Hospital Readmissions Among Patients Experiencing Homelessness: An Electronic Health Record Data Study.

BACKGROUND: Population-level tracking of hospital use patterns with integrated care organizations in patients experiencing homelessness has been difficult. A California law implemented in 2019 (Senate Bill 1152) aimed to ensure safety for this population after discharge from the hospital by requiring additional documentation for patients experiencing homelessness, which provides an opportunity to evaluate hospital use by this population. METHODS: In a large integrated health system in California, patients experiencing homelessness were identified through documentation change requirements associated with this law and compared with a matched group from the general population. RESULTS: Patients experiencing homelessness had increased rates of hospital readmission after discharge compared to the general population matched on demographics and medical comorbidity in 2019 and 2020. Any address change in the prior year for patients was associated with increased odds of emergency department readmission. Patients experiencing homelessness, both enrolled in an integrated delivery system and not, were successfully identified as having higher readmission rates compared with their housed counterparts. CONCLUSION: Documentation of housing status following Senate Bill 1152 has enabled improved study of hospital use among those with housing instability. Understanding patterns of hospital use in this vulnerable group will help practitioners identify timely points of intervention for further social and health care support.

Clinical impacts of an integrated electronic health record-based smoking cessation intervention during hospitalisation.

OBJECTIVE: To assess the effects of an electronic health record (EHR) intervention that prompts the clinician to prescribe nicotine replacement therapy (NRT) at hospital admission and discharge in a large integrated health system. DESIGN: Retrospective cohort study using interrupted time series (ITS) analysis leveraging EHR data generated before and after implementation of the 2015 EHR-based intervention. SETTING: Kaiser Permanente Northern California, a large integrated health system with 4.2 million members. PARTICIPANTS: Current smokers aged ≥18 hospitalised for any reason. EXPOSURE: EHR-based clinical decision supports that prompted the clinician to order NRT on hospital admission (implemented February 2015) and discharge (implemented September 2015). MAIN OUTCOMES AND MEASURES: Primary outcomes included the monthly percentage of admitted smokers with NRT orders during admission and at discharge. A secondary outcome assessed patient quit rates within 30 days of hospital discharge as reported during discharge follow-up outpatient visits. RESULTS: The percentage of admissions with NRT orders increased from 29.9% in the year preceding the intervention to 78.1% in the year following (41.8% change, 95% CI 38.6% to 44.9%) after implementation of the admission hard-stop intervention compared with the baseline trend (ITS estimate). The percentage of discharges with NRT orders increased acutely at the time of both interventions (admission intervention ITS estimate 15.5%, 95% CI 11% to 20%; discharge intervention ITS estimate 13.4%, 95% CI 9.1% to 17.7%). Following the implementation of the discharge intervention, there was a small increase in patient-reported quit rates (ITS estimate 5.0%, 95% CI 2.2% to 7.8%). CONCLUSIONS: An EHR-based clinical decision-making support embedded into admission and discharge documentation was associated with an increase in NRT prescriptions and improvement in quit rates. Similar systemic EHR interventions can help improve smoking cessation efforts after hospitalisation.

Art Interventions to Mitigate Burnout in Health Care Professionals: A Systematic Review.

Burnout in the medical workforce is a growing global concern. Visual arts-based interventions can be a novel way to mitigate burnout and bolster resilience in medicine. Improving tolerance of ambiguity and uncertainty has been associated with decreased rates of burnout in clinicians. No known systematic review exists summarizing the evidence behind the use of visual arts-based interventions to mitigate burnout in clinicians. The authors conducted a systematic literature review of PubMed, EMBASE, and CINAHL in November 2022 using the terms: art, medicine, burnout, and uncertainty. The authors review the evidence for the effects of visual arts-based interventions on clinician burnout. The search identified 58 articles, of which 26 met study inclusion criteria and were assessed by 2 reviewers. These studies reported mixed methods assessments of changes in burnout, empathy, and stress. Overall, visual arts-based interventions promoted empathy, connectedness, and tolerance of ambiguity and had positive effects on burnout; however, some results were mixed. Visual arts-based interventions to mitigate burnout show promise, and additional research should focus on feasibility and longer-term outcomes.

Identifying Predictors of Homelessness Among Adults in a Large Integrated Health System in Northern California.

Introduction Homelessness contributes to worsening health and increased health care costs. There is little published research that leverages rich electronic health record (EHR) data to predict future homelessness risk and inform interventions to address it. The authors' objective was to develop a model for predicting future homelessness using individual EHR and geographic data covariates. Methods This retrospective cohort study included 2,543,504 adult members (≥ 18 years old) from Kaiser Permanente Northern California and evaluated which covariates predicted a composite outcome of homelessness status (hospital discharge documentation of a homeless patient, medical diagnosis of homelessness, approved medical financial assistance application for homelessness, and/or "homeless/shelter" in address name). The predictors were measured in 2018-2019 and included prior diagnoses and demographic and geographic data. The outcome was measured in 2020. The cohort was split (70:30) into a derivation and validation set, and logistic regression was used to model the outcome. Results Homelessness prevalence was 0.35% in the overall sample. The final logistic regression model included 26 prior diagnoses, demographic, and geographic-level predictors. The regression model using the validation set had moderate sensitivity (80.4%) and specificity (83.2%) for predicting future cases of homelessness and achieved excellent classification properties (area under the curve of 0.891 [95% confidence interval = 0.884-0.897]). Discussion This prediction model can be used as an initial triage step to enhance screening and referral tools for identifying and addressing homelessness, which can improve health and reduce health care costs. Conclusions EHR data can be used to predict chance of homelessness at a population health level.

Does the market reward quality? Evidence from India.

There are two salient facts about health care in low and middle-income countries; (1) the private sector plays an important role and (2) the care provided is often of poor quality. Despite these facts we know little about what drives quality of care in the private sector and why patients seek care from poor quality providers. We use two field studies in India that provide insight into this issue. First, we use a discrete choice experiment to show that patients strongly value technical quality. Second, we use standardized patients to show that better quality providers are not able to charge higher prices. Instead providers are able to charge higher prices for elements of quality that the patient can observe, which are less important for health outcomes. Future research should explore whether accessible information on technical quality of local providers can shift demand to higher quality providers and improve health outcomes.

Factors associated with persistent high health care utilization in managed Medicaid.

OBJECTIVES: Prior studies have had difficulty predicting which patients will have persistent high utilization past 1 year within the Medicaid population. The objective of this study was to examine the medical diagnoses at the time of enrollment of patients with persistent high health care utilization over 24 months following enrollment in Medicaid managed care in a large integrated care setting. STUDY DESIGN: Retrospective cohort study in a large integrated managed health care system. METHODS: We identified a cohort of high utilizers (top 5% of health care costs in 2014) and extracted their electronic health record data (2014-2016). Differences in baseline characteristics of high utilizers and the general Medicaid population were determined using bivariate analysis. We used multivariable regression to determine the independent association between medical comorbidities and demographics with persistent high health care utilization over the 2 years following enrollment. RESULTS: Compared with the general Medicaid managed care enrollee population, schizophrenia was the only mental health diagnosis at the time of enrollment associated with persistent high health care utilization (risk ratio [RR], 1.50; 95% CI, 1.20-1.86). Additional characteristics associated with persistent high utilization included age between 31 and 50 years (RR, 1.20; 95% CI, 1.02-1.41), dual enrollment in Medicaid and Medicare (RR, 1.26; 95% CI, 1.09-1.45), chronic pain diagnoses (RR, 1.26; 95% CI, 1.04-1.53), and multimorbidity (RR, 1.43; 95% CI, 1.25-1.63). CONCLUSIONS: Among adults newly enrolled in Medicaid managed care, certain diagnoses noted at the time of enrollment into the plan are associated with persistent high health care utilization over the first 2 years, suggesting that targeting early supportive case management to these individuals could optimize care and reduce health care costs.

Clinical Response to Real-Time Patient-Reported Diabetic Peripheral Neuropathy Symptoms.

INTRODUCTION: To assess clinician response to real-time patient-reported data about diabetic peripheral neuropathy (DPN) symptoms, we analyzed DPN diagnosis and treatment patterns after administration of a 4-question symptom questionnaire in a large vertically integrated health care system. METHODS: Retrospective cohort study to analyze data from 160,852 patients screened for DPN symptoms from April 2012 to March 2014. Electronic medical record data were used to study changes in DPN diagnosis, treatment initiation, and treatment intensification. We used logistic regression to study the association of patient characteristics with the odds of clinical response. RESULTS: Of patients queried, 50,684 (31.5%) reported symptoms. Patients reporting DPN symptoms experienced a greater increase in new DPN diagnoses (16 percentage points; p < 0.0001) and medication use (4 percentage points; p < 0.0001) compared with those denying symptoms. Among patients reporting symptoms, women and nonwhite patients were less likely to receive a DPN diagnosis, whereas older patients were more likely to receive a DPN diagnosis. Overall, patients who were older, were Asian (hazard ratio = 0.67, 95% confidence interval = 0.63-0.77), and had lower socioeconomic status (hazard ratio = 0.89, 95% confidence interval = 0.80-0.99) were less likely to be treated. However, these racial and socioeconomic differences were not statistically significant for patients with preexisting DPN diagnoses. CONCLUSION: Patients' real-time reports of DPN symptoms were associated with increased clinical activity. Patient- and clinician-level factors associated with the likelihood of receiving a DPN diagnosis need further study because a formal diagnosis may be associated with more equitable treatment.

Population Health Management for Diabetes: Health Care System-Level Approaches for Improving Quality and Addressing Disparities.

PURPOSE OF REVIEW: Population care approaches for diabetes have the potential to improve the quality of care and decrease diabetes-related mortality and morbidity. Population care strategies are particularly relevant as accountable care organizations (ACOs), patient-centered medical homes (PCMH), and integrated delivery systems are increasingly focused on managing chronic disease care at the health system level. This review outlines the key elements of population care approaches for diabetes in the current health care environment. RECENT FINDINGS: Population care approaches proactively identify diabetes patients through disease registries and electronic health record data and utilize multidisciplinary care teams, personalized provider feedback, and decision support tools to target and care for patients at risk for poor outcomes. Existing evidence suggests that these strategies can improve care outcomes and potentially ameliorate existing race/ethnic disparities in health care. However, such strategies may be less effective for patients who are disengaged from the health care system. As population care for diabetes continues to evolve, future initiatives should consider ways to tailor population care to meet individual patient needs, while leveraging improvements in clinical information systems and care integration to optimally manage and prevent diabetes in the future.

Extending supplementary feeding for children younger than 5 years with moderate acute malnutrition leads to lower relapse rates.

OBJECTIVES: Children with moderate acute malnutrition (MAM) have a high rate of relapse and death in the year following recovery. In this pilot study, we evaluate the long-term benefits of an extended course of nutritional therapy for children with MAM. METHODS: Rural Malawian children 6 to 59 months old with MAM, defined as a weight-for-height z score (WHZ) between -2 and -3, were provided supplementary feeding for a fixed duration of 12 weeks. The children were then studied for 12 months to assess long-term nutritional status, and compared with children initially treated only until they first reached WHZ > -2. RESULTS: Compared with children treated until they reached WHZ > -2, children treated for 12 weeks were more likely to remain well nourished (71% vs 63%, P = 0.0015) and maintain more normal anthropometric indices during 12 months of follow-up; there was also a trend towards lower rates of severe acute malnutrition (7% vs 10%, P = 0.067) and death (2% vs 4%, P = 0.082). Regression modeling showed that mid-upper arm circumference and WHZ at the end of supplementary feeding were the most important factors in predicting which children remained well nourished (P < 0.001 for each). CONCLUSIONS: The duration of supplementary feeding for children with MAM may not be as important as their anthropometry in terms of remaining well nourished after initial recovery. The presently accepted recovery criteria of WHZ of -2 may be insufficient for ensuring long-term nutritional health; consideration should be given to setting higher recovery criteria.