Acuity-based Performance Evaluation and Tactical Capacity Planning in Primary Care

Effective primary care requires timely and equitable access to care for patients as well as efficient and balanced utilization of physician time. Motivated by a family health clinic in Ontario, Canada, this research proposes ways to improve both of these aspects of primary care through tactical capacity planning based on acuity-based performance targets. First, we propose a new metric based on acuity levels to evaluate timely access to primary care. In Canada, as well as other participant countries in the Organization for Economic Co-operation and Development (OECD), the main metric currently used to evaluate access is the proportion of patients who are able to obtain a same- or next-day appointment. However, not all patients in primary care are urgent and require a same- or next-day appointment. Therefore, accurate evaluation of timely access to primary care should consider the urgency of the patient request. To address this need, we define multiple acuity levels and relative access targets in primary care, akin to the CTAS system in emergency care. Furthermore, current access time evaluation in the province is mostly survey-based, while our evaluation is based on appointment data and hence more objective. Thus, we propose a novel, acuity-based, data-driven approach for evaluation of timely access to primary care. Second, we develop a deterministic tactical capacity planning (TCP) model to balance workload between weeks for each family physician in the specific primary care clinic in this study. Unbalanced workload among weeks may lead to provider overtime for the weeks with high workload and provider idle time for weeks with low workload. In the proposed TCP model, we incorporate the results from access time evaluation in the first study as constraints for access time. The proposed TCP model considers 11 appointment types with multiple access targets for each appointment type. The TCP model takes as input a forecast of demand coming from an ARIMA model. We compare the results of the TCP model based on current access time targets as well as targets resulting from our acuity-based metrics. The use of our proposed acuity-based targets leads to allocation of time slots which is more equitable for patients and also improves physician workload balance. Third, we also propose a robust TCP model based on the cardinality-constrained method to minimize the highest potential physician peak load between weeks. Therefore, the developed robust TCP model enables protection against uncertainty through providing a feasible allocation of capacity for all realizations of demand. The proposed robust TCP model considers two interdependent appointment types (e.g., new patients and follow ups), multiple access time targets for each appointment type and uncertainty in demand for appointments. We conduct a set of experiments to determine how to set the level of robustness based on extra cost and infeasibility probability of a robust solution. In summary, this dissertation advocates for the definition and subsequent use of acuity-based access time targets for both performance evaluation and capacity allocation in primary care. The resulting performance metrics provide a more detailed view of primary care and lead to not only more equitable access policies but also have the potential to improve physician workload balance when used as input to capacity planning models

Access and Resource Management for Clinical Care and Clinical Research in Multi-class Stochastic Queueing Networks.

In healthcare delivery systems, proper coordination between patient visits and the health care resources they rely upon is an area in which important new planning capabilities are very valuable to provide greater value to all stakeholders. Managing supply and demand, while providing an appropriate service level for various types of care and patients of differing levels of urgency is a difficult task to achieve. This task becomes even more complex when planning for (i) stochastic demand, (ii) multi-class customers (i.e., patients with different urgency levels), and (iii) multiple services/visit types (which includes multi-visit itineraries of clinical care and/or clinical research visits that are delivered according to research protocols). These complications in the demand stream require service waiting times and itineraries of visits that may span multiple days/weeks and may utilize many different resources in the organization (each resource with at least one specific service being provided). The key objective of this dissertation is to develop planning models for the optimization of capacity allocation while considering the coordination between resources and patient demand in these multi-class stochastic queueing networks in order to meet the service/access levels required for each patient class. This control can be managed by allocating resources to specific patient types/visits over a planning horizon. In this dissertation, we control key performance metrics that relate to patient access management and resource capacity planning in various healthcare settings with chapters devoted to outpatient services, and clinical research units. The methods developed forecast and optimize (1) the access to care (in a medical specialty) for each patient class, (2) the Time to First Available Visit for clinical research participants enrolling in clinical trials, and (3) the access to downstream resources in an itinerary of care, which we call the itinerary flow time. We also model and control how resources are managed, by incorporating (4) workload/utilization metrics, as well as (5) blocking/overtime probabilities of those resources. We control how to allocate resource capacity along the various multi-visit resource requirements of the patient itineraries, and by doing so, we capture the key correlations between patient access, and resource allocation, coordination, and utilization.PhDIndustrial and Operations EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116770/1/jivan_1.pd

Federated Robust Embedded Systems: Concepts and Challenges

The development within the area of embedded systems (ESs) is moving rapidly, not least due to falling costs of computation and communication equipment. It is believed that increased communication opportunities will lead to the future ESs no longer being parts of isolated products, but rather parts of larger communities or federations of ESs, within which information is exchanged for the benefit of all participants. This vision is asserted by a number of interrelated research topics, such as the internet of things, cyber-physical systems, systems of systems, and multi-agent systems. In this work, the focus is primarily on ESs, with their specific real-time and safety requirements. While the vision of interconnected ESs is quite promising, it also brings great challenges to the development of future systems in an efficient, safe, and reliable way. In this work, a pre-study has been carried out in order to gain a better understanding about common concepts and challenges that naturally arise in federations of ESs. The work was organized around a series of workshops, with contributions from both academic participants and industrial partners with a strong experience in ES development. During the workshops, a portfolio of possible ES federation scenarios was collected, and a number of application examples were discussed more thoroughly on different abstraction levels, starting from screening the nature of interactions on the federation level and proceeding down to the implementation details within each ES. These discussions led to a better understanding of what can be expected in the future federated ESs. In this report, the discussed applications are summarized, together with their characteristics, challenges, and necessary solution elements, providing a ground for the future research within the area of communicating ESs

Key Influences of Patient Satisfaction Measurement as a Quality Indicator in Inpatient Facilities

Patient Satisfaction remains a focal point in overall healthcare experience. Satisfaction of patients has become a priority for hospital administrators because of the ties to improve organization performance, increase reimbursement schedules, prevent claims, and gain return to provider reputation. This study examines the key influences of patient satisfaction and how it is measured in an inpatient facility. A literature search was done through PubMed and Google Scholar to determine specific areas needing improvement. Out of 30 articles that met all search criteria (published in the year 2000 or later, survey administered in United States, published in English, administered in an inpatient facility, abstract of study pertained to one or more research questions, satisfaction scores analyzed through external agency, scores gathered from patients age 19 and older), the most frequently mentioned areas of dissatisfaction include: food, wait time, follow up/discharge, facility, medical personnel interaction, and activities/program. Further breakdown of specific points of dissatisfaction for each factor was determined by frequently mentioned specifics. The systematic review confirmed the concept that access, time, and medical personnel interaction are greatly valued by patients. Limitations of the study include the fact that response bias may exist for individuals answering surveys, interview bias may exist through wording of questionnaires, and the results are propriety in nature due to score analysis through third parties. Recommendations for assessment involve longer follow up period with the same patients and capturing a good sampling plan including both positive and negative experiences

How can business transformation be driven by a new ERP implementation: the Nice case study

openIn the last years, Nice has carried out several Mergers and Acquisitions operations. For the most part, acquired companies are still operating with their own industrial methods, tools and operating processes, configuring a situation of overall fragmentation in terms of Application Landscape within the Group, and generating various issues like timeliness and granularity of data availability and difficulties in processes integration across companies. Given such context, Nice Management would like to evolve its current Application Landscape, in order to enable the transformation into an integrated “One Company”, operating on the new Microsoft D365F&SCM as the common ERP platform. Furthermore, with the aim to reduce infrastructural complexity and rationalize related costs, such evolution will include switching from an On-Cloud “private” ERP setup to an On-Cloud totally outsourced ERP. This ERP implementation project starts from the revision, optimization and formalization of the business processes as fundamental requirement to then reproduce them on the Microsoft platform and this thesis will focus on the analyzed processes during the project. Taking into account the context and the needs, with the aim to perform a digital transformation of his business, Nice requested support to Deloitte in order to: • Define a Global Template to be applied to all Group’s countries standardizing the ways of working and adopting processes based on best practices as first step to prepare the ERP implementation. • Upgrade the Group’s Application Landscape to the new Microsoft D365F&SCM release. • Rationalize the overall IT architecture, to reduce the related cost and to improve the efficiency of it. This project is being followed by three Deloitte teams: • A supply chain team, which has in charge the Global Template definition and so the study and revision of all company’s processes. • A Microsoft team for the implementation of the ERP after the definition of formalized processes. This one is the team of which I am part and in the first part of the project will support the supply chain team for the definition of feasible processes for the implementation inside the ERP and in a second moment will actively implement the system for the company. In particular, for the ERP side I will be in charge of the definition of the production processes, from the planning based on forecast to the production lines. • A Finance team that study and revise financial processes. Considering the focus that I had during the project and the objectives defined, the Global Template will be characterized in this thesis with reference to following end to end processes. These processes are part of one of the frameworks, based on best practices, used by Deloitte for the analysis and improvement of the processes of a company: • Forecast to inventory (FTI): is intended the process of forecast and demand management and in particular the main phases considered are statistical forecast generation, sales plan generation, demand plan generation and management of demand signals. For Nice company the two critical processes analyzed were demand planning and replenishment planning. • Plan to schedule (PTS): is intended the process of planning based on forecast and in particular the main phases are supply and capacity planning, production planning, master planning (MPS and MRP) and production scheduling. In Nice case the main processes studied were the production plan definition and the raw material procurement planning, due to the criticality of these processes in their context. • Make to deploy (MTD): we intend the set of process that, starting from the planning and purchasing processes, aim to manage the flow of material throughout the whole production and distribution process to cover the demand of the Customers and/or Subsidiaries. In particular the main processes that has been analyzed are production and logistic.In the last years, Nice has carried out several Mergers and Acquisitions operations. For the most part, acquired companies are still operating with their own industrial methods, tools and operating processes, configuring a situation of overall fragmentation in terms of Application Landscape within the Group, and generating various issues like timeliness and granularity of data availability and difficulties in processes integration across companies. Given such context, Nice Management would like to evolve its current Application Landscape, in order to enable the transformation into an integrated “One Company”, operating on the new Microsoft D365F&SCM as the common ERP platform. Furthermore, with the aim to reduce infrastructural complexity and rationalize related costs, such evolution will include switching from an On-Cloud “private” ERP setup to an On-Cloud totally outsourced ERP. This ERP implementation project starts from the revision, optimization and formalization of the business processes as fundamental requirement to then reproduce them on the Microsoft platform and this thesis will focus on the analyzed processes during the project. Taking into account the context and the needs, with the aim to perform a digital transformation of his business, Nice requested support to Deloitte in order to: • Define a Global Template to be applied to all Group’s countries standardizing the ways of working and adopting processes based on best practices as first step to prepare the ERP implementation. • Upgrade the Group’s Application Landscape to the new Microsoft D365F&SCM release. • Rationalize the overall IT architecture, to reduce the related cost and to improve the efficiency of it. This project is being followed by three Deloitte teams: • A supply chain team, which has in charge the Global Template definition and so the study and revision of all company’s processes. • A Microsoft team for the implementation of the ERP after the definition of formalized processes. This one is the team of which I am part and in the first part of the project will support the supply chain team for the definition of feasible processes for the implementation inside the ERP and in a second moment will actively implement the system for the company. In particular, for the ERP side I will be in charge of the definition of the production processes, from the planning based on forecast to the production lines. • A Finance team that study and revise financial processes. Considering the focus that I had during the project and the objectives defined, the Global Template will be characterized in this thesis with reference to following end to end processes. These processes are part of one of the frameworks, based on best practices, used by Deloitte for the analysis and improvement of the processes of a company: • Forecast to inventory (FTI): is intended the process of forecast and demand management and in particular the main phases considered are statistical forecast generation, sales plan generation, demand plan generation and management of demand signals. For Nice company the two critical processes analyzed were demand planning and replenishment planning. • Plan to schedule (PTS): is intended the process of planning based on forecast and in particular the main phases are supply and capacity planning, production planning, master planning (MPS and MRP) and production scheduling. In Nice case the main processes studied were the production plan definition and the raw material procurement planning, due to the criticality of these processes in their context. • Make to deploy (MTD): we intend the set of process that, starting from the planning and purchasing processes, aim to manage the flow of material throughout the whole production and distribution process to cover the demand of the Customers and/or Subsidiaries. In particular the main processes that has been analyzed are production and logistic

Health Care Management using Cloud Computing

No abstract provided