Older Adult Frequent 9-1-1 Callers for Emergency Medical Services in a Large Metropolitan City: Individual- and System-Level Considerations.

BACKGROUND: High utilizers of 9-1-1 place a substantial burden on emergency medical services (EMS). Results of a retrospective review of records data of the City of Los Angeles Fire Department (LAFD) showed a significant increase in older adult high utilizers of 9-1-1. OBJECTIVE: The objective of this study was to explore individual- and system-level factors implicated in EMS use among older adults, and to provide system recommendations to mitigate overuse. METHODS: A phenomenological study was conducted, drawing from LAFD EMS records between 2012 and 2016 to identify and contact high-utilizing patients older than 50 years, their family, agency representatives, and LAFD personnel. Interviews were recorded, transcribed, and coded and a thematic analysis was completed. RESULTS: We conducted in-depth interviews with 27 participants, including patients (n = 8), their families (n = 6), social service agency representatives (n = 3), and LAFD personnel (n = 10). The following cross-cutting themes emerged: nature of 9-1-1 calls, barriers to access, and changing the system. In addition, LAFD and social service agency representatives identified the role of EMS responders and social agency representatives. Patients and their families agreed that previous encounters and interactions with emergency care responders were relevant factors. CONCLUSIONS: This study described reasons for 9-1-1 calls related to medical and social service needs, including mental health care. Our analysis offers insight from different stakeholders' perspectives on access to medical care and types of barriers that interfere with medical care. All groups shared recommendations to advance access to medical and mental health care.

Data mining-based clinical profiles of substance use-related emergency department utilizers.

OBJECTIVE: Substance-use is a prevalent presentation to the emergency department (ED); however, the clinical characterization of patients who are treated and discharged without admission for further treatment is under-investigated. The study aims to define and characterize the clinical profiles of this patient population. METHODS: Patients' presentations were examined by clinical data mining (chart review) of ED records of substance use-related events of individuals discharged without admission for further treatment. Records (N = 199) from three major hospitals in New York City from March and June 2017 were randomly sampled with primary diagnosis of alcohol, opioid-related and other psychoactive substance-use presentations. Qualitative thematic coding of clinical presentation with inter-rater reliability was performed. Quantitative distinctive validity tested independence through Pearson's chi-squared and analysis of variance using Fisher's F-test. RESULTS: Six distinct clinical profiles were identified, including, High Utilizers (chronically intoxicated with comorbid health conditions) (36.7%), Single Episode (20.1%), Service Request (14.1%), Altered Mental Status (13.6%), Overdose (9.0%), and Withdrawal (7.5%). The profiles differed (p < 0.05) in age, housing status, payor, mode of arrival, referral source, index visit time, prescribed treatment, triage acuity level, psychiatric history, and medical history. Differences (p < 0.05) between groups across clinical profiles in age and pain level at triage were observed. CONCLUSIONS: The identified clinical profiles represent the broad spectrum and complex nature of substance use-related ED utilization, highlighting critical factors of psychosocial and mental-health comorbidities. These findings provide a preliminary foundation to support person-centered interventions to decrease substance use-related ED utilization and to increase engagement/linkage of patients to addiction treatment.

Impact of Social Needs Navigation on Utilization Among High Utilizers in a Large Integrated Health System: a Quasi-experimental Study.

BACKGROUND: Programs addressing social determinants of health for high-utilizing patients are gaining interest among health systems as an avenue to promote health and decrease utilization. OBJECTIVE: To evaluate impacts of a social needs screening and navigation program for adult predicted high utilizers on total medical visit utilization. DESIGN: A prospective, quasi-experimental study using an intent-to-treat propensity-weighted difference-in-differences approach. Stratified analyses assessed intervention effects among three low-socioeconomic status sub-samples: patients in low-income areas, in low-education areas, and with Medicaid insurance. PARTICIPANTS: Predicted high utilizers-patients predicted to be in the highest 1% for total utilization in a large integrated health system. INTERVENTION: A telephonic social needs screening and navigation program. MAIN MEASURES: Primary difference-in-difference analyses compared total visit count utilization, including outpatient, emergency department (ED), and inpatient utilization, between the intervention and control groups at both in-network and out-of-network facilities. Prevalence of social needs among sample patients and their connection rates to social needs resources are also described. KEY RESULTS: The study included 34,225 patients (7107 intervention, 27,118 control). Most (53%) patients screened reported social needs, but only a minority (10%) of those with a need were able to connect with resources to address these needs. Primary analysis found total utilization visits decreased 2.2% (95% CI - 4.5%, 0.1%; p = 0.058) in the intervention group. Stratified analyses showed decreases in total utilization for all low-socioeconomic status subgroups receiving the intervention compared with controls: - 7.0% (95% CI - 11.9%, - 1.9%; p = 0.008) in the low-income area group, - 11.5% (- 17.6%, 5.0%; p < 0.001) in the low-education area group, and - 12.1% (- 18.1%, - 5.6%; p < 0.001) in the Medicaid group. CONCLUSIONS: Social needs navigation programs for high-utilizing patients may have modest effects on utilization for the population overall. However, significant decreases in utilization were found among low-socioeconomic status patients more likely to experience social needs.

Impact of an individual plan of care for frequent and high utilizers in a large healthcare system.

INTRODUCTION: "Frequent or High Utilizers" are significant stressors to Emergency Departments (EDs) and Inpatient Units across the United States (US). These patients incur higher healthcare costs with ED visits and inpatient admissions. Our aims were to determine whether implementation of individualized care plans (ICPs) could 1) reduce costs, 2) reduce inpatient length of stay (LOS), and 3) reduce ED encounters throughout a large healthcare system. METHODS: 13 EDs were included including academic, community, Free-standing and pediatric EDs. Data was collected from January 1, 2014 through December 31, 2017. ICPs were created for high ED utilizers, as recommended by staff input through multidisciplinary care committees at each site. The ICP consisted of 1) specific symptom-related information with approaches in management, 2) recent assessment from specialists, 3) social work summary, and 4) psychiatry summary. A Best Practice Alert was placed in the electronic medical record that could be seen at all hospitals within the system. ICP's were updated annually. RESULTS: 626 ICPs were written; 452 initial ICPs and 174 updates. The 452 ICP patients accounted for 23,705 encounters during the four-year period; on average, an ICP patient visited the ED 52 times (14.75 encounters/year). Overall indirect and direct costs decreased 42% over first 6 months, inpatient LOS improved from 1.9 to 0.97 days/month, and ED encounters decreased from 1.96 to 1.14. All cost and LOS data significantly improved at 24 months post-ICP inception. CONCLUSION: Implementation of individualized care plan can reduce cost, inpatient LOS, and ED encounters for high utilizers.

Expenditure variations analysis using residuals for identifying high health care utilizers in a state Medicaid program.

BACKGROUND: High utilizers receive great attention in health care research because they have a largely disproportionate spending. Existing analyses usually identify high utilizers with an empirical threshold on the number of health care visits or associated expenditures. However, such count-and-cost based criteria might not be best for identifying impactable high utilizers. METHODS: We propose an approach to identify impactable high utilizers using residuals from regression-based health care utilization risk adjustment models to analyze the variations in health care expenditures. We develop linear and tree-based models to best adjust per-member per-month health care cost by clinical and socioeconomic risk factors using a large administrative claims dataset from a state public insurance program. RESULTS: The risk adjustment models identify a group of patients with high residuals whose demographics and categorization of comorbidities are similar to other patients but who have a significant amount of unexplained health care utilization. Deeper analysis of the essential hypertension cohort and chronic kidney disease cohort shows these variations in expenditures could be within individual ICD-9-CM codes and from different mixtures of ICD-9-CM codes. Additionally, correlation analysis with 3M™ Potentially Preventable Events (PPE) software shows that a portion of this utilization may be preventable. In addition, the high utilizers persist from year to year. CONCLUSIONS: After risk adjustment, patients with higher than expected expenditures (high residuals) are associated with more potentially preventable events. These residuals are temporally consistent and hence may be useful in identifying and intervening impactable high utilizers.

Characterization, Categorization, and 5-Year Mortality of Medicine High Utilizer Inpatients.

BACKGROUND: Patients who are frequently admitted to Medicine inpatient services comprise a distinct subset of readmitted patients about whom not much is known. OBJECTIVE: We sought to characterize this group including mortality rates, with the goal of better understanding this population. DESIGN: Observational study of frequently hospitalized patients defined as 4 or more admissions over a 6-month period, with hospitalization defined as nonelective admission to the hospital. SETTING: Single large academic medical center. PATIENTS: Adult inpatients on general medicine and medicine subspecialty services. MEASUREMENTS: The number of nonelective medicine hospitalizations, age, clinical conditions and comorbidities, calculation of an age-adjusted Charlson Comorbidity Index (CCI), outpatient and emergency department visits, length of stay, costs of hospitalization, and mortality over a 5-year period. Descriptive statistics were used to characterize variables of interest. RESULTS: We identified 153 patients with a total of 781 nonelective hospitalizations, totaling greater than 4000 hospital days and with charges of approximately US$9 million during the 6 months. Nearly all had insurance coverage and good outpatient follow-up (median of 7 appointments over the 6-month study period). Only 14% of those admissions qualified for observation status. Over 40% of patients had comorbid mental health disease or chronic narcotic dependence. Twenty-nine percent of patients died within 1 year; 50% were dead within 5 years. Age-adjusted CCI scores ranged annually from 3.00 to 3.58 among surviving patients versus 4.31 to 6.60 among deceased patients. CONCLUSIONS: These findings point to distinct groups of patients who are frequently hospitalized, and therefore would benefit from tailored management strategies: Those with progression of end-stage disease comprised one-third of the group and targeting that subset with palliative care referrals could help decrease readmission rates. Those with recurrent exacerbations of a chronic medical condition could be managed through telemanagement programs. Those with exacerbations of chronic pain could be addressed through collaboration with pain management specialists. Individualized care management plans may be useful for all, especially the latter two groups. Based on differences between survivors and deceased patients, an age-adjusted CCI score of 4 or 5 could be valuable sensitive or specific cutoffs, respectively, for predicting those who would benefit most from palliative care consultation regarding end-of-life goals and management.

Factors associated with high-utilization in a safety net setting.

BACKGROUND: Patients with frequent hospital readmissions, or high-utilizer patients (HUPs), are a major driver of rising healthcare costs in the United States. This group has a significant burden of medical illness, but less is known about whether or how social determinants of health may drive their increased healthcare use and poor health outcomes. Our study aimed to define the population of HUPs at a large, safety-net hospital system, to understand how these patients differ from patients who are not HUPs, and to analyze how their demographic, medical, and social factors contribute to their healthcare use and mortality rates. METHODS: For this case-control study, data were collected via retrospective chart review. We included 247 patients admitted three or more times in a single calendar year between 2011 and 2013 and 247 controls with one or two admissions in a single calendar year matched for age, sex, and year of high-utilization. We used multivariable logistic regression models to understand which demographic, clinical, and social factors were associated with HUP status, and if HUP status was independently associated with mortality. RESULTS: The factors that contributed significant odds of being a HUP included having Medicaid (OR 3.34, 95% CI 1.50, 7.44) or Medicare (OR 3.39, 95% CI 1.50, 7.67), having a history of recreational drug use (OR 2.44, 95% 1.36, 4.38), and being homeless (OR 3.73, 95% CI 1.69, 8.23) The mortality rate among HUPs was 22.6% compared to 8.9% among controls (p < 0.0001). CONCLUSIONS: These data show that social factors are related to high-utilization in this population. Future efforts to understand and improve the health of this population need to incorporate non-clinical patient factors.

Factors associated with emergency department useamong veteran psychiatric patients.

Frequent utilization of emergency department (ED) services contributes substantially to the cost of healthcare nationally and is often driven by psychiatric factors. Using national-level data from the Veterans Health Administration (VHA), the present study examined patient-level factors associated with ED use among veteran psychiatric patients. Veterans who had at least one ED visit with a psychiatric diagnosis in fiscal years 2011-2012 (n = 226,122) were identified in VHA administrative records. Andersen's behavioral model of healthcare utilization was used to identify need, enabling, and predisposing factors associated with frequency of ED use (primary outcome) in multivariate regression models. Greater ED use was primarily linked with need (psychotic, anxiety, personality, substance use, and bipolar disorders) and enabling (detoxification-related service utilization and homelessness) factors. Chronic medical conditions, receipt of an opioid prescription, and predisposing factors (e.g., younger age) were also linked to greater ED use; however, the effect sizes for these factors were markedly lower than those of most psychiatric and psychosocial factors. The findings suggest that intensive case management programs aimed reducing frequent ED use among psychiatric patients may require greater emphasis on homelessness and other psychosocial deficits that are common among these patients, and future research should explore cost-effective approaches to implementing these programs.

Overutilization of ambulatory medical care in the elderly German population?--An empirical study based on national insurance claims data and a review of foreign studies.

BACKGROUND: By definition, high utilizers receive a large proportion of medical services and produce relatively high costs. The authors report the results of a study on the utilization of ambulatory medical care by the elderly population in Germany in comparison to other OECD countries. Evidence points to an excessive utilization in Germany. It is important to document these utilization figures and compare them to those in other countries since the healthcare system in Germany stopped recording ambulatory healthcare utilization figures in 2008. METHODS: The study is based on the claims data of all insurants aged ≥ 65 of a statutory health insurance company in Germany (n = 123,224). Utilization was analyzed by the number of contacts with physicians in ambulatory medical care and by the number of different practices contacted over one year. Criteria for frequent attendance were ≥ 50 contacts with practices or contacts with ≥ 10 different practices or ≥ 3 practices of the same discipline per year. Descriptive statistical analysis and logistic regression were applied. Morbidity was analyzed by prevalence and relative risk for frequent attendance for 46 chronic diseases. RESULTS: Nineteen percent of the elderly were identified as high utilizers, corresponding to approximately 3.5 million elderly people in Germany. Two main types were identified. One type has many contacts with practices, belongs to the oldest age group, suffers from severe somatic diseases and multimorbidity, and/or is dependent on long-term care. The other type contacts large numbers of practices, consists of younger elderly who often suffer from psychiatric and/or psychosomatic complaints, and is less frequently multimorbid and/or nursing care dependent. CONCLUSION: We found a very high rate of frequent attendance among the German elderly, which is unique among the OECD countries. Further research should clarify its reasons and if this degree of utilization is beneficial for elderly people.

Effects of a Psychosocial Transitional Care Model on Hospitalizations and Cost of Care for High Utilizers.

Evidence of care coordination programs to reduce readmissions is limited. We examined whether a social work transitional care model reduced hospital utilization and costs with a retrospective cohort study conducted from 9/3/2010-8/31/2012. Patients enrolled in the Preventable Admissions Care Team (PACT) program were matched to controls. PACT patients received follow-up from a social worker to address psychosocial strain. PACT reduced thirty-day readmission rate by 34% (p = <0.001), Sixty-day hospitalization rate by 22% (p = 0.004); ninety-day hospitalization rate by 19% (p = 0.006), and but not 180-day hospitalization rate. Inpatient costs thirty days post-index were $2.7 million for PACT patients and $3.6 million for controls.

Prevalence of anxiety disorders among Finnish primary care high utilizers and validation of Finnish translation of GAD-7 and GAD-2 screening tools.

OBJECTIVE: To analyse the prevalence of GAD and other anxiety disorders, as well as sensitivity and specificity of GAD-7 among high utilizers of health care. SETTING: Four municipal health centres in Northern Finland. SUBJECTS: A psychiatric interview was conducted for 150 high utilizers of health care. MAIN OUTCOME MEASURES: Prevalence of GAD as well as sensitivity and specificity of GAD-7. RESULTS: The prevalence of GAD was 4% in this study group of Finnish high utilizers of health care. The sensitivity of GAD-7 was 100.0% (95% CI 54.1-100.0) and the specificity of GAD-7 was 82.6% (95% CI 75.4-88.4) with a cut-off point of 7 or more. CONCLUSION: GAD is rather common among high utilizers of primary care, although the prevalence of 4% is lower than that previously reported. GAD-7 is a valid and useful tool for detecting GAD among primary health care patients.

Characterizing hospitalization trajectories in the high-need, high-cost population using electronic health record data.

High utilization by a minority of patients accounts for a large share of health care costs, but the dynamics of this utilization remain poorly understood. We sought to characterize longitudinal trajectories of hospitalization among adult patients at an academic medical center from 2017 to 2023. Among 3404 patients meeting eligibility criteria, following an initial "rising-risk" period of 3 hospitalizations in 6 months, growth mixture modeling discerned 4 clusters of subsequent hospitalization trajectories: no further utilization, low chronic utilization, persistently high utilization with a slow rate of increase, and persistently high utilization with a fast rate of increase. Baseline factors associated with higher-order hospitalization trajectories included admission to a nonsurgical service, full code status, intensive care unit-level care, opioid administration, discharge home, and comorbid cardiovascular disease, end-stage kidney or liver disease, or cancer. Characterizing hospitalization trajectories and their correlates in this manner lays groundwork for early identification of those most likely to become high-need, high-cost patients.

Trends and drivers of pharmaceutical expenditures from systemic anti-cancer therapy.

Expenditures on medicine for systemic anti-cancer therapy (SACT) have seen large increases in recent years. The characterization of patients with high SACT costs is crucial to identify cost-driving factors, but little is known about the distribution of expenditures at the patient-level. We priced 260,834 registrations of SACT for 12,589 patients from 2008 to 2019 by combining them with product-level billings of EUR 142.1 million. Based on this, we defined high-cost patients as the 2.5% most expensive by accumulated SACT expenditures. We found that high-cost patients accounted for 28.8% of the total SACT expenditures and were observed across all major cancer groups except for pancreatic cancer. The risk of becoming a high-cost patient was increased for younger age groups, i.e., 18-44 and 45-64 years, for patients with BMI ≥ 25, and for patients with multiple cancer diagnoses, while no alteration of risk was observed due to comorbidities or sex. Changes in the characteristics of high-cost patients during the study period were found with an increased risk of becoming high-cost in later years for elderly patients and patients with lung cancer and a decreased risk for breast cancer patients.

Improving the Prediction of Persistent High Health Care Utilizers: Retrospective Analysis Using Ensemble Methodology.

BACKGROUND: A small proportion of high-need patients persistently use the bulk of health care services and incur disproportionate costs. Population health management (PHM) programs often refer to these patients as persistent high utilizers (PHUs). Accurate PHU prediction enables PHM programs to better align scarce health care resources with high-need PHUs while generally improving outcomes. While prior research in PHU prediction has shown promise, traditional regression methods used in these studies have yielded limited accuracy. OBJECTIVE: We are seeking to improve PHU predictions with an ensemble approach in a retrospective observational study design using insurance claim records. METHODS: We defined a PHU as a patient with health care costs in the top 20% of all patients for 4 consecutive 6-month periods. We used 2013 claims data to predict PHU status in next 24 months. Our study population included 165,595 patients in the Johns Hopkins Health Care plan, with 8359 (5.1%) patients identified as PHUs in 2014 and 2015. We assessed the performance of several standalone machine learning methods and then an ensemble approach combining multiple models. RESULTS: The candidate ensemble with complement naïve Bayes and random forest layers produced increased sensitivity and positive predictive value (PPV; 49.0% and 50.3%, respectively) compared to logistic regression (46.8% and 46.1%, respectively). CONCLUSIONS: Our results suggest that ensemble machine learning can improve prediction of care management needs. Improved PPV implies reduced incorrect referral of low-risk patients. With the improved sensitivity/PPV balance of this approach, resources may be directed more efficiently to patients needing them most.

The Role of Using HEART Score to Risk Stratify Chest Pain Among Emergency Department High Utilizers.

The HEART score is used to effectively risk stratify undifferentiated chest pain patients in the Emergency Department (ED). It is unclear whether such risk stratification can be applied among ED high utilizers. We aim to determine the efficacy and safety of using the HEART score to predict 30-day short-term major adverse cardiac events (MACE) in ED high utilizers. We conducted a retrospective, observational study in which ED high utilizers were defined as patients who had four or more ED visits within the past 12 months. ED high utilizers presenting at the study ED with chest pain were enrolled. Patients in which the HEART score was utilized were placed in the HEART group and patients with no HEART scores documented were placed to the usual care group. Hospital admissions and cardiac stress tests performed during the index hospitalizations, and 30-day MACE rates were analyzed and compared between the HEART and usual care groups. From January 1, 2017 to December 31, 2019, a total of 8,315 patient visits from ED high utilizers were enrolled. In the HEART group, 49% of ED visits were admitted with 20% receiving stress tests. A 30-day MACE outcome occurred among 1.4% of visits. In the usual care group, 44% of ED visits were admitted, with only 9% receiving index stress tests and a 1.5% of 30-day MACE occurrence (p=0.727). The study showed that similar short-term MACE outcomes occurred between patients using HEART scores and usual care to risk stratify chest pain among ED high utilizers.

[Hiperfrequency in mental health hospital emergencies: case-control study.] / Hiperfrecuentación en Urgencias Hospitalarias de Salud Mental: Estudio caso-control.

OBJECTIVE: To ensure the efficiency of the operation of the Emergency Department, specific mental health studies are needed. The purpose of the study was to identify and quantify the sociodemographic, clinical and organizational factors associated with the hyperfrequency of hospital Mental Health emergency departments in the three central areas of Asturias. METHODS: A retrospective case-control study was carried out. A total of 110 hyperfrequenters were recorded in 2017, based on a definition of five or more visits to the emergency department. The control group was composed of 170 subjects who attended on one occasion. In addition to descriptive analysis, Chi-square and ANOVA tests were used to identify differences between the two groups. A multivariate study was also carried out using binomial logistic regression. RESULTS: Hyperfrequent users were more likely to be young adult (30-44 years old), single, living with their family of origin, and with no jobs. The most prevalent diagnoses for these users were "Personality and Behavior Disorder" (F60-69) and "Schizophrenia, Schizotypal Disorders and Delusional Disorders" (F20-29). The most frequent reason for consultation was "anxiety/depression/somatization symptoms". The destination of the most frequent emergency was "Continue follow-up at scheduled appointments" and most consultations were made in the morning and on weekdays. CONCLUSIONS: Hyperfrequent users continue to demand attention despite being assigned one or more devices. Knowing their needs would help to improve healthcare and use resources more efficiently and effectively.

OBJETIVO: Para garantizar la eficiencia del funcionamiento del Servicio de Urgencias es necesario realizar estudios específicos de Salud Mental. El propósito del estudio fue identificar y cuantificar los factores sociodemográficos, clínicos y organizativos asociados con la hiperfrecuentación de las Urgencias Hospitalarias del Servicio de Salud Mental de las tres áreas sanitarias centrales de Asturias. METODOS: Se realizó un estudio retrospectivo de tipo casos-controles. Se registraron 110 hiperfrecuentadores en el año 2017, basándonos en una definición de cinco o más visitas al servicio de Urgencias. El grupo control lo compusieron 170 sujetos que acudieron en una sola ocasión. Además del análisis descriptivo, se utilizaron las pruebas Chi cuadrado y ANOVA para identificar diferencias entre ambos grupos. También se realizó un estudio multivariado mediante regresión logística binomial. RESULTADOS: Los usuarios hiperfrecuentadores eran más probablemente adultos jóvenes (30-44 años), solteros, convivientes con la familia de origen e inactivos laboralmente. Los diagnósticos más prevalentes para estos usuarios eran: "Trastorno de la personalidad y el comportamiento" (F60-69) y "Esquizofrenia, trastornos esquizotípicos y trastornos delirantes" (F20-29). El motivo de consulta más frecuente era "Síntomas de ansiedad/depresión/somatizaciones". El destino de la urgencia más frecuente fue "Continuar seguimiento en citas programadas" y la mayor parte de las consultas se realizaron en horario de mañana y en días laborables. CONCLUSIONES: Los usuarios hiperfrecuentadores continúan demandando atención a pesar de tener asignados uno o varios dispositivos de la red de salud mental. Conocer sus necesidades ayudaría a mejorar la atención sanitaria y a utilizar los recursos de manera más eficiente y eficaz.

Assessing the Value of Unsupervised Clustering in Predicting Persistent High Health Care Utilizers: Retrospective Analysis of Insurance Claims Data.

BACKGROUND: A high proportion of health care services are persistently utilized by a small subpopulation of patients. To improve clinical outcomes while reducing costs and utilization, population health management programs often provide targeted interventions to patients who may become persistent high users/utilizers (PHUs). Enhanced prediction and management of PHUs can improve health care system efficiencies and improve the overall quality of patient care. OBJECTIVE: The aim of this study was to detect key classes of diseases and medications among the study population and to assess the predictive value of these classes in identifying PHUs. METHODS: This study was a retrospective analysis of insurance claims data of patients from the Johns Hopkins Health Care system. We defined a PHU as a patient incurring health care costs in the top 20% of all patients' costs for 4 consecutive 6-month periods. We used 2013 claims data to predict PHU status in 2014-2015. We applied latent class analysis (LCA), an unsupervised clustering approach, to identify patient subgroups with similar diagnostic and medication patterns to differentiate variations in health care utilization across PHUs. Logistic regression models were then built to predict PHUs in the full population and in select subpopulations. Predictors included LCA membership probabilities, demographic covariates, and health utilization covariates. Predictive powers of the regression models were assessed and compared using standard metrics. RESULTS: We identified 164,221 patients with continuous enrollment between 2013 and 2015. The mean study population age was 19.7 years, 55.9% were women, 3.3% had ≥1 hospitalization, and 19.1% had 10+ outpatient visits in 2013. A total of 8359 (5.09%) patients were identified as PHUs in both 2014 and 2015. The LCA performed optimally when assigning patients to four probability disease/medication classes. Given the feedback provided by clinical experts, we further divided the population into four diagnostic groups for sensitivity analysis: acute upper respiratory infection (URI) (n=53,232; 4.6% PHUs), mental health (n=34,456; 12.8% PHUs), otitis media (n=24,992; 4.5% PHUs), and musculoskeletal (n=24,799; 15.5% PHUs). For the regression models predicting PHUs in the full population, the F1-score classification metric was lower using a parsimonious model that included LCA categories (F1=38.62%) compared to that of a complex risk stratification model with a full set of predictors (F1=48.20%). However, the LCA-enabled simple models were comparable to the complex model when predicting PHUs in the mental health and musculoskeletal subpopulations (F1-scores of 48.69% and 48.15%, respectively). F1-scores were lower than that of the complex model when the LCA-enabled models were limited to the otitis media and acute URI subpopulations (45.77% and 43.05%, respectively). CONCLUSIONS: Our study illustrates the value of LCA in identifying subgroups of patients with similar patterns of diagnoses and medications. Our results show that LCA-derived classes can simplify predictive models of PHUs without compromising predictive accuracy. Future studies should investigate the value of LCA-derived classes for predicting PHUs in other health care settings.

A "Behind-the-Scenes" Look at Interprofessional Care Coordination: How Person-Centered Care in Safety-Net Health System Complex Care Clinics Produce Better Outcomes.

INTRODUCTION: While the effectiveness of team-based care and wrap-around services for high utilizers is clear, how complex care clinics deliver effective, person-centered care to these vulnerable populations is not well understood. This paper describes how interactions among interprofessional team members enabled individualized, rapid responses to the complex needs of vulnerable patients at the Virginia Commonwealth University Health System's Complex Care Clinic. METHODS: Researchers attended twenty weekly care coordination meetings, audio-recorded the proceedings, and wrote brief observational field notes. Researchers also qualitatively interviewed ten clinic team members. Emergent coding based on grounded theory and a consensus process were used to identify and describe key themes. RESULTS: Analysis resulted in three themes that evidence the structures, processes, and interactions which contributed to the ability to provide person-centred care: team-based communication strategies, interprofessional problem-solving, and personalized patient engagement efforts. CONCLUSION: Our study suggests that in care coordination meetings team members were able to strategize, brainstorm, and reflect on how to better care for patients. Specifically, flexible team leadership opened an inter-disciplinary communicative space to foster conversations, which revealed connections between the physical, and socio-emotional components of patients' lives and hidden factors undermining progress, while proactive strategies prevented patient's rapid deterioration and unnecessary use of inappropriate health services.

Evaluation of a Pharmacist-Based Intervention to Reduce Readmissions in Geriatric High-Utilizer Patients: A Pilot Study.

PURPOSE: The goal of this study was to determine if a pharmacist-led intervention to improve medication safety at hospital discharge reduced the number of hospital readmissions among geriatric high-utilizer patients. This study is the first to test a pharmacist-based intervention in a high-utilizer population. METHODS: This was a quasi-experimental pilot study done at a safety-net hospital in the southeastern US. Fifty-seven patients 65 years old and older who were in the 95th percentile for number of hospital admissions in a year were included. On the day of discharge, one of the study pharmacists reviewed the discharge medication list and calculated the Medication Appropriateness Index (MAI) for each medication and reviewed for Beers Criteria. Any medication identified as potentially high-risk or inappropriate was flagged by the pharmacist and discussed with the team. The primary outcome was the number of admissions in the year following the intervention in the intervention group versus the control group. RESULTS: There were no statistically significant differences in the number of admissions, the MAI scores, or the number of medications meeting Beers Criteria between the two groups. CONCLUSION: Although this study did not demonstrate a decrease in hospital admissions, it shows that pharmacist review of medications at discharge can identify potentially unnecessary medications that could lead to confusion or adverse events. Further research is necessary to identify interventions to prevent readmissions in this high-risk population.