Using mobile technology to promote access, effective patient–provider communication, and adherence in underserved populations

Federally Qualified Health Centers (FQHCs) are community based centers created to provide comprehensive primary and preventive care to individuals unable to access care in the commercial medical system (e.g. related to poverty, and/or race-ethnicity). The Affordable Care Act (ACA) proposes offering Medicaid coverage to many such individuals, thus, FQHCs should receive many new Medicaid enrollees. The ACA has triggered a number of new ideas to improve affordability, health status and patient experience, commonly known as the “triple aim.” These initiatives include quality incentive programs, payment reform, and the promotion of medical homes and accountable care organizations (ACOs). These are in addition to earlier efforts to facilitate market reform, such as incentives to develop information and communication tools, such as interoperable electronic health records (EHRs) (Doebbeling, Chou \u26 Tierney, 2006). The goals of the “triple aim” cannot be met unless there is greater access to primary and preventive care. Since limited access to poor and minority populations exists today, the FQHC system could easily become overwhelmed with demand. Innovative models are essential to ensure access to needed care. If health care coverage expands beginning in 2014 as expected, FQHCs will be in a position to transition their uninsured patient population to Medicaid and state insurance exchanges. Provider networks, such as FQHCs, will be held accountable for reaching the triple aim, as measured by cost, quality, and patient experience. Recent federal and state cutbacks in the funding of Medicaid and FQHCs has led to problems with access to care and little improvement in quality of care, efficiency or satisfaction in many states. Recent “secret shopper” calls of FQHCs demonstrated access to care problems for a variety of common significant health problems at most clinics in Indiana. To investigate this problem, we have recently conducted a series of key informant interviews of clinicians, staff and leaders at three FQHCs in Indiana, regarding operational challenges and access to care. Due to current fiscal shortfalls, current patients often have difficulty in being seen and “no show\u22 cases are common. We found the leadership and clinicians at each of our participating FQHCs interested in opportunities to improve access to care and reduce no-shows, as well as strategies to improve provider-patient communication. Our findings suggest an opportunity to design and implement novel models of patient-centered care and redesign current policies and workflow to ensure that primary care is available, timely, coordinated, and cost effective. In order to address these issues, we are partnering with FQHCs and a not for profit health maintenance organization (MDwise, Inc) in Indiana to test new information and access strategies. In the proposed project, we will explore the feasibility of using mobile technology to increase access to information that will improve patient access to care and satisfaction. Short message service (SMS), or text messaging, is one way in which mobile technology has been used in healthcare. In a review of 61 studies, 50 presented findings showing a positive effect on the desired outcome from the intervention (Yeager \u26 Menachemi, 2011). Most of these studies looked at the influence of text messaging on health behaviors, however, 10 examined the impact of text messaging on administrative processes in healthcare. Nine of the ten studies found text message reminders systems reduced the no-show rates in clinics; several found text messaging was more cost effective than phone call reminders (Yeager \u26 Menachemi, 2011). The authors noted that only two of these 10 studies were conducted in primary care and none were conducted in the United States. In addition, few studies have explored the benefits of using this type of technology in vulnerable populations which are cared for by FQHCs. Thus, the present project will help to address this knowledge gap. In our project, we intend to extend beyond text messaging, into the use of social media such as Facebook and Twitter, to provide patient easy access to clinic information and ease scheduling. Other opportunities to leverage mobile technologies in community health centers that will be considered include: 1) immunization reminders; 2) management of chronic disease; 3) reduction in emergency room visits for urgent care; 4) facilitation of Medicaid reenrollment; 5) education to advance health literacy; and 6) enhance communication to improve member retention. Table 1 outlines our proposed phased approach to developing and deploying the mobile technology solution. First, we will conduct a survey to assess the feasibility of using these mobile technologies in the target population. In a recent study examined the interest in using mobile technology for appointment reminders at a safety-net clinic serving an indigent urban population (Denizard-Thompson et al, 2011). Over three hundred surveys were collected in ten days from patients who were “predominantly African-American (68 vs. 27% white, 3% Latino), and female (65% female vs. 35% male),” with a payer distribution of 24% Medicaid, 27% self-pay, 30% Medicare, and 9% privately insured (Denizard-Thompson et al, p. 458). Over half of the patients surveyed were interested in managing clinic appointments by text message (57%) and emphasized the value of surveying the clinic population to better understand its unique needs. In the proposed research, we plan to adapt the methodology and survey instrument used by Denizard-Thompson et al. Next, we propose conducting focus groups with staff, clinicians and patients in order to assess the needs from the technology and gather design ideas, selected across 5-6 FQHCs. After a prototype is developed, we will conduct a pilot test involving at least one patient from each center. Feedback from interviews conducted during this stage will be used to modify the technology as needed. Rollout to all participating centers will follow a formal training period at each clinic. Table 1 – Mobile Technology Development Plan Month Complete Study Duration/ Center Study Description 6 1 week of data collection with patients as they come to clinic for care Survey Assess patient’s current use of mobile technology and willingness to use for healthcare appointment management and alerts. 1-2 hours Needs Assessment/Formative Evaluation Focus Group/ Design Workshop with Center Staff and Care Providers 1-2 hours Needs Assessment/Formative Evaluation Focus Group/ Design Workshop with Center Patients and Caregivers 12 n/a Professional prototype development 18 Pilot Test Test technology with at least one patient, selected based on criteria deemed important by center staff and care providers. Weeks 4, 8, \u26 12: Contextual interview with patient/caregiver and center staff/ care providers 24 n/a Professional technology development Changes based on pilot testing 36 1-2 hours System Training Roll out to all participating centers In conclusion, we have found that there is a need to improve scheduling, access to care and patient-provider communication in community health centers, such as FQHCs. The proposed application of inexpensive mobile technology available on most cell phones holds promise for both improving access and ensuring higher utilization, as well as in improving patient-provider communication and adherence to current medical care guidelines. References: Doebbeling, B.N., Chou, A.F., Tierney, W.M. Priorities and Strategies for Implementation of an Integrated Informatics and Communications Technology System for Evidence-based Practices. J. Gen. Intern. Med. 21:S98-S105, 2006. Yeager, V.A., Menachemi, N. Text Messaging in Health Care: A Systematic Review of Impact Studies. Biennial Review of Health Care Management. (2011) 235-261. Denizard-Thompson, Nancy M; Feiereisel, Kirsten B; Stevens, Sheila F; Miller, David P; Wofford, James. The Digital Divide at an Urban Community Health Center: Implications for Quality Improvement and Health Care Access. Journal of community health (2011) 36: 456-460

Patient-Centered Appointment Scheduling Using Agent-Based Simulation

Enhanced access and continuity are key components of patient-centered care. Existing studies show that several interventions such as providing same day appointments, walk-in services, after-hours care, and group appointments, have been used to redesign the healthcare systems for improved access to primary care. However, an intervention focusing on a single component of care delivery (i.e. improving access to acute care) might have a negative impact other components of the system (i.e. reduced continuity of care for chronic patients). Therefore, primary care clinics should consider implementing multiple interventions tailored for their patient population needs. We collected rapid ethnography and observations to better understand clinic workflow and key constraints. We then developed an agent-based simulation model that includes all access modalities (appointments, walk-ins, and after-hours access), incorporate resources and key constraints and determine the best appointment scheduling method that improves access and continuity of care. This paper demonstrates the value of simulation models to test a variety of alternative strategies to improve access to care through scheduling

VizCom: A Novel Workflow Model for ICU Clinical Decision-Support

The Intensive Care Unit (ICU) has the highest annual mortality rate (4.4M) of any hospital unit or 25% of all clinical admissions. Studies show a relationship between clinician cognitive load and workflow, and their impact on patient safety and the subsequent occurrence of medical mishaps due to diagnostic error - in spite of advances in health information technology, e.g., bedside and clinical decision support (CDS) systems. The aim of our research is to: 1) investigate the root causes (underlying mechanisms) of ICU error related to the effects of clinical workflow: medical cognition, team communication/collaboration, and the use of diagnostic/CDS systems and 2) construct and validate a novel workflow model that supports improved clinical workflow, with goals to decrease adverse events, increase safety, and reduce intensivist time, effort, and cognitive resources. Lastly, our long-term objective is to apply data from aims one and two to design the next generation of diagnostic visualization-communication (VizCom) system that improves intensive care workflow, communication, and effectiveness in healthcare

Data Analytics and Modeling for Appointment No-show in Community Health Centers

Objectives: Using predictive modeling techniques, we developed and compared appointment no-show prediction models to better understand appointment adherence in underserved populations. Methods and Materials: We collected electronic health record (EHR) data and appointment data including patient, provider and clinical visit characteristics over a 3-year period. All patient data came from an urban system of community health centers (CHCs) with 10 facilities. We sought to identify critical variables through logistic regression, artificial neural network, and naïve Bayes classifier models to predict missed appointments. We used 10-fold cross-validation to assess the models’ ability to identify patients missing their appointments. Results: Following data preprocessing and cleaning, the final dataset included 73811 unique appointments with 12,392 missed appointments. Predictors of missed appointments versus attended appointments included lead time (time between scheduling and the appointment), patient prior missed appointments, cell phone ownership, tobacco use and the number of days since last appointment. Models had a relatively high area under the curve for all 3 models (e.g., 0.86 for naïve Bayes classifier). Discussion: Patient appointment adherence varies across clinics within a healthcare system. Data analytics results demonstrate the value of existing clinical and operational data to address important operational and management issues. Conclusion: EHR data including patient and scheduling information predicted the missed appointments of underserved populations in urban CHCs. Our application of predictive modeling techniques helped prioritize the design and implementation of interventions that may improve efficiency in community health centers for more timely access to care. CHCs would benefit from investing in the technical resources needed to make these data readily available as a means to inform important operational and policy questions

Missing links: challenges in engaging the underserved with health information and communication technology

We sought to understand underserved patients' preferences for health information technology (HIT) and examine the current use of personal health records (PHRs) in Community Health Centers (CHCs) serving low-income, uninsured, and underinsured patients. Forty-three patients and 49 clinic staff, administrators, and providers from these CHC systems were interviewed using open-ended questions assessing patient experience, perceptions of the CHC, access barriers, strategies used to overcome access barriers, technology access and use, and clinic operations and workflow. All seven CHC systems were at some stage of implementing PHRs, with two clinics having already completed implementation. Indiana CHCs have experienced barriers to implementing and using PHRs in a way that provides value for patients or providers/staff There was a general lack of awareness among patients regarding the existence of PHRs, their benefits and a lack of effective promotion to patients. Most patients have access to the internet, primarily through mobile phones, and desire greater functionality in order to communicate with CHCs and manage their health conditions. Despite decades of research, there remain barriers to the adoption and use of PHRs. Novel approaches must be developed to achieve the desired impact of PHRs on patient engagement, communication and satisfaction. Our findings provide a roadmap to greater engagement of patients via PHRs by expanding functionality, training both patients and clinic providers/staff, and incorporating adult learning strategies

Multihospital Infection Prevention Collaborative: Informatics Challenges and Strategies to Prevent MRSA

We formed a collaborative to spread effective MRSA prevention strategies. We conducted a two-phase, multisite, quasi-experimental study of seven hospital systems (11 hospitals) in IN, MT, ME and Ontario, Canada over six years. Patients with prior MRSA were identified at admission using regional health information exchange data. We developed a system to return an alert message indicating a prior history of MRSA, directed to infection preventionists and admissions. Alerts indicated the prior anatomic site, and the originating institution. The combined approach of training and coaching, implementation of MRSA registries, notifying hospitals on admission of previously infected or colonized patients, and change strategies was effective in reducing MRSA infections over 80%. Further research and development of electronic surveillance tools is needed to better integrate the varied data source and support preventing MRSA infections. Our study supports the importance of hospitals collaborating to share data and implement effective strategies to prevent MRSA

Efficiency Strategies for Facilitating Computerized Clinical Documentation in Ambulatory Care

Most providers have experienced increased documentation demands with the use of electronic health records (EHRs). We sought to identify efficiency strategies that providers use to complete clinical documentation tasks in ambulatory care. Two observers performed ethnographic observations and interviews with 22 ambulatory care providers in a U.S. Veterans Affairs Medical Center. Observation notes and interview transcripts were coded for recurrent strategies relating to completion of the EHR progress notes. Findings included: the use of paper artifacts for handwritten notations; electronic templates for automation of certain parts of the note; use of shorthand and phrases rather than narrative writing; copying and pasting from previous EHR notes; directly entering information into the EHR note during the patient encounter; reliance on memory; and pre-populating an EHR note prior to seeing the patient. We discuss the findings in the context of distributed cognition to understand how clinical information is propagated and represented toward completion of a progress note. The study findings have important implications for improving and streamlining clinical documentation related to human factors workload management strategies

Computerised Clinical Reminders Use in an Integrated Healthcare System

Objective: To examine levels of routine computerised clinical reminder use in a nationwide sample of primary care physicians and to identify factors influencing reminder use. Design: Cross-sectional using a self-administered questionnaire. Setting: The United States Veterans Health Administration. Methods: Survey responses from 461 VHA primary care physicians sampled from across the Veterans Health Administration were sampled and analysed. We asked physicians how many computerised clinical reminders they use per patient per visit and when they typically use computerised clinical reminders in their clinics. Measured physician characteristics included age, gender, year of medical degree, number of days in clinic per week, and attitudes towards computerised clinical reminders (measured on Likert-like scales). We used multivariable linear regression to determine factors associated with greater use of computerised clinical reminders per patient per visit. Results: Average computerised clinical reminder use per patient visit was 4.2 (SD = 2.5). Eightysix percent of physicians resolve reminders during the visit. In a multivariable regression model, a higher score on the team factors scale is associated with use of more reminders (increase of 0.24 reminders for each unit increase on the team factors scale, or one extra reminder for each four unit increase in the team factor scale). Working more days in clinic is associated with use of more reminders per patient visit (increase of 0.13 reminders for each extra half-day of clinic per week, or about one additional reminder for physicians working ten half-days per week versus physicians working two half-days per week). Academic facility affiliation is associated with one less reminder used per patient visit as compared with no affiliation. Conclusions: Most United States Veterans Health Administration primary care physicians use computerised clinical reminders, typically during the patient visit. Strategies to increase reminder use should focus on improving physicians’ understanding of their role in completing reminder-related tasks and improving usability for users such as physicians who work in clinic less frequently

Examining the Relationship between Clinical Decision Support and Performance Measurement

In concept and practice, clinical decision support (CDS) and performance measurement represent distinct approaches to organizational change, yet these two organizational processes are interrelated. We set out to better understand how the relationship between the two is perceived, as well as how they jointly influence clinical practice. To understand the use of CDS at benchmark institutions, we conducted semistructured interviews with key managers, information technology personnel, and clinical leaders during a qualitative field study. Improved performance was frequently cited as a rationale for the use of clinical reminders. Pay-for-performance efforts also appeared to provide motivation for the use of clinical reminders. Shared performance measures were associated with shared clinical reminders. The close link between clinical reminders and performance measurement causes these tools to have many of the same implementation challenges

Optimizing Perioperative Decision Making: Improved Information for Clinical Workflow Planning

Perioperative care is complex and involves multiple interconnected subsystems. Delayed starts, prolonged cases and overtime are common. Surgical procedures account for 40–70% of hospital revenues and 30–40% of total costs. Most planning and scheduling in healthcare is done without modern planning tools, which have potential for improving access by assisting in operations planning support. We identified key planning scenarios of interest to perioperative leaders, in order to examine the feasibility of applying combinatorial optimization software solving some of those planning issues in the operative setting. Perioperative leaders desire a broad range of tools for planning and assessing alternate solutions. Our modeled solutions generated feasible solutions that varied as expected, based on resource and policy assumptions and found better utilization of scarce resources. Combinatorial optimization modeling can effectively evaluate alternatives to support key decisions for planning clinical workflow and improving care efficiency and satisfaction