Improving the Patient Discharge Planning Process through Knowledge Management by Using the Internet of Things

Nitya Ahilandam Kamalanathan, Alan Eardley, Caroline Chibelushi, Tim Collins

Faculty of Computing Engineering and Sciences, Staffordshire University, Stafford, UK.

DOI: 10.4236/ait.2013.32A003                

Abstract

The UK National Health Service (NHS) is faced with problems of managing patient discharge and preventing the problems that result from it such as frequent readmissions, delayed discharge, long waiting lists, bed blocking and other such consequences. The problem is exacerbated by the growth in size, complexity and the number of chronic diseases in the NHS. In addition, there is an increase in demand for high quality care, processes and planning. Effective Discharge Planning (DP) requires practitioners to have appropriate, patient personalised and updated knowledge in order to be able to make informed and holistic decisions about a patients’ discharge. This paper examines the role of Knowledge Management (KM) in both sharing knowledge and using tacit knowledge to create appropriate patient discharge pathways. The paper details the factors resulting in inadequate DP, and demonstrates the use of Internet of Things (IoT) and Machine2Machine (M2M) as candidate technologies and possible solutions which can help reduce the problem. The use of devices that a patient can take home and devices which are perused in the hospital generate information, which can serve useful when presented to the right person at the right time, thus harvesting knowledge. The knowledge when fed back can support practitioners in making holistic decisions with regards to a patients’ discharge.

Keywords

National Health Service (NHS); Knowledge Management (KM); Discharge Planning (DP); Internet of Things (IoT); Machine2Machine (M2M)

1. Introduction

The NHS, a publicly funded organisation, provides healthcare for all UK citizens (currently more than 62 million people) [1]. The NHS is divided into primary and secondary care [1]. Patients requiring further attention are usually transferred from Primary care (PC) to Secondary care (SC). Both PC and SC have links between one another and cannot exist without the other [1]. The sharing of information about a patient between a PC and SC is therefore important. The NHS, like any other healthcare system and other systems, is made up of subsystems which have conventional components such as inputs, processes and outputs. These systems and subsystems are interdependent and inter-related. It is therefore important to understand healthcare subsystems in order to gain a deeper insight into the functioning of the system [2,3]. The research project that this paper describes therefore focuses on analysing the hospital system in terms of its structure and process in terms of:

●          The components themselves (e.g. patients, nurses) and their roles in the system;

●          The relationship between the components and their interaction (e.g. nurses care for patients);

●          The boundaries of the system or its extent and scope (e.g. where an admission ward hands over to an operating theatre) or where patients are discharged;

●          How the system deals with and adapts to changes within the organisation (e.g. emergency admission or an outbreak of an infection);

●          How the system deals with its internal factors (e.g. changes in management, targets, IT systems etc.);

●          The relationship of the system to external systems whose services are vital to a patients convalescence (e.g. social care systems);

●          The knowledge flow within the system and subsystems.

With sound understanding of the system and subsystems, the practitioner is able to understand the knowledge required, the knowledge which currently exists and can be updated to make informed decisions in processes such as DP. Patient discharge can be considered to be the beginning of convalescence. Careful planning of post-treatment care is essential to a patient’s complete healthcare pathway, which is an essential component of DP. Careful planning and a clear decision-making framework are vital to the smooth flow of patients from admission to discharge at the end of the treatment period. The NHS has grown, since it was launched in 1948 and is continuously growing in size and complexity [1]. This growth in size, complexity and the number of chronic diseases (e.g. obesity, diabetes) in the NHS causes an increase in demands, processes and planning [1]. A consequence of the complexity, increasing size and demands on the NHS is a disarray of processes that affect functions such as DP.   DP is a key part of the overall process and is not an isolated or final event [1]. It is important to include what happens to a patient after discharge, to prevent unwanted readmissions, delayed discharged, bed blocking, cancellations in procedures and long waiting lists. It has implications for the provision of resources in the healthcare, social care and other support service sectors and warrants this research to improve its efficiency and effectiveness. A smooth DP process facilitates patients moving from one healthcare setting to another, or going home. It begins on admission and is a multidisciplinary process involving physicians, nurses, social workers, and possibly other health professionals [4]. The aim of DP is therefore to enhance the continuity of care and can have significant implications for a patient’s wellbeing and recovery, the efficient use of medical resources and streamlined interconnecting processes within the hospital setting.

The complexity of the discharge process implies that careful planning is needed to make it more effective [5]. Recent years have witnessed significant advances in medical informatics to increase productivity and efficiency in healthcare [6]. Some parts of the NHS are currently faced with the problem of “islands of information”¹ related to the existence of organisational “silos”². In some cases, it is suggested that very little knowledge is shared between these silos. This leads to the foundation of this paper, which is to examine the role of KM in an integrated “cross-silo” approach to use shared knowledge and tacit knowledge to create appropriate patient discharge pathways. The tacit knowledge of Doctors and Nurses is yet to be exploited to its full potential along with the knowledge of patients and carers. According to [7] patients, carers and information are the most underutilised resources the NHS has. It is the patients who are facing the symptom, and the carers who look after the patient, the knowledge they have is most valuable to making decisions, which unfortunately is currently overlooked. Each patient has a unique problem and personalising the discharge process will reduce the current problems faced with DP. KM therefore forms a bridge between these “islands of information” [8].

2. The Current Discharge Planning Dilemma in the NHS

Discharge is defined when an in-patient leaves an acute hospital to return home, or is transferred to a rehabilitation facility or an after-care nursing centre [9]. DP should commence as early as possible in order to facilitate a smooth discharge process. Discharge guidelines have been prescribed by the Department of Health (DH) and different trusts implement discharge pathways or process maps following these guidelines. Several DP improvement attempts have been made and reasonable improvements have been noticed. Several methods by which DP takes place have been identified in the primary research in two UK hospital trusts and include the following:

●          DP commences on admission;

●          Patient and carer are involved in the decision making process;

●          A clinical management plan where an expected date of discharge is predicted based on actual performance in the ward or, on benchmarking information from past cases;

●          Multidisciplinary teams make a decision based on experience during their meetings.

A bed management system stores information on beds occupied and a weekly meeting are held to decide the discharge date for patients. All of these methods involve KM. From the Primary research carried out, it is seen that, a rough DP is currently drafted for patients upon entry to hospital according to their diagnosis, and a tentative discharge date is provided in line with recommendations. Changes are made over the course of the patient’s stay and records are manually updated by nurses, upon instruction by the doctors. This sometimes results in confusion and even disagreement on discharge dates by different doctors (e.g. when treating the patient for different symptoms) and nurses (e.g. when a change of shift occurs). This research proposes that Patient DP requires viewing the whole system and not as isolated units. In the discharge plan the patient and care giver involvement needs to be considered, however very little indication has been provided on these. To date, based on the primary research, clear guidelines are not present on what information needs to be collected, stored and reused on patients. The UK NHS is facing problems of managing patient discharges while having to meet waiting time, treatment time and bed usage targets [10]. Patient discharge is currently being driven by quantitative measures such as targets (e.g. to reduce “bed-blocking”) and problems resulting from this situation has received a great deal of popular press attention recently and political capital has been made from this [10]. Targets are prioritized while compromising patient’s after-care quality.

Being target-driven (rather than knowledge driven) implies that the healthcare system fails to consider the factors that affect the effective recovery of a patient after treatment and discharge [11]. Hospitals focus on accomplishing and achieving internal targets, resulting in compromised patient safety and well-being after discharge. The exact situation with regard to patient discharge and readmissions is not really well established, as there are variations in discharge methods between trusts, as identified in the primary research. However, it is reported in the popular press that doctors have to make quick decisions about patients just to “get the clock to stop ticking” [12] resulting in deteriorating trust between doctors and patients. More reliably, doctors find themselves torn between meeting targets and providing their sick patients with the best treatment. These claims in the assorted news media have been reaffirmed by Andrew Lansley the Secretary of State for Health in the UK Government who in a speech in December 2011 stated that:

“The NHS is full of processes and targets, of performance-management and tariffs, originally, all designed to deliver better patient care, but somewhere along the line, they gained a momentum of their own, increasingly divorced from the patients who should have been at their centre.”

(Guardian 7 December 2012)

Several factors result in the current inadequate DP. These factors are internal and external to the NHS along with psychosocial factors of the patient and family [13]. It is important to understand the factors behind inadequate DP to be able to analyse and diagnose the factors causing the problem systematically. A comparison can then be made between the factors along with the results obtained from the primary research, followed by a catalogue of possible solutions underpinned by KM. This will then lead to making a diagnosis i.e. the proposed KM model. A root cause analysis [14] highlighted the factors contributing to inadequate DP as represented in Figure 1.

Figure 1 demonstrates the discharge of a patient as a complex process, with various inter-related factors. A

Conflicts of Interest

The authors declare no conflicts of interest.

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