Implementation of a Collaborative HIV and Hepatitis C Screening Program in Appalachian Urgent Care Settings

Introduction: With the current hepatitis C (HCV) epidemic in the Appalachian region and the risk of human immunodeficiency virus (HIV) co-infection, there is a need for increased secondary prevention efforts. The purpose of this study was to implement routine HIV and HCV screenings in the urgent care setting through the use of an electronic medical record (EMR) to increase a provider’s likelihood of testing eligible patients. Methods: From June 2017 through May 2018, EMR-based HIV and HCV screenings were implemented in three emergency department-affiliated urgent care settings: a local urgent care walk-in clinic; a university-based student health services center; and an urgent care setting located within a multi-specialty clinic. EMR best practice alerts (BPA) were developed based on Centers for Disease Control and Prevention (CDC) guidelines and populated on registered patients who qualified to receive HIV and/or HCV testing. Patients were excluded from the study if they chose to opt out from testing or the provider deemed it clinically inappropriate. Upon notification of a positive HIV and/or HCV test result through the EMR, patient navigators (PNs) were responsible for linking patients to their first medical appointment. Results: From June 2017 through May 2018, 48,531 patients presented to the three urgent care clinics. Out of 27,230 eligible patients, 1,972 patients (7.2%) agreed to be screened for HIV; for HCV, out of 6,509 eligible patients, 1,895 (29.1%) agreed to be screened. Thirty-one patients (1.6%) screened antibody-positive for HCV, with three being ribonucleic acid confirmed positives. No patients in either setting were confirmed positive for HIV; however, two initially screened HIV- positive. PNs were able to link 17 HCV antibody-positive patients (55%) to their first appointment, with the remainder having a scheduled future appointment. Conclusion: Introducing an EMR-based screening program is an effective method to identify and screen eligible patients for HIV and HCV in Appalachian urgent care settings where universal screenings are not routinely implemented. [West J Emerg Med. 2018;19(6)1057–1064.

How safe is primary care? A systematic review

Improving patient safety is at the forefront of policy and practice. While considerable progress has been made in understanding the frequency, causes and consequences of error in hospitals, less is known about the safety of primary care.We investigated how often patient safety incidents occur in primary care and how often these were associated with patient harm.We searched 18 databases and contacted international experts to identify published and unpublished studies available between 1 January 1980 and 31 July 2014. Patient safety incidents of any type were eligible. Eligible studies were critically appraised using validated instruments and data were descriptively and narratively synthesised.Nine systematic reviews and 100 primary studies were included. Studies reported between <1 and 24 patient safety incidents per 100 consultations. The median from population-based record review studies was 2-3 incidents for every 100 consultations/records reviewed. It was estimated that around 4% of these incidents may be associated with severe harm, defined as significantly impacting on a patients well-being, including long-term physical or psychological issues or death (range <1% to 44% of incidents). Incidents relating to diagnosis and prescribing were most likely to result in severe harm.Millions of people throughout the world use primary care services on any given day. This review suggests that safety incidents are relatively common, but most do not result in serious harm that reaches the patient. Diagnostic and prescribing incidents are the most likely to result in avoidable harm.This systematic review is registered with the International Prospective Register of Systematic Reviews (PROSPERO CRD42012002304)

Measuring multimorbidity in Australia

The ageing of the population is expected to lead to increases in the prevalence of chronic conditions, multimorbidity, and raised demand for primary care services. To enable health systems to respond to these increases, the prevalence of chronic conditions and multimorbidity need to be measured in an accurate and timely manner. However, prevalence estimates of multimorbidity vary widely due to inconsistent definitions and measurement methods used in research. The aim of this thesis is to develop a reliable and practical method of measuring multimorbidity in Australia. The research reported in this thesis is based on two sets of sub-studies of the Bettering the Evaluation and Care of Health (BEACH) program, a continuous national survey of Australian general practice activity. The first survey was conducted between August 2008 and May 2009, and involved 290 randomly selected general practitioners (GPs) who recorded all diagnosed chronic conditions in 8,707 patients at their encounters. Having GPs record patients’ diagnosed chronic conditions avoids the limitations of self-reported data used in most large population prevalence studies. However, patients sampled at GP encounters are not representative of the population as only about 87% of people visit a GP in any year and because older people are more likely to attend and to attend more often. To estimate population prevalence, I weighted each age-sex group to match the distribution of the population. I then weighted the outcome by the proportion in each age-sex group who visited a GP at least once in the survey year, assuming those who did not see a GP did not have a diagnosed chronic condition. I estimated that two-thirds (66.3%) of patients at GP encounters had at least one diagnosed chronic condition as did half (50.8%) of the Australian population. Hypertension was the most prevalent condition, 26.6% of patients at GP encounters and 17.4% of the population having this diagnosed condition. While multimorbidity has been most often defined as 2+ chronic conditions, there have been recent moves towards using 3+. There have been calls for standardisation of multimorbidity research, inconsistent definitions and methods having led to large variance in estimated prevalence between studies. I examined the independent effects on prevalence estimates of: iii 1. how ‘morbidity’ is defined either as a single chronic condition or a ‘group’ of conditions using the chapter/domain structure of the International Classification of Primary Care (Version 2) (ICPC-2), the International Classification of Disease (10th revision)(ICD-10), or the Cumulative Illness Rating Scale (CIRS); 2. the number of ‘morbidities’ required in the definition of multimorbidity; 3. the number of diagnosed chronic conditions included in the study. I found that data grouped by ICPC-2 chapters, ICD-10 chapters or CIRS domains produced similar multimorbidity prevalence estimates. Multimorbidity defined as 2+ morbidities provided similar estimates whether individual conditions or groups of conditions were counted and whether as few as 12 prevalent chronic conditions were studied or all chronic conditions, but it lacked the specificity to be useful, especially among older people. Multimorbidity, defined as 3+ morbidities, required more measurement conformity and inclusion of all chronic conditions, but provided greater specificity than the 2+ definition. These results led to a set of guidelines for multimorbidity researchers, which if followed, will produce results that can be compared with results from other studies adhering to the same guidelines. I also proposed the concept of ‘complex multimorbidity’, the co-occurrence of three or more chronic conditions classified in three or more different body systems within one person, without defining an index chronic condition. Using ‘complex multimorbidity’ may identify high-need individuals. I estimated that: 47.4% of patients at GP encounters and one-third (32.6%) of the population had multimorbidity (2+); further, that 27.4% of patients at GP encounters and 17.0% of the Australian population had complex multimorbidity. The most prevalent pattern of three conditions was hypertension + hyperlipidaemia + osteoarthritis (5.5% of patient at encounters and 3.3% of the population). In my second, larger, survey, conducted between November 2012 and March 2016, 1,449 randomly selected GPs recorded all diagnosed chronic conditions for 43,501 patients. They also recorded the number of times each patient had seen a GP in the previous 12 months. Data collected in Survey 1 had not allowed adjustment for high and low attenders within each age-sex group. The individual attendance data in survey 2 allowed me to adjust for each patient’s chance of being in the survey sample. iv My prevalence estimates for patients at encounters were similar to those from Survey 1, with 26.5% of patients at encounters having diagnosed hypertension, 51.6% multimorbidity and 30.4% having complex multimorbidity. However, the population prevalence estimates produced with the new method were significantly lower than those from the previous method, an estimated 12.4% of the population having diagnosed hypertension, 25.7% multimorbidity and 12.1% complex multimorbidity. This suggests that patients with more chronic conditions attend more often than others in their age-sex group. Adjusting for individual patient attendance is therefore required to produce reliable population estimates from data collected from patients sampled at GP encounters. My final task was to develop a parsimonious model to predict patient GP-visit rate, testing the assumption that the number of chronic conditions is driving GP service use. In Survey 2, the number of diagnosed chronic conditions alone accounted for a significant proportion of the variance (25.5%) in patient GP-visit rate. The number of body systems involved also explained a significant proportion of variance (23.9%). Including patient age, sex and Commonwealth concession health care card status only marginally increased the predictive value of the model to 27.9%. In summary, this thesis demonstrates a practical method of measuring multimorbidity in Australia, using GPs as expert interviewers and adjusting for each patient’s individual attendance. I have shown that to produce robust results that can be compared with other studies, multimorbidity researchers should ideally define multimorbidity as 3+ conditions and include as many chronic conditions as possible in their study. Finally the measure has practical application as the number of diagnosed chronic conditions in an individual is the most significant driver of general practice service use. The results of this research will help inform health policy makers in their response to the challenges posed by continued growth in the prevalence of multimorbidity

Risk stratification tools to predict future hospital admissions in elderly people. Application, development and implementation in the Valencian Healthcare System

La presente tesis se enmarca en un escenario caracterizado por una población que cada vez vive más años y en la que el porcentaje de personas mayores es progresivamente más alto. De forma adicional, el aumento de la prevalencia de las enfermedades crónicas (EC) supone un importante impacto sobre los sistemas sanitarios dado que éstas son la principal causa de muerte a nivel mundial y, en muchos casos, están asociadas a situaciones de dependencia y a la necesidad de cuidados de larga duración. Con el objetivo de llevar a cabo un abordaje más efectivo de las enfermedades asociadas al envejecimiento y a la cronicidad los sistemas asistenciales deberían sufrir un cambio de paradigma en el que se sitúe al paciente en el centro de la relación asistencial. Los servicios de atención primaria (AP) juegan un papel clave para favorecer un cambio de cultura asistencial introduciendo mejoras en la gestión, atención y derivación de pacientes mayores y/o con EC. No obstante, para no sobrecargar las funciones diarias de los profesionales de AP, sería interesante y útil la implementación de sistemas que les ayuden a tomar decisiones relacionadas con la gestión de este tipo de pacientes. Así pues, la presente tesis apuesta por el uso potencial de los sistemas de estratificación en población mayor con EC desde los servicios de AP. A lo largo de esta tesis doctoral se han desarrollado tres estudios independientes pero interconectados entre sí que ofrecen una visión global de la viabilidad y el uso potencial de las herramientas de estratificación en los servicios de AP con el objetivo de detectar pacientes con riesgo de sufrir un ingreso hospitalario futuro (IHF). En primer lugar, se estudió la aplicación de dos herramientas originalmente desarrolladas y validadas en Estados Unidos (Probability of Repeated Admission – Pra – y The Community Assessment Risk Screen – CARS) en una muestra de personas mayores del Sistema Valenciano de Salud (SVS). En segundo lugar, dado que los resultados del estudio anterior fueron limitados, se desarrolló un modelo de estratificación nuevo – asociado a un algoritmo matemático predictivo – partiendo de las características propias del SVS y de la población mayor de la Comunidad Valenciana. Finalmente, se presenta un caso práctico del uso de herramientas de estratificación poblacional para seleccionar e incluir pacientes con EC en un programa de telemonitorización en función su nivel de riesgo de sufrir un IHF. La tesis concluye con una serie de recomendaciones políticas extraídas de los resultados obtenidos en los tres estudios que la componen que el SVS u otros sistemas sanitarios con características similares podrían tener en consideración para mejorar la gestión de pacientes mayores con EC.The scenario in which this thesis is framed is characterized by a population each time living longer and with a percentage of older people being progressively higher. Additionally, the increasing prevalence of chronic diseases (CD) means an important impact on healthcare systems, as they are the main cause of death worldwide and, in many cases, they are associated to dependency situations and long-term care. In order to approach more effectively the conditions associated to ageing and chronicity, care systems should experience a paradigm change in which the patient is placed in the centre of the care relationship. Primary care (PC) services play an indispensable role to encourage these changes in the care culture by introducing improvements in the management, care and referral of elderly patients and/or with CD. However, in order to not overload the daily functions of PC professionals it would be interesting and useful the implementation of support decision making systems related to the management of these patients. Thus, this thesis banks on the potential use of stratification systems in elderly population with CD at PC services. Throughout this doctoral thesis, three independent but interconnected studies have been carried out. They offer a global view of the viability and potential use of stratification tools at PC services aimed to detect patients at risk of future hospital admissions (FHA). Firstly, it was studied the application of two stratification tools originally developed and validated in the United States (Probability of Repeated Admission – Pra – and The Community Assessment Risk Screen – CARS) – in a sample of elderly people from the Valencian Healthcare System (VHS). Secondly, due to the limited results of the previous study, a new stratification model was developed – associated to a predictive mathematical algorithm – based on the own characteristics of the VHS and the elderly population of the Valencia Region. Finally, a practical implementation using population stratification systems is presented aimed to select and include patients with CD in a telemonitoring programme according to their risk of suffering FHA. The thesis concludes with a set of policy recommendation taken from the results obtained in the three studies. These recommendations may be taken into consideration to improve the management of elderly patients with CD at the VHS or other healthcare systems with similar characteristics