Healthcare Management Primer

This primer was written by students enrolled in HMP 721.01, Management of Health Care Organizations, in the Health Management & Policy Program, College of Health and Human Services, University of New Hampshire. This course was taught by Professor Mark Bonica in Fall 2017

Marshfield Clinic: Health Information Technology Paves the Way for Population Health Management

Highlights Fund-defined attributes of an ideal care delivery system and best practices, including an internal electronic health record, primary care teams, physician quality metrics and mentors, and standardized care processes for chronic care management

Validation of the Work Observation Method By Activity Timing (WOMBAT) method of conducting time-motion observations in critical care settings: an observational study

<p>Abstract</p> <p>Background</p> <p>Electronic documentation handling may facilitate information flows in health care settings to support better coordination of care among Health Care Providers (HCPs), but evidence is limited. Methods that accurately depict changes to the workflows of HCPs are needed to assess whether the introduction of a Critical Care clinical Information System (CCIS) to two Intensive Care Units (ICUs) represents a positive step for patient care. To evaluate a previously described method of quantifying amounts of time spent and interruptions encountered by HCPs working in two ICUs.</p> <p>Methods</p> <p>Observers used PDAs running the Work Observation Method By Activity Timing (WOMBAT) software to record the tasks performed by HCPs in advance of the introduction of a Critical Care clinical Information System (CCIS) to quantify amounts of time spent on tasks and interruptions encountered by HCPs in ICUs.</p> <p>Results</p> <p>We report the percentages of time spent on each task category, and the rates of interruptions observed for physicians, nurses, respiratory therapists, and unit clerks. Compared with previously published data from Australian hospital wards, interdisciplinary information sharing and communication in ICUs explain higher proportions of time spent on professional communication and documentation by nurses and physicians, as well as more frequent interruptions which are often followed by professional communication tasks.</p> <p>Conclusions</p> <p>Critical care workloads include requirements for timely information sharing and communication and explain the differences we observed between the two datasets. The data presented here further validate the WOMBAT method, and support plans to compare workflows before and after the introduction of electronic documentation methods in ICUs.</p

Guideline-based decision support in medicine : modeling guidelines for the development and application of clinical decision support systems

Guideline-based Decision Support in Medicine Modeling Guidelines for the Development and Application of Clinical Decision Support Systems The number and use of decision support systems that incorporate guidelines with the goal of improving care is rapidly increasing. Although developing systems that are both effective in supporting clinicians and accepted by them has proven to be a difficult task, of the systems that were evaluated by a controlled trial, the majority showed impact. The work, described in this thesis, aims at developing a methodology and framework that facilitates all stages in the guideline development process, ranging from the definition of models that represent guidelines to the implementation of run-time systems that provide decision support, based on the guidelines that were developed during the previous stages. The framework consists of 1) a guideline representation formalism that uses the concepts of primitives, Problem-Solving Methods (PSMs) and ontologies to represent guidelines of various complexity and granularity and different application domains, 2) a guideline authoring environment that enables guideline authors to define guidelines, based on the newly developed guideline representation formalism, and 3) a guideline execution environment that translates defined guidelines into a more efficient symbol-level representation, which can be read in and processed by an execution-time engine. The described methodology and framework were used to develop and validate a number of guidelines and decision support systems in various clinical domains such as Intensive Care, Family Practice, Psychiatry and the areas of Diabetes and Hypertension control

A Team-Based Approach to Studying Complex Healthcare Processes

Communication is a critical aspect of clinical work. In 2010, the Joint Commission (JC) found that gaps in communication were among leading factors contributing to medical errors. Healthcare processes, such as patient discharge, depend on interdisciplinary communication to be successful. Electronic health records (EHRs) have the potential to facilitate communication and information sharing between interdisciplinary care team members; however, challenges remain in designing tools for team-based care and questions remain in understanding how EHRs impact interdisciplinary team communication. This dissertation focuses on understanding how EHRs can be designed to support communication and information sharing within interdisciplinary patient care teams. The first aim of the dissertation investigated how EHRs impact interdisciplinary clinical teams’ communication, shared mental models, and information sharing activities. The results showed that implementing new EHR tools appeared to have little impact on communication and shared mental models, but new information sharing activities mediated by EHR developed. These changes and lack thereof suggest that new EHR tools will be specifically needed to facilitate interdisciplinary team information sharing activities. The second aim of the dissertation investigates the information sharing activities and information needs of interdisciplinary team members during patient discharge. The results showed that the information clinicians sought out during discharge depended on the roles that person played as well as the progress of the discharge process. Future EHR tools should be aware of how patient care teams are progressing through the patient discharge process in order to provide information contextualized to their current tasks. In conclusion, interdisciplinary team communication and information sharing remain poorly supported by current EHRs and new tools designed specifically for interdisciplinary teams should provide information based on the completion of team activities

Medication decision-making for patients with renal insufficiency in inpatient and outpatient care at a US Veterans Affairs Medical Centre: a qualitative, cognitive task analysis.

BackgroundMany studies identify factors that contribute to renal prescribing errors, but few examine how healthcare professionals (HCPs) detect and recover from an error or potential patient safety concern. Knowledge of this information could inform advanced error detection systems and decision support tools that help prevent prescribing errors.ObjectiveTo examine the cognitive strategies that HCPs used to recognise and manage medication-related problems for patients with renal insufficiency.DesignHCPs submitted documentation about medication-related incidents. We then conducted cognitive task analysis interviews. Qualitative data were analysed inductively.SettingInpatient and outpatient facilities at a major US Veterans Affairs Medical Centre.ParticipantsPhysicians, nurses and pharmacists who took action to prevent or resolve a renal-drug problem in patients with renal insufficiency.OutcomesEmergent themes from interviews, as related to recognition of renal-drug problems and decision-making processes.ResultsWe interviewed 20 HCPs. Results yielded a descriptive model of the decision-making process, comprised of three main stages: detect, gather information and act. These stages often followed a cyclical path due largely to the gradual decline of patients' renal function. Most HCPs relied on being vigilant to detect patients' renal-drug problems rather than relying on systems to detect unanticipated cues. At each stage, HCPs relied on different cognitive cues depending on medication type: for renally eliminated medications, HCPs focused on gathering renal dosing guidelines, while for nephrotoxic medications, HCPs investigated the need for particular medication therapy, and if warranted, safer alternatives.ConclusionsOur model is useful for trainees so they can gain familiarity with managing renal-drug problems. Based on findings, improvements are warranted for three aspects of healthcare systems: (1) supporting the cyclical nature of renal-drug problem management via longitudinal tracking mechanisms, (2) providing tools to alleviate HCPs' heavy reliance on vigilance and (3) supporting HCPs' different decision-making needs for renally eliminated versus nephrotoxic medications

What Works? A Study of Effective Early Childhood Mental Health Consultation Programs

Examines factors that lead to desirable outcomes in mental health consultation programs: solid program infrastructure, highly qualified consultants, and quality support services. Analyzes targeted outcomes, measurements, and intensity of interventions

Organizing the U.S. Health Care Delivery System for High Performance

Analyzes the fragmentation of the healthcare delivery system and makes policy recommendations -- including payment reform, regulatory changes, and infrastructure -- for creating mechanisms to coordinate care across providers and settings

Phenomenological Assessment of Integrative Medicine Decision-making and the Utility of Predictive and Prescriptive Analytics Tools

The U.S. Healthcare system is struggling to manage the burden of chronic disease, racial and socio-economic disparities, and the debilitating impact of the current global pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). More patients need alternatives to allopathic or “Western” medicine focused on fighting disease with mechanism, pharmaceuticals, and invasive measures. They are seeking Integrative Medicine which focuses on health and healing, emphasizing the centrality of the patient-physician relationship. In addition to providing the best conventional care, IM focuses on preventive maintenance, wellness, improved behaviors, and a holistic care plan. This qualitative research assessed whether predictive and prescriptive analytics (artificial intelligence tools that predict patient outcomes and recommend treatments, interventions, and medications) supports the decision-making processes of IM practitioners who treat patients suffering from chronic pain. PPA was used in a few U.S. hospitals but was not widely available for IM practitioners at the time of this research. Phenomenological interviews showed doctors benefit from technology that aggregates data, providing a clear patient snapshot. PPA exposed historical information that doctors often miss. However, current systems lacked the design to manage individualized, holistic care focused on the mind, body, and spirit. Using the Future-Focused Task-Technology Fit theory, the research suggested PPA could actually do more harm than good in its current state. Future technology must be patient-focused and designed with a better understanding of the IM task and group characteristics (e.g., the unique way providers practice medicine) to reduce algorithm aversion and increase adoption. In the ideal future state, PPA will surface healthcare Big Data from multiple sources, support communication and collaboration across the patient’s support system and community of care, and track the various objective and subjective factors contributing to the path to wellness