Prior Health Care Utilization Research Articles

Frailty Screening Using the Electronic Health Record Within a Medicare Accountable Care Organization.

The accumulation of deficits model for frailty has been used to develop an electronic health record (EHR) frailty index (eFI) that has been incorporated into British guidelines for frailty management. However, there have been limited applications of EHR-based approaches in the United States. We constructed an adapted eFI for patients in our Medicare Accountable Care Organization (ACO, N = 12,798) using encounter, diagnosis code, laboratory, medication, and Medicare Annual Wellness Visit (AWV) data from the EHR. We examined the association of the eFI with mortality, health care utilization, and injurious falls. The overall cohort was 55.7% female, 85.7% white, with a mean age of 74.9 (SD = 7.3) years. In the prior 2 years, 32.1% had AWV data. The eFI could be calculated for 9,013 (70.4%) ACO patients. Of these, 46.5% were classified as prefrail (0.10 < eFI ≤ 0.21) and 40.1% frail (eFI > 0.21). Accounting for age, comorbidity, and prior health care utilization, the eFI independently predicted all-cause mortality, inpatient hospitalizations, emergency department visits, and injurious falls (all p < .001). Having at least one functional deficit captured from the AWV was independently associated with an increased risk of hospitalizations and injurious falls, controlling for other components of the eFI. Construction of an eFI from the EHR, within the context of a managed care population, is feasible and can help to identify vulnerable older adults. Future work is needed to integrate the eFI with claims-based approaches and test whether it can be used to effectively target interventions tailored to the health needs of frail patients.

Disparities in health outcomes among seniors without a family physician in the North West Local Health Integration Network: a retrospective cohort study.

The relationship between having a family physician and in-hospital and postdischarge health outcomes among older adults is unclear. We ascertained the proportion of seniors who did not have a family physician and were admitted to an Ontario tertiary care centre, and we determined the association between having/not having a family physician and in-hospital mortality, 1-year mortality and readmission after live discharge. This was a retrospective cohort study of community-dwelling seniors who were admitted to a medical service at Thunder Bay Regional Health Sciences Centre. We conducted regression analyses adjusted for demographic factors, prior health care utilization, and factors associated with the index admission to determine the association between family physician status and the study outcomes. Among the 12 033 seniors admitted to hospital between Apr. 1, 2004, and Mar. 31, 2013, 40.7% lacked a family physician. Among those without a family physician, 8.0% (390/4899) died during the index admission and 15.8% (714/4509) died in the subsequent year. Adjusted regression models showed that not having a family physician was significantly associated with in-hospital mortality (odds ratio 1.56, 95% confidence interval [CI] 1.33-1.83). Regression models of all-cause 1-year mortality and readmission also suggested that lack of a family physician was associated with detrimental health outcomes (hazard ratio 1.14, 95% CI 1.04-1.26; subdistribution hazard ratio 1.17, 95% CI 1.10-1.24, respectively). Elders without family physicians were disadvantaged during their hospital admission as well as in the subsequent year. Additional interventions aimed at increasing the proportion of seniors admitted to hospital who are connected with a family physician are warranted.

Increasing Age Has Limited Impact on Risk of Clostridium difficile Infection in an Elderly Population.

BackgroundNumerous studies have found increased risk of Clostridium difficile infection (CDI) with increasing age. We hypothesized that increased CDI risk in an elderly population is due to poorer overall health status with older age.MethodsA total of 174 903 persons aged 66 years and older coded for CDI in 2011 were identified using Medicare claims data. The comparison population consisted of 1 453 867 uninfected persons. Potential risk factors for CDI were identified in the prior 12 months and organized into categories, including infections, acute noninfectious conditions, chronic comorbidities, frailty indicators, and health care utilization. Multivariable logistic regression models with CDI as the dependent variable were used to determine the categories with the biggest impact on model performance.ResultsIncreasing age was associated with progressively increasing risk of CDI in univariate analysis, with 5-fold increased risk of CDI in 94–95-year-old persons compared with those aged 66–67 years. Independent risk factors for CDI with the highest effect sizes included septicemia (odds ratio [OR], 4.1), emergency hospitalization(s) (OR, 3.9), short-term skilled nursing facility stay(s) (OR, 2.7), diverticulitis (OR, 2.2), and pneumonia (OR, 2.1). Exclusion of age from the full model had no impact on model performance. Exclusion of acute noninfectious conditions followed by frailty indicators resulted in lower c-statistics and poor model fit. Further exclusion of health care utilization variables resulted in a large drop in the c-statistic.ConclusionsAge did not improve CDI risk prediction after controlling for a wide variety of infections, other acute conditions, frailty indicators, and prior health care utilization.

Cost as the Main Driver of T2D Treatment Patterns—Lessons from Real-World Data and Physician Focus Groups

This two-phased study consists of a decision tree model built from real-world claims data to determine factors related to physician choice of 2nd line therapy for type 2 diabetes (T2D) patients after metformin, followed by a physician focus group study to validate results of the data-driven approach. We identified 58patients in the U.S. who initiated sulfonylurea (SU), DPP-4 inhibitor, GLP-1-RA, or insulin after metformin during 2012-2014 from the HealthCore Integrated Research Database. Claims-derived factors, such as demographics, clinical characteristics, and prior healthcare utilization and costs, were selected from a classification and regression tree (CART) model that minimized classification errors. Of factors most predictive of 2nd line drug assignment, patients’ cost sharing for antidiabetic drugs (Relative Importance, RI=1) was 3 times more important than HbA1c level (RI=0.3), and 10 times more important than age, comorbidity, and kidney status (GFR) (RI=0.1). SU was most likely to be assigned to patients with lowest drug spending, moderate HbA1c control, abnormal kidney function, or no comorbid conditions. Similar themes were identified from the four physician focus groups (consisting of 8 endocrinologists and 10 PCPs in NYC and LA) and supported the findings. This study identified a gap in diabetes care where patients often receive SU due to lack of access to other treatment options. Disclosure S. Wu: None. A.D. Raval: None. J.J. Stephenson: None. X. Peng: Employee; Self; Eli Lilly and Company. H. Weisman: Employee; Self; Anthem, Inc. D.E. Faries: Employee; Self; Eli Lilly and Company.

Correlates of HPV vaccine initiation and provider recommendation among male adolescents, 2014 NIS-Teen

Vaccination is a safe and effective way to prevent Human Papillomavirus (HPV) infection and related cancers; however, HPV vaccine uptake remains low in the US. After the 2011 Advisory Committee on Immunization Practices (ACIP) recommendation for routine HPV vaccination of adolescent males, several studies have examined predictors for initiating the vaccine series in this population of interest, particularly with regard to provider recommendations. This study examined racial and ethnic differences for HPV vaccine initiation and provider recommendation in male adolescents. Based on prior HPV vaccine uptake estimates and healthcare utilization data, we hypothesized that minority adolescents would be more likely to initiate HPV vaccines, but less likely to receive a provider recommendation compared to white counterparts. We analyzed the 2014 National Immunization Survey-Teen (NIS-Teen), which included 10,753 male adolescents with provider-verified vaccination data in 50 US states, using multivariate logistic regression models to evaluate racial/ethnic differences in HPV vaccine initiation and provider recommendation. The odds of HPV vaccine initiation were 76 percent higher for Hispanic adolescents and 43 percent higher for non-Hispanic Other or Multiple race adolescents compared to white adolescents. Approximately half of parents reported receiving a provider recommendation for vaccination, with no significant difference in the odds of receiving a provider recommendation across racial/ethnic groups. Despite similar frequency of recommendations across racial and ethnic groups, male adolescents who are racial/ethnic minorities are more likely to initiate vaccination. Future research should focus on developing tailored interventions to increase HPV vaccine receipt among males of all racial/ethnic groups.

Pain catastrophizing is associated with poorer health-related quality of life in pediatric patients with sickle cell disease.

BackgroundSickle cell disease (SCD) is an inherited disorder of the red blood cells and is associated with chronic multisystem involvement. While SCD has been associated with poorer health-related quality of life (HRQoL), there is a paucity of data on the relationship of psychological covariates other than anxiety and depression and quality of life (QoL) in children with SCD.Materials and methodsWe performed a cross-sectional study of psychological factors, HRQoL, and pain-related outcomes in participants with SCD and race-matched controls as part of a larger study of experimental pain phenotyping.ResultsPain catastrophizing was inversely correlated with HRQoL measured by the PedsQL™ Generic Core Scale in children with SCD, while this was not noted in control participants. Psychological factors, such as anxiety and depressive symptoms, were also associated with poorer HRQoL in both children with SCD and controls. We did not find an association of psychological factors with prior health care utilization. Psychological factors such as anxiety and depressive symptoms were inversely correlated with pain interference, but not pain intensity in SCD.ConclusionCatastrophizing is associated with poorer HRQoL in SCD, but in this study, it was not associated with pain intensity or interference and health care utilization in children with SCD. Further studies are needed to fully define the association of psychological factors including catastrophizing with QoL, pain burden, and SCD outcomes.

PRM65 - Predictive Model for Earlier Diagnosis of Dementia Using Administrative Claims

Predictive models for earlier diagnosis of Alzheimer’s disease and related dementias (ADRD) that rely on variables requiring assessment during an office visit, such as cognitive function, body mass index, or lifestyle factors, may not be broadly applicable as that level of data may be inaccessible. The objective of this study was to build a predictive model for earlier diagnosis of ADRD that would be practical for low-burden implementation for a larger provider such as an integrated delivery system or insurance plan by incorporating prior health care utilization (HCU) information found in administrative claims data. We conducted a case-control study using data from the OptumLabs™ Data Warehouse. ADRD was defined using ICD-9 codes and prescription fills for anti-dementia medications. We included individuals with mild cognitive impairment and those with a prescription fill for anti-dementia medication but no ADRD diagnosis. Cases ≥18 years with a diagnosis between 2011-2014 were matched to controls without ADRD. HCU variables were incorporated into regression models along with comorbidities and symptoms. The derivation cohort comprised 24,521 cases and 95,464 controls. Final adjusted models were stratified by age. We obtained moderate accuracy (C-statistic 0.76) for the model among younger (<65 years) adults and poorer discriminatory ability (C-statistic 0.63) for the model among older adults (≥65years). Neurological and psychological disorders had the largest effect estimates. We have created age-stratified predictive models for earlier diagnosis of ADRD using information available in administrative claims. These models could be considered for inclusion in electronic health records to promote cognitive screening and earlier dementia recognition.

Predicting frequent emergency department use among children with epilepsy: A retrospective cohort study using electronic health data from 2 centers.

Among children with epilepsy, to develop and evaluate a model to predict emergency department (ED) use, an indicator of poor disease control and/or poor access to care. We used electronic health record data from 2013 to predict ED use in 2014 at 2 centers, benchmarking predictive performance against machine learning algorithms. We evaluated algorithms by calculating the expected yearly ED visits among the 5% highest risk individuals. We estimated the breakeven cost per patient per year for an intervention that reduced ED visits by 10%. We estimated uncertainty via cross-validation and bootstrapping. Bivariate analyses showed multiple potential predictors of ED use (demographics, social determinants of health, comorbidities, insurance, disease severity, and prior health care utilization). A 3-variable model (prior ED use, insurance, number of antiepileptic drugs [AEDs]) performed as well as the best machine learning algorithm at one center (N=2730; ED visits among top 5% highest risk, 3-variable model, mean = 2.9, interquartile range [IQR] = 2.7-3.1 vs Random Forest, mean = 2.9, IQR = 2.7-3.1), and superior at the second (N=784; mean = 2.5, IQR = 2.2-2.9 vs mean = 1.9, IQR = 1.6-2.5). The per-patient-per-year breakeven point using this model to identify high-risk individuals was $958 (95% confidence interval [CI] = $568-$1390) at one center and $1086 (95% CI = $886-$1320) at the second. Prior ED use, insurance status, and number of AEDs, taken together, predict future ED use for children with epilepsy. Our estimates suggest a program targeting high-risk children with epilepsy that reduced ED visits by 10% could spend approximately $1000 per patient per year and break even. Further work is indicated to develop and evaluate such programs.

Prospective Cohort Study of Hospitalized Adults With Advanced Cancer: Associations Between Complications, Comorbidity, and Utilization.

Inpatient hospital stays account for more than a third of direct medical cancer care costs. Evidence on factors driving these costs can inform planning of services, as well as consideration of equity in access. To measure the association between hospital costs, and demographic, clinical, and system factors, for a cohort of adults with advanced cancer. Prospective multisite cohort study. Four medical and cancer centers. Adults with advanced cancer admitted to a participating hospital between 2007 and 2011, excluding those with dementia. Final analytic sample included 1020 patients. With receipt of palliative care controlled for, the associations between hospital cost and patient factors were estimated. Factors covered the domains of demographics (age, sex, race), socioeconomics and systems (education, insurance, living will, proxy), clinical care (diagnoses, complications deemed to pose a threat to life or bodily functions, comorbidities, symptom burden, activities of daily living), and prior healthcare utilization (home help, analgesic prescribing). Direct hospital costs. A major (markedly abnormal) complication (+$8267; P < 0.01), a minor but not a major complication (+$5289; P < 0.01), and number of comorbidities (+$852; P < 0.01) were associated with higher cost, and admitting diagnosis of electrolyte disorders (-$4759; P = 0.01) and increased age (-$53; P = 0.03) were associated with lower cost. Complications and comorbidity burden drive inhospital utilization for adults with advanced cancer. There is little evidence of sociodemographic associations and no apparent impact of advance directives. Attempts to control growth of hospital cancer costs require consideration of how the most resource-intensive patients are identified promptly and prioritized for cost-effective care. Journal of Hospital Medicine 2017;12:407-413.

Physical Functioning Among Older Adults New to Long-Term Services and Supports.

To identify determinants of self-reported physical functioning (PF) among older adults new to long-term services and supports (LTSS). Using the International Classification of Function, Disability, and Health (ICF) framework, we conducted a secondary analysis of self-reported data on symptoms, basic/instrumental activities of daily living, quality of life, assistive devices, physical therapy needs, prior healthcare utilization, health status, and demographics from 470 older adults new to LTSS (Home/Community-Based n = 156; Assisted Living n = 156; Nursing Home n = 158). Multiple linear regression was used to identify associations between ICF constructs and self-reported PF (SF-12 Physical Composite Summary score [SF12PCS], lower scores indicate worse PF). LTSS recipients were mostly female (71%) and over age 80 (Mean: 80.9 years, SD: 8.7). LTSS recipients' mean SF12PCS score was 37.3 (SD 11.0), indicating overall low self-reported PF. LTSS recipients living in their homes (b = -3.35, p = .003) or assisted living facilities (b = -2.93, p = .012) had significantly lower mean scores compared to recipients in nursing homes. Higher SF12PCS scores were associated with fewer activities of daily living deficits (p < .001), and better quality of life (p < .001). Lower scores were associated with more symptoms (p < .001), poorer nutrition (p = .013), ambulation aid use (p < .001), and physical therapy (p < .026). Diverse health, activity, and environmental factors may facilitate early identification of new LTSS recipients most in need of interventions to optimize self-reported PF. Several health conditions may be targets for such interventions. Additional research is needed to evaluate and compare PF trajectories among older adults receiving LTSS in diverse settings.

FAM-FACE-SG: a score for risk stratification of frequent hospital admitters

BackgroundAn accurate risk stratification tool is critical in identifying patients who are at high risk of frequent hospital readmissions. While 30-day hospital readmissions have been widely studied, there is increasing interest in identifying potential high-cost users or frequent hospital admitters. In this study, we aimed to derive and validate a risk stratification tool to predict frequent hospital admitters.MethodsWe conducted a retrospective cohort study using the readily available clinical and administrative data from the electronic health records of a tertiary hospital in Singapore. The primary outcome was chosen as three or more inpatient readmissions within 12 months of index discharge. We used univariable and multivariable logistic regression models to build a frequent hospital admission risk score (FAM-FACE-SG) by incorporating demographics, indicators of socioeconomic status, prior healthcare utilization, markers of acute illness burden and markers of chronic illness burden. We further validated the risk score on a separate dataset and compared its performance with the LACE index using the receiver operating characteristic analysis.ResultsOur study included 25,244 patients, with 70% randomly selected patients for risk score derivation and the remaining 30% for validation. Overall, 4,322 patients (17.1%) met the outcome. The final FAM-FACE-SG score consisted of nine components: Furosemide (Intravenous 40 mg and above during index admission); Admissions in past one year; Medifund (Required financial assistance); Frequent emergency department (ED) use (≥3 ED visits in 6 month before index admission); Anti-depressants in past one year; Charlson comorbidity index; End Stage Renal Failure on Dialysis; Subsidized ward stay; and Geriatric patient or not. In the experiments, the FAM-FACE-SG score had good discriminative ability with an area under the curve (AUC) of 0.839 (95% confidence interval [CI]: 0.825–0.853) for risk prediction of frequent hospital admission. In comparison, the LACE index only achieved an AUC of 0.761 (0.745–0.777).ConclusionsThe FAM-FACE-SG score shows strong potential for implementation to provide near real-time prediction of frequent admissions. It may serve as the first step to identify high risk patients to receive resource intensive interventions.

Adherence to disease-modifying therapies for multiple sclerosis and subsequent hospitalizations.

The aim of this study was to examine the association between optimal adherence to first-line disease-modifying therapies (DMT) for multiple sclerosis (MS) and hospitalizations. We used population-based administrative data from three Canadian provinces. All individuals receiving DMT (interferon-B-1b, interferon-B-1a, or glatiramer acetate) between January 1, 1996, and December 31, 2011 (British Columbia); March 31, 2012 (Manitoba); or March 31, 2014, (Saskatchewan) were included. Adherence was estimated for the first year of DMT (year 0), using the medication possession ratio (MPR). The association between optimal adherence (MPR≥80%) and all-cause and MS-specific hospitalizations in the subsequent 1, 2, and 5years was assessed using Hurdle Poisson and logistic regression. Rate and odds ratios were adjusted (aRR and aOR) for sociodemographic factors and prior health-care utilization. Overall, 4746 subjects were followed for a mean 7.8 (SD 4.0) years; 3598 (76%) were women. Optimal DMT adherence was achieved in 3564/4746 (75.1%) subjects. Subsequent all-cause and MS-specific hospitalizations were lower for subjects with optimal versus suboptimal adherence, but none reached statistical significance (1-year period, aRR=0.77, 95%CI: 0.47-1.26; aOR=0.80, 95%CI: 0.52-1.25). Similar findings were observed in the 2-year and 5-year periods. Prior health-care utilization (hospitalizations and medications) was associated with future hospitalizations; for every additional medication class, the 5-year all-cause hospitalization rate and likelihood of an MS-specific hospitalization increased by 5% and 11%, respectively (aRR=1.05, 95%CI: 1.02-1.07; and aOR=1.11, 95%CI: 1.07-1.14). Hospitalization rates were lower in subjects with optimal DMT adherence, but findings were not statistically significant. Prior hospitalization and polypharmacy were associated with increased risk for future hospitalizations in MS. Copyright © 2017 John Wiley & Sons, Ltd.

Postoperative 30-day Readmission: Time to Focus on What Happens Outside the Hospital.

The aim of this study is to understand the relative contribution of preoperative patient factors, operative characteristics, and postoperative hospital course on 30-day postoperative readmissions. Determining the risk of readmission after surgery is difficult. Understanding the most important contributing factors is important to improving prediction of and reducing postoperative readmission risk. National Veterans Affairs Surgical Quality Improvement Program data on inpatient general, vascular, and orthopedic surgery from 2008 to 2014 were merged with laboratory, vital signs, prior healthcare utilization, and postoperative complications data. Variables were categorized as preoperative, operative, postoperative/predischarge, and postdischarge. Logistic models predicting 30-day readmission were compared using adjusted R and c-statistics with cross-validation to estimate predictive discrimination. Our study sample included 237,441 surgeries: 43% orthopedic, 39% general, and 18% vascular. Overall 30-day unplanned readmission rate was 11.1%, differing by surgical specialty (vascular 15.4%, general 12.9%, and orthopedic 7.6%, P < 0.001). Most common readmission reasons were wound complications (30.7%), gastrointestinal (16.1%), bleeding (4.9%), and fluid/electrolyte (7.5%) complications. Models using information available at the time of discharge explained 10.4% of the variability in readmissions. Of these, preoperative patient-level factors contributed the most to predictive models (R 7.0% [c-statistic 0.67]); prediction was improved by inclusion of intraoperative (R 9.0%, c-statistic 0.69) and postoperative variables (R 10.4%, c-statistic 0.71). Including postdischarge complications improved predictive ability, explaining 19.6% of the variation (R 19.6%, c-statistic 0.76). Postoperative readmissions are difficult to predict at the time of discharge, and of information available at that time, preoperative factors are the most important.

Health Care Utilization and Costs After Initiating Budesonide/Formoterol Combination or Fluticasone/Salmeterol Combination Among COPD Patients New to ICS/LABA Treatment.

Chronic obstructive pulmonary disease (COPD) affects approximately 15 million people in the United States and accounts for approximately $36 billion in economic burden, primarily due to medical costs. To address the increasing clinical and economic burden, the Global Initiative for Chronic Obstructive Lung Disease emphasizes the use of therapies that help prevent COPD exacerbations, including inhaled corticosteroid/long-acting beta2-agonist (ICS/LABA). To evaluate health care costs and utilization among COPD patients newly initiating ICS/LABA combination therapy with budesonide/formoterol (BFC) or fluticasone/salmeterol (FSC) in a managed care system. COPD patients aged 40 years and older who initiated BFC (160/4.5 μg) or FSC (250/50 μg) treatment between March 1, 2009, and March 31, 2012, were identified using claims data from major U.S. health plans. BFC and FSC patients were propensity score matched (1:1) on age, sex, prior asthma diagnosis, prior COPD-related health care utilization, and respiratory medication use. COPD-related, pneumonia-related, and all-cause costs and utilization were analyzed during the 12-month follow-up period. Post-index costs were assessed with generalized linear models (GLMs) with gamma distribution. Health care utilization data were analyzed via logistic regression (any event vs. none) and GLMs with negative binomial distribution (number of visits) and were adjusted for the analogous pre-index variable as well as pre-index characteristics that remained imbalanced after matching. After matching, each cohort had 3,697 patients balanced on age (mean 64 years), sex (female 52% BFC and 54% FSC), asthma and other comorbid conditions, prior COPD-related health care utilization, and respiratory medication use. During the 12-month follow-up, COPD-related costs averaged $316 less for BFC versus FSC patients ($4,326 vs. $4,846; P = 0.003), reflecting lower inpatient ($966 vs. $1,202; P < 0.001), pharmacy ($1,482 vs. $1,609; P = 0.002), and outpatient/office ($1,378 vs. $1,436; P = 0.048) costs, but higher emergency department ($257 vs. $252; P = 0.033) costs. Pneumonia-related health care costs were also lower on average for BFC patients ($2,855 vs. $3,605; P < 0.001). Similarly, initiating BFC was associated with lower all-use health care costs versus initiating FSC ($21,580 vs. $24,483; P < 0.001, respectively). No differences in health care utilization were found between the 2 groups. In this study, although no difference was observed in rates of health care utilization, COPD patients initiating BFC treatment incurred lower average COPD-related, pneumonia-related, and all-cause costs versus FSC initiators, which was driven by cumulative differences in inpatient, outpatient, and pharmacy costs.

Evaluation of Eligibility Criteria Used to Identify Patients for Medication Therapy Management Services: A Retrospective Cohort Study in a Medicare Advantage Part D Population.

General eligibility criteria used by the Centers for Medicare & Medicaid Services (CMS) to identify patients for medication therapy management (MTM) services include having multiple chronic conditions, taking multiple Part D drugs, and being likely to incur annual drug costs that exceed a predetermined threshold. The performance of these criteria in identifying patients in greatest need of MTM services is unknown. Although there are numerous possible versions of MTM identification algorithms that satisfy these criteria, there are limited data that evaluate the performance of MTM services using eligibility thresholds representative of those used by the majority of Part D sponsors. To (a) evaluate the performance of the 2013 CMS MTM eligibility criteria thresholds in identifying Medicare Advantage Prescription Drug (MAPD) plan patients with at least 2 drug therapy problems (DTPs) relative to alternative criteria threshold levels and (b) identify additional patient risk factors significantly associated with the number of DTPs for consideration as potential future MTM eligibility criteria. All patients in the Medicare Advantage Part D population who had pharmacy eligibility as of December 31, 2013, were included in this retrospective cohort study. Study outcomes included 7 different types of DTPs: use of high-risk medications in the elderly, gaps in medication therapy, medication nonadherence, drug-drug interactions, duplicate therapy, drug-disease interactions, and brand-to-generic conversion opportunities. DTPs were identified for each member based on 6 months of most recent pharmacy claims data and 14 months of most recent medical claims data. Risk factors examined in this study included patient demographics and prior health care utilization in the most recent 6 months. Descriptive statistics were used to summarize patient characteristics and to evaluate unadjusted relationships between the average number of DTPs identified per patient and each risk factor. Quartile values identified in the study population for number of diseases, number of drugs, and annual spend were used as potential new criteria thresholds, resulting in 27 new MTM criteria combinations. The performance of each eligibility criterion was evaluated using sensitivity, specificity, positive predictive values (PPVs), and negative predictive values (NPVs). Patients identified with at least 2 DTPs were defined as those who would benefit from MTM services and were used as the gold standard. As part of a sensitivity analysis, patients identified with at least 1 DTP were used as the gold standard. Lastly, a multivariable negative binomial regression model was used to evaluate the relationship between each risk factor and the number of identified DTPs per patient while controlling for the patients' number of drugs, number of chronic diseases, and annual drug spend. A total of 2,578,336 patients were included in the study. The sensitivity, specificity, PPV, and NPV of CMS MTM criteria for the 2013 plan year were 15.3%, 95.6%, 51.3%, and 78.8%, respectively. Sensitivity and PPV improved when the drug count threshold increased from 8 to 10, and when the annual drug cost decreased from $3,144 to $2,239 or less. Results were consistent when at least 1 DTP was used as the gold standard. The adjusted rate of DTPs was significantly greater among patients identified with higher drug and disease counts, annual drug spend, and prior ER or outpatient or hospital visits. Patients with higher median household incomes who were male, younger, or white had significantly lower rates of DTPs. The performance of MTM eligibility criteria can be improved by increasing the threshold values for drug count while decreasing the threshold value for annual drug spend. Furthermore, additional risk factors, such as a recent ER or hospital visit, may be considered as potential MTM eligibility criteria.

Hospital Readmission From Post-Acute Care Facilities: Risk Factors, Timing, and Outcomes

ObjectivesHospital discharges to post-acute care (PAC) facilities have increased rapidly. This increase may lead to more hospital readmissions from PAC facilities, which are common and poorly understood. We sought to determine the risk factors and timing for hospital readmission from PAC facilities and evaluate the impact of readmission on patient outcomes. DesignRetrospective analysis of Medicare Current Beneficiary Survey (MCBS) from 2003–2009. SettingThe MCBS is a nationally representative survey of beneficiaries matched with claims data. ParticipantsCommunity-dwelling beneficiaries who were hospitalized and discharged to a PAC facility for rehabilitation. Intervention/ExposurePotential readmission risk factors included patient demographics, health utilization, active medical conditions at time of PAC admission, and PAC characteristics. MeasurementsHospital readmission during the PAC stay, return to community residence, and all-cause mortality. ResultsOf 3246 acute hospitalizations followed by PAC facility stays, 739 (22.8%) included at least 1 hospital readmission. The strongest risk factors for readmission included impaired functional status (HR 4.78, 95% CI 3.21–7.10), markers of increased acuity such as need for intravenous medications in PAC (1.63, 1.39–1.92), and for-profit PAC ownership (1.43, 1.21–1.69). Readmitted patients had a higher mortality rate at both 30 days (18.9% vs 8.6%, P < .001) and 100 days (39.9% vs 14.5%, P < .001) even after adjusting for age, comorbidities, and prior health care utilization (30 days: OR 2.01, 95% CI 1.60–2.54; 100 days: OR 3.79, 95% CI 3.13–4.59). ConclusionsHospital readmission from PAC facilities is common and associated with a high mortality rate. Readmission risk factors may signify inadequate transitional care processes or a mismatch between patient needs and PAC resources.

Health care utilization before and after intensive care unit admission in multiple sclerosis

ObjectivesThe incidence of intensive care unit (ICU) admission is elevated in the multiple sclerosis (MS) population but the reasons for this are incompletely understood, as are outcomes post-ICU admission. Among MS patients we examined the association between ICU admission and health care utilization in the year preceding admission, and compared health care utilization following ICU admission among persons with MS and persons from the general population. MethodsWe used population-based administrative data from Manitoba, Canada to identify 4237 MS cases of which 2547 were incident. We compared the incidence rates of ICU admission in the prevalent MS population according to health care utilization in the year before admission, adjusting for age, sex, comorbidity and socioeconomic status. Among incident cases of MS we compared rates of health care utilization after ICU admission to those in a matched general population cohort. We used generalized linear models adjusting for age, sex, socioeconomic status, region, comorbidity and utilization before admission. ResultsOf 4219 prevalent MS cases, 222 (5.3%) were admitted to the ICU. After adjustment, any hospitalization in the prior year conferred an 80% increased incidence, and physician visits in the highest tertile and prescription costs in the highest quartile in the prior year each conferred a more than two-fold increased incidence of admission. Among 2547 incident cases of MS, 109 (4.3%) were admitted to the ICU and 93 survived their admission. Thirty-eight percent of the MS population were re-hospitalized in the year following admission, similar to the matched population (33.8%). Seven percent of both populations were readmitted to the ICU. The MS population had more hospital days after ICU admission than the matched population (adjusted RR 3.11; 95% CI: 1.34–5.90). After adjustment the number of physician visits did not differ between populations. ConclusionsThe incidence of ICU admission is higher among persons with MS who have higher prior health care utilization. Health care utilization remains high after ICU admission. Efforts to prevent ICU admission in this population are needed.

Predicting 30-Day Readmissions: Performance of the LACE Index Compared with a Regression Model among General Medicine Patients in Singapore.

The LACE index (length of stay, acuity of admission, Charlson comorbidity index, CCI, and number of emergency department visits in preceding 6 months) derived in Canada is simple and may have clinical utility in Singapore to predict readmission risk. We compared the performance of the LACE index with a derived model in identifying 30-day readmissions from a population of general medicine patients in Singapore. Additional variables include patient demographics, comorbidities, clinical and laboratory variables during the index admission, and prior healthcare utilization in the preceding year. 5,862 patients were analysed and 572 patients (9.8%) were readmitted in the 30 days following discharge. Age, CCI, count of surgical procedures during index admission, white cell count, serum albumin, and number of emergency department visits in previous 6 months were significantly associated with 30-day readmission risk. The final logistic regression model had fair discriminative ability c-statistic of 0.650 while the LACE index achieved c-statistic of 0.628 in predicting 30-day readmissions. Our derived model has the advantage of being available early in the admission to identify patients at high risk of readmission for interventions. Additional factors predicting readmission risk and machine learning techniques should be considered to improve model performance.

Portraying persons who inject drugs recently infected with hepatitis C accessing antiviral treatment: a cluster analysis.

Objectives. To empirically determine a categorization of people who inject drug (PWIDs) recently infected with hepatitis C virus (HCV), in order to identify profiles most likely associated with early HCV treatment uptake. Methods. The study population was composed of HIV-negative PWIDs with a documented recent HCV infection. Eligibility criteria included being 18 years old or over, and having injected drugs in the previous 6 months preceding the estimated date of HCV exposure. Participant classification was carried out using a TwoStep cluster analysis. Results. From September 2007 to December 2011, 76 participants were included in the study. 60 participants were eligible for HCV treatment. Twenty-one participants initiated HCV treatment. The cluster analysis yielded 4 classes: class 1: Lukewarm health seekers dismissing HCV treatment offer; class 2: multisubstance users willing to shake off the hell; class 3: PWIDs unlinked to health service use; class 4: health seeker PWIDs willing to reverse the fate. Conclusion. Profiles generated by our analysis suggest that prior health care utilization, a key element for treatment uptake, differs between older and younger PWIDs. Such profiles could inform the development of targeted strategies to improve health outcomes and reduce HCV infection among PWIDs.

Improving safety of diabetes mellitus management.

Improving safety of diabetes mellitus management.