommendations (1.71; 95% CI 1.09-2.68). We found a similar pattern for OR of laboratory-specific action. We encountered 2 main challenges: (1) Capturing a historical snapshot of EHR status (number of InBasket messages at time of alert delivery) required incorporation of data generated many months prior with longitudinal follow-up. (2) Accurately interpreting data elements required iterative work by a physician/data manager team taking action within the EHR and then examining audit logs to identify corresponding documentation. CONCLUSIONS: EHR log data could inform future efforts and provide valuable information during development and refinement of CDS interventions. To address challenges, use of these data should be planned before implementing an EHR-based study.

Diagnostic Algorithms for Cardiovascular Death in Administrative Claims Databases: A Systematic Review.

INTRODUCTION: Valid algorithms for identification of cardiovascular (CV) deaths allow researchers to reliably assess the CV safety of medications, which is of importance to regulatory science, patient safety, and public health. OBJECTIVE: The aim was to conduct a systematic review of algorithms to identify CV death in administrative health plan claims databases. METHODS: We searched MEDLINE, EMBASE, and Cochrane Library for English-language studies published between January 1, 2012 and October 17, 2017. We examined references in systematic reviews to identify earlier studies. Selection included any observational study using electronic health care data to evaluate the sensitivity, specificity, positive predictive value (PPV), or negative predictive value (NPV) of algorithms for CV death (sudden cardiac death [SCD], myocardial infarction [MI]-related death, or stroke-related death) among adults aged ≥ 18 years in the United States. Data were extracted by two independent reviewers, with disagreements resolved through further discussion and consensus. The Quality Assessment of Diagnostic Accuracy Studies-2 instrument was used to assess the risk of bias. RESULTS: Five studies (n = 4 on SCD, n = 1 on MI- and stroke-related death) were included after a review of 2053 citations. All studies reported algorithm PPVs, with incomplete reporting on other accuracy parameters. One study was at low risk of bias, three studies were at moderate risk of bias, and one study was at unclear risk of bias. Two studies identified community-occurring SCD: one identified events using International Classification of Disease, Ninth Revision (ICD-9) codes on death certificates and other criteria from medical claims (PPV = 86.8%) and the other identified events resulting in hospital presentation using first-listed ICD-9 codes on emergency department or inpatient medical claims (PPV = 92.3%). Two studies used death certificates alone to identify SCD (PPV = 27% and 32%, respectively). One study used medical claims to identify CV death (PPV = 36.4%), coronary heart disease mortality (PPV = 28.3%), and stroke mortality (PPV = 34.5%). CONCLUSION: Two existing algorithms based on medical claims diagnoses with or without death certificates can accurately identify SCD to support pharmacoepidemiologic studies. Developing valid algorithms identifying MI- and stroke-related death should be a research priority. PROSPERO 2017 CRD42017078745.

Comparison of drug adherence rates among patients with seven different medical conditions.

STUDY OBJECTIVE: To compare drug adherence rates among patients with gout, hypercholesterolemia, hypertension, hypothyroidism, osteoporosis, seizure disorders, and type 2 diabetes mellitus by using a standardized approach. DESIGN: Longitudinal study. DATA SOURCE: Health care claims data from 2001-2004. PATIENTS: A total of 706,032 adults aged 18 years or older with at least one of the seven medical conditions and with incident use of drug therapy for that condition. MEASUREMENTS AND MAIN RESULTS: Drug adherence was measured as the sum of the days' supply of drug therapy over the first year observed. Covariates were age, sex, geographic residence, type of health plan, and a comorbidity score calculated by using the Hierarchical Condition Categories risk adjuster. Bivariate statistics and stratification analyses were used to assess unadjusted means and frequency distributions. Sample sizes ranged from 4984 subjects for seizure disorders to 457,395 for hypertension. During the first year of drug therapy, 72.3% of individuals with hypertension achieved adherence rates of 80% or better compared with 68.4%, 65.4%, 60.8%, 54.6%, 51.2%, or 36.8% for those with hypothyroidism, type 2 diabetes, seizure disorders, hypercholesterolemia, osteoporosis, or gout, respectively. Age younger than 60 years was associated with lower adherence across all diseases except seizure disorders. Comorbidity burden and adherence varied by disease. As comorbidity increased, adherence among subjects with osteoporosis decreased, whereas adherence among those with hypertension, hypercholesterolemia, or gout increased. Add-on drug therapies and previous experience with taking drugs for the condition increased adherence among subjects with hypertension, type 2 diabetes, hypothyroidism, or seizure disorders but not the other conditions. CONCLUSION: This uniform comparison of drug adherence revealed modest variation across six of seven diseases, with the outlier condition being gout.