High-Users of Acute Care in a Teaching Hospital: A Retrospective Chart Review and Survey of Primary Care Physicians

Purpose To characterize high-users (HUs) of inpatient units, obtain insights from their primary care physicians (PCPs) and identify factors that can be modified to reduce resource use. Method The study design included retrospective chart reviews of high-user patients and qualitative surveys of their PCPs. HUs were defined as adults with 3 or more admissions to an index tertiary teaching hospital in Edmonton as well as a cumulative length of stay (cLOS) greater than 30 days at any hospital in the province of Alberta, between September 1, 2015 and September 30, 2016. The charts of HUs were reviewed to assess demographics, admitting and consulting services, medical profile, social profile, community supports, and scores on pre-existing risk-stratification tools to identify patient factors that might be characteristic of HUs. Additionally, a survey comprising 12 multiple-choice and 8 short-answer questions was faxed to their PCPs to assess HU attitudes and behaviors and collect recommendations to prevent high use of acute care. Results Of 125 HUs (median 62 years old, 5 admissions, cLOS 49 days, 14 emergency department (ED) visits, 10 medications), 74% lived at home, 86% had a PCP, 56% received homecare pre-admission and 34% had at least one critical care admission. HUs accounted for 2474 admissions or ED C a n a d i a n J o u r n a l o f G e n e r a l I n t e r n a l M e d i c i n e 28 V o l u m e 1 5 , I s s u e 3 , 2 0 2 0 G a n t a y e t e t a l . CJGIM_3_2020_175414.indd 28 8/25/20 4:35 PM visits (median 14, IQR 10-22) at all sites in the year studied; 41% of their 1605 ED visits and 21% of their 869 admissions were at other hospitals. Their most prevalent comorbidities were hypertension, depression, and diabetes. 49 responses were received to 114 faxed surveys (43% response rate). Only 14 of 49 responding PCPs suggested interventions to address ED revisits and readmissions; PCPs most frequently cited living conditions and lack of social supports as key causative factors. Conclusions We have characterized high-user patients and discussed PCP perspectives and strategies to optimize their healthcare use. Resume Objet Caractériser les grands utilisateurs (HU) des unités d’hospitalisation, obtenir des informations de leurs médecins de soins primaires (PCP) et identifier les facteurs qui peuvent être modifiés pour réduire l’utilisation des ressources. Méthode La conception de l’étude comprenait des examens rétrospectifs de dossiers de patients très utilisateurs et des enquêtes qualitatives sur leurs PPC. Les UH ont été définis comme des adultes ayant été admis à trois reprises ou plus dans un hôpital universitaire tertiaire d’Edmonton et dont la durée de séjour cumulée (DSC) est supérieure à 30 jours dans n’importe quel hôpital de la province de l’Alberta, entre le 1er septembre 2015 et le 30 septembre 2016. Les tableaux des HU ont été examinés afin d’évaluer les données démographiques, les services d’admission et de consultation, le profil médical, le profil social, les soutiens communautaires et les scores des outils de stratification des risques préexistants afin d’identifier les facteurs des patients qui pourraient être caractéristiques des HU. En outre, une enquête comprenant 12 questions à choix multiple et 8 questions à réponse courte a été envoyée par fax à leurs PCP afin d’évaluer les attitudes et les comportements des HU et de recueillir des recommandations pour prévenir un recours élevé aux soins de courte durée. Résultats Sur 125 HU (âge médian 62 ans, 5 admissions, cLOS 49 jours, 14 visites aux urgences, 10 médicaments), 74 % vivaient à domicile, 86 % avaient un PCP, 56 % recevaient des soins à domicile avant leur admission et 34 % avaient au moins une admission en soins intensifs. Les HU ont représenté 2474 admissions ou visites aux urgences (médiane 14, IQR 10-22) dans tous les sites au cours de l’année étudiée ; 41% de leurs 1605 visites aux urgences et 21% de leurs 869 admissions se sont faites dans d’autres hôpitaux. Leurs comorbidités les plus fréquentes étaient l’hypertension, la dépression et le diabète. 49 réponses ont été reçues pour 114 enquêtes envoyées par fax (taux de réponse de 43 %). Seuls 14 des 49 PCP ayant répondu ont suggéré des interventions pour remédier aux problèmes des visites aux urgences et des réadmissions; les PCP ont le plus souvent cité les conditions de vie et le manque de soutien social comme principaux facteurs de causalité. Conclusions Nous avons caractérisé les patients grands utilisateurs et discuté des perspectives et des stratégies de la PCP pour optimiser leur utilisation des soins de santé. C a n a d i a n J o u r n a l o f G e n e r a l I n t e r n a l M e d i c i n e V o l u m e 1 5 , I s s u e 3 , 2 0 2 0 29 O r i g i n a l A r t i c l e CJGIM_3_2020_175414.indd 29 8/25/20 4:35 PM As life expectancy increases and healthcare needs become more complex, it is becoming increasingly important to improve efficiency in healthcare delivery.1,2 It has been observed in various settings that a small proportion of the population accounts for disproportionate use of healthcare resources; 5% of the population accounted for 64% of total health care spending in Ontario3 and 66% in Alberta.4 The biggest driver of these costs are inpatient (IP) admissions.1,3 Although multiple risk scores have been developed to predict single readmissions after hospital discharge,5-7 there are few risk-stratification tools to predict which individuals will become high system users. The objective of this study was to use a patient-focused approach to gain insights into high-users (HUs) and potential approaches to optimizing their care. The goal was to identify and characterize current HUs, obtain insights from their primary care physicians (PCPs) on their healthcare behaviors and attitudes, discover patient and system factors that predispose them to frequent readmissions, and to suggest strategies to intervene against modifiable factors. METHODS This study was performed at a large tertiary care teaching hospital, the University of Alberta Hospital (UAH), Edmonton between Sep 1, 2015 and Sep 30, 2016. The study design included chart reviews of high-user patients and qualitative surveys of their PCPs. As per the Canadian Institute for Health Information (CIHI) definition, HUs were any adult patients with three or more admissions at our index hospital and cumulative length of stay (cLOS) greater than 30 days at any hospital in the province of Alberta, during that year. Patients who met the HU definition were included even if they died in the hospital or during the study period. High user data was obtained from the Alberta Health Services (AHS) medical site administrative office using the Data Integration Monitoring and Reporting (DIMR) unit. We used DIMR to collect all data on visits to ED or acute care hospitals anywhere in the province of Alberta – this allowed us to track resource use by HUs regardless of where else they received care in the province. The descriptive variables derived from the UAH local database and DIMR were organized into the following categories; patient gender, age at last admit, postal code, date of last admission between Sep 1/15 Sep 30/16, number of UAH admissions in study period, number of non-UAH admissions, number of UAH ED visits, number of non-UAH ED visits, cumulative LOS (days) between Sep 1/15 Sep 30/16 at UAH only and cumulative LOS (days) between Sep 1/15 Sep 30/16 at all hospitals in Alberta. DIMR also provided data on whether the identified HUs had any admissions in the prior two years if the HU patient was deceased at the time of analysis, and the number of ambulance arrivals. We obtained the most common admitting diagnosis list from UAH under the hospital’s International Statistical Classification of Disease (ICD) codes. HU data was derived for all specialties except Obstetrics/Gynecology, which is not available at the UAH site, and Pediatrics, as this patient population was not the focus of the study. Admitting service was categorized by specialties; General Internal Medicine (GIM)/Cardiology/Critical care/Gastroenterology/Hematology/ Nephrology/Family Medicine/Surgical specialties including ENT/ Psychiatry/Geriatrics. Quantitative variables were loaded on a ‘Dashboard’ database created by the Performance Improvement Manager at UAH and analysis was performed by the first author using its’ filter applications. The data was documented as number counts and ranges of minimum to maximum, where applicable. Excel worksheets were then used by the first author to calculate proportions, percentages as well as medians with an interquartile range from the 25th to 75th percentile. We obtained ethics approval for chart reviews and PCP surveys, with a waiver of informed patient consent, from the University of Alberta Research Ethics Board (Pro00073914). Physician (PCP) informed consent was obtained by faxing a consent sheet along with the survey. Chart reviews were standardized by the first author using a list of definitions and categorization protocols and were performed by the first and third authors in this study. Only charts for the last admission in the study period were reviewed for each HU, as comprehensive data collection and analysis was not feasible given the large number of admissions for all HUs combined. Descriptive variables derived from the chart review were categorized as living facility at the time of the last admission, time lived in that facility, prior or current home care, duration of home care, types of home supports, types of inter-professional care supports in the community, independent for all activities of daily living (ADLs) and iADLs (in the form of yes, no or unknown), number of regularly prescribed, scheduled medications at the last admission, list of discharge medications after the last admission in the study period, the cumulative number of specialties involved and goals of care documented in the chart at the time of the last admission i