One-Year Recovery Among Survivors of Prolonged Severe COVID-19: A National Multicenter Cohort

OBJECTIVES

Understanding the long-term effects of severe COVID-19 illness on survivors is essential for effective pandemic recovery planning. Therefore, we investigated impairments among hospitalized adults discharged to long-term acute care hospitals (LTACHs) for prolonged severe COVID-19 illness who survived 1 year.

DESIGN

The Recovery After Transfer to an LTACH for COVID-19 (RAFT COVID) study was a national, multicenter, prospective longitudinal cohort study.

SETTING AND PATIENTS

We included hospitalized English-speaking adults transferred to one of nine LTACHs in the United States between March 2020 and February 2021 and completed a survey.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Validated instruments for impairments and free response questions about recovering. Among 282 potentially eligible participants who provided permission to be contacted, 156 (55.3%) participated (median age, 65; 38.5% female; 61.3% in good prior health; median length of stay of 57 d; 77% mechanically ventilated for a median of 26 d; 42% had a tracheostomy). Approximately two-thirds (64%) had a persistent impairment, including physical (57%), respiratory (49%; 19% on supplemental oxygen), psychiatric (24%), and cognitive impairments (15%). Nearly half (47%) had two or more impairment types. Participants also experienced persistent debility from hospital-acquired complications, including mononeuropathies and pressure ulcers. Participants described protracted recovery, attributing improvements to exercise/rehabilitation, support, and time. While considered life-altering with 78.7% not returning to their usual health, participants expressed gratitude for recovering; 99% returned home and 60% of previously employed individuals returned to work.

CONCLUSIONS

Nearly two-thirds of survivors of among the most prolonged severe COVID-19 illness had persistent impairments at 1 year that resembled post-intensive care syndrome after critical illness plus debility from hospital-acquired complications.

Patient and Staff Perspectives on the Impacts and Challenges of Hospital-Based Harm Reduction

Importance

Harm reduction is associated with improved health outcomes among people who use substances. As overdose deaths persist, hospitals are recognizing the need for harm reduction services; however, little is known about the outcomes of hospital-based harm reduction for patients and staff.

Objective

To evaluate patient and staff perspectives on the impact and challenges of a hospital-based harm reduction program offering safer use education and supplies at discharge.

Design, Setting, and Participants

This qualitative study consisted of 40-minute semistructured interviews with hospitalized patients receiving harm reduction services and hospital staff at an urban, safety-net hospital in California from October 2022 to March 2023. Purposive sampling allowed inclusion of diverse patient racial and ethnic identities, substance use disorders (SUDs), and staff roles.

Exposure

Receipt of harm reduction education and/or supplies (eg, syringes, pipes, naloxone, and test strips) from an addiction consult team, or providing care for patients receiving these services.

Main Outcomes and Measures

Interviews were analyzed using thematic analysis to identify key themes.

Results

A total of 40 participants completed interviews, including 20 patients (mean [SD] age, 43 [13] years; 1 American Indian or Alaska Native [5%], 1 Asian and Pacific Islander [5%], 6 Black [30%]; 6 Latine [30%]; and 6 White [30%]) and 20 staff (mean [SD] age 37 [8] years). Patients were diagnosed with a variety of SUDs (7 patients with opioid and stimulant use disorder [35%]; 7 patients with stimulant use disorder [35%]; 3 patients with opioid use disorder [15%]; and 3 patients with alcohol use disorder [15%]). A total of 3 themes were identified; respondents reported that harm reduction programs (1) expanded access to harm reduction education and supplies, particularly for ethnically and racially minoritized populations; (2) built trust by improving the patient care experience and increasing engagement; and (3) catalyzed culture change by helping destigmatize care for individuals who planned to continue using substances and increasing staff fulfillment. Black and Latine patients, those who primarily used stimulants, and those with limited English proficiency (LEP) reported learning new harm reduction strategies. Program challenges included hesitancy regarding regulations, limited SUD education among staff, remaining stigma, and the need for careful assessment of patient goals.

Conclusions and Relevance

In this qualitative study, patients and staff believed that integrating harm reduction services into hospital care increased access for populations unfamiliar with harm reduction, improved trust, and reduced stigma. These findings suggest that efforts to increase access to harm reduction services for Black, Latine, and LEP populations, including those who use stimulants, are especially needed.

Multilevel Determinants of Digital Health Equity: A Literature Synthesis to Advance the Field

Current digital health approaches have not engaged diverse end users or reduced health or health care inequities, despite their promise to deliver more tailored and personalized support to individuals at the right time and the right place. To achieve digital health equity, we must refocus our attention on the current state of digital health uptake and use across the policy, system, community, individual, and intervention levels. We focus here on (a) outlining a multilevel framework underlying digital health equity; (b) summarizingfive types of interventions/programs (with example studies) that hold promise for advancing digital health equity; and (c) recommending future steps for improving policy, practice, and research in this space.

National Prevalence of Alcohol and Other Substance Use Disorders Among Emergency Department Visits and Hospitalizations: NHAMCS 2014-2018

BACKGROUND

Acute healthcare utilization attributed to alcohol use disorders (AUD) and other substance use disorders (SUD) is rising.

OBJECTIVE

To describe the prevalence and characteristics of emergency department (ED) visits and hospitalizations made by adults with AUD or SUD.

DESIGN, SETTING, AND PARTICIPANTS

Observational study with retrospective analysis of the National Hospital Ambulatory Medical Care Survey (2014 to 2018), a nationally representative survey of acute care visits with information on the presence of AUD or SUD abstracted from the medical chart.

MAIN MEASURES

Outcome measured as the presence of AUD or SUD.

KEY RESULTS

From 2014 to 2018, the annual average prevalence of AUD or SUD was 9.4% of ED visits (9.3 million visits) and 11.9% hospitalizations (1.4 million hospitalizations). Both estimates increased over time (30% and 57% relative increase for ED visits and hospitalizations, respectively, from 2014 to 2018). ED visits and hospitalizations from individuals with AUD or SUD, compared to individuals with neither AUD nor SUD, had higher percentages of Medicaid insurance (ED visits: AUD: 33.1%, SUD: 35.0%, neither: 24.4%; hospitalizations: AUD: 30.7%, SUD: 36.3%, neither: 14.8%); homelessness (ED visits: AUD: 6.2%, SUD 4.4%, neither 0.4%; hospitalizations: AUD: 5.9%, SUD 7.3%, neither: 0.4%); coexisting depression (ED visits: AUD: 26.3%, SUD 24.7%, neither 10.5%; hospitalizations: AUD: 33.5%, SUD 35.3%, neither: 13.9%); and injury/trauma (ED visits: AUD: 51.3%, SUD 36.3%, neither: 26.4%; hospitalizations: AUD: 31.8%, SUD: 23.8%, neither: 15.0%).

CONCLUSIONS

In this nationally representative study, 1 in 11 ED visits and 1 in 9 hospitalizations were made by adults with AUD or SUD, and both increased over time. These estimates are higher or similar than previous national estimates using claims data. This highlights the importance of identifying opportunities to address AUD and SUD in acute care settings in tandem with other medical concerns, particularly among visits presenting with injury, trauma, or coexisting depression.

Adapting Existing Resources for Serious Illness Communication Skills Training for Internal Medicine Residents

OBJECTIVES

Goals of care discussions are a vital component of patient care, but Internal Medicine residents receive limited training in these skills. Existing curricula often require simulated patients or faculty development, limiting implementation in many residency programs. Thus, we developed and implemented a curriculum leveraging existing educational resources with the goal of improving resident attitudes and confidence in conducting goals of care discussions in training settings.

METHODS

We developed cases and a detailed faculty guide for small-group discussion with three exercises to standardize the learner experience and minimize the need for faculty development. Exercises introduced established communication skill frameworks including SPIKES (setting, perception, invitation, knowledge, empathy, summary) and REMAP (reframe, emotion, map, align, propose a plan) for how to break bad news, respond to strong emotions, and conduct a goals of care discussion. Participants were 163 Internal Medicine postgraduate year 1, -2, and -3 residents at a large urban academic institution, where residency-wide curriculum is delivered in weekly half-day didactic sessions during the course of 5 weeks. Primary outcomes were resident self-reported confidence with goals of care communication skills.

RESULTS

A total of 109 (response rate 67%) of residents reported improvement in overall confidence in goals of care discussion skills (3.6 ± 0.9 vs 4.1 ± 0.6, P < 0.001), responding to emotions (3.5 ± 0.9 vs 3.9 ± 0.6, P = 0.004), making care recommendations (3.5 ± 1.0 vs 3.9 ± 0.7, P < 0.001), and quickly conducting a code status discussion (3.6 ± 1.0 vs 4.0 ± 0.7, P < 0.001). Residents also expressed an increased desire for supervision and feedback to further develop these skills.

CONCLUSIONS

This goals of care communication curriculum improves resident confidence and requires minimal resources. It may be ideal for programs that have limited access to simulated patients and/or faculty trained in communication skill simulation, but desire enhanced education on this important aspect of patient-doctor communication and high-quality patient care. Future studies measuring clinical outcomes and changes in learner behavior as a result of this intervention are needed. Ongoing observation and feedback on these skills will be important to solidify learning and sustain impact.

Comparative effectiveness of long-term acute care hospital versus skilled nursing facility transfer

Background

Long-term acute care hospital (LTACH) use varies considerably across the U.S., which may reflect uncertainty about the effectiveness of LTACHs vs. skilled nursing facilities (SNF), the principal post-acute care alternative. Given that LTACHs provide more intensive care and thus receive over triple the reimbursement of SNFs for comparable diagnoses, we sought to compare outcomes and spending between LTACH versus SNF transfer.

Methods

Using Medicare claims linked to electronic health record (EHR) data from six Texas Hospitals between 2009 and 2010, we conducted a retrospective cohort study of patients hospitalized on a medicine service in a high-LTACH use region and discharged to either an LTACH or SNF and followed for one year. The primary outcomes included mortality, 60-day recovery without inpatient care, days at home, and healthcare spending

Results

Of 3503 patients, 18% were transferred to an LTACH. Patients transferred to LTACHs were younger (median 71 vs. 82 years), less likely to be female (50.5 vs 66.6%) and white (69.0 vs. 84.1%), but were sicker (24.3 vs. 14.2% for prolonged intensive care unit stay; median diagnosis resource intensity weight of 2.03 vs. 1.38). In unadjusted analyses, patients transferred to an LTACH vs. SNF were less likely to survive (59.1 vs. 65.0%) or recover (62.5 vs 66.0%), and spent fewer days at home (186 vs. 200). Adjusting for demographic and clinical confounders available in Medicare claims and EHR data, LTACH transfer was not significantly associated with differences in mortality (HR, 1.12, 95% CI, 0.94–1.33), recovery (SHR, 1.07, 0.93–1.23), and days spent at home (IRR, 0.96, 0.83–1.10), but was associated with greater Medicare spending ($16,689 for one year, 95% CI, $12,216–$21,162).

Conclusion

LTACH transfer for Medicare beneficiaries is associated with similar clinical outcomes but with higher healthcare spending compared to SNF transfer. LTACH use should be reserved for patients who require complex inpatient care and cannot be cared for in SNFs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-020-05847-6.

Can we predict early 7-day readmissions using a standard 30-day hospital readmission risk prediction model?

BACKGROUND

Despite focus on preventing 30-day readmissions, early readmissions (within 7 days of discharge) may be more preventable than later readmissions (8-30 days). We assessed how well a previously validated 30-day EHR-based readmission prediction model predicts 7-day readmissions and compared differences in strength of predictors.

METHODS

We conducted an observational study on adult hospitalizations from 6 diverse hospitals in North Texas using a 50-50 split-sample derivation and validation approach. We re-derived model coefficients for the same predictors as in the original 30-day model to optimize prediction of 7-day readmissions. We then compared the discrimination and calibration of the 7-day model to the 30-day model to assess model performance. To examine the changes in the point estimates between the two models, we evaluated the percent changes in coefficients.

RESULTS

Of 32,922 index hospitalizations among unique patients, 4.4% had a 7-day admission and 12.7% had a 30-day readmission. Our original 30-day model had modestly lower discrimination for predicting 7-day vs. any 30-day readmission (C-statistic of 0.66 vs. 0.69, p ≤ 0.001). Our re-derived 7-day model had similar discrimination (C-statistic of 0.66, p = 0.38), but improved calibration. For the re-derived 7-day model, discharge day factors were more predictive of early readmissions, while baseline characteristics were less predictive.

CONCLUSION

A previously validated 30-day readmission model can also be used as a stopgap to predict 7-day readmissions as model performance did not substantially change. However, strength of predictors differed between the 7-day and 30-day model; characteristics at discharge were more predictive of 7-day readmissions, while baseline characteristics were less predictive. Improvements in predicting early 7-day readmissions will likely require new risk factors proximal to day of discharge.

Improving Respiratory Rate Accuracy in the Hospital: A Quality Improvement Initiative

Respiratory rate (RR) is a predictor of adverse outcomes. However, RRs are inaccurately measured in the hospital. We conducted a quality improvement (QI) initiative using plan-do-study-act methodology on one inpatient unit of a safety-net hospital to improve RR accuracy. We added time-keeping devices to vital sign carts and retrained patient-care assistants on a newly modified workflow that included concomitant RR measurement during automated blood pressure measurement. The median RR was 18 (interquartile range [IQR] 18-20) preintervention versus 14 (IQR 15-20) postintervention. RR accuracy, defined as ±2 breaths of gold-standard measurements, increased from 36% preintervention to 58% postintervention (P < .01). The median time for vital signs decreased from 2:36 minutes (IQR, 2:04-3:20) to 1:55 minutes (IQR, 1:40-2:22; P < .01). The intervention was associated with a 7.8% reduced incidence of tachypnea-specific systemic inflammatory response syndrome (SIRS = 2 points with RR > 20; 95% CI, -13.5% to -2.2%). Our interdisciplinary, low-cost, low-tech QI initiative improved the accuracy and efficiency of RR measurement.

The Clinical Course after Long-Term Acute Care Hospital Admission among Older Medicare Beneficiaries

OBJECTIVES

Long-term acute care (LTAC) hospitals provide extended complex post-acute care to more than 120 000 Medicare beneficiaries annually, with the goal of helping patients to regain independence and recover. Because little is known about patients' long-term outcomes, we sought to examine the clinical course after LTAC admission.

DESIGN

Nationally representative 5-year cohort study using 5% Medicare data from 2009 to 2013.

SETTING

LTAC hospitals.

PARTICIPANTS

Hospitalized Medicare fee-for-service beneficiaries 65 years of age or older who were transferred to an LTAC hospital.

MEASUREMENTS

Mortality, recovery (defined as achieving 60 consecutive days alive without inpatient care), time spent in an inpatient facility following LTAC hospital admission, receipt of an artificial life-prolonging procedure (feeding tube, tracheostomy, hemodialysis), and palliative care physician consultation.

RESULTS

Of 14 072 hospitalized older adults transferred to an LTAC hospital, median survival was 8.3 months, and 1- and 5-year survival rates were 45% and 18%, respectively. Following LTAC admission, 53% never achieved a 60-day recovery. The median time of their remaining life a patient spent as an inpatient after LTAC admission was 65.6% (interquartile range = 21.4%-100%). More than one-third (36.9%) died in an inpatient setting, never returning home after the LTAC admission. During the preceding hospitalization and index LTAC admission, 30.9% received an artificial life-prolonging procedure, and 1% had a palliative care physician consultation.

CONCLUSION

Hospitalized older adults transferred to LTAC hospitals have poor survival, spend most of their remaining life as an inpatient, and frequently undergo life-prolonging procedures. This prognostic understanding is essential to inform goals of care discussions and prioritize healthcare needs for hospitalized older adults admitted to LTAC hospitals. Given the exceedingly low rates of palliative care consultations, future research is needed to examine unmet palliative care needs in this population. J Am Geriatr Soc 67:2282-2288, 2019.

Acute Myocardial Infarction Readmission Risk Prediction Models: A Systematic Review of Model Performance

BACKGROUND

Hospitals are subject to federal financial penalties for excessive 30-day hospital readmissions for acute myocardial infarction (AMI). Prospectively identifying patients hospitalized with AMI at high risk for readmission could help prevent 30-day readmissions by enabling targeted interventions. However, the performance of AMI-specific readmission risk prediction models is unknown.

METHODS AND RESULTS

We systematically searched the published literature through March 2017 for studies of risk prediction models for 30-day hospital readmission among adults with AMI. We identified 11 studies of 18 unique risk prediction models across diverse settings primarily in the United States, of which 16 models were specific to AMI. The median overall observed all-cause 30-day readmission rate across studies was 16.3% (range, 10.6%-21.0%). Six models were based on administrative data; 4 on electronic health record data; 3 on clinical hospital data; and 5 on cardiac registry data. Models included 7 to 37 predictors, of which demographics, comorbidities, and utilization metrics were the most frequently included domains. Most models, including the Centers for Medicare and Medicaid Services AMI administrative model, had modest discrimination (median C statistic, 0.65; range, 0.53-0.79). Of the 16 reported AMI-specific models, only 8 models were assessed in a validation cohort, limiting generalizability. Observed risk-stratified readmission rates ranged from 3.0% among the lowest-risk individuals to 43.0% among the highest-risk individuals, suggesting good risk stratification across all models.

CONCLUSIONS

Current AMI-specific readmission risk prediction models have modest predictive ability and uncertain generalizability given methodological limitations. No existing models provide actionable information in real time to enable early identification and risk-stratification of patients with AMI before hospital discharge, a functionality needed to optimize the potential effectiveness of readmission reduction interventions.

Evidence-Based Medicine and the American Thoracic Society Clinical Practice Guidelines

This study assesses whether American Thoracic Society clinical practice guidelines are substantiated by high-quality evidence and can be used to promote evidence-based medicine.

Association of Scheduled vs Emergency-Only Dialysis With Health Outcomes and Costs in Undocumented Immigrants With End-stage Renal Disease

IMPORTANCE

In 40 of 50 US states, scheduled dialysis is withheld from undocumented immigrants with end-stage renal disease (ESRD); instead, they receive intermittent emergency-only dialysis to treat life-threatening manifestations of ESRD. However, the comparative effectiveness of scheduled dialysis vs emergency-only dialysis and the influence of treatment on health outcomes, utilization, and costs is uncertain.

OBJECTIVE

To compare the effectiveness of scheduled vs emergency-only dialysis with regard to health outcomes, utilization, and costs in undocumented immigrants with ESRD.

DESIGN, SETTING, AND PARTICIPANTS

Observational cohort study of 181 eligible adults with ESRD receiving emergency-only dialysis in Dallas, Texas, who became newly eligible and applied for private commercial health insurance in February 2015; 105 received coverage and were enrolled in scheduled dialysis; 76 were not enrolled in insurance for nonclinical reasons (eg, lack of capacity at a participating outpatient dialysis center) and remained uninsured, receiving emergency-only dialysis. We examined data on eligible persons during a 6-month period prior to enrollment (baseline period, August 1, 2014-January 31, 2015) until 12 months after enrollment (follow-up period, March 1, 2015-February 29, 2016), with an intervening 1-month washout period (February 2015). All participants were undocumented immigrants; self-reported data on immigration status was collected from Parkland Hospital electronic health records.

EXPOSURES

Enrollment in private health insurance coverage and scheduled dialysis.

MAIN OUTCOMES AND MEASURES

We used enrollment in health insurance and scheduled dialysis to estimate the influence of scheduled dialysis on 1-year mortality, utilization, and health care costs, using a propensity score-adjusted, intention-to-treat approach, including time-to-event analyses for mortality, difference-in-differences (DiD) negative binomial regression analyses for utilization, and DiD gamma generalized linear regression for health care costs.

RESULTS

Of 181 eligible adults with ESRD, 105 (65 men, 40 women; mean age, 45 years) received scheduled dialysis and 76 (38 men, 38 women; mean age, 52 years) received emergency-only dialysis. Compared with emergency-only dialysis, scheduled dialysis was significantly associated with reduced mortality (3% vs 17%, P = .001; absolute risk reduction, 14%; number needed to treat, 7; adjusted hazard ratio, 4.6; 95% CI, 1.2-18.2; P = .03), adjusted emergency department visits (-5.2 vs +1.1 visits/mo; DiD, -6.2; P < .001), adjusted hospitalizations (-2.1 vs -0.5 hospitalizations/6 months; DiD, -1.6; P < .001), adjusted hospital days (-9.2 vs +0.8 days/6 months; DiD, -9.9; P = .007), and adjusted costs (-$4316 vs +$1452 per person per month; DiD, -$5768; P < .001).

CONCLUSIONS AND RELEVANCE

In this study, scheduled dialysis was significantly associated with reduced 1-year mortality, health care utilization, and costs compared with emergency-only dialysis. Scheduled dialysis should be the universal standard of care for all individuals with ESRD in the United States.

Effect of Site-Neutral Payment Policy on Long-Term Acute Care Hospital Use

OBJECTIVE

To assess the projected effect of the Centers for Medicare and Medicaid Services new site-neutral payment policy, which aims to decrease unnecessary long-term acute care hospital (LTACH) admissions by reducing reimbursements for less-ill individuals by 2020.

DESIGN

Observational.

SETTING

National 5% Medicare data (2011-12).

MEASUREMENTS

We examined the proportion of site-neutral LTACH admissions. Regional LTACH market supply was defined as LTACH beds per 100,000 residents, categorized according to tertile. We conducted a hospital-level analysis to compare the projected effect of site-neutral payment on "propensity score" matched high- and low-LTACH-use hospitals.

RESULTS

Forty-one percent of LTACH admissions would be subjected to site-neutral payment. The proportion of site-neutral admissions was large, varied considerably according to LTACH (median 40%, interquartile range 22-60%), and was only modestly greater with greater market supply (Pearson correlation coefficient=0.23, p<.001; coefficient of determination=0.10). The site-neutral payment policy would affect 47% of admissions from the highest-supply regions, versus 30% from the lowest-supply regions (p<.001); and 43% from high-use hospitals versus 36% from propensity score-matched low-use hospitals (p<.001).

CONCLUSION

A considerable proportion of LTACH admissions will be subjected to lower site-neutral payments. Although the policy will disproportionately affect high-use regions and hospitals, it will also affect nearly one-third of the current LTACH population from low-use hospitals and regions. As such, the site-neutral payment policy may limit LTACH access in existing LTAC-scarce markets, with potential adverse implications for recovery of hospitalized older adults. J Am Geriatr Soc 66:2104-2111, 2018.

Long-Term Acute Care Hospital Use of Non-Mechanically Ventilated Hospitalized Older Adults

OBJECTIVES

To determine why non-mechanically ventilated hospitalized older adults are transferred to long-term acute care (LTAC) hospitals rather than remaining in the hospital.

DESIGN

Observational cohort.

SETTING

National Medicare data.

PARTICIPANTS

Non-mechanically ventilated hospitalized adults aged 65 and older with fee-for-service Medicare in 2012 who were transferred to an LTAC hospital (n=1,831) or had a prolonged hospitalization without transfer (average hospital length of stay or longer of those transferred to an LTAC hospital) and had one of the 50 most common hospital diagnoses leading to LTAC transfer (N=12,875).

MEASUREMENTS

We assessed predictors of transfer using a multilevel model, adjusting for patient-, hospital-, and hospital referral region (HRR)-level factors. We estimated proportions of variance at each level and adjusted hospital- and HRR-specific LTAC transfer rates using sequential models.

RESULTS

The strongest predictor of transfer was being hospitalized near an LTAC hospital (<1.4 vs > 33.6 miles, adjusted odds ratio=6.2, 95% confidence interval (CI)=4.2-9.1). After adjusting for case mix, differences between hospitals explained 15.4% of the variation in LTAC use and differences between regions explained 27.8%. Case mix-adjusted LTAC use was high in the South, where many HRRs had rates between 20.3% and 53.1%, whereas many HRRs were less than 5.4% in the Pacific Northwest, North, and New England. From our fully adjusted model, the median adjusted hospital LTAC transfer rate was 7.2% (interquartile range 2.8-17.5%), with substantial within-region variation (intraclass coefficient=0.25, 95% CI=0.21-0.30).

CONCLUSIONS

Nearly half of the variation in LTAC use is independent of illness severity and is explained by which hospital and what region the individual was hospitalized in. Because of the greater fragmentation of care and Medicare spending with LTAC transfers (because LTAC hospitals generate a separate bundled payment from the hospital), greater attention is needed to define the optimal role of LTAC hospitals in caring for older adults. J Am Geriatr Soc 66:2112-2119, 2018.

Predicting 30-Day Hospital Readmissions in Acute Myocardial Infarction: The AMI "READMITS" (Renal Function, Elevated Brain Natriuretic Peptide, Age, Diabetes Mellitus, Nonmale Sex, Intervention with Timely Percutaneous Coronary Intervention, and Low Systolic Blood Pressure) Score

BACKGROUND

Readmissions after hospitalization for acute myocardial infarction (AMI) are common. However, the few currently available AMI readmission risk prediction models have poor-to-modest predictive ability and are not readily actionable in real time. We sought to develop an actionable and accurate AMI readmission risk prediction model to identify high-risk patients as early as possible during hospitalization.

METHODS AND RESULTS

We used electronic health record data from consecutive AMI hospitalizations from 6 hospitals in north Texas from 2009 to 2010 to derive and validate models predicting all-cause nonelective 30-day readmissions, using stepwise backward selection and 5-fold cross-validation. Of 826 patients hospitalized with AMI, 13% had a 30-day readmission. The first-day AMI model (the AMI "READMITS" score) included 7 predictors: renal function, elevated brain natriuretic peptide, age, diabetes mellitus, nonmale sex, intervention with timely percutaneous coronary intervention, and low systolic blood pressure, had an optimism-corrected C-statistic of 0.73 (95% confidence interval, 0.71-0.74) and was well calibrated. The full-stay AMI model, which included 3 additional predictors (use of intravenous diuretics, anemia on discharge, and discharge to postacute care), had an optimism-corrected C-statistic of 0.75 (95% confidence interval, 0.74-0.76) with minimally improved net reclassification and calibration. Both AMI models outperformed corresponding multicondition readmission models.

CONCLUSIONS

The parsimonious AMI READMITS score enables early prospective identification of high-risk AMI patients for targeted readmissions reduction interventions within the first 24 hours of hospitalization. A full-stay AMI readmission model only modestly outperformed the AMI READMITS score in terms of discrimination, but surprisingly did not meaningfully improve reclassification.

Factors Associated With Variation in Long-term Acute Care Hospital vs Skilled Nursing Facility Use Among Hospitalized Older Adults

IMPORTANCE

Despite providing an overlapping level of care, it is unknown why hospitalized older adults are transferred to long-term acute care hospitals (LTACs) vs less costly skilled nursing facilities (SNFs) for postacute care.

OBJECTIVE

To examine factors associated with variation in LTAC vs SNF transfer among hospitalized older adults.

DESIGN, SETTING, AND PARTICIPANTS

We conducted this retrospective observational cohort study of hospitalized older adults (≥65 years) transferred to an LTAC vs SNF during fiscal year 2012 using national 5% Medicare data.

MAIN OUTCOMES AND MEASURES

Predictors of LTAC transfer were assessed using a multilevel mixed-effects model adjusting for patient-, hospital-, and region-level factors. We estimated variation partition coefficients and adjusted hospital- and region-specific LTAC transfer rates using sequential models.

RESULTS

Among 65 525 hospitalized older adults (42 461 [64.8%] women; 39 908 [60.9%] ≥85 years) transferred to an LTAC or SNF, 3093 (4.7%) were transferred to an LTAC. We identified 29 patient-, 3 hospital-, and 5 region-level independent predictors. The strongest predictors of LTAC transfer were receiving a tracheostomy (adjusted odds ration [aOR], 23.8; 95% CI, 15.8-35.9) and being hospitalized in close proximity to an LTAC (0-2 vs >42 miles; aOR, 8.4, 95% CI, 6.1-11.5). After adjusting for case-mix, differences between patients explained 52.1% (95% CI, 47.7%-56.5%) of the variation in LTAC use. The remainder was attributable to hospital (15.0%; 95% CI, 12.3%-17.6%), and regional differences (32.9%; 95% CI, 27.6%-38.3%). Case-mix adjusted LTAC use was very high in the South (17%-37%) compared with the Pacific Northwest, North, and Northeast (<2.2%). From the full multilevel model, the median adjusted hospital LTAC transfer rate was 2.1% (10th-90th percentile, 0.24%-10.8%). Even within a region, adjusted hospital LTAC transfer rates varied substantially (intraclass correlation coefficient [ICC], 0.26; 95% CI, 0.23-0.30).

CONCLUSIONS AND RELEVANCE

Although many patient-level factors were associated with LTAC use, half of the variation in LTAC vs SNF transfer is independent of patients' illness severity or clinical complexity, and is explained by where the patient was hospitalized and in what region, with far greater use in the South. Even among hospitals in regions with similar LTAC access, there was considerable variation in LTAC use. Given the higher expense associated with LTACs vs SNFs, greater attention is needed to define the optimal role of LTACs in the postacute care of older adults.

Is everyone really breathing 20 times a minute? Assessing epidemiology and variation in recorded respiratory rate in hospitalised adults

BACKGROUND

Respiratory rate (RR) is an independent predictor of adverse outcomes and an integral component of many risk prediction scores for hospitalised adults. Yet, it is unclear if RR is recorded accurately. We sought to assess the potential accuracy of RR by analysing the distribution and variation as a proxy, since RR should be normally distributed if recorded accurately.

METHODS

We conducted a descriptive observational study of electronic health record data from consecutive hospitalisations from 2009 to 2010 from six diverse hospitals. We assessed the distribution of the maximum RR on admission, using heart rate (HR) as a comparison since this is objectively measured. We assessed RR patterns among selected subgroups expected to have greater physiological variation using the coefficient of variation (CV=SD/mean).

RESULTS

Among 36 966 hospitalisations, recorded RR was not normally distributed (p<0.001), but right skewed (skewness=3.99) with values clustered at 18 and 20 (kurtosis=23.9). In contrast, HR was relatively normally distributed. Patients with a cardiopulmonary diagnosis or hypoxia only had modestly greater variation (CV increase of 2%-6%). Among 1318 patients transferred from the ward to the intensive care unit (n=1318), RR variation the day preceding transfer was similar to that observed on admission (CV 0.24 vs 0.26), even for those transferred with respiratory failure (CV 0.25).

CONCLUSIONS

The observed patterns suggest that RR is inaccurately recorded, even among those with cardiopulmonary compromise, and represents a 'spot' estimate with values of 18 and 20 breaths per minute representing 'normal.' While spot estimates may potentially be adequate to indicate clinical stability, inaccurate RR may alternatively lead to misclassification of disease severity, potentially jeopardising patient safety. Thus, we recommend greater training for hospital personnel to accurately record RR.

Predicting 30-Day Pneumonia Readmissions Using Electronic Health Record Data

BACKGROUND

Readmissions after hospitalization for pneumonia are common, but the few risk-prediction models have poor to modest predictive ability. Data routinely collected in the electronic health record (EHR) may improve prediction.

OBJECTIVE

To develop pneumonia-specific readmission risk-prediction models using EHR data from the first day and from the entire hospital stay ("full stay").

DESIGN

Observational cohort study using stepwise-backward selection and cross-validation.

SUBJECTS

Consecutive pneumonia hospitalizations from 6 diverse hospitals in north Texas from 2009-2010.

MEASURES

All-cause nonelective 30-day readmissions, ascertained from 75 regional hospitals.

RESULTS

Of 1463 patients, 13.6% were readmitted. The first-day pneumonia-specific model included sociodemographic factors, prior hospitalizations, thrombocytosis, and a modified pneumonia severity index; the full-stay model included disposition status, vital sign instabilities on discharge, and an updated pneumonia severity index calculated using values from the day of discharge as additional predictors. The full-stay pneumonia-specific model outperformed the first-day model (C statistic 0.731 vs 0.695; P = 0.02; net reclassification index = 0.08). Compared to a validated multi-condition readmission model, the Centers for Medicare and Medicaid Services pneumonia model, and 2 commonly used pneumonia severity of illness scores, the full-stay pneumonia-specific model had better discrimination (C statistic range 0.604-0.681; P < 0.01 for all comparisons), predicted a broader range of risk, and better reclassified individuals by their true risk (net reclassification index range, 0.09-0.18).

CONCLUSIONS

EHR data collected from the entire hospitalization can accurately predict readmission risk among patients hospitalized for pneumonia. This approach outperforms a first-day pneumonia-specific model, the Centers for Medicare and Medicaid Services pneumonia model, and 2 commonly used pneumonia severity of illness scores. Journal of Hospital Medicine 2017;12:209-216.

Who Is Food Insecure? Implications for Targeted Recruitment and Outreach, National Health and Nutrition Examination Survey, 2005-2010

Introduction

Food insecurity is negatively associated with health; however, health needs may differ among people participating in food assistance programs. Our objectives were to characterize differences in health among people receiving different types of food assistance and summarize strategies for targeted recruitment and outreach of various food insecure populations.

Methods

We examined health status, behaviors, and health care access associated with food insecurity and receipt of food assistance among US adults aged 20 years or older using data from participants (N = 16,934) of the National Health and Nutrition Examination Survey from 2005 through 2010.

Results

Food insecurity affected 19.3% of US adults (95% confidence interval, 17.9%–20.7%). People who were food insecure reported poorer health and less health care access than those who were food secure (P < .001 for all). Among those who were food insecure, 58.0% received no assistance, 20.3% received only Supplemental Nutrition Assistance Program (SNAP) benefits, 9.7% received only food bank assistance, and 12.0% received both SNAP and food bank assistance. We observed an inverse relationship between receipt of food assistance and health and health behaviors among the food insecure. Receipt of both (SNAP and food bank assistance) was associated with the poorest health; receiving no assistance was associated with the best health. For example, functional limitations were twice as prevalent among people receiving both types of food assistance than among those receiving none.

Conclusion

Receipt of food assistance is an overlooked factor associated with health and has the potential to shape future chronic disease prevention efforts among the food insecure.

Predicting all-cause readmissions using electronic health record data from the entire hospitalization: Model development and comparison

BACKGROUND

Incorporating clinical information from the full hospital course may improve prediction of 30-day readmissions.

OBJECTIVE

To develop an all-cause readmissions risk-prediction model incorporating electronic health record (EHR) data from the full hospital stay, and to compare "full-stay" model performance to a "first day" and 2 other validated models, LACE (includes Length of stay, Acute [nonelective] admission status, Charlson Comorbidity Index, and Emergency department visits in the past year), and HOSPITAL (includes Hemoglobin at discharge, discharge from Oncology service, Sodium level at discharge, Procedure during index hospitalization, Index hospitalization Type [nonelective], number of Admissions in the past year, and Length of stay).

DESIGN

Observational cohort study.

SUBJECTS

All medicine discharges between November 2009 and October 2010 from 6 hospitals in North Texas, including safety net, teaching, and nonteaching sites.

MEASURES

Thirty-day nonelective readmissions were ascertained from 75 regional hospitals.

RESULTS

Among 32,922 admissions (validation = 16,430), 12.7% were readmitted. In addition to many first-day factors, we identified hospital-acquired Clostridium difficile infection (adjusted odds ratio [AOR]: 2.03, 95% confidence interval [CI]: 1.18-3.48), vital sign instability on discharge (AOR: 1.25, 95% CI: 1.15-1.36), hyponatremia on discharge (AOR: 1.34, 95% CI: 1.18-1.51), and length of stay (AOR: 1.06, 95% CI: 1.04-1.07) as significant predictors. The full-stay model had better discrimination than other models though the improvement was modest (C statistic 0.69 vs 0.64-0.67). It was also modestly better in identifying patients at highest risk for readmission (likelihood ratio +2.4 vs. 1.8-2.1) and in reclassifying individuals (net reclassification index 0.02-0.06).

CONCLUSIONS

Incorporating clinically granular EHR data from the full hospital stay modestly improves prediction of 30-day readmissions. Given limited improvement in prediction despite incorporation of data on hospital complications, clinical instabilities, and trajectory, our findings suggest that many factors influencing readmissions remain unaccounted for. Further improvements in readmission models will likely require accounting for psychosocial and behavioral factors not currently captured by EHRs. Journal of Hospital Medicine 2016;11:473-480. © 2016 Society of Hospital Medicine.

Relationship between hospital financial performance and publicly reported outcomes

BACKGROUND

Hospitals that have robust financial performance may have improved publicly reported outcomes.

OBJECTIVES

To assess the relationship between hospital financial performance and publicly reported outcomes of care, and to assess whether improved outcome metrics affect subsequent hospital financial performance.

DESIGN

Observational cohort study.

SETTING AND PATIENTS

Hospital financial data from the Office of Statewide Health Planning and Development in California in 2008 and 2012 were linked to data from the Centers for Medicare and Medicaid Services Hospital Compare website.

MEASUREMENTS

Hospital financial performance was measured by net revenue by operations, operating margin, and total margin. Outcomes were 30-day risk-standardized mortality and readmission rates for acute myocardial infarction (AMI), congestive heart failure (CHF), and pneumonia (PNA).

RESULTS

Among 279 hospitals, there was no consistent relationship between measures of financial performance in 2008 and publicly reported outcomes from 2008 to 2011 for AMI and PNA. However, improved hospital financial performance (by any of the 3 measures) was associated with a modest increase in CHF mortality rates (ie, 0.26% increase in CHF mortality rate for every 10% increase in operating margin [95% confidence interval: 0.07%-0.45%]). Conversely, there were no significant associations between outcomes from 2008 to 2011 and subsequent financial performance in 2012 (P > 0.05 for all).

CONCLUSIONS

Robust financial performance is not associated with improved publicly reported outcomes for AMI, CHF, and PNA. Financial incentives in addition to public reporting, such as readmissions penalties, may help motivate hospitals with robust financial performance to further improve publicly reported outcomes. Reassuringly, improved mortality and readmission rates do not necessarily lead to loss of revenue. Journal of Hospital Medicine 2016;11:481-488. © 2016 Society of Hospital Medicine.

Management of Hypertension in Primary Care Safety-Net Clinics in the United States: A Comparison of Community Health Centers and Private Physicians' Offices

OBJECTIVE

To examine adherence to guideline-concordant hypertension treatment practices at community health centers (CHCs) compared with private physicians' offices.

DATA SOURCES/STUDY SETTING

National Ambulatory Medical Care Survey from 2006 to 2010.

STUDY DESIGN

We examined four guideline-concordant treatment practices: initiation of a new medication for uncontrolled hypertension, use of fixed-dose combination drugs for patients on multiple antihypertensive medications, use of thiazide diuretics among patients with uncontrolled hypertension on ≥3 antihypertensive medications, and use of aldosterone antagonist for resistant hypertension, comparing use at CHC with private physicians' offices overall and by payer group.

DATA COLLECTION/EXTRACTION METHODS

We identified visits of nonpregnant adults with hypertension at CHCs and private physicians' offices.

PRINCIPAL FINDINGS

Medicaid patients at CHCs were as likely as privately insured individuals to receive a new medication for uncontrolled hypertension (AOR 1.0, 95 percent CI: 0.6-1.9), whereas Medicaid patients at private physicians' offices were less likely to receive a new medication (AOR 0.3, 95 percent CI: 0.1-0.6). Use of fixed-dose combination drugs was lower at CHCs (AOR 0.6, 95 percent CI: 0.4-0.9). Thiazide use for patients was similar in both settings (AOR 0.8, 95 percent CI: 0.4-1.7). Use of aldosterone antagonists was too rare (2.1 percent at CHCs and 1.5 percent at private clinics) to allow for statistically reliable comparisons.

CONCLUSIONS

Increasing physician use of fixed-dose combination drugs may be particularly helpful in improving hypertension control at CHCs where there are higher rates of uncontrolled hypertension.

National Use of Safety-Net Clinics for Primary Care among Adults with Non-Medicaid Insurance in the United States

Objective

To describe the prevalence, characteristics, and predictors of safety-net use for primary care among non-Medicaid insured adults (i.e., those with private insurance or Medicare).

Methods

Cross-sectional analysis using the 2006–2010 National Ambulatory Medical Care Surveys, annual probability samples of outpatient visits in the U.S. We estimated national prevalence of safety-net visits using weighted percentages to account for the complex survey design. We conducted bivariate and multivariate logistic regression analyses to examine characteristics associated with safety-net clinic use.

Results

More than one-third (35.0%) of all primary care safety-net clinic visits were among adults with non-Medicaid primary insurance, representing 6,642,000 annual visits nationally. The strongest predictors of safety-net use among non-Medicaid insured adults were: being from a high-poverty neighborhood (AOR 9.53, 95% CI 4.65–19.53), being dually eligible for Medicare and Medicaid (AOR 2.13, 95% CI 1.38–3.30), and being black (AOR 1.97, 95% CI 1.06–3.66) or Hispanic (AOR 2.28, 95% CI 1.32–3.93). Compared to non-safety-net users, non-Medicaid insured adults who used safety-net clinics had a higher prevalence of diabetes (23.5% vs. 15.0%, p<0.001), hypertension (49.4% vs. 36.0%, p<0.001), multimorbidity (≥2 chronic conditions; 53.5% vs. 40.9%, p<0.001) and polypharmacy (≥4 medications; 48.8% vs. 34.0%, p<0.001). Nearly one-third (28.9%) of Medicare beneficiaries in the safety-net were dual eligibles, compared to only 6.8% of Medicare beneficiaries in non-safety-net clinics (p<0.001).

Conclusions

Safety net clinics are important primary care delivery sites for non-Medicaid insured minority and low-income populations with a high burden of chronic illness. The critical role of safety-net clinics in care delivery is likely to persist despite expanded insurance coverage under the Affordable Care Act.

Envisioning a social-health information exchange as a platform to support a patient-centered medical neighborhood: a feasibility study

BACKGROUND

Social determinants directly contribute to poorer health, and coordination between healthcare and community-based resources is pivotal to addressing these needs. However, our healthcare system remains poorly equipped to address social determinants of health. The potential of health information technology to bridge this gap across the delivery of healthcare and social services remains unrealized.

OBJECTIVE, DESIGN, AND PARTICIPANTS

We conducted in-depth, in-person interviews with 50 healthcare and social service providers to determine the feasibility of a social-health information exchange (S-HIE) in an urban safety-net setting in Dallas County, Texas. After completion of interviews, we conducted a town hall meeting to identify desired functionalities for a S-HIE.

APPROACH

We conducted thematic analysis of interview responses using the constant comparative method to explore perceptions about current communication and coordination across sectors, and barriers and enablers to S-HIE implementation. We sought participant confirmation of findings and conducted a forced-rank vote during the town hall to prioritize potential S-HIE functionalities.

KEY RESULTS

We found that healthcare and social service providers perceived a need for improved information sharing, communication, and care coordination across sectors and were enthusiastic about the potential of a S-HIE, but shared many technical, legal, and ethical concerns around cross-sector information sharing. Desired technical S-HIE functionalities encompassed fairly simple transactional operations such as the ability to view basic demographic information, visit and referral data, and medical history from both healthcare and social service settings.

CONCLUSIONS

A S-HIE is an innovative and feasible approach to enabling better linkages between healthcare and social service providers. However, to develop S-HIEs in communities across the country, policy interventions are needed to standardize regulatory requirements, to foster increased IT capability and uptake among social service agencies, and to align healthcare and social service priorities to enable dissemination and broader adoption of this and similar IT initiatives.

Understanding how to improve collaboration between hospitals and primary care in postdischarge care transitions: a qualitative study of primary care leaders' perspectives

BACKGROUND

There is limited collaboration between hospitals and primary care despite parallel efforts to improve postdischarge care transitions.

OBJECTIVE

To understand what primary care leaders perceived as barriers and facilitators to collaboration with hospitals.

METHODS

Qualitative study with in-depth, semistructured interviews of 22 primary care leaders in 2012 from California safety-net clinics.

RESULTS

Major barriers to collaboration included lack of institutional financial incentives for collaboration, competing priorities (e.g., regulatory requirements, strained clinic capacity, financial strain) and mismatched expectations about role and capacity of primary care to improve care transitions. Facilitators included relationship building through interpersonal networking and improving communication and information transfer via electronic health record (EHR) implementation.

CONCLUSIONS

Efforts to improve care transitions should focus on aligning financial incentives, standardizing regulations around EHR interoperability and data sharing, and enhancing opportunities for interpersonal networking.

What's cost got to do with it? Association between hospital costs and frequency of admissions among "high users" of hospital care

BACKGROUND

Efforts to curb healthcare spending have included interventions that target frequently hospitalized individuals. It is unclear the extent to which the most frequently hospitalized individuals also represent the costliest individuals.

OBJECTIVE

To examine the relationship between 2 types of "high users" commonly targeted in cost-containment interventions-those incurring the highest hospital costs ("high cost") and those incurring the highest number of hospitalizations ("high admit").

DESIGN, SETTING, AND PATIENTS

Cross-sectional study of 2566 individuals with a primary care physician and at least 1 hospitalization within an academic health system from 2010 to 2011.

MEASUREMENTS

Overlap between the population constituting the top decile of hospital costs and the population constituting the top decile of hospitalizations; characteristics of the 3 resulting high user subgroups.

RESULTS

Only 48% of individuals who were high cost (>$65,000) were also high admit (≥ 3 hospitalizations). Compared to hospitalizations incurred by high cost-high admit individuals (n = 605), hospitalizations incurred by high cost-low admit individuals (n = 206) were more likely to be for surgical procedures (58 vs 22%, P < 0.001), had a higher cost ($68,000 vs $28,000, P < 0.001), longer length of stay (10 vs 5 days, P < 0.001), and were less likely to be a 30-day readmission (17 vs 47%, P < 0.001).

CONCLUSIONS

Stratifying high admit individuals by costs and high cost individuals by hospitalizations yields 3 distinct high user subgroups with important differences in clinical characteristics and utilization patterns. Consideration of these distinct subgroups may lead to better-tailored interventions and achieve greater cost savings.

Pediatric Cortical Dysplasia: Correlations between Neuroimaging, Electrophysiology and Location of Cytomegalic Neurons and Balloon Cells and Glutamate/GABA Synaptic Circuits

Seizures in cortical dysplasia (CD) could be from cytomegalic neurons and balloon cells acting as epileptic 'pacemakers', or abnormal neurotransmission. This study examined these hypotheses using in vitro electrophysiological techniques to determine intrinsic membrane properties and spontaneous glutamatergic and GABAergic synaptic activity for normal-pyramidal neurons, cytomegalic neurons and balloon cells from 67 neocortical sites originating from 43 CD patients (ages 0.2-14 years). Magnetic resonance imaging (MRI), (18)fluoro-2-deoxyglucose positron emission tomography (FDG-PET) and electrocorticography graded cortical sample sites from least to worst CD abnormality. Results found that cytomegalic neurons and balloon cells were observed more frequently in areas of severe CD compared with mild or normal CD regions as assessed by FDG-PET/MRI. Cytomegalic neurons (but not balloon cells) correlated with the worst electrocorticography scores. Electrophysiological recordings demonstrated that cytomegalic and normal-pyramidal neurons displayed similar firing properties without intrinsic bursting. By contrast, balloon cells were electrically silent. Normal-pyramidal and cytomegalic neurons displayed decreased spontaneous glutamatergic synaptic activity in areas of severe FDG-PET/MRI abnormalities compared with normal regions, while GABAergic activity was unaltered. In CD, these findings indicate that cytomegalic neurons (but not balloon cells) might contribute to epileptogenesis, but are not likely to be 'pacemaker' cells capable of spontaneous paroxysmal depolarizations. Furthermore, there was more GABA relative to glutamate synaptic neurotransmission in areas of severe CD. Thus, in CD tissue alternate mechanisms of epileptogenesis should be considered, and we suggest that GABAergic synaptic circuits interacting with cytomegalic and normal-pyramidal neurons with immature receptor properties might contribute to seizure generation.