Predictive Analytics to Support Clinical Decision Making

A key activity in healthcare is clinical decision making. This decision making typically has to be made rapidly and often without complete information. Moreover, the consequences of these decisions could be far reaching including the difference between life or death. Today analytics can assist in clinical decision making as the following chapter highlights. However, to gain the most from any type of analytics, it is first necessary to fully understand the dynamics around the clinical decision making process.

Comparative Study of Oncology Information Systems for Better Patient and Provider Outcomes

Cancer is among the top three chronic diseases both in developed countries as well as underdeveloped countries. The diagnosis, medication, and treatment for cancer is extremely costly. Typically, cancer treatment involves surgery, radiotherapy, and chemotherapy. Owing to the extremely high price of medicine and treatment along with cytotoxicity of medication, cancer treatment warrants extraordinary care in treating cancer patients. Oncology information systems (OIS) provide an all-in-one solution for such problems. The OIS can integrate different treatment protocols and update change in dose and treatment in real time.

Blockchain in Healthcare

Blockchain is a decentralized, digital ledger that keeps a permanent, unalterable record of transactions between users. One of the greatest advantages of Blockchain is that it is much more secure than other data storage platforms, and thus particularly relevant for healthcare. The chapter serves to outline areas and opportunities for deploying this technology into key healthcare contexts to support effective and efficient operations as well as heightened transparency and trust around activities between and within stakeholders.

A Sentiment Analysis of the 2014-15 Ebola Outbreak in the Media and Social Media

The negative and unbalanced nature of media and social media coverage has amplified anxieties and fears about the Ebola outbreak. The authors analyse news articles on the Ebola outbreak from two leading news outlets, together with comments on the articles from a well-known social media platform, from March 2014 to July 2015. The volume of news articles was greatest between August 2014 and January 2015, with a spike in October 2014, and was driven by the few cases of transmission in Europe and the USA. Sentiment analysis reveals coverage and commentary on the small number of Ebola cases in Europe and the USA were much more extensive than coverage and commentary on the outbreak in West Africa. Articles expressing negative sentiments were more common in the USA and also received more comments than those expressing positive sentiments. The negative sentiments expressed in the media and social media amplified fears about an Ebola outbreak outside West Africa, which increased pressure for unwarranted and wasteful precautionary measures.

The Role of Crowdsourcing in the Healthcare Industry

Crowdsourcing has a role to play in solving healthcare-based problems as it can tap into a vast pool of global medical knowledge. This chapter first categorizes the various problems in the healthcare industry. It then describes the differences in various medical traditions in solving medical problems. The chapter also discusses the challenges in identifying the ideal medical solution. It notes the various types of obstacles to adopting effective healthcare solutions and suggests crowdsourcing solutions that could build up an impetus for bringing about positive change. Finally, the chapter emphasizes the potential of crowdsourcing to disrupt old ideas and introduce new ones as well as make a significant improvement in the social quality for different population groups.

The E-Viewer Study

For patients undergoing surgery in a multi-day admission, standard care requires that their surgeon review the patient post-operatively to check on their progress. This is usually done by the specialist attending in person. However, in the Australian setting, most specialists work at multiple institutions. As a result, review ward rounds, especially of post-operative patients, can be delayed, which can delay management decisions and discharge, which in turn may lower patient satisfaction. A telemedicine solution is designed, and results from a pilot test are examined to assess the benefits of incorporating an electronic discharge capability into the current process.

From Resource to Outcome

Governments often create policies that rely on implementation by arm's length organizations and require practice changes on the part of different segments of the healthcare system without understanding the differences in and complexities of these agencies. This research describes components of a health system and explains how they affect outcomes. It argues that implemented policies affect various components of a health system in terms of service delivery, workforce, information, financing, medical products, technologies, leadership, and governance. Using health system as framework of analysis, the chapter explains that the outcome of health policy implementation determines the availability, quality, and equability of program service delivery. The chapter further argues that policy implementation barriers affect the poor and vulnerable groups from benefiting from public spending on public health policies and programs.

Optimization of Provider Ecosystem Through Actor-Resource Integration

Information technology has enabled healthcare providers such as hospitals to extend their internal operations into external facilities such as urgent and ambulatory care centers and optimizeresources in support of patient care. With the development of the internet, social media, wearables, and telehealth technologies, the potential for patient engagement in preventive and post-discharge care transition has increased. Unlike other organizations where the provider has limited insight into the customer ecosystem, hospitals, for example, have an opportunity to gain insight into the patient ecosystem and influence patient behavior while the patients are within the provider ecosystem. This chapter looks at hospital engagement with patients in two settings—the emergency room (ER) and the patient room (PR)—to illustrate both the opportunities and the strategies that can help hospitals use patient touchpoints to improve continuity of care inside and outside hospital walls.

Technology's Enabling Role to Improve Care Coordination

The U.S. healthcare system has been often characterized as fragmented and disconnected. Lack of effective and concurrent adoption of information technology has been known to be a factor that contributes to the decentralization of healthcare systems. Fragmented systems are also responsible for creating silos that operate with minimal coordination. Clinicians in such systems are providing duplicate services because they are not aware of patient care plans set by other practitioners. These duplications could lead to prescription drug errors due to inconsistencies and lack of coordination in the treatment services and in some cases drug-drug interactions. The following suggests a role for technology to facilitate better care coordination.

Fast Track to Reduce Patient Lead Time

Patient lead time in emergency units is a critical factor for quality of care and patient safety. The objective of the chapter is a public emergency care hospital of a Brazilian city, important for its localization in the second more populated area of the city. Green risk patients constitute more than half of attendances and represent the largest volume of out-of-goal attendances in the hospital. Considering this analysis, it was conducted the process modelling in order to understand patient pathway and the main related problems. A list of undesirable effects was subsequently composed, allowing the construction of the current reality tree (CRT). With the root causes identified, the literature suggested fast track as an alternative to reduce the average waiting time in queue until the medical care. The method used for testing scenarios of fast track was discrete events simulation.